feat: add streaming learning assistant and knowledge base scaffolding

app/api/learning_assistant.py

@@ -0,0 +1,39 @@
+from fastapi import APIRouter, Depends
+from sqlalchemy.orm import Session
+from starlette.responses import StreamingResponse
+
+from app.core.response import ApiResponse, ok
+from app.core.user_context import UserContext, get_user_context
+from app.db.session import get_db
+from app.schemas.learning_assistant import LearningAssistantChatRequest, LearningAssistantChatResponse
+from app.services.learning_assistant_service import LearningAssistantService
+
+router = APIRouter()
+
+
+@router.post("/chat", response_model=ApiResponse[LearningAssistantChatResponse], include_in_schema=False)
+async def learning_assistant_chat(
+    payload: LearningAssistantChatRequest,
+    ctx: UserContext = Depends(get_user_context),
+    db: Session = Depends(get_db),
+):
+    """AI 学习助手调试接口：非流式返回回答，正式前端联调使用流式接口。"""
+    result = await LearningAssistantService(db).chat(ctx, payload)
+    db.commit()
+    return ok(result)
+
+
+@router.post("/chat/stream", response_class=StreamingResponse)
+async def learning_assistant_stream_chat(
+    payload: LearningAssistantChatRequest,
+    ctx: UserContext = Depends(get_user_context),
+    db: Session = Depends(get_db),
+):
+    """AI 学习助手流式问答：返回 retrieval_done、answer_delta、answer_done 事件。"""
+    stream = LearningAssistantService(db).stream_chat(ctx, payload)
+    db.commit()
+    return StreamingResponse(
+        stream,
+        media_type="text/event-stream",
+        headers={"Cache-Control": "no-cache", "Connection": "keep-alive", "X-Accel-Buffering": "no"},
+    )