refactor: extract OpenAI Responses route wrapper
Keep app.main.v1_responses as the compatibility entrypoint while moving the Responses wrapper and SSE bridge into a dedicated module. This reduces app/main.py without changing the existing Responses behavior or test patch points. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
This commit is contained in:
GitHub Actions
6
.omc/handoffs/team-exec.md
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6
.omc/handoffs/team-exec.md
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@@ -0,0 +1,6 @@
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## Handoff: team-exec → team-verify
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- **Decided**: Extracted the OpenAI Responses wrapper from `app/main.py` into `app/http/openai_responses.py` while keeping `app.main.v1_responses` as the compatibility route entry and preserving delegation through `v1_chat_completions`.
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- **Rejected**: No protocol behavior changes, no Responses contract expansion, and no docs drift cleanup in this phase to keep the slice compatibility-first.
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- **Risks**: `app/main.py` still intentionally re-exports some Responses helpers via imports; leave that alone unless a later compatibility pass proves it is safe to remove.
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- **Files**: `app/main.py`, `app/http/openai_responses.py`
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- **Remaining**: Independent verifier review, then mark task #32 completed and prepare the phase checkpoint commit/push.
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6
.omc/handoffs/team-verify.md
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6
.omc/handoffs/team-verify.md
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@@ -0,0 +1,6 @@
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## Handoff: team-verify → complete
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- **Decided**: Kept `app.main.v1_responses` as the compatibility route entry while moving the OpenAI Responses wrapper implementation into `app/http/openai_responses.py`.
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- **Rejected**: No protocol changes, no patch-point changes, and no extra cleanup beyond removing the stale Responses imports left behind by the extraction.
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- **Risks**: `app/http/openai_responses.py` now owns the Responses SSE bridge, so future protocol edits should be validated against the existing Responses regression coverage before touching it.
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- **Files**: `app/main.py`, `app/http/openai_responses.py`, `.omc/handoffs/team-verify.md`
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- **Remaining**: Create the phase checkpoint commit, push it to Gitea, then close out the team session.
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326
app/http/openai_responses.py
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326
app/http/openai_responses.py
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@@ -0,0 +1,326 @@
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from __future__ import annotations
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import asyncio
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import json
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import time
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import uuid
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from typing import Any, Awaitable, Callable
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from fastapi import HTTPException, Request
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from fastapi.responses import JSONResponse, StreamingResponse
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from ..openai_schema import ChatCompletionsRequest, ResponsesRequest
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from .responses_adapter import (
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_responses_non_stream_from_chat_payload,
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_responses_to_chat_request,
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_responses_usage_from_chat,
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_sse_data,
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)
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async def _responses_stream_from_chat_stream(
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chat_stream: StreamingResponse,
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*,
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response_id: str,
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model: str,
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):
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created_at = int(time.time())
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usage: dict[str, int] = {"input_tokens": 0, "output_tokens": 0, "total_tokens": 0}
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completed_sent = False
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output_item_id = f"msg_{uuid.uuid4().hex}"
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output_index = 0
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content_index = 0
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output_text_parts: list[str] = []
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function_call_items: list[dict[str, Any]] = []
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function_call_index_by_id: dict[str, int] = {}
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function_call_arguments_by_id: dict[str, str] = {}
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function_call_name_by_id: dict[str, str] = {}
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function_call_id_by_upstream_index: dict[int, str] = {}
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def _message_item(status: str) -> dict[str, Any]:
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return {
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"id": output_item_id,
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"type": "message",
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"role": "assistant",
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"status": status,
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"content": [
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{
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"type": "output_text",
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"text": "".join(output_text_parts),
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}
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],
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}
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def _function_call_item(call_id: str, *, status: str, name: str, arguments: str) -> dict[str, Any]:
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return {
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"id": call_id,
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"type": "function_call",
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"call_id": call_id,
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"name": name,
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"arguments": arguments,
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"status": status,
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}
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def _completed_output_items() -> list[dict[str, Any]]:
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return [_message_item("completed"), *function_call_items]
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def _completed_frame() -> str:
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return _sse_data(
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{
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"type": "response.completed",
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"response": {
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"id": response_id,
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"object": "response",
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"created_at": created_at,
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"status": "completed",
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"model": model,
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"output": _completed_output_items(),
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"usage": usage,
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},
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}
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)
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def _finish_output_item_frames() -> list[str]:
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frames = [
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_sse_data(
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{
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"type": "response.output_text.done",
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"response_id": response_id,
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"item_id": output_item_id,
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"output_index": output_index,
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"content_index": content_index,
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"text": "".join(output_text_parts),
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}
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),
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_sse_data(
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{
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"type": "response.output_item.done",
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"response_id": response_id,
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"output_index": output_index,
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"item": _message_item("completed"),
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}
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),
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]
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for idx, item in enumerate(function_call_items, start=1):
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frames.append(
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_sse_data(
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{
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"type": "response.function_call_arguments.done",
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"response_id": response_id,
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"item_id": item["id"],
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"output_index": idx,
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"arguments": item["arguments"],
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}
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)
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)
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frames.append(
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_sse_data(
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{
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"type": "response.output_item.done",
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"response_id": response_id,
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"output_index": idx,
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"item": item,
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}
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)
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)
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return frames
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def _ensure_function_call_item(call_id: str) -> list[str]:
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existing_index = function_call_index_by_id.get(call_id)
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name = function_call_name_by_id.get(call_id, "tool")
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arguments = function_call_arguments_by_id.get(call_id, "")
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if existing_index is not None:
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function_call_items[existing_index] = _function_call_item(
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call_id,
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status="completed",
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name=name,
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arguments=arguments,
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)
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return []
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item = _function_call_item(
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call_id,
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status="completed",
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name=name,
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arguments=arguments,
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)
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function_call_items.append(item)
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item_index = len(function_call_items) - 1
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function_call_index_by_id[call_id] = item_index
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return [
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_sse_data(
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{
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"type": "response.output_item.added",
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"response_id": response_id,
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"output_index": item_index + 1,
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"item": _function_call_item(
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call_id,
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status="in_progress",
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name=name,
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arguments="",
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),
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}
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)
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]
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yield _sse_data(
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{
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"type": "response.created",
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"response": {
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"id": response_id,
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"object": "response",
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"created_at": created_at,
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"status": "in_progress",
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"model": model,
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"output": [],
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},
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}
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)
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yield _sse_data(
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{
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"type": "response.output_item.added",
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"response_id": response_id,
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"output_index": output_index,
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"item": _message_item("in_progress"),
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}
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)
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try:
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async for part in chat_stream.body_iterator:
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chunk = part.decode("utf-8") if isinstance(part, bytes) else str(part)
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for frame in chunk.split("\n\n"):
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frame = frame.strip()
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if not frame or not frame.startswith("data:"):
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continue
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body = frame[len("data:") :].strip()
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if body == "[DONE]":
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for event in _finish_output_item_frames():
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yield event
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yield _completed_frame()
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yield "data: [DONE]\n\n"
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completed_sent = True
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return
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try:
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payload = json.loads(body)
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except Exception:
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continue
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frame_usage = _responses_usage_from_chat(payload.get("usage"))
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if any(frame_usage.values()):
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usage = frame_usage
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choices = payload.get("choices")
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if not isinstance(choices, list) or not choices:
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continue
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choice = choices[0] if isinstance(choices[0], dict) else {}
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delta = choice.get("delta") if isinstance(choice.get("delta"), dict) else {}
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text = delta.get("content")
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if isinstance(text, str) and text:
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output_text_parts.append(text)
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yield _sse_data(
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{
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"type": "response.output_text.delta",
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"response_id": response_id,
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"item_id": output_item_id,
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"output_index": output_index,
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"content_index": content_index,
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"delta": text,
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}
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)
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tool_calls = delta.get("tool_calls")
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if isinstance(tool_calls, list):
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for idx, tool_call in enumerate(tool_calls):
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if not isinstance(tool_call, dict):
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continue
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fn = tool_call.get("function") if isinstance(tool_call.get("function"), dict) else {}
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upstream_index_raw = tool_call.get("index")
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upstream_index = upstream_index_raw if isinstance(upstream_index_raw, int) else idx
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call_id = str(
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tool_call.get("id")
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or function_call_id_by_upstream_index.get(upstream_index)
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or f"call_{upstream_index}"
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)
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function_call_id_by_upstream_index[upstream_index] = call_id
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name = str(fn.get("name") or function_call_name_by_id.get(call_id) or "tool")
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function_call_name_by_id[call_id] = name
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arguments_delta = str(fn.get("arguments") or "")
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accumulated_arguments = (
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function_call_arguments_by_id.get(call_id, "") + arguments_delta
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)
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function_call_arguments_by_id[call_id] = accumulated_arguments
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for event in _ensure_function_call_item(call_id):
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yield event
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if arguments_delta:
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yield _sse_data(
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{
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||||
"type": "response.function_call_arguments.delta",
|
||||
"response_id": response_id,
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"item_id": call_id,
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"output_index": function_call_index_by_id[call_id] + 1,
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"delta": arguments_delta,
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}
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)
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except asyncio.CancelledError:
|
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if not completed_sent:
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for event in _finish_output_item_frames():
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yield event
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||||
yield _completed_frame()
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yield "data: [DONE]\n\n"
|
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completed_sent = True
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||||
return
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||||
except Exception:
|
||||
if not completed_sent:
|
||||
for event in _finish_output_item_frames():
|
||||
yield event
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||||
yield _completed_frame()
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yield "data: [DONE]\n\n"
|
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completed_sent = True
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||||
return
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||||
|
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if not completed_sent:
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||||
for event in _finish_output_item_frames():
|
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yield event
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||||
yield _completed_frame()
|
||||
yield "data: [DONE]\n\n"
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||||
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||||
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async def handle_responses(
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req: ResponsesRequest,
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request: Request,
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*,
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chat_completions_handler: Callable[[ChatCompletionsRequest, Request], Awaitable[Any]],
|
||||
streaming_response_headers: dict[str, str],
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):
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chat_req = _responses_to_chat_request(req)
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||||
chat_response = await chat_completions_handler(chat_req, request)
|
||||
|
||||
if isinstance(chat_response, StreamingResponse):
|
||||
response_id = f"resp_{uuid.uuid4().hex}"
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||||
return StreamingResponse(
|
||||
_responses_stream_from_chat_stream(
|
||||
chat_response,
|
||||
response_id=response_id,
|
||||
model=req.model,
|
||||
),
|
||||
media_type="text/event-stream",
|
||||
headers=streaming_response_headers,
|
||||
)
|
||||
|
||||
invalid_upstream_error = {
|
||||
"error": {"message": "invalid upstream response", "type": "upstream_error"}
|
||||
}
|
||||
try:
|
||||
chat_payload = json.loads(chat_response.body)
|
||||
except Exception:
|
||||
raise HTTPException(
|
||||
status_code=502,
|
||||
detail=invalid_upstream_error,
|
||||
)
|
||||
if not isinstance(chat_payload, dict):
|
||||
raise HTTPException(
|
||||
status_code=502,
|
||||
detail=invalid_upstream_error,
|
||||
)
|
||||
return JSONResponse(content=_responses_non_stream_from_chat_payload(chat_payload))
|
||||
317
app/main.py
317
app/main.py
@@ -30,14 +30,7 @@ from .http.execution_core import (
|
||||
_resolve_ask_mode as _shared_resolve_ask_mode,
|
||||
prepare_execution_context,
|
||||
)
|
||||
from .http.responses_adapter import (
|
||||
_responses_id_from_chat_id,
|
||||
_responses_input_to_messages,
|
||||
_responses_non_stream_from_chat_payload,
|
||||
_responses_to_chat_request,
|
||||
_responses_usage_from_chat,
|
||||
_sse_data,
|
||||
)
|
||||
from .http.openai_responses import handle_responses
|
||||
from .http.tool_bridge import (
|
||||
_allowed_stream_tool_event,
|
||||
_allowed_tool_events,
|
||||
@@ -941,314 +934,16 @@ async def v1_chat_completions(req: ChatCompletionsRequest, request: Request):
|
||||
|
||||
|
||||
|
||||
async def _responses_stream_from_chat_stream(
|
||||
chat_stream: StreamingResponse,
|
||||
*,
|
||||
response_id: str,
|
||||
model: str,
|
||||
):
|
||||
created_at = int(time.time())
|
||||
usage: dict[str, int] = {"input_tokens": 0, "output_tokens": 0, "total_tokens": 0}
|
||||
completed_sent = False
|
||||
output_item_id = f"msg_{uuid.uuid4().hex}"
|
||||
output_index = 0
|
||||
content_index = 0
|
||||
output_text_parts: list[str] = []
|
||||
function_call_items: list[dict[str, Any]] = []
|
||||
function_call_index_by_id: dict[str, int] = {}
|
||||
function_call_arguments_by_id: dict[str, str] = {}
|
||||
function_call_name_by_id: dict[str, str] = {}
|
||||
function_call_id_by_upstream_index: dict[int, str] = {}
|
||||
|
||||
def _message_item(status: str) -> dict[str, Any]:
|
||||
return {
|
||||
"id": output_item_id,
|
||||
"type": "message",
|
||||
"role": "assistant",
|
||||
"status": status,
|
||||
"content": [
|
||||
{
|
||||
"type": "output_text",
|
||||
"text": "".join(output_text_parts),
|
||||
}
|
||||
],
|
||||
}
|
||||
|
||||
def _function_call_item(call_id: str, *, status: str, name: str, arguments: str) -> dict[str, Any]:
|
||||
return {
|
||||
"id": call_id,
|
||||
"type": "function_call",
|
||||
"call_id": call_id,
|
||||
"name": name,
|
||||
"arguments": arguments,
|
||||
"status": status,
|
||||
}
|
||||
|
||||
def _completed_output_items() -> list[dict[str, Any]]:
|
||||
return [_message_item("completed"), *function_call_items]
|
||||
|
||||
def _completed_frame() -> str:
|
||||
return _sse_data(
|
||||
{
|
||||
"type": "response.completed",
|
||||
"response": {
|
||||
"id": response_id,
|
||||
"object": "response",
|
||||
"created_at": created_at,
|
||||
"status": "completed",
|
||||
"model": model,
|
||||
"output": _completed_output_items(),
|
||||
"usage": usage,
|
||||
},
|
||||
}
|
||||
)
|
||||
|
||||
def _finish_output_item_frames() -> list[str]:
|
||||
frames = [
|
||||
_sse_data(
|
||||
{
|
||||
"type": "response.output_text.done",
|
||||
"response_id": response_id,
|
||||
"item_id": output_item_id,
|
||||
"output_index": output_index,
|
||||
"content_index": content_index,
|
||||
"text": "".join(output_text_parts),
|
||||
}
|
||||
),
|
||||
_sse_data(
|
||||
{
|
||||
"type": "response.output_item.done",
|
||||
"response_id": response_id,
|
||||
"output_index": output_index,
|
||||
"item": _message_item("completed"),
|
||||
}
|
||||
),
|
||||
]
|
||||
for idx, item in enumerate(function_call_items, start=1):
|
||||
frames.append(
|
||||
_sse_data(
|
||||
{
|
||||
"type": "response.function_call_arguments.done",
|
||||
"response_id": response_id,
|
||||
"item_id": item["id"],
|
||||
"output_index": idx,
|
||||
"arguments": item["arguments"],
|
||||
}
|
||||
)
|
||||
)
|
||||
frames.append(
|
||||
_sse_data(
|
||||
{
|
||||
"type": "response.output_item.done",
|
||||
"response_id": response_id,
|
||||
"output_index": idx,
|
||||
"item": item,
|
||||
}
|
||||
)
|
||||
)
|
||||
return frames
|
||||
|
||||
def _ensure_function_call_item(call_id: str) -> list[str]:
|
||||
existing_index = function_call_index_by_id.get(call_id)
|
||||
name = function_call_name_by_id.get(call_id, "tool")
|
||||
arguments = function_call_arguments_by_id.get(call_id, "")
|
||||
if existing_index is not None:
|
||||
function_call_items[existing_index] = _function_call_item(
|
||||
call_id,
|
||||
status="completed",
|
||||
name=name,
|
||||
arguments=arguments,
|
||||
)
|
||||
return []
|
||||
item = _function_call_item(
|
||||
call_id,
|
||||
status="completed",
|
||||
name=name,
|
||||
arguments=arguments,
|
||||
)
|
||||
function_call_items.append(item)
|
||||
item_index = len(function_call_items) - 1
|
||||
function_call_index_by_id[call_id] = item_index
|
||||
return [
|
||||
_sse_data(
|
||||
{
|
||||
"type": "response.output_item.added",
|
||||
"response_id": response_id,
|
||||
"output_index": item_index + 1,
|
||||
"item": _function_call_item(
|
||||
call_id,
|
||||
status="in_progress",
|
||||
name=name,
|
||||
arguments="",
|
||||
),
|
||||
}
|
||||
)
|
||||
]
|
||||
|
||||
yield _sse_data(
|
||||
{
|
||||
"type": "response.created",
|
||||
"response": {
|
||||
"id": response_id,
|
||||
"object": "response",
|
||||
"created_at": created_at,
|
||||
"status": "in_progress",
|
||||
"model": model,
|
||||
"output": [],
|
||||
},
|
||||
}
|
||||
)
|
||||
yield _sse_data(
|
||||
{
|
||||
"type": "response.output_item.added",
|
||||
"response_id": response_id,
|
||||
"output_index": output_index,
|
||||
"item": _message_item("in_progress"),
|
||||
}
|
||||
)
|
||||
|
||||
try:
|
||||
async for part in chat_stream.body_iterator:
|
||||
chunk = part.decode("utf-8") if isinstance(part, bytes) else str(part)
|
||||
for frame in chunk.split("\n\n"):
|
||||
frame = frame.strip()
|
||||
if not frame or not frame.startswith("data:"):
|
||||
continue
|
||||
body = frame[len("data:") :].strip()
|
||||
if body == "[DONE]":
|
||||
for event in _finish_output_item_frames():
|
||||
yield event
|
||||
yield _completed_frame()
|
||||
yield "data: [DONE]\n\n"
|
||||
completed_sent = True
|
||||
return
|
||||
|
||||
try:
|
||||
payload = json.loads(body)
|
||||
except Exception:
|
||||
continue
|
||||
|
||||
frame_usage = _responses_usage_from_chat(payload.get("usage"))
|
||||
if any(frame_usage.values()):
|
||||
usage = frame_usage
|
||||
|
||||
choices = payload.get("choices")
|
||||
if not isinstance(choices, list) or not choices:
|
||||
continue
|
||||
choice = choices[0] if isinstance(choices[0], dict) else {}
|
||||
delta = choice.get("delta") if isinstance(choice.get("delta"), dict) else {}
|
||||
|
||||
text = delta.get("content")
|
||||
if isinstance(text, str) and text:
|
||||
output_text_parts.append(text)
|
||||
yield _sse_data(
|
||||
{
|
||||
"type": "response.output_text.delta",
|
||||
"response_id": response_id,
|
||||
"item_id": output_item_id,
|
||||
"output_index": output_index,
|
||||
"content_index": content_index,
|
||||
"delta": text,
|
||||
}
|
||||
)
|
||||
|
||||
tool_calls = delta.get("tool_calls")
|
||||
if isinstance(tool_calls, list):
|
||||
for idx, tool_call in enumerate(tool_calls):
|
||||
if not isinstance(tool_call, dict):
|
||||
continue
|
||||
fn = tool_call.get("function") if isinstance(tool_call.get("function"), dict) else {}
|
||||
upstream_index_raw = tool_call.get("index")
|
||||
upstream_index = upstream_index_raw if isinstance(upstream_index_raw, int) else idx
|
||||
call_id = str(
|
||||
tool_call.get("id")
|
||||
or function_call_id_by_upstream_index.get(upstream_index)
|
||||
or f"call_{upstream_index}"
|
||||
)
|
||||
function_call_id_by_upstream_index[upstream_index] = call_id
|
||||
name = str(fn.get("name") or function_call_name_by_id.get(call_id) or "tool")
|
||||
function_call_name_by_id[call_id] = name
|
||||
arguments_delta = str(fn.get("arguments") or "")
|
||||
accumulated_arguments = (
|
||||
function_call_arguments_by_id.get(call_id, "") + arguments_delta
|
||||
)
|
||||
function_call_arguments_by_id[call_id] = accumulated_arguments
|
||||
for event in _ensure_function_call_item(call_id):
|
||||
yield event
|
||||
if arguments_delta:
|
||||
yield _sse_data(
|
||||
{
|
||||
"type": "response.function_call_arguments.delta",
|
||||
"response_id": response_id,
|
||||
"item_id": call_id,
|
||||
"output_index": function_call_index_by_id[call_id] + 1,
|
||||
"delta": arguments_delta,
|
||||
}
|
||||
)
|
||||
except asyncio.CancelledError:
|
||||
if not completed_sent:
|
||||
for event in _finish_output_item_frames():
|
||||
yield event
|
||||
yield _completed_frame()
|
||||
yield "data: [DONE]\n\n"
|
||||
completed_sent = True
|
||||
return
|
||||
except Exception:
|
||||
if not completed_sent:
|
||||
for event in _finish_output_item_frames():
|
||||
yield event
|
||||
yield _completed_frame()
|
||||
yield "data: [DONE]\n\n"
|
||||
completed_sent = True
|
||||
return
|
||||
|
||||
if not completed_sent:
|
||||
for event in _finish_output_item_frames():
|
||||
yield event
|
||||
yield _completed_frame()
|
||||
yield "data: [DONE]\n\n"
|
||||
|
||||
|
||||
|
||||
@app.post("/responses", dependencies=[Depends(auth_guard)])
|
||||
@app.post("/v1/responses", dependencies=[Depends(auth_guard)])
|
||||
async def v1_responses(req: ResponsesRequest, request: Request):
|
||||
chat_req = _responses_to_chat_request(req)
|
||||
chat_response = await v1_chat_completions(chat_req, request)
|
||||
|
||||
if isinstance(chat_response, StreamingResponse):
|
||||
response_id = f"resp_{uuid.uuid4().hex}"
|
||||
return StreamingResponse(
|
||||
_responses_stream_from_chat_stream(
|
||||
chat_response,
|
||||
response_id=response_id,
|
||||
model=req.model,
|
||||
),
|
||||
media_type="text/event-stream",
|
||||
headers={
|
||||
"Cache-Control": "no-cache, no-transform",
|
||||
"X-Accel-Buffering": "no",
|
||||
"Connection": "keep-alive",
|
||||
},
|
||||
return await handle_responses(
|
||||
req,
|
||||
request,
|
||||
chat_completions_handler=v1_chat_completions,
|
||||
streaming_response_headers=STREAMING_RESPONSE_HEADERS,
|
||||
)
|
||||
|
||||
invalid_upstream_error = {
|
||||
"error": {"message": "invalid upstream response", "type": "upstream_error"}
|
||||
}
|
||||
try:
|
||||
chat_payload = json.loads(chat_response.body)
|
||||
except Exception:
|
||||
raise HTTPException(
|
||||
status_code=502,
|
||||
detail=invalid_upstream_error,
|
||||
)
|
||||
if not isinstance(chat_payload, dict):
|
||||
raise HTTPException(
|
||||
status_code=502,
|
||||
detail=invalid_upstream_error,
|
||||
)
|
||||
return JSONResponse(content=_responses_non_stream_from_chat_payload(chat_payload))
|
||||
|
||||
|
||||
|
||||
def _anthropic_error(status_code: int, error_type: str, message: str) -> JSONResponse:
|
||||
|
||||
Reference in New Issue
Block a user