74 lines
2.4 KiB
Python
74 lines
2.4 KiB
Python
from fastapi import APIRouter
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from sse_starlette.sse import EventSourceResponse
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from app.schemas.rag import RagChatRequest, QuickQuestionsResponse, QuickQuestion
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from app.services.mock_data import (
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get_mock_quick_questions,
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get_mock_retrieval,
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get_mock_rag_answer,
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)
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import json
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import asyncio
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router = APIRouter(prefix="/rag", tags=["RAG问答"])
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@router.post("/chat")
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async def rag_chat(request: RagChatRequest):
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"""SSE流式问答"""
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async def generate():
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# 发送检索开始事件
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yield {"event": "message", "data": json.dumps({"type": "retrieving"})}
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# 模拟检索延迟
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await asyncio.sleep(0.3)
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# 执行检索
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docs = get_mock_retrieval(request.query, top_k=request.top_k)
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retrieved_data = [
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{
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"id": d["id"],
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"score": d["score"],
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"preview": d["preview"],
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"doc_name": d.get("doc_name", ""),
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"clause": d.get("clause", ""),
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}
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for d in docs
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]
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yield {"event": "message", "data": json.dumps({"type": "retrieved", "docs": retrieved_data})}
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# 发送生成开始事件
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yield {"event": "message", "data": json.dumps({"type": "generating", "text": "正在生成答案..."})}
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# 模拟生成延迟
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await asyncio.sleep(0.2)
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# 获取预设答案
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answer = get_mock_rag_answer(request.query)
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# 流式输出答案（按句子分割）
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sentences = answer.split("\n\n")
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for sentence in sentences:
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if sentence.strip():
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# 进一步分割长句子
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chunks = sentence.split("\n")
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for chunk in chunks:
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if chunk.strip():
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await asyncio.sleep(0.05) # 模拟生成延迟
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yield {"event": "message", "data": json.dumps({"type": "chunk", "text": chunk + "\n"})}
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# 发送完成事件
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yield {"event": "message", "data": json.dumps({"type": "done"})}
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return EventSourceResponse(generate())
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@router.get("/quick-questions", response_model=QuickQuestionsResponse)
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async def get_quick_questions():
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"""获取预设快捷问题"""
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questions = [
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QuickQuestion(id=q["id"], question=q["question"], category=q["category"])
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for q in get_mock_quick_questions()
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]
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return QuickQuestionsResponse(questions=questions) |