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https://github.com/JefferyHcool/BiliNote.git
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efadbc267d
实现类似 Google NotebookLM 的效果：笔记生成后自动向量化， 用户可针对笔记内容进行 LLM 问答。 ### 后端 - 新增 VectorStoreManager（ChromaDB），按标题/转录分块建立向量索引 - 新增 chat_service.py RAG 问答：检索相关片段 → 构建 prompt → 调用 LLM - 新增 /chat/index, /chat/ask, /chat/status API 端点 - 笔记生成完成后自动建立向量索引 ### 前端 - 使用 @ant-design/x Bubble.List + Sender 组件构建聊天面板 - 新增 chatStore（Zustand + persist）持久化聊天记录 - MarkdownViewer 右侧嵌入 ChatPanel，通过"AI 问答"按钮切换 - 首次打开自动检查/触发索引，支持重新索引 Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
75 lines
2.0 KiB
Python
75 lines
2.0 KiB
Python
from typing import Optional
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from fastapi import APIRouter
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from pydantic import BaseModel
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from app.services.chat_service import chat as chat_service
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from app.services.vector_store import VectorStoreManager
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from app.utils.logger import get_logger
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from app.utils.response import ResponseWrapper as R
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logger = get_logger(__name__)
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router = APIRouter()
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class IndexRequest(BaseModel):
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task_id: str
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class ChatMessage(BaseModel):
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role: str
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content: str
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class AskRequest(BaseModel):
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task_id: str
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question: str
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history: list[ChatMessage] = []
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provider_id: str
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model_name: str
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@router.post("/chat/index")
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def index_task(data: IndexRequest):
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"""为笔记建立向量索引。"""
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try:
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store = VectorStoreManager()
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store.index_task(data.task_id)
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return R.success(msg="索引完成")
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except Exception as e:
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logger.error(f"索引失败: {e}")
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return R.error(msg=f"索引失败: {str(e)}")
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@router.get("/chat/status")
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def chat_status(task_id: str):
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"""检查笔记是否已建立向量索引。"""
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try:
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store = VectorStoreManager()
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indexed = store.is_indexed(task_id)
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return R.success(data={"indexed": indexed})
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except Exception as e:
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logger.error(f"查询索引状态失败: {e}")
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return R.success(data={"indexed": False})
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@router.post("/chat/ask")
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def ask_question(data: AskRequest):
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"""基于笔记内容的 RAG 问答。"""
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try:
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history = [{"role": m.role, "content": m.content} for m in data.history]
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result = chat_service(
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task_id=data.task_id,
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question=data.question,
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history=history,
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provider_id=data.provider_id,
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model_name=data.model_name,
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)
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return R.success(data=result)
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except ValueError as e:
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return R.error(msg=str(e))
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except Exception as e:
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logger.error(f"Chat 问答失败: {e}", exc_info=True)
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return R.error(msg=f"问答失败: {str(e)}")
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