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featu: support passing "extra body" throught to providers

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# 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 2025-10-10 15:42:51 -07:00
parent cb7fb0705b
commit 0ed59497bc
35 changed files with 1893 additions and 200 deletions
Download patch file Download diff file Expand all files Collapse all files

23
docs/static/deprecated-llama-stack-spec.html vendored
View file

@ -1527,7 +1527,7 @@
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/OpenAIChatCompletionRequest"
"$ref": "#/components/schemas/OpenAIChatCompletionRequestWithExtraBody"
}
}
},
@ -1617,7 +1617,7 @@
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/OpenAICompletionRequest"
"$ref": "#/components/schemas/OpenAICompletionRequestWithExtraBody"
}
}
},
@ -7522,7 +7522,7 @@
"title": "OpenAIResponseFormatText",
"description": "Text response format for OpenAI-compatible chat completion requests."
},
"OpenAIChatCompletionRequest": {
"OpenAIChatCompletionRequestWithExtraBody": {
"type": "object",
"properties": {
"model": {
@ -7769,7 +7769,7 @@
"model",
"messages"
],
"title": "OpenAIChatCompletionRequest",
"title": "OpenAIChatCompletionRequestWithExtraBody",
"description": "Request parameters for OpenAI-compatible chat completion endpoint."
},
"OpenAIChatCompletion": {
@ -7966,7 +7966,7 @@
],
"title": "OpenAICompletionWithInputMessages"
},
"OpenAICompletionRequest": {
"OpenAICompletionRequestWithExtraBody": {
"type": "object",
"properties": {
"model": {
@ -8097,17 +8097,6 @@
"type": "string",
"description": "(Optional) The user to use."
},
"guided_choice": {
"type": "array",
"items": {
"type": "string"
},
"description": "(Optional) vLLM-specific parameter for guided generation with a list of choices."
},
"prompt_logprobs": {
"type": "integer",
"description": "(Optional) vLLM-specific parameter for number of log probabilities to return for prompt tokens."
},
"suffix": {
"type": "string",
"description": "(Optional) The suffix that should be appended to the completion."
@ -8118,7 +8107,7 @@
"model",
"prompt"
],
"title": "OpenAICompletionRequest",
"title": "OpenAICompletionRequestWithExtraBody",
"description": "Request parameters for OpenAI-compatible completion endpoint."
},
"OpenAICompletion": {

24
docs/static/deprecated-llama-stack-spec.yaml vendored
View file

@ -1098,7 +1098,7 @@ paths:
content:
application/json:
schema:
$ref: '#/components/schemas/OpenAIChatCompletionRequest'
$ref: '#/components/schemas/OpenAIChatCompletionRequestWithExtraBody'
required: true
deprecated: true
/v1/openai/v1/chat/completions/{completion_id}:
@ -1167,7 +1167,7 @@ paths:
content:
application/json:
schema:
$ref: '#/components/schemas/OpenAICompletionRequest'
$ref: '#/components/schemas/OpenAICompletionRequestWithExtraBody'
required: true
deprecated: true
/v1/openai/v1/embeddings:
@ -5575,7 +5575,7 @@ components:
title: OpenAIResponseFormatText
description: >-
Text response format for OpenAI-compatible chat completion requests.
OpenAIChatCompletionRequest:
OpenAIChatCompletionRequestWithExtraBody:
type: object
properties:
model:
@ -5717,7 +5717,7 @@ components:
required:
- model
- messages
title: OpenAIChatCompletionRequest
title: OpenAIChatCompletionRequestWithExtraBody
description: >-
Request parameters for OpenAI-compatible chat completion endpoint.
OpenAIChatCompletion:
@ -5885,7 +5885,7 @@ components:
- model
- input_messages
title: OpenAICompletionWithInputMessages
OpenAICompletionRequest:
OpenAICompletionRequestWithExtraBody:
type: object
properties:
model:
@ -5973,18 +5973,6 @@ components:
user:
type: string
description: (Optional) The user to use.
guided_choice:
type: array
items:
type: string
description: >-
(Optional) vLLM-specific parameter for guided generation with a list of
choices.
prompt_logprobs:
type: integer
description: >-
(Optional) vLLM-specific parameter for number of log probabilities to
return for prompt tokens.
suffix:
type: string
description: >-
@ -5993,7 +5981,7 @@ components:
required:
- model
- prompt
title: OpenAICompletionRequest
title: OpenAICompletionRequestWithExtraBody
description: >-
Request parameters for OpenAI-compatible completion endpoint.
OpenAICompletion:

23
docs/static/llama-stack-spec.html vendored
View file

@ -153,7 +153,7 @@
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/OpenAIChatCompletionRequest"
"$ref": "#/components/schemas/OpenAIChatCompletionRequestWithExtraBody"
}
}
},
@ -243,7 +243,7 @@
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/OpenAICompletionRequest"
"$ref": "#/components/schemas/OpenAICompletionRequestWithExtraBody"
}
}
},
@ -5018,7 +5018,7 @@
"title": "OpenAIResponseFormatText",
"description": "Text response format for OpenAI-compatible chat completion requests."
},
"OpenAIChatCompletionRequest": {
"OpenAIChatCompletionRequestWithExtraBody": {
"type": "object",
"properties": {
"model": {
@ -5265,7 +5265,7 @@
"model",
"messages"
],
"title": "OpenAIChatCompletionRequest",
"title": "OpenAIChatCompletionRequestWithExtraBody",
"description": "Request parameters for OpenAI-compatible chat completion endpoint."
},
"OpenAIChatCompletion": {
@ -5462,7 +5462,7 @@
],
"title": "OpenAICompletionWithInputMessages"
},
"OpenAICompletionRequest": {
"OpenAICompletionRequestWithExtraBody": {
"type": "object",
"properties": {
"model": {
@ -5593,17 +5593,6 @@
"type": "string",
"description": "(Optional) The user to use."
},
"guided_choice": {
"type": "array",
"items": {
"type": "string"
},
"description": "(Optional) vLLM-specific parameter for guided generation with a list of choices."
},
"prompt_logprobs": {
"type": "integer",
"description": "(Optional) vLLM-specific parameter for number of log probabilities to return for prompt tokens."
},
"suffix": {
"type": "string",
"description": "(Optional) The suffix that should be appended to the completion."
@ -5614,7 +5603,7 @@
"model",
"prompt"
],
"title": "OpenAICompletionRequest",
"title": "OpenAICompletionRequestWithExtraBody",
"description": "Request parameters for OpenAI-compatible completion endpoint."
},
"OpenAICompletion": {

24
docs/static/llama-stack-spec.yaml vendored
View file

@ -98,7 +98,7 @@ paths:
content:
application/json:
schema:
$ref: '#/components/schemas/OpenAIChatCompletionRequest'
$ref: '#/components/schemas/OpenAIChatCompletionRequestWithExtraBody'
required: true
deprecated: false
/v1/chat/completions/{completion_id}:
@ -167,7 +167,7 @@ paths:
content:
application/json:
schema:
$ref: '#/components/schemas/OpenAICompletionRequest'
$ref: '#/components/schemas/OpenAICompletionRequestWithExtraBody'
required: true
deprecated: false
/v1/conversations:
@ -3824,7 +3824,7 @@ components:
title: OpenAIResponseFormatText
description: >-
Text response format for OpenAI-compatible chat completion requests.
OpenAIChatCompletionRequest:
OpenAIChatCompletionRequestWithExtraBody:
type: object
properties:
model:
@ -3966,7 +3966,7 @@ components:
required:
- model
- messages
title: OpenAIChatCompletionRequest
title: OpenAIChatCompletionRequestWithExtraBody
description: >-
Request parameters for OpenAI-compatible chat completion endpoint.
OpenAIChatCompletion:
@ -4134,7 +4134,7 @@ components:
- model
- input_messages
title: OpenAICompletionWithInputMessages
OpenAICompletionRequest:
OpenAICompletionRequestWithExtraBody:
type: object
properties:
model:
@ -4222,18 +4222,6 @@ components:
user:
type: string
description: (Optional) The user to use.
guided_choice:
type: array
items:
type: string
description: >-
(Optional) vLLM-specific parameter for guided generation with a list of
choices.
prompt_logprobs:
type: integer
description: >-
(Optional) vLLM-specific parameter for number of log probabilities to
return for prompt tokens.
suffix:
type: string
description: >-
@ -4242,7 +4230,7 @@ components:
required:
- model
- prompt
title: OpenAICompletionRequest
title: OpenAICompletionRequestWithExtraBody
description: >-
Request parameters for OpenAI-compatible completion endpoint.
OpenAICompletion:

23
docs/static/stainless-llama-stack-spec.html vendored
View file

@ -153,7 +153,7 @@
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/OpenAIChatCompletionRequest"
"$ref": "#/components/schemas/OpenAIChatCompletionRequestWithExtraBody"
}
}
},
@ -243,7 +243,7 @@
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/OpenAICompletionRequest"
"$ref": "#/components/schemas/OpenAICompletionRequestWithExtraBody"
}
}
},
@ -7027,7 +7027,7 @@
"title": "OpenAIResponseFormatText",
"description": "Text response format for OpenAI-compatible chat completion requests."
},
"OpenAIChatCompletionRequest": {
"OpenAIChatCompletionRequestWithExtraBody": {
"type": "object",
"properties": {
"model": {
@ -7274,7 +7274,7 @@
"model",
"messages"
],
"title": "OpenAIChatCompletionRequest",
"title": "OpenAIChatCompletionRequestWithExtraBody",
"description": "Request parameters for OpenAI-compatible chat completion endpoint."
},
"OpenAIChatCompletion": {
@ -7471,7 +7471,7 @@
],
"title": "OpenAICompletionWithInputMessages"
},
"OpenAICompletionRequest": {
"OpenAICompletionRequestWithExtraBody": {
"type": "object",
"properties": {
"model": {
@ -7602,17 +7602,6 @@
"type": "string",
"description": "(Optional) The user to use."
},
"guided_choice": {
"type": "array",
"items": {
"type": "string"
},
"description": "(Optional) vLLM-specific parameter for guided generation with a list of choices."
},
"prompt_logprobs": {
"type": "integer",
"description": "(Optional) vLLM-specific parameter for number of log probabilities to return for prompt tokens."
},
"suffix": {
"type": "string",
"description": "(Optional) The suffix that should be appended to the completion."
@ -7623,7 +7612,7 @@
"model",
"prompt"
],
"title": "OpenAICompletionRequest",
"title": "OpenAICompletionRequestWithExtraBody",
"description": "Request parameters for OpenAI-compatible completion endpoint."
},
"OpenAICompletion": {

24
docs/static/stainless-llama-stack-spec.yaml vendored
View file

@ -101,7 +101,7 @@ paths:
content:
application/json:
schema:
$ref: '#/components/schemas/OpenAIChatCompletionRequest'
$ref: '#/components/schemas/OpenAIChatCompletionRequestWithExtraBody'
required: true
deprecated: false
/v1/chat/completions/{completion_id}:
@ -170,7 +170,7 @@ paths:
content:
application/json:
schema:
$ref: '#/components/schemas/OpenAICompletionRequest'
$ref: '#/components/schemas/OpenAICompletionRequestWithExtraBody'
required: true
deprecated: false
/v1/conversations:
@ -5269,7 +5269,7 @@ components:
title: OpenAIResponseFormatText
description: >-
Text response format for OpenAI-compatible chat completion requests.
OpenAIChatCompletionRequest:
OpenAIChatCompletionRequestWithExtraBody:
type: object
properties:
model:
@ -5411,7 +5411,7 @@ components:
required:
- model
- messages
title: OpenAIChatCompletionRequest
title: OpenAIChatCompletionRequestWithExtraBody
description: >-
Request parameters for OpenAI-compatible chat completion endpoint.
OpenAIChatCompletion:
@ -5579,7 +5579,7 @@ components:
- model
- input_messages
title: OpenAICompletionWithInputMessages
OpenAICompletionRequest:
OpenAICompletionRequestWithExtraBody:
type: object
properties:
model:
@ -5667,18 +5667,6 @@ components:
user:
type: string
description: (Optional) The user to use.
guided_choice:
type: array
items:
type: string
description: >-
(Optional) vLLM-specific parameter for guided generation with a list of
choices.
prompt_logprobs:
type: integer
description: >-
(Optional) vLLM-specific parameter for number of log probabilities to
return for prompt tokens.
suffix:
type: string
description: >-
@ -5687,7 +5675,7 @@ components:
required:
- model
- prompt
title: OpenAICompletionRequest
title: OpenAICompletionRequestWithExtraBody
description: >-
Request parameters for OpenAI-compatible completion endpoint.
OpenAICompletion:

24
llama_stack/apis/inference/inference.py
View file

@ -15,7 +15,7 @@ from typing import (
)
from fastapi import Body
from pydantic import BaseModel, ConfigDict, Field, field_validator
from pydantic import BaseModel, Field, field_validator
from typing_extensions import TypedDict
from llama_stack.apis.common.content_types import ContentDelta, InterleavedContent
@ -1036,8 +1036,9 @@ class ListOpenAIChatCompletionResponse(BaseModel):
object: Literal["list"] = "list"
# extra_body can be accessed via .model_extra
@json_schema_type
class OpenAICompletionRequest(BaseModel):
class OpenAICompletionRequestWithExtraBody(BaseModel, extra="allow"):
"""Request parameters for OpenAI-compatible completion endpoint.
:param model: The identifier of the model to use. The model must be registered with Llama Stack and available via the /models endpoint.
@ -1058,12 +1059,8 @@ class OpenAICompletionRequest(BaseModel):
:param top_p: (Optional) The top p to use.
:param user: (Optional) The user to use.
:param suffix: (Optional) The suffix that should be appended to the completion.
:param guided_choice: (Optional) vLLM-specific parameter for guided generation with a list of choices.
:param prompt_logprobs: (Optional) vLLM-specific parameter for number of log probabilities to return for prompt tokens.
"""
model_config = ConfigDict(extra="allow")
# Standard OpenAI completion parameters
model: str
prompt: str | list[str] | list[int] | list[list[int]]
@ -1082,17 +1079,12 @@ class OpenAICompletionRequest(BaseModel):
temperature: float | None = None
top_p: float | None = None
user: str | None = None
# vLLM-specific parameters (documented here but also allowed via extra fields)
guided_choice: list[str] | None = None
prompt_logprobs: int | None = None
# for fill-in-the-middle type completion
suffix: str | None = None
# extra_body can be accessed via .model_extra
@json_schema_type
class OpenAIChatCompletionRequest(BaseModel):
class OpenAIChatCompletionRequestWithExtraBody(BaseModel, extra="allow"):
"""Request parameters for OpenAI-compatible chat completion endpoint.
:param model: The identifier of the model to use. The model must be registered with Llama Stack and available via the /models endpoint.
@ -1120,8 +1112,6 @@ class OpenAIChatCompletionRequest(BaseModel):
:param user: (Optional) The user to use.
"""
model_config = ConfigDict(extra="allow")
# Standard OpenAI chat completion parameters
model: str
messages: Annotated[list[OpenAIMessageParam], Field(..., min_length=1)]
@ -1182,7 +1172,7 @@ class InferenceProvider(Protocol):
@webmethod(route="/completions", method="POST", level=LLAMA_STACK_API_V1)
async def openai_completion(
self,
params: Annotated[OpenAICompletionRequest, Body(...)],
params: Annotated[OpenAICompletionRequestWithExtraBody, Body(...)],
) -> OpenAICompletion:
"""Create completion.
@ -1195,7 +1185,7 @@ class InferenceProvider(Protocol):
@webmethod(route="/chat/completions", method="POST", level=LLAMA_STACK_API_V1)
async def openai_chat_completion(
self,
params: Annotated[OpenAIChatCompletionRequest, Body(...)],
params: Annotated[OpenAIChatCompletionRequestWithExtraBody, Body(...)],
) -> OpenAIChatCompletion | AsyncIterator[OpenAIChatCompletionChunk]:
"""Create chat completions.

10
llama_stack/core/routers/inference.py
View file

@ -32,13 +32,13 @@ from llama_stack.apis.inference import (
OpenAIAssistantMessageParam,
OpenAIChatCompletion,
OpenAIChatCompletionChunk,
OpenAIChatCompletionRequest,
OpenAIChatCompletionRequestWithExtraBody,
OpenAIChatCompletionToolCall,
OpenAIChatCompletionToolCallFunction,
OpenAIChoice,
OpenAIChoiceLogprobs,
OpenAICompletion,
OpenAICompletionRequest,
OpenAICompletionRequestWithExtraBody,
OpenAICompletionWithInputMessages,
OpenAIEmbeddingsResponse,
OpenAIMessageParam,
@ -183,7 +183,7 @@ class InferenceRouter(Inference):
async def openai_completion(
self,
params: Annotated[OpenAICompletionRequest, Body(...)],
params: Annotated[OpenAICompletionRequestWithExtraBody, Body(...)],
) -> OpenAICompletion:
logger.debug(
f"InferenceRouter.openai_completion: model={params.model}, stream={params.stream}, prompt={params.prompt}",
@ -218,7 +218,7 @@ class InferenceRouter(Inference):
async def openai_chat_completion(
self,
params: Annotated[OpenAIChatCompletionRequest, Body(...)],
params: Annotated[OpenAIChatCompletionRequestWithExtraBody, Body(...)],
) -> OpenAIChatCompletion | AsyncIterator[OpenAIChatCompletionChunk]:
logger.debug(
f"InferenceRouter.openai_chat_completion: model={params.model}, stream={params.stream}, messages={params.messages}",
@ -317,7 +317,7 @@ class InferenceRouter(Inference):
raise NotImplementedError("Get chat completion is not supported: inference store is not configured.")
async def _nonstream_openai_chat_completion(
self, provider: Inference, params: OpenAIChatCompletionRequest
self, provider: Inference, params: OpenAIChatCompletionRequestWithExtraBody
) -> OpenAIChatCompletion:
response = await provider.openai_chat_completion(params)
for choice in response.choices:

4
llama_stack/providers/inline/agents/meta_reference/agent_instance.py
View file

@ -49,7 +49,7 @@ from llama_stack.apis.inference import (
Inference,
Message,
OpenAIAssistantMessageParam,
OpenAIChatCompletionRequest,
OpenAIChatCompletionRequestWithExtraBody,
OpenAIDeveloperMessageParam,
OpenAIMessageParam,
OpenAISystemMessageParam,
@ -583,7 +583,7 @@ class ChatAgent(ShieldRunnerMixin):
max_tokens = getattr(sampling_params, "max_tokens", None)
# Use OpenAI chat completion
params = OpenAIChatCompletionRequest(
params = OpenAIChatCompletionRequestWithExtraBody(
model=self.agent_config.model,
messages=openai_messages,
tools=openai_tools if openai_tools else None,

4
llama_stack/providers/inline/agents/meta_reference/responses/streaming.py
View file

@ -49,7 +49,7 @@ from llama_stack.apis.inference import (
OpenAIAssistantMessageParam,
OpenAIChatCompletion,
OpenAIChatCompletionChunk,
OpenAIChatCompletionRequest,
OpenAIChatCompletionRequestWithExtraBody,
OpenAIChatCompletionToolCall,
OpenAIChoice,
OpenAIMessageParam,
@ -169,7 +169,7 @@ class StreamingResponseOrchestrator:
# (some providers don't support non-empty response_format when tools are present)
response_format = None if self.ctx.response_format.type == "text" else self.ctx.response_format
logger.debug(f"calling openai_chat_completion with tools: {self.ctx.chat_tools}")
params = OpenAIChatCompletionRequest(
params = OpenAIChatCompletionRequestWithExtraBody(
model=self.ctx.model,
messages=messages,
tools=self.ctx.chat_tools,

8
llama_stack/providers/inline/batches/reference/batches.py
View file

@ -22,8 +22,8 @@ from llama_stack.apis.files import Files, OpenAIFilePurpose
from llama_stack.apis.inference import (
Inference,
OpenAIAssistantMessageParam,
OpenAIChatCompletionRequest,
OpenAICompletionRequest,
OpenAIChatCompletionRequestWithExtraBody,
OpenAICompletionRequestWithExtraBody,
OpenAIDeveloperMessageParam,
OpenAIMessageParam,
OpenAISystemMessageParam,
@ -608,7 +608,7 @@ class ReferenceBatchesImpl(Batches):
# TODO(SECURITY): review body for security issues
if request.url == "/v1/chat/completions":
request.body["messages"] = [convert_to_openai_message_param(msg) for msg in request.body["messages"]]
chat_params = OpenAIChatCompletionRequest(**request.body)
chat_params = OpenAIChatCompletionRequestWithExtraBody(**request.body)
chat_response = await self.inference_api.openai_chat_completion(chat_params)
# this is for mypy, we don't allow streaming so we'll get the right type
@ -623,7 +623,7 @@ class ReferenceBatchesImpl(Batches):
},
}
elif request.url == "/v1/completions":
completion_params = OpenAICompletionRequest(**request.body)
completion_params = OpenAICompletionRequestWithExtraBody(**request.body)
completion_response = await self.inference_api.openai_completion(completion_params)
# this is for mypy, we don't allow streaming so we'll get the right type

8
llama_stack/providers/inline/eval/meta_reference/eval.py
View file

@ -14,8 +14,8 @@ from llama_stack.apis.datasetio import DatasetIO
from llama_stack.apis.datasets import Datasets
from llama_stack.apis.inference import (
Inference,
OpenAIChatCompletionRequest,
OpenAICompletionRequest,
OpenAIChatCompletionRequestWithExtraBody,
OpenAICompletionRequestWithExtraBody,
OpenAISystemMessageParam,
OpenAIUserMessageParam,
UserMessage,
@ -175,7 +175,7 @@ class MetaReferenceEvalImpl(
sampling_params["stop"] = candidate.sampling_params.stop
input_content = json.loads(x[ColumnName.completion_input.value])
params = OpenAICompletionRequest(
params = OpenAICompletionRequestWithExtraBody(
model=candidate.model,
prompt=input_content,
**sampling_params,
@ -195,7 +195,7 @@ class MetaReferenceEvalImpl(
messages += [OpenAISystemMessageParam(**x) for x in chat_completion_input_json if x["role"] == "system"]
messages += input_messages
params = OpenAIChatCompletionRequest(
params = OpenAIChatCompletionRequestWithExtraBody(
model=candidate.model,
messages=messages,
**sampling_params,

8
llama_stack/providers/inline/inference/meta_reference/inference.py
View file

@ -9,8 +9,8 @@ from collections.abc import AsyncIterator
from llama_stack.apis.inference import (
InferenceProvider,
OpenAIChatCompletionRequest,
OpenAICompletionRequest,
OpenAIChatCompletionRequestWithExtraBody,
OpenAICompletionRequestWithExtraBody,
)
from llama_stack.apis.inference.inference import (
OpenAIChatCompletion,
@ -67,7 +67,7 @@ class MetaReferenceInferenceImpl(
async def openai_completion(
self,
params: OpenAICompletionRequest,
params: OpenAICompletionRequestWithExtraBody,
) -> OpenAICompletion:
raise NotImplementedError("OpenAI completion not supported by meta reference provider")
@ -153,6 +153,6 @@ class MetaReferenceInferenceImpl(
async def openai_chat_completion(
self,
params: OpenAIChatCompletionRequest,
params: OpenAIChatCompletionRequestWithExtraBody,
) -> OpenAIChatCompletion | AsyncIterator[OpenAIChatCompletionChunk]:
raise NotImplementedError("OpenAI chat completion not supported by meta-reference inference provider")

8
llama_stack/providers/inline/inference/sentence_transformers/sentence_transformers.py
View file

@ -8,8 +8,8 @@ from collections.abc import AsyncIterator
from llama_stack.apis.inference import (
InferenceProvider,
OpenAIChatCompletionRequest,
OpenAICompletionRequest,
OpenAIChatCompletionRequestWithExtraBody,
OpenAICompletionRequestWithExtraBody,
)
from llama_stack.apis.inference.inference import (
OpenAIChatCompletion,
@ -72,12 +72,12 @@ class SentenceTransformersInferenceImpl(
async def openai_completion(
self,
params: OpenAICompletionRequest,
params: OpenAICompletionRequestWithExtraBody,
) -> OpenAICompletion:
raise NotImplementedError("OpenAI completion not supported by sentence transformers provider")
async def openai_chat_completion(
self,
params: OpenAIChatCompletionRequest,
params: OpenAIChatCompletionRequestWithExtraBody,
) -> OpenAIChatCompletion | AsyncIterator[OpenAIChatCompletionChunk]:
raise NotImplementedError("OpenAI chat completion not supported by sentence transformers provider")

6
llama_stack/providers/inline/safety/llama_guard/llama_guard.py
View file

@ -13,7 +13,7 @@ from llama_stack.apis.common.content_types import ImageContentItem, TextContentI
from llama_stack.apis.inference import (
Inference,
Message,
OpenAIChatCompletionRequest,
OpenAIChatCompletionRequestWithExtraBody,
OpenAIUserMessageParam,
UserMessage,
)
@ -296,7 +296,7 @@ class LlamaGuardShield:
else:
shield_input_message = self.build_text_shield_input(messages)
params = OpenAIChatCompletionRequest(
params = OpenAIChatCompletionRequestWithExtraBody(
model=self.model,
messages=[shield_input_message],
stream=False,
@ -384,7 +384,7 @@ class LlamaGuardShield:
# TODO: Add Image based support for OpenAI Moderations
shield_input_message = self.build_text_shield_input(messages)
params = OpenAIChatCompletionRequest(
params = OpenAIChatCompletionRequestWithExtraBody(
model=self.model,
messages=[shield_input_message],
stream=False,

4
llama_stack/providers/inline/scoring/llm_as_judge/scoring_fn/llm_as_judge_scoring_fn.py
View file

@ -6,7 +6,7 @@
import re
from typing import Any
from llama_stack.apis.inference import Inference, OpenAIChatCompletionRequest
from llama_stack.apis.inference import Inference, OpenAIChatCompletionRequestWithExtraBody
from llama_stack.apis.scoring import ScoringResultRow
from llama_stack.apis.scoring_functions import ScoringFnParams
from llama_stack.providers.utils.scoring.base_scoring_fn import RegisteredBaseScoringFn
@ -55,7 +55,7 @@ class LlmAsJudgeScoringFn(RegisteredBaseScoringFn):
generated_answer=generated_answer,
)
params = OpenAIChatCompletionRequest(
params = OpenAIChatCompletionRequestWithExtraBody(
model=fn_def.params.judge_model,
messages=[
{

4
llama_stack/providers/inline/tool_runtime/rag/context_retriever.py
View file

@ -8,7 +8,7 @@
from jinja2 import Template
from llama_stack.apis.common.content_types import InterleavedContent
from llama_stack.apis.inference import OpenAIChatCompletionRequest, OpenAIUserMessageParam
from llama_stack.apis.inference import OpenAIChatCompletionRequestWithExtraBody, OpenAIUserMessageParam
from llama_stack.apis.tools.rag_tool import (
DefaultRAGQueryGeneratorConfig,
LLMRAGQueryGeneratorConfig,
@ -65,7 +65,7 @@ async def llm_rag_query_generator(
model = config.model
message = OpenAIUserMessageParam(content=rendered_content)
params = OpenAIChatCompletionRequest(
params = OpenAIChatCompletionRequestWithExtraBody(
model=model,
messages=[message],
stream=False,

8
llama_stack/providers/remote/inference/bedrock/bedrock.py
View file

@ -12,8 +12,8 @@ from botocore.client import BaseClient
from llama_stack.apis.inference import (
ChatCompletionRequest,
Inference,
OpenAIChatCompletionRequest,
OpenAICompletionRequest,
OpenAIChatCompletionRequestWithExtraBody,
OpenAICompletionRequestWithExtraBody,
OpenAIEmbeddingsResponse,
)
from llama_stack.apis.inference.inference import (
@ -134,12 +134,12 @@ class BedrockInferenceAdapter(
async def openai_completion(
self,
params: OpenAICompletionRequest,
params: OpenAICompletionRequestWithExtraBody,
) -> OpenAICompletion:
raise NotImplementedError("OpenAI completion not supported by the Bedrock provider")
async def openai_chat_completion(
self,
params: OpenAIChatCompletionRequest,
params: OpenAIChatCompletionRequestWithExtraBody,
) -> OpenAIChatCompletion | AsyncIterator[OpenAIChatCompletionChunk]:
raise NotImplementedError("OpenAI chat completion not supported by the Bedrock provider")

4
llama_stack/providers/remote/inference/databricks/databricks.py
View file

@ -8,7 +8,7 @@ from collections.abc import Iterable
from databricks.sdk import WorkspaceClient
from llama_stack.apis.inference import OpenAICompletion, OpenAICompletionRequest
from llama_stack.apis.inference import OpenAICompletion, OpenAICompletionRequestWithExtraBody
from llama_stack.log import get_logger
from llama_stack.providers.utils.inference.openai_mixin import OpenAIMixin
@ -39,6 +39,6 @@ class DatabricksInferenceAdapter(OpenAIMixin):
async def openai_completion(
self,
params: OpenAICompletionRequest,
params: OpenAICompletionRequestWithExtraBody,
) -> OpenAICompletion:
raise NotImplementedError()

9
llama_stack/providers/remote/inference/llama_openai_compat/llama.py
View file

@ -3,7 +3,12 @@
#
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
from llama_stack.apis.inference.inference import OpenAICompletion, OpenAICompletionRequest, OpenAIEmbeddingsResponse
from llama_stack.apis.inference.inference import (
OpenAICompletion,
OpenAICompletionRequestWithExtraBody,
OpenAIEmbeddingsResponse,
)
from llama_stack.log import get_logger
from llama_stack.providers.remote.inference.llama_openai_compat.config import LlamaCompatConfig
from llama_stack.providers.utils.inference.openai_mixin import OpenAIMixin
@ -29,7 +34,7 @@ class LlamaCompatInferenceAdapter(OpenAIMixin):
async def openai_completion(
self,
params: OpenAICompletionRequest,
params: OpenAICompletionRequestWithExtraBody,
) -> OpenAICompletion:
raise NotImplementedError()

8
llama_stack/providers/remote/inference/passthrough/passthrough.py
View file

@ -13,9 +13,9 @@ from llama_stack.apis.inference import (
Inference,
OpenAIChatCompletion,
OpenAIChatCompletionChunk,
OpenAIChatCompletionRequest,
OpenAIChatCompletionRequestWithExtraBody,
OpenAICompletion,
OpenAICompletionRequest,
OpenAICompletionRequestWithExtraBody,
OpenAIEmbeddingsResponse,
)
from llama_stack.apis.models import Model
@ -79,7 +79,7 @@ class PassthroughInferenceAdapter(Inference):
async def openai_completion(
self,
params: OpenAICompletionRequest,
params: OpenAICompletionRequestWithExtraBody,
) -> OpenAICompletion:
client = self._get_client()
model_obj = await self.model_store.get_model(params.model)
@ -93,7 +93,7 @@ class PassthroughInferenceAdapter(Inference):
async def openai_chat_completion(
self,
params: OpenAIChatCompletionRequest,
params: OpenAIChatCompletionRequestWithExtraBody,
) -> OpenAIChatCompletion | AsyncIterator[OpenAIChatCompletionChunk]:
client = self._get_client()
model_obj = await self.model_store.get_model(params.model)

4
llama_stack/providers/remote/inference/runpod/runpod.py
View file

@ -9,7 +9,7 @@ from collections.abc import AsyncIterator
from llama_stack.apis.inference import (
OpenAIChatCompletion,
OpenAIChatCompletionChunk,
OpenAIChatCompletionRequest,
OpenAIChatCompletionRequestWithExtraBody,
)
from llama_stack.providers.utils.inference.openai_mixin import OpenAIMixin
@ -31,7 +31,7 @@ class RunpodInferenceAdapter(OpenAIMixin):
async def openai_chat_completion(
self,
params: OpenAIChatCompletionRequest,
params: OpenAIChatCompletionRequestWithExtraBody,
) -> OpenAIChatCompletion | AsyncIterator[OpenAIChatCompletionChunk]:
"""Override to add RunPod-specific stream_options requirement."""
params = params.model_copy()

4
llama_stack/providers/remote/inference/vllm/vllm.py
View file

@ -14,7 +14,7 @@ from pydantic import ConfigDict
from llama_stack.apis.inference import (
OpenAIChatCompletion,
OpenAIChatCompletionRequest,
OpenAIChatCompletionRequestWithExtraBody,
ToolChoice,
)
from llama_stack.log import get_logger
@ -93,7 +93,7 @@ class VLLMInferenceAdapter(OpenAIMixin):
async def openai_chat_completion(
self,
params: OpenAIChatCompletionRequest,
params: OpenAIChatCompletionRequestWithExtraBody,
) -> OpenAIChatCompletion | AsyncIterator[OpenAIChatCompletionChunk]:
params = params.model_copy()

10
llama_stack/providers/utils/inference/litellm_openai_mixin.py
View file

@ -16,9 +16,9 @@ from llama_stack.apis.inference import (
JsonSchemaResponseFormat,
OpenAIChatCompletion,
OpenAIChatCompletionChunk,
OpenAIChatCompletionRequest,
OpenAIChatCompletionRequestWithExtraBody,
OpenAICompletion,
OpenAICompletionRequest,
OpenAICompletionRequestWithExtraBody,
OpenAIEmbeddingData,
OpenAIEmbeddingsResponse,
OpenAIEmbeddingUsage,
@ -226,7 +226,7 @@ class LiteLLMOpenAIMixin(
async def openai_completion(
self,
params: OpenAICompletionRequest,
params: OpenAICompletionRequestWithExtraBody,
) -> OpenAICompletion:
model_obj = await self.model_store.get_model(params.model)
@ -248,8 +248,6 @@ class LiteLLMOpenAIMixin(
temperature=params.temperature,
top_p=params.top_p,
user=params.user,
guided_choice=params.guided_choice,
prompt_logprobs=params.prompt_logprobs,
suffix=params.suffix,
api_key=self.get_api_key(),
api_base=self.api_base,
@ -258,7 +256,7 @@ class LiteLLMOpenAIMixin(
async def openai_chat_completion(
self,
params: OpenAIChatCompletionRequest,
params: OpenAIChatCompletionRequestWithExtraBody,
) -> OpenAIChatCompletion | AsyncIterator[OpenAIChatCompletionChunk]:
# Add usage tracking for streaming when telemetry is active
from llama_stack.providers.utils.telemetry.tracing import get_current_span

24
llama_stack/providers/utils/inference/openai_mixin.py
View file

@ -17,9 +17,9 @@ from llama_stack.apis.inference import (
Model,
OpenAIChatCompletion,
OpenAIChatCompletionChunk,
OpenAIChatCompletionRequest,
OpenAIChatCompletionRequestWithExtraBody,
OpenAICompletion,
OpenAICompletionRequest,
OpenAICompletionRequestWithExtraBody,
OpenAIEmbeddingData,
OpenAIEmbeddingsResponse,
OpenAIEmbeddingUsage,
@ -223,21 +223,11 @@ class OpenAIMixin(NeedsRequestProviderData, ABC, BaseModel):
async def openai_completion(
self,
params: OpenAICompletionRequest,
params: OpenAICompletionRequestWithExtraBody,
) -> OpenAICompletion:
"""
Direct OpenAI completion API call.
"""
# Handle parameters that are not supported by OpenAI API, but may be by the provider
# prompt_logprobs is supported by vLLM
# guided_choice is supported by vLLM
# TODO: test coverage
extra_body: dict[str, Any] = {}
if params.prompt_logprobs is not None and params.prompt_logprobs >= 0:
extra_body["prompt_logprobs"] = params.prompt_logprobs
if params.guided_choice:
extra_body["guided_choice"] = params.guided_choice
# TODO: fix openai_completion to return type compatible with OpenAI's API response
completion_kwargs = await prepare_openai_completion_params(
model=await self._get_provider_model_id(params.model),
@ -259,13 +249,15 @@ class OpenAIMixin(NeedsRequestProviderData, ABC, BaseModel):
user=params.user,
suffix=params.suffix,
)
resp = await self.client.completions.create(**completion_kwargs, extra_body=extra_body)
if extra_body := params.model_extra:
completion_kwargs["extra_body"] = extra_body
resp = await self.client.completions.create(**completion_kwargs)
return await self._maybe_overwrite_id(resp, params.stream) # type: ignore[no-any-return]
async def openai_chat_completion(
self,
params: OpenAIChatCompletionRequest,
params: OpenAIChatCompletionRequestWithExtraBody,
) -> OpenAIChatCompletion | AsyncIterator[OpenAIChatCompletionChunk]:
"""
Direct OpenAI chat completion API call.
@ -316,6 +308,8 @@ class OpenAIMixin(NeedsRequestProviderData, ABC, BaseModel):
user=params.user,
)
if extra_body := params.model_extra:
request_params["extra_body"] = extra_body
resp = await self.client.chat.completions.create(**request_params)
return await self._maybe_overwrite_id(resp, params.stream) # type: ignore[no-any-return]

881
tests/integration/common/recordings/models-64a2277c90f0f42576f60c1030e3a020403d34a95f56931b792d5939f4cebc57-9ecd9600.json Normal file
View file

@ -0,0 +1,881 @@
{
"test_id": null,
"request": {
"method": "POST",
"url": "https://api.openai.com/v1/v1/models",
"headers": {},
"body": {},
"endpoint": "/v1/models",
"model": ""
},
"response": {
"body": [
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "gpt-4-0613",
"created": 1686588896,
"object": "model",
"owned_by": "openai"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "gpt-4",
"created": 1687882411,
"object": "model",
"owned_by": "openai"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "gpt-3.5-turbo",
"created": 1677610602,
"object": "model",
"owned_by": "openai"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "sora-2-pro",
"created": 1759708663,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "gpt-audio-mini-2025-10-06",
"created": 1759512137,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "gpt-realtime-mini",
"created": 1759517133,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "gpt-realtime-mini-2025-10-06",
"created": 1759517175,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "sora-2",
"created": 1759708615,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "davinci-002",
"created": 1692634301,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "babbage-002",
"created": 1692634615,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "gpt-3.5-turbo-instruct",
"created": 1692901427,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "gpt-3.5-turbo-instruct-0914",
"created": 1694122472,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "dall-e-3",
"created": 1698785189,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "dall-e-2",
"created": 1698798177,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "gpt-4-1106-preview",
"created": 1698957206,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "gpt-3.5-turbo-1106",
"created": 1698959748,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "tts-1-hd",
"created": 1699046015,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "tts-1-1106",
"created": 1699053241,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "tts-1-hd-1106",
"created": 1699053533,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "text-embedding-3-small",
"created": 1705948997,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "text-embedding-3-large",
"created": 1705953180,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "gpt-4-0125-preview",
"created": 1706037612,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "gpt-4-turbo-preview",
"created": 1706037777,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "gpt-3.5-turbo-0125",
"created": 1706048358,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
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"created": 1712361441,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
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"created": 1712601677,
"object": "model",
"owned_by": "system"
}
},
{
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"created": 1715367049,
"object": "model",
"owned_by": "system"
}
},
{
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"__data__": {
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"created": 1715368132,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
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"created": 1721172717,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "gpt-4o-mini",
"created": 1721172741,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
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"created": 1722814719,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
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"created": 1723515131,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
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"created": 1725648979,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
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"created": 1725649008,
"object": "model",
"owned_by": "system"
}
},
{
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"created": 1727131766,
"object": "model",
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}
},
{
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"created": 1727389042,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "gpt-4o-audio-preview",
"created": 1727460443,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "gpt-4o-realtime-preview",
"created": 1727659998,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "omni-moderation-latest",
"created": 1731689265,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "omni-moderation-2024-09-26",
"created": 1732734466,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "gpt-4o-realtime-preview-2024-12-17",
"created": 1733945430,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "gpt-4o-audio-preview-2024-12-17",
"created": 1734034239,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "gpt-4o-mini-realtime-preview-2024-12-17",
"created": 1734112601,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "gpt-4o-mini-audio-preview-2024-12-17",
"created": 1734115920,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "o1-2024-12-17",
"created": 1734326976,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "o1",
"created": 1734375816,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "gpt-4o-mini-realtime-preview",
"created": 1734387380,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "gpt-4o-mini-audio-preview",
"created": 1734387424,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "o3-mini",
"created": 1737146383,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "o3-mini-2025-01-31",
"created": 1738010200,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "gpt-4o-2024-11-20",
"created": 1739331543,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "gpt-4o-search-preview-2025-03-11",
"created": 1741388170,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "gpt-4o-search-preview",
"created": 1741388720,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "gpt-4o-mini-search-preview-2025-03-11",
"created": 1741390858,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "gpt-4o-mini-search-preview",
"created": 1741391161,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "gpt-4o-transcribe",
"created": 1742068463,
"object": "model",
"owned_by": "system"
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "gpt-4o-mini-transcribe",
"created": 1742068596,
"object": "model",
"owned_by": "system"
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"__type__": "openai.types.model.Model",
"__data__": {
"id": "accounts/fireworks/models/glm-4p5",
"created": 1753809636,
"object": "model",
"owned_by": "fireworks",
"kind": "HF_BASE_MODEL",
"supports_chat": true,
"supports_image_input": false,
"supports_tools": true,
"context_length": 131072
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "accounts/fireworks/models/qwen3-coder-30b-a3b-instruct",
"created": 1754063588,
"object": "model",
"owned_by": "fireworks",
"kind": "HF_BASE_MODEL",
"supports_chat": true,
"supports_image_input": false,
"supports_tools": false,
"context_length": 262144
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "accounts/fireworks/models/deepseek-r1",
"created": 1737397673,
"object": "model",
"owned_by": "fireworks",
"kind": "HF_BASE_MODEL",
"supports_chat": true,
"supports_image_input": false,
"supports_tools": false,
"context_length": 163840
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "accounts/fireworks/models/deepseek-v3",
"created": 1735576668,
"object": "model",
"owned_by": "fireworks",
"kind": "HF_BASE_MODEL",
"supports_chat": true,
"supports_image_input": false,
"supports_tools": true,
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}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "accounts/fireworks/models/deepseek-r1-basic",
"created": 1742306746,
"object": "model",
"owned_by": "fireworks",
"kind": "HF_BASE_MODEL",
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"supports_image_input": false,
"supports_tools": false,
"context_length": 163840
}
},
{
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"__data__": {
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"object": "model",
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"kind": "HF_BASE_MODEL",
"supports_chat": true,
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"supports_tools": false,
"context_length": 262144
}
},
{
"__type__": "openai.types.model.Model",
"__data__": {
"id": "accounts/tvergho-87e44d/models/debatecards-70b-ft-3epoch-dpo-v2",
"created": 1743381121,
"object": "model",
"owned_by": "tvergho-87e44d",
"kind": "HF_PEFT_ADDON",
"supports_chat": true,
"supports_image_input": false,
"supports_tools": false
}
}
],
"is_streaming": false
},
"id_normalization_mapping": {}
}

48
tests/integration/inference/recordings/d2ba309413e85d6166f7543a879b890b4e65a5f9917a2d75c5795782ab7cbfff.json Normal file
View file

@ -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": {}
}

54
tests/integration/inference/recordings/e3727f6c749ab8bdee2f581300092002485023b937d72b7aa8d4c15c9204fc5c.json Normal file
View file

@ -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": {}
}

54
tests/integration/inference/recordings/f02f1bfd75adaea87b91dedc59430b99015b5ed0e2bbf24418a31146ffcbca9b.json Normal file
View file

@ -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": {}
}

2
tests/integration/inference/test_openai_completion.py
View file

@ -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]

4
tests/unit/providers/agents/meta_reference/test_openai_responses.py
View file

@ -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,

156
tests/unit/providers/inference/test_remote_vllm.py
View file

@ -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}

6
tests/unit/providers/utils/inference/test_openai_mixin.py
View file

@ -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()