Fix SSE route dependency and align architecture docs
This commit is contained in:
ash66
@@ -1,186 +1,83 @@
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"""Agent API接口 - 问答对话接口"""
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"""Define API routes for agent."""
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from __future__ import annotations
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from fastapi import APIRouter, HTTPException, Depends
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from fastapi.responses import StreamingResponse
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from pydantic import BaseModel, Field
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from typing import List, Dict, Optional, AsyncGenerator
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from loguru import logger
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import json
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import asyncio
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import json
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from typing import AsyncGenerator, List, Optional
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from app.services.agent.qa_agent import QAAgent, AgentConfig
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from app.services.agent.session_manager import SessionManager
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from fastapi import APIRouter, HTTPException
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from fastapi.responses import StreamingResponse
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from dataclasses import asdict
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from app.api.models import (
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AskRequest,
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AskResponse,
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ChatRequest,
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ChatResponse,
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FeedbackRequest,
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SessionInfo,
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)
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from app.config.settings import settings
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from app.shared.bootstrap import get_agent_conversation_service, get_conversation_store
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# Keep route handlers close to their transport-layer wiring for easier auditing.
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router = APIRouter(prefix="/agent", tags=["agent"])
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# 会话管理器（全局实例）
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session_manager = SessionManager()
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# ===== Pydantic Models =====
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class AskRequest(BaseModel):
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"""单次问答请求"""
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query: str = Field(..., description="用户问题", min_length=1, max_length=2000)
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filters: Optional[str] = Field(None, description="检索过滤条件")
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provider: Optional[str] = Field(None, description="LLM提供商 (qwen/deepseek)")
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model: Optional[str] = Field(None, description="LLM模型名称")
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top_k: Optional[int] = Field(None, description="检索数量", ge=1, le=20)
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prompt_template: Optional[str] = Field(None, description="Prompt模板名称")
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class AskResponse(BaseModel):
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"""问答响应"""
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answer: str
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sources: List[Dict] = []
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model: str = ""
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latency_ms: int = 0
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retrieved_count: int = 0
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context_tokens: int = 0
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truncated: bool = False
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error: Optional[str] = None
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class ChatRequest(BaseModel):
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"""多轮对话请求"""
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query: str = Field(..., description="用户问题", min_length=1, max_length=2000)
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session_id: Optional[str] = Field(None, description="会话ID（首次对话可不传）")
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filters: Optional[str] = Field(None, description="检索过滤条件")
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provider: Optional[str] = Field(None, description="LLM提供商")
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model: Optional[str] = Field(None, description="LLM模型名称")
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class ChatResponse(BaseModel):
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"""多轮对话响应"""
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session_id: str
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answer: str
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sources: List[Dict] = []
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model: str = ""
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latency_ms: int = 0
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message_count: int = 0
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class SessionInfo(BaseModel):
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"""会话信息"""
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session_id: str
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message_count: int
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created_at: int
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updated_at: int
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class FeedbackRequest(BaseModel):
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"""反馈请求"""
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session_id: str
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message_index: int
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rating: int = Field(..., ge=1, le=5, description="评分 1-5")
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comment: Optional[str] = Field(None, description="反馈内容")
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class TemplateListResponse(BaseModel):
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"""模板列表响应"""
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templates: Dict[str, str]
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# ===== API Endpoints =====
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@router.post("/ask", response_model=AskResponse)
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async def ask_question(request: AskRequest):
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"""
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单次问答接口
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不保存会话历史，适合单次查询场景。
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"""
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logger.info(f"收到问答请求: {request.query}")
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"""Handle ask question."""
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try:
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# 构建Agent配置
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config = AgentConfig(
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llm_provider=request.provider or settings.llm_provider,
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llm_model=request.model or settings.llm_model,
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top_k=request.top_k or settings.rag_top_k
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)
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# 创建Agent并执行问答
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agent = QAAgent(config)
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response = agent.ask(
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_, result = get_agent_conversation_service().ask(
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query=request.query,
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filters=request.filters,
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prompt_template=request.prompt_template
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provider=request.provider or settings.llm_provider,
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model=request.model or settings.llm_model,
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top_k=request.top_k or settings.rag_top_k,
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prompt_template=request.prompt_template,
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)
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agent.close()
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return AskResponse(
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answer=response.answer,
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sources=response.sources,
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model=response.model,
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latency_ms=response.latency_ms,
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retrieved_count=response.retrieved_count,
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context_tokens=response.context_tokens,
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truncated=response.truncated,
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error=response.error
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answer=result.answer,
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sources=[asdict(source) for source in result.sources],
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model=result.model,
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latency_ms=result.latency_ms,
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retrieved_count=result.retrieved_count,
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context_tokens=result.context_tokens,
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truncated=result.truncated,
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error=result.error,
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)
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except Exception as e:
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logger.error(f"问答失败: {e}")
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raise HTTPException(status_code=500, detail=str(e))
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except Exception as exc:
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raise HTTPException(status_code=500, detail=str(exc))
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@router.post("/chat", response_model=ChatResponse)
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async def chat_with_session(request: ChatRequest):
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"""
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多轮对话接口
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支持会话历史记录，适合连续对话场景。
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"""
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logger.info(f"收到对话请求: session={request.session_id}, query={request.query}")
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"""Handle chat with session."""
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try:
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# 获取或创建会话
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if request.session_id:
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session = session_manager.get_session(request.session_id)
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if not session:
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raise HTTPException(status_code=404, detail="会话不存在或已过期")
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else:
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session = session_manager.create_session()
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# 添加用户消息
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session.add_user_message(request.query)
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# 执行问答
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config = AgentConfig(
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llm_provider=request.provider or settings.llm_provider,
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llm_model=request.model or settings.llm_model
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)
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agent = QAAgent(config)
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response = agent.ask(
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session_id, result = get_agent_conversation_service().chat(
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query=request.query,
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filters=request.filters
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session_id=request.session_id,
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filters=request.filters,
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provider=request.provider or settings.llm_provider,
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model=request.model or settings.llm_model,
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top_k=request.top_k or settings.rag_top_k,
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)
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agent.close()
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# 添加助手消息
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session.add_assistant_message(
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response.answer,
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response.sources
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)
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session = get_conversation_store().get_session(session_id)
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return ChatResponse(
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session_id=session.session_id,
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answer=response.answer,
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sources=response.sources,
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model=response.model,
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latency_ms=response.latency_ms,
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message_count=session.message_count
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session_id=session_id,
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answer=result.answer,
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sources=[asdict(source) for source in result.sources],
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model=result.model,
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latency_ms=result.latency_ms,
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message_count=len(session.messages) if session else 0,
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)
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except HTTPException:
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raise
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except Exception as e:
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logger.error(f"对话失败: {e}")
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raise HTTPException(status_code=500, detail=str(e))
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except ValueError as exc:
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raise HTTPException(status_code=404, detail=str(exc))
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except Exception as exc:
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raise HTTPException(status_code=500, detail=str(exc))
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@router.get("/chat/stream")
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@@ -189,260 +86,93 @@ async def chat_stream_get(
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session_id: Optional[str] = None,
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filters: Optional[str] = None,
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provider: Optional[str] = None,
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model: Optional[str] = None
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model: Optional[str] = None,
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):
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"""
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流式对话接口（SSE）- GET版本
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EventSource只能发送GET请求，因此提供此接口。
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query参数通过URL传递。
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SSE事件格式：
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- event: session - 会话ID
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- event: status - 状态更新（检索中、生成中）
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- event: sources - 引用来源
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- event: content - 回答内容片段
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- event: done - 完成，包含统计信息
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- event: error - 错误信息
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"""
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logger.info(f"收到GET流式对话请求: session={session_id}, query={query}")
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"""Handle chat stream get."""
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async def generate_sse() -> AsyncGenerator[str, None]:
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"""生成SSE事件流"""
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"""Handle generate sse."""
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try:
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# 获取或创建会话
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if session_id:
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session = session_manager.get_session(session_id)
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if not session:
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yield f"event: error\ndata: 会话不存在或已过期\n\n"
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return
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else:
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session = session_manager.create_session()
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# 发送session_id
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yield f"event: session\ndata: {json.dumps({'session_id': session.session_id})}\n\n"
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# 添加用户消息
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session.add_user_message(query)
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# 创建Agent
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config = AgentConfig(
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llm_provider=provider or settings.llm_provider,
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llm_model=model or settings.llm_model
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)
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agent = QAAgent(config)
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# 执行流式问答
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full_answer = ""
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sources = []
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done_data = {}
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for event_data in agent.ask_stream(
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session_id_, event_stream = get_agent_conversation_service().stream_chat(
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query=query,
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filters=filters
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):
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session_id=session_id,
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filters=filters,
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provider=provider or settings.llm_provider,
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model=model or settings.llm_model,
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top_k=settings.rag_top_k,
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)
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yield f"event: session\ndata: {json.dumps({'session_id': session_id_})}\n\n"
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for event_data in event_stream:
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event_type = event_data.get("event", "content")
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data = event_data.get("data", "")
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# 收集完整回答和来源
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if event_type == "content":
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full_answer += str(data)
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elif event_type == "sources":
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sources = data
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elif event_type == "done":
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done_data = data
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# 发送SSE事件
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if isinstance(data, (dict, list)):
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yield f"event: {event_type}\ndata: {json.dumps(data)}\n\n"
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yield f"event: {event_type}\ndata: {json.dumps(data, ensure_ascii=False)}\n\n"
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else:
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yield f"event: {event_type}\ndata: {data}\n\n"
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# 小延迟让其他任务有机会执行
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await asyncio.sleep(0)
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agent.close()
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# 保存到会话历史
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session.add_assistant_message(full_answer, sources)
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except Exception as e:
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logger.error(f"流式对话失败: {e}")
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yield f"event: error\ndata: {str(e)}\n\n"
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except Exception as exc:
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yield f"event: error\ndata: {str(exc)}\n\n"
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return StreamingResponse(
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generate_sse(),
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media_type="text/event-stream",
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headers={
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"Cache-Control": "no-cache",
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"Connection": "keep-alive",
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"X-Accel-Buffering": "no" # 禁用nginx缓冲
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}
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headers={"Cache-Control": "no-cache", "Connection": "keep-alive", "X-Accel-Buffering": "no"},
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)
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@router.post("/chat/stream")
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async def chat_stream(request: ChatRequest):
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"""
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流式对话接口（SSE）
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返回Server-Sent Events格式的流式响应，用户可实时看到思考过程和回答生成。
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SSE事件格式：
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- event: status - 状态更新（检索中、生成中）
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- event: sources - 引用来源
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- event: content - 回答内容片段
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- event: done - 完成，包含统计信息
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- event: error - 错误信息
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"""
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logger.info(f"收到流式对话请求: session={request.session_id}, query={request.query}")
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async def generate_sse() -> AsyncGenerator[str, None]:
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"""生成SSE事件流"""
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try:
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# 获取或创建会话
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if request.session_id:
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session = session_manager.get_session(request.session_id)
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if not session:
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yield f"event: error\ndata: 会话不存在或已过期\n\n"
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return
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else:
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session = session_manager.create_session()
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# 发送session_id
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yield f"event: session\ndata: {json.dumps({'session_id': session.session_id})}\n\n"
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# 添加用户消息
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session.add_user_message(request.query)
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# 创建Agent
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config = AgentConfig(
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llm_provider=request.provider or settings.llm_provider,
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llm_model=request.model or settings.llm_model
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)
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agent = QAAgent(config)
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# 执行流式问答
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full_answer = ""
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sources = []
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done_data = {}
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for event_data in agent.ask_stream(
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query=request.query,
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filters=request.filters
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):
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event_type = event_data.get("event", "content")
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data = event_data.get("data", "")
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# 收集完整回答和来源
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if event_type == "content":
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full_answer += str(data)
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elif event_type == "sources":
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sources = data
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elif event_type == "done":
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done_data = data
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# 发送SSE事件
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if isinstance(data, (dict, list)):
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yield f"event: {event_type}\ndata: {json.dumps(data)}\n\n"
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else:
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yield f"event: {event_type}\ndata: {data}\n\n"
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# 小延迟让其他任务有机会执行
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await asyncio.sleep(0)
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agent.close()
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# 保存到会话历史
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session.add_assistant_message(full_answer, sources)
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except Exception as e:
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logger.error(f"流式对话失败: {e}")
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yield f"event: error\ndata: {str(e)}\n\n"
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return StreamingResponse(
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generate_sse(),
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media_type="text/event-stream",
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headers={
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"Cache-Control": "no-cache",
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"Connection": "keep-alive",
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"X-Accel-Buffering": "no" # 禁用nginx缓冲
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}
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"""Handle chat stream."""
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return await chat_stream_get(
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query=request.query,
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session_id=request.session_id,
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filters=request.filters,
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provider=request.provider,
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model=request.model,
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)
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@router.get("/session/{session_id}", response_model=SessionInfo)
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async def get_session_info(session_id: str):
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"""获取会话信息"""
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session = session_manager.get_session(session_id)
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"""Return session info."""
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session = get_conversation_store().get_session(session_id)
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if not session:
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raise HTTPException(status_code=404, detail="会话不存在或已过期")
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|
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return SessionInfo(
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session_id=session.session_id,
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message_count=session.message_count,
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message_count=len(session.messages),
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created_at=session.created_at,
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updated_at=session.updated_at
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updated_at=session.updated_at,
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)
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@router.get("/session/{session_id}/history")
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async def get_session_history(session_id: str, max_turns: int = 5):
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"""获取会话历史"""
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session = session_manager.get_session(session_id)
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"""Return session history."""
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session = get_conversation_store().get_session(session_id)
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if not session:
|
||||
raise HTTPException(status_code=404, detail="会话不存在或已过期")
|
||||
|
||||
history = session.get_history(max_turns)
|
||||
history = [{"role": msg.role, "content": msg.content} for msg in session.messages[-(max_turns * 2):]]
|
||||
return {"session_id": session_id, "history": history}
|
||||
|
||||
|
||||
@router.delete("/session/{session_id}")
|
||||
async def delete_session(session_id: str):
|
||||
"""删除会话"""
|
||||
success = session_manager.delete_session(session_id)
|
||||
if not success:
|
||||
"""Delete session."""
|
||||
if not get_conversation_store().delete_session(session_id):
|
||||
raise HTTPException(status_code=404, detail="会话不存在")
|
||||
|
||||
return {"message": "会话已删除", "session_id": session_id}
|
||||
|
||||
|
||||
@router.get("/sessions", response_model=List[SessionInfo])
|
||||
async def list_sessions():
|
||||
"""列出所有活跃会话"""
|
||||
sessions = session_manager.list_sessions()
|
||||
return [SessionInfo(**s) for s in sessions]
|
||||
"""List sessions."""
|
||||
return [SessionInfo(**item) for item in get_conversation_store().list_sessions()]
|
||||
|
||||
|
||||
@router.post("/feedback")
|
||||
async def submit_feedback(request: FeedbackRequest):
|
||||
"""提交问答反馈"""
|
||||
session = session_manager.get_session(request.session_id)
|
||||
"""Submit feedback."""
|
||||
session = get_conversation_store().get_session(request.session_id)
|
||||
if not session:
|
||||
raise HTTPException(status_code=404, detail="会话不存在")
|
||||
|
||||
# 记录反馈（实际应用中可存储到数据库）
|
||||
logger.info(f"收到反馈: session={request.session_id}, rating={request.rating}, comment={request.comment}")
|
||||
|
||||
return {"message": "反馈已记录", "rating": request.rating}
|
||||
|
||||
|
||||
@router.get("/templates", response_model=TemplateListResponse)
|
||||
async def list_prompt_templates():
|
||||
"""列出可用的Prompt模板"""
|
||||
from app.services.rag.prompt_templates import PromptTemplates
|
||||
|
||||
templates = PromptTemplates.list_templates()
|
||||
return TemplateListResponse(templates=templates)
|
||||
|
||||
|
||||
@router.get("/models")
|
||||
async def list_available_models():
|
||||
"""列出可用的LLM模型"""
|
||||
from app.services.llm import LLMFactory
|
||||
|
||||
factory = LLMFactory()
|
||||
models = factory.list_available_providers()
|
||||
return {"models": models}
|
||||
return {"message": "反馈已提交", "session_id": request.session_id, "message_index": request.message_index}
|
||||
|
||||
Reference in New Issue
Block a user