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featu: support passing "extra body" throught to providers
# What does this PR do? Allows passing through extra_body parameters to inference providers. closes #2720 ## Test Plan CI and added new test
This commit is contained in:
Eric Huang
parent
80d58ab519
commit
579aa96b2c
42 changed files with 3147 additions and 202 deletions
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"created": 0,
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"object": "text_completion",
|
||||
"system_fingerprint": "fp_ollama",
|
||||
"usage": null
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.completion.Completion",
|
||||
"__data__": {
|
||||
"id": "rec-8567635651a5",
|
||||
"choices": [
|
||||
{
|
||||
"finish_reason": null,
|
||||
"index": 0,
|
||||
"logprobs": null,
|
||||
"text": " which"
|
||||
}
|
||||
],
|
||||
"created": 0,
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"object": "text_completion",
|
||||
"system_fingerprint": "fp_ollama",
|
||||
"usage": null
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.completion.Completion",
|
||||
"__data__": {
|
||||
"id": "rec-8567635651a5",
|
||||
"choices": [
|
||||
{
|
||||
"finish_reason": null,
|
||||
"index": 0,
|
||||
"logprobs": null,
|
||||
"text": " has"
|
||||
}
|
||||
],
|
||||
"created": 0,
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"object": "text_completion",
|
||||
"system_fingerprint": "fp_ollama",
|
||||
"usage": null
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.completion.Completion",
|
||||
"__data__": {
|
||||
"id": "rec-8567635651a5",
|
||||
"choices": [
|
||||
{
|
||||
"finish_reason": null,
|
||||
"index": 0,
|
||||
"logprobs": null,
|
||||
"text": " been"
|
||||
}
|
||||
],
|
||||
"created": 0,
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"object": "text_completion",
|
||||
"system_fingerprint": "fp_ollama",
|
||||
"usage": null
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.completion.Completion",
|
||||
"__data__": {
|
||||
"id": "rec-8567635651a5",
|
||||
"choices": [
|
||||
{
|
||||
"finish_reason": null,
|
||||
"index": 0,
|
||||
"logprobs": null,
|
||||
"text": " a"
|
||||
}
|
||||
],
|
||||
"created": 0,
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"object": "text_completion",
|
||||
"system_fingerprint": "fp_ollama",
|
||||
"usage": null
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.completion.Completion",
|
||||
"__data__": {
|
||||
"id": "rec-8567635651a5",
|
||||
"choices": [
|
||||
{
|
||||
"finish_reason": null,
|
||||
"index": 0,
|
||||
"logprobs": null,
|
||||
"text": " ubiquitous"
|
||||
}
|
||||
],
|
||||
"created": 0,
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"object": "text_completion",
|
||||
"system_fingerprint": "fp_ollama",
|
||||
"usage": null
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.completion.Completion",
|
||||
"__data__": {
|
||||
"id": "rec-8567635651a5",
|
||||
"choices": [
|
||||
{
|
||||
"finish_reason": null,
|
||||
"index": 0,
|
||||
"logprobs": null,
|
||||
"text": " and"
|
||||
}
|
||||
],
|
||||
"created": 0,
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"object": "text_completion",
|
||||
"system_fingerprint": "fp_ollama",
|
||||
"usage": null
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.completion.Completion",
|
||||
"__data__": {
|
||||
"id": "rec-8567635651a5",
|
||||
"choices": [
|
||||
{
|
||||
"finish_reason": "length",
|
||||
"index": 0,
|
||||
"logprobs": null,
|
||||
"text": ""
|
||||
}
|
||||
],
|
||||
"created": 0,
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"object": "text_completion",
|
||||
"system_fingerprint": "fp_ollama",
|
||||
"usage": null
|
||||
}
|
||||
}
|
||||
],
|
||||
"is_streaming": true
|
||||
},
|
||||
"id_normalization_mapping": {}
|
||||
}
|
||||
|
|
@ -0,0 +1,48 @@
|
|||
{
|
||||
"test_id": "tests/integration/inference/test_openai_completion.py::test_openai_completion_guided_choice[txt=vllm/Qwen/Qwen3-0.6B]",
|
||||
"request": {
|
||||
"method": "POST",
|
||||
"url": "http://localhost:8000/v1/v1/completions",
|
||||
"headers": {},
|
||||
"body": {
|
||||
"model": "Qwen/Qwen3-0.6B",
|
||||
"prompt": "I am feeling really sad today.",
|
||||
"stream": false
|
||||
},
|
||||
"endpoint": "/v1/completions",
|
||||
"model": "Qwen/Qwen3-0.6B"
|
||||
},
|
||||
"response": {
|
||||
"body": {
|
||||
"__type__": "openai.types.completion.Completion",
|
||||
"__data__": {
|
||||
"id": "rec-d2ba309413e8",
|
||||
"choices": [
|
||||
{
|
||||
"finish_reason": "length",
|
||||
"index": 0,
|
||||
"logprobs": null,
|
||||
"text": " I have been working on a project that I feel like I'm not doing well",
|
||||
"stop_reason": null,
|
||||
"prompt_logprobs": null
|
||||
}
|
||||
],
|
||||
"created": 0,
|
||||
"model": "Qwen/Qwen3-0.6B",
|
||||
"object": "text_completion",
|
||||
"system_fingerprint": null,
|
||||
"usage": {
|
||||
"completion_tokens": 16,
|
||||
"prompt_tokens": 7,
|
||||
"total_tokens": 23,
|
||||
"completion_tokens_details": null,
|
||||
"prompt_tokens_details": null
|
||||
},
|
||||
"service_tier": null,
|
||||
"kv_transfer_params": null
|
||||
}
|
||||
},
|
||||
"is_streaming": false
|
||||
},
|
||||
"id_normalization_mapping": {}
|
||||
}
|
||||
|
|
@ -0,0 +1,54 @@
|
|||
{
|
||||
"test_id": "tests/integration/inference/test_openai_completion.py::test_openai_completion_guided_choice[txt=vllm/Qwen/Qwen3-0.6B]",
|
||||
"request": {
|
||||
"method": "POST",
|
||||
"url": "http://localhost:8000/v1/v1/completions",
|
||||
"headers": {},
|
||||
"body": {
|
||||
"model": "Qwen/Qwen3-0.6B",
|
||||
"prompt": "I am feeling really sad today.",
|
||||
"stream": false,
|
||||
"extra_body": {
|
||||
"guided_choices": [
|
||||
"joy",
|
||||
"sadness"
|
||||
]
|
||||
}
|
||||
},
|
||||
"endpoint": "/v1/completions",
|
||||
"model": "Qwen/Qwen3-0.6B"
|
||||
},
|
||||
"response": {
|
||||
"body": {
|
||||
"__type__": "openai.types.completion.Completion",
|
||||
"__data__": {
|
||||
"id": "rec-e3727f6c749a",
|
||||
"choices": [
|
||||
{
|
||||
"finish_reason": "length",
|
||||
"index": 0,
|
||||
"logprobs": null,
|
||||
"text": " I feel that I am not good enough, and I feel like I have no",
|
||||
"stop_reason": null,
|
||||
"prompt_logprobs": null
|
||||
}
|
||||
],
|
||||
"created": 0,
|
||||
"model": "Qwen/Qwen3-0.6B",
|
||||
"object": "text_completion",
|
||||
"system_fingerprint": null,
|
||||
"usage": {
|
||||
"completion_tokens": 16,
|
||||
"prompt_tokens": 7,
|
||||
"total_tokens": 23,
|
||||
"completion_tokens_details": null,
|
||||
"prompt_tokens_details": null
|
||||
},
|
||||
"service_tier": null,
|
||||
"kv_transfer_params": null
|
||||
}
|
||||
},
|
||||
"is_streaming": false
|
||||
},
|
||||
"id_normalization_mapping": {}
|
||||
}
|
||||
|
|
@ -0,0 +1,54 @@
|
|||
{
|
||||
"test_id": "tests/integration/inference/test_openai_completion.py::test_openai_completion_guided_choice[txt=vllm/Qwen/Qwen3-0.6B]",
|
||||
"request": {
|
||||
"method": "POST",
|
||||
"url": "http://localhost:8000/v1/v1/completions",
|
||||
"headers": {},
|
||||
"body": {
|
||||
"model": "Qwen/Qwen3-0.6B",
|
||||
"prompt": "I am feeling really sad today.",
|
||||
"stream": false,
|
||||
"extra_body": {
|
||||
"guided_choice": [
|
||||
"joy",
|
||||
"sadness"
|
||||
]
|
||||
}
|
||||
},
|
||||
"endpoint": "/v1/completions",
|
||||
"model": "Qwen/Qwen3-0.6B"
|
||||
},
|
||||
"response": {
|
||||
"body": {
|
||||
"__type__": "openai.types.completion.Completion",
|
||||
"__data__": {
|
||||
"id": "rec-f02f1bfd75ad",
|
||||
"choices": [
|
||||
{
|
||||
"finish_reason": "stop",
|
||||
"index": 0,
|
||||
"logprobs": null,
|
||||
"text": "sadness",
|
||||
"stop_reason": null,
|
||||
"prompt_logprobs": null
|
||||
}
|
||||
],
|
||||
"created": 0,
|
||||
"model": "Qwen/Qwen3-0.6B",
|
||||
"object": "text_completion",
|
||||
"system_fingerprint": null,
|
||||
"usage": {
|
||||
"completion_tokens": 3,
|
||||
"prompt_tokens": 7,
|
||||
"total_tokens": 10,
|
||||
"completion_tokens_details": null,
|
||||
"prompt_tokens_details": null
|
||||
},
|
||||
"service_tier": null,
|
||||
"kv_transfer_params": null
|
||||
}
|
||||
},
|
||||
"is_streaming": false
|
||||
},
|
||||
"id_normalization_mapping": {}
|
||||
}
|
||||
|
|
@ -0,0 +1,44 @@
|
|||
{
|
||||
"test_id": "tests/integration/inference/test_openai_completion.py::test_openai_completion_non_streaming[txt=ollama/llama3.2:3b-instruct-fp16-inference:completion:sanity]",
|
||||
"request": {
|
||||
"method": "POST",
|
||||
"url": "http://0.0.0.0:11434/v1/v1/completions",
|
||||
"headers": {},
|
||||
"body": {
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"prompt": "Respond to this question and explain your answer. Complete the sentence using one word: Roses are red, violets are ",
|
||||
"stream": false
|
||||
},
|
||||
"endpoint": "/v1/completions",
|
||||
"model": "llama3.2:3b-instruct-fp16"
|
||||
},
|
||||
"response": {
|
||||
"body": {
|
||||
"__type__": "openai.types.completion.Completion",
|
||||
"__data__": {
|
||||
"id": "rec-f0f863b7a352",
|
||||
"choices": [
|
||||
{
|
||||
"finish_reason": "stop",
|
||||
"index": 0,
|
||||
"logprobs": null,
|
||||
"text": "blue.\n\nThe traditional nursery rhyme goes like this:\n\n\"Roses are red,\nViolets are blue.\"\n\nThe reason for this specific color pairing is unclear, but it's often thought to represent the poetical notion of love and relationships. The rhyme has been passed down for generations, and its origins remain a topic of debate among scholars.\n\nIn essence, \"blue\" fits the rhythm and meter of the original phrase, creating a sense of continuity and completion in the rhyming couplet."
|
||||
}
|
||||
],
|
||||
"created": 0,
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"object": "text_completion",
|
||||
"system_fingerprint": "fp_ollama",
|
||||
"usage": {
|
||||
"completion_tokens": 100,
|
||||
"prompt_tokens": 50,
|
||||
"total_tokens": 150,
|
||||
"completion_tokens_details": null,
|
||||
"prompt_tokens_details": null
|
||||
}
|
||||
}
|
||||
},
|
||||
"is_streaming": false
|
||||
},
|
||||
"id_normalization_mapping": {}
|
||||
}
|
||||
|
|
@ -223,7 +223,7 @@ def test_openai_completion_guided_choice(llama_stack_client, client_with_models,
|
|||
model=text_model_id,
|
||||
prompt=prompt,
|
||||
stream=False,
|
||||
guided_choice=["joy", "sadness"],
|
||||
extra_body={"guided_choice": ["joy", "sadness"]},
|
||||
)
|
||||
assert len(response.choices) > 0
|
||||
choice = response.choices[0]
|
||||
|
|
|
|||
|
|
@ -33,7 +33,7 @@ from llama_stack.apis.agents.openai_responses import (
|
|||
from llama_stack.apis.inference import (
|
||||
OpenAIAssistantMessageParam,
|
||||
OpenAIChatCompletionContentPartTextParam,
|
||||
OpenAIChatCompletionRequest,
|
||||
OpenAIChatCompletionRequestWithExtraBody,
|
||||
OpenAIDeveloperMessageParam,
|
||||
OpenAIJSONSchema,
|
||||
OpenAIResponseFormatJSONObject,
|
||||
|
|
@ -162,7 +162,7 @@ async def test_create_openai_response_with_string_input(openai_responses_impl, m
|
|||
chunks = [chunk async for chunk in result]
|
||||
|
||||
mock_inference_api.openai_chat_completion.assert_called_once_with(
|
||||
OpenAIChatCompletionRequest(
|
||||
OpenAIChatCompletionRequestWithExtraBody(
|
||||
model=model,
|
||||
messages=[OpenAIUserMessageParam(role="user", content="What is the capital of Ireland?", name=None)],
|
||||
response_format=None,
|
||||
|
|
|
|||
|
|
@ -13,11 +13,16 @@ import pytest
|
|||
from llama_stack.apis.inference import (
|
||||
OpenAIAssistantMessageParam,
|
||||
OpenAIChatCompletion,
|
||||
OpenAIChatCompletionRequest,
|
||||
OpenAIChatCompletionRequestWithExtraBody,
|
||||
OpenAIChoice,
|
||||
OpenAICompletion,
|
||||
OpenAICompletionChoice,
|
||||
OpenAICompletionRequestWithExtraBody,
|
||||
ToolChoice,
|
||||
)
|
||||
from llama_stack.apis.models import Model
|
||||
from llama_stack.core.routers.inference import InferenceRouter
|
||||
from llama_stack.core.routing_tables.models import ModelsRoutingTable
|
||||
from llama_stack.providers.datatypes import HealthStatus
|
||||
from llama_stack.providers.remote.inference.vllm.config import VLLMInferenceAdapterConfig
|
||||
from llama_stack.providers.remote.inference.vllm.vllm import VLLMInferenceAdapter
|
||||
|
|
@ -57,7 +62,7 @@ async def test_old_vllm_tool_choice(vllm_inference_adapter):
|
|||
mock_client_property.return_value = mock_client
|
||||
|
||||
# No tools but auto tool choice
|
||||
params = OpenAIChatCompletionRequest(
|
||||
params = OpenAIChatCompletionRequestWithExtraBody(
|
||||
model="mock-model",
|
||||
messages=[{"role": "user", "content": "test"}],
|
||||
stream=False,
|
||||
|
|
@ -173,7 +178,7 @@ async def test_openai_chat_completion_is_async(vllm_inference_adapter):
|
|||
)
|
||||
|
||||
async def do_inference():
|
||||
params = OpenAIChatCompletionRequest(
|
||||
params = OpenAIChatCompletionRequestWithExtraBody(
|
||||
model="mock-model",
|
||||
messages=[{"role": "user", "content": "one fish two fish"}],
|
||||
stream=False,
|
||||
|
|
@ -191,3 +196,148 @@ async def test_openai_chat_completion_is_async(vllm_inference_adapter):
|
|||
|
||||
assert mock_create_client.call_count == 4 # no cheating
|
||||
assert total_time < (sleep_time * 2), f"Total time taken: {total_time}s exceeded expected max"
|
||||
|
||||
|
||||
async def test_vllm_completion_extra_body():
|
||||
"""
|
||||
Test that vLLM-specific guided_choice and prompt_logprobs parameters are correctly forwarded
|
||||
via extra_body to the underlying OpenAI client through the InferenceRouter.
|
||||
"""
|
||||
# Set up the vLLM adapter
|
||||
config = VLLMInferenceAdapterConfig(url="http://mocked.localhost:12345")
|
||||
vllm_adapter = VLLMInferenceAdapter(config=config)
|
||||
vllm_adapter.__provider_id__ = "vllm"
|
||||
await vllm_adapter.initialize()
|
||||
|
||||
# Create a mock model store
|
||||
mock_model_store = AsyncMock()
|
||||
mock_model = Model(identifier="mock-model", provider_resource_id="mock-model", provider_id="vllm")
|
||||
mock_model_store.get_model.return_value = mock_model
|
||||
mock_model_store.has_model.return_value = True
|
||||
|
||||
# Create a mock dist_registry
|
||||
mock_dist_registry = MagicMock()
|
||||
mock_dist_registry.get = AsyncMock(return_value=mock_model)
|
||||
mock_dist_registry.set = AsyncMock()
|
||||
|
||||
# Set up the routing table
|
||||
routing_table = ModelsRoutingTable(
|
||||
impls_by_provider_id={"vllm": vllm_adapter},
|
||||
dist_registry=mock_dist_registry,
|
||||
policy=[],
|
||||
)
|
||||
# Inject the model store into the adapter
|
||||
vllm_adapter.model_store = routing_table
|
||||
|
||||
# Create the InferenceRouter
|
||||
router = InferenceRouter(routing_table=routing_table)
|
||||
|
||||
# Patch the OpenAI client
|
||||
with patch.object(VLLMInferenceAdapter, "client", new_callable=PropertyMock) as mock_client_property:
|
||||
mock_client = MagicMock()
|
||||
mock_client.completions.create = AsyncMock(
|
||||
return_value=OpenAICompletion(
|
||||
id="cmpl-abc123",
|
||||
created=1,
|
||||
model="mock-model",
|
||||
choices=[
|
||||
OpenAICompletionChoice(
|
||||
text="joy",
|
||||
finish_reason="stop",
|
||||
index=0,
|
||||
)
|
||||
],
|
||||
)
|
||||
)
|
||||
mock_client_property.return_value = mock_client
|
||||
|
||||
# Test with guided_choice and prompt_logprobs as extra fields
|
||||
params = OpenAICompletionRequestWithExtraBody(
|
||||
model="mock-model",
|
||||
prompt="I am feeling happy",
|
||||
stream=False,
|
||||
guided_choice=["joy", "sadness"],
|
||||
prompt_logprobs=5,
|
||||
)
|
||||
await router.openai_completion(params)
|
||||
|
||||
# Verify that the client was called with extra_body containing both parameters
|
||||
mock_client.completions.create.assert_called_once()
|
||||
call_kwargs = mock_client.completions.create.call_args.kwargs
|
||||
assert "extra_body" in call_kwargs
|
||||
assert "guided_choice" in call_kwargs["extra_body"]
|
||||
assert call_kwargs["extra_body"]["guided_choice"] == ["joy", "sadness"]
|
||||
assert "prompt_logprobs" in call_kwargs["extra_body"]
|
||||
assert call_kwargs["extra_body"]["prompt_logprobs"] == 5
|
||||
|
||||
|
||||
async def test_vllm_chat_completion_extra_body():
|
||||
"""
|
||||
Test that vLLM-specific parameters (e.g., chat_template_kwargs) are correctly forwarded
|
||||
via extra_body to the underlying OpenAI client through the InferenceRouter for chat completion.
|
||||
"""
|
||||
# Set up the vLLM adapter
|
||||
config = VLLMInferenceAdapterConfig(url="http://mocked.localhost:12345")
|
||||
vllm_adapter = VLLMInferenceAdapter(config=config)
|
||||
vllm_adapter.__provider_id__ = "vllm"
|
||||
await vllm_adapter.initialize()
|
||||
|
||||
# Create a mock model store
|
||||
mock_model_store = AsyncMock()
|
||||
mock_model = Model(identifier="mock-model", provider_resource_id="mock-model", provider_id="vllm")
|
||||
mock_model_store.get_model.return_value = mock_model
|
||||
mock_model_store.has_model.return_value = True
|
||||
|
||||
# Create a mock dist_registry
|
||||
mock_dist_registry = MagicMock()
|
||||
mock_dist_registry.get = AsyncMock(return_value=mock_model)
|
||||
mock_dist_registry.set = AsyncMock()
|
||||
|
||||
# Set up the routing table
|
||||
routing_table = ModelsRoutingTable(
|
||||
impls_by_provider_id={"vllm": vllm_adapter},
|
||||
dist_registry=mock_dist_registry,
|
||||
policy=[],
|
||||
)
|
||||
# Inject the model store into the adapter
|
||||
vllm_adapter.model_store = routing_table
|
||||
|
||||
# Create the InferenceRouter
|
||||
router = InferenceRouter(routing_table=routing_table)
|
||||
|
||||
# Patch the OpenAI client
|
||||
with patch.object(VLLMInferenceAdapter, "client", new_callable=PropertyMock) as mock_client_property:
|
||||
mock_client = MagicMock()
|
||||
mock_client.chat.completions.create = AsyncMock(
|
||||
return_value=OpenAIChatCompletion(
|
||||
id="chatcmpl-abc123",
|
||||
created=1,
|
||||
model="mock-model",
|
||||
choices=[
|
||||
OpenAIChoice(
|
||||
message=OpenAIAssistantMessageParam(
|
||||
content="test response",
|
||||
),
|
||||
finish_reason="stop",
|
||||
index=0,
|
||||
)
|
||||
],
|
||||
)
|
||||
)
|
||||
mock_client_property.return_value = mock_client
|
||||
|
||||
# Test with chat_template_kwargs as extra field
|
||||
params = OpenAIChatCompletionRequestWithExtraBody(
|
||||
model="mock-model",
|
||||
messages=[{"role": "user", "content": "test"}],
|
||||
stream=False,
|
||||
chat_template_kwargs={"thinking": True},
|
||||
)
|
||||
await router.openai_chat_completion(params)
|
||||
|
||||
# Verify that the client was called with extra_body containing chat_template_kwargs
|
||||
mock_client.chat.completions.create.assert_called_once()
|
||||
call_kwargs = mock_client.chat.completions.create.call_args.kwargs
|
||||
assert "extra_body" in call_kwargs
|
||||
assert "chat_template_kwargs" in call_kwargs["extra_body"]
|
||||
assert call_kwargs["extra_body"]["chat_template_kwargs"] == {"thinking": True}
|
||||
|
|
|
|||
|
|
@ -12,7 +12,7 @@ from unittest.mock import AsyncMock, MagicMock, Mock, PropertyMock, patch
|
|||
import pytest
|
||||
from pydantic import BaseModel, Field
|
||||
|
||||
from llama_stack.apis.inference import Model, OpenAIChatCompletionRequest, OpenAIUserMessageParam
|
||||
from llama_stack.apis.inference import Model, OpenAIChatCompletionRequestWithExtraBody, OpenAIUserMessageParam
|
||||
from llama_stack.apis.models import ModelType
|
||||
from llama_stack.core.request_headers import request_provider_data_context
|
||||
from llama_stack.providers.utils.inference.model_registry import RemoteInferenceProviderConfig
|
||||
|
|
@ -271,7 +271,7 @@ class TestOpenAIMixinImagePreprocessing:
|
|||
with patch("llama_stack.providers.utils.inference.openai_mixin.localize_image_content") as mock_localize:
|
||||
mock_localize.return_value = (b"fake_image_data", "jpeg")
|
||||
|
||||
params = OpenAIChatCompletionRequest(model="test-model", messages=[message])
|
||||
params = OpenAIChatCompletionRequestWithExtraBody(model="test-model", messages=[message])
|
||||
await mixin.openai_chat_completion(params)
|
||||
|
||||
mock_localize.assert_called_once_with("http://example.com/image.jpg")
|
||||
|
|
@ -304,7 +304,7 @@ class TestOpenAIMixinImagePreprocessing:
|
|||
|
||||
with patch.object(type(mixin), "client", new_callable=PropertyMock, return_value=mock_client):
|
||||
with patch("llama_stack.providers.utils.inference.openai_mixin.localize_image_content") as mock_localize:
|
||||
params = OpenAIChatCompletionRequest(model="test-model", messages=[message])
|
||||
params = OpenAIChatCompletionRequestWithExtraBody(model="test-model", messages=[message])
|
||||
await mixin.openai_chat_completion(params)
|
||||
|
||||
mock_localize.assert_not_called()
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue