刘金宝
50 lines
1.9 KiB
Python
50 lines
1.9 KiB
Python
from fastapi import APIRouter, Depends
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from sqlalchemy.orm import Session
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from starlette.responses import StreamingResponse
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from app.core.response import ApiResponse, ok
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from app.core.user_context import UserContext, get_user_context
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from app.db.session import get_db
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from app.schemas.learning_assistant import (
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LearningAssistantChatRequest,
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LearningAssistantSessionCreateRequest,
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LearningAssistantSessionResponse,
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)
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from app.services.learning_assistant_service import LearningAssistantService
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router = APIRouter()
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@router.post("/sessions", response_model=ApiResponse[LearningAssistantSessionResponse])
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async def create_learning_assistant_session(
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payload: LearningAssistantSessionCreateRequest,
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ctx: UserContext = Depends(get_user_context),
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db: Session = Depends(get_db),
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):
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"""学习助手会话创建：进入 AI 学习助手页面时生成短期会话 ID。"""
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result = LearningAssistantService(db).create_session(ctx, payload)
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return ok(result)
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@router.post("/sessions/{assistant_session_id}/chat/stream", response_class=StreamingResponse)
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async def stream_learning_assistant_session_chat(
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assistant_session_id: str,
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payload: LearningAssistantChatRequest,
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ctx: UserContext = Depends(get_user_context),
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db: Session = Depends(get_db),
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):
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"""学习助手会话式流式问答：绑定短期会话上下文，返回 SSE 增量回答。"""
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service = LearningAssistantService(db)
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assistant_session = service.validate_session(ctx, assistant_session_id)
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stream = service.stream_session_chat(ctx, payload, assistant_session)
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return _sse_response(stream)
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def _sse_response(stream) -> StreamingResponse:
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"""SSE 响应封装：关闭代理缓冲，避免前端长时间看不到增量内容。"""
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return StreamingResponse(
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stream,
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media_type="text/event-stream",
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headers={"Cache-Control": "no-cache", "Connection": "keep-alive", "X-Accel-Buffering": "no"},
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)
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