327 lines
11 KiB
Python
327 lines
11 KiB
Python
"""路由: /v1/responses
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处理 Cursor 对 GPT、Claude-Opus 等模型发出的 Responses API 请求。
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请求会先转换为 Chat Completions 中间表示，再按后端类型分发，最后转换回 Responses 格式。
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"""
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from __future__ import annotations
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import json
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import logging
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from typing import Any
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from flask import Blueprint, jsonify, request
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from adapters.cc_anthropic_adapter import cc_to_messages_request, messages_to_cc_response
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from adapters.openai_compat_fixer import fix_response, fix_stream_chunk, normalize_request
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from adapters.responses_cc_adapter import ResponsesStreamConverter, cc_to_responses, responses_to_cc
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from config import Config
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from routes.common import (
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RouteContext,
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apply_body_modifications,
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apply_header_modifications,
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build_anthropic_target,
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build_openai_target,
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build_responses_target,
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build_route_context,
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inject_instructions_anthropic,
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inject_instructions_cc,
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inject_instructions_responses,
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log_route_context,
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log_usage,
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responses_error_event,
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)
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from utils.http import (
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forward_request,
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iter_anthropic_sse,
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iter_openai_sse,
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iter_responses_sse,
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sse_response,
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)
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from utils.think_tag import ThinkTagExtractor
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logger = logging.getLogger(__name__)
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bp = Blueprint('responses', __name__)
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def _dbg(message: str) -> None:
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"""仅在调试模式下输出详细日志。"""
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if Config.DEBUG:
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logger.info('[响应生成调试] %s', message)
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@bp.route('/v1/responses', methods=['POST'])
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def responses_endpoint():
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"""处理 Responses 请求并按模型映射分发。"""
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payload = request.get_json(force=True)
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client_model = payload.get('model', 'unknown')
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is_stream = payload.get('stream', False)
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ctx = build_route_context(client_model, is_stream)
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log_route_context('响应生成', ctx)
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cc_payload = _build_cc_payload(payload, ctx)
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if ctx.backend == 'openai':
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return _handle_openai_backend(ctx, cc_payload)
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if ctx.backend == 'responses':
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return _handle_responses_backend(ctx, payload)
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return _handle_anthropic_backend(ctx, cc_payload)
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def _build_cc_payload(payload: dict[str, Any], ctx: RouteContext) -> dict[str, Any]:
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"""将 Responses 请求统一降级为 Chat Completions 中间表示。
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这样后续无论走 OpenAI 兼容后端还是 Anthropic 后端，都能复用一套
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中间协议，避免在路由层同时维护两套完全不同的请求编排逻辑。
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"""
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cc_payload = responses_to_cc(payload)
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cc_payload['model'] = ctx.upstream_model
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cc_payload = inject_instructions_cc(cc_payload, ctx.custom_instructions, ctx.instructions_position)
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_dbg(
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'已转换为聊天补全中间表示：字段=' + str(list(cc_payload.keys()))
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+ f' 消息数={len(cc_payload.get("messages", []))}'
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)
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return cc_payload
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def _handle_openai_backend(ctx: RouteContext, cc_payload: dict[str, Any]):
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"""处理走 OpenAI 兼容后端的 Responses 请求。"""
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cc_payload = normalize_request(cc_payload)
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_dbg(
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f'标准化完成：模型={cc_payload.get("model")} '
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f'工具数={len(cc_payload.get("tools", []))}'
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)
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url, headers = build_openai_target(ctx)
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cc_payload = apply_body_modifications(cc_payload, ctx.body_modifications)
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headers = apply_header_modifications(headers, ctx.header_modifications)
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if ctx.is_stream:
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return _handle_openai_stream(ctx, cc_payload, url, headers)
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return _handle_openai_non_stream(ctx, cc_payload, url, headers)
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def _handle_openai_non_stream(
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ctx: RouteContext,
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cc_payload: dict[str, Any],
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url: str,
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headers: dict[str, str],
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):
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"""处理 OpenAI 兼容后端的非流式 Responses 返回。"""
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cc_payload['stream'] = False
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resp, err = forward_request(url, headers, cc_payload)
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if err:
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return err
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raw = resp.json()
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_dbg('上游原始响应=' + json.dumps(raw, ensure_ascii=False, default=str)[:1000])
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fixed = fix_response(raw)
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response_data = cc_to_responses(fixed, ctx.client_model)
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return _finalize_responses_response(response_data, debug_label='转换为 Responses 后')
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def _handle_openai_stream(
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ctx: RouteContext,
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cc_payload: dict[str, Any],
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url: str,
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headers: dict[str, str],
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):
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"""处理 OpenAI 兼容后端的流式 Responses 返回。"""
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cc_payload['stream'] = True
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converter = ResponsesStreamConverter(model=ctx.client_model)
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def generate():
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"""消费 OpenAI 聊天补全流，并实时改写为 Responses SSE。"""
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yield from converter.start_events()
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resp, err = forward_request(url, headers, cc_payload, stream=True)
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if err:
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yield responses_error_event(str(err))
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return
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think_extractor = ThinkTagExtractor()
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chunk_count = 0
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for chunk in iter_openai_sse(resp):
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if chunk is None:
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_dbg(f'流式响应结束，共 {chunk_count} 个数据片段')
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yield from converter.finalize()
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return
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if chunk_count < 10:
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_dbg(
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f'上游原始片段#{chunk_count}='
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+ json.dumps(chunk, ensure_ascii=False, default=str)[:500]
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)
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chunk = fix_stream_chunk(chunk)
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for out in think_extractor.process_chunk(chunk):
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if chunk_count < 10:
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_dbg(
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f'转换后片段#{chunk_count}='
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+ json.dumps(out, ensure_ascii=False, default=str)[:500]
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)
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yield from converter.process_cc_chunk(out)
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chunk_count += 1
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return sse_response(generate())
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def _handle_responses_backend(ctx: RouteContext, payload: dict[str, Any]):
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"""处理走原生 Responses 后端的请求。
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当中转站本身就只支持 `/v1/responses` 时，不需要再绕到聊天补全中间协议，
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直接转发原生 Responses 请求即可。
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"""
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payload = dict(payload)
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payload['model'] = ctx.upstream_model
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payload = inject_instructions_responses(payload, ctx.custom_instructions, ctx.instructions_position)
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url, headers = build_responses_target(ctx)
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payload = apply_body_modifications(payload, ctx.body_modifications)
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headers = apply_header_modifications(headers, ctx.header_modifications)
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if ctx.is_stream:
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return _handle_responses_stream(ctx, payload, url, headers)
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return _handle_responses_non_stream(ctx, payload, url, headers)
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def _handle_responses_non_stream(
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ctx: RouteContext,
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payload: dict[str, Any],
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url: str,
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headers: dict[str, str],
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):
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"""处理原生 Responses 后端的非流式返回。"""
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payload['stream'] = False
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resp, err = forward_request(url, headers, payload)
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if err:
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return err
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response_data = resp.json()
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response_data['model'] = ctx.client_model
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return _finalize_responses_response(response_data, debug_label='原生 Responses 返回后')
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def _handle_responses_stream(
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ctx: RouteContext,
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payload: dict[str, Any],
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url: str,
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headers: dict[str, str],
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):
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"""处理原生 Responses 后端的流式返回。"""
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payload['stream'] = True
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converter = ResponsesStreamConverter(model=ctx.client_model)
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def generate():
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"""透传上游原生 Responses 流，并做轻量模型名改写。"""
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resp, err = forward_request(url, headers, payload, stream=True)
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if err:
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yield responses_error_event(str(err))
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return
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event_count = 0
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for event_type, event_data in iter_responses_sse(resp):
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if event_count < 10:
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_dbg(
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f'上游事件#{event_count} 类型={event_type} 数据='
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+ json.dumps(event_data, ensure_ascii=False, default=str)[:500]
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)
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yield from converter.process_responses_event(event_type, event_data)
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event_count += 1
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_dbg(f'流式响应结束，共 {event_count} 个事件')
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return sse_response(generate())
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def _handle_anthropic_backend(ctx: RouteContext, cc_payload: dict[str, Any]):
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"""处理走 Anthropic 后端的 Responses 请求。"""
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anthropic_payload = cc_to_messages_request(cc_payload)
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_dbg(
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'已转换为 Messages 请求：字段=' + str(list(anthropic_payload.keys()))
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+ f' 消息数={len(anthropic_payload.get("messages", []))}'
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)
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url, headers = build_anthropic_target(ctx)
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anthropic_payload = apply_body_modifications(anthropic_payload, ctx.body_modifications)
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headers = apply_header_modifications(headers, ctx.header_modifications)
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if ctx.is_stream:
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return _handle_anthropic_stream(ctx, anthropic_payload, url, headers)
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return _handle_anthropic_non_stream(ctx, anthropic_payload, url, headers)
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def _handle_anthropic_non_stream(
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ctx: RouteContext,
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anthropic_payload: dict[str, Any],
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url: str,
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headers: dict[str, str],
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):
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"""处理 Anthropic 后端的非流式 Responses 返回。"""
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anthropic_payload['stream'] = False
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resp, err = forward_request(url, headers, anthropic_payload)
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if err:
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return err
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raw = resp.json()
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_dbg('上游原始响应=' + json.dumps(raw, ensure_ascii=False, default=str)[:1000])
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cc_data = messages_to_cc_response(raw)
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response_data = cc_to_responses(cc_data, ctx.client_model)
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return _finalize_responses_response(response_data, debug_label='Messages 转回 Responses 后')
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def _handle_anthropic_stream(
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ctx: RouteContext,
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anthropic_payload: dict[str, Any],
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url: str,
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headers: dict[str, str],
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):
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"""处理 Anthropic 后端的流式 Responses 返回。
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这里直接将 Anthropic SSE 事件映射到 Responses SSE，故意跳过 CC 流式中间态，
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这样可以减少一次事件重组，降低流式转换复杂度，也更容易保留原始时序。
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"""
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anthropic_payload['stream'] = True
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converter = ResponsesStreamConverter(model=ctx.client_model)
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def generate():
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"""消费 Anthropic SSE，并直接映射为 Responses 事件序列。"""
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yield from converter.start_events()
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resp, err = forward_request(url, headers, anthropic_payload, stream=True)
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if err:
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yield responses_error_event(str(err))
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return
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event_count = 0
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for event_type, event_data in iter_anthropic_sse(resp):
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if event_count < 10:
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_dbg(
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f'上游事件#{event_count} 类型={event_type} 数据='
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+ json.dumps(event_data, ensure_ascii=False, default=str)[:500]
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)
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yield from converter.process_anthropic_event(event_type, event_data)
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event_count += 1
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_dbg(f'流式响应结束，共 {event_count} 个事件')
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yield from converter.finalize()
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return sse_response(generate())
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def _finalize_responses_response(response_data: dict[str, Any], *, debug_label: str):
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"""统一收尾非流式 Responses 响应。
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两条转换链路和一条原生 Responses 链路最终都会回到 Responses 对象，因此这里集中
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处理调试日志、回填展示模型名以及 usage 日志。
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"""
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response_data['model'] = response_data.get('model') or ''
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_dbg(debug_label + '=' + json.dumps(response_data, ensure_ascii=False, default=str)[:1000])
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log_usage('响应生成', response_data.get('usage', {}), input_key='input_tokens', output_key='output_tokens')
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return jsonify(response_data)
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