revert back test

tests/client-sdk/inference/test_inference.py

@@ -5,7 +5,7 @@
 # the root directory of this source tree.
 
 import base64
-import pathlib
+import os
 
 import pytest
 from pydantic import BaseModel
@@ -16,6 +16,14 @@ PROVIDER_TOOL_PROMPT_FORMAT = {
     "remote::fireworks": "json",
 }
 
+PROVIDER_LOGPROBS_TOP_K = set(
+    {
+        "remote::together",
+        "remote::fireworks",
+        # "remote:vllm"
+    }
+)
+
 
 @pytest.fixture(scope="session")
 def provider_tool_format(inference_provider_type):
@@ -48,31 +56,14 @@ def get_weather_tool_definition():
     }
 
 
-# @pytest.fixture
-# def base64_image_url():
-#     image_path = os.path.join(os.path.dirname(__file__), "dog.png")
-#     with open(image_path, "rb") as image_file:
-#         # Convert the image to base64
-#         base64_string = base64.b64encode(image_file.read()).decode("utf-8")
-#         base64_url = f"data:image/png;base64,{base64_string}"
-#         return base64_url
-
-
 @pytest.fixture
-def image_path():
+def base64_image_url():
-    return pathlib.Path(__file__).parent / "dog.png"
+    image_path = os.path.join(os.path.dirname(__file__), "dog.png")
-
+    with open(image_path, "rb") as image_file:
-
+        # Convert the image to base64
-@pytest.fixture
+        base64_string = base64.b64encode(image_file.read()).decode("utf-8")
-def base64_image_data(image_path):
+        base64_url = f"data:image/png;base64,{base64_string}"
-    # Convert the image to base64
+        return base64_url
-    return base64.b64encode(image_path.read_bytes()).decode("utf-8")
-
-
-@pytest.fixture
-def base64_image_url(base64_image_data, image_path):
-    # suffix includes the ., so we remove it
-    return f"data:image/{image_path.suffix[1:]};base64,{base64_image_data}"
 
 
 def test_text_completion_non_streaming(llama_stack_client, text_model_id):
@@ -100,8 +91,12 @@ def test_text_completion_streaming(llama_stack_client, text_model_id):
     assert "blue" in "".join(streamed_content).lower().strip()
 
 
-@pytest.mark.skip("Most inference providers don't support log probs yet")
+def test_completion_log_probs_non_streaming(
-def test_completion_log_probs_non_streaming(llama_stack_client, text_model_id):
+    llama_stack_client, text_model_id, inference_provider_type
+):
+    if inference_provider_type not in PROVIDER_LOGPROBS_TOP_K:
+        pytest.xfail(f"{inference_provider_type} doesn't support log probs yet")
+
     response = llama_stack_client.inference.completion(
         content="Complete the sentence: Micheael Jordan is born in ",
         stream=False,
@@ -110,16 +105,22 @@ def test_completion_log_probs_non_streaming(llama_stack_client, text_model_id):
             "max_tokens": 5,
         },
         logprobs={
-            "top_k": 3,
+            "top_k": 1,
         },
     )
     assert response.logprobs, "Logprobs should not be empty"
-    assert 1 <= len(response.logprobs) <= 5
+    assert (
-    assert all(len(logprob.logprobs_by_token) == 3 for logprob in response.logprobs)
+        1 <= len(response.logprobs) <= 5
+    )  # each token has 1 logprob and here max_tokens=5
+    assert all(len(logprob.logprobs_by_token) == 1 for logprob in response.logprobs)
 
 
-@pytest.mark.skip("Most inference providers don't support log probs yet")
+def test_completion_log_probs_streaming(
-def test_completion_log_probs_streaming(llama_stack_client, text_model_id):
+    llama_stack_client, text_model_id, inference_provider_type
+):
+    if inference_provider_type not in PROVIDER_LOGPROBS_TOP_K:
+        pytest.xfail(f"{inference_provider_type} doesn't support log probs yet")
+
     response = llama_stack_client.inference.completion(
         content="Complete the sentence: Micheael Jordan is born in ",
         stream=True,
@@ -128,7 +129,7 @@ def test_completion_log_probs_streaming(llama_stack_client, text_model_id):
             "max_tokens": 5,
         },
         logprobs={
-            "top_k": 3,
+            "top_k": 1,
         },
     )
     streamed_content = [chunk for chunk in response]
@@ -136,7 +137,7 @@ def test_completion_log_probs_streaming(llama_stack_client, text_model_id):
         if chunk.delta:  # if there's a token, we expect logprobs
             assert chunk.logprobs, "Logprobs should not be empty"
             assert all(
-                len(logprob.logprobs_by_token) == 3 for logprob in chunk.logprobs
+                len(logprob.logprobs_by_token) == 1 for logprob in chunk.logprobs
             )
         else:  # no token, no logprobs
             assert not chunk.logprobs, "Logprobs should be empty"
@@ -370,30 +371,25 @@ def test_image_chat_completion_streaming(llama_stack_client, vision_model_id):
     assert any(expected in streamed_content for expected in {"dog", "puppy", "pup"})
 
 
-@pytest.mark.parametrize("type_", ["url", "data"])
+def test_image_chat_completion_base64_url(
-def test_image_chat_completion_base64(
+    llama_stack_client, vision_model_id, base64_image_url
-    llama_stack_client, vision_model_id, base64_image_data, base64_image_url, type_
 ):
-    image_spec = {
-        "url": {
-            "type": "image",
-            "image": {
-                "url": {
-                    "uri": base64_image_url,
-                },
-            },
-        },
-        "data": {
-            "type": "image",
-            "image": {
-                "data": base64_image_data,
-            },
-        },
-    }[type_]
-
     message = {
         "role": "user",
-        "content": [image_spec],
+        "content": [
+            {
+                "type": "image",
+                "image": {
+                    "url": {
+                        "uri": base64_image_url,
+                    },
+                },
+            },
+            {
+                "type": "text",
+                "text": "Describe what is in this image.",
+            },
+        ],
     }
     response = llama_stack_client.inference.chat_completion(
         model_id=vision_model_id,