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https://git.datalinker.icu/vllm-project/vllm.git
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[gpt-oss] Support streaming in response API (#22431)
Signed-off-by: Chen Zhang <zhangch99@outlook.com>
This commit is contained in:
Chen Zhang
GitHub
parent
458e74eb90
commit
95a935fc48
@ -2,6 +2,7 @@
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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import asyncio
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import json
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import time
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from collections.abc import AsyncGenerator, AsyncIterator
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from contextlib import AsyncExitStack
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@ -10,10 +11,22 @@ from http import HTTPStatus
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from typing import Any, Callable, Final, Optional, Union
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import jinja2
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import openai.types.responses as openai_responses_types
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from fastapi import Request
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from openai.types.responses import (ResponseFunctionToolCall,
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ResponseOutputItem, ResponseOutputMessage,
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ResponseOutputText, ResponseReasoningItem)
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from openai import BaseModel
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# yapf conflicts with isort for this block
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# yapf: disable
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from openai.types.responses import (ResponseContentPartDoneEvent,
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ResponseCreatedEvent,
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ResponseFunctionToolCall,
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ResponseInProgressEvent,
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ResponseOutputItem,
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ResponseOutputItemDoneEvent,
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ResponseOutputMessage, ResponseOutputText,
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ResponseReasoningItem,
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ResponseReasoningTextDeltaEvent,
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ResponseReasoningTextDoneEvent)
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# yapf: enable
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from openai.types.responses.response_reasoning_item import (
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Content as ResponseReasoningTextContent)
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from openai_harmony import Message as OpenAIHarmonyMessage
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@ -330,8 +343,15 @@ class OpenAIServingResponses(OpenAIServing):
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return response
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if request.stream:
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raise NotImplementedError(
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"Streaming responses are not supported")
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return self.responses_stream_generator(
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request,
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sampling_params,
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result_generator,
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context,
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model_name,
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tokenizer,
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request_metadata,
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)
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try:
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return await self.responses_full_generator(
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@ -744,3 +764,423 @@ class OpenAIServingResponses(OpenAIServing):
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"starting the vLLM server."),
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status_code=HTTPStatus.BAD_REQUEST,
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)
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async def responses_stream_generator(
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self,
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request: ResponsesRequest,
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sampling_params: SamplingParams,
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result_generator: AsyncIterator[Optional[ConversationContext]],
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context: ConversationContext,
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model_name: str,
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tokenizer: AnyTokenizer,
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request_metadata: RequestResponseMetadata,
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created_time: Optional[int] = None,
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) -> AsyncGenerator[str, None]:
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# TODO:
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# 1. Handle disconnect
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if not isinstance(context, StreamingHarmonyContext):
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raise NotImplementedError(
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"Streaming is not supported for responses API without Harmony."
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)
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created_time = created_time or int(time.time())
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sequence_number = 0
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def _send_event(event: BaseModel):
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nonlocal sequence_number
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# Set sequence_number if the event has this attribute
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if hasattr(event, 'sequence_number'):
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event.sequence_number = sequence_number
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sequence_number += 1
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# Get event type from the event's type field if it exists
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event_type = getattr(event, 'type', 'unknown')
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return (f"event: {event_type}\n"
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f"data: {event.model_dump_json(indent=None)}\n\n")
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current_content_index = 0 # FIXME: this number is never changed
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current_output_index = 0
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current_item_id = "" # FIXME: this number is never changed
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sent_output_item_added = False
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initial_response = ResponsesResponse.from_request(
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request,
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sampling_params,
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model_name=model_name,
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created_time=created_time,
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output=[],
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status="in_progress",
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usage=None,
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).model_dump()
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yield _send_event(
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ResponseCreatedEvent(
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type="response.created",
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sequence_number=-1,
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response=initial_response,
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))
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yield _send_event(
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ResponseInProgressEvent(
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type="response.in_progress",
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sequence_number=-1,
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response=initial_response,
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))
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async for ctx in result_generator:
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assert isinstance(ctx, StreamingHarmonyContext)
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if ctx.is_expecting_start():
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current_output_index += 1
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sent_output_item_added = False
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if len(ctx.parser.messages) > 0:
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previous_item = ctx.parser.messages[-1]
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if previous_item.recipient is not None:
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# Deal with tool call here
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pass
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elif previous_item.channel == "analysis":
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reasoning_item = ResponseReasoningItem(
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type="reasoning",
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content=[
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ResponseReasoningTextContent(
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text=previous_item.content[0].text),
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],
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status="completed",
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)
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yield _send_event(
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ResponseReasoningTextDoneEvent(
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type="response.reasoning_text.done",
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item_id=current_item_id,
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sequence_number=-1,
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output_index=current_output_index,
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content_index=current_content_index,
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text=previous_item.content[0].text,
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))
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yield _send_event(
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ResponseContentPartDoneEvent(
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type="response.content_part.done",
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item_id=current_item_id,
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sequence_number=-1,
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output_index=current_output_index,
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content_index=current_content_index,
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part=reasoning_item,
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))
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yield _send_event(
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ResponseOutputItemDoneEvent(
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type="response.output_item.done",
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sequence_number=-1,
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output_index=current_output_index,
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item=reasoning_item,
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))
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elif previous_item.channel == "final":
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text_content = ResponseOutputText(
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type="output_text",
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text=previous_item.content[0].text,
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annotations=[],
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)
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yield _send_event(
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openai_responses_types.ResponseTextDoneEvent(
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type="response.output_text.done",
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sequence_number=-1,
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output_index=current_output_index,
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content_index=current_content_index,
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text=previous_item.content[0].text,
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logprobs=[],
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item_id=current_item_id,
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))
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yield _send_event(
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openai_responses_types.
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ResponseContentPartDoneEvent(
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type="response.content_part.done",
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sequence_number=-1,
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item_id=current_item_id,
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output_index=current_output_index,
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content_index=current_content_index,
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part=text_content,
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))
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yield _send_event(
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openai_responses_types.ResponseOutputItemDoneEvent(
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type="response.output_item.done",
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sequence_number=-1,
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output_index=current_output_index,
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item=ResponseOutputMessage(
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id=current_item_id,
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type="message",
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role="assistant",
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content=[text_content],
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status="completed",
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),
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))
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if ctx.parser.last_content_delta:
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if (ctx.parser.current_channel == "final"
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and ctx.parser.current_recipient is None):
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if not sent_output_item_added:
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sent_output_item_added = True
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yield _send_event(
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openai_responses_types.
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ResponseOutputItemAddedEvent(
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type="response.output_item.added",
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sequence_number=-1,
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output_index=current_output_index,
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item=openai_responses_types.
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ResponseOutputMessage(
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id=current_item_id,
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type="message",
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role="assistant",
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content=[],
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status="in_progress",
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),
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))
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yield _send_event(
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openai_responses_types.
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ResponseContentPartAddedEvent(
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type="response.content_part.added",
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sequence_number=-1,
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output_index=current_output_index,
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item_id=current_item_id,
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content_index=current_content_index,
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part=openai_responses_types.ResponseOutputText(
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type="output_text",
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text="",
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annotations=[],
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logprobs=[],
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),
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))
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yield _send_event(
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openai_responses_types.ResponseTextDeltaEvent(
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type="response.output_text.delta",
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sequence_number=-1,
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content_index=current_content_index,
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output_index=current_output_index,
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item_id=current_item_id,
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delta=ctx.parser.last_content_delta,
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# TODO, use logprobs from ctx.last_request_output
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logprobs=[],
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))
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elif (ctx.parser.current_channel == "analysis"
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and ctx.parser.current_recipient is None):
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if not sent_output_item_added:
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sent_output_item_added = True
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yield _send_event(
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openai_responses_types.
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ResponseOutputItemAddedEvent(
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type="response.output_item.added",
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sequence_number=-1,
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output_index=current_output_index,
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item=openai_responses_types.
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ResponseReasoningItem(
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type="reasoning",
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id=current_item_id,
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summary=[],
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status="in_progress",
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),
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))
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yield _send_event(
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openai_responses_types.
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ResponseContentPartAddedEvent(
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type="response.content_part.added",
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sequence_number=-1,
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output_index=current_output_index,
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item_id=current_item_id,
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content_index=current_content_index,
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part=openai_responses_types.ResponseOutputText(
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type="output_text",
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text="",
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annotations=[],
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logprobs=[],
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),
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))
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yield _send_event(
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ResponseReasoningTextDeltaEvent(
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type="response.reasoning_text.delta",
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item_id=current_item_id,
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output_index=current_output_index,
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content_index=current_content_index,
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delta=ctx.parser.last_content_delta,
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sequence_number=-1,
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))
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if ctx.is_assistant_action_turn() and len(ctx.parser.messages) > 0:
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previous_item = ctx.parser.messages[-1]
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if (self.tool_server is not None
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and self.tool_server.has_tool("browser")
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and previous_item.recipient is not None
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and previous_item.recipient.startswith("browser.")):
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function_name = previous_item.recipient[len("browser."):]
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action = None
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parsed_args = json.loads(previous_item.content[0].text)
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if function_name == "search":
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action = (openai_responses_types.
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response_function_web_search.ActionSearch(
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type="search",
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query=parsed_args["query"],
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))
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elif function_name == "open":
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action = (
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openai_responses_types.
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response_function_web_search.ActionOpenPage(
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type="open_page",
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# TODO: translate to url
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url=f"cursor:{parsed_args.get('cursor', '')}",
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))
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elif function_name == "find":
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action = (
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openai_responses_types.
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response_function_web_search.ActionFind(
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type="find",
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pattern=parsed_args["pattern"],
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# TODO: translate to url
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url=f"cursor:{parsed_args.get('cursor', '')}",
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))
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else:
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raise ValueError(
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f"Unknown function name: {function_name}")
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yield _send_event(
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openai_responses_types.ResponseOutputItemAddedEvent(
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type="response.output_item.added",
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sequence_number=-1,
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output_index=current_output_index,
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item=openai_responses_types.
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response_function_web_search.
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ResponseFunctionWebSearch(
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# TODO: generate a unique id for web search call
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type="web_search_call",
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id=current_item_id,
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action=action,
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status="in_progress",
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),
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))
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yield _send_event(
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openai_responses_types.
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ResponseWebSearchCallInProgressEvent(
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type="response.web_search_call.in_progress",
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sequence_number=-1,
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output_index=current_output_index,
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item_id=current_item_id,
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))
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yield _send_event(
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openai_responses_types.
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ResponseWebSearchCallSearchingEvent(
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type="response.web_search_call.searching",
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sequence_number=-1,
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output_index=current_output_index,
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item_id=current_item_id,
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))
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# enqueue
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yield _send_event(
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openai_responses_types.
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ResponseWebSearchCallCompletedEvent(
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type="response.web_search_call.completed",
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sequence_number=-1,
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output_index=current_output_index,
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item_id=current_item_id,
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))
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yield _send_event(
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openai_responses_types.ResponseOutputItemDoneEvent(
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type="response.output_item.done",
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sequence_number=-1,
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output_index=current_output_index,
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item=openai_responses_types.
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ResponseFunctionWebSearch(
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type="web_search_call",
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id=current_item_id,
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action=action,
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status="completed",
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),
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))
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if (self.tool_server is not None
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and self.tool_server.has_tool("python")
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and previous_item.recipient is not None
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and previous_item.recipient.startswith("python")):
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yield _send_event(
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openai_responses_types.ResponseOutputItemAddedEvent(
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type="response.output_item.added",
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sequence_number=-1,
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output_index=current_output_index,
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item=openai_responses_types.
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ResponseCodeInterpreterToolCallParam(
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type="code_interpreter_call",
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id=current_item_id,
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code="",
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container_id="auto",
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outputs=[],
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status="in_progress",
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),
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))
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yield _send_event(
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openai_responses_types.
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ResponseCodeInterpreterCallInProgressEvent(
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type="response.code_interpreter_call.in_progress",
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sequence_number=-1,
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output_index=current_output_index,
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item_id=current_item_id,
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))
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# TODO: do we need to add delta event here?
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yield _send_event(
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openai_responses_types.
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ResponseCodeInterpreterCallCodeDoneEvent(
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type="response.code_interpreter_call_code.done",
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sequence_number=-1,
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output_index=current_output_index,
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item_id=current_item_id,
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code=previous_item.content[0].text))
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yield _send_event(
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openai_responses_types.
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ResponseCodeInterpreterCallInterpretingEvent(
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type="response.code_interpreter_call.interpreting",
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sequence_number=-1,
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output_index=current_output_index,
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item_id=current_item_id,
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))
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yield _send_event(
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openai_responses_types.
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ResponseCodeInterpreterCallCompletedEvent(
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type="response.code_interpreter_call.completed",
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sequence_number=-1,
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output_index=current_output_index,
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item_id=current_item_id,
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))
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yield _send_event(
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openai_responses_types.ResponseOutputItemDoneEvent(
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type="response.output_item.done",
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sequence_number=-1,
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output_index=current_output_index,
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item=openai_responses_types.
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ResponseCodeInterpreterToolCallParam(
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type="code_interpreter_call",
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id=current_item_id,
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code=previous_item.content[0].text,
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container_id="auto",
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# TODO: add outputs here
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outputs=[],
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status="completed",
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),
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))
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async def empty_async_generator():
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# A hack to trick Python to think this is a generator but in fact
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# it immediately returns.
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if False:
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yield
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final_response = await self.responses_full_generator(
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request,
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sampling_params,
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empty_async_generator(),
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context,
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model_name,
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tokenizer,
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request_metadata,
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created_time=created_time,
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)
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yield _send_event(
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openai_responses_types.ResponseCompletedEvent(
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type="response.completed",
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sequence_number=-1,
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response=final_response.model_dump(),
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))
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