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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
10c7e67fca
35 changed files with 1893 additions and 200 deletions
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||||
"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": {}
|
||||
}
|
||||
|
|
@ -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