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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 15:40:30 -07:00
parent cb7fb0705b
commit 9f50338a4e
35 changed files with 1892 additions and 199 deletions
Download patch file Download diff file Expand all files Collapse all files

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,