Merge branch 'main' into content-extension

tests/integration/README.md

@@ -42,6 +42,27 @@ Model parameters can be influenced by the following options:
 Each of these are comma-separated lists and can be used to generate multiple parameter combinations. Note that tests will be skipped
 if no model is specified.
 
+### Suites (fast selection + sane defaults)
+
+- `--suite`: comma-separated list of named suites that both narrow which tests are collected and prefill common model options (unless you pass them explicitly).
+- Available suites:
+  - `responses`: collects tests under `tests/integration/responses`; this is a separate suite because it needs a strong tool-calling model.
+  - `vision`: collects only `tests/integration/inference/test_vision_inference.py`; defaults `--vision-model=ollama/llama3.2-vision:11b`, `--embedding-model=sentence-transformers/all-MiniLM-L6-v2`.
+- Explicit flags always win. For example, `--suite=responses --text-model=<X>` overrides the suite’s text model.
+
+Examples:
+
+```bash
+# Fast responses run with defaults
+pytest -s -v tests/integration --stack-config=server:starter --suite=responses
+
+# Fast single-file vision run with defaults
+pytest -s -v tests/integration --stack-config=server:starter --suite=vision
+
+# Combine suites and override a default
+pytest -s -v tests/integration --stack-config=server:starter --suite=responses,vision --embedding-model=text-embedding-3-small
+```
+
 ## Examples
 
 ### Testing against a Server
@@ -98,29 +119,25 @@ sentence-transformers/all-MiniLM-L6-v2
 
 The testing system supports three modes controlled by environment variables:
 
-### LIVE Mode (Default)
-Tests make real API calls:
+### REPLAY Mode (Default)
+Uses cached responses instead of making API calls:
 ```bash
-LLAMA_STACK_TEST_INFERENCE_MODE=live pytest tests/integration/
+pytest tests/integration/
 ```
-
 ### RECORD Mode
 Captures API interactions for later replay:
 ```bash
 LLAMA_STACK_TEST_INFERENCE_MODE=record \
-LLAMA_STACK_TEST_RECORDING_DIR=tests/integration/recordings \
 pytest tests/integration/inference/test_new_feature.py
 ```
 
-### REPLAY Mode
-Uses cached responses instead of making API calls:
+### LIVE Mode
+Tests make real API calls (but not recorded):
 ```bash
-LLAMA_STACK_TEST_INFERENCE_MODE=replay \
-LLAMA_STACK_TEST_RECORDING_DIR=tests/integration/recordings \
-pytest tests/integration/
+LLAMA_STACK_TEST_INFERENCE_MODE=live pytest tests/integration/
 ```
 
-Note that right now you must specify the recording directory. This is because different tests use different recording directories and we don't (yet) have a fool-proof way to map a test to a recording directory. We are working on this.
+By default, the recording directory is `tests/integration/recordings`. You can override this by setting the `LLAMA_STACK_TEST_RECORDING_DIR` environment variable.
 
 ## Managing Recordings
 
@@ -146,7 +163,6 @@ See the [main testing guide](../README.md#remote-re-recording-recommended) for f
 ```bash
 # Re-record specific tests
 LLAMA_STACK_TEST_INFERENCE_MODE=record \
-LLAMA_STACK_TEST_RECORDING_DIR=tests/integration/recordings \
 pytest -s -v --stack-config=server:starter tests/integration/inference/test_modified.py
 ```
 

tests/integration/batches/test_batches.py

@@ -268,3 +268,58 @@ class TestBatchesIntegration:
 
         deleted_error_file = openai_client.files.delete(final_batch.error_file_id)
         assert deleted_error_file.deleted, f"Error file {final_batch.error_file_id} was not deleted successfully"
+
+    def test_batch_e2e_completions(self, openai_client, batch_helper, text_model_id):
+        """Run an end-to-end batch with a single successful text completion request."""
+        request_body = {"model": text_model_id, "prompt": "Say completions", "max_tokens": 20}
+
+        batch_requests = [
+            {
+                "custom_id": "success-1",
+                "method": "POST",
+                "url": "/v1/completions",
+                "body": request_body,
+            }
+        ]
+
+        with batch_helper.create_file(batch_requests) as uploaded_file:
+            batch = openai_client.batches.create(
+                input_file_id=uploaded_file.id,
+                endpoint="/v1/completions",
+                completion_window="24h",
+                metadata={"test": "e2e_completions_success"},
+            )
+
+            final_batch = batch_helper.wait_for(
+                batch.id,
+                max_wait_time=3 * 60,
+                expected_statuses={"completed"},
+                timeout_action="skip",
+            )
+
+        assert final_batch.status == "completed"
+        assert final_batch.request_counts is not None
+        assert final_batch.request_counts.total == 1
+        assert final_batch.request_counts.completed == 1
+        assert final_batch.output_file_id is not None
+
+        output_content = openai_client.files.content(final_batch.output_file_id)
+        if isinstance(output_content, str):
+            output_text = output_content
+        else:
+            output_text = output_content.content.decode("utf-8")
+
+        output_lines = output_text.strip().split("\n")
+        assert len(output_lines) == 1
+
+        result = json.loads(output_lines[0])
+        assert result["custom_id"] == "success-1"
+        assert "response" in result
+        assert result["response"]["status_code"] == 200
+
+        deleted_output_file = openai_client.files.delete(final_batch.output_file_id)
+        assert deleted_output_file.deleted
+
+        if final_batch.error_file_id is not None:
+            deleted_error_file = openai_client.files.delete(final_batch.error_file_id)
+            assert deleted_error_file.deleted

tests/integration/conftest.py

@@ -6,15 +6,17 @@
 import inspect
 import itertools
 import os
-import platform
 import textwrap
 import time
+from pathlib import Path
 
 import pytest
 from dotenv import load_dotenv
 
 from llama_stack.log import get_logger
 
+from .suites import SUITE_DEFINITIONS
+
 logger = get_logger(__name__, category="tests")
 
 
@@ -30,6 +32,8 @@ def pytest_runtest_makereport(item, call):
 def pytest_sessionstart(session):
     # stop macOS from complaining about duplicate OpenMP libraries
     os.environ["KMP_DUPLICATE_LIB_OK"] = "TRUE"
+    if "LLAMA_STACK_TEST_INFERENCE_MODE" not in os.environ:
+        os.environ["LLAMA_STACK_TEST_INFERENCE_MODE"] = "replay"
 
 
 def pytest_runtest_teardown(item):
@@ -59,9 +63,22 @@ def pytest_configure(config):
         key, value = env_var.split("=", 1)
         os.environ[key] = value
 
-    if platform.system() == "Darwin":  # Darwin is the system name for macOS
-        os.environ["DISABLE_CODE_SANDBOX"] = "1"
-        logger.info("Setting DISABLE_CODE_SANDBOX=1 for macOS")
+    suites_raw = config.getoption("--suite")
+    suites: list[str] = []
+    if suites_raw:
+        suites = [p.strip() for p in str(suites_raw).split(",") if p.strip()]
+        unknown = [p for p in suites if p not in SUITE_DEFINITIONS]
+        if unknown:
+            raise pytest.UsageError(
+                f"Unknown suite(s): {', '.join(unknown)}. Available: {', '.join(sorted(SUITE_DEFINITIONS.keys()))}"
+            )
+    for suite in suites:
+        suite_def = SUITE_DEFINITIONS.get(suite, {})
+        defaults: dict = suite_def.get("defaults", {})
+        for dest, value in defaults.items():
+            current = getattr(config.option, dest, None)
+            if not current:
+                setattr(config.option, dest, value)
 
 
 def pytest_addoption(parser):
@@ -103,16 +120,21 @@ def pytest_addoption(parser):
         default=384,
         help="Output dimensionality of the embedding model to use for testing. Default: 384",
     )
-    parser.addoption(
-        "--record-responses",
-        action="store_true",
-        help="Record new API responses instead of using cached ones.",
-    )
     parser.addoption(
         "--report",
         help="Path where the test report should be written, e.g. --report=/path/to/report.md",
     )
 
+    available_suites = ", ".join(sorted(SUITE_DEFINITIONS.keys()))
+    suite_help = (
+        "Comma-separated integration test suites to narrow collection and prefill defaults. "
+        "Available: "
+        f"{available_suites}. "
+        "Explicit CLI flags (e.g., --text-model) override suite defaults. "
+        "Examples: --suite=responses or --suite=responses,vision."
+    )
+    parser.addoption("--suite", help=suite_help)
+
 
 MODEL_SHORT_IDS = {
     "meta-llama/Llama-3.2-3B-Instruct": "3B",
@@ -195,3 +217,40 @@ def pytest_generate_tests(metafunc):
 
 
 pytest_plugins = ["tests.integration.fixtures.common"]
+
+
+def pytest_ignore_collect(path: str, config: pytest.Config) -> bool:
+    """Skip collecting paths outside the selected suite roots for speed."""
+    suites_raw = config.getoption("--suite")
+    if not suites_raw:
+        return False
+
+    names = [p.strip() for p in str(suites_raw).split(",") if p.strip()]
+    roots: list[str] = []
+    for name in names:
+        suite_def = SUITE_DEFINITIONS.get(name)
+        if suite_def:
+            roots.extend(suite_def.get("roots", []))
+    if not roots:
+        return False
+
+    p = Path(str(path)).resolve()
+
+    # Only constrain within tests/integration to avoid ignoring unrelated tests
+    integration_root = (Path(str(config.rootpath)) / "tests" / "integration").resolve()
+    if not p.is_relative_to(integration_root):
+        return False
+
+    for r in roots:
+        rp = (Path(str(config.rootpath)) / r).resolve()
+        if rp.is_file():
+            # Allow the exact file and any ancestor directories so pytest can walk into it.
+            if p == rp:
+                return False
+            if p.is_dir() and rp.is_relative_to(p):
+                return False
+        else:
+            # Allow anything inside an allowed directory
+            if p.is_relative_to(rp):
+                return False
+    return True

tests/integration/files/test_files.py

@@ -8,6 +8,7 @@ from io import BytesIO
 from unittest.mock import patch
 
 import pytest
+import requests
 
 from llama_stack.core.datatypes import User
 
@@ -79,6 +80,88 @@ def test_openai_client_basic_operations(openai_client):
                 pass  # ignore 404
 
 
+@pytest.mark.xfail(message="expires_after not available on all providers")
+def test_expires_after(openai_client):
+    """Test uploading a file with expires_after parameter."""
+    client = openai_client
+
+    uploaded_file = None
+    try:
+        with BytesIO(b"expires_after test") as file_buffer:
+            file_buffer.name = "expires_after.txt"
+            uploaded_file = client.files.create(
+                file=file_buffer,
+                purpose="assistants",
+                expires_after={"anchor": "created_at", "seconds": 4545},
+            )
+
+        assert uploaded_file.expires_at is not None
+        assert uploaded_file.expires_at == uploaded_file.created_at + 4545
+
+        listed = client.files.list()
+        ids = [f.id for f in listed.data]
+        assert uploaded_file.id in ids
+
+        retrieved = client.files.retrieve(uploaded_file.id)
+        assert retrieved.id == uploaded_file.id
+
+    finally:
+        if uploaded_file is not None:
+            try:
+                client.files.delete(uploaded_file.id)
+            except Exception:
+                pass
+
+
+@pytest.mark.xfail(message="expires_after not available on all providers")
+def test_expires_after_requests(openai_client):
+    """Upload a file using requests multipart/form-data and bracketed expires_after fields.
+
+    This ensures clients that send form fields like `expires_after[anchor]` and
+    `expires_after[seconds]` are handled by the server.
+    """
+    base_url = f"{openai_client.base_url}files"
+
+    uploaded_id = None
+    try:
+        files = {"file": ("expires_after_with_requests.txt", BytesIO(b"expires_after via requests"))}
+        data = {
+            "purpose": "assistants",
+            "expires_after[anchor]": "created_at",
+            "expires_after[seconds]": "4545",
+        }
+
+        session = requests.Session()
+        request = requests.Request("POST", base_url, files=files, data=data)
+        prepared = session.prepare_request(request)
+        resp = session.send(prepared, timeout=30)
+        resp.raise_for_status()
+        result = resp.json()
+
+        assert result.get("id", "").startswith("file-")
+        uploaded_id = result["id"]
+        assert result.get("created_at") is not None
+        assert result.get("expires_at") == result["created_at"] + 4545
+
+        list_resp = requests.get(base_url, timeout=30)
+        list_resp.raise_for_status()
+        listed = list_resp.json()
+        ids = [f["id"] for f in listed.get("data", [])]
+        assert uploaded_id in ids
+
+        retrieve_resp = requests.get(f"{base_url}/{uploaded_id}", timeout=30)
+        retrieve_resp.raise_for_status()
+        retrieved = retrieve_resp.json()
+        assert retrieved["id"] == uploaded_id
+
+    finally:
+        if uploaded_id:
+            try:
+                requests.delete(f"{base_url}/{uploaded_id}", timeout=30)
+            except Exception:
+                pass
+
+
 @pytest.mark.xfail(message="User isolation broken for current providers, must be fixed.")
 @patch("llama_stack.providers.utils.sqlstore.authorized_sqlstore.get_authenticated_user")
 def test_files_authentication_isolation(mock_get_authenticated_user, llama_stack_client):

tests/integration/inference/test_openai_completion.py

@@ -5,6 +5,8 @@
 # the root directory of this source tree.
 
 
+import time
+
 import pytest
 
 from ..test_cases.test_case import TestCase
@@ -35,6 +37,10 @@ def skip_if_model_doesnt_support_openai_completion(client_with_models, model_id)
         "remote::sambanova",
         "remote::tgi",
         "remote::vertexai",
+        # {"error":{"message":"Unknown request URL: GET /openai/v1/completions. Please check the URL for typos,
+        # or see the docs at https://console.groq.com/docs/","type":"invalid_request_error","code":"unknown_url"}}
+        "remote::groq",
+        "remote::gemini",  # https://generativelanguage.googleapis.com/v1beta/openai/completions -> 404
     ):
         pytest.skip(f"Model {model_id} hosted by {provider.provider_type} doesn't support OpenAI completions.")
 
@@ -56,6 +62,21 @@ def skip_if_model_doesnt_support_suffix(client_with_models, model_id):
         pytest.skip(f"Provider {provider.provider_type} doesn't support suffix.")
 
 
+def skip_if_doesnt_support_n(client_with_models, model_id):
+    provider = provider_from_model(client_with_models, model_id)
+    if provider.provider_type in (
+        "remote::sambanova",
+        "remote::ollama",
+        # https://console.groq.com/docs/openai#currently-unsupported-openai-features
+        # -> Error code: 400 - {'error': {'message': "'n' : number must be at most 1", 'type': 'invalid_request_error'}}
+        "remote::groq",
+        # Error code: 400 - [{'error': {'code': 400, 'message': 'Only one candidate can be specified in the
+        # current model', 'status': 'INVALID_ARGUMENT'}}]
+        "remote::gemini",
+    ):
+        pytest.skip(f"Model {model_id} hosted by {provider.provider_type} doesn't support n param.")
+
+
 def skip_if_model_doesnt_support_openai_chat_completion(client_with_models, model_id):
     provider = provider_from_model(client_with_models, model_id)
     if provider.provider_type in (
@@ -260,10 +281,7 @@ def test_openai_chat_completion_streaming(compat_client, client_with_models, tex
 )
 def test_openai_chat_completion_streaming_with_n(compat_client, client_with_models, text_model_id, test_case):
     skip_if_model_doesnt_support_openai_chat_completion(client_with_models, text_model_id)
-
-    provider = provider_from_model(client_with_models, text_model_id)
-    if provider.provider_type == "remote::ollama":
-        pytest.skip(f"Model {text_model_id} hosted by {provider.provider_type} doesn't support n > 1.")
+    skip_if_doesnt_support_n(client_with_models, text_model_id)
 
     tc = TestCase(test_case)
     question = tc["question"]
@@ -323,8 +341,15 @@ def test_inference_store(compat_client, client_with_models, text_model_id, strea
         response_id = response.id
         content = response.choices[0].message.content
 
-    responses = client.chat.completions.list(limit=1000)
-    assert response_id in [r.id for r in responses.data]
+    tries = 0
+    while tries < 10:
+        responses = client.chat.completions.list(limit=1000)
+        if response_id in [r.id for r in responses.data]:
+            break
+        else:
+            tries += 1
+            time.sleep(0.1)
+    assert tries < 10, f"Response {response_id} not found after 1 second"
 
     retrieved_response = client.chat.completions.retrieve(response_id)
     assert retrieved_response.id == response_id
@@ -388,6 +413,18 @@ def test_inference_store_tool_calls(compat_client, client_with_models, text_mode
         response_id = response.id
         content = response.choices[0].message.content
 
+    # wait for the response to be stored
+    tries = 0
+    while tries < 10:
+        responses = client.chat.completions.list(limit=1000)
+        if response_id in [r.id for r in responses.data]:
+            break
+        else:
+            tries += 1
+            time.sleep(0.1)
+
+    assert tries < 10, f"Response {response_id} not found after 1 second"
+
     responses = client.chat.completions.list(limit=1000)
     assert response_id in [r.id for r in responses.data]
 

tests/integration/recordings/responses/00ba04f74a96.json

@@ -20,15 +20,15 @@
       "__type__": "ollama._types.GenerateResponse",
       "__data__": {
         "model": "llama-guard3:1b",
-        "created_at": "2025-08-01T23:12:53.860911Z",
+        "created_at": "2025-09-03T17:37:35.23084Z",
         "done": true,
         "done_reason": "stop",
-        "total_duration": 249137667,
-        "load_duration": 152509542,
+        "total_duration": 195981375,
+        "load_duration": 110522917,
         "prompt_eval_count": 216,
-        "prompt_eval_duration": 71000000,
+        "prompt_eval_duration": 72393958,
         "eval_count": 2,
-        "eval_duration": 24000000,
+        "eval_duration": 11843000,
         "response": "safe",
         "thinking": null,
         "context": null

tests/integration/recordings/responses/04172112ffbb.json

@@ -21,7 +21,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-07-31T17:59:18.033900164Z",
+          "created_at": "2025-09-03T17:41:43.950283Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -39,7 +39,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-07-31T17:59:18.213371151Z",
+          "created_at": "2025-09-03T17:41:43.991122Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -57,7 +57,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-07-31T17:59:18.387513976Z",
+          "created_at": "2025-09-03T17:41:44.031378Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -75,7 +75,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-07-31T17:59:18.564344287Z",
+          "created_at": "2025-09-03T17:41:44.073098Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -93,7 +93,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-07-31T17:59:18.746579415Z",
+          "created_at": "2025-09-03T17:41:44.115961Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -111,7 +111,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-07-31T17:59:18.923276047Z",
+          "created_at": "2025-09-03T17:41:44.156517Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -129,7 +129,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-07-31T17:59:19.099961963Z",
+          "created_at": "2025-09-03T17:41:44.197079Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -147,7 +147,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-07-31T17:59:19.275621884Z",
+          "created_at": "2025-09-03T17:41:44.237565Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -165,7 +165,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-07-31T17:59:19.452204196Z",
+          "created_at": "2025-09-03T17:41:44.277755Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -183,7 +183,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-07-31T17:59:19.626937514Z",
+          "created_at": "2025-09-03T17:41:44.318476Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -201,7 +201,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-07-31T17:59:19.805566767Z",
+          "created_at": "2025-09-03T17:41:44.358628Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -219,7 +219,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-07-31T17:59:19.985987477Z",
+          "created_at": "2025-09-03T17:41:44.398984Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -237,7 +237,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-07-31T17:59:20.166458601Z",
+          "created_at": "2025-09-03T17:41:44.439232Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -255,7 +255,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-07-31T17:59:20.343346795Z",
+          "created_at": "2025-09-03T17:41:44.479478Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -273,7 +273,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-07-31T17:59:20.525008091Z",
+          "created_at": "2025-09-03T17:41:44.520202Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -291,7 +291,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-07-31T17:59:20.709087695Z",
+          "created_at": "2025-09-03T17:41:44.560517Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -309,7 +309,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-07-31T17:59:20.887074305Z",
+          "created_at": "2025-09-03T17:41:44.601592Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -327,15 +327,15 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-07-31T17:59:21.065244925Z",
+          "created_at": "2025-09-03T17:41:44.642064Z",
           "done": true,
           "done_reason": "stop",
-          "total_duration": 4373531496,
-          "load_duration": 44438132,
+          "total_duration": 887142667,
+          "load_duration": 119331417,
           "prompt_eval_count": 56,
-          "prompt_eval_duration": 1296273199,
+          "prompt_eval_duration": 74294709,
           "eval_count": 18,
-          "eval_duration": 3032321735,
+          "eval_duration": 692842791,
           "response": "",
           "thinking": null,
           "context": null

tests/integration/recordings/responses/0b27fd737699.json

@@ -20,15 +20,15 @@
       "__type__": "ollama._types.GenerateResponse",
       "__data__": {
         "model": "llama-guard3:1b",
-        "created_at": "2025-08-01T23:13:57.556416Z",
+        "created_at": "2025-09-03T17:37:47.461886Z",
         "done": true,
         "done_reason": "stop",
-        "total_duration": 432363250,
-        "load_duration": 159296417,
+        "total_duration": 338927833,
+        "load_duration": 100895125,
         "prompt_eval_count": 223,
-        "prompt_eval_duration": 257000000,
+        "prompt_eval_duration": 221583042,
         "eval_count": 2,
-        "eval_duration": 14000000,
+        "eval_duration": 12341416,
         "response": "safe",
         "thinking": null,
         "context": null

tests/integration/recordings/responses/0b3f2e4754ff.json

@@ -24,7 +24,7 @@
       {
         "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
         "__data__": {
-          "id": "chatcmpl-29",
+          "id": "chatcmpl-414",
           "choices": [
             {
               "delta": {
@@ -39,7 +39,7 @@
               "logprobs": null
             }
           ],
-          "created": 1754090031,
+          "created": 1756921333,
           "model": "llama3.2:3b-instruct-fp16",
           "object": "chat.completion.chunk",
           "service_tier": null,
@@ -50,7 +50,7 @@
       {
         "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
         "__data__": {
-          "id": "chatcmpl-29",
+          "id": "chatcmpl-414",
           "choices": [
             {
               "delta": {
@@ -65,7 +65,7 @@
               "logprobs": null
             }
           ],
-          "created": 1754090031,
+          "created": 1756921333,
           "model": "llama3.2:3b-instruct-fp16",
           "object": "chat.completion.chunk",
           "service_tier": null,
@@ -76,7 +76,7 @@
       {
         "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
         "__data__": {
-          "id": "chatcmpl-29",
+          "id": "chatcmpl-414",
           "choices": [
             {
               "delta": {
@@ -91,7 +91,7 @@
               "logprobs": null
             }
           ],
-          "created": 1754090031,
+          "created": 1756921333,
           "model": "llama3.2:3b-instruct-fp16",
           "object": "chat.completion.chunk",
           "service_tier": null,
@@ -102,7 +102,7 @@
       {
         "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
         "__data__": {
-          "id": "chatcmpl-29",
+          "id": "chatcmpl-414",
           "choices": [
             {
               "delta": {
@@ -117,7 +117,7 @@
               "logprobs": null
             }
           ],
-          "created": 1754090031,
+          "created": 1756921333,
           "model": "llama3.2:3b-instruct-fp16",
           "object": "chat.completion.chunk",
           "service_tier": null,
@@ -128,7 +128,7 @@
       {
         "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
         "__data__": {
-          "id": "chatcmpl-29",
+          "id": "chatcmpl-414",
           "choices": [
             {
               "delta": {
@@ -143,7 +143,7 @@
               "logprobs": null
             }
           ],
-          "created": 1754090031,
+          "created": 1756921334,
           "model": "llama3.2:3b-instruct-fp16",
           "object": "chat.completion.chunk",
           "service_tier": null,
@@ -154,7 +154,7 @@
       {
         "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
         "__data__": {
-          "id": "chatcmpl-29",
+          "id": "chatcmpl-414",
           "choices": [
             {
               "delta": {
@@ -169,7 +169,7 @@
               "logprobs": null
             }
           ],
-          "created": 1754090031,
+          "created": 1756921334,
           "model": "llama3.2:3b-instruct-fp16",
           "object": "chat.completion.chunk",
           "service_tier": null,
@@ -180,7 +180,7 @@
       {
         "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
         "__data__": {
-          "id": "chatcmpl-29",
+          "id": "chatcmpl-414",
           "choices": [
             {
               "delta": {
@@ -195,7 +195,7 @@
               "logprobs": null
             }
           ],
-          "created": 1754090031,
+          "created": 1756921334,
           "model": "llama3.2:3b-instruct-fp16",
           "object": "chat.completion.chunk",
           "service_tier": null,
@@ -206,7 +206,7 @@
       {
         "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
         "__data__": {
-          "id": "chatcmpl-29",
+          "id": "chatcmpl-414",
           "choices": [
             {
               "delta": {
@@ -221,7 +221,7 @@
               "logprobs": null
             }
           ],
-          "created": 1754090031,
+          "created": 1756921334,
           "model": "llama3.2:3b-instruct-fp16",
           "object": "chat.completion.chunk",
           "service_tier": null,

tests/integration/recordings/responses/0e8f2b001dd9.json

@@ -1,7 +1,7 @@
 {
   "request": {
     "method": "POST",
-    "url": "http://localhost:11434/v1/v1/chat/completions",
+    "url": "http://0.0.0.0:11434/v1/v1/chat/completions",
     "headers": {},
     "body": {
       "model": "llama3.2:3b-instruct-fp16",
@@ -20,14 +20,14 @@
     "body": {
       "__type__": "openai.types.chat.chat_completion.ChatCompletion",
       "__data__": {
-        "id": "chatcmpl-368",
+        "id": "chatcmpl-161",
         "choices": [
           {
             "finish_reason": "stop",
             "index": 0,
             "logprobs": null,
             "message": {
-              "content": "Saturn is known for its extensive ring system.",
+              "content": "The answer is Saturn.",
               "refusal": null,
               "role": "assistant",
               "annotations": null,
@@ -37,15 +37,15 @@
             }
           }
         ],
-        "created": 1754081853,
+        "created": 1756921364,
         "model": "llama3.2:3b-instruct-fp16",
         "object": "chat.completion",
         "service_tier": null,
         "system_fingerprint": "fp_ollama",
         "usage": {
-          "completion_tokens": 11,
+          "completion_tokens": 6,
           "prompt_tokens": 39,
-          "total_tokens": 50,
+          "total_tokens": 45,
           "completion_tokens_details": null,
           "prompt_tokens_details": null
         }

tests/integration/recordings/responses/10eea8c15ddc.json

@@ -20,15 +20,15 @@
       "__type__": "ollama._types.GenerateResponse",
       "__data__": {
         "model": "llama-guard3:1b",
-        "created_at": "2025-08-01T23:12:51.682357Z",
+        "created_at": "2025-09-03T17:37:33.473237Z",
         "done": true,
         "done_reason": "stop",
-        "total_duration": 238161000,
-        "load_duration": 72494750,
+        "total_duration": 279025042,
+        "load_duration": 162673250,
         "prompt_eval_count": 212,
-        "prompt_eval_duration": 87000000,
+        "prompt_eval_duration": 73595834,
         "eval_count": 5,
-        "eval_duration": 74000000,
+        "eval_duration": 41950291,
         "response": "unsafe\nS8",
         "thinking": null,
         "context": null

tests/integration/recordings/responses/140187e305dc.json

@@ -1,7 +1,7 @@
 {
   "request": {
     "method": "POST",
-    "url": "http://localhost:11434/v1/v1/chat/completions",
+    "url": "http://0.0.0.0:11434/v1/v1/chat/completions",
     "headers": {},
     "body": {
       "model": "llama3.2:3b-instruct-fp16",
@@ -20,14 +20,14 @@
     "body": {
       "__type__": "openai.types.chat.chat_completion.ChatCompletion",
       "__data__": {
-        "id": "chatcmpl-876",
+        "id": "chatcmpl-974",
         "choices": [
           {
             "finish_reason": "stop",
             "index": 0,
             "logprobs": null,
             "message": {
-              "content": "I'm afraid I don't have a built-in ability to directly interface with or \"test\" OpenAI models, including the original GPT-1 model. However, I can explain how you might approach this task:\n\nThe OpenAI GPT-1 is a large transformer-based language model that was trained on a massive dataset of text and achieved state-of-the-art results in various natural language processing tasks.\n\nTo test or evaluate the performance of a model like GPT-1, you would typically follow these steps:\n\n1. **Get access to the OpenAI API**: The OpenAI API provides a way for developers to interact with the GPT-1 model programmatically. You can sign up for an API key on the OpenAI website.\n2. **Choose a testing platform or environment**: You'll need a compute platform that supports the necessary algorithms and data structures to run inference on the GPT-1 model. Some popular options include AWS, Google Cloud, or Azure Compute Virtual Machines.\n3. **Prepare your test input data**: This will involve creating text inputs in the format expected by the OpenAI API (i.e., a JSON object containing the text to be processed).\n4. **Use the OpenAI Python library or SDK**: The OpenAI Python library provides an easy-to-use interface for interacting with the GPT-1 model through the API.\n\nHere's some example code that demonstrates how you might use the OpenAI Flask API to test a single input:\n\n```python\nfrom flask import Flask, request, jsonify\nimport json\n\napp = Flask(__name__)\n\n@ app . route ( '/ /gpt-en ', ' Text ', methods = ['POST'])\ndef gpt_en () -> Json :\n    data = request . get_json ()\n    if not data or \"message\" in ( data ):\n        return None , 400 , { ' error' : \"Input must be a text string.\" }\n    response = []\n    while True:\n        message = \"\"\n        for token in data [\"input\"]:\n            response_text = f\"{data['prompt']} {token}\"\n            data[\"input\"] = [response_text]\n            new_response = gpt_en()(data)\n            if all([not item or not isinstance(item, dict) for item in new_response]):\n             break\n\n        message = json . dumps ({}\"text\": response_text})\n        response.append(message)\n\n    return jsonify ({\"output\": response}), 200 , {}\n\nif __name__ == \"__main__\":\n   app.run(debug=True)\n```\n\n5. **Evaluate the output**: Once you have processed your test input data using the GPT-1 model, you can evaluate the accuracy of the generated responses.\n\nKeep in mind that this is just a basic example to illustrate how you might approach testing the OpenAI GPT-1 model.",
+              "content": "I'm happy to help you test the OpenAI API, however I can not access the API.\n\nInstead why don't we follow these steps:\n\n*   Check documentation\n*   Contact support\n*   Reach out to their community forum. \n\nLet me know if I can be of any additional assistance",
               "refusal": null,
               "role": "assistant",
               "annotations": null,
@@ -37,15 +37,15 @@
             }
           }
         ],
-        "created": 1754510050,
+        "created": 1756921202,
         "model": "llama3.2:3b-instruct-fp16",
         "object": "chat.completion",
         "service_tier": null,
         "system_fingerprint": "fp_ollama",
         "usage": {
-          "completion_tokens": 567,
+          "completion_tokens": 61,
           "prompt_tokens": 31,
-          "total_tokens": 598,
+          "total_tokens": 92,
           "completion_tokens_details": null,
           "prompt_tokens_details": null
         }

tests/integration/recordings/responses/17253d7cc667.json

@@ -20,15 +20,15 @@
       "__type__": "ollama._types.GenerateResponse",
       "__data__": {
         "model": "llama-guard3:1b",
-        "created_at": "2025-08-01T23:12:52.919624Z",
+        "created_at": "2025-09-03T17:37:34.308033Z",
         "done": true,
         "done_reason": "stop",
-        "total_duration": 201956834,
-        "load_duration": 105132584,
+        "total_duration": 200296000,
+        "load_duration": 115974708,
         "prompt_eval_count": 212,
-        "prompt_eval_duration": 75000000,
+        "prompt_eval_duration": 72173459,
         "eval_count": 2,
-        "eval_duration": 20000000,
+        "eval_duration": 11536750,
         "response": "safe",
         "thinking": null,
         "context": null

tests/integration/recordings/responses/173ecb3aab28.json

@@ -40,7 +40,7 @@
       {
         "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
         "__data__": {
-          "id": "chatcmpl-457",
+          "id": "chatcmpl-921",
           "choices": [
             {
               "delta": {
@@ -55,7 +55,7 @@
               "logprobs": null
             }
           ],
-          "created": 1754090032,
+          "created": 1756920971,
           "model": "llama3.2:3b-instruct-fp16",
           "object": "chat.completion.chunk",
           "service_tier": null,
@@ -66,7 +66,7 @@
       {
         "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
         "__data__": {
-          "id": "chatcmpl-457",
+          "id": "chatcmpl-921",
           "choices": [
             {
               "delta": {
@@ -81,7 +81,7 @@
               "logprobs": null
             }
           ],
-          "created": 1754090032,
+          "created": 1756920971,
           "model": "llama3.2:3b-instruct-fp16",
           "object": "chat.completion.chunk",
           "service_tier": null,
@@ -92,7 +92,7 @@
       {
         "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
         "__data__": {
-          "id": "chatcmpl-457",
+          "id": "chatcmpl-921",
           "choices": [
             {
               "delta": {
@@ -107,7 +107,7 @@
               "logprobs": null
             }
           ],
-          "created": 1754090032,
+          "created": 1756920971,
           "model": "llama3.2:3b-instruct-fp16",
           "object": "chat.completion.chunk",
           "service_tier": null,
@@ -118,7 +118,7 @@
       {
         "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
         "__data__": {
-          "id": "chatcmpl-457",
+          "id": "chatcmpl-921",
           "choices": [
             {
               "delta": {
@@ -133,7 +133,7 @@
               "logprobs": null
             }
           ],
-          "created": 1754090032,
+          "created": 1756920971,
           "model": "llama3.2:3b-instruct-fp16",
           "object": "chat.completion.chunk",
           "service_tier": null,
@@ -144,7 +144,7 @@
       {
         "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
         "__data__": {
-          "id": "chatcmpl-457",
+          "id": "chatcmpl-921",
           "choices": [
             {
               "delta": {
@@ -159,7 +159,7 @@
               "logprobs": null
             }
           ],
-          "created": 1754090032,
+          "created": 1756920971,
           "model": "llama3.2:3b-instruct-fp16",
           "object": "chat.completion.chunk",
           "service_tier": null,
@@ -170,7 +170,7 @@
       {
         "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
         "__data__": {
-          "id": "chatcmpl-457",
+          "id": "chatcmpl-921",
           "choices": [
             {
               "delta": {
@@ -185,7 +185,7 @@
               "logprobs": null
             }
           ],
-          "created": 1754090032,
+          "created": 1756920971,
           "model": "llama3.2:3b-instruct-fp16",
           "object": "chat.completion.chunk",
           "service_tier": null,
@@ -196,7 +196,7 @@
       {
         "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
         "__data__": {
-          "id": "chatcmpl-457",
+          "id": "chatcmpl-921",
           "choices": [
             {
               "delta": {
@@ -211,7 +211,7 @@
               "logprobs": null
             }
           ],
-          "created": 1754090032,
+          "created": 1756920971,
           "model": "llama3.2:3b-instruct-fp16",
           "object": "chat.completion.chunk",
           "service_tier": null,
@@ -222,7 +222,7 @@
       {
         "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
         "__data__": {
-          "id": "chatcmpl-457",
+          "id": "chatcmpl-921",
           "choices": [
             {
               "delta": {
@@ -237,7 +237,7 @@
               "logprobs": null
             }
           ],
-          "created": 1754090032,
+          "created": 1756920971,
           "model": "llama3.2:3b-instruct-fp16",
           "object": "chat.completion.chunk",
           "service_tier": null,

tests/integration/recordings/responses/174458ad71b2.json

@@ -20,15 +20,15 @@
       "__type__": "ollama._types.GenerateResponse",
       "__data__": {
         "model": "llama-guard3:1b",
-        "created_at": "2025-08-01T23:12:53.580806Z",
+        "created_at": "2025-09-03T17:37:34.994704Z",
         "done": true,
         "done_reason": "stop",
-        "total_duration": 205732750,
-        "load_duration": 98967000,
+        "total_duration": 339570875,
+        "load_duration": 262794125,
         "prompt_eval_count": 213,
-        "prompt_eval_duration": 86000000,
+        "prompt_eval_duration": 64061000,
         "eval_count": 2,
-        "eval_duration": 18000000,
+        "eval_duration": 11839042,
         "response": "safe",
         "thinking": null,
         "context": null

tests/integration/recordings/responses/178016edef0e.json

@@ -20,15 +20,15 @@
       "__type__": "ollama._types.GenerateResponse",
       "__data__": {
         "model": "llama-guard3:1b",
-        "created_at": "2025-08-01T23:12:52.354566Z",
+        "created_at": "2025-09-03T17:37:33.769233Z",
         "done": true,
         "done_reason": "stop",
-        "total_duration": 605192500,
-        "load_duration": 457087166,
+        "total_duration": 253836584,
+        "load_duration": 138624959,
         "prompt_eval_count": 210,
-        "prompt_eval_duration": 63000000,
+        "prompt_eval_duration": 69496125,
         "eval_count": 5,
-        "eval_duration": 84000000,
+        "eval_duration": 45062833,
         "response": "unsafe\nS12",
         "thinking": null,
         "context": null

tests/integration/recordings/responses/197228e26971.json

@@ -20,15 +20,15 @@
       "__type__": "ollama._types.GenerateResponse",
       "__data__": {
         "model": "llama-guard3:1b",
-        "created_at": "2025-08-01T23:12:52.686478Z",
+        "created_at": "2025-09-03T17:37:34.074233Z",
         "done": true,
         "done_reason": "stop",
-        "total_duration": 304136208,
-        "load_duration": 155977000,
+        "total_duration": 270746375,
+        "load_duration": 156423042,
         "prompt_eval_count": 213,
-        "prompt_eval_duration": 71000000,
+        "prompt_eval_duration": 70338083,
         "eval_count": 5,
-        "eval_duration": 76000000,
+        "eval_duration": 43379167,
         "response": "unsafe\nS2",
         "thinking": null,
         "context": null

tests/integration/recordings/responses/198ef7208389.json

@@ -20,15 +20,15 @@
       "__type__": "ollama._types.GenerateResponse",
       "__data__": {
         "model": "llama-guard3:1b",
-        "created_at": "2025-08-01T23:12:51.186501Z",
+        "created_at": "2025-09-03T17:37:32.84197Z",
         "done": true,
         "done_reason": "stop",
-        "total_duration": 3146184459,
-        "load_duration": 2533467917,
+        "total_duration": 21572898667,
+        "load_duration": 21155275042,
         "prompt_eval_count": 212,
-        "prompt_eval_duration": 526000000,
+        "prompt_eval_duration": 371898125,
         "eval_count": 5,
-        "eval_duration": 83000000,
+        "eval_duration": 43290458,
         "response": "unsafe\nS1",
         "thinking": null,
         "context": null

tests/integration/recordings/responses/1adfaa0e062e.json

@@ -20,15 +20,15 @@
       "__type__": "ollama._types.GenerateResponse",
       "__data__": {
         "model": "llama-guard3:1b",
-        "created_at": "2025-08-01T23:12:53.332041Z",
+        "created_at": "2025-09-03T17:37:34.607413Z",
         "done": true,
         "done_reason": "stop",
-        "total_duration": 365895333,
-        "load_duration": 257825208,
+        "total_duration": 267812042,
+        "load_duration": 181570000,
         "prompt_eval_count": 213,
-        "prompt_eval_duration": 78000000,
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         "response": "safe",
         "thinking": null,
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tests/integration/recordings/responses/1b8394f90636.json

@@ -22,15 +22,15 @@
       "__type__": "ollama._types.GenerateResponse",
       "__data__": {
         "model": "llama3.2:3b-instruct-fp16",
-        "created_at": "2025-08-04T22:55:05.685988Z",
+        "created_at": "2025-09-03T17:36:13.821929Z",
         "done": true,
         "done_reason": "stop",
-        "total_duration": 14128980625,
-        "load_duration": 7220159208,
+        "total_duration": 1907912167,
+        "load_duration": 90979292,
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+        "prompt_eval_duration": 77350291,
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-        "eval_duration": 2224000000,
+        "eval_duration": 1738568334,
         "response": " _______.\n\nThe best answer is blue. The traditional nursery rhyme goes like this:\n\nRoses are red,\nViolets are blue,\nSugar is sweet,\nAnd so are you! (Or something similar.)",
         "thinking": null,
         "context": null

tests/integration/recordings/responses/1b92be674e2a.json

@@ -20,15 +20,15 @@
       "__type__": "ollama._types.GenerateResponse",
       "__data__": {
         "model": "llama3.2:3b-instruct-fp16",
-        "created_at": "2025-07-31T17:50:06.140190726Z",
+        "created_at": "2025-09-03T17:39:38.236797Z",
         "done": true,
         "done_reason": "stop",
-        "total_duration": 5213341378,
-        "load_duration": 43943569,
+        "total_duration": 1296281500,
+        "load_duration": 283393917,
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+        "prompt_eval_duration": 75453042,
         "eval_count": 24,
-        "eval_duration": 4119422888,
+        "eval_duration": 936860125,
         "response": "Mark Zuckerberg is the founder, chairman and CEO of Meta, which he originally founded as Facebook in 2004.",
         "thinking": null,
         "context": null

tests/integration/recordings/responses/1e11c2b20ff8.json

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+    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
+    "headers": {},
+    "body": {
+      "model": "all-minilm:l6-v2",
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+        "How do systems learn automatically?"
+      ],
+      "encoding_format": "float"
+    },
+    "endpoint": "/v1/embeddings",
+    "model": "all-minilm:l6-v2"
+  },
+  "response": {
+    "body": {
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+}

tests/integration/recordings/responses/211b1562d4e6.json

@@ -20,15 +20,15 @@
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+        "created_at": "2025-09-03T17:36:17.894986Z",
         "done": true,
         "done_reason": "stop",
-        "total_duration": 498612042,
-        "load_duration": 71411834,
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+        "prompt_eval_duration": 68658541,
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-        "eval_duration": 323000000,
+        "eval_duration": 207389084,
         "response": "Humans live on Earth.",
         "thinking": null,
         "context": null

tests/integration/recordings/responses/23506e73bb9e.json

@@ -0,0 +1,422 @@
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+    "model": "all-minilm:l6-v2"
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tests/integration/recordings/responses/2afe3b38ca01.json

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tests/integration/recordings/responses/2d187a11704c.json

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@@ -1534,7 +1534,7 @@
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@@ -1570,7 +1570,7 @@
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@@ -1588,7 +1588,7 @@
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@@ -1606,7 +1606,7 @@
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@@ -1624,7 +1624,7 @@
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@@ -1642,7 +1642,7 @@
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@@ -1660,7 +1660,7 @@
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@@ -1678,7 +1678,7 @@
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@@ -1696,7 +1696,7 @@
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@@ -1714,7 +1714,7 @@
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@@ -1732,7 +1732,7 @@
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@@ -1750,7 +1750,7 @@
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-          "created_at": "2025-08-01T23:14:16.959327Z",
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@@ -1768,7 +1768,7 @@
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@@ -1786,7 +1786,7 @@
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@@ -1804,15 +1804,15 @@
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           "done_reason": "stop",
-          "total_duration": 5499672375,
-          "load_duration": 58161750,
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tests/integration/recordings/responses/382c2f22274c.json

@@ -1,7 +1,7 @@
 {
   "request": {
     "method": "POST",
-    "url": "http://localhost:11434/v1/v1/chat/completions",
+    "url": "http://0.0.0.0:11434/v1/v1/chat/completions",
     "headers": {},
     "body": {
       "model": "llama3.2:3b-instruct-fp16",
@@ -22,14 +22,14 @@
     "body": {
       "__type__": "openai.types.chat.chat_completion.ChatCompletion",
       "__data__": {
-        "id": "chatcmpl-339",
+        "id": "chatcmpl-442",
         "choices": [
           {
             "finish_reason": "length",
             "index": 0,
             "logprobs": null,
             "message": {
-              "content": "I can guide you through the process, but please note that this is not an official OpenAI API call. OpenAI's API terms and conditions prohibit using their models for malicious purposes.\n\nTo test a model like \"text-temperature\" with a temperature of 0 (i.e., no noise or randomness), we'll need to use a third-party library that connects to the OpenAI API. One such library is `transformers`.\n\nFirst, you need to install the `transformers` and `",
+              "content": "I can guide you on how to use the `test-temperature` parameter with OpenAI's API, but please note that using a temperature of 0 may not produce meaningful results. Temperature is a hyperparameter that controls the level of randomness in the model's output.\n\nOpenAI's API uses a variant of the GPT-3 model, which is trained on a large corpus of text data. The `test-temperature` parameter allows you to adjust the level of randomness in the model's output",
               "refusal": null,
               "role": "assistant",
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@@ -39,7 +39,7 @@
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         ],
-        "created": 1754510065,
+        "created": 1756921254,
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tests/integration/recordings/responses/3c0bf9ba81b2.json

@@ -20,14 +20,14 @@
     "body": {
       "__type__": "openai.types.chat.chat_completion.ChatCompletion",
       "__data__": {
-        "id": "chatcmpl-651",
+        "id": "chatcmpl-334",
         "choices": [
           {
             "finish_reason": "length",
             "index": 0,
             "logprobs": null,
             "message": {
-              "content": "I'm ready to help",
+              "content": "It looks like we've",
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@@ -37,7 +37,7 @@
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         ],
-        "created": 1755294941,
+        "created": 1756921086,
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tests/integration/recordings/responses/3c3f13cb7794.json

@@ -21,7 +21,7 @@
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-          "created_at": "2025-08-04T22:55:11.338232Z",
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@@ -39,7 +39,7 @@
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@@ -57,7 +57,7 @@
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@@ -75,7 +75,7 @@
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@@ -111,7 +111,7 @@
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@@ -147,7 +147,7 @@
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@@ -165,7 +165,7 @@
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@@ -183,7 +183,7 @@
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@@ -201,15 +201,15 @@
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-          "created_at": "2025-08-04T22:55:11.854841Z",
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           "done": true,
           "done_reason": "stop",
-          "total_duration": 652371000,
-          "load_duration": 42086042,
+          "total_duration": 628034000,
+          "load_duration": 116384417,
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tests/integration/recordings/responses/3ca695048bee.json

@@ -1,7 +1,7 @@
 {
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     "method": "POST",
-    "url": "http://localhost:11434/v1/v1/chat/completions",
+    "url": "http://0.0.0.0:11434/v1/v1/chat/completions",
     "headers": {},
     "body": {
       "model": "llama3.2:3b-instruct-fp16",
@@ -39,7 +39,7 @@
       {
         "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
         "__data__": {
-          "id": "chatcmpl-490",
+          "id": "chatcmpl-3",
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@@ -50,7 +50,7 @@
                 "tool_calls": [
                   {
                     "index": 0,
-                    "id": "call_rolv1ozt",
+                    "id": "call_3kigugt3",
                     "function": {
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                       "name": "get_weather"
@@ -64,7 +64,7 @@
               "logprobs": null
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-          "created": 1754081852,
+          "created": 1756921361,
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@@ -75,7 +75,7 @@
       {
         "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
         "__data__": {
-          "id": "chatcmpl-490",
+          "id": "chatcmpl-3",
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@@ -85,12 +85,12 @@
                 "role": "assistant",
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-              "finish_reason": "stop",
+              "finish_reason": "tool_calls",
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tests/integration/recordings/responses/3dff18060ebc.json

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+{
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+    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
+    "headers": {},
+    "body": {
+      "model": "all-minilm:l6-v2",
+      "input": [
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+      "encoding_format": "float"
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+    "endpoint": "/v1/embeddings",
+    "model": "all-minilm:l6-v2"
+  },
+  "response": {
+    "body": {
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tests/integration/recordings/responses/417020320684.json

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tests/integration/recordings/responses/41e27b9b5d09.json

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tests/integration/recordings/responses/4420515208a8.json

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+}

tests/integration/recordings/responses/44a1d9de0602.json

@@ -20,7 +20,7 @@
     "body": {
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       "__data__": {
-        "id": "chatcmpl-987",
+        "id": "chatcmpl-507",
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@@ -37,7 +37,7 @@
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         "model": "llama3.2:3b-instruct-fp16",
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         "service_tier": null,

tests/integration/recordings/responses/44fb9cf5875f.json

@@ -20,15 +20,15 @@
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tests/integration/recordings/responses/48d2fb183a2a.json

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tests/integration/recordings/responses/50340cd4d253.json

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         "response": "safe",
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tests/integration/recordings/responses/5370751803dc.json

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+{
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+      "input": [
+        "Python is a high-level programming language with code readability and fewer lines than C++ or Java"
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+      "encoding_format": "float"
+    },
+    "endpoint": "/v1/embeddings",
+    "model": "all-minilm:l6-v2"
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tests/integration/recordings/responses/545d86510a80.json

@@ -22,7 +22,7 @@
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@@ -238,15 +238,15 @@
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-          "total_duration": 914060542,
-          "load_duration": 63705209,
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tests/integration/recordings/responses/554de3cd986f.json

@@ -22,7 +22,7 @@
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@@ -58,7 +58,7 @@
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@@ -76,7 +76,7 @@
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@@ -94,7 +94,7 @@
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@@ -112,7 +112,7 @@
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@@ -130,7 +130,7 @@
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@@ -148,7 +148,7 @@
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@@ -166,7 +166,7 @@
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@@ -184,7 +184,7 @@
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@@ -202,7 +202,7 @@
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@@ -220,7 +220,7 @@
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@@ -238,7 +238,7 @@
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@@ -256,7 +256,7 @@
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@@ -274,7 +274,7 @@
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@@ -292,7 +292,7 @@
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@@ -310,7 +310,7 @@
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@@ -328,7 +328,7 @@
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@@ -346,15 +346,15 @@
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           "done": true,
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tests/integration/recordings/responses/561746e1c8de.json

@@ -21,7 +21,7 @@
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@@ -39,7 +39,7 @@
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@@ -57,7 +57,7 @@
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@@ -75,7 +75,7 @@
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@@ -93,7 +93,7 @@
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@@ -111,7 +111,7 @@
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@@ -129,7 +129,7 @@
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@@ -147,7 +147,7 @@
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@@ -165,7 +165,7 @@
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@@ -183,7 +183,7 @@
         "__type__": "ollama._types.GenerateResponse",
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-          "created_at": "2025-08-15T20:24:50.878846539Z",
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@@ -201,15 +201,15 @@
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         "__data__": {
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-          "created_at": "2025-08-15T20:24:51.063200561Z",
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tests/integration/recordings/responses/563b994bb7d1.json

@@ -20,15 +20,15 @@
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       "__data__": {
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-        "created_at": "2025-08-04T22:55:13.25248Z",
+        "created_at": "2025-09-03T17:36:19.594923Z",
         "done": true,
         "done_reason": "stop",
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-        "load_duration": 200585375,
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         "response": "[get_weather(location=\"San Francisco, CA\")]",
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tests/integration/recordings/responses/5f5d16afadb4.json

@@ -21,7 +21,7 @@
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@@ -57,7 +57,7 @@
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@@ -147,7 +147,7 @@
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@@ -165,7 +165,7 @@
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@@ -183,7 +183,7 @@
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@@ -201,15 +201,15 @@
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tests/integration/recordings/responses/62aa454ea5f9.json

@@ -0,0 +1,422 @@
+{
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+    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
+    "headers": {},
+    "body": {
+      "model": "all-minilm:l6-v2",
+      "input": [
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+      "encoding_format": "float"
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+    "endpoint": "/v1/embeddings",
+    "model": "all-minilm:l6-v2"
+  },
+  "response": {
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+}

tests/integration/recordings/responses/6906a6e71988.json

@@ -20,15 +20,15 @@
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-        "created_at": "2025-08-01T23:14:18.886381Z",
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         "done": true,
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tests/integration/recordings/responses/6cc063bbd7d3.json

@@ -21,7 +21,7 @@
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@@ -39,7 +39,7 @@
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@@ -57,7 +57,7 @@
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@@ -75,7 +75,7 @@
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tests/integration/recordings/responses/6d35c91287e2.json

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tests/integration/recordings/responses/6f96090aa955.json

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-    "url": "http://localhost:11434/v1/v1/chat/completions",
+    "url": "http://0.0.0.0:11434/v1/v1/chat/completions",
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@@ -400,7 +452,7 @@
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           ],
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@@ -411,33 +463,7 @@
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@@ -452,7 +478,7 @@
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@@ -463,7 +489,7 @@
       {
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+          "id": "chatcmpl-698",
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@@ -478,7 +504,7 @@
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@@ -489,7 +515,7 @@
       {
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+          "id": "chatcmpl-698",
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@@ -504,7 +530,7 @@
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@@ -515,7 +541,7 @@
       {
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         "__data__": {
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+          "id": "chatcmpl-698",
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@@ -530,7 +556,7 @@
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@@ -541,7 +567,7 @@
       {
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@@ -556,7 +582,7 @@
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@@ -567,7 +593,7 @@
       {
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+          "id": "chatcmpl-698",
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@@ -593,7 +619,7 @@
       {
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@@ -619,7 +645,7 @@
       {
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tests/integration/recordings/responses/6fbea1abca7c.json

@@ -22,7 +22,7 @@
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         "__data__": {
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-          "created_at": "2025-08-01T23:14:20.337763Z",
+          "created_at": "2025-09-03T17:38:01.89965Z",
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@@ -40,7 +40,7 @@
         "__type__": "ollama._types.GenerateResponse",
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-          "created_at": "2025-08-01T23:14:20.394358Z",
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@@ -58,7 +58,7 @@
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         "__data__": {
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@@ -76,7 +76,7 @@
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-          "created_at": "2025-08-01T23:14:20.504443Z",
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@@ -94,7 +94,7 @@
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@@ -130,7 +130,7 @@
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@@ -148,7 +148,7 @@
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@@ -166,7 +166,7 @@
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@@ -184,7 +184,7 @@
         "__type__": "ollama._types.GenerateResponse",
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@@ -202,7 +202,7 @@
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@@ -220,7 +220,7 @@
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@@ -238,7 +238,7 @@
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@@ -256,7 +256,7 @@
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@@ -274,7 +274,7 @@
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@@ -346,15 +346,15 @@
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           "done_reason": "stop",
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tests/integration/recordings/responses/70adef2c30c4.json

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-        "created_at": "2025-08-04T22:55:55.720345Z",
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         "response": "The answer is Saturn! Saturn's ring system is one of the most iconic and well-known in our solar system. The rings are made up of ice particles, rock debris, and dust that orbit around the planet due to its gravitational pull.\n\nWould you like to know more about Saturn's rings or is there something else I can help you with?",
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tests/integration/recordings/responses/72c1126ff2f9.json

@@ -0,0 +1,422 @@
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+    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
+    "headers": {},
+    "body": {
+      "model": "all-minilm:l6-v2",
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+      "encoding_format": "float"
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+    "endpoint": "/v1/embeddings",
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tests/integration/recordings/responses/7354ec181984.json

@@ -20,15 +20,15 @@
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         "response": "The smallest country in the world is the Vatican City, which has a total area of approximately 0.44 km\u00b2 (0.17 sq mi). It is an independent city-state located within Rome, Italy, and is home to the Pope and the central government of the Catholic Church.\n\nTo put that into perspective, the Vatican City is smaller than a golf course! Despite its tiny size, it has its own government, currency, postal system, and even its own police force. It's also home to numerous iconic landmarks like St. Peter's Basilica and the Sistine Chapel.\n\nInterestingly, the Vatican City is not only the smallest country in the world but also the most densely populated, with a population of just over 800 people!",
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tests/integration/recordings/responses/75d0dd9d0fa3.json

@@ -45,15 +45,15 @@
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         "response": "{ \"name\": \"Michael Jordan\", \"year_born\": \"1963\", \"year_retired\": \"2003\"}\n    ",
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tests/integration/recordings/responses/7b25b702ea18.json

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+    "headers": {},
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+    "endpoint": "/v1/embeddings",
+    "model": "all-minilm:l6-v2"
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+}

tests/integration/recordings/responses/7b4815aba6c5.json

@@ -22,7 +22,7 @@
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@@ -40,7 +40,7 @@
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-          "created_at": "2025-08-01T23:13:59.273466Z",
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@@ -58,7 +58,7 @@
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@@ -76,7 +76,7 @@
         "__type__": "ollama._types.GenerateResponse",
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-          "created_at": "2025-08-01T23:13:59.379223Z",
+          "created_at": "2025-09-03T17:37:48.966274Z",
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@@ -94,7 +94,7 @@
         "__type__": "ollama._types.GenerateResponse",
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-          "created_at": "2025-08-01T23:13:59.436435Z",
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@@ -112,7 +112,7 @@
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-          "created_at": "2025-08-01T23:13:59.48928Z",
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tests/integration/recordings/responses/7e6806cba34a.json

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+            "object": "embedding"
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+        "model": "all-minilm:l6-v2",
+        "object": "list",
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+}

tests/integration/recordings/responses/80e4404d8987.json

@@ -22,7 +22,7 @@
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         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-01T23:13:56.463658Z",
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@@ -40,7 +40,7 @@
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           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-01T23:13:56.51846Z",
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@@ -58,7 +58,7 @@
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         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
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@@ -76,7 +76,7 @@
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           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-01T23:13:56.621666Z",
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@@ -94,7 +94,7 @@
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         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-01T23:13:56.675114Z",
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@@ -112,7 +112,7 @@
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           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-01T23:13:56.727649Z",
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@@ -130,7 +130,7 @@
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         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-01T23:13:56.780249Z",
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@@ -148,7 +148,7 @@
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-          "created_at": "2025-08-01T23:13:56.834148Z",
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@@ -166,7 +166,7 @@
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@@ -184,15 +184,15 @@
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           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-01T23:13:56.936635Z",
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           "done": true,
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-          "total_duration": 1572591291,
-          "load_duration": 77121041,
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           "response": "",
           "thinking": null,
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tests/integration/recordings/responses/8295382a8e7c.json

@@ -1,7 +1,7 @@
 {
   "request": {
     "method": "POST",
-    "url": "http://localhost:11434/v1/v1/chat/completions",
+    "url": "http://0.0.0.0:11434/v1/v1/chat/completions",
     "headers": {},
     "body": {
       "model": "llama3.2:3b-instruct-fp16",
@@ -20,14 +20,14 @@
     "body": {
       "__type__": "openai.types.chat.chat_completion.ChatCompletion",
       "__data__": {
-        "id": "chatcmpl-99",
+        "id": "chatcmpl-713",
         "choices": [
           {
             "finish_reason": "stop",
             "index": 0,
             "logprobs": null,
             "message": {
-              "content": "I'd be happy to help you test the OpenAI 2 architecture!\n\nOpenAI 2 is a neural network model developed by OpenAI, and it's not exactly possible for me to directly \"test\" it. However, I can guide you through a simplified example of how to verify if OpenAI 2 has been implemented correctly in a specific codebase.\n\nHere's an outline of the steps:\n\n1. **Understand the basics**: Before we dive into testing, make sure you understand the architectural and functional details of OpenAI 2.\n2. **Get access to the model**: You'll need to obtain a trained OpenAI 2 model or implement it from scratch using a language like PyTorch or TensorFlow.\n3. **Implement a validation framework**: Create a simple validation framework that uses common tasks, such as classification on the GLUE benchmark, to evaluate the performance of your OpenAI 2 model.\n\nHere's a simplified code example in PyTorch:\n```python\nimport torch\nfrom transformers import AutoModelForSequenceClassification, AutoTokenizer\n\n# Load pre-trained OpenAI 2 Model(s)\nmodel_name = \"github/openai/OpenAIAccelerated-Text-To-Speech\"\nmodel_class = AutoModelForSequenceClassification\ntokenizer = AutoTokenizer.from_pretrained(model_name)\n\n# Initialize the model and tokenizer\nmodel = model_class(pretrained=True, num_labels=8)  # adjust label number according to your task\ntokenizer = tokenizer\n\ndef evaluate_model():\n    batch_size = 100\n    device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n\n    # Create a validation dataset from the GLUE benchmark\n    glue_datasets = [ datasets[\"glue\"][\"sst2\"], datasets[\"glue\"][\"mnli\"] ]\n    val_dataset = []\n    for i, gds in enumerate(glue_datasets):\n        data = gds[:10000]  # take only first few examples to speed up evaluation\n        input_ids = tokenizer encodings(data[\"sentence1\"], \n                                        attention_mask=data[\"attention_mask\"],\n                                        max_length=512,\n                                        padding=\"max_length\",\n                                        truncation=True,\n                                        return_tensors=\"pt\")\n\n        for example in data:\n            for sentence in [example['sentence1'], example['sentence2']]:\n                input_ids = input_ids.to(device)\n                outputs = model(input_ids, labels=None)  # adjust label to empty\n              \n\n    # Compute evaluation metrics\n    predictions = []\n    labels = []\n    accuracy = torch.zeros(8).to(device)\n\n    for sentence in data.values():\n        sentenceids = [input_ids[\"input_ids\"].flatten()]\n        _, pred_labels = model(sentenceids)\n        if len(predictions) == 0:\n            labels.extend([1, 2])\n        else:\n            assert len(labels)==len(sentences), 'error'\n            labels.append(preds[-1]) \n\n        # Append the prediction to the list\n        predictions.append(pred)\n\n    return accuracy\n\naccuracy = evaluate_model()\nprint(\"Accuracy:\", accuracy)\n```\n\nAfter running this code, you should get an estimate of the model's performance on the GLUE benchmark. Keep in mind that this is a simplified example and real-world openai 2 testing may require more involved validation processes.\n\nI hope this helps! Let me know if you have any further questions or if there are any specific areas where you'd like more information.",
+              "content": "I'd be happy to help you test the Transformer-XL (denoted as \"Test Trace OpenAI 2\") model, but first I need to clarify a few things:\n\n1. **Transformer-XL** is not an official name from OpenAI. It's actually a variant of the Transformer model proposed in the paper \"Long-Short Term Memory Are General: A Study on The Curvature of Time\" (2017) by Jinyu Chen, et al.\n2. **Trace OpenAI 2** sounds like a specific version or configuration of the Transformer-XL model, possibly developed by OpenAI.\n\nGiven these clarifications, I'll provide you with a general idea of how to test the Transformer-XL (or \"Test Trace OpenAI 2\") model using popular frameworks and libraries. Please note that this is not an exhaustive or definitive guide.\n\nTo test the Transformer-XL model, you can follow these steps:\n\n1. **Install the necessary dependencies**: You'll need a deep learning framework like TensorFlow or PyTorch, as well as a library for natural language processing (NLP) like Hugging Face's transformers.\n2. **Load the pre-trained weights**: You can use a pre-trained model checkpoint from Hugging Face's Transformers library or load your own weights trained on a specific task or dataset.\n3. **Prepare your data**: Load your text data into tokens, such as words or characters, and preprocess it according to the specific requirements of the Transformer-XL architecture (e.g., tokenization, padding, etc.).\n4. **Configure the model**: Adjust the hyperparameters to suit your specific test case, including the model's configuration, batch size, learning rate, etc.\n5. **Run the inference**: Use the loaded pre-trained weights to perform inference on your test data.\n\nHere's some sample Python code using PyTorch and Hugging Face's Transformers library to get you started:\n```python\nimport torch\nfrom transformers import LongformerForSequenceClassification, LongformerTokenizer\n\n# Load pre-trained weights\nmodel = LongformerForSequenceClassification.from_pretrained('test-trace-openai-2')\n\n# Prepare data\ntokenizer = model.tokenizer\ntext = \"This is a test sentence\"\ninputs = tokenizer(text, return_tensors='pt')\noutput = model(inputs['input_ids'], attention_mask=inputs['attention_mask'])\n\n# Print the results\nprint(output.logits)\n```\nPlease note that this code snippet is just an example and may not work as-is. You'll need to adapt it to your specific requirements and test data.\n\nKeep in mind that testing a model's performance on a specific task or dataset requires careful consideration of factors like:\n\n* **Test data quality**: Your test data should accurately represent the underlying distribution of your target dataset.\n* **Model evaluation metrics**: Choose relevant evaluation metrics that measure the model's performance on your specific task, such as accuracy, precision, recall, F1-score, etc.\n\nFeel free to ask if you have any further questions or need more guidance!",
               "refusal": null,
               "role": "assistant",
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@@ -37,15 +37,15 @@
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         "object": "chat.completion",
         "service_tier": null,
         "system_fingerprint": "fp_ollama",
         "usage": {
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           "prompt_tokens": 31,
-          "total_tokens": 725,
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tests/integration/recordings/responses/836f51dfb3c5.json

@@ -20,15 +20,15 @@
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       "__data__": {
         "model": "llama-guard3:1b",
-        "created_at": "2025-08-01T23:14:03.770002Z",
+        "created_at": "2025-09-03T17:37:51.562847Z",
         "done": true,
         "done_reason": "stop",
-        "total_duration": 395965875,
-        "load_duration": 178888708,
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-        "eval_duration": 44000000,
+        "eval_duration": 15572291,
         "response": "safe",
         "thinking": null,
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tests/integration/recordings/responses/840fbb380b73.json

@@ -20,15 +20,15 @@
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       "__data__": {
         "model": "llama-guard3:1b",
-        "created_at": "2025-08-01T23:13:57.935921Z",
+        "created_at": "2025-09-03T17:37:47.871962Z",
         "done": true,
         "done_reason": "stop",
-        "total_duration": 313787333,
-        "load_duration": 89797542,
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         "response": "unsafe\nS1",
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tests/integration/recordings/responses/85594a69d74a.json

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       "__data__": {
         "model": "llama-guard3:1b",
-        "created_at": "2025-08-01T23:12:54.634929Z",
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         "done": true,
         "done_reason": "stop",
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         "response": "safe",
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tests/integration/recordings/responses/97d3812bfccb.json

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       "__data__": {
         "model": "llama-guard3:1b",
-        "created_at": "2025-08-01T23:14:06.082832Z",
+        "created_at": "2025-09-03T17:37:52.965106Z",
         "done": true,
         "done_reason": "stop",
-        "total_duration": 421905083,
-        "load_duration": 88557750,
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         "response": "unsafe\nS1",
         "thinking": null,
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tests/integration/recordings/responses/97e259c0d3e5.json

@@ -22,7 +22,7 @@
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         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-01T23:14:07.138696Z",
+          "created_at": "2025-09-03T17:37:53.505006Z",
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@@ -40,7 +40,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-01T23:14:07.195013Z",
+          "created_at": "2025-09-03T17:37:53.547032Z",
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@@ -58,7 +58,7 @@
         "__type__": "ollama._types.GenerateResponse",
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           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-01T23:14:07.246591Z",
+          "created_at": "2025-09-03T17:37:53.588985Z",
           "done": false,
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@@ -76,7 +76,7 @@
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           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-01T23:14:07.29736Z",
+          "created_at": "2025-09-03T17:37:53.631139Z",
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@@ -94,7 +94,7 @@
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           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-01T23:14:07.347941Z",
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           "done": false,
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@@ -112,7 +112,7 @@
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         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-01T23:14:07.399151Z",
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@@ -130,7 +130,7 @@
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           "model": "llama3.2:3b-instruct-fp16",
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@@ -148,7 +148,7 @@
         "__type__": "ollama._types.GenerateResponse",
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           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-01T23:14:07.50538Z",
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           "done": false,
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@@ -166,7 +166,7 @@
         "__type__": "ollama._types.GenerateResponse",
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           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-01T23:14:07.558656Z",
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@@ -184,7 +184,7 @@
         "__type__": "ollama._types.GenerateResponse",
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           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-01T23:14:07.610408Z",
+          "created_at": "2025-09-03T17:37:53.882555Z",
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@@ -202,7 +202,7 @@
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           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-01T23:14:07.66358Z",
+          "created_at": "2025-09-03T17:37:53.924566Z",
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@@ -220,7 +220,7 @@
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-          "created_at": "2025-08-01T23:14:07.717638Z",
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@@ -238,7 +238,7 @@
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           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-01T23:14:07.769423Z",
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@@ -256,7 +256,7 @@
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@@ -274,7 +274,7 @@
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@@ -292,7 +292,7 @@
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           "model": "llama3.2:3b-instruct-fp16",
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@@ -310,7 +310,7 @@
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@@ -328,7 +328,7 @@
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@@ -346,15 +346,15 @@
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           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-01T23:14:08.082749Z",
+          "created_at": "2025-09-03T17:37:54.259141Z",
           "done": true,
           "done_reason": "stop",
-          "total_duration": 1425800209,
-          "load_duration": 138858459,
+          "total_duration": 1008303875,
+          "load_duration": 119709875,
           "prompt_eval_count": 384,
-          "prompt_eval_duration": 340000000,
+          "prompt_eval_duration": 132645959,
           "eval_count": 19,
-          "eval_duration": 945000000,
+          "eval_duration": 755215708,
           "response": "",
           "thinking": null,
           "context": null

tests/integration/recordings/responses/9c140a29ae09.json

@@ -22,7 +22,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-01T23:14:09.83858Z",
+          "created_at": "2025-09-03T17:37:55.13567Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -40,7 +40,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-01T23:14:09.891488Z",
+          "created_at": "2025-09-03T17:37:55.17774Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -58,7 +58,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-01T23:14:09.945656Z",
+          "created_at": "2025-09-03T17:37:55.220061Z",
           "done": false,
           "done_reason": null,
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@@ -76,7 +76,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-01T23:14:09.996898Z",
+          "created_at": "2025-09-03T17:37:55.261406Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -94,7 +94,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-01T23:14:10.053632Z",
+          "created_at": "2025-09-03T17:37:55.302615Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -112,7 +112,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-01T23:14:10.105753Z",
+          "created_at": "2025-09-03T17:37:55.343879Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -130,7 +130,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-01T23:14:10.157953Z",
+          "created_at": "2025-09-03T17:37:55.384951Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -148,7 +148,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-01T23:14:10.210869Z",
+          "created_at": "2025-09-03T17:37:55.426563Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -166,7 +166,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-01T23:14:10.263387Z",
+          "created_at": "2025-09-03T17:37:55.467648Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -184,7 +184,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-01T23:14:10.317794Z",
+          "created_at": "2025-09-03T17:37:55.509469Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -202,7 +202,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-01T23:14:10.373978Z",
+          "created_at": "2025-09-03T17:37:55.552302Z",
           "done": false,
           "done_reason": null,
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@@ -220,7 +220,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-01T23:14:10.429702Z",
+          "created_at": "2025-09-03T17:37:55.596236Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -238,15 +238,15 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-01T23:14:10.483762Z",
+          "created_at": "2025-09-03T17:37:55.637816Z",
           "done": true,
           "done_reason": "stop",
-          "total_duration": 1041142084,
-          "load_duration": 110407459,
+          "total_duration": 726849208,
+          "load_duration": 147625750,
           "prompt_eval_count": 415,
-          "prompt_eval_duration": 283000000,
+          "prompt_eval_duration": 75722709,
           "eval_count": 13,
-          "eval_duration": 646000000,
+          "eval_duration": 502787333,
           "response": "",
           "thinking": null,
           "context": null

tests/integration/recordings/responses/9c28ec9ac338.json

@@ -21,7 +21,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-07-29T23:46:36.316207Z",
+          "created_at": "2025-09-03T17:34:23.434819Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -39,7 +39,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-07-29T23:46:36.358611Z",
+          "created_at": "2025-09-03T17:34:23.477986Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -57,7 +57,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-07-29T23:46:36.401272Z",
+          "created_at": "2025-09-03T17:34:23.520282Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -75,7 +75,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-07-29T23:46:36.444321Z",
+          "created_at": "2025-09-03T17:34:23.561947Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -93,7 +93,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-07-29T23:46:36.48795Z",
+          "created_at": "2025-09-03T17:34:23.603986Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -111,7 +111,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-07-29T23:46:36.530158Z",
+          "created_at": "2025-09-03T17:34:23.646447Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -129,7 +129,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-07-29T23:46:36.573318Z",
+          "created_at": "2025-09-03T17:34:23.688452Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -147,7 +147,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-07-29T23:46:36.616297Z",
+          "created_at": "2025-09-03T17:34:23.730147Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -165,7 +165,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-07-29T23:46:36.659527Z",
+          "created_at": "2025-09-03T17:34:23.772004Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -183,7 +183,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-07-29T23:46:36.702422Z",
+          "created_at": "2025-09-03T17:34:23.813913Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -201,7 +201,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-07-29T23:46:36.745894Z",
+          "created_at": "2025-09-03T17:34:23.856Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -219,7 +219,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-07-29T23:46:36.788811Z",
+          "created_at": "2025-09-03T17:34:23.897939Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -237,7 +237,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-07-29T23:46:36.831618Z",
+          "created_at": "2025-09-03T17:34:23.939953Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -255,7 +255,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-07-29T23:46:36.874469Z",
+          "created_at": "2025-09-03T17:34:23.982033Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -273,7 +273,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-07-29T23:46:36.917372Z",
+          "created_at": "2025-09-03T17:34:24.026067Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -291,7 +291,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-07-29T23:46:36.960558Z",
+          "created_at": "2025-09-03T17:34:24.069083Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -309,7 +309,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-07-29T23:46:37.004223Z",
+          "created_at": "2025-09-03T17:34:24.112349Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -327,15 +327,15 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-07-29T23:46:37.046563Z",
+          "created_at": "2025-09-03T17:34:24.155424Z",
           "done": true,
           "done_reason": "stop",
-          "total_duration": 845522667,
-          "load_duration": 47784875,
+          "total_duration": 896931125,
+          "load_duration": 89697291,
           "prompt_eval_count": 511,
-          "prompt_eval_duration": 66135292,
+          "prompt_eval_duration": 83876750,
           "eval_count": 18,
-          "eval_duration": 730999291,
+          "eval_duration": 722156292,
           "response": "",
           "thinking": null,
           "context": null

tests/integration/recordings/responses/9e7a83d3d596.json

@@ -15,23 +15,23 @@
     "body": {
       "__type__": "openai.types.completion.Completion",
       "__data__": {
-        "id": "cmpl-43",
+        "id": "cmpl-775",
         "choices": [
           {
             "finish_reason": "stop",
             "index": 0,
             "logprobs": null,
-            "text": "Blue.\n\nMy response is based on the traditional English rhyme that pairs the colors of roses (red) with violets in a poetic and somewhat whimsical way. This specific version of the rhyme goes like this:\n\n\"Roses are red,\nViolets are blue,\nSugar is sweet,\nAnd so are you.\"\n\nIn modern times, variations of this rhyme can deviate from the original \"blue\" for violets, but in my complete sentence as requested, sticking with a widely recognized completion adds an air of timelessness and familiarity to the phrase."
+            "text": "Blue.\n\nMy response is based on the traditional rhyme \"Roses are Red, Violets are Blue,\" which is a well-known poem or phrase often used as a greeting or way to express affection. The exact wording may vary slightly depending on the source, but the general meaning remains the same: violets are typically depicted as blue-colored flowers in this rhyme."
           }
         ],
-        "created": 1754348148,
+        "created": 1756921025,
         "model": "llama3.2:3b-instruct-fp16",
         "object": "text_completion",
         "system_fingerprint": "fp_ollama",
         "usage": {
-          "completion_tokens": 113,
+          "completion_tokens": 75,
           "prompt_tokens": 50,
-          "total_tokens": 163,
+          "total_tokens": 125,
           "completion_tokens_details": null,
           "prompt_tokens_details": null
         }

tests/integration/recordings/responses/9fadf5a3d68f.json

@@ -20,15 +20,15 @@
       "__type__": "ollama._types.GenerateResponse",
       "__data__": {
         "model": "llama-guard3:1b",
-        "created_at": "2025-08-01T23:14:22.168612Z",
+        "created_at": "2025-09-03T17:38:03.270261Z",
         "done": true,
         "done_reason": "stop",
-        "total_duration": 198446125,
-        "load_duration": 31859666,
+        "total_duration": 244051875,
+        "load_duration": 111239500,
         "prompt_eval_count": 224,
-        "prompt_eval_duration": 151000000,
+        "prompt_eval_duration": 120962791,
         "eval_count": 2,
-        "eval_duration": 13000000,
+        "eval_duration": 11306292,
         "response": "safe",
         "thinking": null,
         "context": null

tests/integration/recordings/responses/a4c8d19bb1eb.json

@@ -1,7 +1,7 @@
 {
   "request": {
     "method": "POST",
-    "url": "http://localhost:11434/v1/v1/chat/completions",
+    "url": "http://0.0.0.0:11434/v1/v1/chat/completions",
     "headers": {},
     "body": {
       "model": "llama3.2:3b-instruct-fp16",
@@ -20,14 +20,14 @@
     "body": {
       "__type__": "openai.types.chat.chat_completion.ChatCompletion",
       "__data__": {
-        "id": "chatcmpl-560",
+        "id": "chatcmpl-715",
         "choices": [
           {
             "finish_reason": "stop",
             "index": 0,
             "logprobs": null,
             "message": {
-              "content": "Hello! It's nice to meet you. How can I assist you today?",
+              "content": "Hello! It's nice to meet you. Is there something I can help you with or would you like to chat?",
               "refusal": null,
               "role": "assistant",
               "annotations": null,
@@ -37,15 +37,15 @@
             }
           }
         ],
-        "created": 1754081856,
+        "created": 1756921367,
         "model": "llama3.2:3b-instruct-fp16",
         "object": "chat.completion",
         "service_tier": null,
         "system_fingerprint": "fp_ollama",
         "usage": {
-          "completion_tokens": 17,
+          "completion_tokens": 25,
           "prompt_tokens": 29,
-          "total_tokens": 46,
+          "total_tokens": 54,
           "completion_tokens_details": null,
           "prompt_tokens_details": null
         }

tests/integration/recordings/responses/a5187d9d5057.json

@@ -1,7 +1,7 @@
 {
   "request": {
     "method": "POST",
-    "url": "http://localhost:11434/v1/v1/chat/completions",
+    "url": "http://0.0.0.0:11434/v1/v1/chat/completions",
     "headers": {},
     "body": {
       "model": "llama3.2:3b-instruct-fp16",
@@ -20,14 +20,14 @@
     "body": {
       "__type__": "openai.types.chat.chat_completion.ChatCompletion",
       "__data__": {
-        "id": "chatcmpl-64",
+        "id": "chatcmpl-376",
         "choices": [
           {
             "finish_reason": "stop",
             "index": 0,
             "logprobs": null,
             "message": {
-              "content": "You want to test the capabilities of the OpenAI Text-to-Text model (also known as T0).\n\nPlease note that I'll be using a pre-trained model, so my responses might not be entirely customized to your specific prompt or context. That being said, I'll do my best to mimic the behavior of the original model.\n\nWhat would you like to test or ask? Please provide a prompt or question, and I'll respond accordingly.\n\n(Note: if you'd like to run a longer experiment or try out specific models like text completion or code generation, feel free to let me know and we can figure out a way to collaborate.)",
+              "content": "I'll simulate a test for the LA-1030/5B linear accelerator, specifically for the H8 (High Voltage) model found in early models of the test rail. Note that this is not meant to be taken as actual test results but rather a demonstration.\n\n### Introduction:\nThe LA-1030/5B was used primarily for high-energy physics and nuclear research during the 1970s and 1980s. This linear accelerator was capable of producing proton beams with energies up to several GeV. The H8 model, also known as the 'High Voltage' component, is a series of power supplies that drive the high voltage DC (HV) accelerators.\n\n### Test Setup:\n\n- **Test Goal:** Measure the output of the LA-1030/5B H8 model linear accelerator and assess its ability to generate stable, high-voltage direct current (HVDC) to power it properly.\n  \n  - The setup consists of a single test rail containing one of these H8 modules. A precise DC voltage is supplied to the linear accelerator via an external DC source.\n\n### Operating Parameters:\n\n- **Input Voltage:** To ensure the linear accelerator operates within its safe operating parameters, input voltages will be varied from 20KV to 140KV.\n- **Current Delivery:** Monitoring current at these different output levels requires a precise multimeter or oscilloscope. \n- **Voltage Level and Current Stability:** The voltage should stabilize as close as possible to the desired output level.\n\n### Potential Issues\n\n1.) Over-Pressure in H8 Modules\n    - During high voltage levels, there's a risk of over-pressurization in the component casing due to the vacuum properties within the modules.\n    - Check for any external signs of stress or leakage.\n2.) Current Limitation and Arcing\n    - High current requirements demand close monitoring of the accelerator components and associated connections.\n    - An excessive arc can be detrimental to electronics connected to the system.\n3.) Interlocks and Safe Guards\n\n- **Ensure alignment:** Prevent accidental triggering.\n\n4.) Insulation integrity \n    - Potential risks from faulty or non-insulated components\n\n### Results Analysis:\n\nBased on this hypothetical test, some potential results could include:\n1.  Output voltage stability for the chosen input voltages\n2.  Ability to exceed the accelerator's highest voltage ratings.\n3. Consistency between different current levels at various output voltage tests.\n\nThis exercise is a general simulation and might not reflect real-world conditions or performance specifications of an actual LA-1030/5B linear accelerator. The focus here was on demonstrating how one could analyze data from such a system, given typical components involved in linear accelerators at that time period.",
               "refusal": null,
               "role": "assistant",
               "annotations": null,
@@ -37,15 +37,15 @@
             }
           }
         ],
-        "created": 1754510052,
+        "created": 1756921225,
         "model": "llama3.2:3b-instruct-fp16",
         "object": "chat.completion",
         "service_tier": null,
         "system_fingerprint": "fp_ollama",
         "usage": {
-          "completion_tokens": 129,
+          "completion_tokens": 547,
           "prompt_tokens": 31,
-          "total_tokens": 160,
+          "total_tokens": 578,
           "completion_tokens_details": null,
           "prompt_tokens_details": null
         }

tests/integration/recordings/responses/a59d0d7c1485.json

@@ -20,15 +20,15 @@
       "__type__": "ollama._types.GenerateResponse",
       "__data__": {
         "model": "llama-guard3:1b",
-        "created_at": "2025-08-01T23:14:23.46316Z",
+        "created_at": "2025-09-03T17:38:04.367295Z",
         "done": true,
         "done_reason": "stop",
-        "total_duration": 270313833,
-        "load_duration": 71668791,
+        "total_duration": 276503250,
+        "load_duration": 125852000,
         "prompt_eval_count": 238,
-        "prompt_eval_duration": 169000000,
+        "prompt_eval_duration": 138575125,
         "eval_count": 2,
-        "eval_duration": 25000000,
+        "eval_duration": 11277208,
         "response": "safe",
         "thinking": null,
         "context": null

tests/integration/recordings/responses/a6810c23eda8.json

@@ -23,7 +23,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-04T22:55:05.992185Z",
+          "created_at": "2025-09-03T17:36:13.985194Z",
           "done": false,
           "done_reason": null,
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@@ -41,7 +41,7 @@
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tests/integration/recordings/responses/ae1c22f18ecc.json

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         "response": "I'm happy to help you with your test, but I don't see what kind of test we are testing. Could you please provide more context or clarify what kind of test you would like me to perform? Is it a programming test, a language proficiency test, or something else?",
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tests/integration/recordings/responses/ae6835cfe70e.json

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tests/integration/recordings/responses/b14ff438ca99.json

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         "response": "The official currency of Japan is the Japanese yen (\u00a5). It is abbreviated as \"JPY\" and its symbol is \u00a5. The yen is divided into 100 sen, although the sen has been officially discontinued since 1967.\n\nYou can exchange your money for yen at banks, currency exchange offices, or use ATMs to withdraw cash from an ATM. Credit cards are also widely accepted in Japan, especially among major retailers and restaurants.\n\nIt's worth noting that some businesses may not accept foreign currencies other than US dollars, so it's a good idea to have some local currency on hand when traveling to Japan.",
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tests/integration/recordings/responses/b5e3ed420986.json

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+{
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+    "method": "POST",
+    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
+    "headers": {},
+    "body": {
+      "model": "all-minilm:l6-v2",
+      "input": [
+        "What makes Python different from other languages?"
+      ],
+      "encoding_format": "float"
+    },
+    "endpoint": "/v1/embeddings",
+    "model": "all-minilm:l6-v2"
+  },
+  "response": {
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+            ],
+            "index": 0,
+            "object": "embedding"
+          }
+        ],
+        "model": "all-minilm:l6-v2",
+        "object": "list",
+        "usage": {
+          "prompt_tokens": 6,
+          "total_tokens": 6
+        }
+      }
+    },
+    "is_streaming": false
+  }
+}

tests/integration/recordings/responses/bd356b27a085.json

@@ -21,7 +21,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-07-29T23:46:35.850399Z",
+          "created_at": "2025-09-03T17:34:22.916043Z",
           "done": false,
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           "total_duration": null,
@@ -39,7 +39,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-07-29T23:46:35.89419Z",
+          "created_at": "2025-09-03T17:34:22.957379Z",
           "done": false,
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@@ -57,7 +57,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-07-29T23:46:35.938049Z",
+          "created_at": "2025-09-03T17:34:23.00029Z",
           "done": false,
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@@ -75,7 +75,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-07-29T23:46:35.980392Z",
+          "created_at": "2025-09-03T17:34:23.043332Z",
           "done": false,
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@@ -93,7 +93,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-07-29T23:46:36.023004Z",
+          "created_at": "2025-09-03T17:34:23.085324Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -111,7 +111,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-07-29T23:46:36.065467Z",
+          "created_at": "2025-09-03T17:34:23.128181Z",
           "done": false,
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@@ -129,7 +129,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-07-29T23:46:36.108189Z",
+          "created_at": "2025-09-03T17:34:23.172026Z",
           "done": false,
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@@ -147,15 +147,15 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-07-29T23:46:36.150902Z",
+          "created_at": "2025-09-03T17:34:23.216706Z",
           "done": true,
           "done_reason": "stop",
-          "total_duration": 468910417,
-          "load_duration": 93969000,
+          "total_duration": 516060000,
+          "load_duration": 127260334,
           "prompt_eval_count": 479,
-          "prompt_eval_duration": 72596750,
+          "prompt_eval_duration": 87107292,
           "eval_count": 8,
-          "eval_duration": 301590375,
+          "eval_duration": 299381042,
           "response": "",
           "thinking": null,
           "context": null

tests/integration/recordings/responses/c2199d6064db.json

@@ -0,0 +1,422 @@
+{
+  "request": {
+    "method": "POST",
+    "url": "http://0.0.0.0:11434/v1/v1/embeddings",
+    "headers": {},
+    "body": {
+      "model": "all-minilm:l6-v2",
+      "input": [
+        "This is a test file 0"
+      ],
+      "encoding_format": "float"
+    },
+    "endpoint": "/v1/embeddings",
+    "model": "all-minilm:l6-v2"
+  },
+  "response": {
+    "body": {
+      "__type__": "openai.types.create_embedding_response.CreateEmbeddingResponse",
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+}

tests/integration/recordings/responses/c9cba6f3ee38.json

@@ -20,15 +20,15 @@
       "__type__": "ollama._types.GenerateResponse",
       "__data__": {
         "model": "llama-guard3:1b",
-        "created_at": "2025-08-01T23:14:21.909783Z",
+        "created_at": "2025-09-03T17:38:03.002753Z",
         "done": true,
         "done_reason": "stop",
-        "total_duration": 311036333,
-        "load_duration": 37569542,
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         "prompt_eval_count": 219,
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-        "eval_duration": 12000000,
+        "eval_duration": 11119166,
         "response": "safe",
         "thinking": null,
         "context": null

tests/integration/recordings/responses/cb3df2a1dc22.json

@@ -1,7 +1,7 @@
 {
   "request": {
     "method": "POST",
-    "url": "http://localhost:11434/v1/v1/chat/completions",
+    "url": "http://0.0.0.0:11434/v1/v1/chat/completions",
     "headers": {},
     "body": {
       "model": "llama3.2:3b-instruct-fp16",
@@ -20,14 +20,14 @@
     "body": {
       "__type__": "openai.types.chat.chat_completion.ChatCompletion",
       "__data__": {
-        "id": "chatcmpl-877",
+        "id": "chatcmpl-271",
         "choices": [
           {
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             "message": {
-              "content": "I'm not capable of directly testing the functionality of external systems like Telemetry. However, I can provide you with some general information about creating telemetry data and offer suggestions on how to set up a basic telemetry system.\r\n\r\nTelemetry is the automatic measurement, reporting, and transmission of data from sensors or other devices. In the context of OpenAI, telemetry refers to the collection and analysis of data related to the company's products and services.\r\n\r\nTo create telemetry creation using the OpenAI APIs you would need to follow these steps:\r\n\r\n1. Register for an OpenAI account and get an access token.\r\n2. Choose the OpenAI API that you want to use (e.g., GPT-3).\r\n3. Create a new file or project in your preferred programming language or framework.\r\n4. Import the necessary libraries and modules to interact with the OpenAI API.\r\n5. Use the OpenAI API to create and send telemetry data.\r\n\r\nHere is an example of how you might create a basic telemetry system using Python and the OpenAI GPT-3 API:\r\n\r\n```python\r\nimport os\r\nimport json\r\n\r\n# Set your OpenAI access token\r\naccess_token = \"YOUR_OPENAI_ACCESS_TOKEN\"\r\n\r\n# Define the telemetry data\r\ntelemetry_data = {\r\n    \"name\": \"example-telemetry\",\r\n    \"description\": \"Example telemetry data.\r\n\r\n    # Define the telemetry metrics\r\n    \"metrics\": [\r\n        {\"key\": \"users\", \"value\": 100},\r\n        {\"key\": \" engagement\", \"value\": 20}\r\n    ]\r\n}\r\n\r\n# Convert the telemetry data to JSON\r\ntelemetry_json = json.dumps(telemetry_data)\r\n\r\n# Set the OpenAI API endpoint and headers\r\napi_endpoint = \"https://api.openai.com/v1/telemetry\"\r\nheaders = {\r\n    \"Authorization\": f\"Bearer {access_token}\",\r\n    \"Content-Type\": \"application/json\"\r\n}\r\n\r\n# Send the telemetry data to the OpenAI API\r\nimport requests\r\n\r\nresponse = requests.post(api_endpoint, headers=headers, data=telemetry_json)\r\n\r\n# Check if the request was successful\r\nif response.status_code == 200:\r\n    print(\"Telemetry data sent successfully\")\r\nelse:\r\n    print(\"Error sending telemetry data\")\r\n```\n\nPlease note that this is a basic example and you should adjust it according to your needs. Also, the specific implementation details may vary depending on the OpenAI API you're using and the programming language or framework you're working with.\r\n\r\nI hope this helps! Let me know if you have any further questions.",
+              "content": "# OpenAI Telemetry Creation Testing\n\nThis guide provides a test environment for creating and analyzing telemetries using the OpenAI API.\n\n## Prerequisites\n\n-   Python 3.8 or higher\n-   `requests` library\n-   An OpenAI API key (create an account on the [OpenAI website](https://openai.com/))\n\n## Step 1: Install Required Libraries\n\nFirst, install the required libraries by running the following command in your terminal:\n\n```bash\npip install requests\n```\n\n## Step 2: Create a Telemetry Object\n\nCreate a new Python file (e.g., `telemetry.py`) and import the required library. Define a telemetry object with the relevant data:\n\n```python\n# Import the requests library\nimport requests\n\nclass Telemetry:\n    def __init__(self, api_key):\n        \"\"\"\n        Initialize the telemetry object.\n\n        Args:\n            api_key (str): The OpenAI API key.\n        \"\"\"\n\n        self.api_key = api_key\n\n    def create_telemetry(self, id, data):\n        \"\"\"\n        Create a new telemetry entry using the OpenAI API.\n\n        Args:\n            id (str): The ID of the model or dataset.\n            data (dict): The telemetry data to be created.\n\n        Returns:\n            dict: The response from the OpenAI API.\n\n        Raises:\n            ValueError: If the request fails.\n        \"\"\"\n\n        url = f\"https://api.openai.com/v1/models/{id}/telemetry\"\n\n        headers = {\n            \"Authorization\": self.api_key,\n            \"Content-Type\": \"application/json\",\n        }\n\n        telemetry_data = {\"events\": data}\n\n        response = requests.post(url, json=telemetry_data, headers=headers)\n\n        if not response.ok:\n            raise ValueError(\"Failed to create telemetry\")\n\n        return response.json()\n```\n\n## Step 3: Usage Example\n\nHere's an example usage of the `Telemetry` class:\n\n```python\n# Create a new Telemetry object with your OpenAI API key\ntelemetry = Telemetry(\n    \"YOUR_OPENAI_API_KEY_HERE\"\n)\n\n# Define the telemetry data\ndata = {\"event\": \"example_event\"}\n\n# Create a new telemetry entry\nid = \"my_model_id\"  # Replace with your model or dataset ID\n\ntry:\n    result = telemetry.create_telemetry(id, data)\n    print(result)\nexcept ValueError as e:\n    print(e)\n```\n\nThis code creates a new `Telemetry` object, defines some sample telemetry data, and uses the `create_telemetry` method to create a new telemetry entry. The response from the OpenAI API is printed out.\n\nNote: Replace `\"YOUR_OPENAI_API_KEY_HERE\"` with your actual OpenAI API key.\n\n## Conclusion\n\nThis guide provides a basic example of how to create telemetries using the OpenAI API. You can modify the code and implement additional features as needed for your project.\n\nStay updated on our latest tutorials and guides:\n\n*   [Check out our Discord channel](link): https://discord.gg/openai-exists\n\nHappy coding!",
               "refusal": null,
               "role": "assistant",
               "annotations": null,
@@ -37,15 +37,15 @@
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         ],
-        "created": 1754510083,
+        "created": 1756921299,
         "model": "llama3.2:3b-instruct-fp16",
         "object": "chat.completion",
         "service_tier": null,
         "system_fingerprint": "fp_ollama",
         "usage": {
-          "completion_tokens": 505,
+          "completion_tokens": 633,
           "prompt_tokens": 30,
-          "total_tokens": 535,
+          "total_tokens": 663,
           "completion_tokens_details": null,
           "prompt_tokens_details": null
         }

tests/integration/recordings/responses/d0ac68cbde69.json

@@ -13,21 +13,21 @@
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         "models": [
           {
-            "model": "llama3.2:3b-instruct-fp16",
-            "name": "llama3.2:3b-instruct-fp16",
-            "digest": "195a8c01d91ec3cb1e0aad4624a51f2602c51fa7d96110f8ab5a20c84081804d",
-            "expires_at": "2025-08-18T13:47:44.262256-07:00",
-            "size": 7919570944,
-            "size_vram": 7919570944,
+            "model": "llama3.2-vision:11b",
+            "name": "llama3.2-vision:11b",
+            "digest": "6f2f9757ae97e8a3f8ea33d6adb2b11d93d9a35bef277cd2c0b1b5af8e8d0b1e",
+            "expires_at": "2025-09-03T11:51:35.966409-07:00",
+            "size": 12401209008,
+            "size_vram": 12401209008,
             "details": {
               "parent_model": "",
               "format": "gguf",
-              "family": "llama",
+              "family": "mllama",
               "families": [
-                "llama"
+                "mllama"
               ],
-              "parameter_size": "3.2B",
-              "quantization_level": "F16"
+              "parameter_size": "10.7B",
+              "quantization_level": "Q4_K_M"
             }
           }
         ]

tests/integration/recordings/responses/d4c86ac355fb.json

@@ -20,15 +20,15 @@
       "__type__": "ollama._types.GenerateResponse",
       "__data__": {
         "model": "llama-guard3:1b",
-        "created_at": "2025-08-01T23:12:54.357928Z",
+        "created_at": "2025-09-03T17:37:35.824092Z",
         "done": true,
         "done_reason": "stop",
-        "total_duration": 227148458,
-        "load_duration": 113314916,
+        "total_duration": 270017875,
+        "load_duration": 183186083,
         "prompt_eval_count": 220,
-        "prompt_eval_duration": 83000000,
+        "prompt_eval_duration": 74457250,
         "eval_count": 2,
-        "eval_duration": 27000000,
+        "eval_duration": 11684125,
         "response": "safe",
         "thinking": null,
         "context": null

tests/integration/recordings/responses/d86d4fc1eaca.json

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+    "body": {
+      "model": "all-minilm:l6-v2",
+      "input": [
+        "machine learning and artificial intelligence"
+      ],
+      "encoding_format": "float"
+    },
+    "endpoint": "/v1/embeddings",
+    "model": "all-minilm:l6-v2"
+  },
+  "response": {
+    "body": {
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+}

tests/integration/recordings/responses/dac7a32e5db9.json

@@ -20,15 +20,15 @@
       "__type__": "ollama._types.GenerateResponse",
       "__data__": {
         "model": "llama3.2:3b-instruct-fp16",
-        "created_at": "2025-07-31T17:50:00.921192644Z",
+        "created_at": "2025-09-03T17:39:36.919474Z",
         "done": true,
         "done_reason": "stop",
-        "total_duration": 2073152067,
-        "load_duration": 42902450,
+        "total_duration": 470635833,
+        "load_duration": 113755958,
         "prompt_eval_count": 23,
-        "prompt_eval_duration": 795517987,
+        "prompt_eval_duration": 67480542,
         "eval_count": 8,
-        "eval_duration": 1234259942,
+        "eval_duration": 288746541,
         "response": "The capital of France is Paris.",
         "thinking": null,
         "context": null

tests/integration/recordings/responses/dd226d71f844.json

@@ -22,7 +22,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-01T23:14:25.381208Z",
+          "created_at": "2025-09-03T17:38:05.682744Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -40,7 +40,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-01T23:14:25.441511Z",
+          "created_at": "2025-09-03T17:38:05.72605Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -58,7 +58,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-01T23:14:25.499052Z",
+          "created_at": "2025-09-03T17:38:05.770654Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -76,7 +76,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-01T23:14:25.577259Z",
+          "created_at": "2025-09-03T17:38:05.819087Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -94,7 +94,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-01T23:14:25.635016Z",
+          "created_at": "2025-09-03T17:38:05.862915Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -112,7 +112,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-01T23:14:25.68944Z",
+          "created_at": "2025-09-03T17:38:05.913209Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -130,7 +130,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-01T23:14:25.742314Z",
+          "created_at": "2025-09-03T17:38:05.951646Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -148,7 +148,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-01T23:14:25.795086Z",
+          "created_at": "2025-09-03T17:38:05.996738Z",
           "done": false,
           "done_reason": null,
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@@ -166,7 +166,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-01T23:14:25.847905Z",
+          "created_at": "2025-09-03T17:38:06.046726Z",
           "done": false,
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@@ -184,7 +184,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-01T23:14:25.898666Z",
+          "created_at": "2025-09-03T17:38:06.08508Z",
           "done": false,
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@@ -202,7 +202,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-01T23:14:25.952292Z",
+          "created_at": "2025-09-03T17:38:06.128566Z",
           "done": false,
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@@ -220,7 +220,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-01T23:14:26.001903Z",
+          "created_at": "2025-09-03T17:38:06.173309Z",
           "done": false,
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@@ -238,15 +238,15 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-01T23:14:26.053764Z",
+          "created_at": "2025-09-03T17:38:06.218818Z",
           "done": true,
           "done_reason": "stop",
-          "total_duration": 880684833,
-          "load_duration": 101945250,
+          "total_duration": 755252250,
+          "load_duration": 141479625,
           "prompt_eval_count": 402,
-          "prompt_eval_duration": 100000000,
+          "prompt_eval_duration": 76304166,
           "eval_count": 13,
-          "eval_duration": 677000000,
+          "eval_duration": 536202125,
           "response": "",
           "thinking": null,
           "context": null

tests/integration/recordings/responses/dd9e7d5913e9.json

@@ -21,7 +21,7 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-04T22:55:41.559883Z",
+          "created_at": "2025-09-03T17:36:40.972565Z",
           "done": false,
           "done_reason": null,
           "total_duration": null,
@@ -39,15 +39,15 @@
         "__type__": "ollama._types.GenerateResponse",
         "__data__": {
           "model": "llama3.2:3b-instruct-fp16",
-          "created_at": "2025-08-04T22:55:41.619829Z",
+          "created_at": "2025-09-03T17:36:41.014682Z",
           "done": true,
           "done_reason": "stop",
-          "total_duration": 915493834,
-          "load_duration": 167838417,
+          "total_duration": 693115125,
+          "load_duration": 114019375,
           "prompt_eval_count": 386,
-          "prompt_eval_duration": 683000000,
+          "prompt_eval_duration": 535931209,
           "eval_count": 2,
-          "eval_duration": 63000000,
+          "eval_duration": 42505166,
           "response": "",
           "thinking": null,
           "context": null

tests/integration/recordings/responses/decfd950646c.json

@@ -1,7 +1,7 @@
 {
   "request": {
     "method": "POST",
-    "url": "http://localhost:11434/v1/v1/chat/completions",
+    "url": "http://0.0.0.0:11434/v1/v1/chat/completions",
     "headers": {},
     "body": {
       "model": "llama3.2:3b-instruct-fp16",
@@ -44,32 +44,22 @@
       {
         "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
         "__data__": {
-          "id": "chatcmpl-620",
+          "id": "chatcmpl-202",
           "choices": [
             {
               "delta": {
-                "content": "",
+                "content": "{\"name\":\"get_weather\",\"parameters{\"key\"]=\"Tokyo\"}}",
                 "function_call": null,
                 "refusal": null,
                 "role": "assistant",
-                "tool_calls": [
-                  {
-                    "index": 0,
-                    "id": "call_490d5ur7",
-                    "function": {
-                      "arguments": "{\"city\":\"Tokyo\"}",
-                      "name": "get_weather"
-                    },
-                    "type": "function"
-                  }
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+                "tool_calls": null
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               "index": 0,
               "logprobs": null
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+          "created": 1756921363,
           "model": "llama3.2:3b-instruct-fp16",
           "object": "chat.completion.chunk",
           "service_tier": null,
@@ -80,7 +70,7 @@
       {
         "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
         "__data__": {
-          "id": "chatcmpl-620",
+          "id": "chatcmpl-202",
           "choices": [
             {
               "delta": {
@@ -90,12 +80,12 @@
                 "role": "assistant",
                 "tool_calls": null
               },
-              "finish_reason": "tool_calls",
+              "finish_reason": "stop",
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+          "created": 1756921363,
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           "object": "chat.completion.chunk",
           "service_tier": null,

tests/integration/recordings/responses/e0a6dce1d94b.json

@@ -0,0 +1,422 @@
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+    "headers": {},
+    "body": {
+      "model": "all-minilm:l6-v2",
+      "input": [
+        "This is a test file 2"
+      ],
+      "encoding_format": "float"
+    },
+    "endpoint": "/v1/embeddings",
+    "model": "all-minilm:l6-v2"
+  },
+  "response": {
+    "body": {
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+            ],
+            "index": 0,
+            "object": "embedding"
+          }
+        ],
+        "model": "all-minilm:l6-v2",
+        "object": "list",
+        "usage": {
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+          "total_tokens": 6
+        }
+      }
+    },
+    "is_streaming": false
+  }
+}

tests/integration/recordings/responses/e2c9b07709fe.json

@@ -1,7 +1,7 @@
 {
   "request": {
     "method": "POST",
-    "url": "http://localhost:11434/v1/v1/chat/completions",
+    "url": "http://0.0.0.0:11434/v1/v1/chat/completions",
     "headers": {},
     "body": {
       "model": "llama3.2:3b-instruct-fp16",
@@ -22,14 +22,14 @@
     "body": {
       "__type__": "openai.types.chat.chat_completion.ChatCompletion",
       "__data__": {
-        "id": "chatcmpl-494",
+        "id": "chatcmpl-662",
         "choices": [
           {
             "finish_reason": "length",
             "index": 0,
             "logprobs": null,
             "message": {
-              "content": "To test the OpenAI API with a temperature of 1, you can use the following Python code:\n\n```python\nimport requests\n\ndef generate_text(model_name, prompt, temperature=1):\n    # Set the API endpoint and parameters\n    url = \"https://api.openai.com/v1/models/\" + model_name + \"/generate\"\n    params = {\n        \"prompt\": prompt,\n        \"temperature\": temperature\n    }\n\n    # Send a GET request to the API\n    response =",
+              "content": "To test the prompt understanding of OpenAI's text generation capabilities, I'll simulate a conversation. \n\nYou mentioned testing the model with a temperature setting of 1. The temperature parameter in OpenAI's text models controls the diversity and coherence of generated text.\n\nA temperature of 1 is considered \"colder\" than usual, meaning the model will generate more coherent but potentially less diverse text compared to higher temperatures (e.g., 0.5 or 0.7).\n\nPlease provide a prompt for",
               "refusal": null,
               "role": "assistant",
               "annotations": null,
@@ -39,7 +39,7 @@
             }
           }
         ],
-        "created": 1754510067,
+        "created": 1756921259,
         "model": "llama3.2:3b-instruct-fp16",
         "object": "chat.completion",
         "service_tier": null,

tests/integration/recordings/responses/e96152610712.json

@@ -20,15 +20,15 @@
       "__type__": "ollama._types.GenerateResponse",
       "__data__": {
         "model": "llama-guard3:1b",
-        "created_at": "2025-08-01T23:12:51.421145Z",
+        "created_at": "2025-09-03T17:37:33.16899Z",
         "done": true,
         "done_reason": "stop",
-        "total_duration": 201670125,
-        "load_duration": 70275459,
+        "total_duration": 300698625,
+        "load_duration": 179823875,
         "prompt_eval_count": 207,
-        "prompt_eval_duration": 71000000,
+        "prompt_eval_duration": 65083666,
         "eval_count": 5,
-        "eval_duration": 58000000,
+        "eval_duration": 55216084,
         "response": "unsafe\nS2",
         "thinking": null,
         "context": null

tests/integration/recordings/responses/e9c8a0e4f0e0.json

@@ -1,7 +1,7 @@
 {
   "request": {
     "method": "POST",
-    "url": "http://localhost:11434/v1/v1/chat/completions",
+    "url": "http://0.0.0.0:11434/v1/v1/chat/completions",
     "headers": {},
     "body": {
       "model": "llama3.2:3b-instruct-fp16",
@@ -20,14 +20,14 @@
     "body": {
       "__type__": "openai.types.chat.chat_completion.ChatCompletion",
       "__data__": {
-        "id": "chatcmpl-57",
+        "id": "chatcmpl-957",
         "choices": [
           {
             "finish_reason": "stop",
             "index": 0,
             "logprobs": null,
             "message": {
-              "content": "Humans live on Earth. It is the third planet from the Sun and is the only known planet in the universe that currently supports human life.",
+              "content": "Humans live on Earth. It's a terrestrial planet in the Solar System, located in the outer reaches of the Sun's gravitational pull.",
               "refusal": null,
               "role": "assistant",
               "annotations": null,
@@ -37,15 +37,15 @@
             }
           }
         ],
-        "created": 1754081845,
+        "created": 1756921355,
         "model": "llama3.2:3b-instruct-fp16",
         "object": "chat.completion",
         "service_tier": null,
         "system_fingerprint": "fp_ollama",
         "usage": {
-          "completion_tokens": 29,
+          "completion_tokens": 28,
           "prompt_tokens": 32,
-          "total_tokens": 61,
+          "total_tokens": 60,
           "completion_tokens_details": null,
           "prompt_tokens_details": null
         }

tests/integration/recordings/responses/ed9e9b34008d.json

@@ -20,15 +20,15 @@
       "__type__": "ollama._types.GenerateResponse",
       "__data__": {
         "model": "llama3.2:3b-instruct-fp16",
-        "created_at": "2025-07-31T17:50:48.719062652Z",
+        "created_at": "2025-09-03T17:39:48.030217Z",
         "done": true,
         "done_reason": "stop",
-        "total_duration": 42572007410,
-        "load_duration": 42791399,
+        "total_duration": 9760536750,
+        "load_duration": 242188583,
         "prompt_eval_count": 26,
-        "prompt_eval_duration": 1301967184,
+        "prompt_eval_duration": 83819333,
         "eval_count": 232,
-        "eval_duration": 41226696354,
+        "eval_duration": 9434009042,
         "response": "The largest planet in our solar system is Jupiter. It is a gas giant, meaning it is primarily composed of hydrogen and helium gases. Jupiter has a diameter of approximately 142,984 kilometers (88,846 miles), which is more than 11 times the diameter of Earth.\n\nJupiter is not only the largest planet in terms of size, but also the most massive planet in our solar system, with a mass that is more than 318 times that of Earth. It has a thick atmosphere and a strong magnetic field, and is known for its distinctive banded appearance, which is caused by strong winds in the upper atmosphere.\n\nJupiter's massive size and gravitational pull have a significant impact on the surrounding space, including the orbits of nearby planets and asteroids. Its moons are also notable, with four large ones: Io, Europa, Ganymede, and Callisto, which are known as the Galilean moons due to their discovery by Galileo Galilei in 1610.\n\nJupiter is a fascinating planet that continues to be studied by astronomers and space agencies around the world, offering insights into the formation and evolution of our solar system.",
         "thinking": null,
         "context": null