diff --git a/tests/verifications/REPORT.md b/tests/verifications/REPORT.md
index ba4b3414e..9214eada3 100644
--- a/tests/verifications/REPORT.md
+++ b/tests/verifications/REPORT.md
@@ -1,6 +1,6 @@
 # Test Results Report
 
-*Generated on: 2025-04-17 11:08:16*
+*Generated on: 2025-04-17 11:50:48*
 
 *This report was generated by running `python tests/verifications/generate_report.py`*
 
@@ -15,23 +15,23 @@
 
 | Provider | Pass Rate | Tests Passed | Total Tests |
 | --- | --- | --- | --- |
-| Meta_reference | 100.0% | 26 | 26 |
-| Together | 51.3% | 39 | 76 |
-| Fireworks | 47.4% | 36 | 76 |
-| Openai | 100.0% | 52 | 52 |
+| Meta_reference | 100.0% | 28 | 28 |
+| Together | 51.2% | 41 | 80 |
+| Fireworks | 0.0% | 0 | 80 |
+| Openai | 100.0% | 56 | 56 |
 
 
 
 ## Meta_reference
 
-*Tests run on: 2025-04-15 17:08:59*
+*Tests run on: 2025-04-17 11:41:51*
 
 ```bash
 # Run all tests for this provider:
 pytest tests/verifications/openai_api/test_chat_completion.py --provider=meta_reference -v
 
-# Example: Run only the 'earth' case of test_chat_non_streaming_basic:
-pytest tests/verifications/openai_api/test_chat_completion.py --provider=meta_reference -k "test_chat_non_streaming_basic and earth"
+# Example: Run only the 'stream=False' case of test_chat_multi_turn_multiple_images:
+pytest tests/verifications/openai_api/test_chat_completion.py --provider=meta_reference -k "test_chat_multi_turn_multiple_images and stream=False"
 ```
 
 
@@ -44,6 +44,8 @@ pytest tests/verifications/openai_api/test_chat_completion.py --provider=meta_re
 
 | Test | Llama-4-Scout-Instruct |
 | --- | --- |
+| test_chat_multi_turn_multiple_images (stream=False) | ✅ |
+| test_chat_multi_turn_multiple_images (stream=True) | ✅ |
 | test_chat_non_streaming_basic (earth) | ✅ |
 | test_chat_non_streaming_basic (saturn) | ✅ |
 | test_chat_non_streaming_image | ✅ |
@@ -73,14 +75,14 @@ pytest tests/verifications/openai_api/test_chat_completion.py --provider=meta_re
 
 ## Together
 
-*Tests run on: 2025-04-16 15:03:51*
+*Tests run on: 2025-04-17 11:45:14*
 
 ```bash
 # Run all tests for this provider:
 pytest tests/verifications/openai_api/test_chat_completion.py --provider=together -v
 
-# Example: Run only the 'earth' case of test_chat_non_streaming_basic:
-pytest tests/verifications/openai_api/test_chat_completion.py --provider=together -k "test_chat_non_streaming_basic and earth"
+# Example: Run only the 'stream=False' case of test_chat_multi_turn_multiple_images:
+pytest tests/verifications/openai_api/test_chat_completion.py --provider=together -k "test_chat_multi_turn_multiple_images and stream=False"
 ```
 
 
@@ -95,6 +97,8 @@ pytest tests/verifications/openai_api/test_chat_completion.py --provider=togethe
 
 | Test | Llama-3.3-70B-Instruct | Llama-4-Maverick-Instruct | Llama-4-Scout-Instruct |
 | --- | --- | --- | --- |
+| test_chat_multi_turn_multiple_images (stream=False) | ⚪ | ✅ | ✅ |
+| test_chat_multi_turn_multiple_images (stream=True) | ⚪ | ❌ | ❌ |
 | test_chat_non_streaming_basic (earth) | ✅ | ✅ | ✅ |
 | test_chat_non_streaming_basic (saturn) | ✅ | ✅ | ✅ |
 | test_chat_non_streaming_image | ⚪ | ✅ | ✅ |
@@ -124,14 +128,14 @@ pytest tests/verifications/openai_api/test_chat_completion.py --provider=togethe
 
 ## Fireworks
 
-*Tests run on: 2025-04-16 15:05:54*
+*Tests run on: 2025-04-17 11:47:52*
 
 ```bash
 # Run all tests for this provider:
 pytest tests/verifications/openai_api/test_chat_completion.py --provider=fireworks -v
 
-# Example: Run only the 'earth' case of test_chat_non_streaming_basic:
-pytest tests/verifications/openai_api/test_chat_completion.py --provider=fireworks -k "test_chat_non_streaming_basic and earth"
+# Example: Run only the 'stream=False' case of test_chat_multi_turn_multiple_images:
+pytest tests/verifications/openai_api/test_chat_completion.py --provider=fireworks -k "test_chat_multi_turn_multiple_images and stream=False"
 ```
 
 
@@ -146,43 +150,45 @@ pytest tests/verifications/openai_api/test_chat_completion.py --provider=firewor
 
 | Test | Llama-3.3-70B-Instruct | Llama-4-Maverick-Instruct | Llama-4-Scout-Instruct |
 | --- | --- | --- | --- |
-| test_chat_non_streaming_basic (earth) | ✅ | ✅ | ✅ |
-| test_chat_non_streaming_basic (saturn) | ✅ | ✅ | ✅ |
-| test_chat_non_streaming_image | ⚪ | ✅ | ✅ |
+| test_chat_multi_turn_multiple_images (stream=False) | ⚪ | ❌ | ❌ |
+| test_chat_multi_turn_multiple_images (stream=True) | ⚪ | ❌ | ❌ |
+| test_chat_non_streaming_basic (earth) | ❌ | ❌ | ❌ |
+| test_chat_non_streaming_basic (saturn) | ❌ | ❌ | ❌ |
+| test_chat_non_streaming_image | ⚪ | ❌ | ❌ |
 | test_chat_non_streaming_multi_turn_tool_calling (add_product_tool) | ❌ | ❌ | ❌ |
 | test_chat_non_streaming_multi_turn_tool_calling (compare_monthly_expense_tool) | ❌ | ❌ | ❌ |
 | test_chat_non_streaming_multi_turn_tool_calling (get_then_create_event_tool) | ❌ | ❌ | ❌ |
 | test_chat_non_streaming_multi_turn_tool_calling (text_then_weather_tool) | ❌ | ❌ | ❌ |
 | test_chat_non_streaming_multi_turn_tool_calling (weather_tool_then_text) | ❌ | ❌ | ❌ |
-| test_chat_non_streaming_structured_output (calendar) | ✅ | ✅ | ✅ |
-| test_chat_non_streaming_structured_output (math) | ✅ | ✅ | ✅ |
+| test_chat_non_streaming_structured_output (calendar) | ❌ | ❌ | ❌ |
+| test_chat_non_streaming_structured_output (math) | ❌ | ❌ | ❌ |
 | test_chat_non_streaming_tool_calling | ❌ | ❌ | ❌ |
-| test_chat_non_streaming_tool_choice_none | ✅ | ✅ | ✅ |
-| test_chat_non_streaming_tool_choice_required | ✅ | ❌ | ❌ |
-| test_chat_streaming_basic (earth) | ✅ | ✅ | ✅ |
-| test_chat_streaming_basic (saturn) | ✅ | ✅ | ✅ |
-| test_chat_streaming_image | ⚪ | ✅ | ✅ |
+| test_chat_non_streaming_tool_choice_none | ❌ | ❌ | ❌ |
+| test_chat_non_streaming_tool_choice_required | ❌ | ❌ | ❌ |
+| test_chat_streaming_basic (earth) | ❌ | ❌ | ❌ |
+| test_chat_streaming_basic (saturn) | ❌ | ❌ | ❌ |
+| test_chat_streaming_image | ⚪ | ❌ | ❌ |
 | test_chat_streaming_multi_turn_tool_calling (add_product_tool) | ❌ | ❌ | ❌ |
 | test_chat_streaming_multi_turn_tool_calling (compare_monthly_expense_tool) | ❌ | ❌ | ❌ |
 | test_chat_streaming_multi_turn_tool_calling (get_then_create_event_tool) | ❌ | ❌ | ❌ |
 | test_chat_streaming_multi_turn_tool_calling (text_then_weather_tool) | ❌ | ❌ | ❌ |
 | test_chat_streaming_multi_turn_tool_calling (weather_tool_then_text) | ❌ | ❌ | ❌ |
-| test_chat_streaming_structured_output (calendar) | ✅ | ✅ | ✅ |
-| test_chat_streaming_structured_output (math) | ✅ | ✅ | ✅ |
+| test_chat_streaming_structured_output (calendar) | ❌ | ❌ | ❌ |
+| test_chat_streaming_structured_output (math) | ❌ | ❌ | ❌ |
 | test_chat_streaming_tool_calling | ❌ | ❌ | ❌ |
-| test_chat_streaming_tool_choice_none | ✅ | ✅ | ✅ |
-| test_chat_streaming_tool_choice_required | ✅ | ❌ | ❌ |
+| test_chat_streaming_tool_choice_none | ❌ | ❌ | ❌ |
+| test_chat_streaming_tool_choice_required | ❌ | ❌ | ❌ |
 
 ## Openai
 
-*Tests run on: 2025-04-16 15:09:18*
+*Tests run on: 2025-04-17 11:48:19*
 
 ```bash
 # Run all tests for this provider:
 pytest tests/verifications/openai_api/test_chat_completion.py --provider=openai -v
 
-# Example: Run only the 'earth' case of test_chat_non_streaming_basic:
-pytest tests/verifications/openai_api/test_chat_completion.py --provider=openai -k "test_chat_non_streaming_basic and earth"
+# Example: Run only the 'stream=False' case of test_chat_multi_turn_multiple_images:
+pytest tests/verifications/openai_api/test_chat_completion.py --provider=openai -k "test_chat_multi_turn_multiple_images and stream=False"
 ```
 
 
@@ -196,6 +202,8 @@ pytest tests/verifications/openai_api/test_chat_completion.py --provider=openai
 
 | Test | gpt-4o | gpt-4o-mini |
 | --- | --- | --- |
+| test_chat_multi_turn_multiple_images (stream=False) | ✅ | ✅ |
+| test_chat_multi_turn_multiple_images (stream=True) | ✅ | ✅ |
 | test_chat_non_streaming_basic (earth) | ✅ | ✅ |
 | test_chat_non_streaming_basic (saturn) | ✅ | ✅ |
 | test_chat_non_streaming_image | ✅ | ✅ |
diff --git a/tests/verifications/conf/cerebras.yaml b/tests/verifications/conf/cerebras.yaml
index 5b19b4916..37fc713d6 100644
--- a/tests/verifications/conf/cerebras.yaml
+++ b/tests/verifications/conf/cerebras.yaml
@@ -8,3 +8,4 @@ test_exclusions:
   llama-3.3-70b:
   - test_chat_non_streaming_image
   - test_chat_streaming_image
+  - test_chat_multi_turn_multiple_images
diff --git a/tests/verifications/conf/fireworks-llama-stack.yaml b/tests/verifications/conf/fireworks-llama-stack.yaml
index d91443dd9..fc78a1377 100644
--- a/tests/verifications/conf/fireworks-llama-stack.yaml
+++ b/tests/verifications/conf/fireworks-llama-stack.yaml
@@ -12,3 +12,4 @@ test_exclusions:
   fireworks/llama-v3p3-70b-instruct:
   - test_chat_non_streaming_image
   - test_chat_streaming_image
+  - test_chat_multi_turn_multiple_images
diff --git a/tests/verifications/conf/fireworks.yaml b/tests/verifications/conf/fireworks.yaml
index f55b707ba..9bb21f706 100644
--- a/tests/verifications/conf/fireworks.yaml
+++ b/tests/verifications/conf/fireworks.yaml
@@ -12,3 +12,4 @@ test_exclusions:
   accounts/fireworks/models/llama-v3p3-70b-instruct:
   - test_chat_non_streaming_image
   - test_chat_streaming_image
+  - test_chat_multi_turn_multiple_images
diff --git a/tests/verifications/conf/groq-llama-stack.yaml b/tests/verifications/conf/groq-llama-stack.yaml
index fd5e9abec..6958bafc5 100644
--- a/tests/verifications/conf/groq-llama-stack.yaml
+++ b/tests/verifications/conf/groq-llama-stack.yaml
@@ -12,3 +12,4 @@ test_exclusions:
   groq/llama-3.3-70b-versatile:
   - test_chat_non_streaming_image
   - test_chat_streaming_image
+  - test_chat_multi_turn_multiple_images
diff --git a/tests/verifications/conf/groq.yaml b/tests/verifications/conf/groq.yaml
index 76b1244ae..bc3de58e9 100644
--- a/tests/verifications/conf/groq.yaml
+++ b/tests/verifications/conf/groq.yaml
@@ -12,3 +12,4 @@ test_exclusions:
   llama-3.3-70b-versatile:
   - test_chat_non_streaming_image
   - test_chat_streaming_image
+  - test_chat_multi_turn_multiple_images
diff --git a/tests/verifications/conf/together-llama-stack.yaml b/tests/verifications/conf/together-llama-stack.yaml
index e49d82604..719e2d776 100644
--- a/tests/verifications/conf/together-llama-stack.yaml
+++ b/tests/verifications/conf/together-llama-stack.yaml
@@ -12,3 +12,4 @@ test_exclusions:
   together/meta-llama/Llama-3.3-70B-Instruct-Turbo:
   - test_chat_non_streaming_image
   - test_chat_streaming_image
+  - test_chat_multi_turn_multiple_images
diff --git a/tests/verifications/conf/together.yaml b/tests/verifications/conf/together.yaml
index 258616662..e8fb62ab9 100644
--- a/tests/verifications/conf/together.yaml
+++ b/tests/verifications/conf/together.yaml
@@ -12,3 +12,4 @@ test_exclusions:
   meta-llama/Llama-3.3-70B-Instruct-Turbo:
   - test_chat_non_streaming_image
   - test_chat_streaming_image
+  - test_chat_multi_turn_multiple_images
diff --git a/tests/verifications/generate_report.py b/tests/verifications/generate_report.py
index f0894bfce..2f87a16fd 100755
--- a/tests/verifications/generate_report.py
+++ b/tests/verifications/generate_report.py
@@ -412,7 +412,22 @@ def generate_report(
             # Determine display name based on case count
             base_name = base_test_name_map.get(test, test)  # Get base name
             case_count = base_test_case_counts.get(base_name, 1)  # Get count
-            display_test_name = base_name if case_count == 1 else test  # Choose display name
+            # --- BEGIN PATCH: show stream param name if test_chat_multiple_images ---
+            if case_count > 1 and test.startswith("test_chat_multiple_images "):
+                # Try to extract the param value from the test name
+                m = re.match(r"^(test_chat_multiple_images) \\\((.*)\\\)$", test)
+                if m:
+                    param_val = m.group(2)
+                    # Only replace True/False with stream=True/False if that's the only param
+                    if param_val in ("True", "False"):
+                        display_test_name = f"test_chat_multiple_images (stream={param_val})"
+                    else:
+                        display_test_name = test
+                else:
+                    display_test_name = test
+            else:
+                display_test_name = base_name if case_count == 1 else test  # Choose display name
+            # --- END PATCH ---
             row = f"| {display_test_name} |"  # Use display name
 
             for model_id in provider_models:
diff --git a/tests/verifications/openai_api/fixtures/images/vision_test_1.jpg b/tests/verifications/openai_api/fixtures/images/vision_test_1.jpg
new file mode 100644
index 000000000..32fd0c0e3
Binary files /dev/null and b/tests/verifications/openai_api/fixtures/images/vision_test_1.jpg differ
diff --git a/tests/verifications/openai_api/fixtures/images/vision_test_2.jpg b/tests/verifications/openai_api/fixtures/images/vision_test_2.jpg
new file mode 100644
index 000000000..f9c28e3d5
Binary files /dev/null and b/tests/verifications/openai_api/fixtures/images/vision_test_2.jpg differ
diff --git a/tests/verifications/openai_api/fixtures/images/vision_test_3.jpg b/tests/verifications/openai_api/fixtures/images/vision_test_3.jpg
new file mode 100644
index 000000000..63165ea86
Binary files /dev/null and b/tests/verifications/openai_api/fixtures/images/vision_test_3.jpg differ
diff --git a/tests/verifications/openai_api/test_chat_completion.py b/tests/verifications/openai_api/test_chat_completion.py
index 00a005fc8..3a311667a 100644
--- a/tests/verifications/openai_api/test_chat_completion.py
+++ b/tests/verifications/openai_api/test_chat_completion.py
@@ -4,9 +4,11 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
+import base64
 import copy
 import json
 import re
+from pathlib import Path
 from typing import Any
 
 import pytest
@@ -19,6 +21,8 @@ from tests.verifications.openai_api.fixtures.load import load_test_cases
 
 chat_completion_test_cases = load_test_cases("chat_completion")
 
+THIS_DIR = Path(__file__).parent
+
 
 def case_id_generator(case):
     """Generate a test ID from the case's 'case_id' field, or use a default."""
@@ -71,6 +75,21 @@ def get_base_test_name(request):
     return request.node.originalname
 
 
+@pytest.fixture
+def multi_image_data():
+    files = [
+        THIS_DIR / "fixtures/images/vision_test_1.jpg",
+        THIS_DIR / "fixtures/images/vision_test_2.jpg",
+        THIS_DIR / "fixtures/images/vision_test_3.jpg",
+    ]
+    encoded_files = []
+    for file in files:
+        with open(file, "rb") as image_file:
+            base64_data = base64.b64encode(image_file.read()).decode("utf-8")
+            encoded_files.append(f"data:image/jpeg;base64,{base64_data}")
+    return encoded_files
+
+
 # --- Test Functions ---
 
 
@@ -533,6 +552,86 @@ def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, p
             )
 
 
+@pytest.mark.parametrize("stream", [False, True], ids=["stream=False", "stream=True"])
+def test_chat_multi_turn_multiple_images(
+    request, openai_client, model, provider, verification_config, multi_image_data, stream
+):
+    test_name_base = get_base_test_name(request)
+    if should_skip_test(verification_config, provider, model, test_name_base):
+        pytest.skip(f"Skipping {test_name_base} for model {model} on provider {provider} based on config.")
+
+    messages_turn1 = [
+        {
+            "role": "user",
+            "content": [
+                {
+                    "type": "image_url",
+                    "image_url": {
+                        "url": multi_image_data[0],
+                    },
+                },
+                {
+                    "type": "image_url",
+                    "image_url": {
+                        "url": multi_image_data[1],
+                    },
+                },
+                {
+                    "type": "text",
+                    "text": "What furniture is in the first image that is not in the second image?",
+                },
+            ],
+        },
+    ]
+
+    # First API call
+    response1 = openai_client.chat.completions.create(
+        model=model,
+        messages=messages_turn1,
+        stream=stream,
+    )
+    if stream:
+        message_content1 = ""
+        for chunk in response1:
+            message_content1 += chunk.choices[0].delta.content or ""
+    else:
+        message_content1 = response1.choices[0].message.content
+    assert len(message_content1) > 0
+    assert any(expected in message_content1.lower().strip() for expected in {"chair", "table"}), message_content1
+
+    # Prepare messages for the second turn
+    messages_turn2 = messages_turn1 + [
+        {"role": "assistant", "content": message_content1},
+        {
+            "role": "user",
+            "content": [
+                {
+                    "type": "image_url",
+                    "image_url": {
+                        "url": multi_image_data[2],
+                    },
+                },
+                {"type": "text", "text": "What is in this image that is also in the first image?"},
+            ],
+        },
+    ]
+
+    # Second API call
+    response2 = openai_client.chat.completions.create(
+        model=model,
+        messages=messages_turn2,
+        stream=stream,
+    )
+    if stream:
+        message_content2 = ""
+        for chunk in response2:
+            message_content2 += chunk.choices[0].delta.content or ""
+    else:
+        message_content2 = response2.choices[0].message.content
+    assert len(message_content2) > 0
+    assert any(expected in message_content2.lower().strip() for expected in {"bed"}), message_content2
+
+
 # --- Helper functions (structured output validation) ---
 
 
diff --git a/tests/verifications/test_results/fireworks.json b/tests/verifications/test_results/fireworks.json
index 96bd250f2..cdab1d5a1 100644
--- a/tests/verifications/test_results/fireworks.json
+++ b/tests/verifications/test_results/fireworks.json
@@ -1,15 +1,14 @@
 {
-  "created": 1744841358.733644,
-  "duration": 198.2893340587616,
+  "created": 1744915698.8314075,
+  "duration": 25.619409322738647,
   "exitcode": 1,
-  "root": "/Users/erichuang/projects/llama-stack",
+  "root": "/home/erichuang/llama-stack",
   "environment": {},
   "summary": {
-    "passed": 36,
-    "skipped": 2,
-    "failed": 40,
-    "total": 78,
-    "collected": 78
+    "failed": 80,
+    "skipped": 4,
+    "total": 84,
+    "collected": 84
   },
   "collectors": [
     {
@@ -29,392 +28,422 @@
         {
           "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_basic[accounts/fireworks/models/llama-v3p3-70b-instruct-earth]",
           "type": "Function",
-          "lineno": 74
+          "lineno": 95
         },
         {
           "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_basic[accounts/fireworks/models/llama-v3p3-70b-instruct-saturn]",
           "type": "Function",
-          "lineno": 74
+          "lineno": 95
         },
         {
           "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_basic[accounts/fireworks/models/llama4-scout-instruct-basic-earth]",
           "type": "Function",
-          "lineno": 74
+          "lineno": 95
         },
         {
           "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_basic[accounts/fireworks/models/llama4-scout-instruct-basic-saturn]",
           "type": "Function",
-          "lineno": 74
+          "lineno": 95
         },
         {
           "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_basic[accounts/fireworks/models/llama4-maverick-instruct-basic-earth]",
           "type": "Function",
-          "lineno": 74
+          "lineno": 95
         },
         {
           "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_basic[accounts/fireworks/models/llama4-maverick-instruct-basic-saturn]",
           "type": "Function",
-          "lineno": 74
+          "lineno": 95
         },
         {
           "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_basic[accounts/fireworks/models/llama-v3p3-70b-instruct-earth]",
           "type": "Function",
-          "lineno": 93
+          "lineno": 114
         },
         {
           "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_basic[accounts/fireworks/models/llama-v3p3-70b-instruct-saturn]",
           "type": "Function",
-          "lineno": 93
+          "lineno": 114
         },
         {
           "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_basic[accounts/fireworks/models/llama4-scout-instruct-basic-earth]",
           "type": "Function",
-          "lineno": 93
+          "lineno": 114
         },
         {
           "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_basic[accounts/fireworks/models/llama4-scout-instruct-basic-saturn]",
           "type": "Function",
-          "lineno": 93
+          "lineno": 114
         },
         {
           "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_basic[accounts/fireworks/models/llama4-maverick-instruct-basic-earth]",
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@@ -441,22 +470,60 @@
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+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
+          }
+        ],
+        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_basic[accounts/fireworks/models/llama-v3p3-70b-instruct-earth]>>\nopenai_client = <openai.OpenAI object at 0x7fa60ff6d630>\nmodel = 'accounts/fireworks/models/llama-v3p3-70b-instruct'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'earth', 'input': {'messages': [{'content': 'Which planet do humans live on?', 'role': 'user'}]}, 'output': 'Earth'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_basic\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_basic(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n>       response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            stream=False,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:106: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60ff6d630>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.00017529213801026344,
+        "duration": 0.00032798200845718384,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_basic[accounts/fireworks/models/llama-v3p3-70b-instruct-saturn]",
-      "lineno": 74,
-      "outcome": "passed",
+      "lineno": 95,
+      "outcome": "failed",
       "keywords": [
         "test_chat_non_streaming_basic[accounts/fireworks/models/llama-v3p3-70b-instruct-saturn]",
         "parametrize",
@@ -474,22 +541,60 @@
         "case_id": "saturn"
       },
       "setup": {
-        "duration": 0.0087524161208421,
+        "duration": 0.07205227017402649,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.7628215830773115,
-        "outcome": "passed"
+        "duration": 0.1848590886220336,
+        "outcome": "failed",
+        "crash": {
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
+        },
+        "traceback": [
+          {
+            "path": "tests/verifications/openai_api/test_chat_completion.py",
+            "lineno": 106,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
+          }
+        ],
+        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_basic[accounts/fireworks/models/llama-v3p3-70b-instruct-saturn]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fc4fd60>\nmodel = 'accounts/fireworks/models/llama-v3p3-70b-instruct'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'saturn', 'input': {'messages': [{'content': 'Which planet has rings around it with a name starting with letter S?', 'role': 'user'}]}, 'output': 'Saturn'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_basic\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_basic(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n>       response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            stream=False,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:106: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fc4fd60>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.00014924979768693447,
+        "duration": 0.0003115283325314522,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_basic[accounts/fireworks/models/llama4-scout-instruct-basic-earth]",
-      "lineno": 74,
-      "outcome": "passed",
+      "lineno": 95,
+      "outcome": "failed",
       "keywords": [
         "test_chat_non_streaming_basic[accounts/fireworks/models/llama4-scout-instruct-basic-earth]",
         "parametrize",
@@ -507,22 +612,60 @@
         "case_id": "earth"
       },
       "setup": {
-        "duration": 0.022251666989177465,
+        "duration": 0.06999052409082651,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.9107230410445482,
-        "outcome": "passed"
+        "duration": 0.20786387100815773,
+        "outcome": "failed",
+        "crash": {
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
+        },
+        "traceback": [
+          {
+            "path": "tests/verifications/openai_api/test_chat_completion.py",
+            "lineno": 106,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
+          }
+        ],
+        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_basic[accounts/fireworks/models/llama4-scout-instruct-basic-earth]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fc18dc0>\nmodel = 'accounts/fireworks/models/llama4-scout-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'earth', 'input': {'messages': [{'content': 'Which planet do humans live on?', 'role': 'user'}]}, 'output': 'Earth'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_basic\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_basic(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n>       response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            stream=False,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:106: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fc18dc0>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.0005349158309400082,
+        "duration": 0.000301288440823555,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_basic[accounts/fireworks/models/llama4-scout-instruct-basic-saturn]",
-      "lineno": 74,
-      "outcome": "passed",
+      "lineno": 95,
+      "outcome": "failed",
       "keywords": [
         "test_chat_non_streaming_basic[accounts/fireworks/models/llama4-scout-instruct-basic-saturn]",
         "parametrize",
@@ -540,22 +683,60 @@
         "case_id": "saturn"
       },
       "setup": {
-        "duration": 0.013857041951268911,
+        "duration": 0.07327916752547026,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.8181981248781085,
-        "outcome": "passed"
+        "duration": 0.26050146389752626,
+        "outcome": "failed",
+        "crash": {
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
+        },
+        "traceback": [
+          {
+            "path": "tests/verifications/openai_api/test_chat_completion.py",
+            "lineno": 106,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
+          }
+        ],
+        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_basic[accounts/fireworks/models/llama4-scout-instruct-basic-saturn]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fc18310>\nmodel = 'accounts/fireworks/models/llama4-scout-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'saturn', 'input': {'messages': [{'content': 'Which planet has rings around it with a name starting with letter S?', 'role': 'user'}]}, 'output': 'Saturn'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_basic\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_basic(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n>       response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            stream=False,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:106: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fc18310>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.00025879195891320705,
+        "duration": 0.0004022866487503052,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_basic[accounts/fireworks/models/llama4-maverick-instruct-basic-earth]",
-      "lineno": 74,
-      "outcome": "passed",
+      "lineno": 95,
+      "outcome": "failed",
       "keywords": [
         "test_chat_non_streaming_basic[accounts/fireworks/models/llama4-maverick-instruct-basic-earth]",
         "parametrize",
@@ -573,22 +754,60 @@
         "case_id": "earth"
       },
       "setup": {
-        "duration": 0.009510500123724341,
+        "duration": 0.07078082300722599,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.9497090419754386,
-        "outcome": "passed"
+        "duration": 0.12057740241289139,
+        "outcome": "failed",
+        "crash": {
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
+        },
+        "traceback": [
+          {
+            "path": "tests/verifications/openai_api/test_chat_completion.py",
+            "lineno": 106,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
+          }
+        ],
+        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_basic[accounts/fireworks/models/llama4-maverick-instruct-basic-earth]>>\nopenai_client = <openai.OpenAI object at 0x7fa60ff28280>\nmodel = 'accounts/fireworks/models/llama4-maverick-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'earth', 'input': {'messages': [{'content': 'Which planet do humans live on?', 'role': 'user'}]}, 'output': 'Earth'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_basic\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_basic(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n>       response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            stream=False,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:106: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60ff28280>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.0002393750473856926,
+        "duration": 0.0003570122644305229,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_basic[accounts/fireworks/models/llama4-maverick-instruct-basic-saturn]",
-      "lineno": 74,
-      "outcome": "passed",
+      "lineno": 95,
+      "outcome": "failed",
       "keywords": [
         "test_chat_non_streaming_basic[accounts/fireworks/models/llama4-maverick-instruct-basic-saturn]",
         "parametrize",
@@ -606,22 +825,60 @@
         "case_id": "saturn"
       },
       "setup": {
-        "duration": 0.007223791908472776,
+        "duration": 0.07103450503200293,
         "outcome": "passed"
       },
       "call": {
-        "duration": 1.0455189999192953,
-        "outcome": "passed"
+        "duration": 0.1985377622768283,
+        "outcome": "failed",
+        "crash": {
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
+        },
+        "traceback": [
+          {
+            "path": "tests/verifications/openai_api/test_chat_completion.py",
+            "lineno": 106,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
+          }
+        ],
+        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_basic[accounts/fireworks/models/llama4-maverick-instruct-basic-saturn]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fedb280>\nmodel = 'accounts/fireworks/models/llama4-maverick-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'saturn', 'input': {'messages': [{'content': 'Which planet has rings around it with a name starting with letter S?', 'role': 'user'}]}, 'output': 'Saturn'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_basic\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_basic(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n>       response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            stream=False,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:106: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fedb280>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.00016391696408391,
+        "duration": 0.00040165428072214127,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_basic[accounts/fireworks/models/llama-v3p3-70b-instruct-earth]",
-      "lineno": 93,
-      "outcome": "passed",
+      "lineno": 114,
+      "outcome": "failed",
       "keywords": [
         "test_chat_streaming_basic[accounts/fireworks/models/llama-v3p3-70b-instruct-earth]",
         "parametrize",
@@ -639,22 +896,60 @@
         "case_id": "earth"
       },
       "setup": {
-        "duration": 0.00976466597057879,
+        "duration": 0.07413783948868513,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.43124016700312495,
-        "outcome": "passed"
+        "duration": 0.11946621909737587,
+        "outcome": "failed",
+        "crash": {
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
+        },
+        "traceback": [
+          {
+            "path": "tests/verifications/openai_api/test_chat_completion.py",
+            "lineno": 125,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
+          }
+        ],
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_basic[accounts/fireworks/models/llama-v3p3-70b-instruct-earth]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fcdb850>\nmodel = 'accounts/fireworks/models/llama-v3p3-70b-instruct'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'earth', 'input': {'messages': [{'content': 'Which planet do humans live on?', 'role': 'user'}]}, 'output': 'Earth'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_basic\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_basic(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n>       response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            stream=True,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:125: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fcdb850>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.00027937511913478374,
+        "duration": 0.000340278260409832,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_basic[accounts/fireworks/models/llama-v3p3-70b-instruct-saturn]",
-      "lineno": 93,
-      "outcome": "passed",
+      "lineno": 114,
+      "outcome": "failed",
       "keywords": [
         "test_chat_streaming_basic[accounts/fireworks/models/llama-v3p3-70b-instruct-saturn]",
         "parametrize",
@@ -672,22 +967,60 @@
         "case_id": "saturn"
       },
       "setup": {
-        "duration": 0.010796832852065563,
+        "duration": 0.07317963056266308,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.7021721659693867,
-        "outcome": "passed"
+        "duration": 0.12889465410262346,
+        "outcome": "failed",
+        "crash": {
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
+        },
+        "traceback": [
+          {
+            "path": "tests/verifications/openai_api/test_chat_completion.py",
+            "lineno": 125,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
+          }
+        ],
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_basic[accounts/fireworks/models/llama-v3p3-70b-instruct-saturn]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fd5bd90>\nmodel = 'accounts/fireworks/models/llama-v3p3-70b-instruct'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'saturn', 'input': {'messages': [{'content': 'Which planet has rings around it with a name starting with letter S?', 'role': 'user'}]}, 'output': 'Saturn'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_basic\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_basic(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n>       response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            stream=True,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:125: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fd5bd90>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.00016912491992115974,
+        "duration": 0.00041081756353378296,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_basic[accounts/fireworks/models/llama4-scout-instruct-basic-earth]",
-      "lineno": 93,
-      "outcome": "passed",
+      "lineno": 114,
+      "outcome": "failed",
       "keywords": [
         "test_chat_streaming_basic[accounts/fireworks/models/llama4-scout-instruct-basic-earth]",
         "parametrize",
@@ -705,22 +1038,60 @@
         "case_id": "earth"
       },
       "setup": {
-        "duration": 0.013177082873880863,
+        "duration": 0.07138469163328409,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.6185361249372363,
-        "outcome": "passed"
+        "duration": 0.15935677476227283,
+        "outcome": "failed",
+        "crash": {
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
+        },
+        "traceback": [
+          {
+            "path": "tests/verifications/openai_api/test_chat_completion.py",
+            "lineno": 125,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
+          }
+        ],
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_basic[accounts/fireworks/models/llama4-scout-instruct-basic-earth]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fc47c40>\nmodel = 'accounts/fireworks/models/llama4-scout-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'earth', 'input': {'messages': [{'content': 'Which planet do humans live on?', 'role': 'user'}]}, 'output': 'Earth'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_basic\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_basic(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n>       response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            stream=True,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:125: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fc47c40>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.00015533296391367912,
+        "duration": 0.0004040272906422615,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_basic[accounts/fireworks/models/llama4-scout-instruct-basic-saturn]",
-      "lineno": 93,
-      "outcome": "passed",
+      "lineno": 114,
+      "outcome": "failed",
       "keywords": [
         "test_chat_streaming_basic[accounts/fireworks/models/llama4-scout-instruct-basic-saturn]",
         "parametrize",
@@ -738,22 +1109,60 @@
         "case_id": "saturn"
       },
       "setup": {
-        "duration": 0.010240375064313412,
+        "duration": 0.07108956202864647,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.821553833084181,
-        "outcome": "passed"
+        "duration": 0.16156401950865984,
+        "outcome": "failed",
+        "crash": {
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
+        },
+        "traceback": [
+          {
+            "path": "tests/verifications/openai_api/test_chat_completion.py",
+            "lineno": 125,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
+          }
+        ],
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_basic[accounts/fireworks/models/llama4-scout-instruct-basic-saturn]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fc44070>\nmodel = 'accounts/fireworks/models/llama4-scout-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'saturn', 'input': {'messages': [{'content': 'Which planet has rings around it with a name starting with letter S?', 'role': 'user'}]}, 'output': 'Saturn'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_basic\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_basic(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n>       response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            stream=True,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:125: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fc44070>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.00016791699454188347,
+        "duration": 0.0005099587142467499,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_basic[accounts/fireworks/models/llama4-maverick-instruct-basic-earth]",
-      "lineno": 93,
-      "outcome": "passed",
+      "lineno": 114,
+      "outcome": "failed",
       "keywords": [
         "test_chat_streaming_basic[accounts/fireworks/models/llama4-maverick-instruct-basic-earth]",
         "parametrize",
@@ -771,22 +1180,60 @@
         "case_id": "earth"
       },
       "setup": {
-        "duration": 0.027903249952942133,
+        "duration": 0.10071694944053888,
         "outcome": "passed"
       },
       "call": {
-        "duration": 1.0108601248357445,
-        "outcome": "passed"
+        "duration": 0.10996749810874462,
+        "outcome": "failed",
+        "crash": {
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
+        },
+        "traceback": [
+          {
+            "path": "tests/verifications/openai_api/test_chat_completion.py",
+            "lineno": 125,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
+          }
+        ],
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_basic[accounts/fireworks/models/llama4-maverick-instruct-basic-earth]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fc506a0>\nmodel = 'accounts/fireworks/models/llama4-maverick-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'earth', 'input': {'messages': [{'content': 'Which planet do humans live on?', 'role': 'user'}]}, 'output': 'Earth'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_basic\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_basic(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n>       response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            stream=True,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:125: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fc506a0>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.00086424988694489,
+        "duration": 0.0003982819616794586,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_basic[accounts/fireworks/models/llama4-maverick-instruct-basic-saturn]",
-      "lineno": 93,
-      "outcome": "passed",
+      "lineno": 114,
+      "outcome": "failed",
       "keywords": [
         "test_chat_streaming_basic[accounts/fireworks/models/llama4-maverick-instruct-basic-saturn]",
         "parametrize",
@@ -804,21 +1251,59 @@
         "case_id": "saturn"
       },
       "setup": {
-        "duration": 0.01084445882588625,
+        "duration": 0.07027470227330923,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.7071538330055773,
-        "outcome": "passed"
+        "duration": 0.2695386055856943,
+        "outcome": "failed",
+        "crash": {
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
+        },
+        "traceback": [
+          {
+            "path": "tests/verifications/openai_api/test_chat_completion.py",
+            "lineno": 125,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
+          }
+        ],
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_basic[accounts/fireworks/models/llama4-maverick-instruct-basic-saturn]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fbc1f60>\nmodel = 'accounts/fireworks/models/llama4-maverick-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'saturn', 'input': {'messages': [{'content': 'Which planet has rings around it with a name starting with letter S?', 'role': 'user'}]}, 'output': 'Saturn'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_basic\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_basic(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n>       response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            stream=True,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:125: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fbc1f60>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.00016791699454188347,
+        "duration": 0.00039549078792333603,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_image[accounts/fireworks/models/llama-v3p3-70b-instruct-case0]",
-      "lineno": 117,
+      "lineno": 138,
       "outcome": "skipped",
       "keywords": [
         "test_chat_non_streaming_image[accounts/fireworks/models/llama-v3p3-70b-instruct-case0]",
@@ -837,23 +1322,23 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.008069749921560287,
+        "duration": 0.07210677769035101,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.00013195793144404888,
+        "duration": 0.0004008617252111435,
         "outcome": "skipped",
-        "longrepr": "('/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py', 126, 'Skipped: Skipping test_chat_non_streaming_image for model accounts/fireworks/models/llama-v3p3-70b-instruct on provider fireworks based on config.')"
+        "longrepr": "('/home/erichuang/llama-stack/tests/verifications/openai_api/test_chat_completion.py', 147, 'Skipped: Skipping test_chat_non_streaming_image for model accounts/fireworks/models/llama-v3p3-70b-instruct on provider fireworks based on config.')"
       },
       "teardown": {
-        "duration": 0.0001144171692430973,
+        "duration": 0.00022324267774820328,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_image[accounts/fireworks/models/llama4-scout-instruct-basic-case0]",
-      "lineno": 117,
-      "outcome": "passed",
+      "lineno": 138,
+      "outcome": "failed",
       "keywords": [
         "test_chat_non_streaming_image[accounts/fireworks/models/llama4-scout-instruct-basic-case0]",
         "parametrize",
@@ -871,22 +1356,60 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.007050167070701718,
+        "duration": 0.07092681247740984,
         "outcome": "passed"
       },
       "call": {
-        "duration": 3.9182373338844627,
-        "outcome": "passed"
+        "duration": 0.1368834748864174,
+        "outcome": "failed",
+        "crash": {
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
+        },
+        "traceback": [
+          {
+            "path": "tests/verifications/openai_api/test_chat_completion.py",
+            "lineno": 149,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
+          }
+        ],
+        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_image[accounts/fireworks/models/llama4-scout-instruct-basic-case0]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fc51570>\nmodel = 'accounts/fireworks/models/llama4-scout-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': [{'text': 'What is in this image?', 'type': 'text'}, {'image_url': {...}, 'type': 'image_url'}], 'role': 'user'}]}, 'output': 'llama'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_image\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_image(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n>       response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            stream=False,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:149: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fc51570>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.00019966717809438705,
+        "duration": 0.00034329574555158615,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_image[accounts/fireworks/models/llama4-maverick-instruct-basic-case0]",
-      "lineno": 117,
-      "outcome": "passed",
+      "lineno": 138,
+      "outcome": "failed",
       "keywords": [
         "test_chat_non_streaming_image[accounts/fireworks/models/llama4-maverick-instruct-basic-case0]",
         "parametrize",
@@ -904,21 +1427,59 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.008392874849960208,
+        "duration": 0.07233018893748522,
         "outcome": "passed"
       },
       "call": {
-        "duration": 2.8514340829569846,
-        "outcome": "passed"
+        "duration": 0.2651740964502096,
+        "outcome": "failed",
+        "crash": {
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
+        },
+        "traceback": [
+          {
+            "path": "tests/verifications/openai_api/test_chat_completion.py",
+            "lineno": 149,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
+          }
+        ],
+        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_image[accounts/fireworks/models/llama4-maverick-instruct-basic-case0]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fb2b940>\nmodel = 'accounts/fireworks/models/llama4-maverick-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': [{'text': 'What is in this image?', 'type': 'text'}, {'image_url': {...}, 'type': 'image_url'}], 'role': 'user'}]}, 'output': 'llama'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_image\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_image(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n>       response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            stream=False,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:149: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fb2b940>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.00015016598626971245,
+        "duration": 0.00043803267180919647,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_image[accounts/fireworks/models/llama-v3p3-70b-instruct-case0]",
-      "lineno": 136,
+      "lineno": 157,
       "outcome": "skipped",
       "keywords": [
         "test_chat_streaming_image[accounts/fireworks/models/llama-v3p3-70b-instruct-case0]",
@@ -937,23 +1498,23 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.008044542046263814,
+        "duration": 0.07322083134204149,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.00013612513430416584,
+        "duration": 0.0002896450459957123,
         "outcome": "skipped",
-        "longrepr": "('/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py', 145, 'Skipped: Skipping test_chat_streaming_image for model accounts/fireworks/models/llama-v3p3-70b-instruct on provider fireworks based on config.')"
+        "longrepr": "('/home/erichuang/llama-stack/tests/verifications/openai_api/test_chat_completion.py', 166, 'Skipped: Skipping test_chat_streaming_image for model accounts/fireworks/models/llama-v3p3-70b-instruct on provider fireworks based on config.')"
       },
       "teardown": {
-        "duration": 0.00011420785449445248,
+        "duration": 0.0003790464252233505,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_image[accounts/fireworks/models/llama4-scout-instruct-basic-case0]",
-      "lineno": 136,
-      "outcome": "passed",
+      "lineno": 157,
+      "outcome": "failed",
       "keywords": [
         "test_chat_streaming_image[accounts/fireworks/models/llama4-scout-instruct-basic-case0]",
         "parametrize",
@@ -971,22 +1532,60 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.022763416869565845,
+        "duration": 0.07414108049124479,
         "outcome": "passed"
       },
       "call": {
-        "duration": 3.268299042014405,
-        "outcome": "passed"
+        "duration": 0.11951867491006851,
+        "outcome": "failed",
+        "crash": {
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
+        },
+        "traceback": [
+          {
+            "path": "tests/verifications/openai_api/test_chat_completion.py",
+            "lineno": 168,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
+          }
+        ],
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_image[accounts/fireworks/models/llama4-scout-instruct-basic-case0]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fea8c70>\nmodel = 'accounts/fireworks/models/llama4-scout-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': [{'text': 'What is in this image?', 'type': 'text'}, {'image_url': {...}, 'type': 'image_url'}], 'role': 'user'}]}, 'output': 'llama'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_image\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_image(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n>       response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            stream=True,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:168: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fea8c70>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.00027012499049305916,
+        "duration": 0.00031629856675863266,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_image[accounts/fireworks/models/llama4-maverick-instruct-basic-case0]",
-      "lineno": 136,
-      "outcome": "passed",
+      "lineno": 157,
+      "outcome": "failed",
       "keywords": [
         "test_chat_streaming_image[accounts/fireworks/models/llama4-maverick-instruct-basic-case0]",
         "parametrize",
@@ -1004,22 +1603,60 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.011526082875207067,
+        "duration": 0.07023830153048038,
         "outcome": "passed"
       },
       "call": {
-        "duration": 2.2131577918771654,
-        "outcome": "passed"
+        "duration": 0.27065565437078476,
+        "outcome": "failed",
+        "crash": {
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
+        },
+        "traceback": [
+          {
+            "path": "tests/verifications/openai_api/test_chat_completion.py",
+            "lineno": 168,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
+          }
+        ],
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_image[accounts/fireworks/models/llama4-maverick-instruct-basic-case0]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fd7c490>\nmodel = 'accounts/fireworks/models/llama4-maverick-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': [{'text': 'What is in this image?', 'type': 'text'}, {'image_url': {...}, 'type': 'image_url'}], 'role': 'user'}]}, 'output': 'llama'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_image\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_image(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n>       response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            stream=True,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:168: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fd7c490>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.00036754203028976917,
+        "duration": 0.00030570197850465775,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_structured_output[accounts/fireworks/models/llama-v3p3-70b-instruct-calendar]",
-      "lineno": 160,
-      "outcome": "passed",
+      "lineno": 181,
+      "outcome": "failed",
       "keywords": [
         "test_chat_non_streaming_structured_output[accounts/fireworks/models/llama-v3p3-70b-instruct-calendar]",
         "parametrize",
@@ -1037,22 +1674,60 @@
         "case_id": "calendar"
       },
       "setup": {
-        "duration": 0.007315041031688452,
+        "duration": 0.06930147111415863,
         "outcome": "passed"
       },
       "call": {
-        "duration": 1.0874837909359485,
-        "outcome": "passed"
+        "duration": 0.12505585234612226,
+        "outcome": "failed",
+        "crash": {
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
+        },
+        "traceback": [
+          {
+            "path": "tests/verifications/openai_api/test_chat_completion.py",
+            "lineno": 192,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
+          }
+        ],
+        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_structured_output[accounts/fireworks/models/llama-v3p3-70b-instruct-calendar]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fd56470>\nmodel = 'accounts/fireworks/models/llama-v3p3-70b-instruct'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'calendar', 'input': {'messages': [{'content': 'Extract the event information.', 'role': 'system'}, {'cont...articipants'], 'title': 'CalendarEvent', 'type': 'object'}}, 'type': 'json_schema'}}, 'output': 'valid_calendar_event'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_structured_output\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_structured_output(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n>       response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            response_format=case[\"input\"][\"response_format\"],\n            stream=False,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:192: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fd56470>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.0001659579575061798,
+        "duration": 0.00032288581132888794,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_structured_output[accounts/fireworks/models/llama-v3p3-70b-instruct-math]",
-      "lineno": 160,
-      "outcome": "passed",
+      "lineno": 181,
+      "outcome": "failed",
       "keywords": [
         "test_chat_non_streaming_structured_output[accounts/fireworks/models/llama-v3p3-70b-instruct-math]",
         "parametrize",
@@ -1070,22 +1745,60 @@
         "case_id": "math"
       },
       "setup": {
-        "duration": 0.007333416026085615,
+        "duration": 0.07256390806287527,
         "outcome": "passed"
       },
       "call": {
-        "duration": 2.1965952501632273,
-        "outcome": "passed"
+        "duration": 0.19006201811134815,
+        "outcome": "failed",
+        "crash": {
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
+        },
+        "traceback": [
+          {
+            "path": "tests/verifications/openai_api/test_chat_completion.py",
+            "lineno": 192,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
+          }
+        ],
+        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_structured_output[accounts/fireworks/models/llama-v3p3-70b-instruct-math]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fd5a1d0>\nmodel = 'accounts/fireworks/models/llama-v3p3-70b-instruct'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'math', 'input': {'messages': [{'content': 'You are a helpful math tutor. Guide the user through the solut... ['steps', 'final_answer'], 'title': 'MathReasoning', ...}}, 'type': 'json_schema'}}, 'output': 'valid_math_reasoning'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_structured_output\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_structured_output(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n>       response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            response_format=case[\"input\"][\"response_format\"],\n            stream=False,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:192: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fd5a1d0>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.00016695796512067318,
+        "duration": 0.0003082631155848503,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_structured_output[accounts/fireworks/models/llama4-scout-instruct-basic-calendar]",
-      "lineno": 160,
-      "outcome": "passed",
+      "lineno": 181,
+      "outcome": "failed",
       "keywords": [
         "test_chat_non_streaming_structured_output[accounts/fireworks/models/llama4-scout-instruct-basic-calendar]",
         "parametrize",
@@ -1103,22 +1816,60 @@
         "case_id": "calendar"
       },
       "setup": {
-        "duration": 0.018881832947954535,
+        "duration": 0.07006069924682379,
         "outcome": "passed"
       },
       "call": {
-        "duration": 1.0430783748161048,
-        "outcome": "passed"
+        "duration": 0.15021017380058765,
+        "outcome": "failed",
+        "crash": {
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
+        },
+        "traceback": [
+          {
+            "path": "tests/verifications/openai_api/test_chat_completion.py",
+            "lineno": 192,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
+          }
+        ],
+        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_structured_output[accounts/fireworks/models/llama4-scout-instruct-basic-calendar]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fb01000>\nmodel = 'accounts/fireworks/models/llama4-scout-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'calendar', 'input': {'messages': [{'content': 'Extract the event information.', 'role': 'system'}, {'cont...articipants'], 'title': 'CalendarEvent', 'type': 'object'}}, 'type': 'json_schema'}}, 'output': 'valid_calendar_event'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_structured_output\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_structured_output(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n>       response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            response_format=case[\"input\"][\"response_format\"],\n            stream=False,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:192: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fb01000>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.00017116684466600418,
+        "duration": 0.0003278367221355438,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_structured_output[accounts/fireworks/models/llama4-scout-instruct-basic-math]",
-      "lineno": 160,
-      "outcome": "passed",
+      "lineno": 181,
+      "outcome": "failed",
       "keywords": [
         "test_chat_non_streaming_structured_output[accounts/fireworks/models/llama4-scout-instruct-basic-math]",
         "parametrize",
@@ -1136,22 +1887,60 @@
         "case_id": "math"
       },
       "setup": {
-        "duration": 0.007428582990542054,
+        "duration": 0.07383340876549482,
         "outcome": "passed"
       },
       "call": {
-        "duration": 2.2213701670989394,
-        "outcome": "passed"
+        "duration": 0.2492945184931159,
+        "outcome": "failed",
+        "crash": {
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
+        },
+        "traceback": [
+          {
+            "path": "tests/verifications/openai_api/test_chat_completion.py",
+            "lineno": 192,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
+          }
+        ],
+        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_structured_output[accounts/fireworks/models/llama4-scout-instruct-basic-math]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fc188b0>\nmodel = 'accounts/fireworks/models/llama4-scout-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'math', 'input': {'messages': [{'content': 'You are a helpful math tutor. Guide the user through the solut... ['steps', 'final_answer'], 'title': 'MathReasoning', ...}}, 'type': 'json_schema'}}, 'output': 'valid_math_reasoning'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_structured_output\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_structured_output(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n>       response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            response_format=case[\"input\"][\"response_format\"],\n            stream=False,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:192: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fc188b0>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.00017379201017320156,
+        "duration": 0.00041339918971061707,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_structured_output[accounts/fireworks/models/llama4-maverick-instruct-basic-calendar]",
-      "lineno": 160,
-      "outcome": "passed",
+      "lineno": 181,
+      "outcome": "failed",
       "keywords": [
         "test_chat_non_streaming_structured_output[accounts/fireworks/models/llama4-maverick-instruct-basic-calendar]",
         "parametrize",
@@ -1169,22 +1958,60 @@
         "case_id": "calendar"
       },
       "setup": {
-        "duration": 0.010865207994356751,
+        "duration": 0.07140334881842136,
         "outcome": "passed"
       },
       "call": {
-        "duration": 1.2025520419701934,
-        "outcome": "passed"
+        "duration": 0.3302767900750041,
+        "outcome": "failed",
+        "crash": {
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
+        },
+        "traceback": [
+          {
+            "path": "tests/verifications/openai_api/test_chat_completion.py",
+            "lineno": 192,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
+          }
+        ],
+        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_structured_output[accounts/fireworks/models/llama4-maverick-instruct-basic-calendar]>>\nopenai_client = <openai.OpenAI object at 0x7fa60ff6d480>\nmodel = 'accounts/fireworks/models/llama4-maverick-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'calendar', 'input': {'messages': [{'content': 'Extract the event information.', 'role': 'system'}, {'cont...articipants'], 'title': 'CalendarEvent', 'type': 'object'}}, 'type': 'json_schema'}}, 'output': 'valid_calendar_event'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_structured_output\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_structured_output(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n>       response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            response_format=case[\"input\"][\"response_format\"],\n            stream=False,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:192: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60ff6d480>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.00022362498566508293,
+        "duration": 0.0004214206710457802,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_structured_output[accounts/fireworks/models/llama4-maverick-instruct-basic-math]",
-      "lineno": 160,
-      "outcome": "passed",
+      "lineno": 181,
+      "outcome": "failed",
       "keywords": [
         "test_chat_non_streaming_structured_output[accounts/fireworks/models/llama4-maverick-instruct-basic-math]",
         "parametrize",
@@ -1202,22 +2029,60 @@
         "case_id": "math"
       },
       "setup": {
-        "duration": 0.00713775004260242,
+        "duration": 0.07027470134198666,
         "outcome": "passed"
       },
       "call": {
-        "duration": 1.9540662500075996,
-        "outcome": "passed"
+        "duration": 0.13318416848778725,
+        "outcome": "failed",
+        "crash": {
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
+        },
+        "traceback": [
+          {
+            "path": "tests/verifications/openai_api/test_chat_completion.py",
+            "lineno": 192,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
+          }
+        ],
+        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_structured_output[accounts/fireworks/models/llama4-maverick-instruct-basic-math]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fb01c30>\nmodel = 'accounts/fireworks/models/llama4-maverick-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'math', 'input': {'messages': [{'content': 'You are a helpful math tutor. Guide the user through the solut... ['steps', 'final_answer'], 'title': 'MathReasoning', ...}}, 'type': 'json_schema'}}, 'output': 'valid_math_reasoning'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_structured_output\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_structured_output(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n>       response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            response_format=case[\"input\"][\"response_format\"],\n            stream=False,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:192: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fb01c30>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.00015320791862905025,
+        "duration": 0.0003965655341744423,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_structured_output[accounts/fireworks/models/llama-v3p3-70b-instruct-calendar]",
-      "lineno": 183,
-      "outcome": "passed",
+      "lineno": 204,
+      "outcome": "failed",
       "keywords": [
         "test_chat_streaming_structured_output[accounts/fireworks/models/llama-v3p3-70b-instruct-calendar]",
         "parametrize",
@@ -1235,22 +2100,60 @@
         "case_id": "calendar"
       },
       "setup": {
-        "duration": 0.007249874994158745,
+        "duration": 0.07036527991294861,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.8976205829530954,
-        "outcome": "passed"
+        "duration": 0.10335173550993204,
+        "outcome": "failed",
+        "crash": {
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
+        },
+        "traceback": [
+          {
+            "path": "tests/verifications/openai_api/test_chat_completion.py",
+            "lineno": 215,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
+          }
+        ],
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_structured_output[accounts/fireworks/models/llama-v3p3-70b-instruct-calendar]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fc4ffa0>\nmodel = 'accounts/fireworks/models/llama-v3p3-70b-instruct'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'calendar', 'input': {'messages': [{'content': 'Extract the event information.', 'role': 'system'}, {'cont...articipants'], 'title': 'CalendarEvent', 'type': 'object'}}, 'type': 'json_schema'}}, 'output': 'valid_calendar_event'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_structured_output\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_structured_output(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n>       response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            response_format=case[\"input\"][\"response_format\"],\n            stream=True,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:215: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fc4ffa0>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.0004331250675022602,
+        "duration": 0.0003379611298441887,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_structured_output[accounts/fireworks/models/llama-v3p3-70b-instruct-math]",
-      "lineno": 183,
-      "outcome": "passed",
+      "lineno": 204,
+      "outcome": "failed",
       "keywords": [
         "test_chat_streaming_structured_output[accounts/fireworks/models/llama-v3p3-70b-instruct-math]",
         "parametrize",
@@ -1268,22 +2171,60 @@
         "case_id": "math"
       },
       "setup": {
-        "duration": 0.014962124871090055,
+        "duration": 0.06978577468544245,
         "outcome": "passed"
       },
       "call": {
-        "duration": 3.4227065418381244,
-        "outcome": "passed"
+        "duration": 0.12087872251868248,
+        "outcome": "failed",
+        "crash": {
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
+        },
+        "traceback": [
+          {
+            "path": "tests/verifications/openai_api/test_chat_completion.py",
+            "lineno": 215,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
+          }
+        ],
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_structured_output[accounts/fireworks/models/llama-v3p3-70b-instruct-math]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fe19cf0>\nmodel = 'accounts/fireworks/models/llama-v3p3-70b-instruct'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'math', 'input': {'messages': [{'content': 'You are a helpful math tutor. Guide the user through the solut... ['steps', 'final_answer'], 'title': 'MathReasoning', ...}}, 'type': 'json_schema'}}, 'output': 'valid_math_reasoning'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_structured_output\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_structured_output(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n>       response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            response_format=case[\"input\"][\"response_format\"],\n            stream=True,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:215: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fe19cf0>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.0003969999961555004,
+        "duration": 0.00042513664811849594,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_structured_output[accounts/fireworks/models/llama4-scout-instruct-basic-calendar]",
-      "lineno": 183,
-      "outcome": "passed",
+      "lineno": 204,
+      "outcome": "failed",
       "keywords": [
         "test_chat_streaming_structured_output[accounts/fireworks/models/llama4-scout-instruct-basic-calendar]",
         "parametrize",
@@ -1301,22 +2242,60 @@
         "case_id": "calendar"
       },
       "setup": {
-        "duration": 0.009212916949763894,
+        "duration": 0.07085503917187452,
         "outcome": "passed"
       },
       "call": {
-        "duration": 1.1613242500461638,
-        "outcome": "passed"
+        "duration": 0.11609443742781878,
+        "outcome": "failed",
+        "crash": {
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
+        },
+        "traceback": [
+          {
+            "path": "tests/verifications/openai_api/test_chat_completion.py",
+            "lineno": 215,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
+          }
+        ],
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_structured_output[accounts/fireworks/models/llama4-scout-instruct-basic-calendar]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fbca530>\nmodel = 'accounts/fireworks/models/llama4-scout-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'calendar', 'input': {'messages': [{'content': 'Extract the event information.', 'role': 'system'}, {'cont...articipants'], 'title': 'CalendarEvent', 'type': 'object'}}, 'type': 'json_schema'}}, 'output': 'valid_calendar_event'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_structured_output\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_structured_output(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n>       response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            response_format=case[\"input\"][\"response_format\"],\n            stream=True,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:215: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fbca530>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.00015120790340006351,
+        "duration": 0.000426730141043663,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_structured_output[accounts/fireworks/models/llama4-scout-instruct-basic-math]",
-      "lineno": 183,
-      "outcome": "passed",
+      "lineno": 204,
+      "outcome": "failed",
       "keywords": [
         "test_chat_streaming_structured_output[accounts/fireworks/models/llama4-scout-instruct-basic-math]",
         "parametrize",
@@ -1334,22 +2313,60 @@
         "case_id": "math"
       },
       "setup": {
-        "duration": 0.008335874881595373,
+        "duration": 0.07437158096581697,
         "outcome": "passed"
       },
       "call": {
-        "duration": 3.4217867080587894,
-        "outcome": "passed"
+        "duration": 0.12889361381530762,
+        "outcome": "failed",
+        "crash": {
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
+        },
+        "traceback": [
+          {
+            "path": "tests/verifications/openai_api/test_chat_completion.py",
+            "lineno": 215,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
+          }
+        ],
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_structured_output[accounts/fireworks/models/llama4-scout-instruct-basic-math]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fc52500>\nmodel = 'accounts/fireworks/models/llama4-scout-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'math', 'input': {'messages': [{'content': 'You are a helpful math tutor. Guide the user through the solut... ['steps', 'final_answer'], 'title': 'MathReasoning', ...}}, 'type': 'json_schema'}}, 'output': 'valid_math_reasoning'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_structured_output\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_structured_output(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n>       response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            response_format=case[\"input\"][\"response_format\"],\n            stream=True,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:215: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fc52500>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.00015149987302720547,
+        "duration": 0.00043479073792696,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_structured_output[accounts/fireworks/models/llama4-maverick-instruct-basic-calendar]",
-      "lineno": 183,
-      "outcome": "passed",
+      "lineno": 204,
+      "outcome": "failed",
       "keywords": [
         "test_chat_streaming_structured_output[accounts/fireworks/models/llama4-maverick-instruct-basic-calendar]",
         "parametrize",
@@ -1367,22 +2384,60 @@
         "case_id": "calendar"
       },
       "setup": {
-        "duration": 0.007714165840297937,
+        "duration": 0.07079631183296442,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.9328924999572337,
-        "outcome": "passed"
+        "duration": 0.17871549632400274,
+        "outcome": "failed",
+        "crash": {
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
+        },
+        "traceback": [
+          {
+            "path": "tests/verifications/openai_api/test_chat_completion.py",
+            "lineno": 215,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
+          }
+        ],
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_structured_output[accounts/fireworks/models/llama4-maverick-instruct-basic-calendar]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fbf54e0>\nmodel = 'accounts/fireworks/models/llama4-maverick-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'calendar', 'input': {'messages': [{'content': 'Extract the event information.', 'role': 'system'}, {'cont...articipants'], 'title': 'CalendarEvent', 'type': 'object'}}, 'type': 'json_schema'}}, 'output': 'valid_calendar_event'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_structured_output\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_structured_output(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n>       response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            response_format=case[\"input\"][\"response_format\"],\n            stream=True,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:215: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fbf54e0>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.00019675004296004772,
+        "duration": 0.0003268783912062645,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_structured_output[accounts/fireworks/models/llama4-maverick-instruct-basic-math]",
-      "lineno": 183,
-      "outcome": "passed",
+      "lineno": 204,
+      "outcome": "failed",
       "keywords": [
         "test_chat_streaming_structured_output[accounts/fireworks/models/llama4-maverick-instruct-basic-math]",
         "parametrize",
@@ -1400,21 +2455,59 @@
         "case_id": "math"
       },
       "setup": {
-        "duration": 0.026319167111068964,
+        "duration": 0.07951002009212971,
         "outcome": "passed"
       },
       "call": {
-        "duration": 2.318451583152637,
-        "outcome": "passed"
+        "duration": 0.1458642790094018,
+        "outcome": "failed",
+        "crash": {
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
+        },
+        "traceback": [
+          {
+            "path": "tests/verifications/openai_api/test_chat_completion.py",
+            "lineno": 215,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
+          }
+        ],
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_structured_output[accounts/fireworks/models/llama4-maverick-instruct-basic-math]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fe1a230>\nmodel = 'accounts/fireworks/models/llama4-maverick-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'math', 'input': {'messages': [{'content': 'You are a helpful math tutor. Guide the user through the solut... ['steps', 'final_answer'], 'title': 'MathReasoning', ...}}, 'type': 'json_schema'}}, 'output': 'valid_math_reasoning'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_structured_output\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_structured_output(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n>       response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            response_format=case[\"input\"][\"response_format\"],\n            stream=True,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:215: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fe1a230>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.00014829100109636784,
+        "duration": 0.0004075644537806511,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-case0]",
-      "lineno": 205,
+      "lineno": 226,
       "outcome": "failed",
       "keywords": [
         "test_chat_non_streaming_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-case0]",
@@ -1433,34 +2526,59 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.007551209069788456,
+        "duration": 0.07230154424905777,
         "outcome": "passed"
       },
       "call": {
-        "duration": 10.397802790859714,
+        "duration": 0.13512122631072998,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 224,
-          "message": "TypeError: object of type 'NoneType' has no len()"
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 224,
-            "message": "TypeError"
+            "lineno": 237,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-case0]>>\nopenai_client = <openai.OpenAI object at 0x12126e7d0>\nmodel = 'accounts/fireworks/models/llama-v3p3-70b-instruct'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_tool_calling(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            stream=False,\n        )\n    \n        assert response.choices[0].message.role == \"assistant\"\n>       assert len(response.choices[0].message.tool_calls) > 0\nE       TypeError: object of type 'NoneType' has no len()\n\ntests/verifications/openai_api/test_chat_completion.py:224: TypeError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-case0]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fb9c6d0>\nmodel = 'accounts/fireworks/models/llama-v3p3-70b-instruct'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_tool_calling(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n>       response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            stream=False,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:237: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fb9c6d0>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.00037254090420901775,
+        "duration": 0.0003347489982843399,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-case0]",
-      "lineno": 205,
+      "lineno": 226,
       "outcome": "failed",
       "keywords": [
         "test_chat_non_streaming_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-case0]",
@@ -1479,34 +2597,59 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.018039333866909146,
+        "duration": 0.07080346252769232,
         "outcome": "passed"
       },
       "call": {
-        "duration": 3.3043739169370383,
+        "duration": 0.1290199300274253,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 224,
-          "message": "TypeError: object of type 'NoneType' has no len()"
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 224,
-            "message": "TypeError"
+            "lineno": 237,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-case0]>>\nopenai_client = <openai.OpenAI object at 0x121d3bd60>\nmodel = 'accounts/fireworks/models/llama4-scout-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_tool_calling(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            stream=False,\n        )\n    \n        assert response.choices[0].message.role == \"assistant\"\n>       assert len(response.choices[0].message.tool_calls) > 0\nE       TypeError: object of type 'NoneType' has no len()\n\ntests/verifications/openai_api/test_chat_completion.py:224: TypeError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-case0]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fb6e3e0>\nmodel = 'accounts/fireworks/models/llama4-scout-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_tool_calling(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n>       response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            stream=False,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:237: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fb6e3e0>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.00028795795515179634,
+        "duration": 0.0003189612179994583,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-case0]",
-      "lineno": 205,
+      "lineno": 226,
       "outcome": "failed",
       "keywords": [
         "test_chat_non_streaming_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-case0]",
@@ -1525,34 +2668,59 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.008603750029578805,
+        "duration": 0.07067843340337276,
         "outcome": "passed"
       },
       "call": {
-        "duration": 1.060112499864772,
+        "duration": 0.12150294054299593,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 224,
-          "message": "TypeError: object of type 'NoneType' has no len()"
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 224,
-            "message": "TypeError"
+            "lineno": 237,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-case0]>>\nopenai_client = <openai.OpenAI object at 0x121517b50>\nmodel = 'accounts/fireworks/models/llama4-maverick-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_tool_calling(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            stream=False,\n        )\n    \n        assert response.choices[0].message.role == \"assistant\"\n>       assert len(response.choices[0].message.tool_calls) > 0\nE       TypeError: object of type 'NoneType' has no len()\n\ntests/verifications/openai_api/test_chat_completion.py:224: TypeError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-case0]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fb01ba0>\nmodel = 'accounts/fireworks/models/llama4-maverick-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_tool_calling(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n>       response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            stream=False,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:237: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fb01ba0>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.0002542920410633087,
+        "duration": 0.00032811518758535385,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-case0]",
-      "lineno": 229,
+      "lineno": 250,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-case0]",
@@ -1571,34 +2739,59 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.007324707927182317,
+        "duration": 0.0696528134867549,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.5497581248637289,
+        "duration": 0.2847281629219651,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 248,
-          "message": "assert 0 == 1\n +  where 0 = len([])"
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 248,
-            "message": "AssertionError"
+            "lineno": 261,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-case0]>>\nopenai_client = <openai.OpenAI object at 0x121d3a200>\nmodel = 'accounts/fireworks/models/llama-v3p3-70b-instruct'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_tool_calling(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        stream = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            stream=True,\n        )\n    \n        _, tool_calls_buffer = _accumulate_streaming_tool_calls(stream)\n>       assert len(tool_calls_buffer) == 1\nE       assert 0 == 1\nE        +  where 0 = len([])\n\ntests/verifications/openai_api/test_chat_completion.py:248: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-case0]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fb7b2b0>\nmodel = 'accounts/fireworks/models/llama-v3p3-70b-instruct'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_tool_calling(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n>       stream = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            stream=True,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:261: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fb7b2b0>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.0003177919425070286,
+        "duration": 0.0004156995564699173,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-case0]",
-      "lineno": 229,
+      "lineno": 250,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-case0]",
@@ -1617,34 +2810,59 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.008655000012367964,
+        "duration": 0.07187621854245663,
         "outcome": "passed"
       },
       "call": {
-        "duration": 4.679868750041351,
+        "duration": 0.12863421067595482,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 248,
-          "message": "assert 0 == 1\n +  where 0 = len([])"
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 248,
-            "message": "AssertionError"
+            "lineno": 261,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-case0]>>\nopenai_client = <openai.OpenAI object at 0x12152e3e0>\nmodel = 'accounts/fireworks/models/llama4-scout-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_tool_calling(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        stream = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            stream=True,\n        )\n    \n        _, tool_calls_buffer = _accumulate_streaming_tool_calls(stream)\n>       assert len(tool_calls_buffer) == 1\nE       assert 0 == 1\nE        +  where 0 = len([])\n\ntests/verifications/openai_api/test_chat_completion.py:248: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-case0]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fb9c3a0>\nmodel = 'accounts/fireworks/models/llama4-scout-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_tool_calling(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n>       stream = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            stream=True,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:261: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fb9c3a0>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.0019099169876426458,
+        "duration": 0.00036760419607162476,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-case0]",
-      "lineno": 229,
+      "lineno": 250,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-case0]",
@@ -1663,35 +2881,60 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.009765458991751075,
+        "duration": 0.07296357583254576,
         "outcome": "passed"
       },
       "call": {
-        "duration": 7.277718541910872,
+        "duration": 0.12340501230210066,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 248,
-          "message": "assert 0 == 1\n +  where 0 = len([])"
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 248,
-            "message": "AssertionError"
+            "lineno": 261,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-case0]>>\nopenai_client = <openai.OpenAI object at 0x121542680>\nmodel = 'accounts/fireworks/models/llama4-maverick-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_tool_calling(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        stream = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            stream=True,\n        )\n    \n        _, tool_calls_buffer = _accumulate_streaming_tool_calls(stream)\n>       assert len(tool_calls_buffer) == 1\nE       assert 0 == 1\nE        +  where 0 = len([])\n\ntests/verifications/openai_api/test_chat_completion.py:248: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-case0]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fea83d0>\nmodel = 'accounts/fireworks/models/llama4-maverick-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_tool_calling(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n>       stream = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            stream=True,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:261: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fea83d0>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.00022799987345933914,
+        "duration": 0.00042413268238306046,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_tool_choice_required[accounts/fireworks/models/llama-v3p3-70b-instruct-case0]",
-      "lineno": 257,
-      "outcome": "passed",
+      "lineno": 278,
+      "outcome": "failed",
       "keywords": [
         "test_chat_non_streaming_tool_choice_required[accounts/fireworks/models/llama-v3p3-70b-instruct-case0]",
         "parametrize",
@@ -1709,22 +2952,59 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.00739812501706183,
+        "duration": 0.07447731029242277,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.6399214998818934,
-        "outcome": "passed",
-        "stdout": "ChatCompletion(id='ebbe2103-61bd-4b78-8386-810656aefecb', choices=[Choice(finish_reason='tool_calls', index=0, logprobs=None, message=ChatCompletionMessage(content=None, refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_4OSG1PnI71J1cYMJktMrxYUs', function=Function(arguments='{\"location\": \"San Francisco, USA\"}', name='get_weather'), type='function', index=0)]))], created=1744841233, model='accounts/fireworks/models/llama-v3p3-70b-instruct', object='chat.completion', service_tier=None, system_fingerprint=None, usage=CompletionUsage(completion_tokens=21, prompt_tokens=201, total_tokens=222, completion_tokens_details=None, prompt_tokens_details=None))\n"
+        "duration": 0.13054667692631483,
+        "outcome": "failed",
+        "crash": {
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
+        },
+        "traceback": [
+          {
+            "path": "tests/verifications/openai_api/test_chat_completion.py",
+            "lineno": 289,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
+          }
+        ],
+        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_tool_choice_required[accounts/fireworks/models/llama-v3p3-70b-instruct-case0]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fd71450>\nmodel = 'accounts/fireworks/models/llama-v3p3-70b-instruct'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],  # Reusing existing case for now\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_tool_choice_required(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n>       response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            tool_choice=\"required\",  # Force tool call\n            stream=False,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:289: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fd71450>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.00016408413648605347,
+        "duration": 0.00034614279866218567,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_tool_choice_required[accounts/fireworks/models/llama4-scout-instruct-basic-case0]",
-      "lineno": 257,
+      "lineno": 278,
       "outcome": "failed",
       "keywords": [
         "test_chat_non_streaming_tool_choice_required[accounts/fireworks/models/llama4-scout-instruct-basic-case0]",
@@ -1743,35 +3023,59 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.07514370908029377,
+        "duration": 0.07243293151259422,
         "outcome": "passed"
       },
       "call": {
-        "duration": 2.5754468340892345,
+        "duration": 0.12261831760406494,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 278,
-          "message": "TypeError: object of type 'NoneType' has no len()"
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 278,
-            "message": "TypeError"
+            "lineno": 289,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
           }
         ],
-        "stdout": "ChatCompletion(id='bd868590-b860-40a0-9572-0a2da202442b', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='{\"name\": \"get_weather\", \"parameters\": {\"description\": \"San Francisco in California, United States\", \"parameters\": {\"additionalProperties\": \"false\", \"properties\": {\"location\": {\"description\": \"City and country eg. Bogota, Colombia\", \"type\": \"string\"}}, \"type\": \"object\"}}}assistant\\n\\n{\"name\": \"get_weather\", \"parameters\": {\"description\": \"San Francisco in California, United States\", \"parameters\": {\"location\": \"San Francisco\"}}}assistant\\n\\n{\"name\": \"get_weather\", \"parameters\": {\"description\": \"San Francisco in California, United States\", \"parameters\": {\"location\": \"San Francisco\"}}}\\\\assistant\\n\\nThe provided function call is for the `get_weather` function, with the location as \"San Francisco\". The description of the location is not provided in the function call, so I assumed it as \"San Francisco in California, United States\". \\n\\nPlease replace \"San Francisco in California, United States\" with the actual description of the location if it is available. \\n\\nAlso, please note that the function call is in JSON format. \\n\\nThe function call is:\\n\\n{\"name\": \"get_weather\", \"parameters\": {\"description\": \"San Francisco in California, United States\", \"parameters\": {\"location\": \"San Francisco\"}}}', refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=None))], created=1744841233, model='accounts/fireworks/models/llama4-scout-instruct-basic', object='chat.completion', service_tier=None, system_fingerprint=None, usage=CompletionUsage(completion_tokens=274, prompt_tokens=924, total_tokens=1198, completion_tokens_details=None, prompt_tokens_details=None))\n",
-        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_tool_choice_required[accounts/fireworks/models/llama4-scout-instruct-basic-case0]>>\nopenai_client = <openai.OpenAI object at 0x12158d900>\nmodel = 'accounts/fireworks/models/llama4-scout-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],  # Reusing existing case for now\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_tool_choice_required(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            tool_choice=\"required\",  # Force tool call\n            stream=False,\n        )\n        print(response)\n    \n        assert response.choices[0].message.role == \"assistant\"\n>       assert len(response.choices[0].message.tool_calls) > 0, \"Expected tool call when tool_choice='required'\"\nE       TypeError: object of type 'NoneType' has no len()\n\ntests/verifications/openai_api/test_chat_completion.py:278: TypeError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_tool_choice_required[accounts/fireworks/models/llama4-scout-instruct-basic-case0]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fe198d0>\nmodel = 'accounts/fireworks/models/llama4-scout-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],  # Reusing existing case for now\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_tool_choice_required(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n>       response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            tool_choice=\"required\",  # Force tool call\n            stream=False,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:289: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fe198d0>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.0003993329592049122,
+        "duration": 0.0004268251359462738,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_tool_choice_required[accounts/fireworks/models/llama4-maverick-instruct-basic-case0]",
-      "lineno": 257,
+      "lineno": 278,
       "outcome": "failed",
       "keywords": [
         "test_chat_non_streaming_tool_choice_required[accounts/fireworks/models/llama4-maverick-instruct-basic-case0]",
@@ -1790,36 +3094,60 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.007923166966065764,
+        "duration": 0.07407685182988644,
         "outcome": "passed"
       },
       "call": {
-        "duration": 2.3553062081336975,
+        "duration": 0.09860698413103819,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 278,
-          "message": "TypeError: object of type 'NoneType' has no len()"
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 278,
-            "message": "TypeError"
+            "lineno": 289,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
           }
         ],
-        "stdout": "ChatCompletion(id='2ccf29f8-ed2a-4a60-b6e0-74e29025b409', choices=[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(content='{\"name\": \"get_weather\", \"parameters\": {\"properties\": {\"location\": {\"description\": \"City and country e.g. Bogot\u00e1, Colombia\", \"type\": \"string\", \"value\": \"San Francisco\"}}}} \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 Coaching \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 Coaching \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 Coaching Coaching Coaching Coaching Coaching Coaching Coaching Coaching Coaching Coaching Coaching Coaching Coaching Coaching Coaching Coaching Coaching Coaching Coaching Coaching Coaching Coaching Coaching Coaching Coaching Coaching Coaching Coaching Coaching Coaching Coaching Coaching Coaching Coaching Coaching Coaching Coaching Coaching Coaching Coaching Coaching Coaching Coaching Coaching Coaching Coaching Coaching Coaching coaching \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438 \u0421\u043e\u0447\u0438', refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=None))], created=1744841236, model='accounts/fireworks/models/llama4-maverick-instruct-basic', object='chat.completion', service_tier=None, system_fingerprint=None, usage=CompletionUsage(completion_tokens=205, prompt_tokens=924, total_tokens=1129, completion_tokens_details=None, prompt_tokens_details=None))\n",
-        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_tool_choice_required[accounts/fireworks/models/llama4-maverick-instruct-basic-case0]>>\nopenai_client = <openai.OpenAI object at 0x1215b8b50>\nmodel = 'accounts/fireworks/models/llama4-maverick-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],  # Reusing existing case for now\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_tool_choice_required(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            tool_choice=\"required\",  # Force tool call\n            stream=False,\n        )\n        print(response)\n    \n        assert response.choices[0].message.role == \"assistant\"\n>       assert len(response.choices[0].message.tool_calls) > 0, \"Expected tool call when tool_choice='required'\"\nE       TypeError: object of type 'NoneType' has no len()\n\ntests/verifications/openai_api/test_chat_completion.py:278: TypeError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_tool_choice_required[accounts/fireworks/models/llama4-maverick-instruct-basic-case0]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fd70a60>\nmodel = 'accounts/fireworks/models/llama4-maverick-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],  # Reusing existing case for now\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_tool_choice_required(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n>       response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            tool_choice=\"required\",  # Force tool call\n            stream=False,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:289: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fd70a60>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.0002499590627849102,
+        "duration": 0.00039894692599773407,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_tool_choice_required[accounts/fireworks/models/llama-v3p3-70b-instruct-case0]",
-      "lineno": 282,
-      "outcome": "passed",
+      "lineno": 302,
+      "outcome": "failed",
       "keywords": [
         "test_chat_streaming_tool_choice_required[accounts/fireworks/models/llama-v3p3-70b-instruct-case0]",
         "parametrize",
@@ -1837,21 +3165,59 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.010595374973490834,
+        "duration": 0.07139755226671696,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.7214656670112163,
-        "outcome": "passed"
+        "duration": 0.27306741289794445,
+        "outcome": "failed",
+        "crash": {
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
+        },
+        "traceback": [
+          {
+            "path": "tests/verifications/openai_api/test_chat_completion.py",
+            "lineno": 313,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
+          }
+        ],
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_tool_choice_required[accounts/fireworks/models/llama-v3p3-70b-instruct-case0]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fbc8580>\nmodel = 'accounts/fireworks/models/llama-v3p3-70b-instruct'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],  # Reusing existing case for now\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_tool_choice_required(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n>       stream = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            tool_choice=\"required\",  # Force tool call\n            stream=True,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:313: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fbc8580>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.0006131248082965612,
+        "duration": 0.00032315682619810104,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_tool_choice_required[accounts/fireworks/models/llama4-scout-instruct-basic-case0]",
-      "lineno": 282,
+      "lineno": 302,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_tool_choice_required[accounts/fireworks/models/llama4-scout-instruct-basic-case0]",
@@ -1870,34 +3236,59 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.00959512498229742,
+        "duration": 0.0701784947887063,
         "outcome": "passed"
       },
       "call": {
-        "duration": 5.1717818330507725,
+        "duration": 0.12367013934999704,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 303,
-          "message": "AssertionError: Expected tool call when tool_choice='required'\nassert 0 > 0\n +  where 0 = len([])"
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 303,
-            "message": "AssertionError"
+            "lineno": 313,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_tool_choice_required[accounts/fireworks/models/llama4-scout-instruct-basic-case0]>>\nopenai_client = <openai.OpenAI object at 0x121558b80>\nmodel = 'accounts/fireworks/models/llama4-scout-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],  # Reusing existing case for now\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_tool_choice_required(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        stream = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            tool_choice=\"required\",  # Force tool call\n            stream=True,\n        )\n    \n        _, tool_calls_buffer = _accumulate_streaming_tool_calls(stream)\n    \n>       assert len(tool_calls_buffer) > 0, \"Expected tool call when tool_choice='required'\"\nE       AssertionError: Expected tool call when tool_choice='required'\nE       assert 0 > 0\nE        +  where 0 = len([])\n\ntests/verifications/openai_api/test_chat_completion.py:303: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_tool_choice_required[accounts/fireworks/models/llama4-scout-instruct-basic-case0]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fe0b580>\nmodel = 'accounts/fireworks/models/llama4-scout-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],  # Reusing existing case for now\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_tool_choice_required(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n>       stream = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            tool_choice=\"required\",  # Force tool call\n            stream=True,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:313: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fe0b580>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.00022537494078278542,
+        "duration": 0.0003095511347055435,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_tool_choice_required[accounts/fireworks/models/llama4-maverick-instruct-basic-case0]",
-      "lineno": 282,
+      "lineno": 302,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_tool_choice_required[accounts/fireworks/models/llama4-maverick-instruct-basic-case0]",
@@ -1916,35 +3307,60 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.007616708986461163,
+        "duration": 0.07112481445074081,
         "outcome": "passed"
       },
       "call": {
-        "duration": 2.809985833009705,
+        "duration": 0.11879229731857777,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 303,
-          "message": "AssertionError: Expected tool call when tool_choice='required'\nassert 0 > 0\n +  where 0 = len([])"
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 303,
-            "message": "AssertionError"
+            "lineno": 313,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_tool_choice_required[accounts/fireworks/models/llama4-maverick-instruct-basic-case0]>>\nopenai_client = <openai.OpenAI object at 0x12157b730>\nmodel = 'accounts/fireworks/models/llama4-maverick-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],  # Reusing existing case for now\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_tool_choice_required(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        stream = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            tool_choice=\"required\",  # Force tool call\n            stream=True,\n        )\n    \n        _, tool_calls_buffer = _accumulate_streaming_tool_calls(stream)\n    \n>       assert len(tool_calls_buffer) > 0, \"Expected tool call when tool_choice='required'\"\nE       AssertionError: Expected tool call when tool_choice='required'\nE       assert 0 > 0\nE        +  where 0 = len([])\n\ntests/verifications/openai_api/test_chat_completion.py:303: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_tool_choice_required[accounts/fireworks/models/llama4-maverick-instruct-basic-case0]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fb7b6a0>\nmodel = 'accounts/fireworks/models/llama4-maverick-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],  # Reusing existing case for now\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_tool_choice_required(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n>       stream = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            tool_choice=\"required\",  # Force tool call\n            stream=True,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:313: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fb7b6a0>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.0002737501636147499,
+        "duration": 0.00032928306609392166,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_tool_choice_none[accounts/fireworks/models/llama-v3p3-70b-instruct-case0]",
-      "lineno": 309,
-      "outcome": "passed",
+      "lineno": 329,
+      "outcome": "failed",
       "keywords": [
         "test_chat_non_streaming_tool_choice_none[accounts/fireworks/models/llama-v3p3-70b-instruct-case0]",
         "parametrize",
@@ -1962,22 +3378,60 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.008539875037968159,
+        "duration": 0.0733236288651824,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.4815418750513345,
-        "outcome": "passed"
+        "duration": 0.20418731309473515,
+        "outcome": "failed",
+        "crash": {
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
+        },
+        "traceback": [
+          {
+            "path": "tests/verifications/openai_api/test_chat_completion.py",
+            "lineno": 340,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
+          }
+        ],
+        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_tool_choice_none[accounts/fireworks/models/llama-v3p3-70b-instruct-case0]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fb198d0>\nmodel = 'accounts/fireworks/models/llama-v3p3-70b-instruct'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],  # Reusing existing case for now\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_tool_choice_none(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n>       response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            tool_choice=\"none\",\n            stream=False,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:340: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fb198d0>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.00026479107327759266,
+        "duration": 0.0003160899505019188,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_tool_choice_none[accounts/fireworks/models/llama4-scout-instruct-basic-case0]",
-      "lineno": 309,
-      "outcome": "passed",
+      "lineno": 329,
+      "outcome": "failed",
       "keywords": [
         "test_chat_non_streaming_tool_choice_none[accounts/fireworks/models/llama4-scout-instruct-basic-case0]",
         "parametrize",
@@ -1995,22 +3449,60 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.017829209100455046,
+        "duration": 0.07103190571069717,
         "outcome": "passed"
       },
       "call": {
-        "duration": 3.461141875013709,
-        "outcome": "passed"
+        "duration": 0.13796625938266516,
+        "outcome": "failed",
+        "crash": {
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
+        },
+        "traceback": [
+          {
+            "path": "tests/verifications/openai_api/test_chat_completion.py",
+            "lineno": 340,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
+          }
+        ],
+        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_tool_choice_none[accounts/fireworks/models/llama4-scout-instruct-basic-case0]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fd5afe0>\nmodel = 'accounts/fireworks/models/llama4-scout-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],  # Reusing existing case for now\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_tool_choice_none(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n>       response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            tool_choice=\"none\",\n            stream=False,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:340: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fd5afe0>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.0001559578813612461,
+        "duration": 0.0003080805763602257,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_tool_choice_none[accounts/fireworks/models/llama4-maverick-instruct-basic-case0]",
-      "lineno": 309,
-      "outcome": "passed",
+      "lineno": 329,
+      "outcome": "failed",
       "keywords": [
         "test_chat_non_streaming_tool_choice_none[accounts/fireworks/models/llama4-maverick-instruct-basic-case0]",
         "parametrize",
@@ -2028,22 +3520,60 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.020885124802589417,
+        "duration": 0.07084846775978804,
         "outcome": "passed"
       },
       "call": {
-        "duration": 1.165734917158261,
-        "outcome": "passed"
+        "duration": 0.11544281151145697,
+        "outcome": "failed",
+        "crash": {
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
+        },
+        "traceback": [
+          {
+            "path": "tests/verifications/openai_api/test_chat_completion.py",
+            "lineno": 340,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
+          }
+        ],
+        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_tool_choice_none[accounts/fireworks/models/llama4-maverick-instruct-basic-case0]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fb21d80>\nmodel = 'accounts/fireworks/models/llama4-maverick-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],  # Reusing existing case for now\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_tool_choice_none(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n>       response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            tool_choice=\"none\",\n            stream=False,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:340: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fb21d80>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.0006582499481737614,
+        "duration": 0.00031726714223623276,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_tool_choice_none[accounts/fireworks/models/llama-v3p3-70b-instruct-case0]",
-      "lineno": 332,
-      "outcome": "passed",
+      "lineno": 352,
+      "outcome": "failed",
       "keywords": [
         "test_chat_streaming_tool_choice_none[accounts/fireworks/models/llama-v3p3-70b-instruct-case0]",
         "parametrize",
@@ -2061,22 +3591,60 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.02804262493737042,
+        "duration": 0.07118451129645109,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.8278106248471886,
-        "outcome": "passed"
+        "duration": 0.3085783813148737,
+        "outcome": "failed",
+        "crash": {
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
+        },
+        "traceback": [
+          {
+            "path": "tests/verifications/openai_api/test_chat_completion.py",
+            "lineno": 363,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
+          }
+        ],
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_tool_choice_none[accounts/fireworks/models/llama-v3p3-70b-instruct-case0]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fb01150>\nmodel = 'accounts/fireworks/models/llama-v3p3-70b-instruct'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],  # Reusing existing case for now\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_tool_choice_none(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n>       stream = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            tool_choice=\"none\",\n            stream=True,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:363: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fb01150>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.00017454102635383606,
+        "duration": 0.0003956826403737068,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_tool_choice_none[accounts/fireworks/models/llama4-scout-instruct-basic-case0]",
-      "lineno": 332,
-      "outcome": "passed",
+      "lineno": 352,
+      "outcome": "failed",
       "keywords": [
         "test_chat_streaming_tool_choice_none[accounts/fireworks/models/llama4-scout-instruct-basic-case0]",
         "parametrize",
@@ -2094,22 +3662,60 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.007836499949917197,
+        "duration": 0.07257829792797565,
         "outcome": "passed"
       },
       "call": {
-        "duration": 4.224512833869085,
-        "outcome": "passed"
+        "duration": 0.09841848351061344,
+        "outcome": "failed",
+        "crash": {
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
+        },
+        "traceback": [
+          {
+            "path": "tests/verifications/openai_api/test_chat_completion.py",
+            "lineno": 363,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
+          }
+        ],
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_tool_choice_none[accounts/fireworks/models/llama4-scout-instruct-basic-case0]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fbf5600>\nmodel = 'accounts/fireworks/models/llama4-scout-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],  # Reusing existing case for now\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_tool_choice_none(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n>       stream = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            tool_choice=\"none\",\n            stream=True,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:363: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fbf5600>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.00017945817671716213,
+        "duration": 0.0005597397685050964,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_tool_choice_none[accounts/fireworks/models/llama4-maverick-instruct-basic-case0]",
-      "lineno": 332,
-      "outcome": "passed",
+      "lineno": 352,
+      "outcome": "failed",
       "keywords": [
         "test_chat_streaming_tool_choice_none[accounts/fireworks/models/llama4-maverick-instruct-basic-case0]",
         "parametrize",
@@ -2127,21 +3733,59 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.007193875033408403,
+        "duration": 0.0763206360861659,
         "outcome": "passed"
       },
       "call": {
-        "duration": 1.0631800829432905,
-        "outcome": "passed"
+        "duration": 0.24762020073831081,
+        "outcome": "failed",
+        "crash": {
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
+        },
+        "traceback": [
+          {
+            "path": "tests/verifications/openai_api/test_chat_completion.py",
+            "lineno": 363,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
+          }
+        ],
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_tool_choice_none[accounts/fireworks/models/llama4-maverick-instruct-basic-case0]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fd585b0>\nmodel = 'accounts/fireworks/models/llama4-maverick-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],  # Reusing existing case for now\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_tool_choice_none(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n>       stream = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            tool_choice=\"none\",\n            stream=True,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:363: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fd585b0>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.0007307089399546385,
+        "duration": 0.0003156941384077072,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-text_then_weather_tool]",
-      "lineno": 360,
+      "lineno": 380,
       "outcome": "failed",
       "keywords": [
         "test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-text_then_weather_tool]",
@@ -2160,34 +3804,59 @@
         "case_id": "text_then_weather_tool"
       },
       "setup": {
-        "duration": 0.033505375031381845,
+        "duration": 0.07102795876562595,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.722855375148356,
+        "duration": 0.11488684639334679,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 447,
-          "message": "AssertionError: Expected one of ['sol'] in content, but got: 'I cannot perform this task as it requires additional functionality that is not available in the given functions.'\nassert False\n +  where False = any(<generator object test_chat_non_streaming_multi_turn_tool_calling.<locals>.<genexpr> at 0x121d85620>)"
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 447,
-            "message": "AssertionError"
+            "lineno": 421,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-text_then_weather_tool]>>\nopenai_client = <openai.OpenAI object at 0x121d4abf0>\nmodel = 'accounts/fireworks/models/llama-v3p3-70b-instruct'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'text_then_weather_tool', 'expected': [{'answer': ['sol'], 'num_tool_calls': 0}, {'num_tool_calls': 1, 'to...], 'type': 'object'}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': '70 degrees and foggy'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\"\n        Test cases for multi-turn tool calling.\n        Tool calls are asserted.\n        Tool responses are provided in the test case.\n        Final response is asserted.\n        \"\"\"\n    \n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        # Create a copy of the messages list to avoid modifying the original\n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        # Use deepcopy to prevent modification across runs/parametrization\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        # keep going until either\n        # 1. we have messages to test in multi-turn\n        # 2. no messages but last message is tool response\n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            # do not take new messages if last message is tool response\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                # Ensure new_messages is a list of message objects\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    # If it's a single message object, add it directly\n                    messages.append(new_messages)\n    \n            # --- API Call ---\n            response = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=False,\n            )\n    \n            # --- Process Response ---\n            assistant_message = response.choices[0].message\n            messages.append(assistant_message.model_dump(exclude_unset=True))\n    \n            assert assistant_message.role == \"assistant\"\n    \n            # Get the expected result data\n            expected = expected_results.pop(0)\n            num_tool_calls = expected[\"num_tool_calls\"]\n    \n            # --- Assertions based on expected result ---\n            assert len(assistant_message.tool_calls or []) == num_tool_calls, (\n                f\"Expected {num_tool_calls} tool calls, but got {len(assistant_message.tool_calls or [])}\"\n            )\n    \n            if num_tool_calls > 0:\n                tool_call = assistant_message.tool_calls[0]\n                assert tool_call.function.name == expected[\"tool_name\"], (\n                    f\"Expected tool '{expected['tool_name']}', got '{tool_call.function.name}'\"\n                )\n                # Parse the JSON string arguments before comparing\n                actual_arguments = json.loads(tool_call.function.arguments)\n                assert actual_arguments == expected[\"tool_arguments\"], (\n                    f\"Expected arguments '{expected['tool_arguments']}', got '{actual_arguments}'\"\n                )\n    \n                # Prepare and append the tool response for the next turn\n                tool_response = tool_responses.pop(0)\n                messages.append(\n                    {\n                        \"role\": \"tool\",\n                        \"tool_call_id\": tool_call.id,\n                        \"content\": tool_response[\"response\"],\n                    }\n                )\n            else:\n                assert assistant_message.content is not None, \"Expected content, but none received.\"\n                expected_answers = expected[\"answer\"]  # This is now a list\n                content_lower = assistant_message.content.lower()\n>               assert any(ans.lower() in content_lower for ans in expected_answers), (\n                    f\"Expected one of {expected_answers} in content, but got: '{assistant_message.content}'\"\n                )\nE               AssertionError: Expected one of ['sol'] in content, but got: 'I cannot perform this task as it requires additional functionality that is not available in the given functions.'\nE               assert False\nE                +  where False = any(<generator object test_chat_non_streaming_multi_turn_tool_calling.<locals>.<genexpr> at 0x121d85620>)\n\ntests/verifications/openai_api/test_chat_completion.py:447: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-text_then_weather_tool]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fab8fa0>\nmodel = 'accounts/fireworks/models/llama-v3p3-70b-instruct'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'text_then_weather_tool', 'expected': [{'answer': ['sol'], 'num_tool_calls': 0}, {'num_tool_calls': 1, 'to...], 'type': 'object'}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': '70 degrees and foggy'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\"\n        Test cases for multi-turn tool calling.\n        Tool calls are asserted.\n        Tool responses are provided in the test case.\n        Final response is asserted.\n        \"\"\"\n    \n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        # Create a copy of the messages list to avoid modifying the original\n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        # Use deepcopy to prevent modification across runs/parametrization\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        # keep going until either\n        # 1. we have messages to test in multi-turn\n        # 2. no messages but last message is tool response\n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            # do not take new messages if last message is tool response\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                # Ensure new_messages is a list of message objects\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    # If it's a single message object, add it directly\n                    messages.append(new_messages)\n    \n            # --- API Call ---\n>           response = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=False,\n            )\n\ntests/verifications/openai_api/test_chat_completion.py:421: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fab8fa0>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.001098334090784192,
+        "duration": 0.00033565983176231384,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-weather_tool_then_text]",
-      "lineno": 360,
+      "lineno": 380,
       "outcome": "failed",
       "keywords": [
         "test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-weather_tool_then_text]",
@@ -2206,34 +3875,59 @@
         "case_id": "weather_tool_then_text"
       },
       "setup": {
-        "duration": 0.014729209011420608,
+        "duration": 0.07645629066973925,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.5405448749661446,
+        "duration": 0.11238154675811529,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 419,
-          "message": "AssertionError: Expected 1 tool calls, but got 0\nassert 0 == 1\n +  where 0 = len((None or []))\n +    where None = ChatCompletionMessage(content='{\"type\": \"function\", \"name\": \"get_weather\", \"parameters\": {\"location\": \"San Francisco, CA\"}}', refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=None).tool_calls"
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 419,
-            "message": "AssertionError"
+            "lineno": 421,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-weather_tool_then_text]>>\nopenai_client = <openai.OpenAI object at 0x121140e50>\nmodel = 'accounts/fireworks/models/llama-v3p3-70b-instruct'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'weather_tool_then_text', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'location': 'San Francisco...], 'type': 'object'}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': '70 degrees and foggy'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\"\n        Test cases for multi-turn tool calling.\n        Tool calls are asserted.\n        Tool responses are provided in the test case.\n        Final response is asserted.\n        \"\"\"\n    \n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        # Create a copy of the messages list to avoid modifying the original\n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        # Use deepcopy to prevent modification across runs/parametrization\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        # keep going until either\n        # 1. we have messages to test in multi-turn\n        # 2. no messages but last message is tool response\n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            # do not take new messages if last message is tool response\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                # Ensure new_messages is a list of message objects\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    # If it's a single message object, add it directly\n                    messages.append(new_messages)\n    \n            # --- API Call ---\n            response = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=False,\n            )\n    \n            # --- Process Response ---\n            assistant_message = response.choices[0].message\n            messages.append(assistant_message.model_dump(exclude_unset=True))\n    \n            assert assistant_message.role == \"assistant\"\n    \n            # Get the expected result data\n            expected = expected_results.pop(0)\n            num_tool_calls = expected[\"num_tool_calls\"]\n    \n            # --- Assertions based on expected result ---\n>           assert len(assistant_message.tool_calls or []) == num_tool_calls, (\n                f\"Expected {num_tool_calls} tool calls, but got {len(assistant_message.tool_calls or [])}\"\n            )\nE           AssertionError: Expected 1 tool calls, but got 0\nE           assert 0 == 1\nE            +  where 0 = len((None or []))\nE            +    where None = ChatCompletionMessage(content='{\"type\": \"function\", \"name\": \"get_weather\", \"parameters\": {\"location\": \"San Francisco, CA\"}}', refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=None).tool_calls\n\ntests/verifications/openai_api/test_chat_completion.py:419: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-weather_tool_then_text]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fea93c0>\nmodel = 'accounts/fireworks/models/llama-v3p3-70b-instruct'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'weather_tool_then_text', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'location': 'San Francisco...], 'type': 'object'}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': '70 degrees and foggy'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\"\n        Test cases for multi-turn tool calling.\n        Tool calls are asserted.\n        Tool responses are provided in the test case.\n        Final response is asserted.\n        \"\"\"\n    \n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        # Create a copy of the messages list to avoid modifying the original\n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        # Use deepcopy to prevent modification across runs/parametrization\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        # keep going until either\n        # 1. we have messages to test in multi-turn\n        # 2. no messages but last message is tool response\n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            # do not take new messages if last message is tool response\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                # Ensure new_messages is a list of message objects\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    # If it's a single message object, add it directly\n                    messages.append(new_messages)\n    \n            # --- API Call ---\n>           response = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=False,\n            )\n\ntests/verifications/openai_api/test_chat_completion.py:421: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fea93c0>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.0002915831282734871,
+        "duration": 0.0004070783033967018,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-add_product_tool]",
-      "lineno": 360,
+      "lineno": 380,
       "outcome": "failed",
       "keywords": [
         "test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-add_product_tool]",
@@ -2252,34 +3946,59 @@
         "case_id": "add_product_tool"
       },
       "setup": {
-        "duration": 0.006871750112622976,
+        "duration": 0.07554292771965265,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.8019717501010746,
+        "duration": 0.2664942145347595,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 419,
-          "message": "AssertionError: Expected 1 tool calls, but got 0\nassert 0 == 1\n +  where 0 = len((None or []))\n +    where None = ChatCompletionMessage(content='{\"type\": \"function\", \"name\": \"addProduct\", \"parameters\": {\"name\": \"Widget\", \"price\": \"19.99\", \"inStock\": \"true\", \"tags\": \"[\\\\\"new\\\\\", \\\\\"sale\\\\\"]\"}}', refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=None).tool_calls"
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 419,
-            "message": "AssertionError"
+            "lineno": 421,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-add_product_tool]>>\nopenai_client = <openai.OpenAI object at 0x12126fa00>\nmodel = 'accounts/fireworks/models/llama-v3p3-70b-instruct'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'add_product_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'inStock': True, 'name': 'Widget...}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': 'Successfully added product with id: 123'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\"\n        Test cases for multi-turn tool calling.\n        Tool calls are asserted.\n        Tool responses are provided in the test case.\n        Final response is asserted.\n        \"\"\"\n    \n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        # Create a copy of the messages list to avoid modifying the original\n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        # Use deepcopy to prevent modification across runs/parametrization\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        # keep going until either\n        # 1. we have messages to test in multi-turn\n        # 2. no messages but last message is tool response\n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            # do not take new messages if last message is tool response\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                # Ensure new_messages is a list of message objects\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    # If it's a single message object, add it directly\n                    messages.append(new_messages)\n    \n            # --- API Call ---\n            response = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=False,\n            )\n    \n            # --- Process Response ---\n            assistant_message = response.choices[0].message\n            messages.append(assistant_message.model_dump(exclude_unset=True))\n    \n            assert assistant_message.role == \"assistant\"\n    \n            # Get the expected result data\n            expected = expected_results.pop(0)\n            num_tool_calls = expected[\"num_tool_calls\"]\n    \n            # --- Assertions based on expected result ---\n>           assert len(assistant_message.tool_calls or []) == num_tool_calls, (\n                f\"Expected {num_tool_calls} tool calls, but got {len(assistant_message.tool_calls or [])}\"\n            )\nE           AssertionError: Expected 1 tool calls, but got 0\nE           assert 0 == 1\nE            +  where 0 = len((None or []))\nE            +    where None = ChatCompletionMessage(content='{\"type\": \"function\", \"name\": \"addProduct\", \"parameters\": {\"name\": \"Widget\", \"price\": \"19.99\", \"inStock\": \"true\", \"tags\": \"[\\\\\"new\\\\\", \\\\\"sale\\\\\"]\"}}', refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=None).tool_calls\n\ntests/verifications/openai_api/test_chat_completion.py:419: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-add_product_tool]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fbcb010>\nmodel = 'accounts/fireworks/models/llama-v3p3-70b-instruct'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'add_product_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'inStock': True, 'name': 'Widget...}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': 'Successfully added product with id: 123'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\"\n        Test cases for multi-turn tool calling.\n        Tool calls are asserted.\n        Tool responses are provided in the test case.\n        Final response is asserted.\n        \"\"\"\n    \n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        # Create a copy of the messages list to avoid modifying the original\n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        # Use deepcopy to prevent modification across runs/parametrization\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        # keep going until either\n        # 1. we have messages to test in multi-turn\n        # 2. no messages but last message is tool response\n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            # do not take new messages if last message is tool response\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                # Ensure new_messages is a list of message objects\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    # If it's a single message object, add it directly\n                    messages.append(new_messages)\n    \n            # --- API Call ---\n>           response = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=False,\n            )\n\ntests/verifications/openai_api/test_chat_completion.py:421: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fbcb010>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.0002685000654309988,
+        "duration": 0.00040212273597717285,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-get_then_create_event_tool]",
-      "lineno": 360,
+      "lineno": 380,
       "outcome": "failed",
       "keywords": [
         "test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-get_then_create_event_tool]",
@@ -2298,34 +4017,59 @@
         "case_id": "get_then_create_event_tool"
       },
       "setup": {
-        "duration": 0.008089208975434303,
+        "duration": 0.07388069480657578,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.6005201658699661,
+        "duration": 0.12607386708259583,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 419,
-          "message": "AssertionError: Expected 1 tool calls, but got 0\nassert 0 == 1\n +  where 0 = len((None or []))\n +    where None = ChatCompletionMessage(content='{\"type\": \"function\", \"name\": \"get_event\", \"parameters\": {\"date\": \"2025-03-03\", \"time\": \"10:00\"}}', refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=None).tool_calls"
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 419,
-            "message": "AssertionError"
+            "lineno": 421,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-get_then_create_event_tool]>>\nopenai_client = <openai.OpenAI object at 0x121dcceb0>\nmodel = 'accounts/fireworks/models/llama-v3p3-70b-instruct'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'get_then_create_event_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'date': '2025-03-03', ...ents found for 2025-03-03 at 10:00'}\"}, {'response': \"{'response': 'Successfully created new event with id: e_123'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\"\n        Test cases for multi-turn tool calling.\n        Tool calls are asserted.\n        Tool responses are provided in the test case.\n        Final response is asserted.\n        \"\"\"\n    \n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        # Create a copy of the messages list to avoid modifying the original\n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        # Use deepcopy to prevent modification across runs/parametrization\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        # keep going until either\n        # 1. we have messages to test in multi-turn\n        # 2. no messages but last message is tool response\n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            # do not take new messages if last message is tool response\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                # Ensure new_messages is a list of message objects\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    # If it's a single message object, add it directly\n                    messages.append(new_messages)\n    \n            # --- API Call ---\n            response = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=False,\n            )\n    \n            # --- Process Response ---\n            assistant_message = response.choices[0].message\n            messages.append(assistant_message.model_dump(exclude_unset=True))\n    \n            assert assistant_message.role == \"assistant\"\n    \n            # Get the expected result data\n            expected = expected_results.pop(0)\n            num_tool_calls = expected[\"num_tool_calls\"]\n    \n            # --- Assertions based on expected result ---\n>           assert len(assistant_message.tool_calls or []) == num_tool_calls, (\n                f\"Expected {num_tool_calls} tool calls, but got {len(assistant_message.tool_calls or [])}\"\n            )\nE           AssertionError: Expected 1 tool calls, but got 0\nE           assert 0 == 1\nE            +  where 0 = len((None or []))\nE            +    where None = ChatCompletionMessage(content='{\"type\": \"function\", \"name\": \"get_event\", \"parameters\": {\"date\": \"2025-03-03\", \"time\": \"10:00\"}}', refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=None).tool_calls\n\ntests/verifications/openai_api/test_chat_completion.py:419: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-get_then_create_event_tool]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fd7ed10>\nmodel = 'accounts/fireworks/models/llama-v3p3-70b-instruct'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'get_then_create_event_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'date': '2025-03-03', ...ents found for 2025-03-03 at 10:00'}\"}, {'response': \"{'response': 'Successfully created new event with id: e_123'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\"\n        Test cases for multi-turn tool calling.\n        Tool calls are asserted.\n        Tool responses are provided in the test case.\n        Final response is asserted.\n        \"\"\"\n    \n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        # Create a copy of the messages list to avoid modifying the original\n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        # Use deepcopy to prevent modification across runs/parametrization\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        # keep going until either\n        # 1. we have messages to test in multi-turn\n        # 2. no messages but last message is tool response\n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            # do not take new messages if last message is tool response\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                # Ensure new_messages is a list of message objects\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    # If it's a single message object, add it directly\n                    messages.append(new_messages)\n    \n            # --- API Call ---\n>           response = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=False,\n            )\n\ntests/verifications/openai_api/test_chat_completion.py:421: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fd7ed10>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.00036270800046622753,
+        "duration": 0.0003165826201438904,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-compare_monthly_expense_tool]",
-      "lineno": 360,
+      "lineno": 380,
       "outcome": "failed",
       "keywords": [
         "test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-compare_monthly_expense_tool]",
@@ -2344,34 +4088,59 @@
         "case_id": "compare_monthly_expense_tool"
       },
       "setup": {
-        "duration": 0.007170833880081773,
+        "duration": 0.0708252303302288,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.34380250005051494,
+        "duration": 0.24374851863831282,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 419,
-          "message": "AssertionError: Expected 1 tool calls, but got 0\nassert 0 == 1\n +  where 0 = len((None or []))\n +    where None = ChatCompletionMessage(content='{\"type\": \"function\", \"name\": \"getMonthlyExpenseSummary\", \"parameters\": {\"month\": \"1\", \"year\": \"2025\"}}', refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=None).tool_calls"
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 419,
-            "message": "AssertionError"
+            "lineno": 421,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-compare_monthly_expense_tool]>>\nopenai_client = <openai.OpenAI object at 0x1212fc1f0>\nmodel = 'accounts/fireworks/models/llama-v3p3-70b-instruct'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'compare_monthly_expense_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'month': 1, 'year': ... 'Total expenses for January 2025: $1000'}\"}, {'response': \"{'response': 'Total expenses for February 2024: $2000'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\"\n        Test cases for multi-turn tool calling.\n        Tool calls are asserted.\n        Tool responses are provided in the test case.\n        Final response is asserted.\n        \"\"\"\n    \n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        # Create a copy of the messages list to avoid modifying the original\n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        # Use deepcopy to prevent modification across runs/parametrization\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        # keep going until either\n        # 1. we have messages to test in multi-turn\n        # 2. no messages but last message is tool response\n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            # do not take new messages if last message is tool response\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                # Ensure new_messages is a list of message objects\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    # If it's a single message object, add it directly\n                    messages.append(new_messages)\n    \n            # --- API Call ---\n            response = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=False,\n            )\n    \n            # --- Process Response ---\n            assistant_message = response.choices[0].message\n            messages.append(assistant_message.model_dump(exclude_unset=True))\n    \n            assert assistant_message.role == \"assistant\"\n    \n            # Get the expected result data\n            expected = expected_results.pop(0)\n            num_tool_calls = expected[\"num_tool_calls\"]\n    \n            # --- Assertions based on expected result ---\n>           assert len(assistant_message.tool_calls or []) == num_tool_calls, (\n                f\"Expected {num_tool_calls} tool calls, but got {len(assistant_message.tool_calls or [])}\"\n            )\nE           AssertionError: Expected 1 tool calls, but got 0\nE           assert 0 == 1\nE            +  where 0 = len((None or []))\nE            +    where None = ChatCompletionMessage(content='{\"type\": \"function\", \"name\": \"getMonthlyExpenseSummary\", \"parameters\": {\"month\": \"1\", \"year\": \"2025\"}}', refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=None).tool_calls\n\ntests/verifications/openai_api/test_chat_completion.py:419: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-compare_monthly_expense_tool]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fb798d0>\nmodel = 'accounts/fireworks/models/llama-v3p3-70b-instruct'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'compare_monthly_expense_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'month': 1, 'year': ... 'Total expenses for January 2025: $1000'}\"}, {'response': \"{'response': 'Total expenses for February 2024: $2000'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\"\n        Test cases for multi-turn tool calling.\n        Tool calls are asserted.\n        Tool responses are provided in the test case.\n        Final response is asserted.\n        \"\"\"\n    \n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        # Create a copy of the messages list to avoid modifying the original\n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        # Use deepcopy to prevent modification across runs/parametrization\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        # keep going until either\n        # 1. we have messages to test in multi-turn\n        # 2. no messages but last message is tool response\n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            # do not take new messages if last message is tool response\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                # Ensure new_messages is a list of message objects\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    # If it's a single message object, add it directly\n                    messages.append(new_messages)\n    \n            # --- API Call ---\n>           response = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=False,\n            )\n\ntests/verifications/openai_api/test_chat_completion.py:421: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fb798d0>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.00026466697454452515,
+        "duration": 0.0003087436780333519,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-text_then_weather_tool]",
-      "lineno": 360,
+      "lineno": 380,
       "outcome": "failed",
       "keywords": [
         "test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-text_then_weather_tool]",
@@ -2390,34 +4159,59 @@
         "case_id": "text_then_weather_tool"
       },
       "setup": {
-        "duration": 0.007314041955396533,
+        "duration": 0.07189069222658873,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.8803163750562817,
+        "duration": 0.1129898214712739,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 447,
-          "message": "AssertionError: Expected one of ['sol'] in content, but got: '{\"name\": \"get_weather\", \"parameters\": {\"description\": \"Get the current weather\", \"parameter\": {\"type\": \"object\", \"properties\": {\"location\": {\"description\": \"The city and state (both required). e.g. San Francisco, CA.\", \"type\": \"string\"}}}, \"required\": [\"location\"]}}'\nassert False\n +  where False = any(<generator object test_chat_non_streaming_multi_turn_tool_calling.<locals>.<genexpr> at 0x121ddc890>)"
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 447,
-            "message": "AssertionError"
+            "lineno": 421,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-text_then_weather_tool]>>\nopenai_client = <openai.OpenAI object at 0x121141900>\nmodel = 'accounts/fireworks/models/llama4-scout-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'text_then_weather_tool', 'expected': [{'answer': ['sol'], 'num_tool_calls': 0}, {'num_tool_calls': 1, 'to...], 'type': 'object'}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': '70 degrees and foggy'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\"\n        Test cases for multi-turn tool calling.\n        Tool calls are asserted.\n        Tool responses are provided in the test case.\n        Final response is asserted.\n        \"\"\"\n    \n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        # Create a copy of the messages list to avoid modifying the original\n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        # Use deepcopy to prevent modification across runs/parametrization\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        # keep going until either\n        # 1. we have messages to test in multi-turn\n        # 2. no messages but last message is tool response\n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            # do not take new messages if last message is tool response\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                # Ensure new_messages is a list of message objects\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    # If it's a single message object, add it directly\n                    messages.append(new_messages)\n    \n            # --- API Call ---\n            response = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=False,\n            )\n    \n            # --- Process Response ---\n            assistant_message = response.choices[0].message\n            messages.append(assistant_message.model_dump(exclude_unset=True))\n    \n            assert assistant_message.role == \"assistant\"\n    \n            # Get the expected result data\n            expected = expected_results.pop(0)\n            num_tool_calls = expected[\"num_tool_calls\"]\n    \n            # --- Assertions based on expected result ---\n            assert len(assistant_message.tool_calls or []) == num_tool_calls, (\n                f\"Expected {num_tool_calls} tool calls, but got {len(assistant_message.tool_calls or [])}\"\n            )\n    \n            if num_tool_calls > 0:\n                tool_call = assistant_message.tool_calls[0]\n                assert tool_call.function.name == expected[\"tool_name\"], (\n                    f\"Expected tool '{expected['tool_name']}', got '{tool_call.function.name}'\"\n                )\n                # Parse the JSON string arguments before comparing\n                actual_arguments = json.loads(tool_call.function.arguments)\n                assert actual_arguments == expected[\"tool_arguments\"], (\n                    f\"Expected arguments '{expected['tool_arguments']}', got '{actual_arguments}'\"\n                )\n    \n                # Prepare and append the tool response for the next turn\n                tool_response = tool_responses.pop(0)\n                messages.append(\n                    {\n                        \"role\": \"tool\",\n                        \"tool_call_id\": tool_call.id,\n                        \"content\": tool_response[\"response\"],\n                    }\n                )\n            else:\n                assert assistant_message.content is not None, \"Expected content, but none received.\"\n                expected_answers = expected[\"answer\"]  # This is now a list\n                content_lower = assistant_message.content.lower()\n>               assert any(ans.lower() in content_lower for ans in expected_answers), (\n                    f\"Expected one of {expected_answers} in content, but got: '{assistant_message.content}'\"\n                )\nE               AssertionError: Expected one of ['sol'] in content, but got: '{\"name\": \"get_weather\", \"parameters\": {\"description\": \"Get the current weather\", \"parameter\": {\"type\": \"object\", \"properties\": {\"location\": {\"description\": \"The city and state (both required). e.g. San Francisco, CA.\", \"type\": \"string\"}}}, \"required\": [\"location\"]}}'\nE               assert False\nE                +  where False = any(<generator object test_chat_non_streaming_multi_turn_tool_calling.<locals>.<genexpr> at 0x121ddc890>)\n\ntests/verifications/openai_api/test_chat_completion.py:447: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-text_then_weather_tool]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fb7dd80>\nmodel = 'accounts/fireworks/models/llama4-scout-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'text_then_weather_tool', 'expected': [{'answer': ['sol'], 'num_tool_calls': 0}, {'num_tool_calls': 1, 'to...], 'type': 'object'}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': '70 degrees and foggy'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\"\n        Test cases for multi-turn tool calling.\n        Tool calls are asserted.\n        Tool responses are provided in the test case.\n        Final response is asserted.\n        \"\"\"\n    \n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        # Create a copy of the messages list to avoid modifying the original\n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        # Use deepcopy to prevent modification across runs/parametrization\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        # keep going until either\n        # 1. we have messages to test in multi-turn\n        # 2. no messages but last message is tool response\n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            # do not take new messages if last message is tool response\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                # Ensure new_messages is a list of message objects\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    # If it's a single message object, add it directly\n                    messages.append(new_messages)\n    \n            # --- API Call ---\n>           response = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=False,\n            )\n\ntests/verifications/openai_api/test_chat_completion.py:421: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fb7dd80>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.00023358315229415894,
+        "duration": 0.00041724275797605515,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-weather_tool_then_text]",
-      "lineno": 360,
+      "lineno": 380,
       "outcome": "failed",
       "keywords": [
         "test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-weather_tool_then_text]",
@@ -2436,34 +4230,59 @@
         "case_id": "weather_tool_then_text"
       },
       "setup": {
-        "duration": 0.012344583868980408,
+        "duration": 0.07218896970152855,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.8308421669062227,
+        "duration": 0.2670225091278553,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 419,
-          "message": "AssertionError: Expected 1 tool calls, but got 0\nassert 0 == 1\n +  where 0 = len((None or []))\n +    where None = ChatCompletionMessage(content='{\"name\": \"get_weather\", \"parameters\": {\"description\": \"Get the current weather\", \"parameters\": {\"type\": \"object\", \"properties\": {\"location\": {\"description\": \"The city and state (both required)\", \"type\": \"string\"}}}, \"required\": [\"location\"]}}', refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=None).tool_calls"
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 419,
-            "message": "AssertionError"
+            "lineno": 421,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-weather_tool_then_text]>>\nopenai_client = <openai.OpenAI object at 0x121514a60>\nmodel = 'accounts/fireworks/models/llama4-scout-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'weather_tool_then_text', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'location': 'San Francisco...], 'type': 'object'}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': '70 degrees and foggy'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\"\n        Test cases for multi-turn tool calling.\n        Tool calls are asserted.\n        Tool responses are provided in the test case.\n        Final response is asserted.\n        \"\"\"\n    \n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        # Create a copy of the messages list to avoid modifying the original\n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        # Use deepcopy to prevent modification across runs/parametrization\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        # keep going until either\n        # 1. we have messages to test in multi-turn\n        # 2. no messages but last message is tool response\n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            # do not take new messages if last message is tool response\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                # Ensure new_messages is a list of message objects\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    # If it's a single message object, add it directly\n                    messages.append(new_messages)\n    \n            # --- API Call ---\n            response = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=False,\n            )\n    \n            # --- Process Response ---\n            assistant_message = response.choices[0].message\n            messages.append(assistant_message.model_dump(exclude_unset=True))\n    \n            assert assistant_message.role == \"assistant\"\n    \n            # Get the expected result data\n            expected = expected_results.pop(0)\n            num_tool_calls = expected[\"num_tool_calls\"]\n    \n            # --- Assertions based on expected result ---\n>           assert len(assistant_message.tool_calls or []) == num_tool_calls, (\n                f\"Expected {num_tool_calls} tool calls, but got {len(assistant_message.tool_calls or [])}\"\n            )\nE           AssertionError: Expected 1 tool calls, but got 0\nE           assert 0 == 1\nE            +  where 0 = len((None or []))\nE            +    where None = ChatCompletionMessage(content='{\"name\": \"get_weather\", \"parameters\": {\"description\": \"Get the current weather\", \"parameters\": {\"type\": \"object\", \"properties\": {\"location\": {\"description\": \"The city and state (both required)\", \"type\": \"string\"}}}, \"required\": [\"location\"]}}', refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=None).tool_calls\n\ntests/verifications/openai_api/test_chat_completion.py:419: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-weather_tool_then_text]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fc45e70>\nmodel = 'accounts/fireworks/models/llama4-scout-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'weather_tool_then_text', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'location': 'San Francisco...], 'type': 'object'}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': '70 degrees and foggy'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\"\n        Test cases for multi-turn tool calling.\n        Tool calls are asserted.\n        Tool responses are provided in the test case.\n        Final response is asserted.\n        \"\"\"\n    \n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        # Create a copy of the messages list to avoid modifying the original\n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        # Use deepcopy to prevent modification across runs/parametrization\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        # keep going until either\n        # 1. we have messages to test in multi-turn\n        # 2. no messages but last message is tool response\n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            # do not take new messages if last message is tool response\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                # Ensure new_messages is a list of message objects\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    # If it's a single message object, add it directly\n                    messages.append(new_messages)\n    \n            # --- API Call ---\n>           response = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=False,\n            )\n\ntests/verifications/openai_api/test_chat_completion.py:421: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fc45e70>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.0002704169601202011,
+        "duration": 0.0003341538831591606,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-add_product_tool]",
-      "lineno": 360,
+      "lineno": 380,
       "outcome": "failed",
       "keywords": [
         "test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-add_product_tool]",
@@ -2482,34 +4301,59 @@
         "case_id": "add_product_tool"
       },
       "setup": {
-        "duration": 0.010503917001187801,
+        "duration": 0.07147200033068657,
         "outcome": "passed"
       },
       "call": {
-        "duration": 2.760397708043456,
+        "duration": 0.11082868836820126,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 419,
-          "message": "AssertionError: Expected 1 tool calls, but got 0\nassert 0 == 1\n +  where 0 = len((None or []))\n +    where None = ChatCompletionMessage(content='{\"name\": \"addProduct\", \"parameters\": {\"name\": {\"description\": \"Name of the product\", \"type\": \"string\"}, \"price\": {\"description\": \"Price of the product\", \"type\": \"number\"}, \"inStock\": {\"description\": \"Availability status of the product.\", \"type\": \"boolean\"}, \"tags\": {\"description\": \"List of product tags\", \"type\": \"array\"}}}assistant\\n\\n{\"name\": \"addProduct\", \"parameters\": {\"name\": {\"description\": \"Name of the product\", \"type\": \"string\"}, \"name\": \"Widget\", \"price\": {\"description\": \"Price of the product\", \"type\": \"number\"}, \"price\": 19.99, \"inStock\": {\"description\": \"Availability status of the product.\", \"type\": \"boolean\"}, \"inStock\": true, \"tags\": {\"description\": \"List of product tags\", \"type\": \"array\"}, \"tags\": [\"new\", \"sale\"]}}assistant\\n\\n{\"name\": \"addProduct\", \"parameters\": {\"name\": \"Widget\", \"price\": 19.99, \"inStock\": true, \"tags\": [\"new\", \"sale\"]}}', refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=None).tool_calls"
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 419,
-            "message": "AssertionError"
+            "lineno": 421,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-add_product_tool]>>\nopenai_client = <openai.OpenAI object at 0x121517730>\nmodel = 'accounts/fireworks/models/llama4-scout-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'add_product_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'inStock': True, 'name': 'Widget...}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': 'Successfully added product with id: 123'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\"\n        Test cases for multi-turn tool calling.\n        Tool calls are asserted.\n        Tool responses are provided in the test case.\n        Final response is asserted.\n        \"\"\"\n    \n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        # Create a copy of the messages list to avoid modifying the original\n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        # Use deepcopy to prevent modification across runs/parametrization\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        # keep going until either\n        # 1. we have messages to test in multi-turn\n        # 2. no messages but last message is tool response\n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            # do not take new messages if last message is tool response\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                # Ensure new_messages is a list of message objects\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    # If it's a single message object, add it directly\n                    messages.append(new_messages)\n    \n            # --- API Call ---\n            response = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=False,\n            )\n    \n            # --- Process Response ---\n            assistant_message = response.choices[0].message\n            messages.append(assistant_message.model_dump(exclude_unset=True))\n    \n            assert assistant_message.role == \"assistant\"\n    \n            # Get the expected result data\n            expected = expected_results.pop(0)\n            num_tool_calls = expected[\"num_tool_calls\"]\n    \n            # --- Assertions based on expected result ---\n>           assert len(assistant_message.tool_calls or []) == num_tool_calls, (\n                f\"Expected {num_tool_calls} tool calls, but got {len(assistant_message.tool_calls or [])}\"\n            )\nE           AssertionError: Expected 1 tool calls, but got 0\nE           assert 0 == 1\nE            +  where 0 = len((None or []))\nE            +    where None = ChatCompletionMessage(content='{\"name\": \"addProduct\", \"parameters\": {\"name\": {\"description\": \"Name of the product\", \"type\": \"string\"}, \"price\": {\"description\": \"Price of the product\", \"type\": \"number\"}, \"inStock\": {\"description\": \"Availability status of the product.\", \"type\": \"boolean\"}, \"tags\": {\"description\": \"List of product tags\", \"type\": \"array\"}}}assistant\\n\\n{\"name\": \"addProduct\", \"parameters\": {\"name\": {\"description\": \"Name of the product\", \"type\": \"string\"}, \"name\": \"Widget\", \"price\": {\"description\": \"Price of the product\", \"type\": \"number\"}, \"price\": 19.99, \"inStock\": {\"description\": \"Availability status of the product.\", \"type\": \"boolean\"}, \"inStock\": true, \"tags\": {\"description\": \"List of product tags\", \"type\": \"array\"}, \"tags\": [\"new\", \"sale\"]}}assistant\\n\\n{\"name\": \"addProduct\", \"parameters\": {\"name\": \"Widget\", \"price\": 19.99, \"inStock\": true, \"tags\": [\"new\", \"sale\"]}}', refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=None).tool_calls\n\ntests/verifications/openai_api/test_chat_completion.py:419: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-add_product_tool]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fcdb850>\nmodel = 'accounts/fireworks/models/llama4-scout-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'add_product_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'inStock': True, 'name': 'Widget...}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': 'Successfully added product with id: 123'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\"\n        Test cases for multi-turn tool calling.\n        Tool calls are asserted.\n        Tool responses are provided in the test case.\n        Final response is asserted.\n        \"\"\"\n    \n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        # Create a copy of the messages list to avoid modifying the original\n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        # Use deepcopy to prevent modification across runs/parametrization\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        # keep going until either\n        # 1. we have messages to test in multi-turn\n        # 2. no messages but last message is tool response\n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            # do not take new messages if last message is tool response\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                # Ensure new_messages is a list of message objects\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    # If it's a single message object, add it directly\n                    messages.append(new_messages)\n    \n            # --- API Call ---\n>           response = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=False,\n            )\n\ntests/verifications/openai_api/test_chat_completion.py:421: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fcdb850>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.000388207845389843,
+        "duration": 0.00040625128895044327,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-get_then_create_event_tool]",
-      "lineno": 360,
+      "lineno": 380,
       "outcome": "failed",
       "keywords": [
         "test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-get_then_create_event_tool]",
@@ -2528,34 +4372,59 @@
         "case_id": "get_then_create_event_tool"
       },
       "setup": {
-        "duration": 0.014598833862692118,
+        "duration": 0.07236841041594744,
         "outcome": "passed"
       },
       "call": {
-        "duration": 17.76403620815836,
+        "duration": 0.27738126553595066,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 419,
-          "message": "AssertionError: Expected 1 tool calls, but got 0\nassert 0 == 1\n +  where 0 = len((None or []))\n +    where None = ChatCompletionMessage(content='{\"name\": \"get_event\", \"parameters\": {\"date\": {\"description\": \"Date of the event in ISO format\", \"type\": \"string\"}, \"time\": {\"description\": \"Event Time (HH:MM)\", \"type\": \"string\"}}}assistant\\n\\n{\"name\": \"get_event\", \"parameters\": {\"date\": {\"description\": \"Date of the event in ISO format\", \"type\": \"string\"}, \"time\": {\"description\": \"Event Time (HH:MM)\", \"type\": \"string\"}}}assistant\\n\\n{\"name\": \"get_event\", \"parameters\": {\"date\": {\"description\": \"Date of the event in ISO format\", \"type\": \"string\"}, \"time\": {\"description\": \"Event Time (HH:MM)\", \"type\": \"string\"}}}assistant\\n\\n{\"name\": \"get_event\", \"parameters\": {\"date\": {\"description\": \"Date of the event in ISO format\", \"type\": \"string\"}, \"time\": {\"description\": \"Event Time (HH:MM)\", \"type\": \"string\"}}}assistant\\n\\n{\"name\": \"get_event\", \"parameters\": {\"date\": {\"description\": \"Date of the event in ISO format\", \"type\": \"string\"}, \"time\": {\"description\": \"Event Time (HH:MM)\", \"type\": \"string\"}}}assistant\\n\\n{\"name\": \"get_event\", \"parameters\": {\"date\": {\"description\": \"Date of the event in ISO format\", \"type\": \"string\"}, \"time\": {\"description\": \"Event Time (HH:MM)\", \"type\": \"string\"}}}assistant\\n\\n{\"name\": ...description\": \"Date of the event in ISO format\", \"type\": \"string\"}, \"time\": {\"description\": \"Event Time (HH:MM)\", \"type\": \"string\"}}}assistant\\n\\n{\"name\": \"get_event\", \"parameters\": {\"date\": {\"description\": \"Date of the event in ISO format\", \"type\": \"string\"}, \"time\": {\"description\": \"Event Time (HH:MM)\", \"type\": \"string\"}}}assistant\\n\\n{\"name\": \"get_event\", \"parameters\": {\"date\": {\"description\": \"Date of the event in ISO format\", \"type\": \"string\"}, \"time\": {\"description\": \"Event Time (HH:MM)\", \"type\": \"string\"}}}assistant\\n\\n{\"name\": \"get_event\", \"parameters\": {\"date\": {\"description\": \"Date of the event in ISO format\", \"type\": \"string\"}, \"time\": {\"description\": \"Event Time (HH:MM)\", \"type\": \"string\"}}}assistant\\n\\n{\"name\": \"get_event\", \"parameters\": {\"date\": {\"description\": \"Date of the event in ISO format\", \"type\": \"string\"}, \"time\": {\"description\": \"Event Time (HH:MM)\", \"type\": \"string\"}}}assistant\\n\\n{\"name\": \"get_event\", \"parameters\": {\"date\": {\"description\": \"Date of the event in ISO format\", \"type\": \"string\"}, \"time\": {\"description\": \"Event Time (HH:MM)\", \"type\": \"string\"}}}', refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=None).tool_calls"
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 419,
-            "message": "AssertionError"
+            "lineno": 421,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-get_then_create_event_tool]>>\nopenai_client = <openai.OpenAI object at 0x121d33430>\nmodel = 'accounts/fireworks/models/llama4-scout-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'get_then_create_event_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'date': '2025-03-03', ...ents found for 2025-03-03 at 10:00'}\"}, {'response': \"{'response': 'Successfully created new event with id: e_123'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\"\n        Test cases for multi-turn tool calling.\n        Tool calls are asserted.\n        Tool responses are provided in the test case.\n        Final response is asserted.\n        \"\"\"\n    \n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        # Create a copy of the messages list to avoid modifying the original\n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        # Use deepcopy to prevent modification across runs/parametrization\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        # keep going until either\n        # 1. we have messages to test in multi-turn\n        # 2. no messages but last message is tool response\n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            # do not take new messages if last message is tool response\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                # Ensure new_messages is a list of message objects\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    # If it's a single message object, add it directly\n                    messages.append(new_messages)\n    \n            # --- API Call ---\n            response = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=False,\n            )\n    \n            # --- Process Response ---\n            assistant_message = response.choices[0].message\n            messages.append(assistant_message.model_dump(exclude_unset=True))\n    \n            assert assistant_message.role == \"assistant\"\n    \n            # Get the expected result data\n            expected = expected_results.pop(0)\n            num_tool_calls = expected[\"num_tool_calls\"]\n    \n            # --- Assertions based on expected result ---\n>           assert len(assistant_message.tool_calls or []) == num_tool_calls, (\n                f\"Expected {num_tool_calls} tool calls, but got {len(assistant_message.tool_calls or [])}\"\n            )\nE           AssertionError: Expected 1 tool calls, but got 0\nE           assert 0 == 1\nE            +  where 0 = len((None or []))\nE            +    where None = ChatCompletionMessage(content='{\"name\": \"get_event\", \"parameters\": {\"date\": {\"description\": \"Date of the event in ISO format\", \"type\": \"string\"}, \"time\": {\"description\": \"Event Time (HH:MM)\", \"type\": \"string\"}}}assistant\\n\\n{\"name\": \"get_event\", \"parameters\": {\"date\": {\"description\": \"Date of the event in ISO format\", \"type\": \"string\"}, \"time\": {\"description\": \"Event Time (HH:MM)\", \"type\": \"string\"}}}assistant\\n\\n{\"name\": \"get_event\", \"parameters\": {\"date\": {\"description\": \"Date of the event in ISO format\", \"type\": \"string\"}, \"time\": {\"description\": \"Event Time (HH:MM)\", \"type\": \"string\"}}}assistant\\n\\n{\"name\": \"get_event\", \"parameters\": {\"date\": {\"description\": \"Date of the event in ISO format\", \"type\": \"string\"}, \"time\": {\"description\": \"Event Time (HH:MM)\", \"type\": \"string\"}}}assistant\\n\\n{\"name\": \"get_event\", \"parameters\": {\"date\": {\"description\": \"Date of the event in ISO format\", \"type\": \"string\"}, \"time\": {\"description\": \"Event Time (HH:MM)\", \"type\": \"string\"}}}assistant\\n\\n{\"name\": \"get_event\", \"parameters\": {\"date\": {\"description\": \"Date of the event in ISO format\", \"type\": \"string\"}, \"time\": {\"description\": \"Event Time (HH:MM)\", \"type\": \"string\"}}}assistant\\n\\n{\"name\": ...description\": \"Date of the event in ISO format\", \"type\": \"string\"}, \"time\": {\"description\": \"Event Time (HH:MM)\", \"type\": \"string\"}}}assistant\\n\\n{\"name\": \"get_event\", \"parameters\": {\"date\": {\"description\": \"Date of the event in ISO format\", \"type\": \"string\"}, \"time\": {\"description\": \"Event Time (HH:MM)\", \"type\": \"string\"}}}assistant\\n\\n{\"name\": \"get_event\", \"parameters\": {\"date\": {\"description\": \"Date of the event in ISO format\", \"type\": \"string\"}, \"time\": {\"description\": \"Event Time (HH:MM)\", \"type\": \"string\"}}}assistant\\n\\n{\"name\": \"get_event\", \"parameters\": {\"date\": {\"description\": \"Date of the event in ISO format\", \"type\": \"string\"}, \"time\": {\"description\": \"Event Time (HH:MM)\", \"type\": \"string\"}}}assistant\\n\\n{\"name\": \"get_event\", \"parameters\": {\"date\": {\"description\": \"Date of the event in ISO format\", \"type\": \"string\"}, \"time\": {\"description\": \"Event Time (HH:MM)\", \"type\": \"string\"}}}assistant\\n\\n{\"name\": \"get_event\", \"parameters\": {\"date\": {\"description\": \"Date of the event in ISO format\", \"type\": \"string\"}, \"time\": {\"description\": \"Event Time (HH:MM)\", \"type\": \"string\"}}}', refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=None).tool_calls\n\ntests/verifications/openai_api/test_chat_completion.py:419: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-get_then_create_event_tool]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fdb0f70>\nmodel = 'accounts/fireworks/models/llama4-scout-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'get_then_create_event_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'date': '2025-03-03', ...ents found for 2025-03-03 at 10:00'}\"}, {'response': \"{'response': 'Successfully created new event with id: e_123'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\"\n        Test cases for multi-turn tool calling.\n        Tool calls are asserted.\n        Tool responses are provided in the test case.\n        Final response is asserted.\n        \"\"\"\n    \n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        # Create a copy of the messages list to avoid modifying the original\n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        # Use deepcopy to prevent modification across runs/parametrization\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        # keep going until either\n        # 1. we have messages to test in multi-turn\n        # 2. no messages but last message is tool response\n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            # do not take new messages if last message is tool response\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                # Ensure new_messages is a list of message objects\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    # If it's a single message object, add it directly\n                    messages.append(new_messages)\n    \n            # --- API Call ---\n>           response = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=False,\n            )\n\ntests/verifications/openai_api/test_chat_completion.py:421: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fdb0f70>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.0003917089197784662,
+        "duration": 0.0003846520557999611,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-compare_monthly_expense_tool]",
-      "lineno": 360,
+      "lineno": 380,
       "outcome": "failed",
       "keywords": [
         "test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-compare_monthly_expense_tool]",
@@ -2574,34 +4443,59 @@
         "case_id": "compare_monthly_expense_tool"
       },
       "setup": {
-        "duration": 0.01373741589486599,
+        "duration": 0.06980593129992485,
         "outcome": "passed"
       },
       "call": {
-        "duration": 2.1500849169678986,
+        "duration": 0.12573269568383694,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 419,
-          "message": "AssertionError: Expected 1 tool calls, but got 0\nassert 0 == 1\n +  where 0 = len((None or []))\n +    where None = ChatCompletionMessage(content='{\"name\": \"getMonthlyExpenseSummary\", \"parameters\": {\"type\": \"object\", \"properties\": {\"month\": {\"description\": \"Month of the year (1-12)\", \"type\": \"integer\"}, \"year\": {\"description\": \"Year\", \"type\": \"integer\"}}}}assistant\\n\\n{\"name\": \"getMonthlyExpenseSummary\", \"parameters\": {\"month\": {\"description\": \"Month of the year (1-12)\", \"type\": \"integer\"}, \"year\": {\"description\": \"Year\", \"type\": \"integer\"}}}assistant\\n\\n{\"name\": \"getMonthlyExpenseSummary\", \"parameters\": {\"month\": {\"description\": \"Month of the year (1-12)\", \"type\": \"integer\", \"value\": 1}, \"year\": {\"description\": \"Year\", \"type\": \"integer\", \"value\": 2025}}}', refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=None).tool_calls"
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 419,
-            "message": "AssertionError"
+            "lineno": 421,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-compare_monthly_expense_tool]>>\nopenai_client = <openai.OpenAI object at 0x1212eb220>\nmodel = 'accounts/fireworks/models/llama4-scout-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'compare_monthly_expense_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'month': 1, 'year': ... 'Total expenses for January 2025: $1000'}\"}, {'response': \"{'response': 'Total expenses for February 2024: $2000'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\"\n        Test cases for multi-turn tool calling.\n        Tool calls are asserted.\n        Tool responses are provided in the test case.\n        Final response is asserted.\n        \"\"\"\n    \n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        # Create a copy of the messages list to avoid modifying the original\n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        # Use deepcopy to prevent modification across runs/parametrization\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        # keep going until either\n        # 1. we have messages to test in multi-turn\n        # 2. no messages but last message is tool response\n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            # do not take new messages if last message is tool response\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                # Ensure new_messages is a list of message objects\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    # If it's a single message object, add it directly\n                    messages.append(new_messages)\n    \n            # --- API Call ---\n            response = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=False,\n            )\n    \n            # --- Process Response ---\n            assistant_message = response.choices[0].message\n            messages.append(assistant_message.model_dump(exclude_unset=True))\n    \n            assert assistant_message.role == \"assistant\"\n    \n            # Get the expected result data\n            expected = expected_results.pop(0)\n            num_tool_calls = expected[\"num_tool_calls\"]\n    \n            # --- Assertions based on expected result ---\n>           assert len(assistant_message.tool_calls or []) == num_tool_calls, (\n                f\"Expected {num_tool_calls} tool calls, but got {len(assistant_message.tool_calls or [])}\"\n            )\nE           AssertionError: Expected 1 tool calls, but got 0\nE           assert 0 == 1\nE            +  where 0 = len((None or []))\nE            +    where None = ChatCompletionMessage(content='{\"name\": \"getMonthlyExpenseSummary\", \"parameters\": {\"type\": \"object\", \"properties\": {\"month\": {\"description\": \"Month of the year (1-12)\", \"type\": \"integer\"}, \"year\": {\"description\": \"Year\", \"type\": \"integer\"}}}}assistant\\n\\n{\"name\": \"getMonthlyExpenseSummary\", \"parameters\": {\"month\": {\"description\": \"Month of the year (1-12)\", \"type\": \"integer\"}, \"year\": {\"description\": \"Year\", \"type\": \"integer\"}}}assistant\\n\\n{\"name\": \"getMonthlyExpenseSummary\", \"parameters\": {\"month\": {\"description\": \"Month of the year (1-12)\", \"type\": \"integer\", \"value\": 1}, \"year\": {\"description\": \"Year\", \"type\": \"integer\", \"value\": 2025}}}', refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=None).tool_calls\n\ntests/verifications/openai_api/test_chat_completion.py:419: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-compare_monthly_expense_tool]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fd7e980>\nmodel = 'accounts/fireworks/models/llama4-scout-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'compare_monthly_expense_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'month': 1, 'year': ... 'Total expenses for January 2025: $1000'}\"}, {'response': \"{'response': 'Total expenses for February 2024: $2000'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\"\n        Test cases for multi-turn tool calling.\n        Tool calls are asserted.\n        Tool responses are provided in the test case.\n        Final response is asserted.\n        \"\"\"\n    \n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        # Create a copy of the messages list to avoid modifying the original\n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        # Use deepcopy to prevent modification across runs/parametrization\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        # keep going until either\n        # 1. we have messages to test in multi-turn\n        # 2. no messages but last message is tool response\n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            # do not take new messages if last message is tool response\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                # Ensure new_messages is a list of message objects\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    # If it's a single message object, add it directly\n                    messages.append(new_messages)\n    \n            # --- API Call ---\n>           response = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=False,\n            )\n\ntests/verifications/openai_api/test_chat_completion.py:421: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fd7e980>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.00025054183788597584,
+        "duration": 0.0003903098404407501,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-text_then_weather_tool]",
-      "lineno": 360,
+      "lineno": 380,
       "outcome": "failed",
       "keywords": [
         "test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-text_then_weather_tool]",
@@ -2620,34 +4514,59 @@
         "case_id": "text_then_weather_tool"
       },
       "setup": {
-        "duration": 0.006956875091418624,
+        "duration": 0.07204260025173426,
         "outcome": "passed"
       },
       "call": {
-        "duration": 3.101176916854456,
+        "duration": 0.15989400260150433,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 447,
-          "message": "AssertionError: Expected one of ['sol'] in content, but got: 'Since there's no function provided to directly answer the name of the Sun in Latin, I'll assume a function exists to provide the information. Let's hypothetically consider a function named `get_celestial_body_info` that could be used to fetch such information.\n  \n  The response for the prompt could be in the format requested:\n  \n  ```json\n  {\n    \"name\": \"get_celestial_body_info\",\n    \"parameters\": {\n      \"body\": \"Sun\",\n      \"info\": \"Latin name\"\n    }\n  }\n  ```\n  \n  However, to strictly follow the given format and assuming the function definition matches the structure given in the prompt, the response should be adjusted accordingly. For the sake of providing an answer, let's directly translate the prompt into the required JSON format assuming the function is defined as per the details.\n  \n  If we were to directly fill the given JSON structure with a hypothetical function call to get the Latin name of the Sun, and assuming a function `get_celestial_body_name` exists with a parameter `name_type` (e.g., \"Latin\"), the answer could be adjusted. However, the exact function and its parameters aren't specified, so a hypothetical is used.\n  \n  Let's adjust our response to fit a plausible scenario:\n  \n  ```json\n  {\n    \"name\": \"get_celestial_body_name\",\n    \"parameters\": {\n      \"body\": \"Sun\",\n      \"name_type\": \"Latin\"\n    }\n  }\n  ```'\nassert False\n +  where False = any(<generator object test_chat_non_streaming_multi_turn_tool_calling.<locals>.<genexpr> at 0x121d86c70>)"
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 447,
-            "message": "AssertionError"
+            "lineno": 421,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-text_then_weather_tool]>>\nopenai_client = <openai.OpenAI object at 0x121d3bfd0>\nmodel = 'accounts/fireworks/models/llama4-maverick-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'text_then_weather_tool', 'expected': [{'answer': ['sol'], 'num_tool_calls': 0}, {'num_tool_calls': 1, 'to...], 'type': 'object'}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': '70 degrees and foggy'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\"\n        Test cases for multi-turn tool calling.\n        Tool calls are asserted.\n        Tool responses are provided in the test case.\n        Final response is asserted.\n        \"\"\"\n    \n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        # Create a copy of the messages list to avoid modifying the original\n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        # Use deepcopy to prevent modification across runs/parametrization\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        # keep going until either\n        # 1. we have messages to test in multi-turn\n        # 2. no messages but last message is tool response\n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            # do not take new messages if last message is tool response\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                # Ensure new_messages is a list of message objects\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    # If it's a single message object, add it directly\n                    messages.append(new_messages)\n    \n            # --- API Call ---\n            response = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=False,\n            )\n    \n            # --- Process Response ---\n            assistant_message = response.choices[0].message\n            messages.append(assistant_message.model_dump(exclude_unset=True))\n    \n            assert assistant_message.role == \"assistant\"\n    \n            # Get the expected result data\n            expected = expected_results.pop(0)\n            num_tool_calls = expected[\"num_tool_calls\"]\n    \n            # --- Assertions based on expected result ---\n            assert len(assistant_message.tool_calls or []) == num_tool_calls, (\n                f\"Expected {num_tool_calls} tool calls, but got {len(assistant_message.tool_calls or [])}\"\n            )\n    \n            if num_tool_calls > 0:\n                tool_call = assistant_message.tool_calls[0]\n                assert tool_call.function.name == expected[\"tool_name\"], (\n                    f\"Expected tool '{expected['tool_name']}', got '{tool_call.function.name}'\"\n                )\n                # Parse the JSON string arguments before comparing\n                actual_arguments = json.loads(tool_call.function.arguments)\n                assert actual_arguments == expected[\"tool_arguments\"], (\n                    f\"Expected arguments '{expected['tool_arguments']}', got '{actual_arguments}'\"\n                )\n    \n                # Prepare and append the tool response for the next turn\n                tool_response = tool_responses.pop(0)\n                messages.append(\n                    {\n                        \"role\": \"tool\",\n                        \"tool_call_id\": tool_call.id,\n                        \"content\": tool_response[\"response\"],\n                    }\n                )\n            else:\n                assert assistant_message.content is not None, \"Expected content, but none received.\"\n                expected_answers = expected[\"answer\"]  # This is now a list\n                content_lower = assistant_message.content.lower()\n>               assert any(ans.lower() in content_lower for ans in expected_answers), (\n                    f\"Expected one of {expected_answers} in content, but got: '{assistant_message.content}'\"\n                )\nE               AssertionError: Expected one of ['sol'] in content, but got: 'Since there's no function provided to directly answer the name of the Sun in Latin, I'll assume a function exists to provide the information. Let's hypothetically consider a function named `get_celestial_body_info` that could be used to fetch such information.\nE                 \nE                 The response for the prompt could be in the format requested:\nE                 \nE                 ```json\nE                 {\nE                   \"name\": \"get_celestial_body_info\",\nE                   \"parameters\": {\nE                     \"body\": \"Sun\",\nE                     \"info\": \"Latin name\"\nE                   }\nE                 }\nE                 ```\nE                 \nE                 However, to strictly follow the given format and assuming the function definition matches the structure given in the prompt, the response should be adjusted accordingly. For the sake of providing an answer, let's directly translate the prompt into the required JSON format assuming the function is defined as per the details.\nE                 \nE                 If we were to directly fill the given JSON structure with a hypothetical function call to get the Latin name of the Sun, and assuming a function `get_celestial_body_name` exists with a parameter `name_type` (e.g., \"Latin\"), the answer could be adjusted. However, the exact function and its parameters aren't specified, so a hypothetical is used.\nE                 \nE                 Let's adjust our response to fit a plausible scenario:\nE                 \nE                 ```json\nE                 {\nE                   \"name\": \"get_celestial_body_name\",\nE                   \"parameters\": {\nE                     \"body\": \"Sun\",\nE                     \"name_type\": \"Latin\"\nE                   }\nE                 }\nE                 ```'\nE               assert False\nE                +  where False = any(<generator object test_chat_non_streaming_multi_turn_tool_calling.<locals>.<genexpr> at 0x121d86c70>)\n\ntests/verifications/openai_api/test_chat_completion.py:447: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-text_then_weather_tool]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fdab4f0>\nmodel = 'accounts/fireworks/models/llama4-maverick-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'text_then_weather_tool', 'expected': [{'answer': ['sol'], 'num_tool_calls': 0}, {'num_tool_calls': 1, 'to...], 'type': 'object'}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': '70 degrees and foggy'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\"\n        Test cases for multi-turn tool calling.\n        Tool calls are asserted.\n        Tool responses are provided in the test case.\n        Final response is asserted.\n        \"\"\"\n    \n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        # Create a copy of the messages list to avoid modifying the original\n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        # Use deepcopy to prevent modification across runs/parametrization\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        # keep going until either\n        # 1. we have messages to test in multi-turn\n        # 2. no messages but last message is tool response\n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            # do not take new messages if last message is tool response\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                # Ensure new_messages is a list of message objects\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    # If it's a single message object, add it directly\n                    messages.append(new_messages)\n    \n            # --- API Call ---\n>           response = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=False,\n            )\n\ntests/verifications/openai_api/test_chat_completion.py:421: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fdab4f0>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.0002607081551104784,
+        "duration": 0.00032292958348989487,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-weather_tool_then_text]",
-      "lineno": 360,
+      "lineno": 380,
       "outcome": "failed",
       "keywords": [
         "test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-weather_tool_then_text]",
@@ -2666,34 +4585,59 @@
         "case_id": "weather_tool_then_text"
       },
       "setup": {
-        "duration": 0.008886416908353567,
+        "duration": 0.07113024219870567,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.7743674169760197,
+        "duration": 0.11847934126853943,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 419,
-          "message": "AssertionError: Expected 1 tool calls, but got 0\nassert 0 == 1\n +  where 0 = len((None or []))\n +    where None = ChatCompletionMessage(content='{\"name\": \"get_weather\", \"parameters\": {\"location\": \"San Francisco, CA\"}}', refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=None).tool_calls"
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 419,
-            "message": "AssertionError"
+            "lineno": 421,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-weather_tool_then_text]>>\nopenai_client = <openai.OpenAI object at 0x121d389d0>\nmodel = 'accounts/fireworks/models/llama4-maverick-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'weather_tool_then_text', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'location': 'San Francisco...], 'type': 'object'}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': '70 degrees and foggy'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\"\n        Test cases for multi-turn tool calling.\n        Tool calls are asserted.\n        Tool responses are provided in the test case.\n        Final response is asserted.\n        \"\"\"\n    \n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        # Create a copy of the messages list to avoid modifying the original\n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        # Use deepcopy to prevent modification across runs/parametrization\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        # keep going until either\n        # 1. we have messages to test in multi-turn\n        # 2. no messages but last message is tool response\n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            # do not take new messages if last message is tool response\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                # Ensure new_messages is a list of message objects\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    # If it's a single message object, add it directly\n                    messages.append(new_messages)\n    \n            # --- API Call ---\n            response = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=False,\n            )\n    \n            # --- Process Response ---\n            assistant_message = response.choices[0].message\n            messages.append(assistant_message.model_dump(exclude_unset=True))\n    \n            assert assistant_message.role == \"assistant\"\n    \n            # Get the expected result data\n            expected = expected_results.pop(0)\n            num_tool_calls = expected[\"num_tool_calls\"]\n    \n            # --- Assertions based on expected result ---\n>           assert len(assistant_message.tool_calls or []) == num_tool_calls, (\n                f\"Expected {num_tool_calls} tool calls, but got {len(assistant_message.tool_calls or [])}\"\n            )\nE           AssertionError: Expected 1 tool calls, but got 0\nE           assert 0 == 1\nE            +  where 0 = len((None or []))\nE            +    where None = ChatCompletionMessage(content='{\"name\": \"get_weather\", \"parameters\": {\"location\": \"San Francisco, CA\"}}', refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=None).tool_calls\n\ntests/verifications/openai_api/test_chat_completion.py:419: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-weather_tool_then_text]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fcf4160>\nmodel = 'accounts/fireworks/models/llama4-maverick-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'weather_tool_then_text', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'location': 'San Francisco...], 'type': 'object'}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': '70 degrees and foggy'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\"\n        Test cases for multi-turn tool calling.\n        Tool calls are asserted.\n        Tool responses are provided in the test case.\n        Final response is asserted.\n        \"\"\"\n    \n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        # Create a copy of the messages list to avoid modifying the original\n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        # Use deepcopy to prevent modification across runs/parametrization\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        # keep going until either\n        # 1. we have messages to test in multi-turn\n        # 2. no messages but last message is tool response\n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            # do not take new messages if last message is tool response\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                # Ensure new_messages is a list of message objects\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    # If it's a single message object, add it directly\n                    messages.append(new_messages)\n    \n            # --- API Call ---\n>           response = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=False,\n            )\n\ntests/verifications/openai_api/test_chat_completion.py:421: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fcf4160>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.00027175014838576317,
+        "duration": 0.0004066070541739464,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-add_product_tool]",
-      "lineno": 360,
+      "lineno": 380,
       "outcome": "failed",
       "keywords": [
         "test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-add_product_tool]",
@@ -2712,34 +4656,59 @@
         "case_id": "add_product_tool"
       },
       "setup": {
-        "duration": 0.011746292002499104,
+        "duration": 0.07287267316132784,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.9007023749873042,
+        "duration": 0.2623152956366539,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 419,
-          "message": "AssertionError: Expected 1 tool calls, but got 0\nassert 0 == 1\n +  where 0 = len((None or []))\n +    where None = ChatCompletionMessage(content='{\"name\": \"addProduct\", \"parameters\": {\"name\": \"Widget\", \"price\": 19.99, \"inStock\": true, \"tags\": [\"new\", \"sale\"]}}', refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=None).tool_calls"
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 419,
-            "message": "AssertionError"
+            "lineno": 421,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-add_product_tool]>>\nopenai_client = <openai.OpenAI object at 0x12126fe80>\nmodel = 'accounts/fireworks/models/llama4-maverick-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'add_product_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'inStock': True, 'name': 'Widget...}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': 'Successfully added product with id: 123'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\"\n        Test cases for multi-turn tool calling.\n        Tool calls are asserted.\n        Tool responses are provided in the test case.\n        Final response is asserted.\n        \"\"\"\n    \n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        # Create a copy of the messages list to avoid modifying the original\n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        # Use deepcopy to prevent modification across runs/parametrization\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        # keep going until either\n        # 1. we have messages to test in multi-turn\n        # 2. no messages but last message is tool response\n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            # do not take new messages if last message is tool response\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                # Ensure new_messages is a list of message objects\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    # If it's a single message object, add it directly\n                    messages.append(new_messages)\n    \n            # --- API Call ---\n            response = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=False,\n            )\n    \n            # --- Process Response ---\n            assistant_message = response.choices[0].message\n            messages.append(assistant_message.model_dump(exclude_unset=True))\n    \n            assert assistant_message.role == \"assistant\"\n    \n            # Get the expected result data\n            expected = expected_results.pop(0)\n            num_tool_calls = expected[\"num_tool_calls\"]\n    \n            # --- Assertions based on expected result ---\n>           assert len(assistant_message.tool_calls or []) == num_tool_calls, (\n                f\"Expected {num_tool_calls} tool calls, but got {len(assistant_message.tool_calls or [])}\"\n            )\nE           AssertionError: Expected 1 tool calls, but got 0\nE           assert 0 == 1\nE            +  where 0 = len((None or []))\nE            +    where None = ChatCompletionMessage(content='{\"name\": \"addProduct\", \"parameters\": {\"name\": \"Widget\", \"price\": 19.99, \"inStock\": true, \"tags\": [\"new\", \"sale\"]}}', refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=None).tool_calls\n\ntests/verifications/openai_api/test_chat_completion.py:419: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-add_product_tool]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fb973d0>\nmodel = 'accounts/fireworks/models/llama4-maverick-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'add_product_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'inStock': True, 'name': 'Widget...}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': 'Successfully added product with id: 123'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\"\n        Test cases for multi-turn tool calling.\n        Tool calls are asserted.\n        Tool responses are provided in the test case.\n        Final response is asserted.\n        \"\"\"\n    \n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        # Create a copy of the messages list to avoid modifying the original\n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        # Use deepcopy to prevent modification across runs/parametrization\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        # keep going until either\n        # 1. we have messages to test in multi-turn\n        # 2. no messages but last message is tool response\n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            # do not take new messages if last message is tool response\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                # Ensure new_messages is a list of message objects\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    # If it's a single message object, add it directly\n                    messages.append(new_messages)\n    \n            # --- API Call ---\n>           response = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=False,\n            )\n\ntests/verifications/openai_api/test_chat_completion.py:421: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fb973d0>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.0002447080332785845,
+        "duration": 0.00032747630029916763,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-get_then_create_event_tool]",
-      "lineno": 360,
+      "lineno": 380,
       "outcome": "failed",
       "keywords": [
         "test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-get_then_create_event_tool]",
@@ -2758,34 +4727,59 @@
         "case_id": "get_then_create_event_tool"
       },
       "setup": {
-        "duration": 0.007389291888102889,
+        "duration": 0.0714963860809803,
         "outcome": "passed"
       },
       "call": {
-        "duration": 4.593799042049795,
+        "duration": 0.1075747637078166,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 419,
-          "message": "AssertionError: Expected 1 tool calls, but got 0\nassert 0 == 1\n +  where 0 = len((None or []))\n +    where None = ChatCompletionMessage(content='{\"type\": \"function\", \"name\": \"get_event\", \"parameters\": {\"date\": \"2025-03-03\", \"time\": \"10:00\"}}assistant\\n\\nimport json\\n\\n# Define the functions\\ndef create_event(name, date, time, location, participants):\\n    return f\"Event \\'{name}\\' created on {date} at {time} in {location} with participants: {\\', \\'.join(participants)}\"\\n\\ndef get_event(date, time):\\n    # This is a mock function. In a real application, this would query a database or calendar API.\\n    events = {\\n        \"2025-03-03\": {\\n            \"10:00\": \"Meeting with John\",\\n            \"14:00\": \"Team meeting\"\\n        }\\n    }\\n    if date in events and time in events[date]:\\n        return f\"Yes, you have an event: {events[date][time]}\"\\n    else:\\n        return \"No, you don\\'t have any events at this time.\"\\n\\n# Load the function definitions from the given prompt\\nfunctions = json.loads(\"[\" + \"\"\"{\"type\": \"function\", \"name\": \"create_event\", \"parameters\": {\"name\": \"New Year\\'s Party\", \"date\": \"2025-01-01\", \"time\": \"20:00\", \"location\": \"Downtown\", \"participants\": [\"Alice\", \"Bob\"]}}\"\"\" + \",\" + \"\"\"{\"type\": \"function\", \"name\": \"get_event\", \"parameters\": {\"date\": \"2025-03-03\", \"time\": \"10:00\"}}\"\"\" + \"]\")\\n\\n# Execute the functions\\nfor function in functions:\\n    if function[\"type\"] == \"function\":\\n        func_name = function[\"name\"]\\n        params = function[\"parameters\"]\\n        if func_name == \"create_event\":\\n            print(create_event(**params))\\n        elif func_name == \"get_event\":\\n            print(get_event(**params))[{\\'type\\': \\'function\\', \\'name\\': \\'create_event\\', \\'parameters\\': {\\'name\\': \\'New Year\\\\\\'s Party\\', \\'date\\': \\'2025-01-01\\', \\'time\\': \\'20:00\\', \\'location\\': \\'Downtown\\', \\'participants\\': [\\'Alice\\', \\'Bob\\']}}}, {\\'type\\': \\'function\\', \\'name\\': \\'get_event\\', \\'parameters\\': {\\'date\\': \\'2025-03-03\\', \\'time\\': \\'10:00\\'}}]assistant\\n\\nYes, you have an event: Meeting with John.', refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=None).tool_calls"
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 419,
-            "message": "AssertionError"
+            "lineno": 421,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-get_then_create_event_tool]>>\nopenai_client = <openai.OpenAI object at 0x1212fe9e0>\nmodel = 'accounts/fireworks/models/llama4-maverick-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'get_then_create_event_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'date': '2025-03-03', ...ents found for 2025-03-03 at 10:00'}\"}, {'response': \"{'response': 'Successfully created new event with id: e_123'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\"\n        Test cases for multi-turn tool calling.\n        Tool calls are asserted.\n        Tool responses are provided in the test case.\n        Final response is asserted.\n        \"\"\"\n    \n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        # Create a copy of the messages list to avoid modifying the original\n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        # Use deepcopy to prevent modification across runs/parametrization\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        # keep going until either\n        # 1. we have messages to test in multi-turn\n        # 2. no messages but last message is tool response\n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            # do not take new messages if last message is tool response\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                # Ensure new_messages is a list of message objects\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    # If it's a single message object, add it directly\n                    messages.append(new_messages)\n    \n            # --- API Call ---\n            response = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=False,\n            )\n    \n            # --- Process Response ---\n            assistant_message = response.choices[0].message\n            messages.append(assistant_message.model_dump(exclude_unset=True))\n    \n            assert assistant_message.role == \"assistant\"\n    \n            # Get the expected result data\n            expected = expected_results.pop(0)\n            num_tool_calls = expected[\"num_tool_calls\"]\n    \n            # --- Assertions based on expected result ---\n>           assert len(assistant_message.tool_calls or []) == num_tool_calls, (\n                f\"Expected {num_tool_calls} tool calls, but got {len(assistant_message.tool_calls or [])}\"\n            )\nE           AssertionError: Expected 1 tool calls, but got 0\nE           assert 0 == 1\nE            +  where 0 = len((None or []))\nE            +    where None = ChatCompletionMessage(content='{\"type\": \"function\", \"name\": \"get_event\", \"parameters\": {\"date\": \"2025-03-03\", \"time\": \"10:00\"}}assistant\\n\\nimport json\\n\\n# Define the functions\\ndef create_event(name, date, time, location, participants):\\n    return f\"Event \\'{name}\\' created on {date} at {time} in {location} with participants: {\\', \\'.join(participants)}\"\\n\\ndef get_event(date, time):\\n    # This is a mock function. In a real application, this would query a database or calendar API.\\n    events = {\\n        \"2025-03-03\": {\\n            \"10:00\": \"Meeting with John\",\\n            \"14:00\": \"Team meeting\"\\n        }\\n    }\\n    if date in events and time in events[date]:\\n        return f\"Yes, you have an event: {events[date][time]}\"\\n    else:\\n        return \"No, you don\\'t have any events at this time.\"\\n\\n# Load the function definitions from the given prompt\\nfunctions = json.loads(\"[\" + \"\"\"{\"type\": \"function\", \"name\": \"create_event\", \"parameters\": {\"name\": \"New Year\\'s Party\", \"date\": \"2025-01-01\", \"time\": \"20:00\", \"location\": \"Downtown\", \"participants\": [\"Alice\", \"Bob\"]}}\"\"\" + \",\" + \"\"\"{\"type\": \"function\", \"name\": \"get_event\", \"parameters\": {\"date\": \"2025-03-03\", \"time\": \"10:00\"}}\"\"\" + \"]\")\\n\\n# Execute the functions\\nfor function in functions:\\n    if function[\"type\"] == \"function\":\\n        func_name = function[\"name\"]\\n        params = function[\"parameters\"]\\n        if func_name == \"create_event\":\\n            print(create_event(**params))\\n        elif func_name == \"get_event\":\\n            print(get_event(**params))[{\\'type\\': \\'function\\', \\'name\\': \\'create_event\\', \\'parameters\\': {\\'name\\': \\'New Year\\\\\\'s Party\\', \\'date\\': \\'2025-01-01\\', \\'time\\': \\'20:00\\', \\'location\\': \\'Downtown\\', \\'participants\\': [\\'Alice\\', \\'Bob\\']}}}, {\\'type\\': \\'function\\', \\'name\\': \\'get_event\\', \\'parameters\\': {\\'date\\': \\'2025-03-03\\', \\'time\\': \\'10:00\\'}}]assistant\\n\\nYes, you have an event: Meeting with John.', refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=None).tool_calls\n\ntests/verifications/openai_api/test_chat_completion.py:419: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-get_then_create_event_tool]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fbd2620>\nmodel = 'accounts/fireworks/models/llama4-maverick-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'get_then_create_event_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'date': '2025-03-03', ...ents found for 2025-03-03 at 10:00'}\"}, {'response': \"{'response': 'Successfully created new event with id: e_123'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\"\n        Test cases for multi-turn tool calling.\n        Tool calls are asserted.\n        Tool responses are provided in the test case.\n        Final response is asserted.\n        \"\"\"\n    \n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        # Create a copy of the messages list to avoid modifying the original\n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        # Use deepcopy to prevent modification across runs/parametrization\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        # keep going until either\n        # 1. we have messages to test in multi-turn\n        # 2. no messages but last message is tool response\n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            # do not take new messages if last message is tool response\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                # Ensure new_messages is a list of message objects\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    # If it's a single message object, add it directly\n                    messages.append(new_messages)\n    \n            # --- API Call ---\n>           response = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=False,\n            )\n\ntests/verifications/openai_api/test_chat_completion.py:421: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fbd2620>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.00027425005100667477,
+        "duration": 0.0003954702988266945,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-compare_monthly_expense_tool]",
-      "lineno": 360,
+      "lineno": 380,
       "outcome": "failed",
       "keywords": [
         "test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-compare_monthly_expense_tool]",
@@ -2804,34 +4798,59 @@
         "case_id": "compare_monthly_expense_tool"
       },
       "setup": {
-        "duration": 0.02276737499050796,
+        "duration": 0.07068679295480251,
         "outcome": "passed"
       },
       "call": {
-        "duration": 18.476525041041896,
+        "duration": 0.12899171095341444,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 419,
-          "message": "AssertionError: Expected 1 tool calls, but got 0\nassert 0 == 1\n +  where 0 = len((None or []))\n +    where None = ChatCompletionMessage(content='{\"name\": \"getMonthlyExpenseSummary\", \"parameters\": {\"month\": 1, \"year\": 2024}} \" \" \" \" \"\" \" \" \" \"\"\" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \"... \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \"', refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=None).tool_calls"
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 419,
-            "message": "AssertionError"
+            "lineno": 421,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-compare_monthly_expense_tool]>>\nopenai_client = <openai.OpenAI object at 0x121541db0>\nmodel = 'accounts/fireworks/models/llama4-maverick-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'compare_monthly_expense_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'month': 1, 'year': ... 'Total expenses for January 2025: $1000'}\"}, {'response': \"{'response': 'Total expenses for February 2024: $2000'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\"\n        Test cases for multi-turn tool calling.\n        Tool calls are asserted.\n        Tool responses are provided in the test case.\n        Final response is asserted.\n        \"\"\"\n    \n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        # Create a copy of the messages list to avoid modifying the original\n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        # Use deepcopy to prevent modification across runs/parametrization\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        # keep going until either\n        # 1. we have messages to test in multi-turn\n        # 2. no messages but last message is tool response\n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            # do not take new messages if last message is tool response\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                # Ensure new_messages is a list of message objects\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    # If it's a single message object, add it directly\n                    messages.append(new_messages)\n    \n            # --- API Call ---\n            response = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=False,\n            )\n    \n            # --- Process Response ---\n            assistant_message = response.choices[0].message\n            messages.append(assistant_message.model_dump(exclude_unset=True))\n    \n            assert assistant_message.role == \"assistant\"\n    \n            # Get the expected result data\n            expected = expected_results.pop(0)\n            num_tool_calls = expected[\"num_tool_calls\"]\n    \n            # --- Assertions based on expected result ---\n>           assert len(assistant_message.tool_calls or []) == num_tool_calls, (\n                f\"Expected {num_tool_calls} tool calls, but got {len(assistant_message.tool_calls or [])}\"\n            )\nE           AssertionError: Expected 1 tool calls, but got 0\nE           assert 0 == 1\nE            +  where 0 = len((None or []))\nE            +    where None = ChatCompletionMessage(content='{\"name\": \"getMonthlyExpenseSummary\", \"parameters\": {\"month\": 1, \"year\": 2024}} \" \" \" \" \"\" \" \" \" \"\"\" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \"... \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \" \"', refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=None).tool_calls\n\ntests/verifications/openai_api/test_chat_completion.py:419: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-compare_monthly_expense_tool]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fc09570>\nmodel = 'accounts/fireworks/models/llama4-maverick-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'compare_monthly_expense_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'month': 1, 'year': ... 'Total expenses for January 2025: $1000'}\"}, {'response': \"{'response': 'Total expenses for February 2024: $2000'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\"\n        Test cases for multi-turn tool calling.\n        Tool calls are asserted.\n        Tool responses are provided in the test case.\n        Final response is asserted.\n        \"\"\"\n    \n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        # Create a copy of the messages list to avoid modifying the original\n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        # Use deepcopy to prevent modification across runs/parametrization\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        # keep going until either\n        # 1. we have messages to test in multi-turn\n        # 2. no messages but last message is tool response\n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            # do not take new messages if last message is tool response\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                # Ensure new_messages is a list of message objects\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    # If it's a single message object, add it directly\n                    messages.append(new_messages)\n    \n            # --- API Call ---\n>           response = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=False,\n            )\n\ntests/verifications/openai_api/test_chat_completion.py:421: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fc09570>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.00042933295480906963,
+        "duration": 0.00031181517988443375,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-text_then_weather_tool]",
-      "lineno": 451,
+      "lineno": 471,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-text_then_weather_tool]",
@@ -2850,34 +4869,59 @@
         "case_id": "text_then_weather_tool"
       },
       "setup": {
-        "duration": 0.00958816590718925,
+        "duration": 0.06948941852897406,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.7410690418910235,
+        "duration": 0.1193860862404108,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 530,
-          "message": "AssertionError: Expected one of ['sol'] in content, but got: 'I am not able to execute this task as it exceeds the limitations of the functions I have been given.'\nassert False\n +  where False = any(<generator object test_chat_streaming_multi_turn_tool_calling.<locals>.<genexpr> at 0x121df6c00>)"
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 530,
-            "message": "AssertionError"
+            "lineno": 498,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-text_then_weather_tool]>>\nopenai_client = <openai.OpenAI object at 0x121578430>\nmodel = 'accounts/fireworks/models/llama-v3p3-70b-instruct'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'text_then_weather_tool', 'expected': [{'answer': ['sol'], 'num_tool_calls': 0}, {'num_tool_calls': 1, 'to...], 'type': 'object'}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': '70 degrees and foggy'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n            stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n    \n            # --- Process Stream ---\n            accumulated_content, accumulated_tool_calls = _accumulate_streaming_tool_calls(stream)\n    \n            # --- Construct Assistant Message for History ---\n            assistant_message_dict = {\"role\": \"assistant\"}\n            if accumulated_content:\n                assistant_message_dict[\"content\"] = accumulated_content\n            if accumulated_tool_calls:\n                assistant_message_dict[\"tool_calls\"] = accumulated_tool_calls\n    \n            messages.append(assistant_message_dict)\n    \n            # --- Assertions ---\n            expected = expected_results.pop(0)\n            num_tool_calls = expected[\"num_tool_calls\"]\n    \n            assert len(accumulated_tool_calls or []) == num_tool_calls, (\n                f\"Expected {num_tool_calls} tool calls, but got {len(accumulated_tool_calls or [])}\"\n            )\n    \n            if num_tool_calls > 0:\n                # Use the first accumulated tool call for assertion\n                tool_call = accumulated_tool_calls[0]\n                assert tool_call[\"function\"][\"name\"] == expected[\"tool_name\"], (\n                    f\"Expected tool '{expected['tool_name']}', got '{tool_call['function']['name']}'\"\n                )\n                # Parse the accumulated arguments string for comparison\n                actual_arguments = json.loads(tool_call[\"function\"][\"arguments\"])\n                assert actual_arguments == expected[\"tool_arguments\"], (\n                    f\"Expected arguments '{expected['tool_arguments']}', got '{actual_arguments}'\"\n                )\n    \n                # Prepare and append the tool response for the next turn\n                tool_response = tool_responses.pop(0)\n                messages.append(\n                    {\n                        \"role\": \"tool\",\n                        \"tool_call_id\": tool_call[\"id\"],\n                        \"content\": tool_response[\"response\"],\n                    }\n                )\n            else:\n                assert accumulated_content is not None and accumulated_content != \"\", \"Expected content, but none received.\"\n                expected_answers = expected[\"answer\"]\n                content_lower = accumulated_content.lower()\n>               assert any(ans.lower() in content_lower for ans in expected_answers), (\n                    f\"Expected one of {expected_answers} in content, but got: '{accumulated_content}'\"\n                )\nE               AssertionError: Expected one of ['sol'] in content, but got: 'I am not able to execute this task as it exceeds the limitations of the functions I have been given.'\nE               assert False\nE                +  where False = any(<generator object test_chat_streaming_multi_turn_tool_calling.<locals>.<genexpr> at 0x121df6c00>)\n\ntests/verifications/openai_api/test_chat_completion.py:530: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-text_then_weather_tool]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fc06560>\nmodel = 'accounts/fireworks/models/llama-v3p3-70b-instruct'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'text_then_weather_tool', 'expected': [{'answer': ['sol'], 'num_tool_calls': 0}, {'num_tool_calls': 1, 'to...], 'type': 'object'}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': '70 degrees and foggy'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n>           stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n\ntests/verifications/openai_api/test_chat_completion.py:498: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fc06560>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.0002305000089108944,
+        "duration": 0.0004093386232852936,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-weather_tool_then_text]",
-      "lineno": 451,
+      "lineno": 471,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-weather_tool_then_text]",
@@ -2896,34 +4940,59 @@
         "case_id": "weather_tool_then_text"
       },
       "setup": {
-        "duration": 0.008747542044147849,
+        "duration": 0.07101139053702354,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.7824950830545276,
+        "duration": 0.1606877325102687,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 501,
-          "message": "AssertionError: Expected 1 tool calls, but got 0\nassert 0 == 1\n +  where 0 = len(([] or []))"
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 501,
-            "message": "AssertionError"
+            "lineno": 498,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-weather_tool_then_text]>>\nopenai_client = <openai.OpenAI object at 0x127a5f880>\nmodel = 'accounts/fireworks/models/llama-v3p3-70b-instruct'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'weather_tool_then_text', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'location': 'San Francisco...], 'type': 'object'}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': '70 degrees and foggy'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n            stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n    \n            # --- Process Stream ---\n            accumulated_content, accumulated_tool_calls = _accumulate_streaming_tool_calls(stream)\n    \n            # --- Construct Assistant Message for History ---\n            assistant_message_dict = {\"role\": \"assistant\"}\n            if accumulated_content:\n                assistant_message_dict[\"content\"] = accumulated_content\n            if accumulated_tool_calls:\n                assistant_message_dict[\"tool_calls\"] = accumulated_tool_calls\n    \n            messages.append(assistant_message_dict)\n    \n            # --- Assertions ---\n            expected = expected_results.pop(0)\n            num_tool_calls = expected[\"num_tool_calls\"]\n    \n>           assert len(accumulated_tool_calls or []) == num_tool_calls, (\n                f\"Expected {num_tool_calls} tool calls, but got {len(accumulated_tool_calls or [])}\"\n            )\nE           AssertionError: Expected 1 tool calls, but got 0\nE           assert 0 == 1\nE            +  where 0 = len(([] or []))\n\ntests/verifications/openai_api/test_chat_completion.py:501: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-weather_tool_then_text]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fe09630>\nmodel = 'accounts/fireworks/models/llama-v3p3-70b-instruct'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'weather_tool_then_text', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'location': 'San Francisco...], 'type': 'object'}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': '70 degrees and foggy'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n>           stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n\ntests/verifications/openai_api/test_chat_completion.py:498: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fe09630>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.00025100004859268665,
+        "duration": 0.00041847582906484604,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-add_product_tool]",
-      "lineno": 451,
+      "lineno": 471,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-add_product_tool]",
@@ -2942,34 +5011,59 @@
         "case_id": "add_product_tool"
       },
       "setup": {
-        "duration": 0.01297900010831654,
+        "duration": 0.07783220708370209,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.5051176671404392,
+        "duration": 0.11765131819993258,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 501,
-          "message": "AssertionError: Expected 1 tool calls, but got 0\nassert 0 == 1\n +  where 0 = len(([] or []))"
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 501,
-            "message": "AssertionError"
+            "lineno": 498,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-add_product_tool]>>\nopenai_client = <openai.OpenAI object at 0x12155b4f0>\nmodel = 'accounts/fireworks/models/llama-v3p3-70b-instruct'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'add_product_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'inStock': True, 'name': 'Widget...}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': 'Successfully added product with id: 123'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n            stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n    \n            # --- Process Stream ---\n            accumulated_content, accumulated_tool_calls = _accumulate_streaming_tool_calls(stream)\n    \n            # --- Construct Assistant Message for History ---\n            assistant_message_dict = {\"role\": \"assistant\"}\n            if accumulated_content:\n                assistant_message_dict[\"content\"] = accumulated_content\n            if accumulated_tool_calls:\n                assistant_message_dict[\"tool_calls\"] = accumulated_tool_calls\n    \n            messages.append(assistant_message_dict)\n    \n            # --- Assertions ---\n            expected = expected_results.pop(0)\n            num_tool_calls = expected[\"num_tool_calls\"]\n    \n>           assert len(accumulated_tool_calls or []) == num_tool_calls, (\n                f\"Expected {num_tool_calls} tool calls, but got {len(accumulated_tool_calls or [])}\"\n            )\nE           AssertionError: Expected 1 tool calls, but got 0\nE           assert 0 == 1\nE            +  where 0 = len(([] or []))\n\ntests/verifications/openai_api/test_chat_completion.py:501: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-add_product_tool]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fe19f00>\nmodel = 'accounts/fireworks/models/llama-v3p3-70b-instruct'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'add_product_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'inStock': True, 'name': 'Widget...}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': 'Successfully added product with id: 123'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n>           stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n\ntests/verifications/openai_api/test_chat_completion.py:498: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fe19f00>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.00025749998167157173,
+        "duration": 0.0004519466310739517,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-get_then_create_event_tool]",
-      "lineno": 451,
+      "lineno": 471,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-get_then_create_event_tool]",
@@ -2988,34 +5082,59 @@
         "case_id": "get_then_create_event_tool"
       },
       "setup": {
-        "duration": 0.007148250006139278,
+        "duration": 0.07041152473539114,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.6131707499735057,
+        "duration": 0.13473773282021284,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 501,
-          "message": "AssertionError: Expected 1 tool calls, but got 0\nassert 0 == 1\n +  where 0 = len(([] or []))"
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 501,
-            "message": "AssertionError"
+            "lineno": 498,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-get_then_create_event_tool]>>\nopenai_client = <openai.OpenAI object at 0x127a1aad0>\nmodel = 'accounts/fireworks/models/llama-v3p3-70b-instruct'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'get_then_create_event_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'date': '2025-03-03', ...ents found for 2025-03-03 at 10:00'}\"}, {'response': \"{'response': 'Successfully created new event with id: e_123'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n            stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n    \n            # --- Process Stream ---\n            accumulated_content, accumulated_tool_calls = _accumulate_streaming_tool_calls(stream)\n    \n            # --- Construct Assistant Message for History ---\n            assistant_message_dict = {\"role\": \"assistant\"}\n            if accumulated_content:\n                assistant_message_dict[\"content\"] = accumulated_content\n            if accumulated_tool_calls:\n                assistant_message_dict[\"tool_calls\"] = accumulated_tool_calls\n    \n            messages.append(assistant_message_dict)\n    \n            # --- Assertions ---\n            expected = expected_results.pop(0)\n            num_tool_calls = expected[\"num_tool_calls\"]\n    \n>           assert len(accumulated_tool_calls or []) == num_tool_calls, (\n                f\"Expected {num_tool_calls} tool calls, but got {len(accumulated_tool_calls or [])}\"\n            )\nE           AssertionError: Expected 1 tool calls, but got 0\nE           assert 0 == 1\nE            +  where 0 = len(([] or []))\n\ntests/verifications/openai_api/test_chat_completion.py:501: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-get_then_create_event_tool]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fa59b40>\nmodel = 'accounts/fireworks/models/llama-v3p3-70b-instruct'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'get_then_create_event_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'date': '2025-03-03', ...ents found for 2025-03-03 at 10:00'}\"}, {'response': \"{'response': 'Successfully created new event with id: e_123'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n>           stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n\ntests/verifications/openai_api/test_chat_completion.py:498: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fa59b40>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.0002789171412587166,
+        "duration": 0.00039084814488887787,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-compare_monthly_expense_tool]",
-      "lineno": 451,
+      "lineno": 471,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-compare_monthly_expense_tool]",
@@ -3034,34 +5153,59 @@
         "case_id": "compare_monthly_expense_tool"
       },
       "setup": {
-        "duration": 0.007116375025361776,
+        "duration": 0.07150810118764639,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.6857830828521401,
+        "duration": 0.2046368457376957,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 501,
-          "message": "AssertionError: Expected 1 tool calls, but got 0\nassert 0 == 1\n +  where 0 = len(([] or []))"
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 501,
-            "message": "AssertionError"
+            "lineno": 498,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-compare_monthly_expense_tool]>>\nopenai_client = <openai.OpenAI object at 0x121dcd0c0>\nmodel = 'accounts/fireworks/models/llama-v3p3-70b-instruct'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'compare_monthly_expense_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'month': 1, 'year': ... 'Total expenses for January 2025: $1000'}\"}, {'response': \"{'response': 'Total expenses for February 2024: $2000'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n            stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n    \n            # --- Process Stream ---\n            accumulated_content, accumulated_tool_calls = _accumulate_streaming_tool_calls(stream)\n    \n            # --- Construct Assistant Message for History ---\n            assistant_message_dict = {\"role\": \"assistant\"}\n            if accumulated_content:\n                assistant_message_dict[\"content\"] = accumulated_content\n            if accumulated_tool_calls:\n                assistant_message_dict[\"tool_calls\"] = accumulated_tool_calls\n    \n            messages.append(assistant_message_dict)\n    \n            # --- Assertions ---\n            expected = expected_results.pop(0)\n            num_tool_calls = expected[\"num_tool_calls\"]\n    \n>           assert len(accumulated_tool_calls or []) == num_tool_calls, (\n                f\"Expected {num_tool_calls} tool calls, but got {len(accumulated_tool_calls or [])}\"\n            )\nE           AssertionError: Expected 1 tool calls, but got 0\nE           assert 0 == 1\nE            +  where 0 = len(([] or []))\n\ntests/verifications/openai_api/test_chat_completion.py:501: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama-v3p3-70b-instruct-compare_monthly_expense_tool]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fed82b0>\nmodel = 'accounts/fireworks/models/llama-v3p3-70b-instruct'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'compare_monthly_expense_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'month': 1, 'year': ... 'Total expenses for January 2025: $1000'}\"}, {'response': \"{'response': 'Total expenses for February 2024: $2000'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n>           stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n\ntests/verifications/openai_api/test_chat_completion.py:498: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fed82b0>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.000278000021353364,
+        "duration": 0.0003378065302968025,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-text_then_weather_tool]",
-      "lineno": 451,
+      "lineno": 471,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-text_then_weather_tool]",
@@ -3080,34 +5224,59 @@
         "case_id": "text_then_weather_tool"
       },
       "setup": {
-        "duration": 0.011740291956812143,
+        "duration": 0.07012568973004818,
         "outcome": "passed"
       },
       "call": {
-        "duration": 2.4472044170834124,
+        "duration": 0.12623131182044744,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 530,
-          "message": "AssertionError: Expected one of ['sol'] in content, but got: '{\"name\": \"get_weather\", \"parameters\": {\"description\": \"Get the current weather\", \"type\": \"object\", \"properties\": {\"location\": {\"description\": \"The city and state (both required) (e.g. San Francisco, CA.\", \"type\": \"string\"}}}}\n  \n  However, based on the provided function definitions in JSON it seems like the function is designed to get weather. It seems to not align with your prompt which seems to suggest you want information about the Sun.\n  \n  So I re-evaluate and decide that I should look for a hypothetical or align function (that I believe probably exists:)\n  \n  Most probable proper response{\n  \"name\": \"query_latin_name\",\n  \"parameters\": {\n  \"object\": \"Sun\"\n  }\n  } \n  However, function definitions and names you provided are:\n  \n   I have reached end of parsing available data \n  Function not present make next best educated guess\n  \n  {\"name\": \"get_weather\", \"parameters\": {\"location\": {\"description\": \"The city and state (both required) (e.g. San Francisco, CA.\", \"type\": \"string\", \"value\": \"Sun\"}}}'\nassert False\n +  where False = any(<generator object test_chat_streaming_multi_turn_tool_calling.<locals>.<genexpr> at 0x121d84b30>)"
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 530,
-            "message": "AssertionError"
+            "lineno": 498,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-text_then_weather_tool]>>\nopenai_client = <openai.OpenAI object at 0x120fbf340>\nmodel = 'accounts/fireworks/models/llama4-scout-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'text_then_weather_tool', 'expected': [{'answer': ['sol'], 'num_tool_calls': 0}, {'num_tool_calls': 1, 'to...], 'type': 'object'}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': '70 degrees and foggy'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n            stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n    \n            # --- Process Stream ---\n            accumulated_content, accumulated_tool_calls = _accumulate_streaming_tool_calls(stream)\n    \n            # --- Construct Assistant Message for History ---\n            assistant_message_dict = {\"role\": \"assistant\"}\n            if accumulated_content:\n                assistant_message_dict[\"content\"] = accumulated_content\n            if accumulated_tool_calls:\n                assistant_message_dict[\"tool_calls\"] = accumulated_tool_calls\n    \n            messages.append(assistant_message_dict)\n    \n            # --- Assertions ---\n            expected = expected_results.pop(0)\n            num_tool_calls = expected[\"num_tool_calls\"]\n    \n            assert len(accumulated_tool_calls or []) == num_tool_calls, (\n                f\"Expected {num_tool_calls} tool calls, but got {len(accumulated_tool_calls or [])}\"\n            )\n    \n            if num_tool_calls > 0:\n                # Use the first accumulated tool call for assertion\n                tool_call = accumulated_tool_calls[0]\n                assert tool_call[\"function\"][\"name\"] == expected[\"tool_name\"], (\n                    f\"Expected tool '{expected['tool_name']}', got '{tool_call['function']['name']}'\"\n                )\n                # Parse the accumulated arguments string for comparison\n                actual_arguments = json.loads(tool_call[\"function\"][\"arguments\"])\n                assert actual_arguments == expected[\"tool_arguments\"], (\n                    f\"Expected arguments '{expected['tool_arguments']}', got '{actual_arguments}'\"\n                )\n    \n                # Prepare and append the tool response for the next turn\n                tool_response = tool_responses.pop(0)\n                messages.append(\n                    {\n                        \"role\": \"tool\",\n                        \"tool_call_id\": tool_call[\"id\"],\n                        \"content\": tool_response[\"response\"],\n                    }\n                )\n            else:\n                assert accumulated_content is not None and accumulated_content != \"\", \"Expected content, but none received.\"\n                expected_answers = expected[\"answer\"]\n                content_lower = accumulated_content.lower()\n>               assert any(ans.lower() in content_lower for ans in expected_answers), (\n                    f\"Expected one of {expected_answers} in content, but got: '{accumulated_content}'\"\n                )\nE               AssertionError: Expected one of ['sol'] in content, but got: '{\"name\": \"get_weather\", \"parameters\": {\"description\": \"Get the current weather\", \"type\": \"object\", \"properties\": {\"location\": {\"description\": \"The city and state (both required) (e.g. San Francisco, CA.\", \"type\": \"string\"}}}}\nE                 \nE                 However, based on the provided function definitions in JSON it seems like the function is designed to get weather. It seems to not align with your prompt which seems to suggest you want information about the Sun.\nE                 \nE                 So I re-evaluate and decide that I should look for a hypothetical or align function (that I believe probably exists:)\nE                 \nE                 Most probable proper response{\nE                 \"name\": \"query_latin_name\",\nE                 \"parameters\": {\nE                 \"object\": \"Sun\"\nE                 }\nE                 } \nE                 However, function definitions and names you provided are:\nE                 \nE                  I have reached end of parsing available data \nE                 Function not present make next best educated guess\nE                 \nE                 {\"name\": \"get_weather\", \"parameters\": {\"location\": {\"description\": \"The city and state (both required) (e.g. San Francisco, CA.\", \"type\": \"string\", \"value\": \"Sun\"}}}'\nE               assert False\nE                +  where False = any(<generator object test_chat_streaming_multi_turn_tool_calling.<locals>.<genexpr> at 0x121d84b30>)\n\ntests/verifications/openai_api/test_chat_completion.py:530: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-text_then_weather_tool]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fc1abf0>\nmodel = 'accounts/fireworks/models/llama4-scout-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'text_then_weather_tool', 'expected': [{'answer': ['sol'], 'num_tool_calls': 0}, {'num_tool_calls': 1, 'to...], 'type': 'object'}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': '70 degrees and foggy'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n>           stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n\ntests/verifications/openai_api/test_chat_completion.py:498: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fc1abf0>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.0002887500450015068,
+        "duration": 0.00034175068140029907,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-weather_tool_then_text]",
-      "lineno": 451,
+      "lineno": 471,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-weather_tool_then_text]",
@@ -3126,34 +5295,59 @@
         "case_id": "weather_tool_then_text"
       },
       "setup": {
-        "duration": 0.007779333041980863,
+        "duration": 0.07349637430161238,
         "outcome": "passed"
       },
       "call": {
-        "duration": 1.4661752090323716,
+        "duration": 0.11243469640612602,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 501,
-          "message": "AssertionError: Expected 1 tool calls, but got 0\nassert 0 == 1\n +  where 0 = len(([] or []))"
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 501,
-            "message": "AssertionError"
+            "lineno": 498,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-weather_tool_then_text]>>\nopenai_client = <openai.OpenAI object at 0x1212fcbb0>\nmodel = 'accounts/fireworks/models/llama4-scout-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'weather_tool_then_text', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'location': 'San Francisco...], 'type': 'object'}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': '70 degrees and foggy'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n            stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n    \n            # --- Process Stream ---\n            accumulated_content, accumulated_tool_calls = _accumulate_streaming_tool_calls(stream)\n    \n            # --- Construct Assistant Message for History ---\n            assistant_message_dict = {\"role\": \"assistant\"}\n            if accumulated_content:\n                assistant_message_dict[\"content\"] = accumulated_content\n            if accumulated_tool_calls:\n                assistant_message_dict[\"tool_calls\"] = accumulated_tool_calls\n    \n            messages.append(assistant_message_dict)\n    \n            # --- Assertions ---\n            expected = expected_results.pop(0)\n            num_tool_calls = expected[\"num_tool_calls\"]\n    \n>           assert len(accumulated_tool_calls or []) == num_tool_calls, (\n                f\"Expected {num_tool_calls} tool calls, but got {len(accumulated_tool_calls or [])}\"\n            )\nE           AssertionError: Expected 1 tool calls, but got 0\nE           assert 0 == 1\nE            +  where 0 = len(([] or []))\n\ntests/verifications/openai_api/test_chat_completion.py:501: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-weather_tool_then_text]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fbc3ac0>\nmodel = 'accounts/fireworks/models/llama4-scout-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'weather_tool_then_text', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'location': 'San Francisco...], 'type': 'object'}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': '70 degrees and foggy'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n>           stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n\ntests/verifications/openai_api/test_chat_completion.py:498: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fbc3ac0>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.0003039159346371889,
+        "duration": 0.0003092559054493904,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-add_product_tool]",
-      "lineno": 451,
+      "lineno": 471,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-add_product_tool]",
@@ -3172,34 +5366,59 @@
         "case_id": "add_product_tool"
       },
       "setup": {
-        "duration": 0.007942582946270704,
+        "duration": 0.07129209581762552,
         "outcome": "passed"
       },
       "call": {
-        "duration": 1.9714854168705642,
+        "duration": 0.13334522116929293,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 501,
-          "message": "AssertionError: Expected 1 tool calls, but got 0\nassert 0 == 1\n +  where 0 = len(([] or []))"
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 501,
-            "message": "AssertionError"
+            "lineno": 498,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-add_product_tool]>>\nopenai_client = <openai.OpenAI object at 0x12155a1a0>\nmodel = 'accounts/fireworks/models/llama4-scout-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'add_product_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'inStock': True, 'name': 'Widget...}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': 'Successfully added product with id: 123'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n            stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n    \n            # --- Process Stream ---\n            accumulated_content, accumulated_tool_calls = _accumulate_streaming_tool_calls(stream)\n    \n            # --- Construct Assistant Message for History ---\n            assistant_message_dict = {\"role\": \"assistant\"}\n            if accumulated_content:\n                assistant_message_dict[\"content\"] = accumulated_content\n            if accumulated_tool_calls:\n                assistant_message_dict[\"tool_calls\"] = accumulated_tool_calls\n    \n            messages.append(assistant_message_dict)\n    \n            # --- Assertions ---\n            expected = expected_results.pop(0)\n            num_tool_calls = expected[\"num_tool_calls\"]\n    \n>           assert len(accumulated_tool_calls or []) == num_tool_calls, (\n                f\"Expected {num_tool_calls} tool calls, but got {len(accumulated_tool_calls or [])}\"\n            )\nE           AssertionError: Expected 1 tool calls, but got 0\nE           assert 0 == 1\nE            +  where 0 = len(([] or []))\n\ntests/verifications/openai_api/test_chat_completion.py:501: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-add_product_tool]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fab85b0>\nmodel = 'accounts/fireworks/models/llama4-scout-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'add_product_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'inStock': True, 'name': 'Widget...}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': 'Successfully added product with id: 123'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n>           stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n\ntests/verifications/openai_api/test_chat_completion.py:498: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fab85b0>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.00024158298037946224,
+        "duration": 0.0004090704023838043,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-get_then_create_event_tool]",
-      "lineno": 451,
+      "lineno": 471,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-get_then_create_event_tool]",
@@ -3218,34 +5437,59 @@
         "case_id": "get_then_create_event_tool"
       },
       "setup": {
-        "duration": 0.007213916862383485,
+        "duration": 0.07043681107461452,
         "outcome": "passed"
       },
       "call": {
-        "duration": 17.57335195899941,
+        "duration": 0.10430899448692799,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 501,
-          "message": "AssertionError: Expected 1 tool calls, but got 0\nassert 0 == 1\n +  where 0 = len(([] or []))"
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 501,
-            "message": "AssertionError"
+            "lineno": 498,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-get_then_create_event_tool]>>\nopenai_client = <openai.OpenAI object at 0x121d32a70>\nmodel = 'accounts/fireworks/models/llama4-scout-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'get_then_create_event_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'date': '2025-03-03', ...ents found for 2025-03-03 at 10:00'}\"}, {'response': \"{'response': 'Successfully created new event with id: e_123'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n            stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n    \n            # --- Process Stream ---\n            accumulated_content, accumulated_tool_calls = _accumulate_streaming_tool_calls(stream)\n    \n            # --- Construct Assistant Message for History ---\n            assistant_message_dict = {\"role\": \"assistant\"}\n            if accumulated_content:\n                assistant_message_dict[\"content\"] = accumulated_content\n            if accumulated_tool_calls:\n                assistant_message_dict[\"tool_calls\"] = accumulated_tool_calls\n    \n            messages.append(assistant_message_dict)\n    \n            # --- Assertions ---\n            expected = expected_results.pop(0)\n            num_tool_calls = expected[\"num_tool_calls\"]\n    \n>           assert len(accumulated_tool_calls or []) == num_tool_calls, (\n                f\"Expected {num_tool_calls} tool calls, but got {len(accumulated_tool_calls or [])}\"\n            )\nE           AssertionError: Expected 1 tool calls, but got 0\nE           assert 0 == 1\nE            +  where 0 = len(([] or []))\n\ntests/verifications/openai_api/test_chat_completion.py:501: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-get_then_create_event_tool]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fdb30a0>\nmodel = 'accounts/fireworks/models/llama4-scout-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'get_then_create_event_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'date': '2025-03-03', ...ents found for 2025-03-03 at 10:00'}\"}, {'response': \"{'response': 'Successfully created new event with id: e_123'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n>           stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n\ntests/verifications/openai_api/test_chat_completion.py:498: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fdb30a0>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.00033066701143980026,
+        "duration": 0.0003421120345592499,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-compare_monthly_expense_tool]",
-      "lineno": 451,
+      "lineno": 471,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-compare_monthly_expense_tool]",
@@ -3264,34 +5508,59 @@
         "case_id": "compare_monthly_expense_tool"
       },
       "setup": {
-        "duration": 0.008934499928727746,
+        "duration": 0.0733558852225542,
         "outcome": "passed"
       },
       "call": {
-        "duration": 3.2668798330705613,
+        "duration": 0.10938013903796673,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 501,
-          "message": "AssertionError: Expected 1 tool calls, but got 0\nassert 0 == 1\n +  where 0 = len(([] or []))"
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 501,
-            "message": "AssertionError"
+            "lineno": 498,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-compare_monthly_expense_tool]>>\nopenai_client = <openai.OpenAI object at 0x127a5dc00>\nmodel = 'accounts/fireworks/models/llama4-scout-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'compare_monthly_expense_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'month': 1, 'year': ... 'Total expenses for January 2025: $1000'}\"}, {'response': \"{'response': 'Total expenses for February 2024: $2000'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n            stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n    \n            # --- Process Stream ---\n            accumulated_content, accumulated_tool_calls = _accumulate_streaming_tool_calls(stream)\n    \n            # --- Construct Assistant Message for History ---\n            assistant_message_dict = {\"role\": \"assistant\"}\n            if accumulated_content:\n                assistant_message_dict[\"content\"] = accumulated_content\n            if accumulated_tool_calls:\n                assistant_message_dict[\"tool_calls\"] = accumulated_tool_calls\n    \n            messages.append(assistant_message_dict)\n    \n            # --- Assertions ---\n            expected = expected_results.pop(0)\n            num_tool_calls = expected[\"num_tool_calls\"]\n    \n>           assert len(accumulated_tool_calls or []) == num_tool_calls, (\n                f\"Expected {num_tool_calls} tool calls, but got {len(accumulated_tool_calls or [])}\"\n            )\nE           AssertionError: Expected 1 tool calls, but got 0\nE           assert 0 == 1\nE            +  where 0 = len(([] or []))\n\ntests/verifications/openai_api/test_chat_completion.py:501: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-scout-instruct-basic-compare_monthly_expense_tool]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fd708e0>\nmodel = 'accounts/fireworks/models/llama4-scout-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'compare_monthly_expense_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'month': 1, 'year': ... 'Total expenses for January 2025: $1000'}\"}, {'response': \"{'response': 'Total expenses for February 2024: $2000'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n>           stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n\ntests/verifications/openai_api/test_chat_completion.py:498: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fd708e0>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.00029624998569488525,
+        "duration": 0.00038493238389492035,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-text_then_weather_tool]",
-      "lineno": 451,
+      "lineno": 471,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-text_then_weather_tool]",
@@ -3310,34 +5579,59 @@
         "case_id": "text_then_weather_tool"
       },
       "setup": {
-        "duration": 0.007810707902535796,
+        "duration": 0.07225227076560259,
         "outcome": "passed"
       },
       "call": {
-        "duration": 2.599484374979511,
+        "duration": 0.11426256597042084,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 530,
-          "message": "AssertionError: Expected one of ['sol'] in content, but got: 'Since there is no function related to the name of the Sun in Latin, we should look at the given functions to see if any of them can be used. The provided function is \"get_weather\" which requires a \"location\". This function is not related to the prompt.\n  \n  However, a JSON response in the required format for a hypothetical function \"get_latin_name\" or \"get_celestial_body_info\" could be:\n  \n  {\"name\": \"get_celestial_body_info\", \"parameters\": {\"body\": \"Sun\", \"info\": \"latin_name\"}}\n  \n  or \n  \n  {\"name\": \"get_latin_name\", \"parameters\": {\"celestial_body\": \"Sun\"}}\n  \n  But since the actual function definitions are not given and only \"get_weather\" is provided, we can't directly apply them to the given prompt. If we had a function like \"get_latin_name\", the correct response would be in the required format.\n  \n  Let's assume we have a function \"get_celestial_body_info\". \n  \n  The response will be: \n  {\"name\": \"get_celestial_body_info\", \"parameters\": {\"body\": \"Sun\", \"info\": \"latin_name\"}}'\nassert False\n +  where False = any(<generator object test_chat_streaming_multi_turn_tool_calling.<locals>.<genexpr> at 0x127a412a0>)"
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 530,
-            "message": "AssertionError"
+            "lineno": 498,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-text_then_weather_tool]>>\nopenai_client = <openai.OpenAI object at 0x12126f580>\nmodel = 'accounts/fireworks/models/llama4-maverick-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'text_then_weather_tool', 'expected': [{'answer': ['sol'], 'num_tool_calls': 0}, {'num_tool_calls': 1, 'to...], 'type': 'object'}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': '70 degrees and foggy'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n            stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n    \n            # --- Process Stream ---\n            accumulated_content, accumulated_tool_calls = _accumulate_streaming_tool_calls(stream)\n    \n            # --- Construct Assistant Message for History ---\n            assistant_message_dict = {\"role\": \"assistant\"}\n            if accumulated_content:\n                assistant_message_dict[\"content\"] = accumulated_content\n            if accumulated_tool_calls:\n                assistant_message_dict[\"tool_calls\"] = accumulated_tool_calls\n    \n            messages.append(assistant_message_dict)\n    \n            # --- Assertions ---\n            expected = expected_results.pop(0)\n            num_tool_calls = expected[\"num_tool_calls\"]\n    \n            assert len(accumulated_tool_calls or []) == num_tool_calls, (\n                f\"Expected {num_tool_calls} tool calls, but got {len(accumulated_tool_calls or [])}\"\n            )\n    \n            if num_tool_calls > 0:\n                # Use the first accumulated tool call for assertion\n                tool_call = accumulated_tool_calls[0]\n                assert tool_call[\"function\"][\"name\"] == expected[\"tool_name\"], (\n                    f\"Expected tool '{expected['tool_name']}', got '{tool_call['function']['name']}'\"\n                )\n                # Parse the accumulated arguments string for comparison\n                actual_arguments = json.loads(tool_call[\"function\"][\"arguments\"])\n                assert actual_arguments == expected[\"tool_arguments\"], (\n                    f\"Expected arguments '{expected['tool_arguments']}', got '{actual_arguments}'\"\n                )\n    \n                # Prepare and append the tool response for the next turn\n                tool_response = tool_responses.pop(0)\n                messages.append(\n                    {\n                        \"role\": \"tool\",\n                        \"tool_call_id\": tool_call[\"id\"],\n                        \"content\": tool_response[\"response\"],\n                    }\n                )\n            else:\n                assert accumulated_content is not None and accumulated_content != \"\", \"Expected content, but none received.\"\n                expected_answers = expected[\"answer\"]\n                content_lower = accumulated_content.lower()\n>               assert any(ans.lower() in content_lower for ans in expected_answers), (\n                    f\"Expected one of {expected_answers} in content, but got: '{accumulated_content}'\"\n                )\nE               AssertionError: Expected one of ['sol'] in content, but got: 'Since there is no function related to the name of the Sun in Latin, we should look at the given functions to see if any of them can be used. The provided function is \"get_weather\" which requires a \"location\". This function is not related to the prompt.\nE                 \nE                 However, a JSON response in the required format for a hypothetical function \"get_latin_name\" or \"get_celestial_body_info\" could be:\nE                 \nE                 {\"name\": \"get_celestial_body_info\", \"parameters\": {\"body\": \"Sun\", \"info\": \"latin_name\"}}\nE                 \nE                 or \nE                 \nE                 {\"name\": \"get_latin_name\", \"parameters\": {\"celestial_body\": \"Sun\"}}\nE                 \nE                 But since the actual function definitions are not given and only \"get_weather\" is provided, we can't directly apply them to the given prompt. If we had a function like \"get_latin_name\", the correct response would be in the required format.\nE                 \nE                 Let's assume we have a function \"get_celestial_body_info\". \nE                 \nE                 The response will be: \nE                 {\"name\": \"get_celestial_body_info\", \"parameters\": {\"body\": \"Sun\", \"info\": \"latin_name\"}}'\nE               assert False\nE                +  where False = any(<generator object test_chat_streaming_multi_turn_tool_calling.<locals>.<genexpr> at 0x127a412a0>)\n\ntests/verifications/openai_api/test_chat_completion.py:530: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-text_then_weather_tool]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fb2ebc0>\nmodel = 'accounts/fireworks/models/llama4-maverick-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'text_then_weather_tool', 'expected': [{'answer': ['sol'], 'num_tool_calls': 0}, {'num_tool_calls': 1, 'to...], 'type': 'object'}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': '70 degrees and foggy'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n>           stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n\ntests/verifications/openai_api/test_chat_completion.py:498: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fb2ebc0>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.00026241689920425415,
+        "duration": 0.0003271028399467468,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-weather_tool_then_text]",
-      "lineno": 451,
+      "lineno": 471,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-weather_tool_then_text]",
@@ -3356,34 +5650,59 @@
         "case_id": "weather_tool_then_text"
       },
       "setup": {
-        "duration": 0.01244854205287993,
+        "duration": 0.07055194210261106,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.9839951249305159,
+        "duration": 0.1077765729278326,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 501,
-          "message": "AssertionError: Expected 1 tool calls, but got 0\nassert 0 == 1\n +  where 0 = len(([] or []))"
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 501,
-            "message": "AssertionError"
+            "lineno": 498,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-weather_tool_then_text]>>\nopenai_client = <openai.OpenAI object at 0x121542620>\nmodel = 'accounts/fireworks/models/llama4-maverick-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'weather_tool_then_text', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'location': 'San Francisco...], 'type': 'object'}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': '70 degrees and foggy'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n            stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n    \n            # --- Process Stream ---\n            accumulated_content, accumulated_tool_calls = _accumulate_streaming_tool_calls(stream)\n    \n            # --- Construct Assistant Message for History ---\n            assistant_message_dict = {\"role\": \"assistant\"}\n            if accumulated_content:\n                assistant_message_dict[\"content\"] = accumulated_content\n            if accumulated_tool_calls:\n                assistant_message_dict[\"tool_calls\"] = accumulated_tool_calls\n    \n            messages.append(assistant_message_dict)\n    \n            # --- Assertions ---\n            expected = expected_results.pop(0)\n            num_tool_calls = expected[\"num_tool_calls\"]\n    \n>           assert len(accumulated_tool_calls or []) == num_tool_calls, (\n                f\"Expected {num_tool_calls} tool calls, but got {len(accumulated_tool_calls or [])}\"\n            )\nE           AssertionError: Expected 1 tool calls, but got 0\nE           assert 0 == 1\nE            +  where 0 = len(([] or []))\n\ntests/verifications/openai_api/test_chat_completion.py:501: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-weather_tool_then_text]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fb85e10>\nmodel = 'accounts/fireworks/models/llama4-maverick-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'weather_tool_then_text', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'location': 'San Francisco...], 'type': 'object'}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': '70 degrees and foggy'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n>           stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n\ntests/verifications/openai_api/test_chat_completion.py:498: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fb85e10>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.0002496249508112669,
+        "duration": 0.0003206087276339531,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-add_product_tool]",
-      "lineno": 451,
+      "lineno": 471,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-add_product_tool]",
@@ -3402,34 +5721,59 @@
         "case_id": "add_product_tool"
       },
       "setup": {
-        "duration": 0.007355917012318969,
+        "duration": 0.08054796047508717,
         "outcome": "passed"
       },
       "call": {
-        "duration": 1.154026625212282,
+        "duration": 0.12442617677152157,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 501,
-          "message": "AssertionError: Expected 1 tool calls, but got 0\nassert 0 == 1\n +  where 0 = len(([] or []))"
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 501,
-            "message": "AssertionError"
+            "lineno": 498,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-add_product_tool]>>\nopenai_client = <openai.OpenAI object at 0x1215b84c0>\nmodel = 'accounts/fireworks/models/llama4-maverick-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'add_product_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'inStock': True, 'name': 'Widget...}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': 'Successfully added product with id: 123'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n            stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n    \n            # --- Process Stream ---\n            accumulated_content, accumulated_tool_calls = _accumulate_streaming_tool_calls(stream)\n    \n            # --- Construct Assistant Message for History ---\n            assistant_message_dict = {\"role\": \"assistant\"}\n            if accumulated_content:\n                assistant_message_dict[\"content\"] = accumulated_content\n            if accumulated_tool_calls:\n                assistant_message_dict[\"tool_calls\"] = accumulated_tool_calls\n    \n            messages.append(assistant_message_dict)\n    \n            # --- Assertions ---\n            expected = expected_results.pop(0)\n            num_tool_calls = expected[\"num_tool_calls\"]\n    \n>           assert len(accumulated_tool_calls or []) == num_tool_calls, (\n                f\"Expected {num_tool_calls} tool calls, but got {len(accumulated_tool_calls or [])}\"\n            )\nE           AssertionError: Expected 1 tool calls, but got 0\nE           assert 0 == 1\nE            +  where 0 = len(([] or []))\n\ntests/verifications/openai_api/test_chat_completion.py:501: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-add_product_tool]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fde9d20>\nmodel = 'accounts/fireworks/models/llama4-maverick-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'add_product_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'inStock': True, 'name': 'Widget...}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': 'Successfully added product with id: 123'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n>           stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n\ntests/verifications/openai_api/test_chat_completion.py:498: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fde9d20>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.00027445796877145767,
+        "duration": 0.00040055252611637115,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-get_then_create_event_tool]",
-      "lineno": 451,
+      "lineno": 471,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-get_then_create_event_tool]",
@@ -3448,34 +5792,59 @@
         "case_id": "get_then_create_event_tool"
       },
       "setup": {
-        "duration": 0.008532499894499779,
+        "duration": 0.07104168552905321,
         "outcome": "passed"
       },
       "call": {
-        "duration": 2.8470693749841303,
+        "duration": 0.10808593034744263,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 501,
-          "message": "AssertionError: Expected 1 tool calls, but got 0\nassert 0 == 1\n +  where 0 = len(([] or []))"
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 501,
-            "message": "AssertionError"
+            "lineno": 498,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-get_then_create_event_tool]>>\nopenai_client = <openai.OpenAI object at 0x121541630>\nmodel = 'accounts/fireworks/models/llama4-maverick-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'get_then_create_event_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'date': '2025-03-03', ...ents found for 2025-03-03 at 10:00'}\"}, {'response': \"{'response': 'Successfully created new event with id: e_123'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n            stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n    \n            # --- Process Stream ---\n            accumulated_content, accumulated_tool_calls = _accumulate_streaming_tool_calls(stream)\n    \n            # --- Construct Assistant Message for History ---\n            assistant_message_dict = {\"role\": \"assistant\"}\n            if accumulated_content:\n                assistant_message_dict[\"content\"] = accumulated_content\n            if accumulated_tool_calls:\n                assistant_message_dict[\"tool_calls\"] = accumulated_tool_calls\n    \n            messages.append(assistant_message_dict)\n    \n            # --- Assertions ---\n            expected = expected_results.pop(0)\n            num_tool_calls = expected[\"num_tool_calls\"]\n    \n>           assert len(accumulated_tool_calls or []) == num_tool_calls, (\n                f\"Expected {num_tool_calls} tool calls, but got {len(accumulated_tool_calls or [])}\"\n            )\nE           AssertionError: Expected 1 tool calls, but got 0\nE           assert 0 == 1\nE            +  where 0 = len(([] or []))\n\ntests/verifications/openai_api/test_chat_completion.py:501: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-get_then_create_event_tool]>>\nopenai_client = <openai.OpenAI object at 0x7fa60f9bc700>\nmodel = 'accounts/fireworks/models/llama4-maverick-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'get_then_create_event_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'date': '2025-03-03', ...ents found for 2025-03-03 at 10:00'}\"}, {'response': \"{'response': 'Successfully created new event with id: e_123'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n>           stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n\ntests/verifications/openai_api/test_chat_completion.py:498: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60f9bc700>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.00025687506422400475,
+        "duration": 0.00033656321465969086,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-compare_monthly_expense_tool]",
-      "lineno": 451,
+      "lineno": 471,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-compare_monthly_expense_tool]",
@@ -3494,31 +5863,408 @@
         "case_id": "compare_monthly_expense_tool"
       },
       "setup": {
-        "duration": 0.00857908301986754,
+        "duration": 0.06945569068193436,
         "outcome": "passed"
       },
       "call": {
-        "duration": 6.787827457999811,
+        "duration": 0.12593147810548544,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 501,
-          "message": "AssertionError: Expected 1 tool calls, but got 0\nassert 0 == 1\n +  where 0 = len(([] or []))"
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 501,
-            "message": "AssertionError"
+            "lineno": 498,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-compare_monthly_expense_tool]>>\nopenai_client = <openai.OpenAI object at 0x121527250>\nmodel = 'accounts/fireworks/models/llama4-maverick-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'compare_monthly_expense_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'month': 1, 'year': ... 'Total expenses for January 2025: $1000'}\"}, {'response': \"{'response': 'Total expenses for February 2024: $2000'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n            stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n    \n            # --- Process Stream ---\n            accumulated_content, accumulated_tool_calls = _accumulate_streaming_tool_calls(stream)\n    \n            # --- Construct Assistant Message for History ---\n            assistant_message_dict = {\"role\": \"assistant\"}\n            if accumulated_content:\n                assistant_message_dict[\"content\"] = accumulated_content\n            if accumulated_tool_calls:\n                assistant_message_dict[\"tool_calls\"] = accumulated_tool_calls\n    \n            messages.append(assistant_message_dict)\n    \n            # --- Assertions ---\n            expected = expected_results.pop(0)\n            num_tool_calls = expected[\"num_tool_calls\"]\n    \n>           assert len(accumulated_tool_calls or []) == num_tool_calls, (\n                f\"Expected {num_tool_calls} tool calls, but got {len(accumulated_tool_calls or [])}\"\n            )\nE           AssertionError: Expected 1 tool calls, but got 0\nE           assert 0 == 1\nE            +  where 0 = len(([] or []))\n\ntests/verifications/openai_api/test_chat_completion.py:501: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[accounts/fireworks/models/llama4-maverick-instruct-basic-compare_monthly_expense_tool]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fc066b0>\nmodel = 'accounts/fireworks/models/llama4-maverick-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'compare_monthly_expense_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'month': 1, 'year': ... 'Total expenses for January 2025: $1000'}\"}, {'response': \"{'response': 'Total expenses for February 2024: $2000'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n>           stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n\ntests/verifications/openai_api/test_chat_completion.py:498: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fc066b0>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
       },
       "teardown": {
-        "duration": 0.0011689579114317894,
+        "duration": 0.0004069330170750618,
+        "outcome": "passed"
+      }
+    },
+    {
+      "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_multi_turn_multiple_images[accounts/fireworks/models/llama-v3p3-70b-instruct-stream=False]",
+      "lineno": 554,
+      "outcome": "skipped",
+      "keywords": [
+        "test_chat_multi_turn_multiple_images[accounts/fireworks/models/llama-v3p3-70b-instruct-stream=False]",
+        "parametrize",
+        "pytestmark",
+        "accounts/fireworks/models/llama-v3p3-70b-instruct-stream=False",
+        "test_chat_completion.py",
+        "openai_api",
+        "verifications",
+        "tests",
+        "llama-stack",
+        ""
+      ],
+      "metadata": {
+        "model": "accounts/fireworks/models/llama-v3p3-70b-instruct",
+        "case_id": "stream=False"
+      },
+      "setup": {
+        "duration": 0.07031089067459106,
+        "outcome": "passed"
+      },
+      "call": {
+        "duration": 0.00027627311646938324,
+        "outcome": "skipped",
+        "longrepr": "('/home/erichuang/llama-stack/tests/verifications/openai_api/test_chat_completion.py', 561, 'Skipped: Skipping test_chat_multi_turn_multiple_images for model accounts/fireworks/models/llama-v3p3-70b-instruct on provider fireworks based on config.')"
+      },
+      "teardown": {
+        "duration": 0.0003817221149802208,
+        "outcome": "passed"
+      }
+    },
+    {
+      "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_multi_turn_multiple_images[accounts/fireworks/models/llama-v3p3-70b-instruct-stream=True]",
+      "lineno": 554,
+      "outcome": "skipped",
+      "keywords": [
+        "test_chat_multi_turn_multiple_images[accounts/fireworks/models/llama-v3p3-70b-instruct-stream=True]",
+        "parametrize",
+        "pytestmark",
+        "accounts/fireworks/models/llama-v3p3-70b-instruct-stream=True",
+        "test_chat_completion.py",
+        "openai_api",
+        "verifications",
+        "tests",
+        "llama-stack",
+        ""
+      ],
+      "metadata": {
+        "model": "accounts/fireworks/models/llama-v3p3-70b-instruct",
+        "case_id": "stream=True"
+      },
+      "setup": {
+        "duration": 0.07004163973033428,
+        "outcome": "passed"
+      },
+      "call": {
+        "duration": 0.000285550020635128,
+        "outcome": "skipped",
+        "longrepr": "('/home/erichuang/llama-stack/tests/verifications/openai_api/test_chat_completion.py', 561, 'Skipped: Skipping test_chat_multi_turn_multiple_images for model accounts/fireworks/models/llama-v3p3-70b-instruct on provider fireworks based on config.')"
+      },
+      "teardown": {
+        "duration": 0.00021260324865579605,
+        "outcome": "passed"
+      }
+    },
+    {
+      "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_multi_turn_multiple_images[accounts/fireworks/models/llama4-scout-instruct-basic-stream=False]",
+      "lineno": 554,
+      "outcome": "failed",
+      "keywords": [
+        "test_chat_multi_turn_multiple_images[accounts/fireworks/models/llama4-scout-instruct-basic-stream=False]",
+        "parametrize",
+        "pytestmark",
+        "accounts/fireworks/models/llama4-scout-instruct-basic-stream=False",
+        "test_chat_completion.py",
+        "openai_api",
+        "verifications",
+        "tests",
+        "llama-stack",
+        ""
+      ],
+      "metadata": {
+        "model": "accounts/fireworks/models/llama4-scout-instruct-basic",
+        "case_id": "stream=False"
+      },
+      "setup": {
+        "duration": 0.07160913478583097,
+        "outcome": "passed"
+      },
+      "call": {
+        "duration": 0.23755338042974472,
+        "outcome": "failed",
+        "crash": {
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
+        },
+        "traceback": [
+          {
+            "path": "tests/verifications/openai_api/test_chat_completion.py",
+            "lineno": 588,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
+          }
+        ],
+        "longrepr": "request = <FixtureRequest for <Function test_chat_multi_turn_multiple_images[accounts/fireworks/models/llama4-scout-instruct-basic-stream=False]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fbf4190>\nmodel = 'accounts/fireworks/models/llama4-scout-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\nmulti_image_data = ['data:image/jpeg;base64,/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAIBAQEBAQIBAQECAgICAgQDAgICAgUEBAMEBgUGBgYFBgYGBwkIBgcJBwYGC...6pH9jaTzNv7vfRRXzubfxj9f8Pv8AkTz/AMX/ALbEz5Ly38lfMk/5Z/u64PxhqEZh+z/6rzvn2UUV5EvgPuzy/wAc6p5dt5ccibJpNkkdFFFec27mZ//Z']\nstream = False\n\n    @pytest.mark.parametrize(\"stream\", [False, True], ids=[\"stream=False\", \"stream=True\"])\n    def test_chat_multi_turn_multiple_images(\n        request, openai_client, model, provider, verification_config, multi_image_data, stream\n    ):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages_turn1 = [\n            {\n                \"role\": \"user\",\n                \"content\": [\n                    {\n                        \"type\": \"image_url\",\n                        \"image_url\": {\n                            \"url\": multi_image_data[0],\n                        },\n                    },\n                    {\n                        \"type\": \"image_url\",\n                        \"image_url\": {\n                            \"url\": multi_image_data[1],\n                        },\n                    },\n                    {\n                        \"type\": \"text\",\n                        \"text\": \"What furniture is in the first image that is not in the second image?\",\n                    },\n                ],\n            },\n        ]\n    \n        # First API call\n>       response1 = openai_client.chat.completions.create(\n            model=model,\n            messages=messages_turn1,\n            stream=stream,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:588: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fbf4190>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
+      },
+      "teardown": {
+        "duration": 0.00033799000084400177,
+        "outcome": "passed"
+      }
+    },
+    {
+      "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_multi_turn_multiple_images[accounts/fireworks/models/llama4-scout-instruct-basic-stream=True]",
+      "lineno": 554,
+      "outcome": "failed",
+      "keywords": [
+        "test_chat_multi_turn_multiple_images[accounts/fireworks/models/llama4-scout-instruct-basic-stream=True]",
+        "parametrize",
+        "pytestmark",
+        "accounts/fireworks/models/llama4-scout-instruct-basic-stream=True",
+        "test_chat_completion.py",
+        "openai_api",
+        "verifications",
+        "tests",
+        "llama-stack",
+        ""
+      ],
+      "metadata": {
+        "model": "accounts/fireworks/models/llama4-scout-instruct-basic",
+        "case_id": "stream=True"
+      },
+      "setup": {
+        "duration": 0.0742298774421215,
+        "outcome": "passed"
+      },
+      "call": {
+        "duration": 0.28080874867737293,
+        "outcome": "failed",
+        "crash": {
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
+        },
+        "traceback": [
+          {
+            "path": "tests/verifications/openai_api/test_chat_completion.py",
+            "lineno": 588,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
+          }
+        ],
+        "longrepr": "request = <FixtureRequest for <Function test_chat_multi_turn_multiple_images[accounts/fireworks/models/llama4-scout-instruct-basic-stream=True]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fb6e920>\nmodel = 'accounts/fireworks/models/llama4-scout-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\nmulti_image_data = ['data:image/jpeg;base64,/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAIBAQEBAQIBAQECAgICAgQDAgICAgUEBAMEBgUGBgYFBgYGBwkIBgcJBwYGC...6pH9jaTzNv7vfRRXzubfxj9f8Pv8AkTz/AMX/ALbEz5Ly38lfMk/5Z/u64PxhqEZh+z/6rzvn2UUV5EvgPuzy/wAc6p5dt5ccibJpNkkdFFFec27mZ//Z']\nstream = True\n\n    @pytest.mark.parametrize(\"stream\", [False, True], ids=[\"stream=False\", \"stream=True\"])\n    def test_chat_multi_turn_multiple_images(\n        request, openai_client, model, provider, verification_config, multi_image_data, stream\n    ):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages_turn1 = [\n            {\n                \"role\": \"user\",\n                \"content\": [\n                    {\n                        \"type\": \"image_url\",\n                        \"image_url\": {\n                            \"url\": multi_image_data[0],\n                        },\n                    },\n                    {\n                        \"type\": \"image_url\",\n                        \"image_url\": {\n                            \"url\": multi_image_data[1],\n                        },\n                    },\n                    {\n                        \"type\": \"text\",\n                        \"text\": \"What furniture is in the first image that is not in the second image?\",\n                    },\n                ],\n            },\n        ]\n    \n        # First API call\n>       response1 = openai_client.chat.completions.create(\n            model=model,\n            messages=messages_turn1,\n            stream=stream,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:588: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fb6e920>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
+      },
+      "teardown": {
+        "duration": 0.0003352127969264984,
+        "outcome": "passed"
+      }
+    },
+    {
+      "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_multi_turn_multiple_images[accounts/fireworks/models/llama4-maverick-instruct-basic-stream=False]",
+      "lineno": 554,
+      "outcome": "failed",
+      "keywords": [
+        "test_chat_multi_turn_multiple_images[accounts/fireworks/models/llama4-maverick-instruct-basic-stream=False]",
+        "parametrize",
+        "pytestmark",
+        "accounts/fireworks/models/llama4-maverick-instruct-basic-stream=False",
+        "test_chat_completion.py",
+        "openai_api",
+        "verifications",
+        "tests",
+        "llama-stack",
+        ""
+      ],
+      "metadata": {
+        "model": "accounts/fireworks/models/llama4-maverick-instruct-basic",
+        "case_id": "stream=False"
+      },
+      "setup": {
+        "duration": 0.07394346781075001,
+        "outcome": "passed"
+      },
+      "call": {
+        "duration": 0.2838349239900708,
+        "outcome": "failed",
+        "crash": {
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
+        },
+        "traceback": [
+          {
+            "path": "tests/verifications/openai_api/test_chat_completion.py",
+            "lineno": 588,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
+          }
+        ],
+        "longrepr": "request = <FixtureRequest for <Function test_chat_multi_turn_multiple_images[accounts/fireworks/models/llama4-maverick-instruct-basic-stream=False]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fabb6d0>\nmodel = 'accounts/fireworks/models/llama4-maverick-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\nmulti_image_data = ['data:image/jpeg;base64,/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAIBAQEBAQIBAQECAgICAgQDAgICAgUEBAMEBgUGBgYFBgYGBwkIBgcJBwYGC...6pH9jaTzNv7vfRRXzubfxj9f8Pv8AkTz/AMX/ALbEz5Ly38lfMk/5Z/u64PxhqEZh+z/6rzvn2UUV5EvgPuzy/wAc6p5dt5ccibJpNkkdFFFec27mZ//Z']\nstream = False\n\n    @pytest.mark.parametrize(\"stream\", [False, True], ids=[\"stream=False\", \"stream=True\"])\n    def test_chat_multi_turn_multiple_images(\n        request, openai_client, model, provider, verification_config, multi_image_data, stream\n    ):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages_turn1 = [\n            {\n                \"role\": \"user\",\n                \"content\": [\n                    {\n                        \"type\": \"image_url\",\n                        \"image_url\": {\n                            \"url\": multi_image_data[0],\n                        },\n                    },\n                    {\n                        \"type\": \"image_url\",\n                        \"image_url\": {\n                            \"url\": multi_image_data[1],\n                        },\n                    },\n                    {\n                        \"type\": \"text\",\n                        \"text\": \"What furniture is in the first image that is not in the second image?\",\n                    },\n                ],\n            },\n        ]\n    \n        # First API call\n>       response1 = openai_client.chat.completions.create(\n            model=model,\n            messages=messages_turn1,\n            stream=stream,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:588: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fabb6d0>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
+      },
+      "teardown": {
+        "duration": 0.0003282083198428154,
+        "outcome": "passed"
+      }
+    },
+    {
+      "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_multi_turn_multiple_images[accounts/fireworks/models/llama4-maverick-instruct-basic-stream=True]",
+      "lineno": 554,
+      "outcome": "failed",
+      "keywords": [
+        "test_chat_multi_turn_multiple_images[accounts/fireworks/models/llama4-maverick-instruct-basic-stream=True]",
+        "parametrize",
+        "pytestmark",
+        "accounts/fireworks/models/llama4-maverick-instruct-basic-stream=True",
+        "test_chat_completion.py",
+        "openai_api",
+        "verifications",
+        "tests",
+        "llama-stack",
+        ""
+      ],
+      "metadata": {
+        "model": "accounts/fireworks/models/llama4-maverick-instruct-basic",
+        "case_id": "stream=True"
+      },
+      "setup": {
+        "duration": 0.0713854730129242,
+        "outcome": "passed"
+      },
+      "call": {
+        "duration": 0.20238025579601526,
+        "outcome": "failed",
+        "crash": {
+          "path": "/home/erichuang/.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+          "lineno": 1023,
+          "message": "openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}"
+        },
+        "traceback": [
+          {
+            "path": "tests/verifications/openai_api/test_chat_completion.py",
+            "lineno": 588,
+            "message": ""
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py",
+            "lineno": 279,
+            "message": "in wrapper"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py",
+            "lineno": 914,
+            "message": "in create"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1242,
+            "message": "in post"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 919,
+            "message": "in request"
+          },
+          {
+            "path": "../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py",
+            "lineno": 1023,
+            "message": "PermissionDeniedError"
+          }
+        ],
+        "longrepr": "request = <FixtureRequest for <Function test_chat_multi_turn_multiple_images[accounts/fireworks/models/llama4-maverick-instruct-basic-stream=True]>>\nopenai_client = <openai.OpenAI object at 0x7fa60fc46d40>\nmodel = 'accounts/fireworks/models/llama4-maverick-instruct-basic'\nprovider = 'fireworks'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\nmulti_image_data = ['data:image/jpeg;base64,/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAIBAQEBAQIBAQECAgICAgQDAgICAgUEBAMEBgUGBgYFBgYGBwkIBgcJBwYGC...6pH9jaTzNv7vfRRXzubfxj9f8Pv8AkTz/AMX/ALbEz5Ly38lfMk/5Z/u64PxhqEZh+z/6rzvn2UUV5EvgPuzy/wAc6p5dt5ccibJpNkkdFFFec27mZ//Z']\nstream = True\n\n    @pytest.mark.parametrize(\"stream\", [False, True], ids=[\"stream=False\", \"stream=True\"])\n    def test_chat_multi_turn_multiple_images(\n        request, openai_client, model, provider, verification_config, multi_image_data, stream\n    ):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages_turn1 = [\n            {\n                \"role\": \"user\",\n                \"content\": [\n                    {\n                        \"type\": \"image_url\",\n                        \"image_url\": {\n                            \"url\": multi_image_data[0],\n                        },\n                    },\n                    {\n                        \"type\": \"image_url\",\n                        \"image_url\": {\n                            \"url\": multi_image_data[1],\n                        },\n                    },\n                    {\n                        \"type\": \"text\",\n                        \"text\": \"What furniture is in the first image that is not in the second image?\",\n                    },\n                ],\n            },\n        ]\n    \n        # First API call\n>       response1 = openai_client.chat.completions.create(\n            model=model,\n            messages=messages_turn1,\n            stream=stream,\n        )\n\ntests/verifications/openai_api/test_chat_completion.py:588: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_utils/_utils.py:279: in wrapper\n    return func(*args, **kwargs)\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/resources/chat/completions/completions.py:914: in create\n    return self._post(\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1242: in post\n    return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:919: in request\n    return self._request(\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <openai.OpenAI object at 0x7fa60fc46d40>\n\n    def _request(\n        self,\n        *,\n        cast_to: Type[ResponseT],\n        options: FinalRequestOptions,\n        retries_taken: int,\n        stream: bool,\n        stream_cls: type[_StreamT] | None,\n    ) -> ResponseT | _StreamT:\n        # create a copy of the options we were given so that if the\n        # options are mutated later & we then retry, the retries are\n        # given the original options\n        input_options = model_copy(options)\n    \n        cast_to = self._maybe_override_cast_to(cast_to, options)\n        options = self._prepare_options(options)\n    \n        remaining_retries = options.get_max_retries(self.max_retries) - retries_taken\n        request = self._build_request(options, retries_taken=retries_taken)\n        self._prepare_request(request)\n    \n        kwargs: HttpxSendArgs = {}\n        if self.custom_auth is not None:\n            kwargs[\"auth\"] = self.custom_auth\n    \n        log.debug(\"Sending HTTP Request: %s %s\", request.method, request.url)\n    \n        try:\n            response = self._client.send(\n                request,\n                stream=stream or self._should_stream_response_body(request=request),\n                **kwargs,\n            )\n        except httpx.TimeoutException as err:\n            log.debug(\"Encountered httpx.TimeoutException\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising timeout error\")\n            raise APITimeoutError(request=request) from err\n        except Exception as err:\n            log.debug(\"Encountered Exception\", exc_info=True)\n    \n            if remaining_retries > 0:\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                    response_headers=None,\n                )\n    \n            log.debug(\"Raising connection error\")\n            raise APIConnectionError(request=request) from err\n    \n        log.debug(\n            'HTTP Response: %s %s \"%i %s\" %s',\n            request.method,\n            request.url,\n            response.status_code,\n            response.reason_phrase,\n            response.headers,\n        )\n        log.debug(\"request_id: %s\", response.headers.get(\"x-request-id\"))\n    \n        try:\n            response.raise_for_status()\n        except httpx.HTTPStatusError as err:  # thrown on 4xx and 5xx status code\n            log.debug(\"Encountered httpx.HTTPStatusError\", exc_info=True)\n    \n            if remaining_retries > 0 and self._should_retry(err.response):\n                err.response.close()\n                return self._retry_request(\n                    input_options,\n                    cast_to,\n                    retries_taken=retries_taken,\n                    response_headers=err.response.headers,\n                    stream=stream,\n                    stream_cls=stream_cls,\n                )\n    \n            # If the response is streamed then we need to explicitly read the response\n            # to completion before attempting to access the response text.\n            if not err.response.is_closed:\n                err.response.read()\n    \n            log.debug(\"Re-raising status error\")\n>           raise self._make_status_error_from_response(err.response) from None\nE           openai.PermissionDeniedError: Error code: 403 - {'error': 'unauthorized'}\n\n../.conda/envs/myenv/lib/python3.10/site-packages/openai/_base_client.py:1023: PermissionDeniedError"
+      },
+      "teardown": {
+        "duration": 0.0019415868446230888,
         "outcome": "passed"
       }
     }
   ],
-  "run_timestamp": 1744841154
+  "run_timestamp": 1744915672
 }
diff --git a/tests/verifications/test_results/meta_reference.json b/tests/verifications/test_results/meta_reference.json
index 54c08bc62..5d4c7137e 100644
--- a/tests/verifications/test_results/meta_reference.json
+++ b/tests/verifications/test_results/meta_reference.json
@@ -1,13 +1,13 @@
 {
-  "created": 1744762318.264238,
-  "duration": 177.55697464942932,
+  "created": 1744915514.208135,
+  "duration": 202.18266344070435,
   "exitcode": 0,
   "root": "/home/erichuang/llama-stack",
   "environment": {},
   "summary": {
-    "passed": 26,
-    "total": 26,
-    "collected": 26
+    "passed": 28,
+    "total": 28,
+    "collected": 28
   },
   "collectors": [
     {
@@ -27,132 +27,142 @@
         {
           "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_basic[meta-llama/Llama-4-Scout-17B-16E-Instruct-earth]",
           "type": "Function",
-          "lineno": 80
+          "lineno": 95
         },
         {
           "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_basic[meta-llama/Llama-4-Scout-17B-16E-Instruct-saturn]",
           "type": "Function",
-          "lineno": 80
+          "lineno": 95
         },
         {
           "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_basic[meta-llama/Llama-4-Scout-17B-16E-Instruct-earth]",
           "type": "Function",
-          "lineno": 103
+          "lineno": 114
         },
         {
           "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_basic[meta-llama/Llama-4-Scout-17B-16E-Instruct-saturn]",
           "type": "Function",
-          "lineno": 103
+          "lineno": 114
         },
         {
           "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_image[meta-llama/Llama-4-Scout-17B-16E-Instruct-case0]",
           "type": "Function",
-          "lineno": 131
+          "lineno": 138
         },
         {
           "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_image[meta-llama/Llama-4-Scout-17B-16E-Instruct-case0]",
           "type": "Function",
-          "lineno": 154
+          "lineno": 157
         },
         {
           "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_structured_output[meta-llama/Llama-4-Scout-17B-16E-Instruct-calendar]",
           "type": "Function",
-          "lineno": 182
+          "lineno": 181
         },
         {
           "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_structured_output[meta-llama/Llama-4-Scout-17B-16E-Instruct-math]",
           "type": "Function",
-          "lineno": 182
+          "lineno": 181
         },
         {
           "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_structured_output[meta-llama/Llama-4-Scout-17B-16E-Instruct-calendar]",
           "type": "Function",
-          "lineno": 209
+          "lineno": 204
         },
         {
           "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_structured_output[meta-llama/Llama-4-Scout-17B-16E-Instruct-math]",
           "type": "Function",
-          "lineno": 209
+          "lineno": 204
         },
         {
           "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-case0]",
           "type": "Function",
-          "lineno": 235
+          "lineno": 226
         },
         {
           "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-case0]",
           "type": "Function",
-          "lineno": 263
+          "lineno": 250
         },
         {
           "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_tool_choice_required[meta-llama/Llama-4-Scout-17B-16E-Instruct-case0]",
           "type": "Function",
-          "lineno": 296
+          "lineno": 278
         },
         {
           "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_tool_choice_required[meta-llama/Llama-4-Scout-17B-16E-Instruct-case0]",
           "type": "Function",
-          "lineno": 329
+          "lineno": 302
         },
         {
           "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_tool_choice_none[meta-llama/Llama-4-Scout-17B-16E-Instruct-case0]",
           "type": "Function",
-          "lineno": 362
+          "lineno": 329
         },
         {
           "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_tool_choice_none[meta-llama/Llama-4-Scout-17B-16E-Instruct-case0]",
           "type": "Function",
-          "lineno": 395
+          "lineno": 352
         },
         {
           "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-text_then_weather_tool]",
           "type": "Function",
-          "lineno": 431
+          "lineno": 380
         },
         {
           "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-weather_tool_then_text]",
           "type": "Function",
-          "lineno": 431
+          "lineno": 380
         },
         {
           "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-add_product_tool]",
           "type": "Function",
-          "lineno": 431
+          "lineno": 380
         },
         {
           "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-get_then_create_event_tool]",
           "type": "Function",
-          "lineno": 431
+          "lineno": 380
         },
         {
           "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-compare_monthly_expense_tool]",
           "type": "Function",
-          "lineno": 431
+          "lineno": 380
         },
         {
           "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-text_then_weather_tool]",
           "type": "Function",
-          "lineno": 532
+          "lineno": 471
         },
         {
           "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-weather_tool_then_text]",
           "type": "Function",
-          "lineno": 532
+          "lineno": 471
         },
         {
           "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-add_product_tool]",
           "type": "Function",
-          "lineno": 532
+          "lineno": 471
         },
         {
           "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-get_then_create_event_tool]",
           "type": "Function",
-          "lineno": 532
+          "lineno": 471
         },
         {
           "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-compare_monthly_expense_tool]",
           "type": "Function",
-          "lineno": 532
+          "lineno": 471
+        },
+        {
+          "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_multi_turn_multiple_images[meta-llama/Llama-4-Scout-17B-16E-Instruct-stream=False]",
+          "type": "Function",
+          "lineno": 554
+        },
+        {
+          "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_multi_turn_multiple_images[meta-llama/Llama-4-Scout-17B-16E-Instruct-stream=True]",
+          "type": "Function",
+          "lineno": 554
         }
       ]
     }
@@ -160,7 +170,7 @@
   "tests": [
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_basic[meta-llama/Llama-4-Scout-17B-16E-Instruct-earth]",
-      "lineno": 80,
+      "lineno": 95,
       "outcome": "passed",
       "keywords": [
         "test_chat_non_streaming_basic[meta-llama/Llama-4-Scout-17B-16E-Instruct-earth]",
@@ -179,21 +189,21 @@
         "case_id": "earth"
       },
       "setup": {
-        "duration": 0.048547716811299324,
+        "duration": 0.09510238654911518,
         "outcome": "passed"
       },
       "call": {
-        "duration": 2.2047047605738044,
+        "duration": 2.7976166242733598,
         "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.00029009580612182617,
+        "duration": 0.0002804817631840706,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_basic[meta-llama/Llama-4-Scout-17B-16E-Instruct-saturn]",
-      "lineno": 80,
+      "lineno": 95,
       "outcome": "passed",
       "keywords": [
         "test_chat_non_streaming_basic[meta-llama/Llama-4-Scout-17B-16E-Instruct-saturn]",
@@ -212,21 +222,21 @@
         "case_id": "saturn"
       },
       "setup": {
-        "duration": 0.025718219578266144,
+        "duration": 0.0735457269474864,
         "outcome": "passed"
       },
       "call": {
-        "duration": 1.1276333406567574,
+        "duration": 1.0852967854589224,
         "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.00028874073177576065,
+        "duration": 0.00029948819428682327,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_basic[meta-llama/Llama-4-Scout-17B-16E-Instruct-earth]",
-      "lineno": 103,
+      "lineno": 114,
       "outcome": "passed",
       "keywords": [
         "test_chat_streaming_basic[meta-llama/Llama-4-Scout-17B-16E-Instruct-earth]",
@@ -245,21 +255,21 @@
         "case_id": "earth"
       },
       "setup": {
-        "duration": 0.02475887257605791,
+        "duration": 0.07200248818844557,
         "outcome": "passed"
       },
       "call": {
-        "duration": 2.219081767834723,
+        "duration": 0.41483108792454004,
         "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.0002961978316307068,
+        "duration": 0.0002880822867155075,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_basic[meta-llama/Llama-4-Scout-17B-16E-Instruct-saturn]",
-      "lineno": 103,
+      "lineno": 114,
       "outcome": "passed",
       "keywords": [
         "test_chat_streaming_basic[meta-llama/Llama-4-Scout-17B-16E-Instruct-saturn]",
@@ -278,21 +288,21 @@
         "case_id": "saturn"
       },
       "setup": {
-        "duration": 0.025741156190633774,
+        "duration": 0.07424226123839617,
         "outcome": "passed"
       },
       "call": {
-        "duration": 1.1742202220484614,
+        "duration": 1.1533718826249242,
         "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.000283985398709774,
+        "duration": 0.00026405230164527893,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_image[meta-llama/Llama-4-Scout-17B-16E-Instruct-case0]",
-      "lineno": 131,
+      "lineno": 138,
       "outcome": "passed",
       "keywords": [
         "test_chat_non_streaming_image[meta-llama/Llama-4-Scout-17B-16E-Instruct-case0]",
@@ -311,21 +321,21 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.024309909902513027,
+        "duration": 0.07035014033317566,
         "outcome": "passed"
       },
       "call": {
-        "duration": 8.937463724054396,
+        "duration": 11.941276826895773,
         "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.00032057054340839386,
+        "duration": 0.0002712151035666466,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_image[meta-llama/Llama-4-Scout-17B-16E-Instruct-case0]",
-      "lineno": 154,
+      "lineno": 157,
       "outcome": "passed",
       "keywords": [
         "test_chat_streaming_image[meta-llama/Llama-4-Scout-17B-16E-Instruct-case0]",
@@ -344,21 +354,21 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.024973606690764427,
+        "duration": 0.08027863781899214,
         "outcome": "passed"
       },
       "call": {
-        "duration": 10.170741765759885,
+        "duration": 5.189308542758226,
         "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.00030694250017404556,
+        "duration": 0.000255669467151165,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_structured_output[meta-llama/Llama-4-Scout-17B-16E-Instruct-calendar]",
-      "lineno": 182,
+      "lineno": 181,
       "outcome": "passed",
       "keywords": [
         "test_chat_non_streaming_structured_output[meta-llama/Llama-4-Scout-17B-16E-Instruct-calendar]",
@@ -377,21 +387,21 @@
         "case_id": "calendar"
       },
       "setup": {
-        "duration": 0.02560058142989874,
+        "duration": 0.07215503882616758,
         "outcome": "passed"
       },
       "call": {
-        "duration": 5.377012901939452,
+        "duration": 7.25669299531728,
         "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.0002925479784607887,
+        "duration": 0.0002499222755432129,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_structured_output[meta-llama/Llama-4-Scout-17B-16E-Instruct-math]",
-      "lineno": 182,
+      "lineno": 181,
       "outcome": "passed",
       "keywords": [
         "test_chat_non_streaming_structured_output[meta-llama/Llama-4-Scout-17B-16E-Instruct-math]",
@@ -410,21 +420,21 @@
         "case_id": "math"
       },
       "setup": {
-        "duration": 0.025032303296029568,
+        "duration": 0.0723958220332861,
         "outcome": "passed"
       },
       "call": {
-        "duration": 19.210087121464312,
+        "duration": 23.26972564868629,
         "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.00026431307196617126,
+        "duration": 0.0002250121906399727,
         "outcome": "passed"
       }
     },
     {
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@@ -443,21 +453,21 @@
         "case_id": "calendar"
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       "outcome": "passed",
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@@ -476,21 +486,21 @@
         "case_id": "math"
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-      "lineno": 235,
+      "lineno": 226,
       "outcome": "passed",
       "keywords": [
         "test_chat_non_streaming_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-case0]",
@@ -509,21 +519,21 @@
         "case_id": "case0"
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         "outcome": "passed"
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       "outcome": "passed",
       "keywords": [
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@@ -542,22 +552,21 @@
         "case_id": "case0"
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         "outcome": "passed"
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-        "outcome": "passed",
-        "stdout": "{'id': '621ab525-811d-4c30-be73-0eab728a05b4', 'type': 'function', 'function': {'name': 'get_weather', 'arguments': '{\"location\": \"San Francisco, United States\"}'}}\n"
+        "duration": 0.7484909351915121,
+        "outcome": "passed"
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-        "duration": 0.00028704386204481125,
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-      "lineno": 296,
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       "outcome": "passed",
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@@ -576,22 +585,21 @@
         "case_id": "case0"
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+        "duration": 0.7497121002525091,
+        "outcome": "passed"
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-      "lineno": 329,
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       "outcome": "passed",
       "keywords": [
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@@ -610,21 +618,21 @@
         "case_id": "case0"
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-      "lineno": 362,
+      "lineno": 329,
       "outcome": "passed",
       "keywords": [
         "test_chat_non_streaming_tool_choice_none[meta-llama/Llama-4-Scout-17B-16E-Instruct-case0]",
@@ -643,21 +651,21 @@
         "case_id": "case0"
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         "outcome": "passed"
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-      "lineno": 395,
+      "lineno": 352,
       "outcome": "passed",
       "keywords": [
         "test_chat_streaming_tool_choice_none[meta-llama/Llama-4-Scout-17B-16E-Instruct-case0]",
@@ -676,21 +684,21 @@
         "case_id": "case0"
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         "outcome": "passed"
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       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-text_then_weather_tool]",
-      "lineno": 431,
+      "lineno": 380,
       "outcome": "passed",
       "keywords": [
         "test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-text_then_weather_tool]",
@@ -709,21 +717,21 @@
         "case_id": "text_then_weather_tool"
       },
       "setup": {
-        "duration": 0.024312538094818592,
+        "duration": 0.10514138638973236,
         "outcome": "passed"
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         "outcome": "passed"
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         "outcome": "passed"
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     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-weather_tool_then_text]",
-      "lineno": 431,
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       "outcome": "passed",
       "keywords": [
         "test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-weather_tool_then_text]",
@@ -742,21 +750,21 @@
         "case_id": "weather_tool_then_text"
       },
       "setup": {
-        "duration": 0.02405371330678463,
+        "duration": 0.09724622592329979,
         "outcome": "passed"
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         "outcome": "passed"
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         "outcome": "passed"
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       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-add_product_tool]",
-      "lineno": 431,
+      "lineno": 380,
       "outcome": "passed",
       "keywords": [
         "test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-add_product_tool]",
@@ -775,21 +783,21 @@
         "case_id": "add_product_tool"
       },
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-        "duration": 0.02578610647469759,
+        "duration": 0.0717660365626216,
         "outcome": "passed"
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         "outcome": "passed"
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         "outcome": "passed"
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     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-get_then_create_event_tool]",
-      "lineno": 431,
+      "lineno": 380,
       "outcome": "passed",
       "keywords": [
         "test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-get_then_create_event_tool]",
@@ -808,21 +816,21 @@
         "case_id": "get_then_create_event_tool"
       },
       "setup": {
-        "duration": 0.024106032215058804,
+        "duration": 0.07237224746495485,
         "outcome": "passed"
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         "outcome": "passed"
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         "outcome": "passed"
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     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-compare_monthly_expense_tool]",
-      "lineno": 431,
+      "lineno": 380,
       "outcome": "passed",
       "keywords": [
         "test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-compare_monthly_expense_tool]",
@@ -841,21 +849,21 @@
         "case_id": "compare_monthly_expense_tool"
       },
       "setup": {
-        "duration": 0.02426640223711729,
+        "duration": 0.07419578451663256,
         "outcome": "passed"
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         "outcome": "passed"
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       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-text_then_weather_tool]",
-      "lineno": 532,
+      "lineno": 471,
       "outcome": "passed",
       "keywords": [
         "test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-text_then_weather_tool]",
@@ -874,21 +882,21 @@
         "case_id": "text_then_weather_tool"
       },
       "setup": {
-        "duration": 0.024594508111476898,
+        "duration": 0.07015236373990774,
         "outcome": "passed"
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         "outcome": "passed"
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-      "lineno": 532,
+      "lineno": 471,
       "outcome": "passed",
       "keywords": [
         "test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-weather_tool_then_text]",
@@ -907,21 +915,21 @@
         "case_id": "weather_tool_then_text"
       },
       "setup": {
-        "duration": 0.02453650813549757,
+        "duration": 0.07009198423475027,
         "outcome": "passed"
       },
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         "outcome": "passed"
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       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-add_product_tool]",
-      "lineno": 532,
+      "lineno": 471,
       "outcome": "passed",
       "keywords": [
         "test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-add_product_tool]",
@@ -940,21 +948,21 @@
         "case_id": "add_product_tool"
       },
       "setup": {
-        "duration": 0.025252479128539562,
+        "duration": 0.07378454692661762,
         "outcome": "passed"
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         "outcome": "passed"
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     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-get_then_create_event_tool]",
-      "lineno": 532,
+      "lineno": 471,
       "outcome": "passed",
       "keywords": [
         "test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-get_then_create_event_tool]",
@@ -973,21 +981,21 @@
         "case_id": "get_then_create_event_tool"
       },
       "setup": {
-        "duration": 0.025367626920342445,
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         "outcome": "passed"
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         "outcome": "passed"
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       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-compare_monthly_expense_tool]",
-      "lineno": 532,
+      "lineno": 471,
       "outcome": "passed",
       "keywords": [
         "test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-compare_monthly_expense_tool]",
@@ -1006,18 +1014,84 @@
         "case_id": "compare_monthly_expense_tool"
       },
       "setup": {
-        "duration": 0.0242690397426486,
+        "duration": 0.07353641279041767,
         "outcome": "passed"
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         "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.0007346374914050102,
+        "duration": 0.0003117518499493599,
+        "outcome": "passed"
+      }
+    },
+    {
+      "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_multi_turn_multiple_images[meta-llama/Llama-4-Scout-17B-16E-Instruct-stream=False]",
+      "lineno": 554,
+      "outcome": "passed",
+      "keywords": [
+        "test_chat_multi_turn_multiple_images[meta-llama/Llama-4-Scout-17B-16E-Instruct-stream=False]",
+        "parametrize",
+        "pytestmark",
+        "meta-llama/Llama-4-Scout-17B-16E-Instruct-stream=False",
+        "test_chat_completion.py",
+        "openai_api",
+        "verifications",
+        "tests",
+        "llama-stack",
+        ""
+      ],
+      "metadata": {
+        "model": "meta-llama/Llama-4-Scout-17B-16E-Instruct",
+        "case_id": "stream=False"
+      },
+      "setup": {
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+        "outcome": "passed"
+      }
+    },
+    {
+      "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_multi_turn_multiple_images[meta-llama/Llama-4-Scout-17B-16E-Instruct-stream=True]",
+      "lineno": 554,
+      "outcome": "passed",
+      "keywords": [
+        "test_chat_multi_turn_multiple_images[meta-llama/Llama-4-Scout-17B-16E-Instruct-stream=True]",
+        "parametrize",
+        "pytestmark",
+        "meta-llama/Llama-4-Scout-17B-16E-Instruct-stream=True",
+        "test_chat_completion.py",
+        "openai_api",
+        "verifications",
+        "tests",
+        "llama-stack",
+        ""
+      ],
+      "metadata": {
+        "model": "meta-llama/Llama-4-Scout-17B-16E-Instruct",
+        "case_id": "stream=True"
+      },
+      "setup": {
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+        "outcome": "passed"
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+      "call": {
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+        "outcome": "passed"
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         "outcome": "passed"
       }
     }
   ],
-  "run_timestamp": 1744762139
+  "run_timestamp": 1744915311
 }
diff --git a/tests/verifications/test_results/openai.json b/tests/verifications/test_results/openai.json
index ae60917c0..98d21ca7d 100644
--- a/tests/verifications/test_results/openai.json
+++ b/tests/verifications/test_results/openai.json
@@ -1,13 +1,13 @@
 {
-  "created": 1744841456.846108,
-  "duration": 94.55667495727539,
+  "created": 1744915847.9751267,
+  "duration": 148.2403597831726,
   "exitcode": 0,
-  "root": "/Users/erichuang/projects/llama-stack",
+  "root": "/home/erichuang/llama-stack",
   "environment": {},
   "summary": {
-    "passed": 52,
-    "total": 52,
-    "collected": 52
+    "passed": 56,
+    "total": 56,
+    "collected": 56
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   "collectors": [
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@@ -27,262 +27,282 @@
         {
           "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_basic[gpt-4o-earth]",
           "type": "Function",
-          "lineno": 74
+          "lineno": 95
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@@ -738,21 +758,21 @@
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@@ -771,21 +791,21 @@
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@@ -969,21 +989,21 @@
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@@ -1367,21 +1385,21 @@
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@@ -1400,21 +1418,21 @@
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@@ -1433,21 +1451,21 @@
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@@ -1466,21 +1484,21 @@
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@@ -1499,21 +1517,21 @@
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@@ -1532,21 +1550,21 @@
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@@ -1565,21 +1583,21 @@
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@@ -1598,21 +1616,21 @@
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@@ -1631,21 +1649,21 @@
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@@ -1664,21 +1682,21 @@
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@@ -1697,21 +1715,21 @@
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@@ -1730,21 +1748,21 @@
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+      "lineno": 471,
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@@ -1763,21 +1781,21 @@
         "case_id": "add_product_tool"
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+      "lineno": 471,
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@@ -1796,21 +1814,21 @@
         "case_id": "get_then_create_event_tool"
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-      "lineno": 451,
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       "outcome": "passed",
       "keywords": [
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@@ -1829,21 +1847,21 @@
         "case_id": "compare_monthly_expense_tool"
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@@ -1862,21 +1880,21 @@
         "case_id": "text_then_weather_tool"
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@@ -1895,21 +1913,21 @@
         "case_id": "weather_tool_then_text"
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       "outcome": "passed",
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@@ -1928,21 +1946,21 @@
         "case_id": "add_product_tool"
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@@ -1961,21 +1979,21 @@
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@@ -1994,18 +2012,150 @@
         "case_id": "compare_monthly_expense_tool"
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+      }
+    },
+    {
+      "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_multi_turn_multiple_images[gpt-4o-stream=False]",
+      "lineno": 554,
+      "outcome": "passed",
+      "keywords": [
+        "test_chat_multi_turn_multiple_images[gpt-4o-stream=False]",
+        "parametrize",
+        "pytestmark",
+        "gpt-4o-stream=False",
+        "test_chat_completion.py",
+        "openai_api",
+        "verifications",
+        "tests",
+        "llama-stack",
+        ""
+      ],
+      "metadata": {
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+        "case_id": "stream=False"
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+    {
+      "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_multi_turn_multiple_images[gpt-4o-stream=True]",
+      "lineno": 554,
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+        "parametrize",
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+        "test_chat_completion.py",
+        "openai_api",
+        "verifications",
+        "tests",
+        "llama-stack",
+        ""
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+        "case_id": "stream=True"
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+    {
+      "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_multi_turn_multiple_images[gpt-4o-mini-stream=False]",
+      "lineno": 554,
+      "outcome": "passed",
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+        "parametrize",
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+        "test_chat_completion.py",
+        "openai_api",
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+        "tests",
+        "llama-stack",
+        ""
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+      }
+    },
+    {
+      "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_multi_turn_multiple_images[gpt-4o-mini-stream=True]",
+      "lineno": 554,
+      "outcome": "passed",
+      "keywords": [
+        "test_chat_multi_turn_multiple_images[gpt-4o-mini-stream=True]",
+        "parametrize",
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+        "gpt-4o-mini-stream=True",
+        "test_chat_completion.py",
+        "openai_api",
+        "verifications",
+        "tests",
+        "llama-stack",
+        ""
+      ],
+      "metadata": {
+        "model": "gpt-4o-mini",
+        "case_id": "stream=True"
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+        "outcome": "passed"
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         "outcome": "passed"
       }
     }
   ],
-  "run_timestamp": 1744841358
+  "run_timestamp": 1744915699
 }
diff --git a/tests/verifications/test_results/together.json b/tests/verifications/test_results/together.json
index 4ee3f7546..0075763bc 100644
--- a/tests/verifications/test_results/together.json
+++ b/tests/verifications/test_results/together.json
@@ -1,15 +1,15 @@
 {
-  "created": 1744841154.6007879,
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+  "created": 1744915672.332456,
+  "duration": 157.25543904304504,
   "exitcode": 1,
-  "root": "/Users/erichuang/projects/llama-stack",
+  "root": "/home/erichuang/llama-stack",
   "environment": {},
   "summary": {
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@@ -29,392 +29,422 @@
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           "type": "Function",
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+          "lineno": 95
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           "type": "Function",
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+        {
+          "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_multi_turn_multiple_images[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-stream=False]",
+          "type": "Function",
+          "lineno": 554
+        },
+        {
+          "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_multi_turn_multiple_images[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-stream=True]",
+          "type": "Function",
+          "lineno": 554
         }
       ]
     }
@@ -422,7 +452,7 @@
   "tests": [
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_basic[meta-llama/Llama-3.3-70B-Instruct-Turbo-earth]",
-      "lineno": 74,
+      "lineno": 95,
       "outcome": "passed",
       "keywords": [
         "test_chat_non_streaming_basic[meta-llama/Llama-3.3-70B-Instruct-Turbo-earth]",
@@ -441,21 +471,21 @@
         "case_id": "earth"
       },
       "setup": {
-        "duration": 0.21532604098320007,
+        "duration": 0.11770237609744072,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.9991857919376343,
+        "duration": 0.6406435770913959,
         "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.0001563748810440302,
+        "duration": 0.0002960069105029106,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_basic[meta-llama/Llama-3.3-70B-Instruct-Turbo-saturn]",
-      "lineno": 74,
+      "lineno": 95,
       "outcome": "passed",
       "keywords": [
         "test_chat_non_streaming_basic[meta-llama/Llama-3.3-70B-Instruct-Turbo-saturn]",
@@ -474,21 +504,21 @@
         "case_id": "saturn"
       },
       "setup": {
-        "duration": 0.007130792131647468,
+        "duration": 0.07460446748882532,
         "outcome": "passed"
       },
       "call": {
-        "duration": 1.1308259170036763,
+        "duration": 0.5787241570651531,
         "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.00015199999324977398,
+        "duration": 0.00026445742696523666,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_basic[meta-llama/Llama-4-Scout-17B-16E-Instruct-earth]",
-      "lineno": 74,
+      "lineno": 95,
       "outcome": "passed",
       "keywords": [
         "test_chat_non_streaming_basic[meta-llama/Llama-4-Scout-17B-16E-Instruct-earth]",
@@ -507,21 +537,21 @@
         "case_id": "earth"
       },
       "setup": {
-        "duration": 0.015451540937647223,
+        "duration": 0.07483412884175777,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.8688064580783248,
+        "duration": 0.8699872978031635,
         "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.00015308288857340813,
+        "duration": 0.0002666134387254715,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_basic[meta-llama/Llama-4-Scout-17B-16E-Instruct-saturn]",
-      "lineno": 74,
+      "lineno": 95,
       "outcome": "passed",
       "keywords": [
         "test_chat_non_streaming_basic[meta-llama/Llama-4-Scout-17B-16E-Instruct-saturn]",
@@ -540,21 +570,21 @@
         "case_id": "saturn"
       },
       "setup": {
-        "duration": 0.007731583202257752,
+        "duration": 0.07169668562710285,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.46771004190668464,
+        "duration": 0.5061587328091264,
         "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.0007200830150395632,
+        "duration": 0.00028620287775993347,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_basic[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-earth]",
-      "lineno": 74,
+      "lineno": 95,
       "outcome": "passed",
       "keywords": [
         "test_chat_non_streaming_basic[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-earth]",
@@ -573,21 +603,21 @@
         "case_id": "earth"
       },
       "setup": {
-        "duration": 0.007446125149726868,
+        "duration": 0.0829654112458229,
         "outcome": "passed"
       },
       "call": {
-        "duration": 1.3933757909107953,
+        "duration": 1.2450250089168549,
         "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.002874624915421009,
+        "duration": 0.00024125166237354279,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_basic[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-saturn]",
-      "lineno": 74,
+      "lineno": 95,
       "outcome": "passed",
       "keywords": [
         "test_chat_non_streaming_basic[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-saturn]",
@@ -606,21 +636,21 @@
         "case_id": "saturn"
       },
       "setup": {
-        "duration": 0.01013387506827712,
+        "duration": 0.07169047556817532,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.39105829200707376,
+        "duration": 0.7659840155392885,
         "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.00015466706827282906,
+        "duration": 0.00023942161351442337,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_basic[meta-llama/Llama-3.3-70B-Instruct-Turbo-earth]",
-      "lineno": 93,
+      "lineno": 114,
       "outcome": "passed",
       "keywords": [
         "test_chat_streaming_basic[meta-llama/Llama-3.3-70B-Instruct-Turbo-earth]",
@@ -639,21 +669,21 @@
         "case_id": "earth"
       },
       "setup": {
-        "duration": 0.008418583078309894,
+        "duration": 0.0718865105882287,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.4248087501619011,
+        "duration": 0.9115259740501642,
         "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.00016704201698303223,
+        "duration": 0.0002334779128432274,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_basic[meta-llama/Llama-3.3-70B-Instruct-Turbo-saturn]",
-      "lineno": 93,
+      "lineno": 114,
       "outcome": "passed",
       "keywords": [
         "test_chat_streaming_basic[meta-llama/Llama-3.3-70B-Instruct-Turbo-saturn]",
@@ -672,21 +702,21 @@
         "case_id": "saturn"
       },
       "setup": {
-        "duration": 0.007518124999478459,
+        "duration": 0.07380938995629549,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.7563416250050068,
+        "duration": 0.9997824784368277,
         "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.00016262498684227467,
+        "duration": 0.00029965396970510483,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_basic[meta-llama/Llama-4-Scout-17B-16E-Instruct-earth]",
-      "lineno": 93,
+      "lineno": 114,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_basic[meta-llama/Llama-4-Scout-17B-16E-Instruct-earth]",
@@ -705,34 +735,34 @@
         "case_id": "earth"
       },
       "setup": {
-        "duration": 0.009950791951268911,
+        "duration": 0.07564573176205158,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.2686829590238631,
+        "duration": 0.7452597729861736,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 111,
+          "path": "/home/erichuang/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
+          "lineno": 132,
           "message": "IndexError: list index out of range"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 111,
+            "lineno": 132,
             "message": "IndexError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_basic[meta-llama/Llama-4-Scout-17B-16E-Instruct-earth]>>\nopenai_client = <openai.OpenAI object at 0x10c61d7e0>\nmodel = 'meta-llama/Llama-4-Scout-17B-16E-Instruct', provider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'earth', 'input': {'messages': [{'content': 'Which planet do humans live on?', 'role': 'user'}]}, 'output': 'Earth'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_basic\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_basic(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            stream=True,\n        )\n        content = \"\"\n        for chunk in response:\n>           content += chunk.choices[0].delta.content or \"\"\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:111: IndexError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_basic[meta-llama/Llama-4-Scout-17B-16E-Instruct-earth]>>\nopenai_client = <openai.OpenAI object at 0x7f31280cf760>\nmodel = 'meta-llama/Llama-4-Scout-17B-16E-Instruct', provider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'earth', 'input': {'messages': [{'content': 'Which planet do humans live on?', 'role': 'user'}]}, 'output': 'Earth'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_basic\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_basic(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            stream=True,\n        )\n        content = \"\"\n        for chunk in response:\n>           content += chunk.choices[0].delta.content or \"\"\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:132: IndexError"
       },
       "teardown": {
-        "duration": 0.0002637500874698162,
+        "duration": 0.0003521796315908432,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_basic[meta-llama/Llama-4-Scout-17B-16E-Instruct-saturn]",
-      "lineno": 93,
+      "lineno": 114,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_basic[meta-llama/Llama-4-Scout-17B-16E-Instruct-saturn]",
@@ -751,34 +781,34 @@
         "case_id": "saturn"
       },
       "setup": {
-        "duration": 0.011679667048156261,
+        "duration": 0.07307655736804008,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.4552199998870492,
+        "duration": 0.45107892248779535,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 111,
+          "path": "/home/erichuang/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
+          "lineno": 132,
           "message": "IndexError: list index out of range"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 111,
+            "lineno": 132,
             "message": "IndexError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_basic[meta-llama/Llama-4-Scout-17B-16E-Instruct-saturn]>>\nopenai_client = <openai.OpenAI object at 0x10c61c4f0>\nmodel = 'meta-llama/Llama-4-Scout-17B-16E-Instruct', provider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'saturn', 'input': {'messages': [{'content': 'Which planet has rings around it with a name starting with letter S?', 'role': 'user'}]}, 'output': 'Saturn'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_basic\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_basic(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            stream=True,\n        )\n        content = \"\"\n        for chunk in response:\n>           content += chunk.choices[0].delta.content or \"\"\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:111: IndexError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_basic[meta-llama/Llama-4-Scout-17B-16E-Instruct-saturn]>>\nopenai_client = <openai.OpenAI object at 0x7f3127f38040>\nmodel = 'meta-llama/Llama-4-Scout-17B-16E-Instruct', provider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'saturn', 'input': {'messages': [{'content': 'Which planet has rings around it with a name starting with letter S?', 'role': 'user'}]}, 'output': 'Saturn'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_basic\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_basic(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            stream=True,\n        )\n        content = \"\"\n        for chunk in response:\n>           content += chunk.choices[0].delta.content or \"\"\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:132: IndexError"
       },
       "teardown": {
-        "duration": 0.00024562515318393707,
+        "duration": 0.00031046755611896515,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_basic[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-earth]",
-      "lineno": 93,
+      "lineno": 114,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_basic[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-earth]",
@@ -797,34 +827,34 @@
         "case_id": "earth"
       },
       "setup": {
-        "duration": 0.007694624830037355,
+        "duration": 0.07041068747639656,
         "outcome": "passed"
       },
       "call": {
-        "duration": 1.998882583109662,
+        "duration": 1.1565949888899922,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 111,
+          "path": "/home/erichuang/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
+          "lineno": 132,
           "message": "IndexError: list index out of range"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 111,
+            "lineno": 132,
             "message": "IndexError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_basic[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-earth]>>\nopenai_client = <openai.OpenAI object at 0x10c175810>\nmodel = 'meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8'\nprovider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'earth', 'input': {'messages': [{'content': 'Which planet do humans live on?', 'role': 'user'}]}, 'output': 'Earth'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_basic\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_basic(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            stream=True,\n        )\n        content = \"\"\n        for chunk in response:\n>           content += chunk.choices[0].delta.content or \"\"\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:111: IndexError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_basic[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-earth]>>\nopenai_client = <openai.OpenAI object at 0x7f3127f64370>\nmodel = 'meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8'\nprovider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'earth', 'input': {'messages': [{'content': 'Which planet do humans live on?', 'role': 'user'}]}, 'output': 'Earth'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_basic\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_basic(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            stream=True,\n        )\n        content = \"\"\n        for chunk in response:\n>           content += chunk.choices[0].delta.content or \"\"\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:132: IndexError"
       },
       "teardown": {
-        "duration": 0.00022433395497500896,
+        "duration": 0.0002977624535560608,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_basic[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-saturn]",
-      "lineno": 93,
+      "lineno": 114,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_basic[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-saturn]",
@@ -843,34 +873,34 @@
         "case_id": "saturn"
       },
       "setup": {
-        "duration": 0.006812750129029155,
+        "duration": 0.07026446517556906,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.34369166707620025,
+        "duration": 0.7347098160535097,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 111,
+          "path": "/home/erichuang/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
+          "lineno": 132,
           "message": "IndexError: list index out of range"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 111,
+            "lineno": 132,
             "message": "IndexError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_basic[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-saturn]>>\nopenai_client = <openai.OpenAI object at 0x10c61c7c0>\nmodel = 'meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8'\nprovider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'saturn', 'input': {'messages': [{'content': 'Which planet has rings around it with a name starting with letter S?', 'role': 'user'}]}, 'output': 'Saturn'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_basic\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_basic(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            stream=True,\n        )\n        content = \"\"\n        for chunk in response:\n>           content += chunk.choices[0].delta.content or \"\"\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:111: IndexError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_basic[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-saturn]>>\nopenai_client = <openai.OpenAI object at 0x7f31280cf3a0>\nmodel = 'meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8'\nprovider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'saturn', 'input': {'messages': [{'content': 'Which planet has rings around it with a name starting with letter S?', 'role': 'user'}]}, 'output': 'Saturn'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_basic\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_basic(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            stream=True,\n        )\n        content = \"\"\n        for chunk in response:\n>           content += chunk.choices[0].delta.content or \"\"\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:132: IndexError"
       },
       "teardown": {
-        "duration": 0.00029608397744596004,
+        "duration": 0.000298389233648777,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_image[meta-llama/Llama-3.3-70B-Instruct-Turbo-case0]",
-      "lineno": 117,
+      "lineno": 138,
       "outcome": "skipped",
       "keywords": [
         "test_chat_non_streaming_image[meta-llama/Llama-3.3-70B-Instruct-Turbo-case0]",
@@ -889,22 +919,22 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.006911124801263213,
+        "duration": 0.07295764330774546,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.00013570813462138176,
+        "duration": 0.0002657398581504822,
         "outcome": "skipped",
-        "longrepr": "('/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py', 126, 'Skipped: Skipping test_chat_non_streaming_image for model meta-llama/Llama-3.3-70B-Instruct-Turbo on provider together based on config.')"
+        "longrepr": "('/home/erichuang/llama-stack/tests/verifications/openai_api/test_chat_completion.py', 147, 'Skipped: Skipping test_chat_non_streaming_image for model meta-llama/Llama-3.3-70B-Instruct-Turbo on provider together based on config.')"
       },
       "teardown": {
-        "duration": 0.00011799996718764305,
+        "duration": 0.00035269279032945633,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_image[meta-llama/Llama-4-Scout-17B-16E-Instruct-case0]",
-      "lineno": 117,
+      "lineno": 138,
       "outcome": "passed",
       "keywords": [
         "test_chat_non_streaming_image[meta-llama/Llama-4-Scout-17B-16E-Instruct-case0]",
@@ -923,21 +953,21 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.007865542080253363,
+        "duration": 0.07182978931814432,
         "outcome": "passed"
       },
       "call": {
-        "duration": 2.211856249952689,
+        "duration": 1.746746251359582,
         "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.00015016691759228706,
+        "duration": 0.00026807747781276703,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_image[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-case0]",
-      "lineno": 117,
+      "lineno": 138,
       "outcome": "passed",
       "keywords": [
         "test_chat_non_streaming_image[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-case0]",
@@ -956,21 +986,21 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.007291208021342754,
+        "duration": 0.07101599592715502,
         "outcome": "passed"
       },
       "call": {
-        "duration": 4.980133082950488,
+        "duration": 5.472218153998256,
         "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.0002584999892860651,
+        "duration": 0.00029551703482866287,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_image[meta-llama/Llama-3.3-70B-Instruct-Turbo-case0]",
-      "lineno": 136,
+      "lineno": 157,
       "outcome": "skipped",
       "keywords": [
         "test_chat_streaming_image[meta-llama/Llama-3.3-70B-Instruct-Turbo-case0]",
@@ -989,22 +1019,22 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.009254832984879613,
+        "duration": 0.07391759566962719,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.00016950001008808613,
+        "duration": 0.00026184599846601486,
         "outcome": "skipped",
-        "longrepr": "('/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py', 145, 'Skipped: Skipping test_chat_streaming_image for model meta-llama/Llama-3.3-70B-Instruct-Turbo on provider together based on config.')"
+        "longrepr": "('/home/erichuang/llama-stack/tests/verifications/openai_api/test_chat_completion.py', 166, 'Skipped: Skipping test_chat_streaming_image for model meta-llama/Llama-3.3-70B-Instruct-Turbo on provider together based on config.')"
       },
       "teardown": {
-        "duration": 0.0001239590346813202,
+        "duration": 0.0002144472673535347,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_image[meta-llama/Llama-4-Scout-17B-16E-Instruct-case0]",
-      "lineno": 136,
+      "lineno": 157,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_image[meta-llama/Llama-4-Scout-17B-16E-Instruct-case0]",
@@ -1023,34 +1053,34 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.019581791944801807,
+        "duration": 0.08702181186527014,
         "outcome": "passed"
       },
       "call": {
-        "duration": 1.487935832934454,
+        "duration": 2.685878618620336,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 154,
+          "path": "/home/erichuang/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
+          "lineno": 175,
           "message": "IndexError: list index out of range"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 154,
+            "lineno": 175,
             "message": "IndexError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_image[meta-llama/Llama-4-Scout-17B-16E-Instruct-case0]>>\nopenai_client = <openai.OpenAI object at 0x10c6a37f0>\nmodel = 'meta-llama/Llama-4-Scout-17B-16E-Instruct', provider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': [{'text': 'What is in this image?', 'type': 'text'}, {'image_url': {...}, 'type': 'image_url'}], 'role': 'user'}]}, 'output': 'llama'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_image\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_image(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            stream=True,\n        )\n        content = \"\"\n        for chunk in response:\n>           content += chunk.choices[0].delta.content or \"\"\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:154: IndexError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_image[meta-llama/Llama-4-Scout-17B-16E-Instruct-case0]>>\nopenai_client = <openai.OpenAI object at 0x7f3127e67430>\nmodel = 'meta-llama/Llama-4-Scout-17B-16E-Instruct', provider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': [{'text': 'What is in this image?', 'type': 'text'}, {'image_url': {...}, 'type': 'image_url'}], 'role': 'user'}]}, 'output': 'llama'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_image\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_image(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            stream=True,\n        )\n        content = \"\"\n        for chunk in response:\n>           content += chunk.choices[0].delta.content or \"\"\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:175: IndexError"
       },
       "teardown": {
-        "duration": 0.00024645915254950523,
+        "duration": 0.00031331367790699005,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_image[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-case0]",
-      "lineno": 136,
+      "lineno": 157,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_image[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-case0]",
@@ -1069,34 +1099,34 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.01211779098957777,
+        "duration": 0.07287734653800726,
         "outcome": "passed"
       },
       "call": {
-        "duration": 3.920052665984258,
+        "duration": 3.985588035546243,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 154,
+          "path": "/home/erichuang/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
+          "lineno": 175,
           "message": "IndexError: list index out of range"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 154,
+            "lineno": 175,
             "message": "IndexError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_image[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-case0]>>\nopenai_client = <openai.OpenAI object at 0x10c175f30>\nmodel = 'meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8'\nprovider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': [{'text': 'What is in this image?', 'type': 'text'}, {'image_url': {...}, 'type': 'image_url'}], 'role': 'user'}]}, 'output': 'llama'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_image\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_image(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            stream=True,\n        )\n        content = \"\"\n        for chunk in response:\n>           content += chunk.choices[0].delta.content or \"\"\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:154: IndexError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_image[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-case0]>>\nopenai_client = <openai.OpenAI object at 0x7f3127e42980>\nmodel = 'meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8'\nprovider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': [{'text': 'What is in this image?', 'type': 'text'}, {'image_url': {...}, 'type': 'image_url'}], 'role': 'user'}]}, 'output': 'llama'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_image\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_image(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            stream=True,\n        )\n        content = \"\"\n        for chunk in response:\n>           content += chunk.choices[0].delta.content or \"\"\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:175: IndexError"
       },
       "teardown": {
-        "duration": 0.00047275004908442497,
+        "duration": 0.0002881418913602829,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_structured_output[meta-llama/Llama-3.3-70B-Instruct-Turbo-calendar]",
-      "lineno": 160,
+      "lineno": 181,
       "outcome": "passed",
       "keywords": [
         "test_chat_non_streaming_structured_output[meta-llama/Llama-3.3-70B-Instruct-Turbo-calendar]",
@@ -1115,21 +1145,21 @@
         "case_id": "calendar"
       },
       "setup": {
-        "duration": 0.01848520804196596,
+        "duration": 0.07055713329464197,
         "outcome": "passed"
       },
       "call": {
-        "duration": 1.4586717090569437,
+        "duration": 0.7881239131093025,
         "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.0002318748738616705,
+        "duration": 0.00024167727679014206,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_structured_output[meta-llama/Llama-3.3-70B-Instruct-Turbo-math]",
-      "lineno": 160,
+      "lineno": 181,
       "outcome": "passed",
       "keywords": [
         "test_chat_non_streaming_structured_output[meta-llama/Llama-3.3-70B-Instruct-Turbo-math]",
@@ -1148,21 +1178,21 @@
         "case_id": "math"
       },
       "setup": {
-        "duration": 0.0069474580232053995,
+        "duration": 0.07159801851958036,
         "outcome": "passed"
       },
       "call": {
-        "duration": 2.9735800828784704,
+        "duration": 4.972125994041562,
         "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.00016279099509119987,
+        "duration": 0.0002335989847779274,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_structured_output[meta-llama/Llama-4-Scout-17B-16E-Instruct-calendar]",
-      "lineno": 160,
+      "lineno": 181,
       "outcome": "passed",
       "keywords": [
         "test_chat_non_streaming_structured_output[meta-llama/Llama-4-Scout-17B-16E-Instruct-calendar]",
@@ -1181,21 +1211,21 @@
         "case_id": "calendar"
       },
       "setup": {
-        "duration": 0.006996707990765572,
+        "duration": 0.07872365694493055,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.6836131250020117,
+        "duration": 0.5325954724103212,
         "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.00015366706065833569,
+        "duration": 0.0002604750916361809,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_structured_output[meta-llama/Llama-4-Scout-17B-16E-Instruct-math]",
-      "lineno": 160,
+      "lineno": 181,
       "outcome": "passed",
       "keywords": [
         "test_chat_non_streaming_structured_output[meta-llama/Llama-4-Scout-17B-16E-Instruct-math]",
@@ -1214,21 +1244,21 @@
         "case_id": "math"
       },
       "setup": {
-        "duration": 0.0066205840557813644,
+        "duration": 0.07101414445787668,
         "outcome": "passed"
       },
       "call": {
-        "duration": 3.5288485831115395,
+        "duration": 2.5978550128638744,
         "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.00015287497080862522,
+        "duration": 0.00032774079591035843,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_structured_output[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-calendar]",
-      "lineno": 160,
+      "lineno": 181,
       "outcome": "passed",
       "keywords": [
         "test_chat_non_streaming_structured_output[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-calendar]",
@@ -1247,21 +1277,21 @@
         "case_id": "calendar"
       },
       "setup": {
-        "duration": 0.007501666899770498,
+        "duration": 0.0737495282664895,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.5137577499262989,
+        "duration": 0.7547545190900564,
         "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.00015366706065833569,
+        "duration": 0.00024818163365125656,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_structured_output[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-math]",
-      "lineno": 160,
+      "lineno": 181,
       "outcome": "passed",
       "keywords": [
         "test_chat_non_streaming_structured_output[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-math]",
@@ -1280,21 +1310,21 @@
         "case_id": "math"
       },
       "setup": {
-        "duration": 0.0072085000574588776,
+        "duration": 0.07616753969341516,
         "outcome": "passed"
       },
       "call": {
-        "duration": 2.893309208098799,
+        "duration": 4.4260268323123455,
         "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.00017254101112484932,
+        "duration": 0.00023849774152040482,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_structured_output[meta-llama/Llama-3.3-70B-Instruct-Turbo-calendar]",
-      "lineno": 183,
+      "lineno": 204,
       "outcome": "passed",
       "keywords": [
         "test_chat_streaming_structured_output[meta-llama/Llama-3.3-70B-Instruct-Turbo-calendar]",
@@ -1313,21 +1343,21 @@
         "case_id": "calendar"
       },
       "setup": {
-        "duration": 0.006752792047336698,
+        "duration": 0.07280991226434708,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.520758124999702,
+        "duration": 1.2391796316951513,
         "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.00022079190239310265,
+        "duration": 0.00022371485829353333,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_structured_output[meta-llama/Llama-3.3-70B-Instruct-Turbo-math]",
-      "lineno": 183,
+      "lineno": 204,
       "outcome": "passed",
       "keywords": [
         "test_chat_streaming_structured_output[meta-llama/Llama-3.3-70B-Instruct-Turbo-math]",
@@ -1346,21 +1376,21 @@
         "case_id": "math"
       },
       "setup": {
-        "duration": 0.008957375073805451,
+        "duration": 0.07361716963350773,
         "outcome": "passed"
       },
       "call": {
-        "duration": 15.490330374799669,
+        "duration": 6.5637129517272115,
         "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.00014704209752380848,
+        "duration": 0.00024466682225465775,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_structured_output[meta-llama/Llama-4-Scout-17B-16E-Instruct-calendar]",
-      "lineno": 183,
+      "lineno": 204,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_structured_output[meta-llama/Llama-4-Scout-17B-16E-Instruct-calendar]",
@@ -1379,34 +1409,34 @@
         "case_id": "calendar"
       },
       "setup": {
-        "duration": 0.007771959062665701,
+        "duration": 0.07750869635492563,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.644345791079104,
+        "duration": 0.6057027634233236,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 202,
+          "path": "/home/erichuang/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
+          "lineno": 223,
           "message": "IndexError: list index out of range"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 202,
+            "lineno": 223,
             "message": "IndexError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_structured_output[meta-llama/Llama-4-Scout-17B-16E-Instruct-calendar]>>\nopenai_client = <openai.OpenAI object at 0x10c6bdb40>\nmodel = 'meta-llama/Llama-4-Scout-17B-16E-Instruct', provider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'calendar', 'input': {'messages': [{'content': 'Extract the event information.', 'role': 'system'}, {'cont...articipants'], 'title': 'CalendarEvent', 'type': 'object'}}, 'type': 'json_schema'}}, 'output': 'valid_calendar_event'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_structured_output\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_structured_output(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            response_format=case[\"input\"][\"response_format\"],\n            stream=True,\n        )\n        maybe_json_content = \"\"\n        for chunk in response:\n>           maybe_json_content += chunk.choices[0].delta.content or \"\"\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:202: IndexError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_structured_output[meta-llama/Llama-4-Scout-17B-16E-Instruct-calendar]>>\nopenai_client = <openai.OpenAI object at 0x7f3127eb4c70>\nmodel = 'meta-llama/Llama-4-Scout-17B-16E-Instruct', provider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'calendar', 'input': {'messages': [{'content': 'Extract the event information.', 'role': 'system'}, {'cont...articipants'], 'title': 'CalendarEvent', 'type': 'object'}}, 'type': 'json_schema'}}, 'output': 'valid_calendar_event'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_structured_output\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_structured_output(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            response_format=case[\"input\"][\"response_format\"],\n            stream=True,\n        )\n        maybe_json_content = \"\"\n        for chunk in response:\n>           maybe_json_content += chunk.choices[0].delta.content or \"\"\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:223: IndexError"
       },
       "teardown": {
-        "duration": 0.00024341698735952377,
+        "duration": 0.00031183846294879913,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_structured_output[meta-llama/Llama-4-Scout-17B-16E-Instruct-math]",
-      "lineno": 183,
+      "lineno": 204,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_structured_output[meta-llama/Llama-4-Scout-17B-16E-Instruct-math]",
@@ -1425,34 +1455,34 @@
         "case_id": "math"
       },
       "setup": {
-        "duration": 0.008734249975532293,
+        "duration": 0.0722011923789978,
         "outcome": "passed"
       },
       "call": {
-        "duration": 4.31767199980095,
+        "duration": 3.635944495908916,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 202,
+          "path": "/home/erichuang/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
+          "lineno": 223,
           "message": "IndexError: list index out of range"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 202,
+            "lineno": 223,
             "message": "IndexError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_structured_output[meta-llama/Llama-4-Scout-17B-16E-Instruct-math]>>\nopenai_client = <openai.OpenAI object at 0x10ca5bc10>\nmodel = 'meta-llama/Llama-4-Scout-17B-16E-Instruct', provider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'math', 'input': {'messages': [{'content': 'You are a helpful math tutor. Guide the user through the solut... ['steps', 'final_answer'], 'title': 'MathReasoning', ...}}, 'type': 'json_schema'}}, 'output': 'valid_math_reasoning'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_structured_output\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_structured_output(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            response_format=case[\"input\"][\"response_format\"],\n            stream=True,\n        )\n        maybe_json_content = \"\"\n        for chunk in response:\n>           maybe_json_content += chunk.choices[0].delta.content or \"\"\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:202: IndexError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_structured_output[meta-llama/Llama-4-Scout-17B-16E-Instruct-math]>>\nopenai_client = <openai.OpenAI object at 0x7f3127eb4370>\nmodel = 'meta-llama/Llama-4-Scout-17B-16E-Instruct', provider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'math', 'input': {'messages': [{'content': 'You are a helpful math tutor. Guide the user through the solut... ['steps', 'final_answer'], 'title': 'MathReasoning', ...}}, 'type': 'json_schema'}}, 'output': 'valid_math_reasoning'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_structured_output\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_structured_output(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            response_format=case[\"input\"][\"response_format\"],\n            stream=True,\n        )\n        maybe_json_content = \"\"\n        for chunk in response:\n>           maybe_json_content += chunk.choices[0].delta.content or \"\"\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:223: IndexError"
       },
       "teardown": {
-        "duration": 0.00026674987748265266,
+        "duration": 0.00029693637043237686,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_structured_output[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-calendar]",
-      "lineno": 183,
+      "lineno": 204,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_structured_output[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-calendar]",
@@ -1471,34 +1501,34 @@
         "case_id": "calendar"
       },
       "setup": {
-        "duration": 0.006908582989126444,
+        "duration": 0.07182575855404139,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.46308279200457036,
+        "duration": 0.583567344583571,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 202,
+          "path": "/home/erichuang/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
+          "lineno": 223,
           "message": "IndexError: list index out of range"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 202,
+            "lineno": 223,
             "message": "IndexError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_structured_output[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-calendar]>>\nopenai_client = <openai.OpenAI object at 0x10b7bffa0>\nmodel = 'meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8'\nprovider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'calendar', 'input': {'messages': [{'content': 'Extract the event information.', 'role': 'system'}, {'cont...articipants'], 'title': 'CalendarEvent', 'type': 'object'}}, 'type': 'json_schema'}}, 'output': 'valid_calendar_event'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_structured_output\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_structured_output(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            response_format=case[\"input\"][\"response_format\"],\n            stream=True,\n        )\n        maybe_json_content = \"\"\n        for chunk in response:\n>           maybe_json_content += chunk.choices[0].delta.content or \"\"\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:202: IndexError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_structured_output[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-calendar]>>\nopenai_client = <openai.OpenAI object at 0x7f3127e37f70>\nmodel = 'meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8'\nprovider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'calendar', 'input': {'messages': [{'content': 'Extract the event information.', 'role': 'system'}, {'cont...articipants'], 'title': 'CalendarEvent', 'type': 'object'}}, 'type': 'json_schema'}}, 'output': 'valid_calendar_event'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_structured_output\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_structured_output(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            response_format=case[\"input\"][\"response_format\"],\n            stream=True,\n        )\n        maybe_json_content = \"\"\n        for chunk in response:\n>           maybe_json_content += chunk.choices[0].delta.content or \"\"\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:223: IndexError"
       },
       "teardown": {
-        "duration": 0.0003908751532435417,
+        "duration": 0.0002760365605354309,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_structured_output[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-math]",
-      "lineno": 183,
+      "lineno": 204,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_structured_output[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-math]",
@@ -1517,34 +1547,34 @@
         "case_id": "math"
       },
       "setup": {
-        "duration": 0.0073979999870061874,
+        "duration": 0.07146896701306105,
         "outcome": "passed"
       },
       "call": {
-        "duration": 2.537265666993335,
+        "duration": 3.9762256713584065,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 202,
+          "path": "/home/erichuang/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
+          "lineno": 223,
           "message": "IndexError: list index out of range"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 202,
+            "lineno": 223,
             "message": "IndexError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_structured_output[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-math]>>\nopenai_client = <openai.OpenAI object at 0x10c6c5d50>\nmodel = 'meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8'\nprovider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'math', 'input': {'messages': [{'content': 'You are a helpful math tutor. Guide the user through the solut... ['steps', 'final_answer'], 'title': 'MathReasoning', ...}}, 'type': 'json_schema'}}, 'output': 'valid_math_reasoning'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_structured_output\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_structured_output(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            response_format=case[\"input\"][\"response_format\"],\n            stream=True,\n        )\n        maybe_json_content = \"\"\n        for chunk in response:\n>           maybe_json_content += chunk.choices[0].delta.content or \"\"\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:202: IndexError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_structured_output[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-math]>>\nopenai_client = <openai.OpenAI object at 0x7f3127e656f0>\nmodel = 'meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8'\nprovider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'math', 'input': {'messages': [{'content': 'You are a helpful math tutor. Guide the user through the solut... ['steps', 'final_answer'], 'title': 'MathReasoning', ...}}, 'type': 'json_schema'}}, 'output': 'valid_math_reasoning'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_chat_structured_output\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_structured_output(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            response_format=case[\"input\"][\"response_format\"],\n            stream=True,\n        )\n        maybe_json_content = \"\"\n        for chunk in response:\n>           maybe_json_content += chunk.choices[0].delta.content or \"\"\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:223: IndexError"
       },
       "teardown": {
-        "duration": 0.00026933313347399235,
+        "duration": 0.00030822213739156723,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_tool_calling[meta-llama/Llama-3.3-70B-Instruct-Turbo-case0]",
-      "lineno": 205,
+      "lineno": 226,
       "outcome": "passed",
       "keywords": [
         "test_chat_non_streaming_tool_calling[meta-llama/Llama-3.3-70B-Instruct-Turbo-case0]",
@@ -1563,21 +1593,21 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.007018249947577715,
+        "duration": 0.07303964532911777,
         "outcome": "passed"
       },
       "call": {
-        "duration": 1.0225670000072569,
+        "duration": 0.7525951210409403,
         "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.00030558393336832523,
+        "duration": 0.0002357764169573784,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-case0]",
-      "lineno": 205,
+      "lineno": 226,
       "outcome": "passed",
       "keywords": [
         "test_chat_non_streaming_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-case0]",
@@ -1596,21 +1626,21 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.007612749934196472,
+        "duration": 0.07376459613442421,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.35967333405278623,
+        "duration": 0.4931257301941514,
         "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.00023795804008841515,
+        "duration": 0.0002181418240070343,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_tool_calling[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-case0]",
-      "lineno": 205,
+      "lineno": 226,
       "outcome": "passed",
       "keywords": [
         "test_chat_non_streaming_tool_calling[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-case0]",
@@ -1629,21 +1659,21 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.007069834042340517,
+        "duration": 0.07053922209888697,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.3653114167973399,
+        "duration": 0.5402723103761673,
         "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.00015424983575940132,
+        "duration": 0.00022673048079013824,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_tool_calling[meta-llama/Llama-3.3-70B-Instruct-Turbo-case0]",
-      "lineno": 229,
+      "lineno": 250,
       "outcome": "passed",
       "keywords": [
         "test_chat_streaming_tool_calling[meta-llama/Llama-3.3-70B-Instruct-Turbo-case0]",
@@ -1662,21 +1692,21 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.007679749978706241,
+        "duration": 0.07116104569286108,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.5530709580052644,
+        "duration": 0.816182347945869,
         "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.00016416702419519424,
+        "duration": 0.0003773067146539688,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-case0]",
-      "lineno": 229,
+      "lineno": 250,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-case0]",
@@ -1695,39 +1725,39 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.007491416065022349,
+        "duration": 0.07258457317948341,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.4884651671163738,
+        "duration": 0.4603788387030363,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 588,
+          "path": "/home/erichuang/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
+          "lineno": 688,
           "message": "IndexError: list index out of range"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 247,
+            "lineno": 268,
             "message": ""
           },
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 588,
+            "lineno": 688,
             "message": "IndexError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-case0]>>\nopenai_client = <openai.OpenAI object at 0x10ca426b0>\nmodel = 'meta-llama/Llama-4-Scout-17B-16E-Instruct', provider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_tool_calling(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        stream = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            stream=True,\n        )\n    \n>       _, tool_calls_buffer = _accumulate_streaming_tool_calls(stream)\n\ntests/verifications/openai_api/test_chat_completion.py:247: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nstream = <openai.Stream object at 0x10caac9d0>\n\n    def _accumulate_streaming_tool_calls(stream):\n        \"\"\"Accumulates tool calls and content from a streaming ChatCompletion response.\"\"\"\n        tool_calls_buffer = {}\n        current_id = None\n        full_content = \"\"  # Initialize content accumulator\n        # Process streaming chunks\n        for chunk in stream:\n>           choice = chunk.choices[0]\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:588: IndexError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-case0]>>\nopenai_client = <openai.OpenAI object at 0x7f3127e40610>\nmodel = 'meta-llama/Llama-4-Scout-17B-16E-Instruct', provider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_tool_calling(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        stream = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            stream=True,\n        )\n    \n>       _, tool_calls_buffer = _accumulate_streaming_tool_calls(stream)\n\ntests/verifications/openai_api/test_chat_completion.py:268: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nstream = <openai.Stream object at 0x7f3127f53190>\n\n    def _accumulate_streaming_tool_calls(stream):\n        \"\"\"Accumulates tool calls and content from a streaming ChatCompletion response.\"\"\"\n        tool_calls_buffer = {}\n        current_id = None\n        full_content = \"\"  # Initialize content accumulator\n        # Process streaming chunks\n        for chunk in stream:\n>           choice = chunk.choices[0]\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:688: IndexError"
       },
       "teardown": {
-        "duration": 0.0002495420631021261,
+        "duration": 0.0003149937838315964,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_tool_calling[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-case0]",
-      "lineno": 229,
+      "lineno": 250,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_tool_calling[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-case0]",
@@ -1746,39 +1776,39 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.00810704194009304,
+        "duration": 0.07071060407906771,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.4408426668960601,
+        "duration": 0.5184564171358943,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 588,
+          "path": "/home/erichuang/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
+          "lineno": 688,
           "message": "IndexError: list index out of range"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 247,
+            "lineno": 268,
             "message": ""
           },
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 588,
+            "lineno": 688,
             "message": "IndexError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_tool_calling[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-case0]>>\nopenai_client = <openai.OpenAI object at 0x10c000400>\nmodel = 'meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8'\nprovider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_tool_calling(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        stream = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            stream=True,\n        )\n    \n>       _, tool_calls_buffer = _accumulate_streaming_tool_calls(stream)\n\ntests/verifications/openai_api/test_chat_completion.py:247: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nstream = <openai.Stream object at 0x10caaeec0>\n\n    def _accumulate_streaming_tool_calls(stream):\n        \"\"\"Accumulates tool calls and content from a streaming ChatCompletion response.\"\"\"\n        tool_calls_buffer = {}\n        current_id = None\n        full_content = \"\"  # Initialize content accumulator\n        # Process streaming chunks\n        for chunk in stream:\n>           choice = chunk.choices[0]\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:588: IndexError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_tool_calling[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-case0]>>\nopenai_client = <openai.OpenAI object at 0x7f3127e9fbe0>\nmodel = 'meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8'\nprovider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_tool_calling(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        stream = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            stream=True,\n        )\n    \n>       _, tool_calls_buffer = _accumulate_streaming_tool_calls(stream)\n\ntests/verifications/openai_api/test_chat_completion.py:268: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nstream = <openai.Stream object at 0x7f3127ec75b0>\n\n    def _accumulate_streaming_tool_calls(stream):\n        \"\"\"Accumulates tool calls and content from a streaming ChatCompletion response.\"\"\"\n        tool_calls_buffer = {}\n        current_id = None\n        full_content = \"\"  # Initialize content accumulator\n        # Process streaming chunks\n        for chunk in stream:\n>           choice = chunk.choices[0]\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:688: IndexError"
       },
       "teardown": {
-        "duration": 0.0002715839073061943,
+        "duration": 0.00034826435148715973,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_tool_choice_required[meta-llama/Llama-3.3-70B-Instruct-Turbo-case0]",
-      "lineno": 257,
+      "lineno": 278,
       "outcome": "passed",
       "keywords": [
         "test_chat_non_streaming_tool_choice_required[meta-llama/Llama-3.3-70B-Instruct-Turbo-case0]",
@@ -1797,22 +1827,21 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.008122375002130866,
+        "duration": 0.08638827316462994,
         "outcome": "passed"
       },
       "call": {
-        "duration": 1.2647117911837995,
-        "outcome": "passed",
-        "stdout": "ChatCompletion(id='nqNdhnC-2j9zxn-9316fb372a8dcfc8', choices=[Choice(finish_reason='tool_calls', index=0, logprobs=None, message=ChatCompletionMessage(content=None, refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_bmer2gstj7kb3av5poqbufp1', function=Function(arguments='{\"location\":\"San Francisco, USA\"}', name='get_weather'), type='function', index=0)]), seed=14065825304993057000)], created=1744841096, model='meta-llama/Llama-3.3-70B-Instruct-Turbo', object='chat.completion', service_tier=None, system_fingerprint=None, usage=CompletionUsage(completion_tokens=26, prompt_tokens=220, total_tokens=246, completion_tokens_details=None, prompt_tokens_details=None, cached_tokens=0), prompt=[])\n"
+        "duration": 0.9104743050411344,
+        "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.00014750007539987564,
+        "duration": 0.0002754591405391693,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_tool_choice_required[meta-llama/Llama-4-Scout-17B-16E-Instruct-case0]",
-      "lineno": 257,
+      "lineno": 278,
       "outcome": "passed",
       "keywords": [
         "test_chat_non_streaming_tool_choice_required[meta-llama/Llama-4-Scout-17B-16E-Instruct-case0]",
@@ -1831,22 +1860,21 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.00704649998806417,
+        "duration": 0.0742760868743062,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.42037149984389544,
-        "outcome": "passed",
-        "stdout": "ChatCompletion(id='nqNdi94-2j9zxn-9316fb3eef09ebe3', choices=[Choice(finish_reason='tool_calls', index=0, logprobs=None, message=ChatCompletionMessage(content=None, refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_wmv7dk50bsnhnk2poocg0cwl', function=Function(arguments='{\"location\":\"San Francisco\"}', name='get_weather'), type='function', index=0)]), seed=None)], created=1744841098, model='meta-llama/Llama-4-Scout-17B-16E-Instruct', object='chat.completion', service_tier=None, system_fingerprint=None, usage=CompletionUsage(completion_tokens=18, prompt_tokens=198, total_tokens=216, completion_tokens_details=None, prompt_tokens_details=None), prompt=[])\n"
+        "duration": 0.462676758877933,
+        "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.00017291703261435032,
+        "duration": 0.00025860220193862915,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_tool_choice_required[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-case0]",
-      "lineno": 257,
+      "lineno": 278,
       "outcome": "passed",
       "keywords": [
         "test_chat_non_streaming_tool_choice_required[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-case0]",
@@ -1865,22 +1893,21 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.008176584029570222,
+        "duration": 0.07174691930413246,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.3381002079695463,
-        "outcome": "passed",
-        "stdout": "ChatCompletion(id='nqNdiFd-28Eivz-9316fb419863944d', choices=[Choice(finish_reason='tool_calls', index=0, logprobs=None, message=ChatCompletionMessage(content=None, refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_5h00zb6me3342igyllvyrjj7', function=Function(arguments='{\"location\":\"San Francisco\"}', name='get_weather'), type='function', index=0)]), seed=None)], created=1744841098, model='meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8', object='chat.completion', service_tier=None, system_fingerprint=None, usage=CompletionUsage(completion_tokens=18, prompt_tokens=198, total_tokens=216, completion_tokens_details=None, prompt_tokens_details=None), prompt=[])\n"
+        "duration": 0.9501504441723228,
+        "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.00015812506899237633,
+        "duration": 0.0002819998189806938,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_tool_choice_required[meta-llama/Llama-3.3-70B-Instruct-Turbo-case0]",
-      "lineno": 282,
+      "lineno": 302,
       "outcome": "passed",
       "keywords": [
         "test_chat_streaming_tool_choice_required[meta-llama/Llama-3.3-70B-Instruct-Turbo-case0]",
@@ -1899,21 +1926,21 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.009897291893139482,
+        "duration": 0.0707088652998209,
         "outcome": "passed"
       },
       "call": {
-        "duration": 1.5261498331092298,
+        "duration": 1.5536296227946877,
         "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.0002149590291082859,
+        "duration": 0.0002662409096956253,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_tool_choice_required[meta-llama/Llama-4-Scout-17B-16E-Instruct-case0]",
-      "lineno": 282,
+      "lineno": 302,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_tool_choice_required[meta-llama/Llama-4-Scout-17B-16E-Instruct-case0]",
@@ -1932,39 +1959,39 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.007385874865576625,
+        "duration": 0.07114748656749725,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.5376293750014156,
+        "duration": 0.7880472335964441,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 588,
+          "path": "/home/erichuang/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
+          "lineno": 688,
           "message": "IndexError: list index out of range"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 301,
+            "lineno": 321,
             "message": ""
           },
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 588,
+            "lineno": 688,
             "message": "IndexError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_tool_choice_required[meta-llama/Llama-4-Scout-17B-16E-Instruct-case0]>>\nopenai_client = <openai.OpenAI object at 0x10ca42da0>\nmodel = 'meta-llama/Llama-4-Scout-17B-16E-Instruct', provider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],  # Reusing existing case for now\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_tool_choice_required(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        stream = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            tool_choice=\"required\",  # Force tool call\n            stream=True,\n        )\n    \n>       _, tool_calls_buffer = _accumulate_streaming_tool_calls(stream)\n\ntests/verifications/openai_api/test_chat_completion.py:301: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nstream = <openai.Stream object at 0x10ca41b40>\n\n    def _accumulate_streaming_tool_calls(stream):\n        \"\"\"Accumulates tool calls and content from a streaming ChatCompletion response.\"\"\"\n        tool_calls_buffer = {}\n        current_id = None\n        full_content = \"\"  # Initialize content accumulator\n        # Process streaming chunks\n        for chunk in stream:\n>           choice = chunk.choices[0]\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:588: IndexError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_tool_choice_required[meta-llama/Llama-4-Scout-17B-16E-Instruct-case0]>>\nopenai_client = <openai.OpenAI object at 0x7f3127e65210>\nmodel = 'meta-llama/Llama-4-Scout-17B-16E-Instruct', provider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],  # Reusing existing case for now\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_tool_choice_required(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        stream = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            tool_choice=\"required\",  # Force tool call\n            stream=True,\n        )\n    \n>       _, tool_calls_buffer = _accumulate_streaming_tool_calls(stream)\n\ntests/verifications/openai_api/test_chat_completion.py:321: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nstream = <openai.Stream object at 0x7f3127f2cf70>\n\n    def _accumulate_streaming_tool_calls(stream):\n        \"\"\"Accumulates tool calls and content from a streaming ChatCompletion response.\"\"\"\n        tool_calls_buffer = {}\n        current_id = None\n        full_content = \"\"  # Initialize content accumulator\n        # Process streaming chunks\n        for chunk in stream:\n>           choice = chunk.choices[0]\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:688: IndexError"
       },
       "teardown": {
-        "duration": 0.0002947079483419657,
+        "duration": 0.00038287416100502014,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_tool_choice_required[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-case0]",
-      "lineno": 282,
+      "lineno": 302,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_tool_choice_required[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-case0]",
@@ -1983,39 +2010,39 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.008081958163529634,
+        "duration": 0.0964375538751483,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.4107254999689758,
+        "duration": 0.5333329876884818,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 588,
+          "path": "/home/erichuang/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
+          "lineno": 688,
           "message": "IndexError: list index out of range"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 301,
+            "lineno": 321,
             "message": ""
           },
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 588,
+            "lineno": 688,
             "message": "IndexError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_tool_choice_required[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-case0]>>\nopenai_client = <openai.OpenAI object at 0x10ca6b6a0>\nmodel = 'meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8'\nprovider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],  # Reusing existing case for now\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_tool_choice_required(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        stream = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            tool_choice=\"required\",  # Force tool call\n            stream=True,\n        )\n    \n>       _, tool_calls_buffer = _accumulate_streaming_tool_calls(stream)\n\ntests/verifications/openai_api/test_chat_completion.py:301: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nstream = <openai.Stream object at 0x10ca85db0>\n\n    def _accumulate_streaming_tool_calls(stream):\n        \"\"\"Accumulates tool calls and content from a streaming ChatCompletion response.\"\"\"\n        tool_calls_buffer = {}\n        current_id = None\n        full_content = \"\"  # Initialize content accumulator\n        # Process streaming chunks\n        for chunk in stream:\n>           choice = chunk.choices[0]\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:588: IndexError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_tool_choice_required[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-case0]>>\nopenai_client = <openai.OpenAI object at 0x7f3127e27d60>\nmodel = 'meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8'\nprovider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],  # Reusing existing case for now\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_tool_choice_required(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        stream = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            tool_choice=\"required\",  # Force tool call\n            stream=True,\n        )\n    \n>       _, tool_calls_buffer = _accumulate_streaming_tool_calls(stream)\n\ntests/verifications/openai_api/test_chat_completion.py:321: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nstream = <openai.Stream object at 0x7f31280cdae0>\n\n    def _accumulate_streaming_tool_calls(stream):\n        \"\"\"Accumulates tool calls and content from a streaming ChatCompletion response.\"\"\"\n        tool_calls_buffer = {}\n        current_id = None\n        full_content = \"\"  # Initialize content accumulator\n        # Process streaming chunks\n        for chunk in stream:\n>           choice = chunk.choices[0]\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:688: IndexError"
       },
       "teardown": {
-        "duration": 0.00025158398784697056,
+        "duration": 0.0003780834376811981,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_tool_choice_none[meta-llama/Llama-3.3-70B-Instruct-Turbo-case0]",
-      "lineno": 309,
+      "lineno": 329,
       "outcome": "failed",
       "keywords": [
         "test_chat_non_streaming_tool_choice_none[meta-llama/Llama-3.3-70B-Instruct-Turbo-case0]",
@@ -2034,34 +2061,34 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.010461833095178008,
+        "duration": 0.0716709028929472,
         "outcome": "passed"
       },
       "call": {
-        "duration": 1.1223525418899953,
+        "duration": 2.4488353775814176,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 329,
-          "message": "AssertionError: Expected no tool calls when tool_choice='none'\nassert [ChatCompletionMessageToolCall(id='call_g9yti6yqsw38wvtvndlflei7', function=Function(arguments='{\"location\":\"San Francisco, USA\"}', name='get_weather'), type='function', index=0)] is None\n +  where [ChatCompletionMessageToolCall(id='call_g9yti6yqsw38wvtvndlflei7', function=Function(arguments='{\"location\":\"San Francisco, USA\"}', name='get_weather'), type='function', index=0)] = ChatCompletionMessage(content=None, refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_g9yti6yqsw38wvtvndlflei7', function=Function(arguments='{\"location\":\"San Francisco, USA\"}', name='get_weather'), type='function', index=0)]).tool_calls\n +    where ChatCompletionMessage(content=None, refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_g9yti6yqsw38wvtvndlflei7', function=Function(arguments='{\"location\":\"San Francisco, USA\"}', name='get_weather'), type='function', index=0)]) = Choice(finish_reason='tool_calls', index=0, logprobs=None, message=ChatCompletionMessage(content=None, refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_g9yti6yqsw38wvtvndlflei7', function=Function(arguments='{\"location\":\"San Francisco, USA\"}', name='get_weather'), type='function', index=0)]), seed=1754099529794631000).message"
+          "path": "/home/erichuang/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
+          "lineno": 349,
+          "message": "AssertionError: Expected no tool calls when tool_choice='none'\nassert [ChatCompletionMessageToolCall(id='call_efyus3lwok2l7czire0yxkqm', function=Function(arguments='{\"location\":\"San Francisco, USA\"}', name='get_weather'), type='function', index=0)] is None\n +  where [ChatCompletionMessageToolCall(id='call_efyus3lwok2l7czire0yxkqm', function=Function(arguments='{\"location\":\"San Francisco, USA\"}', name='get_weather'), type='function', index=0)] = ChatCompletionMessage(content=None, refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_efyus3lwok2l7czire0yxkqm', function=Function(arguments='{\"location\":\"San Francisco, USA\"}', name='get_weather'), type='function', index=0)]).tool_calls\n +    where ChatCompletionMessage(content=None, refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_efyus3lwok2l7czire0yxkqm', function=Function(arguments='{\"location\":\"San Francisco, USA\"}', name='get_weather'), type='function', index=0)]) = Choice(finish_reason='tool_calls', index=0, logprobs=None, message=ChatCompletionMessage(content=None, refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_efyus3lwok2l7czire0yxkqm', function=Function(arguments='{\"location\":\"San Francisco, USA\"}', name='get_weather'), type='function', index=0)]), seed=10291057599279921000).message"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 329,
+            "lineno": 349,
             "message": "AssertionError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_tool_choice_none[meta-llama/Llama-3.3-70B-Instruct-Turbo-case0]>>\nopenai_client = <openai.OpenAI object at 0x10c6c6560>\nmodel = 'meta-llama/Llama-3.3-70B-Instruct-Turbo', provider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],  # Reusing existing case for now\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_tool_choice_none(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            tool_choice=\"none\",\n            stream=False,\n        )\n    \n        assert response.choices[0].message.role == \"assistant\"\n>       assert response.choices[0].message.tool_calls is None, \"Expected no tool calls when tool_choice='none'\"\nE       AssertionError: Expected no tool calls when tool_choice='none'\nE       assert [ChatCompletionMessageToolCall(id='call_g9yti6yqsw38wvtvndlflei7', function=Function(arguments='{\"location\":\"San Francisco, USA\"}', name='get_weather'), type='function', index=0)] is None\nE        +  where [ChatCompletionMessageToolCall(id='call_g9yti6yqsw38wvtvndlflei7', function=Function(arguments='{\"location\":\"San Francisco, USA\"}', name='get_weather'), type='function', index=0)] = ChatCompletionMessage(content=None, refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_g9yti6yqsw38wvtvndlflei7', function=Function(arguments='{\"location\":\"San Francisco, USA\"}', name='get_weather'), type='function', index=0)]).tool_calls\nE        +    where ChatCompletionMessage(content=None, refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_g9yti6yqsw38wvtvndlflei7', function=Function(arguments='{\"location\":\"San Francisco, USA\"}', name='get_weather'), type='function', index=0)]) = Choice(finish_reason='tool_calls', index=0, logprobs=None, message=ChatCompletionMessage(content=None, refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_g9yti6yqsw38wvtvndlflei7', function=Function(arguments='{\"location\":\"San Francisco, USA\"}', name='get_weather'), type='function', index=0)]), seed=1754099529794631000).message\n\ntests/verifications/openai_api/test_chat_completion.py:329: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_tool_choice_none[meta-llama/Llama-3.3-70B-Instruct-Turbo-case0]>>\nopenai_client = <openai.OpenAI object at 0x7f3127f67d00>\nmodel = 'meta-llama/Llama-3.3-70B-Instruct-Turbo', provider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],  # Reusing existing case for now\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_tool_choice_none(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            tool_choice=\"none\",\n            stream=False,\n        )\n    \n        assert response.choices[0].message.role == \"assistant\"\n>       assert response.choices[0].message.tool_calls is None, \"Expected no tool calls when tool_choice='none'\"\nE       AssertionError: Expected no tool calls when tool_choice='none'\nE       assert [ChatCompletionMessageToolCall(id='call_efyus3lwok2l7czire0yxkqm', function=Function(arguments='{\"location\":\"San Francisco, USA\"}', name='get_weather'), type='function', index=0)] is None\nE        +  where [ChatCompletionMessageToolCall(id='call_efyus3lwok2l7czire0yxkqm', function=Function(arguments='{\"location\":\"San Francisco, USA\"}', name='get_weather'), type='function', index=0)] = ChatCompletionMessage(content=None, refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_efyus3lwok2l7czire0yxkqm', function=Function(arguments='{\"location\":\"San Francisco, USA\"}', name='get_weather'), type='function', index=0)]).tool_calls\nE        +    where ChatCompletionMessage(content=None, refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_efyus3lwok2l7czire0yxkqm', function=Function(arguments='{\"location\":\"San Francisco, USA\"}', name='get_weather'), type='function', index=0)]) = Choice(finish_reason='tool_calls', index=0, logprobs=None, message=ChatCompletionMessage(content=None, refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_efyus3lwok2l7czire0yxkqm', function=Function(arguments='{\"location\":\"San Francisco, USA\"}', name='get_weather'), type='function', index=0)]), seed=10291057599279921000).message\n\ntests/verifications/openai_api/test_chat_completion.py:349: AssertionError"
       },
       "teardown": {
-        "duration": 0.0002299160696566105,
+        "duration": 0.00031497515738010406,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_tool_choice_none[meta-llama/Llama-4-Scout-17B-16E-Instruct-case0]",
-      "lineno": 309,
+      "lineno": 329,
       "outcome": "failed",
       "keywords": [
         "test_chat_non_streaming_tool_choice_none[meta-llama/Llama-4-Scout-17B-16E-Instruct-case0]",
@@ -2080,34 +2107,34 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.0073735828045755625,
+        "duration": 0.07444119732826948,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.38580279191955924,
+        "duration": 0.6588975815102458,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 329,
-          "message": "AssertionError: Expected no tool calls when tool_choice='none'\nassert [ChatCompletionMessageToolCall(id='call_f3d5174dyb3hxwsnotdhu0bn', function=Function(arguments='{\"location\":\"San Francisco\"}', name='get_weather'), type='function', index=0)] is None\n +  where [ChatCompletionMessageToolCall(id='call_f3d5174dyb3hxwsnotdhu0bn', function=Function(arguments='{\"location\":\"San Francisco\"}', name='get_weather'), type='function', index=0)] = ChatCompletionMessage(content=None, refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_f3d5174dyb3hxwsnotdhu0bn', function=Function(arguments='{\"location\":\"San Francisco\"}', name='get_weather'), type='function', index=0)]).tool_calls\n +    where ChatCompletionMessage(content=None, refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_f3d5174dyb3hxwsnotdhu0bn', function=Function(arguments='{\"location\":\"San Francisco\"}', name='get_weather'), type='function', index=0)]) = Choice(finish_reason='tool_calls', index=0, logprobs=None, message=ChatCompletionMessage(content=None, refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_f3d5174dyb3hxwsnotdhu0bn', function=Function(arguments='{\"location\":\"San Francisco\"}', name='get_weather'), type='function', index=0)]), seed=None).message"
+          "path": "/home/erichuang/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
+          "lineno": 349,
+          "message": "AssertionError: Expected no tool calls when tool_choice='none'\nassert [ChatCompletionMessageToolCall(id='call_biqe1tvadyupbqpgarqi91rn', function=Function(arguments='{\"location\":\"San Francisco, USA\"}', name='get_weather'), type='function', index=0)] is None\n +  where [ChatCompletionMessageToolCall(id='call_biqe1tvadyupbqpgarqi91rn', function=Function(arguments='{\"location\":\"San Francisco, USA\"}', name='get_weather'), type='function', index=0)] = ChatCompletionMessage(content=None, refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_biqe1tvadyupbqpgarqi91rn', function=Function(arguments='{\"location\":\"San Francisco, USA\"}', name='get_weather'), type='function', index=0)]).tool_calls\n +    where ChatCompletionMessage(content=None, refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_biqe1tvadyupbqpgarqi91rn', function=Function(arguments='{\"location\":\"San Francisco, USA\"}', name='get_weather'), type='function', index=0)]) = Choice(finish_reason='tool_calls', index=0, logprobs=None, message=ChatCompletionMessage(content=None, refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_biqe1tvadyupbqpgarqi91rn', function=Function(arguments='{\"location\":\"San Francisco, USA\"}', name='get_weather'), type='function', index=0)]), seed=None).message"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 329,
+            "lineno": 349,
             "message": "AssertionError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_tool_choice_none[meta-llama/Llama-4-Scout-17B-16E-Instruct-case0]>>\nopenai_client = <openai.OpenAI object at 0x10ca42da0>\nmodel = 'meta-llama/Llama-4-Scout-17B-16E-Instruct', provider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],  # Reusing existing case for now\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_tool_choice_none(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            tool_choice=\"none\",\n            stream=False,\n        )\n    \n        assert response.choices[0].message.role == \"assistant\"\n>       assert response.choices[0].message.tool_calls is None, \"Expected no tool calls when tool_choice='none'\"\nE       AssertionError: Expected no tool calls when tool_choice='none'\nE       assert [ChatCompletionMessageToolCall(id='call_f3d5174dyb3hxwsnotdhu0bn', function=Function(arguments='{\"location\":\"San Francisco\"}', name='get_weather'), type='function', index=0)] is None\nE        +  where [ChatCompletionMessageToolCall(id='call_f3d5174dyb3hxwsnotdhu0bn', function=Function(arguments='{\"location\":\"San Francisco\"}', name='get_weather'), type='function', index=0)] = ChatCompletionMessage(content=None, refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_f3d5174dyb3hxwsnotdhu0bn', function=Function(arguments='{\"location\":\"San Francisco\"}', name='get_weather'), type='function', index=0)]).tool_calls\nE        +    where ChatCompletionMessage(content=None, refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_f3d5174dyb3hxwsnotdhu0bn', function=Function(arguments='{\"location\":\"San Francisco\"}', name='get_weather'), type='function', index=0)]) = Choice(finish_reason='tool_calls', index=0, logprobs=None, message=ChatCompletionMessage(content=None, refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_f3d5174dyb3hxwsnotdhu0bn', function=Function(arguments='{\"location\":\"San Francisco\"}', name='get_weather'), type='function', index=0)]), seed=None).message\n\ntests/verifications/openai_api/test_chat_completion.py:329: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_tool_choice_none[meta-llama/Llama-4-Scout-17B-16E-Instruct-case0]>>\nopenai_client = <openai.OpenAI object at 0x7f3127f91900>\nmodel = 'meta-llama/Llama-4-Scout-17B-16E-Instruct', provider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],  # Reusing existing case for now\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_tool_choice_none(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            tool_choice=\"none\",\n            stream=False,\n        )\n    \n        assert response.choices[0].message.role == \"assistant\"\n>       assert response.choices[0].message.tool_calls is None, \"Expected no tool calls when tool_choice='none'\"\nE       AssertionError: Expected no tool calls when tool_choice='none'\nE       assert [ChatCompletionMessageToolCall(id='call_biqe1tvadyupbqpgarqi91rn', function=Function(arguments='{\"location\":\"San Francisco, USA\"}', name='get_weather'), type='function', index=0)] is None\nE        +  where [ChatCompletionMessageToolCall(id='call_biqe1tvadyupbqpgarqi91rn', function=Function(arguments='{\"location\":\"San Francisco, USA\"}', name='get_weather'), type='function', index=0)] = ChatCompletionMessage(content=None, refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_biqe1tvadyupbqpgarqi91rn', function=Function(arguments='{\"location\":\"San Francisco, USA\"}', name='get_weather'), type='function', index=0)]).tool_calls\nE        +    where ChatCompletionMessage(content=None, refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_biqe1tvadyupbqpgarqi91rn', function=Function(arguments='{\"location\":\"San Francisco, USA\"}', name='get_weather'), type='function', index=0)]) = Choice(finish_reason='tool_calls', index=0, logprobs=None, message=ChatCompletionMessage(content=None, refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_biqe1tvadyupbqpgarqi91rn', function=Function(arguments='{\"location\":\"San Francisco, USA\"}', name='get_weather'), type='function', index=0)]), seed=None).message\n\ntests/verifications/openai_api/test_chat_completion.py:349: AssertionError"
       },
       "teardown": {
-        "duration": 0.00027966685593128204,
+        "duration": 0.000378509983420372,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_tool_choice_none[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-case0]",
-      "lineno": 309,
+      "lineno": 329,
       "outcome": "failed",
       "keywords": [
         "test_chat_non_streaming_tool_choice_none[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-case0]",
@@ -2126,34 +2153,34 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.006746791070327163,
+        "duration": 0.07218985445797443,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.3289988338947296,
+        "duration": 0.46723131835460663,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 329,
-          "message": "AssertionError: Expected no tool calls when tool_choice='none'\nassert [ChatCompletionMessageToolCall(id='call_z5imwjfzlce7v1sjx2x7z7rj', function=Function(arguments='{\"location\":\"San Francisco\"}', name='get_weather'), type='function', index=0)] is None\n +  where [ChatCompletionMessageToolCall(id='call_z5imwjfzlce7v1sjx2x7z7rj', function=Function(arguments='{\"location\":\"San Francisco\"}', name='get_weather'), type='function', index=0)] = ChatCompletionMessage(content=None, refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_z5imwjfzlce7v1sjx2x7z7rj', function=Function(arguments='{\"location\":\"San Francisco\"}', name='get_weather'), type='function', index=0)]).tool_calls\n +    where ChatCompletionMessage(content=None, refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_z5imwjfzlce7v1sjx2x7z7rj', function=Function(arguments='{\"location\":\"San Francisco\"}', name='get_weather'), type='function', index=0)]) = Choice(finish_reason='tool_calls', index=0, logprobs=None, message=ChatCompletionMessage(content=None, refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_z5imwjfzlce7v1sjx2x7z7rj', function=Function(arguments='{\"location\":\"San Francisco\"}', name='get_weather'), type='function', index=0)]), seed=None).message"
+          "path": "/home/erichuang/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
+          "lineno": 349,
+          "message": "AssertionError: Expected no tool calls when tool_choice='none'\nassert [ChatCompletionMessageToolCall(id='call_ie8s7wjdypmhv2zzqeqkrif5', function=Function(arguments='{\"location\":\"San Francisco\"}', name='get_weather'), type='function', index=0)] is None\n +  where [ChatCompletionMessageToolCall(id='call_ie8s7wjdypmhv2zzqeqkrif5', function=Function(arguments='{\"location\":\"San Francisco\"}', name='get_weather'), type='function', index=0)] = ChatCompletionMessage(content=None, refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_ie8s7wjdypmhv2zzqeqkrif5', function=Function(arguments='{\"location\":\"San Francisco\"}', name='get_weather'), type='function', index=0)]).tool_calls\n +    where ChatCompletionMessage(content=None, refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_ie8s7wjdypmhv2zzqeqkrif5', function=Function(arguments='{\"location\":\"San Francisco\"}', name='get_weather'), type='function', index=0)]) = Choice(finish_reason='tool_calls', index=0, logprobs=None, message=ChatCompletionMessage(content=None, refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_ie8s7wjdypmhv2zzqeqkrif5', function=Function(arguments='{\"location\":\"San Francisco\"}', name='get_weather'), type='function', index=0)]), seed=None).message"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 329,
+            "lineno": 349,
             "message": "AssertionError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_tool_choice_none[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-case0]>>\nopenai_client = <openai.OpenAI object at 0x10ce06bc0>\nmodel = 'meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8'\nprovider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],  # Reusing existing case for now\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_tool_choice_none(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            tool_choice=\"none\",\n            stream=False,\n        )\n    \n        assert response.choices[0].message.role == \"assistant\"\n>       assert response.choices[0].message.tool_calls is None, \"Expected no tool calls when tool_choice='none'\"\nE       AssertionError: Expected no tool calls when tool_choice='none'\nE       assert [ChatCompletionMessageToolCall(id='call_z5imwjfzlce7v1sjx2x7z7rj', function=Function(arguments='{\"location\":\"San Francisco\"}', name='get_weather'), type='function', index=0)] is None\nE        +  where [ChatCompletionMessageToolCall(id='call_z5imwjfzlce7v1sjx2x7z7rj', function=Function(arguments='{\"location\":\"San Francisco\"}', name='get_weather'), type='function', index=0)] = ChatCompletionMessage(content=None, refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_z5imwjfzlce7v1sjx2x7z7rj', function=Function(arguments='{\"location\":\"San Francisco\"}', name='get_weather'), type='function', index=0)]).tool_calls\nE        +    where ChatCompletionMessage(content=None, refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_z5imwjfzlce7v1sjx2x7z7rj', function=Function(arguments='{\"location\":\"San Francisco\"}', name='get_weather'), type='function', index=0)]) = Choice(finish_reason='tool_calls', index=0, logprobs=None, message=ChatCompletionMessage(content=None, refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_z5imwjfzlce7v1sjx2x7z7rj', function=Function(arguments='{\"location\":\"San Francisco\"}', name='get_weather'), type='function', index=0)]), seed=None).message\n\ntests/verifications/openai_api/test_chat_completion.py:329: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_tool_choice_none[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-case0]>>\nopenai_client = <openai.OpenAI object at 0x7f3127e63100>\nmodel = 'meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8'\nprovider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],  # Reusing existing case for now\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_tool_choice_none(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        response = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            tool_choice=\"none\",\n            stream=False,\n        )\n    \n        assert response.choices[0].message.role == \"assistant\"\n>       assert response.choices[0].message.tool_calls is None, \"Expected no tool calls when tool_choice='none'\"\nE       AssertionError: Expected no tool calls when tool_choice='none'\nE       assert [ChatCompletionMessageToolCall(id='call_ie8s7wjdypmhv2zzqeqkrif5', function=Function(arguments='{\"location\":\"San Francisco\"}', name='get_weather'), type='function', index=0)] is None\nE        +  where [ChatCompletionMessageToolCall(id='call_ie8s7wjdypmhv2zzqeqkrif5', function=Function(arguments='{\"location\":\"San Francisco\"}', name='get_weather'), type='function', index=0)] = ChatCompletionMessage(content=None, refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_ie8s7wjdypmhv2zzqeqkrif5', function=Function(arguments='{\"location\":\"San Francisco\"}', name='get_weather'), type='function', index=0)]).tool_calls\nE        +    where ChatCompletionMessage(content=None, refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_ie8s7wjdypmhv2zzqeqkrif5', function=Function(arguments='{\"location\":\"San Francisco\"}', name='get_weather'), type='function', index=0)]) = Choice(finish_reason='tool_calls', index=0, logprobs=None, message=ChatCompletionMessage(content=None, refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_ie8s7wjdypmhv2zzqeqkrif5', function=Function(arguments='{\"location\":\"San Francisco\"}', name='get_weather'), type='function', index=0)]), seed=None).message\n\ntests/verifications/openai_api/test_chat_completion.py:349: AssertionError"
       },
       "teardown": {
-        "duration": 0.0002757080364972353,
+        "duration": 0.00030298903584480286,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_tool_choice_none[meta-llama/Llama-3.3-70B-Instruct-Turbo-case0]",
-      "lineno": 332,
+      "lineno": 352,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_tool_choice_none[meta-llama/Llama-3.3-70B-Instruct-Turbo-case0]",
@@ -2172,34 +2199,34 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.006751707987859845,
+        "duration": 0.07074183039367199,
         "outcome": "passed"
       },
       "call": {
-        "duration": 1.8982260411139578,
+        "duration": 0.5427122255787253,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 356,
-          "message": "AssertionError: Expected no tool call chunks when tool_choice='none'\nassert not [ChoiceDeltaToolCall(index=0, id='call_x4m8hvw4d9iktfabb0lwwagm', function=ChoiceDeltaToolCallFunction(arguments='', name='get_weather'), type='function')]\n +  where [ChoiceDeltaToolCall(index=0, id='call_x4m8hvw4d9iktfabb0lwwagm', function=ChoiceDeltaToolCallFunction(arguments='', name='get_weather'), type='function')] = ChoiceDelta(content=None, function_call=None, refusal=None, role=None, tool_calls=[ChoiceDeltaToolCall(index=0, id='call_x4m8hvw4d9iktfabb0lwwagm', function=ChoiceDeltaToolCallFunction(arguments='', name='get_weather'), type='function')]).tool_calls"
+          "path": "/home/erichuang/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
+          "lineno": 376,
+          "message": "AssertionError: Expected no tool call chunks when tool_choice='none'\nassert not [ChoiceDeltaToolCall(index=0, id='call_b3357o23munvhfy8cqg7wwwd', function=ChoiceDeltaToolCallFunction(arguments='', name='get_weather'), type='function')]\n +  where [ChoiceDeltaToolCall(index=0, id='call_b3357o23munvhfy8cqg7wwwd', function=ChoiceDeltaToolCallFunction(arguments='', name='get_weather'), type='function')] = ChoiceDelta(content=None, function_call=None, refusal=None, role=None, tool_calls=[ChoiceDeltaToolCall(index=0, id='call_b3357o23munvhfy8cqg7wwwd', function=ChoiceDeltaToolCallFunction(arguments='', name='get_weather'), type='function')]).tool_calls"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 356,
+            "lineno": 376,
             "message": "AssertionError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_tool_choice_none[meta-llama/Llama-3.3-70B-Instruct-Turbo-case0]>>\nopenai_client = <openai.OpenAI object at 0x10c6ffac0>\nmodel = 'meta-llama/Llama-3.3-70B-Instruct-Turbo', provider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],  # Reusing existing case for now\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_tool_choice_none(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        stream = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            tool_choice=\"none\",\n            stream=True,\n        )\n    \n        content = \"\"\n        for chunk in stream:\n            delta = chunk.choices[0].delta\n            if delta.content:\n                content += delta.content\n>           assert not delta.tool_calls, \"Expected no tool call chunks when tool_choice='none'\"\nE           AssertionError: Expected no tool call chunks when tool_choice='none'\nE           assert not [ChoiceDeltaToolCall(index=0, id='call_x4m8hvw4d9iktfabb0lwwagm', function=ChoiceDeltaToolCallFunction(arguments='', name='get_weather'), type='function')]\nE            +  where [ChoiceDeltaToolCall(index=0, id='call_x4m8hvw4d9iktfabb0lwwagm', function=ChoiceDeltaToolCallFunction(arguments='', name='get_weather'), type='function')] = ChoiceDelta(content=None, function_call=None, refusal=None, role=None, tool_calls=[ChoiceDeltaToolCall(index=0, id='call_x4m8hvw4d9iktfabb0lwwagm', function=ChoiceDeltaToolCallFunction(arguments='', name='get_weather'), type='function')]).tool_calls\n\ntests/verifications/openai_api/test_chat_completion.py:356: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_tool_choice_none[meta-llama/Llama-3.3-70B-Instruct-Turbo-case0]>>\nopenai_client = <openai.OpenAI object at 0x7f312800cdc0>\nmodel = 'meta-llama/Llama-3.3-70B-Instruct-Turbo', provider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],  # Reusing existing case for now\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_tool_choice_none(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        stream = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            tool_choice=\"none\",\n            stream=True,\n        )\n    \n        content = \"\"\n        for chunk in stream:\n            delta = chunk.choices[0].delta\n            if delta.content:\n                content += delta.content\n>           assert not delta.tool_calls, \"Expected no tool call chunks when tool_choice='none'\"\nE           AssertionError: Expected no tool call chunks when tool_choice='none'\nE           assert not [ChoiceDeltaToolCall(index=0, id='call_b3357o23munvhfy8cqg7wwwd', function=ChoiceDeltaToolCallFunction(arguments='', name='get_weather'), type='function')]\nE            +  where [ChoiceDeltaToolCall(index=0, id='call_b3357o23munvhfy8cqg7wwwd', function=ChoiceDeltaToolCallFunction(arguments='', name='get_weather'), type='function')] = ChoiceDelta(content=None, function_call=None, refusal=None, role=None, tool_calls=[ChoiceDeltaToolCall(index=0, id='call_b3357o23munvhfy8cqg7wwwd', function=ChoiceDeltaToolCallFunction(arguments='', name='get_weather'), type='function')]).tool_calls\n\ntests/verifications/openai_api/test_chat_completion.py:376: AssertionError"
       },
       "teardown": {
-        "duration": 0.00020166696049273014,
+        "duration": 0.00037453509867191315,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_tool_choice_none[meta-llama/Llama-4-Scout-17B-16E-Instruct-case0]",
-      "lineno": 332,
+      "lineno": 352,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_tool_choice_none[meta-llama/Llama-4-Scout-17B-16E-Instruct-case0]",
@@ -2218,34 +2245,34 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.007537916069850326,
+        "duration": 0.07261296082288027,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.463320666924119,
+        "duration": 0.44528466928750277,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 356,
-          "message": "AssertionError: Expected no tool call chunks when tool_choice='none'\nassert not [ChoiceDeltaToolCall(index=0, id='call_d4wm4bj2gtl64dbr8p9yvwxe', function=ChoiceDeltaToolCallFunction(arguments='', name='get_weather'), type='function')]\n +  where [ChoiceDeltaToolCall(index=0, id='call_d4wm4bj2gtl64dbr8p9yvwxe', function=ChoiceDeltaToolCallFunction(arguments='', name='get_weather'), type='function')] = ChoiceDelta(content=None, function_call=None, refusal=None, role=None, tool_calls=[ChoiceDeltaToolCall(index=0, id='call_d4wm4bj2gtl64dbr8p9yvwxe', function=ChoiceDeltaToolCallFunction(arguments='', name='get_weather'), type='function')]).tool_calls"
+          "path": "/home/erichuang/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
+          "lineno": 376,
+          "message": "AssertionError: Expected no tool call chunks when tool_choice='none'\nassert not [ChoiceDeltaToolCall(index=0, id='call_00xpv69hsw7zrbkwnbq9ewxw', function=ChoiceDeltaToolCallFunction(arguments='', name='get_weather'), type='function')]\n +  where [ChoiceDeltaToolCall(index=0, id='call_00xpv69hsw7zrbkwnbq9ewxw', function=ChoiceDeltaToolCallFunction(arguments='', name='get_weather'), type='function')] = ChoiceDelta(content=None, function_call=None, refusal=None, role=None, tool_calls=[ChoiceDeltaToolCall(index=0, id='call_00xpv69hsw7zrbkwnbq9ewxw', function=ChoiceDeltaToolCallFunction(arguments='', name='get_weather'), type='function')]).tool_calls"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 356,
+            "lineno": 376,
             "message": "AssertionError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_tool_choice_none[meta-llama/Llama-4-Scout-17B-16E-Instruct-case0]>>\nopenai_client = <openai.OpenAI object at 0x10cadf460>\nmodel = 'meta-llama/Llama-4-Scout-17B-16E-Instruct', provider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],  # Reusing existing case for now\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_tool_choice_none(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        stream = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            tool_choice=\"none\",\n            stream=True,\n        )\n    \n        content = \"\"\n        for chunk in stream:\n            delta = chunk.choices[0].delta\n            if delta.content:\n                content += delta.content\n>           assert not delta.tool_calls, \"Expected no tool call chunks when tool_choice='none'\"\nE           AssertionError: Expected no tool call chunks when tool_choice='none'\nE           assert not [ChoiceDeltaToolCall(index=0, id='call_d4wm4bj2gtl64dbr8p9yvwxe', function=ChoiceDeltaToolCallFunction(arguments='', name='get_weather'), type='function')]\nE            +  where [ChoiceDeltaToolCall(index=0, id='call_d4wm4bj2gtl64dbr8p9yvwxe', function=ChoiceDeltaToolCallFunction(arguments='', name='get_weather'), type='function')] = ChoiceDelta(content=None, function_call=None, refusal=None, role=None, tool_calls=[ChoiceDeltaToolCall(index=0, id='call_d4wm4bj2gtl64dbr8p9yvwxe', function=ChoiceDeltaToolCallFunction(arguments='', name='get_weather'), type='function')]).tool_calls\n\ntests/verifications/openai_api/test_chat_completion.py:356: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_tool_choice_none[meta-llama/Llama-4-Scout-17B-16E-Instruct-case0]>>\nopenai_client = <openai.OpenAI object at 0x7f3127e34220>\nmodel = 'meta-llama/Llama-4-Scout-17B-16E-Instruct', provider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],  # Reusing existing case for now\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_tool_choice_none(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        stream = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            tool_choice=\"none\",\n            stream=True,\n        )\n    \n        content = \"\"\n        for chunk in stream:\n            delta = chunk.choices[0].delta\n            if delta.content:\n                content += delta.content\n>           assert not delta.tool_calls, \"Expected no tool call chunks when tool_choice='none'\"\nE           AssertionError: Expected no tool call chunks when tool_choice='none'\nE           assert not [ChoiceDeltaToolCall(index=0, id='call_00xpv69hsw7zrbkwnbq9ewxw', function=ChoiceDeltaToolCallFunction(arguments='', name='get_weather'), type='function')]\nE            +  where [ChoiceDeltaToolCall(index=0, id='call_00xpv69hsw7zrbkwnbq9ewxw', function=ChoiceDeltaToolCallFunction(arguments='', name='get_weather'), type='function')] = ChoiceDelta(content=None, function_call=None, refusal=None, role=None, tool_calls=[ChoiceDeltaToolCall(index=0, id='call_00xpv69hsw7zrbkwnbq9ewxw', function=ChoiceDeltaToolCallFunction(arguments='', name='get_weather'), type='function')]).tool_calls\n\ntests/verifications/openai_api/test_chat_completion.py:376: AssertionError"
       },
       "teardown": {
-        "duration": 0.0002644169144332409,
+        "duration": 0.00035339873284101486,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_tool_choice_none[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-case0]",
-      "lineno": 332,
+      "lineno": 352,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_tool_choice_none[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-case0]",
@@ -2264,34 +2291,34 @@
         "case_id": "case0"
       },
       "setup": {
-        "duration": 0.010220374912023544,
+        "duration": 0.0712411506101489,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.3469825841020793,
+        "duration": 0.792656259611249,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 356,
-          "message": "AssertionError: Expected no tool call chunks when tool_choice='none'\nassert not [ChoiceDeltaToolCall(index=0, id='call_q4lv7coily23gc1z694vgpn8', function=ChoiceDeltaToolCallFunction(arguments='', name='get_weather'), type='function')]\n +  where [ChoiceDeltaToolCall(index=0, id='call_q4lv7coily23gc1z694vgpn8', function=ChoiceDeltaToolCallFunction(arguments='', name='get_weather'), type='function')] = ChoiceDelta(content=None, function_call=None, refusal=None, role=None, tool_calls=[ChoiceDeltaToolCall(index=0, id='call_q4lv7coily23gc1z694vgpn8', function=ChoiceDeltaToolCallFunction(arguments='', name='get_weather'), type='function')]).tool_calls"
+          "path": "/home/erichuang/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
+          "lineno": 376,
+          "message": "AssertionError: Expected no tool call chunks when tool_choice='none'\nassert not [ChoiceDeltaToolCall(index=0, id='call_kiye5b1nrq2b9yf0vy5feki8', function=ChoiceDeltaToolCallFunction(arguments='', name='get_weather'), type='function')]\n +  where [ChoiceDeltaToolCall(index=0, id='call_kiye5b1nrq2b9yf0vy5feki8', function=ChoiceDeltaToolCallFunction(arguments='', name='get_weather'), type='function')] = ChoiceDelta(content=None, function_call=None, refusal=None, role=None, tool_calls=[ChoiceDeltaToolCall(index=0, id='call_kiye5b1nrq2b9yf0vy5feki8', function=ChoiceDeltaToolCallFunction(arguments='', name='get_weather'), type='function')]).tool_calls"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 356,
+            "lineno": 376,
             "message": "AssertionError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_tool_choice_none[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-case0]>>\nopenai_client = <openai.OpenAI object at 0x10ca40ca0>\nmodel = 'meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8'\nprovider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],  # Reusing existing case for now\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_tool_choice_none(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        stream = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            tool_choice=\"none\",\n            stream=True,\n        )\n    \n        content = \"\"\n        for chunk in stream:\n            delta = chunk.choices[0].delta\n            if delta.content:\n                content += delta.content\n>           assert not delta.tool_calls, \"Expected no tool call chunks when tool_choice='none'\"\nE           AssertionError: Expected no tool call chunks when tool_choice='none'\nE           assert not [ChoiceDeltaToolCall(index=0, id='call_q4lv7coily23gc1z694vgpn8', function=ChoiceDeltaToolCallFunction(arguments='', name='get_weather'), type='function')]\nE            +  where [ChoiceDeltaToolCall(index=0, id='call_q4lv7coily23gc1z694vgpn8', function=ChoiceDeltaToolCallFunction(arguments='', name='get_weather'), type='function')] = ChoiceDelta(content=None, function_call=None, refusal=None, role=None, tool_calls=[ChoiceDeltaToolCall(index=0, id='call_q4lv7coily23gc1z694vgpn8', function=ChoiceDeltaToolCallFunction(arguments='', name='get_weather'), type='function')]).tool_calls\n\ntests/verifications/openai_api/test_chat_completion.py:356: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_tool_choice_none[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-case0]>>\nopenai_client = <openai.OpenAI object at 0x7f3127eb4220>\nmodel = 'meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8'\nprovider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'input': {'messages': [{'content': 'You are a helpful assistant that can use tools to get information.', 'role': 'sys..., 'properties': {...}, 'required': [...], 'type': 'object'}}, 'type': 'function'}]}, 'output': 'get_weather_tool_call'}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases[\"test_tool_calling\"][\"test_params\"][\"case\"],  # Reusing existing case for now\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_tool_choice_none(request, openai_client, model, provider, verification_config, case):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        stream = openai_client.chat.completions.create(\n            model=model,\n            messages=case[\"input\"][\"messages\"],\n            tools=case[\"input\"][\"tools\"],\n            tool_choice=\"none\",\n            stream=True,\n        )\n    \n        content = \"\"\n        for chunk in stream:\n            delta = chunk.choices[0].delta\n            if delta.content:\n                content += delta.content\n>           assert not delta.tool_calls, \"Expected no tool call chunks when tool_choice='none'\"\nE           AssertionError: Expected no tool call chunks when tool_choice='none'\nE           assert not [ChoiceDeltaToolCall(index=0, id='call_kiye5b1nrq2b9yf0vy5feki8', function=ChoiceDeltaToolCallFunction(arguments='', name='get_weather'), type='function')]\nE            +  where [ChoiceDeltaToolCall(index=0, id='call_kiye5b1nrq2b9yf0vy5feki8', function=ChoiceDeltaToolCallFunction(arguments='', name='get_weather'), type='function')] = ChoiceDelta(content=None, function_call=None, refusal=None, role=None, tool_calls=[ChoiceDeltaToolCall(index=0, id='call_kiye5b1nrq2b9yf0vy5feki8', function=ChoiceDeltaToolCallFunction(arguments='', name='get_weather'), type='function')]).tool_calls\n\ntests/verifications/openai_api/test_chat_completion.py:376: AssertionError"
       },
       "teardown": {
-        "duration": 0.00033033289946615696,
+        "duration": 0.0003104889765381813,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-3.3-70B-Instruct-Turbo-text_then_weather_tool]",
-      "lineno": 360,
+      "lineno": 380,
       "outcome": "failed",
       "keywords": [
         "test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-3.3-70B-Instruct-Turbo-text_then_weather_tool]",
@@ -2310,34 +2337,34 @@
         "case_id": "text_then_weather_tool"
       },
       "setup": {
-        "duration": 0.0076314168982207775,
+        "duration": 0.07114225905388594,
         "outcome": "passed"
       },
       "call": {
-        "duration": 1.2038672079797834,
+        "duration": 0.9180215634405613,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 419,
-          "message": "AssertionError: Expected 0 tool calls, but got 1\nassert 1 == 0\n +  where 1 = len(([ChatCompletionMessageToolCall(id='call_z4rvmn0r7oung1cu16ul3gu3', function=Function(arguments='{\"location\":\"San Francisco, CA\"}', name='get_weather'), type='function', index=0)]))\n +    where [ChatCompletionMessageToolCall(id='call_z4rvmn0r7oung1cu16ul3gu3', function=Function(arguments='{\"location\":\"San Francisco, CA\"}', name='get_weather'), type='function', index=0)] = ChatCompletionMessage(content=None, refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_z4rvmn0r7oung1cu16ul3gu3', function=Function(arguments='{\"location\":\"San Francisco, CA\"}', name='get_weather'), type='function', index=0)]).tool_calls"
+          "path": "/home/erichuang/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
+          "lineno": 439,
+          "message": "AssertionError: Expected 0 tool calls, but got 1\nassert 1 == 0\n +  where 1 = len(([ChatCompletionMessageToolCall(id='call_2qsbu2opq85hsx2fyb643xix', function=Function(arguments='{\"location\":\"San Francisco, CA\"}', name='get_weather'), type='function', index=0)]))\n +    where [ChatCompletionMessageToolCall(id='call_2qsbu2opq85hsx2fyb643xix', function=Function(arguments='{\"location\":\"San Francisco, CA\"}', name='get_weather'), type='function', index=0)] = ChatCompletionMessage(content=None, refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_2qsbu2opq85hsx2fyb643xix', function=Function(arguments='{\"location\":\"San Francisco, CA\"}', name='get_weather'), type='function', index=0)]).tool_calls"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 419,
+            "lineno": 439,
             "message": "AssertionError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-3.3-70B-Instruct-Turbo-text_then_weather_tool]>>\nopenai_client = <openai.OpenAI object at 0x10c03c550>\nmodel = 'meta-llama/Llama-3.3-70B-Instruct-Turbo', provider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'text_then_weather_tool', 'expected': [{'answer': ['sol'], 'num_tool_calls': 0}, {'num_tool_calls': 1, 'to...], 'type': 'object'}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': '70 degrees and foggy'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\"\n        Test cases for multi-turn tool calling.\n        Tool calls are asserted.\n        Tool responses are provided in the test case.\n        Final response is asserted.\n        \"\"\"\n    \n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        # Create a copy of the messages list to avoid modifying the original\n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        # Use deepcopy to prevent modification across runs/parametrization\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        # keep going until either\n        # 1. we have messages to test in multi-turn\n        # 2. no messages but last message is tool response\n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            # do not take new messages if last message is tool response\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                # Ensure new_messages is a list of message objects\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    # If it's a single message object, add it directly\n                    messages.append(new_messages)\n    \n            # --- API Call ---\n            response = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=False,\n            )\n    \n            # --- Process Response ---\n            assistant_message = response.choices[0].message\n            messages.append(assistant_message.model_dump(exclude_unset=True))\n    \n            assert assistant_message.role == \"assistant\"\n    \n            # Get the expected result data\n            expected = expected_results.pop(0)\n            num_tool_calls = expected[\"num_tool_calls\"]\n    \n            # --- Assertions based on expected result ---\n>           assert len(assistant_message.tool_calls or []) == num_tool_calls, (\n                f\"Expected {num_tool_calls} tool calls, but got {len(assistant_message.tool_calls or [])}\"\n            )\nE           AssertionError: Expected 0 tool calls, but got 1\nE           assert 1 == 0\nE            +  where 1 = len(([ChatCompletionMessageToolCall(id='call_z4rvmn0r7oung1cu16ul3gu3', function=Function(arguments='{\"location\":\"San Francisco, CA\"}', name='get_weather'), type='function', index=0)]))\nE            +    where [ChatCompletionMessageToolCall(id='call_z4rvmn0r7oung1cu16ul3gu3', function=Function(arguments='{\"location\":\"San Francisco, CA\"}', name='get_weather'), type='function', index=0)] = ChatCompletionMessage(content=None, refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_z4rvmn0r7oung1cu16ul3gu3', function=Function(arguments='{\"location\":\"San Francisco, CA\"}', name='get_weather'), type='function', index=0)]).tool_calls\n\ntests/verifications/openai_api/test_chat_completion.py:419: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-3.3-70B-Instruct-Turbo-text_then_weather_tool]>>\nopenai_client = <openai.OpenAI object at 0x7f3127d8feb0>\nmodel = 'meta-llama/Llama-3.3-70B-Instruct-Turbo', provider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'text_then_weather_tool', 'expected': [{'answer': ['sol'], 'num_tool_calls': 0}, {'num_tool_calls': 1, 'to...], 'type': 'object'}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': '70 degrees and foggy'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\"\n        Test cases for multi-turn tool calling.\n        Tool calls are asserted.\n        Tool responses are provided in the test case.\n        Final response is asserted.\n        \"\"\"\n    \n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        # Create a copy of the messages list to avoid modifying the original\n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        # Use deepcopy to prevent modification across runs/parametrization\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        # keep going until either\n        # 1. we have messages to test in multi-turn\n        # 2. no messages but last message is tool response\n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            # do not take new messages if last message is tool response\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                # Ensure new_messages is a list of message objects\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    # If it's a single message object, add it directly\n                    messages.append(new_messages)\n    \n            # --- API Call ---\n            response = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=False,\n            )\n    \n            # --- Process Response ---\n            assistant_message = response.choices[0].message\n            messages.append(assistant_message.model_dump(exclude_unset=True))\n    \n            assert assistant_message.role == \"assistant\"\n    \n            # Get the expected result data\n            expected = expected_results.pop(0)\n            num_tool_calls = expected[\"num_tool_calls\"]\n    \n            # --- Assertions based on expected result ---\n>           assert len(assistant_message.tool_calls or []) == num_tool_calls, (\n                f\"Expected {num_tool_calls} tool calls, but got {len(assistant_message.tool_calls or [])}\"\n            )\nE           AssertionError: Expected 0 tool calls, but got 1\nE           assert 1 == 0\nE            +  where 1 = len(([ChatCompletionMessageToolCall(id='call_2qsbu2opq85hsx2fyb643xix', function=Function(arguments='{\"location\":\"San Francisco, CA\"}', name='get_weather'), type='function', index=0)]))\nE            +    where [ChatCompletionMessageToolCall(id='call_2qsbu2opq85hsx2fyb643xix', function=Function(arguments='{\"location\":\"San Francisco, CA\"}', name='get_weather'), type='function', index=0)] = ChatCompletionMessage(content=None, refusal=None, role='assistant', annotations=None, audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='call_2qsbu2opq85hsx2fyb643xix', function=Function(arguments='{\"location\":\"San Francisco, CA\"}', name='get_weather'), type='function', index=0)]).tool_calls\n\ntests/verifications/openai_api/test_chat_completion.py:439: AssertionError"
       },
       "teardown": {
-        "duration": 0.0002806668635457754,
+        "duration": 0.00033766962587833405,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-3.3-70B-Instruct-Turbo-weather_tool_then_text]",
-      "lineno": 360,
+      "lineno": 380,
       "outcome": "passed",
       "keywords": [
         "test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-3.3-70B-Instruct-Turbo-weather_tool_then_text]",
@@ -2356,21 +2383,21 @@
         "case_id": "weather_tool_then_text"
       },
       "setup": {
-        "duration": 0.007497292011976242,
+        "duration": 0.07061670627444983,
         "outcome": "passed"
       },
       "call": {
-        "duration": 2.314662832999602,
+        "duration": 1.9790025427937508,
         "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.0002090830821543932,
+        "duration": 0.0002498161047697067,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-3.3-70B-Instruct-Turbo-add_product_tool]",
-      "lineno": 360,
+      "lineno": 380,
       "outcome": "passed",
       "keywords": [
         "test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-3.3-70B-Instruct-Turbo-add_product_tool]",
@@ -2389,21 +2416,21 @@
         "case_id": "add_product_tool"
       },
       "setup": {
-        "duration": 0.010512124979868531,
+        "duration": 0.07382979057729244,
         "outcome": "passed"
       },
       "call": {
-        "duration": 1.7789271660149097,
+        "duration": 0.8887521298602223,
         "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.00014504184946417809,
+        "duration": 0.000309688039124012,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-3.3-70B-Instruct-Turbo-get_then_create_event_tool]",
-      "lineno": 360,
+      "lineno": 380,
       "outcome": "passed",
       "keywords": [
         "test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-3.3-70B-Instruct-Turbo-get_then_create_event_tool]",
@@ -2422,21 +2449,21 @@
         "case_id": "get_then_create_event_tool"
       },
       "setup": {
-        "duration": 0.008220916846767068,
+        "duration": 0.07273934967815876,
         "outcome": "passed"
       },
       "call": {
-        "duration": 2.6108481250703335,
+        "duration": 4.823556405492127,
         "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.00035962508991360664,
+        "duration": 0.00023336336016654968,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-3.3-70B-Instruct-Turbo-compare_monthly_expense_tool]",
-      "lineno": 360,
+      "lineno": 380,
       "outcome": "passed",
       "keywords": [
         "test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-3.3-70B-Instruct-Turbo-compare_monthly_expense_tool]",
@@ -2455,21 +2482,21 @@
         "case_id": "compare_monthly_expense_tool"
       },
       "setup": {
-        "duration": 0.007435625186190009,
+        "duration": 0.07417754456400871,
         "outcome": "passed"
       },
       "call": {
-        "duration": 2.0318919168785214,
+        "duration": 15.95331169757992,
         "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.00015241606160998344,
+        "duration": 0.00023916177451610565,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-text_then_weather_tool]",
-      "lineno": 360,
+      "lineno": 380,
       "outcome": "failed",
       "keywords": [
         "test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-text_then_weather_tool]",
@@ -2488,34 +2515,34 @@
         "case_id": "text_then_weather_tool"
       },
       "setup": {
-        "duration": 0.008867957862094045,
+        "duration": 0.07702007982879877,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.3960520001128316,
+        "duration": 0.735025598667562,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 447,
-          "message": "AssertionError: Expected one of ['sol'] in content, but got: 'I am unable to fulfill this request as the functions provided are insufficient.'\nassert False\n +  where False = any(<generator object test_chat_non_streaming_multi_turn_tool_calling.<locals>.<genexpr> at 0x10c688660>)"
+          "path": "/home/erichuang/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
+          "lineno": 467,
+          "message": "AssertionError: Expected one of ['sol'] in content, but got: 'I cannot perform this task as it requires additional functionality that is not available in the given functions.'\nassert False\n +  where False = any(<generator object test_chat_non_streaming_multi_turn_tool_calling.<locals>.<genexpr> at 0x7f3127d3f610>)"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 447,
+            "lineno": 467,
             "message": "AssertionError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-text_then_weather_tool]>>\nopenai_client = <openai.OpenAI object at 0x10c175b40>\nmodel = 'meta-llama/Llama-4-Scout-17B-16E-Instruct', provider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'text_then_weather_tool', 'expected': [{'answer': ['sol'], 'num_tool_calls': 0}, {'num_tool_calls': 1, 'to...], 'type': 'object'}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': '70 degrees and foggy'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\"\n        Test cases for multi-turn tool calling.\n        Tool calls are asserted.\n        Tool responses are provided in the test case.\n        Final response is asserted.\n        \"\"\"\n    \n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        # Create a copy of the messages list to avoid modifying the original\n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        # Use deepcopy to prevent modification across runs/parametrization\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        # keep going until either\n        # 1. we have messages to test in multi-turn\n        # 2. no messages but last message is tool response\n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            # do not take new messages if last message is tool response\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                # Ensure new_messages is a list of message objects\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    # If it's a single message object, add it directly\n                    messages.append(new_messages)\n    \n            # --- API Call ---\n            response = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=False,\n            )\n    \n            # --- Process Response ---\n            assistant_message = response.choices[0].message\n            messages.append(assistant_message.model_dump(exclude_unset=True))\n    \n            assert assistant_message.role == \"assistant\"\n    \n            # Get the expected result data\n            expected = expected_results.pop(0)\n            num_tool_calls = expected[\"num_tool_calls\"]\n    \n            # --- Assertions based on expected result ---\n            assert len(assistant_message.tool_calls or []) == num_tool_calls, (\n                f\"Expected {num_tool_calls} tool calls, but got {len(assistant_message.tool_calls or [])}\"\n            )\n    \n            if num_tool_calls > 0:\n                tool_call = assistant_message.tool_calls[0]\n                assert tool_call.function.name == expected[\"tool_name\"], (\n                    f\"Expected tool '{expected['tool_name']}', got '{tool_call.function.name}'\"\n                )\n                # Parse the JSON string arguments before comparing\n                actual_arguments = json.loads(tool_call.function.arguments)\n                assert actual_arguments == expected[\"tool_arguments\"], (\n                    f\"Expected arguments '{expected['tool_arguments']}', got '{actual_arguments}'\"\n                )\n    \n                # Prepare and append the tool response for the next turn\n                tool_response = tool_responses.pop(0)\n                messages.append(\n                    {\n                        \"role\": \"tool\",\n                        \"tool_call_id\": tool_call.id,\n                        \"content\": tool_response[\"response\"],\n                    }\n                )\n            else:\n                assert assistant_message.content is not None, \"Expected content, but none received.\"\n                expected_answers = expected[\"answer\"]  # This is now a list\n                content_lower = assistant_message.content.lower()\n>               assert any(ans.lower() in content_lower for ans in expected_answers), (\n                    f\"Expected one of {expected_answers} in content, but got: '{assistant_message.content}'\"\n                )\nE               AssertionError: Expected one of ['sol'] in content, but got: 'I am unable to fulfill this request as the functions provided are insufficient.'\nE               assert False\nE                +  where False = any(<generator object test_chat_non_streaming_multi_turn_tool_calling.<locals>.<genexpr> at 0x10c688660>)\n\ntests/verifications/openai_api/test_chat_completion.py:447: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-text_then_weather_tool]>>\nopenai_client = <openai.OpenAI object at 0x7f3127de4c70>\nmodel = 'meta-llama/Llama-4-Scout-17B-16E-Instruct', provider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'text_then_weather_tool', 'expected': [{'answer': ['sol'], 'num_tool_calls': 0}, {'num_tool_calls': 1, 'to...], 'type': 'object'}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': '70 degrees and foggy'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\"\n        Test cases for multi-turn tool calling.\n        Tool calls are asserted.\n        Tool responses are provided in the test case.\n        Final response is asserted.\n        \"\"\"\n    \n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        # Create a copy of the messages list to avoid modifying the original\n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        # Use deepcopy to prevent modification across runs/parametrization\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        # keep going until either\n        # 1. we have messages to test in multi-turn\n        # 2. no messages but last message is tool response\n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            # do not take new messages if last message is tool response\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                # Ensure new_messages is a list of message objects\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    # If it's a single message object, add it directly\n                    messages.append(new_messages)\n    \n            # --- API Call ---\n            response = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=False,\n            )\n    \n            # --- Process Response ---\n            assistant_message = response.choices[0].message\n            messages.append(assistant_message.model_dump(exclude_unset=True))\n    \n            assert assistant_message.role == \"assistant\"\n    \n            # Get the expected result data\n            expected = expected_results.pop(0)\n            num_tool_calls = expected[\"num_tool_calls\"]\n    \n            # --- Assertions based on expected result ---\n            assert len(assistant_message.tool_calls or []) == num_tool_calls, (\n                f\"Expected {num_tool_calls} tool calls, but got {len(assistant_message.tool_calls or [])}\"\n            )\n    \n            if num_tool_calls > 0:\n                tool_call = assistant_message.tool_calls[0]\n                assert tool_call.function.name == expected[\"tool_name\"], (\n                    f\"Expected tool '{expected['tool_name']}', got '{tool_call.function.name}'\"\n                )\n                # Parse the JSON string arguments before comparing\n                actual_arguments = json.loads(tool_call.function.arguments)\n                assert actual_arguments == expected[\"tool_arguments\"], (\n                    f\"Expected arguments '{expected['tool_arguments']}', got '{actual_arguments}'\"\n                )\n    \n                # Prepare and append the tool response for the next turn\n                tool_response = tool_responses.pop(0)\n                messages.append(\n                    {\n                        \"role\": \"tool\",\n                        \"tool_call_id\": tool_call.id,\n                        \"content\": tool_response[\"response\"],\n                    }\n                )\n            else:\n                assert assistant_message.content is not None, \"Expected content, but none received.\"\n                expected_answers = expected[\"answer\"]  # This is now a list\n                content_lower = assistant_message.content.lower()\n>               assert any(ans.lower() in content_lower for ans in expected_answers), (\n                    f\"Expected one of {expected_answers} in content, but got: '{assistant_message.content}'\"\n                )\nE               AssertionError: Expected one of ['sol'] in content, but got: 'I cannot perform this task as it requires additional functionality that is not available in the given functions.'\nE               assert False\nE                +  where False = any(<generator object test_chat_non_streaming_multi_turn_tool_calling.<locals>.<genexpr> at 0x7f3127d3f610>)\n\ntests/verifications/openai_api/test_chat_completion.py:467: AssertionError"
       },
       "teardown": {
-        "duration": 0.0002513329964131117,
+        "duration": 0.00030991993844509125,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-weather_tool_then_text]",
-      "lineno": 360,
+      "lineno": 380,
       "outcome": "passed",
       "keywords": [
         "test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-weather_tool_then_text]",
@@ -2534,21 +2561,21 @@
         "case_id": "weather_tool_then_text"
       },
       "setup": {
-        "duration": 0.0098578748293221,
+        "duration": 0.07215368840843439,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.7098766670096666,
+        "duration": 2.01631036773324,
         "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.00051716691814363,
+        "duration": 0.0002633333206176758,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-add_product_tool]",
-      "lineno": 360,
+      "lineno": 380,
       "outcome": "passed",
       "keywords": [
         "test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-add_product_tool]",
@@ -2567,21 +2594,21 @@
         "case_id": "add_product_tool"
       },
       "setup": {
-        "duration": 0.007647499907761812,
+        "duration": 0.0734679875895381,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.932010707911104,
+        "duration": 1.122296486981213,
         "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.0001623330172151327,
+        "duration": 0.0003703571856021881,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-get_then_create_event_tool]",
-      "lineno": 360,
+      "lineno": 380,
       "outcome": "passed",
       "keywords": [
         "test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-get_then_create_event_tool]",
@@ -2600,21 +2627,21 @@
         "case_id": "get_then_create_event_tool"
       },
       "setup": {
-        "duration": 0.00763283297419548,
+        "duration": 0.07337972242385149,
         "outcome": "passed"
       },
       "call": {
-        "duration": 2.6117105002049357,
+        "duration": 5.233728421851993,
         "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.00015487498603761196,
+        "duration": 0.00024013593792915344,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-compare_monthly_expense_tool]",
-      "lineno": 360,
+      "lineno": 380,
       "outcome": "passed",
       "keywords": [
         "test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-compare_monthly_expense_tool]",
@@ -2633,21 +2660,21 @@
         "case_id": "compare_monthly_expense_tool"
       },
       "setup": {
-        "duration": 0.007260291138663888,
+        "duration": 0.07165702432394028,
         "outcome": "passed"
       },
       "call": {
-        "duration": 2.2083667907863855,
+        "duration": 2.579101173207164,
         "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.00043349992483854294,
+        "duration": 0.00022159796208143234,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-text_then_weather_tool]",
-      "lineno": 360,
+      "lineno": 380,
       "outcome": "failed",
       "keywords": [
         "test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-text_then_weather_tool]",
@@ -2666,34 +2693,34 @@
         "case_id": "text_then_weather_tool"
       },
       "setup": {
-        "duration": 0.010255292057991028,
+        "duration": 0.07499713078141212,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.3150998749770224,
+        "duration": 0.345451476983726,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 447,
-          "message": "AssertionError: Expected one of ['sol'] in content, but got: '{\"name\": null, \"parameters\": null}'\nassert False\n +  where False = any(<generator object test_chat_non_streaming_multi_turn_tool_calling.<locals>.<genexpr> at 0x10c68b990>)"
+          "path": "/home/erichuang/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
+          "lineno": 467,
+          "message": "AssertionError: Expected one of ['sol'] in content, but got: '{\"name\": null, \"parameters\": null}'\nassert False\n +  where False = any(<generator object test_chat_non_streaming_multi_turn_tool_calling.<locals>.<genexpr> at 0x7f3127fc2ab0>)"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 447,
+            "lineno": 467,
             "message": "AssertionError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-text_then_weather_tool]>>\nopenai_client = <openai.OpenAI object at 0x10c601db0>\nmodel = 'meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8'\nprovider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'text_then_weather_tool', 'expected': [{'answer': ['sol'], 'num_tool_calls': 0}, {'num_tool_calls': 1, 'to...], 'type': 'object'}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': '70 degrees and foggy'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\"\n        Test cases for multi-turn tool calling.\n        Tool calls are asserted.\n        Tool responses are provided in the test case.\n        Final response is asserted.\n        \"\"\"\n    \n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        # Create a copy of the messages list to avoid modifying the original\n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        # Use deepcopy to prevent modification across runs/parametrization\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        # keep going until either\n        # 1. we have messages to test in multi-turn\n        # 2. no messages but last message is tool response\n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            # do not take new messages if last message is tool response\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                # Ensure new_messages is a list of message objects\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    # If it's a single message object, add it directly\n                    messages.append(new_messages)\n    \n            # --- API Call ---\n            response = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=False,\n            )\n    \n            # --- Process Response ---\n            assistant_message = response.choices[0].message\n            messages.append(assistant_message.model_dump(exclude_unset=True))\n    \n            assert assistant_message.role == \"assistant\"\n    \n            # Get the expected result data\n            expected = expected_results.pop(0)\n            num_tool_calls = expected[\"num_tool_calls\"]\n    \n            # --- Assertions based on expected result ---\n            assert len(assistant_message.tool_calls or []) == num_tool_calls, (\n                f\"Expected {num_tool_calls} tool calls, but got {len(assistant_message.tool_calls or [])}\"\n            )\n    \n            if num_tool_calls > 0:\n                tool_call = assistant_message.tool_calls[0]\n                assert tool_call.function.name == expected[\"tool_name\"], (\n                    f\"Expected tool '{expected['tool_name']}', got '{tool_call.function.name}'\"\n                )\n                # Parse the JSON string arguments before comparing\n                actual_arguments = json.loads(tool_call.function.arguments)\n                assert actual_arguments == expected[\"tool_arguments\"], (\n                    f\"Expected arguments '{expected['tool_arguments']}', got '{actual_arguments}'\"\n                )\n    \n                # Prepare and append the tool response for the next turn\n                tool_response = tool_responses.pop(0)\n                messages.append(\n                    {\n                        \"role\": \"tool\",\n                        \"tool_call_id\": tool_call.id,\n                        \"content\": tool_response[\"response\"],\n                    }\n                )\n            else:\n                assert assistant_message.content is not None, \"Expected content, but none received.\"\n                expected_answers = expected[\"answer\"]  # This is now a list\n                content_lower = assistant_message.content.lower()\n>               assert any(ans.lower() in content_lower for ans in expected_answers), (\n                    f\"Expected one of {expected_answers} in content, but got: '{assistant_message.content}'\"\n                )\nE               AssertionError: Expected one of ['sol'] in content, but got: '{\"name\": null, \"parameters\": null}'\nE               assert False\nE                +  where False = any(<generator object test_chat_non_streaming_multi_turn_tool_calling.<locals>.<genexpr> at 0x10c68b990>)\n\ntests/verifications/openai_api/test_chat_completion.py:447: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-text_then_weather_tool]>>\nopenai_client = <openai.OpenAI object at 0x7f3127f2f370>\nmodel = 'meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8'\nprovider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'text_then_weather_tool', 'expected': [{'answer': ['sol'], 'num_tool_calls': 0}, {'num_tool_calls': 1, 'to...], 'type': 'object'}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': '70 degrees and foggy'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_non_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\"\n        Test cases for multi-turn tool calling.\n        Tool calls are asserted.\n        Tool responses are provided in the test case.\n        Final response is asserted.\n        \"\"\"\n    \n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        # Create a copy of the messages list to avoid modifying the original\n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        # Use deepcopy to prevent modification across runs/parametrization\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        # keep going until either\n        # 1. we have messages to test in multi-turn\n        # 2. no messages but last message is tool response\n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            # do not take new messages if last message is tool response\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                # Ensure new_messages is a list of message objects\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    # If it's a single message object, add it directly\n                    messages.append(new_messages)\n    \n            # --- API Call ---\n            response = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=False,\n            )\n    \n            # --- Process Response ---\n            assistant_message = response.choices[0].message\n            messages.append(assistant_message.model_dump(exclude_unset=True))\n    \n            assert assistant_message.role == \"assistant\"\n    \n            # Get the expected result data\n            expected = expected_results.pop(0)\n            num_tool_calls = expected[\"num_tool_calls\"]\n    \n            # --- Assertions based on expected result ---\n            assert len(assistant_message.tool_calls or []) == num_tool_calls, (\n                f\"Expected {num_tool_calls} tool calls, but got {len(assistant_message.tool_calls or [])}\"\n            )\n    \n            if num_tool_calls > 0:\n                tool_call = assistant_message.tool_calls[0]\n                assert tool_call.function.name == expected[\"tool_name\"], (\n                    f\"Expected tool '{expected['tool_name']}', got '{tool_call.function.name}'\"\n                )\n                # Parse the JSON string arguments before comparing\n                actual_arguments = json.loads(tool_call.function.arguments)\n                assert actual_arguments == expected[\"tool_arguments\"], (\n                    f\"Expected arguments '{expected['tool_arguments']}', got '{actual_arguments}'\"\n                )\n    \n                # Prepare and append the tool response for the next turn\n                tool_response = tool_responses.pop(0)\n                messages.append(\n                    {\n                        \"role\": \"tool\",\n                        \"tool_call_id\": tool_call.id,\n                        \"content\": tool_response[\"response\"],\n                    }\n                )\n            else:\n                assert assistant_message.content is not None, \"Expected content, but none received.\"\n                expected_answers = expected[\"answer\"]  # This is now a list\n                content_lower = assistant_message.content.lower()\n>               assert any(ans.lower() in content_lower for ans in expected_answers), (\n                    f\"Expected one of {expected_answers} in content, but got: '{assistant_message.content}'\"\n                )\nE               AssertionError: Expected one of ['sol'] in content, but got: '{\"name\": null, \"parameters\": null}'\nE               assert False\nE                +  where False = any(<generator object test_chat_non_streaming_multi_turn_tool_calling.<locals>.<genexpr> at 0x7f3127fc2ab0>)\n\ntests/verifications/openai_api/test_chat_completion.py:467: AssertionError"
       },
       "teardown": {
-        "duration": 0.000294666038826108,
+        "duration": 0.0003060000017285347,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-weather_tool_then_text]",
-      "lineno": 360,
+      "lineno": 380,
       "outcome": "passed",
       "keywords": [
         "test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-weather_tool_then_text]",
@@ -2712,21 +2739,21 @@
         "case_id": "weather_tool_then_text"
       },
       "setup": {
-        "duration": 0.007977542001754045,
+        "duration": 0.07219678908586502,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.5852054171264172,
+        "duration": 2.1842003548517823,
         "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.0005060839466750622,
+        "duration": 0.00023157335817813873,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-add_product_tool]",
-      "lineno": 360,
+      "lineno": 380,
       "outcome": "passed",
       "keywords": [
         "test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-add_product_tool]",
@@ -2745,21 +2772,21 @@
         "case_id": "add_product_tool"
       },
       "setup": {
-        "duration": 0.008944625034928322,
+        "duration": 0.07263681385666132,
         "outcome": "passed"
       },
       "call": {
-        "duration": 3.147708958014846,
+        "duration": 2.064652710221708,
         "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.0005282082129269838,
+        "duration": 0.0002187909558415413,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-get_then_create_event_tool]",
-      "lineno": 360,
+      "lineno": 380,
       "outcome": "passed",
       "keywords": [
         "test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-get_then_create_event_tool]",
@@ -2778,21 +2805,21 @@
         "case_id": "get_then_create_event_tool"
       },
       "setup": {
-        "duration": 0.009134833933785558,
+        "duration": 0.07442002464085817,
         "outcome": "passed"
       },
       "call": {
-        "duration": 3.0222986668813974,
+        "duration": 4.3001746302470565,
         "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.00014937506057322025,
+        "duration": 0.0002673650160431862,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-compare_monthly_expense_tool]",
-      "lineno": 360,
+      "lineno": 380,
       "outcome": "passed",
       "keywords": [
         "test_chat_non_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-compare_monthly_expense_tool]",
@@ -2811,21 +2838,21 @@
         "case_id": "compare_monthly_expense_tool"
       },
       "setup": {
-        "duration": 0.008050082949921489,
+        "duration": 0.0752437636256218,
         "outcome": "passed"
       },
       "call": {
-        "duration": 1.8753544169012457,
+        "duration": 3.1100223967805505,
         "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.00026400014758110046,
+        "duration": 0.00023829564452171326,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-3.3-70B-Instruct-Turbo-text_then_weather_tool]",
-      "lineno": 451,
+      "lineno": 471,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-3.3-70B-Instruct-Turbo-text_then_weather_tool]",
@@ -2844,34 +2871,34 @@
         "case_id": "text_then_weather_tool"
       },
       "setup": {
-        "duration": 0.012623165966942906,
+        "duration": 0.07147279102355242,
         "outcome": "passed"
       },
       "call": {
-        "duration": 1.3625199170783162,
+        "duration": 0.7697121743112803,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 527,
-          "message": "AssertionError: Expected content, but none received.\nassert ('' is not None and '' != '')"
+          "path": "/home/erichuang/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
+          "lineno": 521,
+          "message": "AssertionError: Expected 0 tool calls, but got 1\nassert 1 == 0\n +  where 1 = len(([{'function': {'arguments': '{\"location\":\"San Francisco, CA\"}', 'name': 'get_weather'}, 'id': 'call_kpb5gnyu9klkx2yzft43dxez', 'type': 'function'}]))"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 527,
+            "lineno": 521,
             "message": "AssertionError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-3.3-70B-Instruct-Turbo-text_then_weather_tool]>>\nopenai_client = <openai.OpenAI object at 0x10c69cee0>\nmodel = 'meta-llama/Llama-3.3-70B-Instruct-Turbo', provider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'text_then_weather_tool', 'expected': [{'answer': ['sol'], 'num_tool_calls': 0}, {'num_tool_calls': 1, 'to...], 'type': 'object'}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': '70 degrees and foggy'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n            stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n    \n            # --- Process Stream ---\n            accumulated_content, accumulated_tool_calls = _accumulate_streaming_tool_calls(stream)\n    \n            # --- Construct Assistant Message for History ---\n            assistant_message_dict = {\"role\": \"assistant\"}\n            if accumulated_content:\n                assistant_message_dict[\"content\"] = accumulated_content\n            if accumulated_tool_calls:\n                assistant_message_dict[\"tool_calls\"] = accumulated_tool_calls\n    \n            messages.append(assistant_message_dict)\n    \n            # --- Assertions ---\n            expected = expected_results.pop(0)\n            num_tool_calls = expected[\"num_tool_calls\"]\n    \n            assert len(accumulated_tool_calls or []) == num_tool_calls, (\n                f\"Expected {num_tool_calls} tool calls, but got {len(accumulated_tool_calls or [])}\"\n            )\n    \n            if num_tool_calls > 0:\n                # Use the first accumulated tool call for assertion\n                tool_call = accumulated_tool_calls[0]\n                assert tool_call[\"function\"][\"name\"] == expected[\"tool_name\"], (\n                    f\"Expected tool '{expected['tool_name']}', got '{tool_call['function']['name']}'\"\n                )\n                # Parse the accumulated arguments string for comparison\n                actual_arguments = json.loads(tool_call[\"function\"][\"arguments\"])\n                assert actual_arguments == expected[\"tool_arguments\"], (\n                    f\"Expected arguments '{expected['tool_arguments']}', got '{actual_arguments}'\"\n                )\n    \n                # Prepare and append the tool response for the next turn\n                tool_response = tool_responses.pop(0)\n                messages.append(\n                    {\n                        \"role\": \"tool\",\n                        \"tool_call_id\": tool_call[\"id\"],\n                        \"content\": tool_response[\"response\"],\n                    }\n                )\n            else:\n>               assert accumulated_content is not None and accumulated_content != \"\", \"Expected content, but none received.\"\nE               AssertionError: Expected content, but none received.\nE               assert ('' is not None and '' != '')\n\ntests/verifications/openai_api/test_chat_completion.py:527: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-3.3-70B-Instruct-Turbo-text_then_weather_tool]>>\nopenai_client = <openai.OpenAI object at 0x7f3127dae0b0>\nmodel = 'meta-llama/Llama-3.3-70B-Instruct-Turbo', provider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'text_then_weather_tool', 'expected': [{'answer': ['sol'], 'num_tool_calls': 0}, {'num_tool_calls': 1, 'to...], 'type': 'object'}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': '70 degrees and foggy'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n            stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n    \n            # --- Process Stream ---\n            accumulated_content, accumulated_tool_calls = _accumulate_streaming_tool_calls(stream)\n    \n            # --- Construct Assistant Message for History ---\n            assistant_message_dict = {\"role\": \"assistant\"}\n            if accumulated_content:\n                assistant_message_dict[\"content\"] = accumulated_content\n            if accumulated_tool_calls:\n                assistant_message_dict[\"tool_calls\"] = accumulated_tool_calls\n    \n            messages.append(assistant_message_dict)\n    \n            # --- Assertions ---\n            expected = expected_results.pop(0)\n            num_tool_calls = expected[\"num_tool_calls\"]\n    \n>           assert len(accumulated_tool_calls or []) == num_tool_calls, (\n                f\"Expected {num_tool_calls} tool calls, but got {len(accumulated_tool_calls or [])}\"\n            )\nE           AssertionError: Expected 0 tool calls, but got 1\nE           assert 1 == 0\nE            +  where 1 = len(([{'function': {'arguments': '{\"location\":\"San Francisco, CA\"}', 'name': 'get_weather'}, 'id': 'call_kpb5gnyu9klkx2yzft43dxez', 'type': 'function'}]))\n\ntests/verifications/openai_api/test_chat_completion.py:521: AssertionError"
       },
       "teardown": {
-        "duration": 0.00024533295072615147,
+        "duration": 0.0003948565572500229,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-3.3-70B-Instruct-Turbo-weather_tool_then_text]",
-      "lineno": 451,
+      "lineno": 471,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-3.3-70B-Instruct-Turbo-weather_tool_then_text]",
@@ -2890,34 +2917,34 @@
         "case_id": "weather_tool_then_text"
       },
       "setup": {
-        "duration": 0.007315667113289237,
+        "duration": 0.0739708598703146,
         "outcome": "passed"
       },
       "call": {
-        "duration": 1.8457820839248598,
+        "duration": 0.8291563373059034,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 527,
+          "path": "/home/erichuang/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
+          "lineno": 547,
           "message": "AssertionError: Expected content, but none received.\nassert ('' is not None and '' != '')"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 527,
+            "lineno": 547,
             "message": "AssertionError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-3.3-70B-Instruct-Turbo-weather_tool_then_text]>>\nopenai_client = <openai.OpenAI object at 0x10c6bf9d0>\nmodel = 'meta-llama/Llama-3.3-70B-Instruct-Turbo', provider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'weather_tool_then_text', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'location': 'San Francisco...], 'type': 'object'}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': '70 degrees and foggy'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n            stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n    \n            # --- Process Stream ---\n            accumulated_content, accumulated_tool_calls = _accumulate_streaming_tool_calls(stream)\n    \n            # --- Construct Assistant Message for History ---\n            assistant_message_dict = {\"role\": \"assistant\"}\n            if accumulated_content:\n                assistant_message_dict[\"content\"] = accumulated_content\n            if accumulated_tool_calls:\n                assistant_message_dict[\"tool_calls\"] = accumulated_tool_calls\n    \n            messages.append(assistant_message_dict)\n    \n            # --- Assertions ---\n            expected = expected_results.pop(0)\n            num_tool_calls = expected[\"num_tool_calls\"]\n    \n            assert len(accumulated_tool_calls or []) == num_tool_calls, (\n                f\"Expected {num_tool_calls} tool calls, but got {len(accumulated_tool_calls or [])}\"\n            )\n    \n            if num_tool_calls > 0:\n                # Use the first accumulated tool call for assertion\n                tool_call = accumulated_tool_calls[0]\n                assert tool_call[\"function\"][\"name\"] == expected[\"tool_name\"], (\n                    f\"Expected tool '{expected['tool_name']}', got '{tool_call['function']['name']}'\"\n                )\n                # Parse the accumulated arguments string for comparison\n                actual_arguments = json.loads(tool_call[\"function\"][\"arguments\"])\n                assert actual_arguments == expected[\"tool_arguments\"], (\n                    f\"Expected arguments '{expected['tool_arguments']}', got '{actual_arguments}'\"\n                )\n    \n                # Prepare and append the tool response for the next turn\n                tool_response = tool_responses.pop(0)\n                messages.append(\n                    {\n                        \"role\": \"tool\",\n                        \"tool_call_id\": tool_call[\"id\"],\n                        \"content\": tool_response[\"response\"],\n                    }\n                )\n            else:\n>               assert accumulated_content is not None and accumulated_content != \"\", \"Expected content, but none received.\"\nE               AssertionError: Expected content, but none received.\nE               assert ('' is not None and '' != '')\n\ntests/verifications/openai_api/test_chat_completion.py:527: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-3.3-70B-Instruct-Turbo-weather_tool_then_text]>>\nopenai_client = <openai.OpenAI object at 0x7f3127f3b220>\nmodel = 'meta-llama/Llama-3.3-70B-Instruct-Turbo', provider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'weather_tool_then_text', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'location': 'San Francisco...], 'type': 'object'}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': '70 degrees and foggy'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n            stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n    \n            # --- Process Stream ---\n            accumulated_content, accumulated_tool_calls = _accumulate_streaming_tool_calls(stream)\n    \n            # --- Construct Assistant Message for History ---\n            assistant_message_dict = {\"role\": \"assistant\"}\n            if accumulated_content:\n                assistant_message_dict[\"content\"] = accumulated_content\n            if accumulated_tool_calls:\n                assistant_message_dict[\"tool_calls\"] = accumulated_tool_calls\n    \n            messages.append(assistant_message_dict)\n    \n            # --- Assertions ---\n            expected = expected_results.pop(0)\n            num_tool_calls = expected[\"num_tool_calls\"]\n    \n            assert len(accumulated_tool_calls or []) == num_tool_calls, (\n                f\"Expected {num_tool_calls} tool calls, but got {len(accumulated_tool_calls or [])}\"\n            )\n    \n            if num_tool_calls > 0:\n                # Use the first accumulated tool call for assertion\n                tool_call = accumulated_tool_calls[0]\n                assert tool_call[\"function\"][\"name\"] == expected[\"tool_name\"], (\n                    f\"Expected tool '{expected['tool_name']}', got '{tool_call['function']['name']}'\"\n                )\n                # Parse the accumulated arguments string for comparison\n                actual_arguments = json.loads(tool_call[\"function\"][\"arguments\"])\n                assert actual_arguments == expected[\"tool_arguments\"], (\n                    f\"Expected arguments '{expected['tool_arguments']}', got '{actual_arguments}'\"\n                )\n    \n                # Prepare and append the tool response for the next turn\n                tool_response = tool_responses.pop(0)\n                messages.append(\n                    {\n                        \"role\": \"tool\",\n                        \"tool_call_id\": tool_call[\"id\"],\n                        \"content\": tool_response[\"response\"],\n                    }\n                )\n            else:\n>               assert accumulated_content is not None and accumulated_content != \"\", \"Expected content, but none received.\"\nE               AssertionError: Expected content, but none received.\nE               assert ('' is not None and '' != '')\n\ntests/verifications/openai_api/test_chat_completion.py:547: AssertionError"
       },
       "teardown": {
-        "duration": 0.00028316606767475605,
+        "duration": 0.0003177514299750328,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-3.3-70B-Instruct-Turbo-add_product_tool]",
-      "lineno": 451,
+      "lineno": 471,
       "outcome": "passed",
       "keywords": [
         "test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-3.3-70B-Instruct-Turbo-add_product_tool]",
@@ -2936,21 +2963,21 @@
         "case_id": "add_product_tool"
       },
       "setup": {
-        "duration": 0.007260374957695603,
+        "duration": 0.07326000090688467,
         "outcome": "passed"
       },
       "call": {
-        "duration": 2.4652266670018435,
+        "duration": 2.20385564584285,
         "outcome": "passed"
       },
       "teardown": {
-        "duration": 0.00016629090532660484,
+        "duration": 0.00035414285957813263,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-3.3-70B-Instruct-Turbo-get_then_create_event_tool]",
-      "lineno": 451,
+      "lineno": 471,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-3.3-70B-Instruct-Turbo-get_then_create_event_tool]",
@@ -2969,34 +2996,34 @@
         "case_id": "get_then_create_event_tool"
       },
       "setup": {
-        "duration": 0.025101042119786143,
+        "duration": 0.10739517118781805,
         "outcome": "passed"
       },
       "call": {
-        "duration": 1.8374365421477705,
+        "duration": 3.1176233775913715,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 527,
+          "path": "/home/erichuang/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
+          "lineno": 547,
           "message": "AssertionError: Expected content, but none received.\nassert ('' is not None and '' != '')"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 527,
+            "lineno": 547,
             "message": "AssertionError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-3.3-70B-Instruct-Turbo-get_then_create_event_tool]>>\nopenai_client = <openai.OpenAI object at 0x10ca6a140>\nmodel = 'meta-llama/Llama-3.3-70B-Instruct-Turbo', provider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'get_then_create_event_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'date': '2025-03-03', ...ents found for 2025-03-03 at 10:00'}\"}, {'response': \"{'response': 'Successfully created new event with id: e_123'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n            stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n    \n            # --- Process Stream ---\n            accumulated_content, accumulated_tool_calls = _accumulate_streaming_tool_calls(stream)\n    \n            # --- Construct Assistant Message for History ---\n            assistant_message_dict = {\"role\": \"assistant\"}\n            if accumulated_content:\n                assistant_message_dict[\"content\"] = accumulated_content\n            if accumulated_tool_calls:\n                assistant_message_dict[\"tool_calls\"] = accumulated_tool_calls\n    \n            messages.append(assistant_message_dict)\n    \n            # --- Assertions ---\n            expected = expected_results.pop(0)\n            num_tool_calls = expected[\"num_tool_calls\"]\n    \n            assert len(accumulated_tool_calls or []) == num_tool_calls, (\n                f\"Expected {num_tool_calls} tool calls, but got {len(accumulated_tool_calls or [])}\"\n            )\n    \n            if num_tool_calls > 0:\n                # Use the first accumulated tool call for assertion\n                tool_call = accumulated_tool_calls[0]\n                assert tool_call[\"function\"][\"name\"] == expected[\"tool_name\"], (\n                    f\"Expected tool '{expected['tool_name']}', got '{tool_call['function']['name']}'\"\n                )\n                # Parse the accumulated arguments string for comparison\n                actual_arguments = json.loads(tool_call[\"function\"][\"arguments\"])\n                assert actual_arguments == expected[\"tool_arguments\"], (\n                    f\"Expected arguments '{expected['tool_arguments']}', got '{actual_arguments}'\"\n                )\n    \n                # Prepare and append the tool response for the next turn\n                tool_response = tool_responses.pop(0)\n                messages.append(\n                    {\n                        \"role\": \"tool\",\n                        \"tool_call_id\": tool_call[\"id\"],\n                        \"content\": tool_response[\"response\"],\n                    }\n                )\n            else:\n>               assert accumulated_content is not None and accumulated_content != \"\", \"Expected content, but none received.\"\nE               AssertionError: Expected content, but none received.\nE               assert ('' is not None and '' != '')\n\ntests/verifications/openai_api/test_chat_completion.py:527: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-3.3-70B-Instruct-Turbo-get_then_create_event_tool]>>\nopenai_client = <openai.OpenAI object at 0x7f3127e2b580>\nmodel = 'meta-llama/Llama-3.3-70B-Instruct-Turbo', provider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'get_then_create_event_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'date': '2025-03-03', ...ents found for 2025-03-03 at 10:00'}\"}, {'response': \"{'response': 'Successfully created new event with id: e_123'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n            stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n    \n            # --- Process Stream ---\n            accumulated_content, accumulated_tool_calls = _accumulate_streaming_tool_calls(stream)\n    \n            # --- Construct Assistant Message for History ---\n            assistant_message_dict = {\"role\": \"assistant\"}\n            if accumulated_content:\n                assistant_message_dict[\"content\"] = accumulated_content\n            if accumulated_tool_calls:\n                assistant_message_dict[\"tool_calls\"] = accumulated_tool_calls\n    \n            messages.append(assistant_message_dict)\n    \n            # --- Assertions ---\n            expected = expected_results.pop(0)\n            num_tool_calls = expected[\"num_tool_calls\"]\n    \n            assert len(accumulated_tool_calls or []) == num_tool_calls, (\n                f\"Expected {num_tool_calls} tool calls, but got {len(accumulated_tool_calls or [])}\"\n            )\n    \n            if num_tool_calls > 0:\n                # Use the first accumulated tool call for assertion\n                tool_call = accumulated_tool_calls[0]\n                assert tool_call[\"function\"][\"name\"] == expected[\"tool_name\"], (\n                    f\"Expected tool '{expected['tool_name']}', got '{tool_call['function']['name']}'\"\n                )\n                # Parse the accumulated arguments string for comparison\n                actual_arguments = json.loads(tool_call[\"function\"][\"arguments\"])\n                assert actual_arguments == expected[\"tool_arguments\"], (\n                    f\"Expected arguments '{expected['tool_arguments']}', got '{actual_arguments}'\"\n                )\n    \n                # Prepare and append the tool response for the next turn\n                tool_response = tool_responses.pop(0)\n                messages.append(\n                    {\n                        \"role\": \"tool\",\n                        \"tool_call_id\": tool_call[\"id\"],\n                        \"content\": tool_response[\"response\"],\n                    }\n                )\n            else:\n>               assert accumulated_content is not None and accumulated_content != \"\", \"Expected content, but none received.\"\nE               AssertionError: Expected content, but none received.\nE               assert ('' is not None and '' != '')\n\ntests/verifications/openai_api/test_chat_completion.py:547: AssertionError"
       },
       "teardown": {
-        "duration": 0.00024591688998043537,
+        "duration": 0.0003009289503097534,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-3.3-70B-Instruct-Turbo-compare_monthly_expense_tool]",
-      "lineno": 451,
+      "lineno": 471,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-3.3-70B-Instruct-Turbo-compare_monthly_expense_tool]",
@@ -3015,34 +3042,34 @@
         "case_id": "compare_monthly_expense_tool"
       },
       "setup": {
-        "duration": 0.006902666063979268,
+        "duration": 0.07599783595651388,
         "outcome": "passed"
       },
       "call": {
-        "duration": 2.5201194169931114,
+        "duration": 2.0640214709565043,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 527,
+          "path": "/home/erichuang/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
+          "lineno": 547,
           "message": "AssertionError: Expected content, but none received.\nassert ('' is not None and '' != '')"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 527,
+            "lineno": 547,
             "message": "AssertionError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-3.3-70B-Instruct-Turbo-compare_monthly_expense_tool]>>\nopenai_client = <openai.OpenAI object at 0x10ca55870>\nmodel = 'meta-llama/Llama-3.3-70B-Instruct-Turbo', provider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'compare_monthly_expense_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'month': 1, 'year': ... 'Total expenses for January 2025: $1000'}\"}, {'response': \"{'response': 'Total expenses for February 2024: $2000'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n            stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n    \n            # --- Process Stream ---\n            accumulated_content, accumulated_tool_calls = _accumulate_streaming_tool_calls(stream)\n    \n            # --- Construct Assistant Message for History ---\n            assistant_message_dict = {\"role\": \"assistant\"}\n            if accumulated_content:\n                assistant_message_dict[\"content\"] = accumulated_content\n            if accumulated_tool_calls:\n                assistant_message_dict[\"tool_calls\"] = accumulated_tool_calls\n    \n            messages.append(assistant_message_dict)\n    \n            # --- Assertions ---\n            expected = expected_results.pop(0)\n            num_tool_calls = expected[\"num_tool_calls\"]\n    \n            assert len(accumulated_tool_calls or []) == num_tool_calls, (\n                f\"Expected {num_tool_calls} tool calls, but got {len(accumulated_tool_calls or [])}\"\n            )\n    \n            if num_tool_calls > 0:\n                # Use the first accumulated tool call for assertion\n                tool_call = accumulated_tool_calls[0]\n                assert tool_call[\"function\"][\"name\"] == expected[\"tool_name\"], (\n                    f\"Expected tool '{expected['tool_name']}', got '{tool_call['function']['name']}'\"\n                )\n                # Parse the accumulated arguments string for comparison\n                actual_arguments = json.loads(tool_call[\"function\"][\"arguments\"])\n                assert actual_arguments == expected[\"tool_arguments\"], (\n                    f\"Expected arguments '{expected['tool_arguments']}', got '{actual_arguments}'\"\n                )\n    \n                # Prepare and append the tool response for the next turn\n                tool_response = tool_responses.pop(0)\n                messages.append(\n                    {\n                        \"role\": \"tool\",\n                        \"tool_call_id\": tool_call[\"id\"],\n                        \"content\": tool_response[\"response\"],\n                    }\n                )\n            else:\n>               assert accumulated_content is not None and accumulated_content != \"\", \"Expected content, but none received.\"\nE               AssertionError: Expected content, but none received.\nE               assert ('' is not None and '' != '')\n\ntests/verifications/openai_api/test_chat_completion.py:527: AssertionError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-3.3-70B-Instruct-Turbo-compare_monthly_expense_tool]>>\nopenai_client = <openai.OpenAI object at 0x7f3127f12a10>\nmodel = 'meta-llama/Llama-3.3-70B-Instruct-Turbo', provider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'compare_monthly_expense_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'month': 1, 'year': ... 'Total expenses for January 2025: $1000'}\"}, {'response': \"{'response': 'Total expenses for February 2024: $2000'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n            stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n    \n            # --- Process Stream ---\n            accumulated_content, accumulated_tool_calls = _accumulate_streaming_tool_calls(stream)\n    \n            # --- Construct Assistant Message for History ---\n            assistant_message_dict = {\"role\": \"assistant\"}\n            if accumulated_content:\n                assistant_message_dict[\"content\"] = accumulated_content\n            if accumulated_tool_calls:\n                assistant_message_dict[\"tool_calls\"] = accumulated_tool_calls\n    \n            messages.append(assistant_message_dict)\n    \n            # --- Assertions ---\n            expected = expected_results.pop(0)\n            num_tool_calls = expected[\"num_tool_calls\"]\n    \n            assert len(accumulated_tool_calls or []) == num_tool_calls, (\n                f\"Expected {num_tool_calls} tool calls, but got {len(accumulated_tool_calls or [])}\"\n            )\n    \n            if num_tool_calls > 0:\n                # Use the first accumulated tool call for assertion\n                tool_call = accumulated_tool_calls[0]\n                assert tool_call[\"function\"][\"name\"] == expected[\"tool_name\"], (\n                    f\"Expected tool '{expected['tool_name']}', got '{tool_call['function']['name']}'\"\n                )\n                # Parse the accumulated arguments string for comparison\n                actual_arguments = json.loads(tool_call[\"function\"][\"arguments\"])\n                assert actual_arguments == expected[\"tool_arguments\"], (\n                    f\"Expected arguments '{expected['tool_arguments']}', got '{actual_arguments}'\"\n                )\n    \n                # Prepare and append the tool response for the next turn\n                tool_response = tool_responses.pop(0)\n                messages.append(\n                    {\n                        \"role\": \"tool\",\n                        \"tool_call_id\": tool_call[\"id\"],\n                        \"content\": tool_response[\"response\"],\n                    }\n                )\n            else:\n>               assert accumulated_content is not None and accumulated_content != \"\", \"Expected content, but none received.\"\nE               AssertionError: Expected content, but none received.\nE               assert ('' is not None and '' != '')\n\ntests/verifications/openai_api/test_chat_completion.py:547: AssertionError"
       },
       "teardown": {
-        "duration": 0.00026037520729005337,
+        "duration": 0.00029294565320014954,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-text_then_weather_tool]",
-      "lineno": 451,
+      "lineno": 471,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-text_then_weather_tool]",
@@ -3061,39 +3088,39 @@
         "case_id": "text_then_weather_tool"
       },
       "setup": {
-        "duration": 0.008579750079661608,
+        "duration": 0.07202461268752813,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.3671212091576308,
+        "duration": 0.6093930723145604,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 588,
+          "path": "/home/erichuang/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
+          "lineno": 688,
           "message": "IndexError: list index out of range"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 486,
+            "lineno": 506,
             "message": ""
           },
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 588,
+            "lineno": 688,
             "message": "IndexError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-text_then_weather_tool]>>\nopenai_client = <openai.OpenAI object at 0x10c6c5360>\nmodel = 'meta-llama/Llama-4-Scout-17B-16E-Instruct', provider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'text_then_weather_tool', 'expected': [{'answer': ['sol'], 'num_tool_calls': 0}, {'num_tool_calls': 1, 'to...], 'type': 'object'}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': '70 degrees and foggy'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n            stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n    \n            # --- Process Stream ---\n>           accumulated_content, accumulated_tool_calls = _accumulate_streaming_tool_calls(stream)\n\ntests/verifications/openai_api/test_chat_completion.py:486: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nstream = <openai.Stream object at 0x10ca66140>\n\n    def _accumulate_streaming_tool_calls(stream):\n        \"\"\"Accumulates tool calls and content from a streaming ChatCompletion response.\"\"\"\n        tool_calls_buffer = {}\n        current_id = None\n        full_content = \"\"  # Initialize content accumulator\n        # Process streaming chunks\n        for chunk in stream:\n>           choice = chunk.choices[0]\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:588: IndexError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-text_then_weather_tool]>>\nopenai_client = <openai.OpenAI object at 0x7f3127dad4e0>\nmodel = 'meta-llama/Llama-4-Scout-17B-16E-Instruct', provider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'text_then_weather_tool', 'expected': [{'answer': ['sol'], 'num_tool_calls': 0}, {'num_tool_calls': 1, 'to...], 'type': 'object'}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': '70 degrees and foggy'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n            stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n    \n            # --- Process Stream ---\n>           accumulated_content, accumulated_tool_calls = _accumulate_streaming_tool_calls(stream)\n\ntests/verifications/openai_api/test_chat_completion.py:506: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nstream = <openai.Stream object at 0x7f3127e18760>\n\n    def _accumulate_streaming_tool_calls(stream):\n        \"\"\"Accumulates tool calls and content from a streaming ChatCompletion response.\"\"\"\n        tool_calls_buffer = {}\n        current_id = None\n        full_content = \"\"  # Initialize content accumulator\n        # Process streaming chunks\n        for chunk in stream:\n>           choice = chunk.choices[0]\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:688: IndexError"
       },
       "teardown": {
-        "duration": 0.00025516608729958534,
+        "duration": 0.00030322466045618057,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-weather_tool_then_text]",
-      "lineno": 451,
+      "lineno": 471,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-weather_tool_then_text]",
@@ -3112,39 +3139,39 @@
         "case_id": "weather_tool_then_text"
       },
       "setup": {
-        "duration": 0.008525707991793752,
+        "duration": 0.06955079920589924,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.49603341589681804,
+        "duration": 0.4394088052213192,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 588,
+          "path": "/home/erichuang/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
+          "lineno": 688,
           "message": "IndexError: list index out of range"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 486,
+            "lineno": 506,
             "message": ""
           },
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 588,
+            "lineno": 688,
             "message": "IndexError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-weather_tool_then_text]>>\nopenai_client = <openai.OpenAI object at 0x10c6bc6a0>\nmodel = 'meta-llama/Llama-4-Scout-17B-16E-Instruct', provider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'weather_tool_then_text', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'location': 'San Francisco...], 'type': 'object'}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': '70 degrees and foggy'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n            stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n    \n            # --- Process Stream ---\n>           accumulated_content, accumulated_tool_calls = _accumulate_streaming_tool_calls(stream)\n\ntests/verifications/openai_api/test_chat_completion.py:486: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nstream = <openai.Stream object at 0x10c175ff0>\n\n    def _accumulate_streaming_tool_calls(stream):\n        \"\"\"Accumulates tool calls and content from a streaming ChatCompletion response.\"\"\"\n        tool_calls_buffer = {}\n        current_id = None\n        full_content = \"\"  # Initialize content accumulator\n        # Process streaming chunks\n        for chunk in stream:\n>           choice = chunk.choices[0]\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:588: IndexError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-weather_tool_then_text]>>\nopenai_client = <openai.OpenAI object at 0x7f312800e5c0>\nmodel = 'meta-llama/Llama-4-Scout-17B-16E-Instruct', provider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'weather_tool_then_text', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'location': 'San Francisco...], 'type': 'object'}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': '70 degrees and foggy'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n            stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n    \n            # --- Process Stream ---\n>           accumulated_content, accumulated_tool_calls = _accumulate_streaming_tool_calls(stream)\n\ntests/verifications/openai_api/test_chat_completion.py:506: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nstream = <openai.Stream object at 0x7f3127e351e0>\n\n    def _accumulate_streaming_tool_calls(stream):\n        \"\"\"Accumulates tool calls and content from a streaming ChatCompletion response.\"\"\"\n        tool_calls_buffer = {}\n        current_id = None\n        full_content = \"\"  # Initialize content accumulator\n        # Process streaming chunks\n        for chunk in stream:\n>           choice = chunk.choices[0]\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:688: IndexError"
       },
       "teardown": {
-        "duration": 0.00023645791225135326,
+        "duration": 0.00038521457463502884,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-add_product_tool]",
-      "lineno": 451,
+      "lineno": 471,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-add_product_tool]",
@@ -3163,39 +3190,39 @@
         "case_id": "add_product_tool"
       },
       "setup": {
-        "duration": 0.006683999905362725,
+        "duration": 0.07154521346092224,
         "outcome": "passed"
       },
       "call": {
-        "duration": 1.8375662080943584,
+        "duration": 4.631643522530794,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 588,
+          "path": "/home/erichuang/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
+          "lineno": 688,
           "message": "IndexError: list index out of range"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 486,
+            "lineno": 506,
             "message": ""
           },
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 588,
+            "lineno": 688,
             "message": "IndexError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-add_product_tool]>>\nopenai_client = <openai.OpenAI object at 0x10c61d5a0>\nmodel = 'meta-llama/Llama-4-Scout-17B-16E-Instruct', provider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'add_product_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'inStock': True, 'name': 'Widget...}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': 'Successfully added product with id: 123'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n            stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n    \n            # --- Process Stream ---\n>           accumulated_content, accumulated_tool_calls = _accumulate_streaming_tool_calls(stream)\n\ntests/verifications/openai_api/test_chat_completion.py:486: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nstream = <openai.Stream object at 0x10c6a32e0>\n\n    def _accumulate_streaming_tool_calls(stream):\n        \"\"\"Accumulates tool calls and content from a streaming ChatCompletion response.\"\"\"\n        tool_calls_buffer = {}\n        current_id = None\n        full_content = \"\"  # Initialize content accumulator\n        # Process streaming chunks\n        for chunk in stream:\n>           choice = chunk.choices[0]\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:588: IndexError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-add_product_tool]>>\nopenai_client = <openai.OpenAI object at 0x7f3127e1a8c0>\nmodel = 'meta-llama/Llama-4-Scout-17B-16E-Instruct', provider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'add_product_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'inStock': True, 'name': 'Widget...}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': 'Successfully added product with id: 123'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n            stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n    \n            # --- Process Stream ---\n>           accumulated_content, accumulated_tool_calls = _accumulate_streaming_tool_calls(stream)\n\ntests/verifications/openai_api/test_chat_completion.py:506: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nstream = <openai.Stream object at 0x7f3127de5660>\n\n    def _accumulate_streaming_tool_calls(stream):\n        \"\"\"Accumulates tool calls and content from a streaming ChatCompletion response.\"\"\"\n        tool_calls_buffer = {}\n        current_id = None\n        full_content = \"\"  # Initialize content accumulator\n        # Process streaming chunks\n        for chunk in stream:\n>           choice = chunk.choices[0]\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:688: IndexError"
       },
       "teardown": {
-        "duration": 0.00024145888164639473,
+        "duration": 0.0003909459337592125,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-get_then_create_event_tool]",
-      "lineno": 451,
+      "lineno": 471,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-get_then_create_event_tool]",
@@ -3214,39 +3241,39 @@
         "case_id": "get_then_create_event_tool"
       },
       "setup": {
-        "duration": 0.01287274993956089,
+        "duration": 0.07234212290495634,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.7619118748698384,
+        "duration": 0.5346909575164318,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 588,
+          "path": "/home/erichuang/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
+          "lineno": 688,
           "message": "IndexError: list index out of range"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 486,
+            "lineno": 506,
             "message": ""
           },
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 588,
+            "lineno": 688,
             "message": "IndexError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-get_then_create_event_tool]>>\nopenai_client = <openai.OpenAI object at 0x10ce5d0c0>\nmodel = 'meta-llama/Llama-4-Scout-17B-16E-Instruct', provider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'get_then_create_event_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'date': '2025-03-03', ...ents found for 2025-03-03 at 10:00'}\"}, {'response': \"{'response': 'Successfully created new event with id: e_123'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n            stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n    \n            # --- Process Stream ---\n>           accumulated_content, accumulated_tool_calls = _accumulate_streaming_tool_calls(stream)\n\ntests/verifications/openai_api/test_chat_completion.py:486: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nstream = <openai.Stream object at 0x10ce5c190>\n\n    def _accumulate_streaming_tool_calls(stream):\n        \"\"\"Accumulates tool calls and content from a streaming ChatCompletion response.\"\"\"\n        tool_calls_buffer = {}\n        current_id = None\n        full_content = \"\"  # Initialize content accumulator\n        # Process streaming chunks\n        for chunk in stream:\n>           choice = chunk.choices[0]\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:588: IndexError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-get_then_create_event_tool]>>\nopenai_client = <openai.OpenAI object at 0x7f3127dbe8c0>\nmodel = 'meta-llama/Llama-4-Scout-17B-16E-Instruct', provider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'get_then_create_event_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'date': '2025-03-03', ...ents found for 2025-03-03 at 10:00'}\"}, {'response': \"{'response': 'Successfully created new event with id: e_123'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n            stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n    \n            # --- Process Stream ---\n>           accumulated_content, accumulated_tool_calls = _accumulate_streaming_tool_calls(stream)\n\ntests/verifications/openai_api/test_chat_completion.py:506: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nstream = <openai.Stream object at 0x7f3127d717e0>\n\n    def _accumulate_streaming_tool_calls(stream):\n        \"\"\"Accumulates tool calls and content from a streaming ChatCompletion response.\"\"\"\n        tool_calls_buffer = {}\n        current_id = None\n        full_content = \"\"  # Initialize content accumulator\n        # Process streaming chunks\n        for chunk in stream:\n>           choice = chunk.choices[0]\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:688: IndexError"
       },
       "teardown": {
-        "duration": 0.00023716595023870468,
+        "duration": 0.00038490165024995804,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-compare_monthly_expense_tool]",
-      "lineno": 451,
+      "lineno": 471,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-compare_monthly_expense_tool]",
@@ -3265,39 +3292,39 @@
         "case_id": "compare_monthly_expense_tool"
       },
       "setup": {
-        "duration": 0.008577040862292051,
+        "duration": 0.0718430494889617,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.44602233287878335,
+        "duration": 0.57699906360358,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 588,
+          "path": "/home/erichuang/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
+          "lineno": 688,
           "message": "IndexError: list index out of range"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 486,
+            "lineno": 506,
             "message": ""
           },
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 588,
+            "lineno": 688,
             "message": "IndexError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-compare_monthly_expense_tool]>>\nopenai_client = <openai.OpenAI object at 0x10ce5c3a0>\nmodel = 'meta-llama/Llama-4-Scout-17B-16E-Instruct', provider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'compare_monthly_expense_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'month': 1, 'year': ... 'Total expenses for January 2025: $1000'}\"}, {'response': \"{'response': 'Total expenses for February 2024: $2000'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n            stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n    \n            # --- Process Stream ---\n>           accumulated_content, accumulated_tool_calls = _accumulate_streaming_tool_calls(stream)\n\ntests/verifications/openai_api/test_chat_completion.py:486: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nstream = <openai.Stream object at 0x10ca567d0>\n\n    def _accumulate_streaming_tool_calls(stream):\n        \"\"\"Accumulates tool calls and content from a streaming ChatCompletion response.\"\"\"\n        tool_calls_buffer = {}\n        current_id = None\n        full_content = \"\"  # Initialize content accumulator\n        # Process streaming chunks\n        for chunk in stream:\n>           choice = chunk.choices[0]\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:588: IndexError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Scout-17B-16E-Instruct-compare_monthly_expense_tool]>>\nopenai_client = <openai.OpenAI object at 0x7f3127f2e350>\nmodel = 'meta-llama/Llama-4-Scout-17B-16E-Instruct', provider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'compare_monthly_expense_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'month': 1, 'year': ... 'Total expenses for January 2025: $1000'}\"}, {'response': \"{'response': 'Total expenses for February 2024: $2000'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n            stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n    \n            # --- Process Stream ---\n>           accumulated_content, accumulated_tool_calls = _accumulate_streaming_tool_calls(stream)\n\ntests/verifications/openai_api/test_chat_completion.py:506: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nstream = <openai.Stream object at 0x7f3127ed0ac0>\n\n    def _accumulate_streaming_tool_calls(stream):\n        \"\"\"Accumulates tool calls and content from a streaming ChatCompletion response.\"\"\"\n        tool_calls_buffer = {}\n        current_id = None\n        full_content = \"\"  # Initialize content accumulator\n        # Process streaming chunks\n        for chunk in stream:\n>           choice = chunk.choices[0]\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:688: IndexError"
       },
       "teardown": {
-        "duration": 0.00022924994118511677,
+        "duration": 0.0003002053126692772,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-text_then_weather_tool]",
-      "lineno": 451,
+      "lineno": 471,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-text_then_weather_tool]",
@@ -3316,39 +3343,39 @@
         "case_id": "text_then_weather_tool"
       },
       "setup": {
-        "duration": 0.007508292095735669,
+        "duration": 0.07102924212813377,
         "outcome": "passed"
       },
       "call": {
-        "duration": 6.219006249913946,
+        "duration": 0.3103123838081956,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 588,
+          "path": "/home/erichuang/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
+          "lineno": 688,
           "message": "IndexError: list index out of range"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 486,
+            "lineno": 506,
             "message": ""
           },
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 588,
+            "lineno": 688,
             "message": "IndexError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-text_then_weather_tool]>>\nopenai_client = <openai.OpenAI object at 0x10c175f60>\nmodel = 'meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8'\nprovider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'text_then_weather_tool', 'expected': [{'answer': ['sol'], 'num_tool_calls': 0}, {'num_tool_calls': 1, 'to...], 'type': 'object'}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': '70 degrees and foggy'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n            stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n    \n            # --- Process Stream ---\n>           accumulated_content, accumulated_tool_calls = _accumulate_streaming_tool_calls(stream)\n\ntests/verifications/openai_api/test_chat_completion.py:486: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nstream = <openai.Stream object at 0x10ca75ae0>\n\n    def _accumulate_streaming_tool_calls(stream):\n        \"\"\"Accumulates tool calls and content from a streaming ChatCompletion response.\"\"\"\n        tool_calls_buffer = {}\n        current_id = None\n        full_content = \"\"  # Initialize content accumulator\n        # Process streaming chunks\n        for chunk in stream:\n>           choice = chunk.choices[0]\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:588: IndexError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-text_then_weather_tool]>>\nopenai_client = <openai.OpenAI object at 0x7f3127e64f40>\nmodel = 'meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8'\nprovider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'text_then_weather_tool', 'expected': [{'answer': ['sol'], 'num_tool_calls': 0}, {'num_tool_calls': 1, 'to...], 'type': 'object'}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': '70 degrees and foggy'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n            stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n    \n            # --- Process Stream ---\n>           accumulated_content, accumulated_tool_calls = _accumulate_streaming_tool_calls(stream)\n\ntests/verifications/openai_api/test_chat_completion.py:506: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nstream = <openai.Stream object at 0x7f3127f65d20>\n\n    def _accumulate_streaming_tool_calls(stream):\n        \"\"\"Accumulates tool calls and content from a streaming ChatCompletion response.\"\"\"\n        tool_calls_buffer = {}\n        current_id = None\n        full_content = \"\"  # Initialize content accumulator\n        # Process streaming chunks\n        for chunk in stream:\n>           choice = chunk.choices[0]\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:688: IndexError"
       },
       "teardown": {
-        "duration": 0.00025975005701184273,
+        "duration": 0.000398833304643631,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-weather_tool_then_text]",
-      "lineno": 451,
+      "lineno": 471,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-weather_tool_then_text]",
@@ -3367,39 +3394,39 @@
         "case_id": "weather_tool_then_text"
       },
       "setup": {
-        "duration": 0.056057041976600885,
+        "duration": 0.07346561551094055,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.42864158283919096,
+        "duration": 2.515005356632173,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 588,
+          "path": "/home/erichuang/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
+          "lineno": 688,
           "message": "IndexError: list index out of range"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 486,
+            "lineno": 506,
             "message": ""
           },
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 588,
+            "lineno": 688,
             "message": "IndexError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-weather_tool_then_text]>>\nopenai_client = <openai.OpenAI object at 0x10ca561d0>\nmodel = 'meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8'\nprovider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'weather_tool_then_text', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'location': 'San Francisco...], 'type': 'object'}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': '70 degrees and foggy'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n            stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n    \n            # --- Process Stream ---\n>           accumulated_content, accumulated_tool_calls = _accumulate_streaming_tool_calls(stream)\n\ntests/verifications/openai_api/test_chat_completion.py:486: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nstream = <openai.Stream object at 0x10c1778b0>\n\n    def _accumulate_streaming_tool_calls(stream):\n        \"\"\"Accumulates tool calls and content from a streaming ChatCompletion response.\"\"\"\n        tool_calls_buffer = {}\n        current_id = None\n        full_content = \"\"  # Initialize content accumulator\n        # Process streaming chunks\n        for chunk in stream:\n>           choice = chunk.choices[0]\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:588: IndexError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-weather_tool_then_text]>>\nopenai_client = <openai.OpenAI object at 0x7f3127de4f40>\nmodel = 'meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8'\nprovider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'weather_tool_then_text', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'location': 'San Francisco...], 'type': 'object'}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': '70 degrees and foggy'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n            stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n    \n            # --- Process Stream ---\n>           accumulated_content, accumulated_tool_calls = _accumulate_streaming_tool_calls(stream)\n\ntests/verifications/openai_api/test_chat_completion.py:506: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nstream = <openai.Stream object at 0x7f3127df6d10>\n\n    def _accumulate_streaming_tool_calls(stream):\n        \"\"\"Accumulates tool calls and content from a streaming ChatCompletion response.\"\"\"\n        tool_calls_buffer = {}\n        current_id = None\n        full_content = \"\"  # Initialize content accumulator\n        # Process streaming chunks\n        for chunk in stream:\n>           choice = chunk.choices[0]\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:688: IndexError"
       },
       "teardown": {
-        "duration": 0.00025275000371038914,
+        "duration": 0.0003784680739045143,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-add_product_tool]",
-      "lineno": 451,
+      "lineno": 471,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-add_product_tool]",
@@ -3418,39 +3445,39 @@
         "case_id": "add_product_tool"
       },
       "setup": {
-        "duration": 0.007619959069415927,
+        "duration": 0.07150219846516848,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.6468547079712152,
+        "duration": 0.770132390782237,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 588,
+          "path": "/home/erichuang/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
+          "lineno": 688,
           "message": "IndexError: list index out of range"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 486,
+            "lineno": 506,
             "message": ""
           },
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 588,
+            "lineno": 688,
             "message": "IndexError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-add_product_tool]>>\nopenai_client = <openai.OpenAI object at 0x10c6c7760>\nmodel = 'meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8'\nprovider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'add_product_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'inStock': True, 'name': 'Widget...}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': 'Successfully added product with id: 123'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n            stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n    \n            # --- Process Stream ---\n>           accumulated_content, accumulated_tool_calls = _accumulate_streaming_tool_calls(stream)\n\ntests/verifications/openai_api/test_chat_completion.py:486: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nstream = <openai.Stream object at 0x10ca40eb0>\n\n    def _accumulate_streaming_tool_calls(stream):\n        \"\"\"Accumulates tool calls and content from a streaming ChatCompletion response.\"\"\"\n        tool_calls_buffer = {}\n        current_id = None\n        full_content = \"\"  # Initialize content accumulator\n        # Process streaming chunks\n        for chunk in stream:\n>           choice = chunk.choices[0]\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:588: IndexError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-add_product_tool]>>\nopenai_client = <openai.OpenAI object at 0x7f3127df7070>\nmodel = 'meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8'\nprovider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'add_product_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'inStock': True, 'name': 'Widget...}}, 'type': 'function'}]}, 'tool_responses': [{'response': \"{'response': 'Successfully added product with id: 123'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n            stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n    \n            # --- Process Stream ---\n>           accumulated_content, accumulated_tool_calls = _accumulate_streaming_tool_calls(stream)\n\ntests/verifications/openai_api/test_chat_completion.py:506: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nstream = <openai.Stream object at 0x7f3127eb7460>\n\n    def _accumulate_streaming_tool_calls(stream):\n        \"\"\"Accumulates tool calls and content from a streaming ChatCompletion response.\"\"\"\n        tool_calls_buffer = {}\n        current_id = None\n        full_content = \"\"  # Initialize content accumulator\n        # Process streaming chunks\n        for chunk in stream:\n>           choice = chunk.choices[0]\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:688: IndexError"
       },
       "teardown": {
-        "duration": 0.0002552920486778021,
+        "duration": 0.00032351352274417877,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-get_then_create_event_tool]",
-      "lineno": 451,
+      "lineno": 471,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-get_then_create_event_tool]",
@@ -3469,39 +3496,39 @@
         "case_id": "get_then_create_event_tool"
       },
       "setup": {
-        "duration": 0.00699983281083405,
+        "duration": 0.07132976595312357,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.46285866713151336,
+        "duration": 0.5259293485432863,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 588,
+          "path": "/home/erichuang/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
+          "lineno": 688,
           "message": "IndexError: list index out of range"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 486,
+            "lineno": 506,
             "message": ""
           },
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 588,
+            "lineno": 688,
             "message": "IndexError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-get_then_create_event_tool]>>\nopenai_client = <openai.OpenAI object at 0x10c637640>\nmodel = 'meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8'\nprovider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'get_then_create_event_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'date': '2025-03-03', ...ents found for 2025-03-03 at 10:00'}\"}, {'response': \"{'response': 'Successfully created new event with id: e_123'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n            stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n    \n            # --- Process Stream ---\n>           accumulated_content, accumulated_tool_calls = _accumulate_streaming_tool_calls(stream)\n\ntests/verifications/openai_api/test_chat_completion.py:486: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nstream = <openai.Stream object at 0x10d906380>\n\n    def _accumulate_streaming_tool_calls(stream):\n        \"\"\"Accumulates tool calls and content from a streaming ChatCompletion response.\"\"\"\n        tool_calls_buffer = {}\n        current_id = None\n        full_content = \"\"  # Initialize content accumulator\n        # Process streaming chunks\n        for chunk in stream:\n>           choice = chunk.choices[0]\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:588: IndexError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-get_then_create_event_tool]>>\nopenai_client = <openai.OpenAI object at 0x7f3127ed1a20>\nmodel = 'meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8'\nprovider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'get_then_create_event_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'date': '2025-03-03', ...ents found for 2025-03-03 at 10:00'}\"}, {'response': \"{'response': 'Successfully created new event with id: e_123'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n            stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n    \n            # --- Process Stream ---\n>           accumulated_content, accumulated_tool_calls = _accumulate_streaming_tool_calls(stream)\n\ntests/verifications/openai_api/test_chat_completion.py:506: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nstream = <openai.Stream object at 0x7f31280cc0a0>\n\n    def _accumulate_streaming_tool_calls(stream):\n        \"\"\"Accumulates tool calls and content from a streaming ChatCompletion response.\"\"\"\n        tool_calls_buffer = {}\n        current_id = None\n        full_content = \"\"  # Initialize content accumulator\n        # Process streaming chunks\n        for chunk in stream:\n>           choice = chunk.choices[0]\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:688: IndexError"
       },
       "teardown": {
-        "duration": 0.00024433317594230175,
+        "duration": 0.00037543755024671555,
         "outcome": "passed"
       }
     },
     {
       "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-compare_monthly_expense_tool]",
-      "lineno": 451,
+      "lineno": 471,
       "outcome": "failed",
       "keywords": [
         "test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-compare_monthly_expense_tool]",
@@ -3520,36 +3547,262 @@
         "case_id": "compare_monthly_expense_tool"
       },
       "setup": {
-        "duration": 0.007548208115622401,
+        "duration": 0.07170393783599138,
         "outcome": "passed"
       },
       "call": {
-        "duration": 0.502064208034426,
+        "duration": 0.4805993800982833,
         "outcome": "failed",
         "crash": {
-          "path": "/Users/erichuang/projects/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
-          "lineno": 588,
+          "path": "/home/erichuang/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
+          "lineno": 688,
           "message": "IndexError: list index out of range"
         },
         "traceback": [
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 486,
+            "lineno": 506,
             "message": ""
           },
           {
             "path": "tests/verifications/openai_api/test_chat_completion.py",
-            "lineno": 588,
+            "lineno": 688,
             "message": "IndexError"
           }
         ],
-        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-compare_monthly_expense_tool]>>\nopenai_client = <openai.OpenAI object at 0x10c602b30>\nmodel = 'meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8'\nprovider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'compare_monthly_expense_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'month': 1, 'year': ... 'Total expenses for January 2025: $1000'}\"}, {'response': \"{'response': 'Total expenses for February 2024: $2000'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n            stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n    \n            # --- Process Stream ---\n>           accumulated_content, accumulated_tool_calls = _accumulate_streaming_tool_calls(stream)\n\ntests/verifications/openai_api/test_chat_completion.py:486: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nstream = <openai.Stream object at 0x10caaedd0>\n\n    def _accumulate_streaming_tool_calls(stream):\n        \"\"\"Accumulates tool calls and content from a streaming ChatCompletion response.\"\"\"\n        tool_calls_buffer = {}\n        current_id = None\n        full_content = \"\"  # Initialize content accumulator\n        # Process streaming chunks\n        for chunk in stream:\n>           choice = chunk.choices[0]\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:588: IndexError"
+        "longrepr": "request = <FixtureRequest for <Function test_chat_streaming_multi_turn_tool_calling[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-compare_monthly_expense_tool]>>\nopenai_client = <openai.OpenAI object at 0x7f3127eb60e0>\nmodel = 'meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8'\nprovider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\ncase = {'case_id': 'compare_monthly_expense_tool', 'expected': [{'num_tool_calls': 1, 'tool_arguments': {'month': 1, 'year': ... 'Total expenses for January 2025: $1000'}\"}, {'response': \"{'response': 'Total expenses for February 2024: $2000'}\"}]}\n\n    @pytest.mark.parametrize(\n        \"case\",\n        chat_completion_test_cases.get(\"test_chat_multi_turn_tool_calling\", {}).get(\"test_params\", {}).get(\"case\", []),\n        ids=case_id_generator,\n    )\n    def test_chat_streaming_multi_turn_tool_calling(request, openai_client, model, provider, verification_config, case):\n        \"\"\" \"\"\"\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages = []\n        tools = case[\"input\"][\"tools\"]\n        expected_results = copy.deepcopy(case[\"expected\"])\n        tool_responses = copy.deepcopy(case.get(\"tool_responses\", []))\n        input_messages_turns = copy.deepcopy(case[\"input\"][\"messages\"])\n    \n        while len(input_messages_turns) > 0 or (len(messages) > 0 and messages[-1][\"role\"] == \"tool\"):\n            if len(messages) == 0 or messages[-1][\"role\"] != \"tool\":\n                new_messages = input_messages_turns.pop(0)\n                if isinstance(new_messages, list):\n                    messages.extend(new_messages)\n                else:\n                    messages.append(new_messages)\n    \n            # --- API Call (Streaming) ---\n            stream = openai_client.chat.completions.create(\n                model=model,\n                messages=messages,\n                tools=tools,\n                stream=True,\n            )\n    \n            # --- Process Stream ---\n>           accumulated_content, accumulated_tool_calls = _accumulate_streaming_tool_calls(stream)\n\ntests/verifications/openai_api/test_chat_completion.py:506: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nstream = <openai.Stream object at 0x7f3127e59f00>\n\n    def _accumulate_streaming_tool_calls(stream):\n        \"\"\"Accumulates tool calls and content from a streaming ChatCompletion response.\"\"\"\n        tool_calls_buffer = {}\n        current_id = None\n        full_content = \"\"  # Initialize content accumulator\n        # Process streaming chunks\n        for chunk in stream:\n>           choice = chunk.choices[0]\nE           IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:688: IndexError"
       },
       "teardown": {
-        "duration": 0.001067916164174676,
+        "duration": 0.0003568241372704506,
+        "outcome": "passed"
+      }
+    },
+    {
+      "nodeid": "tests/verifications/openai_api/test_chat_completion.py::test_chat_multi_turn_multiple_images[meta-llama/Llama-3.3-70B-Instruct-Turbo-stream=False]",
+      "lineno": 554,
+      "outcome": "skipped",
+      "keywords": [
+        "test_chat_multi_turn_multiple_images[meta-llama/Llama-3.3-70B-Instruct-Turbo-stream=False]",
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+      "lineno": 554,
+      "outcome": "failed",
+      "keywords": [
+        "test_chat_multi_turn_multiple_images[meta-llama/Llama-4-Scout-17B-16E-Instruct-stream=True]",
+        "parametrize",
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+        "meta-llama/Llama-4-Scout-17B-16E-Instruct-stream=True",
+        "test_chat_completion.py",
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+        ""
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+      "metadata": {
+        "model": "meta-llama/Llama-4-Scout-17B-16E-Instruct",
+        "case_id": "stream=True"
+      },
+      "setup": {
+        "duration": 0.07148486748337746,
+        "outcome": "passed"
+      },
+      "call": {
+        "duration": 1.4055311204865575,
+        "outcome": "failed",
+        "crash": {
+          "path": "/home/erichuang/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
+          "lineno": 596,
+          "message": "IndexError: list index out of range"
+        },
+        "traceback": [
+          {
+            "path": "tests/verifications/openai_api/test_chat_completion.py",
+            "lineno": 596,
+            "message": "IndexError"
+          }
+        ],
+        "longrepr": "request = <FixtureRequest for <Function test_chat_multi_turn_multiple_images[meta-llama/Llama-4-Scout-17B-16E-Instruct-stream=True]>>\nopenai_client = <openai.OpenAI object at 0x7f3127f67a00>\nmodel = 'meta-llama/Llama-4-Scout-17B-16E-Instruct', provider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\nmulti_image_data = ['data:image/jpeg;base64,/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAIBAQEBAQIBAQECAgICAgQDAgICAgUEBAMEBgUGBgYFBgYGBwkIBgcJBwYGC...6pH9jaTzNv7vfRRXzubfxj9f8Pv8AkTz/AMX/ALbEz5Ly38lfMk/5Z/u64PxhqEZh+z/6rzvn2UUV5EvgPuzy/wAc6p5dt5ccibJpNkkdFFFec27mZ//Z']\nstream = True\n\n    @pytest.mark.parametrize(\"stream\", [False, True], ids=[\"stream=False\", \"stream=True\"])\n    def test_chat_multi_turn_multiple_images(\n        request, openai_client, model, provider, verification_config, multi_image_data, stream\n    ):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages_turn1 = [\n            {\n                \"role\": \"user\",\n                \"content\": [\n                    {\n                        \"type\": \"image_url\",\n                        \"image_url\": {\n                            \"url\": multi_image_data[0],\n                        },\n                    },\n                    {\n                        \"type\": \"image_url\",\n                        \"image_url\": {\n                            \"url\": multi_image_data[1],\n                        },\n                    },\n                    {\n                        \"type\": \"text\",\n                        \"text\": \"What furniture is in the first image that is not in the second image?\",\n                    },\n                ],\n            },\n        ]\n    \n        # First API call\n        response1 = openai_client.chat.completions.create(\n            model=model,\n            messages=messages_turn1,\n            stream=stream,\n        )\n        if stream:\n            message_content1 = \"\"\n            for chunk in response1:\n>               message_content1 += chunk.choices[0].delta.content or \"\"\nE               IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:596: IndexError"
+      },
+      "teardown": {
+        "duration": 0.00031107570976018906,
+        "outcome": "passed"
+      }
+    },
+    {
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+      "lineno": 554,
+      "outcome": "passed",
+      "keywords": [
+        "test_chat_multi_turn_multiple_images[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-stream=False]",
+        "parametrize",
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+        "meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-stream=False",
+        "test_chat_completion.py",
+        "openai_api",
+        "verifications",
+        "tests",
+        "llama-stack",
+        ""
+      ],
+      "metadata": {
+        "model": "meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8",
+        "case_id": "stream=False"
+      },
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+        "outcome": "passed"
+      },
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+        "duration": 6.755587887018919,
+        "outcome": "passed"
+      },
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+        "duration": 0.00022470485419034958,
+        "outcome": "passed"
+      }
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+    {
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+      "lineno": 554,
+      "outcome": "failed",
+      "keywords": [
+        "test_chat_multi_turn_multiple_images[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-stream=True]",
+        "parametrize",
+        "pytestmark",
+        "meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-stream=True",
+        "test_chat_completion.py",
+        "openai_api",
+        "verifications",
+        "tests",
+        "llama-stack",
+        ""
+      ],
+      "metadata": {
+        "model": "meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8",
+        "case_id": "stream=True"
+      },
+      "setup": {
+        "duration": 0.07265954371541739,
+        "outcome": "passed"
+      },
+      "call": {
+        "duration": 1.973216057755053,
+        "outcome": "failed",
+        "crash": {
+          "path": "/home/erichuang/llama-stack/tests/verifications/openai_api/test_chat_completion.py",
+          "lineno": 596,
+          "message": "IndexError: list index out of range"
+        },
+        "traceback": [
+          {
+            "path": "tests/verifications/openai_api/test_chat_completion.py",
+            "lineno": 596,
+            "message": "IndexError"
+          }
+        ],
+        "longrepr": "request = <FixtureRequest for <Function test_chat_multi_turn_multiple_images[meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8-stream=True]>>\nopenai_client = <openai.OpenAI object at 0x7f3127cd28c0>\nmodel = 'meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8'\nprovider = 'together'\nverification_config = {'providers': {'cerebras': {'api_key_var': 'CEREBRAS_API_KEY', 'base_url': 'https://api.cerebras.ai/v1', 'model_displa...-versatile', 'meta-llama/llama-4-scout-17b-16e-instruct', 'meta-llama/llama-4-maverick-17b-128e-instruct'], ...}, ...}}\nmulti_image_data = ['data:image/jpeg;base64,/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAIBAQEBAQIBAQECAgICAgQDAgICAgUEBAMEBgUGBgYFBgYGBwkIBgcJBwYGC...6pH9jaTzNv7vfRRXzubfxj9f8Pv8AkTz/AMX/ALbEz5Ly38lfMk/5Z/u64PxhqEZh+z/6rzvn2UUV5EvgPuzy/wAc6p5dt5ccibJpNkkdFFFec27mZ//Z']\nstream = True\n\n    @pytest.mark.parametrize(\"stream\", [False, True], ids=[\"stream=False\", \"stream=True\"])\n    def test_chat_multi_turn_multiple_images(\n        request, openai_client, model, provider, verification_config, multi_image_data, stream\n    ):\n        test_name_base = get_base_test_name(request)\n        if should_skip_test(verification_config, provider, model, test_name_base):\n            pytest.skip(f\"Skipping {test_name_base} for model {model} on provider {provider} based on config.\")\n    \n        messages_turn1 = [\n            {\n                \"role\": \"user\",\n                \"content\": [\n                    {\n                        \"type\": \"image_url\",\n                        \"image_url\": {\n                            \"url\": multi_image_data[0],\n                        },\n                    },\n                    {\n                        \"type\": \"image_url\",\n                        \"image_url\": {\n                            \"url\": multi_image_data[1],\n                        },\n                    },\n                    {\n                        \"type\": \"text\",\n                        \"text\": \"What furniture is in the first image that is not in the second image?\",\n                    },\n                ],\n            },\n        ]\n    \n        # First API call\n        response1 = openai_client.chat.completions.create(\n            model=model,\n            messages=messages_turn1,\n            stream=stream,\n        )\n        if stream:\n            message_content1 = \"\"\n            for chunk in response1:\n>               message_content1 += chunk.choices[0].delta.content or \"\"\nE               IndexError: list index out of range\n\ntests/verifications/openai_api/test_chat_completion.py:596: IndexError"
+      },
+      "teardown": {
+        "duration": 0.0017197001725435257,
         "outcome": "passed"
       }
     }
   ],
-  "run_timestamp": 1744841031
+  "run_timestamp": 1744915514
 }