Merge pull request #299 from JefferyHcool/feature/note-qa-chat-optimize

Feature/note qa chat optimize

backend/app/routers/chat.py

@@ -0,0 +1,101 @@
+from fastapi import APIRouter, BackgroundTasks
+from pydantic import BaseModel
+
+from app.services.chat_service import chat as chat_service
+from app.services.vector_store import VectorStoreManager
+from app.utils.logger import get_logger
+from app.utils.response import ResponseWrapper as R
+
+logger = get_logger(__name__)
+
+router = APIRouter()
+
+# 索引状态追踪: task_id -> "indexing" | "indexed" | "failed"
+_index_status: dict[str, str] = {}
+
+
+class IndexRequest(BaseModel):
+    task_id: str
+
+
+class ChatMessage(BaseModel):
+    role: str
+    content: str
+
+
+class AskRequest(BaseModel):
+    task_id: str
+    question: str
+    history: list[ChatMessage] = []
+    provider_id: str
+    model_name: str
+
+
+def _do_index(task_id: str):
+    """后台执行索引任务。"""
+    try:
+        _index_status[task_id] = "indexing"
+        store = VectorStoreManager()
+        store.index_task(task_id)
+        _index_status[task_id] = "indexed"
+        logger.info(f"索引完成: {task_id}")
+    except Exception as e:
+        _index_status[task_id] = "failed"
+        logger.error(f"索引失败: {task_id}, {e}")
+
+
+@router.post("/chat/index")
+def index_task(data: IndexRequest, background_tasks: BackgroundTasks):
+    """触发后台索引，立即返回。"""
+    if _index_status.get(data.task_id) == "indexing":
+        return R.success(msg="正在索引中")
+
+    # 如果已经索引过，直接返回
+    store = VectorStoreManager()
+    if store.is_indexed(data.task_id):
+        _index_status[data.task_id] = "indexed"
+        return R.success(msg="已完成索引")
+
+    _index_status[data.task_id] = "indexing"
+    background_tasks.add_task(_do_index, data.task_id)
+    return R.success(msg="开始索引")
+
+
+@router.get("/chat/status")
+def chat_status(task_id: str):
+    """返回索引状态：idle / indexing / indexed / failed。"""
+    try:
+        # 优先检查内存状态
+        status = _index_status.get(task_id)
+        if status:
+            return R.success(data={"status": status, "indexed": status == "indexed"})
+
+        # 内存没有记录，检查持久化
+        store = VectorStoreManager()
+        indexed = store.is_indexed(task_id)
+        if indexed:
+            _index_status[task_id] = "indexed"
+        return R.success(data={"status": "indexed" if indexed else "idle", "indexed": indexed})
+    except Exception as e:
+        logger.error(f"查询索引状态失败: {e}")
+        return R.success(data={"status": "idle", "indexed": False})
+
+
+@router.post("/chat/ask")
+def ask_question(data: AskRequest):
+    """基于笔记内容的 RAG 问答。"""
+    try:
+        history = [{"role": m.role, "content": m.content} for m in data.history]
+        result = chat_service(
+            task_id=data.task_id,
+            question=data.question,
+            history=history,
+            provider_id=data.provider_id,
+            model_name=data.model_name,
+        )
+        return R.success(data=result)
+    except ValueError as e:
+        return R.error(msg=str(e))
+    except Exception as e:
+        logger.error(f"Chat 问答失败: {e}", exc_info=True)
+        return R.error(msg=f"问答失败: {str(e)}")

backend/app/routers/note.py

@@ -109,6 +109,12 @@ def run_note_task(task_id: str, video_url: str, platform: str, quality: Download
         return
     save_note_to_file(task_id, note)
 
+    # 自动建立向量索引（用于 AI 问答），失败不影响笔记生成
+    try:
+        from app.services.vector_store import VectorStoreManager
+        VectorStoreManager().index_task(task_id)
+    except Exception as e:
+        logger.warning(f"向量索引失败（不影响笔记）: {e}")
 
 
 @router.post('/delete_task')