From c7b0cfb92b2ca68d4181669d0334930249fdda2f Mon Sep 17 00:00:00 2001 From: gavindiaz Date: Sat, 24 Oct 2026 03:12:20 +0800 Subject: [PATCH] feat: add BookMate AI reading workspace and full EPUB reader --- .gitignore | 68 +- README.md | 53 +- backend/.env.example | 15 + AGENTS.md => backend/AGENTS.md | 0 backend/app/__init__.py | 0 backend/app/api/__init__.py | 0 backend/app/api/books.py | 146 + backend/app/api/chat.py | 356 ++ backend/app/api/models.py | 183 + backend/app/core/__init__.py | 0 backend/app/core/config.py | 43 + backend/app/core/database.py | 33 + backend/app/epub/__init__.py | 0 backend/app/epub/cfi.py | 37 + backend/app/epub/chunker.py | 97 + backend/app/epub/cleaner.py | 187 + backend/app/epub/parser.py | 207 + backend/app/epub/toc.py | 216 + backend/app/llm/__init__.py | 0 backend/app/llm/hub.py | 277 ++ backend/app/main.py | 42 + backend/app/models/__init__.py | 0 backend/app/models/ai_model.py | 28 + backend/app/models/book.py | 60 + backend/app/models/chat.py | 43 + backend/app/rag/__init__.py | 0 backend/app/rag/engine.py | 286 ++ backend/app/rag/vector.py | 218 + backend/app/schemas/__init__.py | 0 backend/app/schemas/book.py | 56 + backend/requirements.txt | 16 + backend/test_book_file.py | 57 + frontend/.gitignore | 41 + frontend/AGENTS.md | 9 + frontend/README.md | 36 + .../eslint.config.mjs | 0 next.config.ts => frontend/next.config.ts | 4 +- .../package-lock.json | 3510 ++++++++++++++++- package.json => frontend/package.json | 17 +- {public => frontend/public}/file.svg | 0 {public => frontend/public}/globe.svg | 0 {public => frontend/public}/next.svg | 0 {public => frontend/public}/vercel.svg | 0 {public => frontend/public}/window.svg | 0 {src => frontend/src}/app/favicon.ico | Bin frontend/src/app/globals.css | 128 + frontend/src/app/layout.tsx | 15 + frontend/src/app/page.tsx | 899 +++++ .../src/components/CitationReaderDialog.tsx | 112 + frontend/src/components/CodeBlock.tsx | 42 + frontend/src/components/EpubReader.tsx | 195 + frontend/src/components/MarkdownRenderer.tsx | 130 + frontend/src/components/MermaidDiagram.tsx | 55 + frontend/src/components/MindMap.tsx | 494 +++ .../src/components/ModelManagerDialog.tsx | 469 +++ frontend/src/lib/api.ts | 183 + tsconfig.json => frontend/tsconfig.json | 0 src/app/globals.css | 26 - src/app/layout.tsx | 29 - src/app/page.tsx | 69 - 60 files changed, 8996 insertions(+), 191 deletions(-) create mode 100644 backend/.env.example rename AGENTS.md => backend/AGENTS.md (100%) create mode 100644 backend/app/__init__.py create mode 100644 backend/app/api/__init__.py create mode 100644 backend/app/api/books.py create mode 100644 backend/app/api/chat.py create mode 100644 backend/app/api/models.py create mode 100644 backend/app/core/__init__.py create mode 100644 backend/app/core/config.py create mode 100644 backend/app/core/database.py create mode 100644 backend/app/epub/__init__.py create mode 100644 backend/app/epub/cfi.py create mode 100644 backend/app/epub/chunker.py create mode 100644 backend/app/epub/cleaner.py create mode 100644 backend/app/epub/parser.py create mode 100644 backend/app/epub/toc.py create mode 100644 backend/app/llm/__init__.py create mode 100644 backend/app/llm/hub.py create mode 100644 backend/app/main.py create mode 100644 backend/app/models/__init__.py create mode 100644 backend/app/models/ai_model.py create mode 100644 backend/app/models/book.py create mode 100644 backend/app/models/chat.py create mode 100644 backend/app/rag/__init__.py create mode 100644 backend/app/rag/engine.py create mode 100644 backend/app/rag/vector.py create mode 100644 backend/app/schemas/__init__.py create mode 100644 backend/app/schemas/book.py create mode 100644 backend/requirements.txt create mode 100644 backend/test_book_file.py create mode 100644 frontend/.gitignore create mode 100644 frontend/AGENTS.md create mode 100644 frontend/README.md rename eslint.config.mjs => frontend/eslint.config.mjs (100%) rename next.config.ts => frontend/next.config.ts (82%) rename package-lock.json => frontend/package-lock.json (63%) rename package.json => frontend/package.json (56%) rename {public => frontend/public}/file.svg (100%) rename {public => frontend/public}/globe.svg (100%) rename {public => frontend/public}/next.svg (100%) rename {public => frontend/public}/vercel.svg (100%) rename {public => frontend/public}/window.svg (100%) rename {src => frontend/src}/app/favicon.ico (100%) create mode 100644 frontend/src/app/globals.css create mode 100644 frontend/src/app/layout.tsx create mode 100644 frontend/src/app/page.tsx create mode 100644 frontend/src/components/CitationReaderDialog.tsx create mode 100644 frontend/src/components/CodeBlock.tsx create mode 100644 frontend/src/components/EpubReader.tsx create mode 100644 frontend/src/components/MarkdownRenderer.tsx create mode 100644 frontend/src/components/MermaidDiagram.tsx create mode 100644 frontend/src/components/MindMap.tsx create mode 100644 frontend/src/components/ModelManagerDialog.tsx create mode 100644 frontend/src/lib/api.ts rename tsconfig.json => frontend/tsconfig.json (100%) delete mode 100644 src/app/globals.css delete mode 100644 src/app/layout.tsx delete mode 100644 src/app/page.tsx diff --git a/.gitignore b/.gitignore index 5ef6a52..1beff95 100644 --- a/.gitignore +++ b/.gitignore @@ -1,41 +1,37 @@ -# See https://help.github.com/articles/ignoring-files/ for more about ignoring files. - -# dependencies -/node_modules -/.pnp -.pnp.* -.yarn/* -!.yarn/patches -!.yarn/plugins -!.yarn/releases -!.yarn/versions - -# testing -/coverage - -# next.js -/.next/ -/out/ - -# production -/build - -# misc -.DS_Store +# Local configuration and credentials +.env +.env.* +!.env.example *.pem +*.key -# debug -npm-debug.log* -yarn-debug.log* -yarn-error.log* -.pnpm-debug.log* +# Python +.venv/ +venv/ +__pycache__/ +*.py[cod] +.pytest_cache/ -# env files (can opt-in for committing if needed) -.env* - -# vercel -.vercel - -# typescript +# Dependencies and generated output +node_modules/ +.next/ +out/ +build/ +coverage/ *.tsbuildinfo next-env.d.ts + +# Local application data (includes book files and saved model credentials) +backend/data/ +backend/uploads/ +*.db +*.db-* +*.sqlite* +*.epub + +# Local tooling +.idea/ +.vscode/ +.DS_Store +Thumbs.db +*.log diff --git a/README.md b/README.md index e215bc4..e94e674 100644 --- a/README.md +++ b/README.md @@ -1,36 +1,45 @@ -This is a [Next.js](https://nextjs.org) project bootstrapped with [`create-next-app`](https://nextjs.org/docs/app/api-reference/cli/create-next-app). +# BookMate -## Getting Started +基于 FastAPI 和 Next.js 的 AI 读书助手。支持 EPUB 导入、围绕书籍内容对话、原文引用和完整 EPUB 网页阅读。 -First, run the development server: +## 本地启动 -```bash -npm run dev -# or -yarn dev -# or -pnpm dev -# or -bun dev +后端（Python 3.12）： + +```powershell +cd backend +python -m venv .venv +.venv/Scripts/python.exe -m pip install -r requirements.txt +Copy-Item .env.example .env +.venv/Scripts/python.exe -m uvicorn app.main:app --host 0.0.0.0 --port 8000 --reload ``` -Open [http://localhost:3000](http://localhost:3000) with your browser to see the result. +在 `.env` 配置模型 API，或启动后在网页的模型管理中添加模型。数据库和上传目录会自动创建。未配置向量服务时使用关键词检索。 -You can start editing the page by modifying `app/page.tsx`. The page auto-updates as you edit the file. +另开终端启动前端（Node.js 20.9+）： -This project uses [`next/font`](https://nextjs.org/docs/app/building-your-application/optimizing/fonts) to automatically optimize and load [Geist](https://vercel.com/font), a new font family for Vercel. +```powershell +cd frontend +npm ci +npm run dev +``` -## Learn More +访问 http://localhost:3000。前端默认连接 http://localhost:8000/api。 -To learn more about Next.js, take a look at the following resources: +## 阅读与对话 -- [Next.js Documentation](https://nextjs.org/docs) - learn about Next.js features and API. -- [Learn Next.js](https://nextjs.org/learn) - an interactive Next.js tutorial. +导入 EPUB 后，在书架或聊天页面点击「阅读全书」。阅读器支持目录、翻页、字号调整，以及在当前浏览器保存阅读位置。选中文字后可将原文带入 AI 聊天输入框。 -You can check out [the Next.js GitHub repository](https://github.com/vercel/next.js) - your feedback and contributions are welcome! +## 验证 -## Deploy on Vercel +```powershell +cd backend +.venv/Scripts/python.exe -B -m unittest test_book_file +``` -The easiest way to deploy your Next.js app is to use the [Vercel Platform](https://vercel.com/new?utm_medium=default-template&filter=next.js&utm_source=create-next-app&utm_campaign=create-next-app-readme) from the creators of Next.js. +```powershell +cd frontend +npm run build +``` -Check out our [Next.js deployment documentation](https://nextjs.org/docs/app/building-your-application/deploying) for more details. +本地 `.env`、模型凭据、数据库、上传书籍和构建产物不纳入版本控制。 diff --git a/backend/.env.example b/backend/.env.example new file mode 100644 index 0000000..fd79e01 --- /dev/null +++ b/backend/.env.example @@ -0,0 +1,15 @@ +# Optional: configure providers here, or add a model from the web UI. +OPENAI_API_KEY= +OPENAI_BASE_URL=https://api.openai.com/v1 +OPENAI_MODEL=gpt-4o + +ANTHROPIC_API_KEY= +ANTHROPIC_MODEL=claude-sonnet-4-20250514 + +DEEPSEEK_API_KEY= +DEEPSEEK_BASE_URL=https://api.deepseek.com/v1 +DEEPSEEK_MODEL=deepseek-chat + +# Optional embedding/reranking; empty keys use keyword retrieval. +EMBEDDING_API_KEY= +RERANK_API_KEY= diff --git a/AGENTS.md b/backend/AGENTS.md similarity index 100% rename from AGENTS.md rename to backend/AGENTS.md diff --git a/backend/app/__init__.py b/backend/app/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/backend/app/api/__init__.py b/backend/app/api/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/backend/app/api/books.py b/backend/app/api/books.py new file mode 100644 index 0000000..379a764 --- /dev/null +++ b/backend/app/api/books.py @@ -0,0 +1,146 @@ +import os +import uuid +from pathlib import Path +import aiofiles +from fastapi import APIRouter, UploadFile, File, Depends, HTTPException, BackgroundTasks +from fastapi.responses import FileResponse +from sqlalchemy.ext.asyncio import AsyncSession +from sqlalchemy import select, func + +from app.core.database import get_db, async_session +from app.core.config import settings +from app.models.book import Book, Chapter, Segment +from app.schemas.book import BookOut, BookDetailOut, ChapterOut, SegmentOut +from app.epub.parser import parse_epub +from app.rag.vector import ensure_embeddings + +router = APIRouter(prefix="/books", tags=["books"]) + + +async def _embed_book_in_background(book_id: str): + """上传后后台批量生成向量；失败时状态记 failed，首次对话会懒补。""" + async with async_session() as session: + try: + await ensure_embeddings(session, book_id) + except Exception: + pass + + +@router.post("", response_model=BookOut) +async def upload_book( + file: UploadFile = File(...), + db: AsyncSession = Depends(get_db), + background_tasks: BackgroundTasks = BackgroundTasks(), +): + if not file.filename or not file.filename.lower().endswith(".epub"): + raise HTTPException(400, "仅支持 .epub 文件") + + upload_dir = settings.upload_path + ext = ".epub" + filename = f"{uuid.uuid4().hex}{ext}" + file_path = upload_dir / filename + async with aiofiles.open(file_path, "wb") as f: + content = await file.read() + await f.write(content) + + try: + book = await parse_epub(str(file_path), db) + await db.commit() + await db.refresh(book) + background_tasks.add_task(_embed_book_in_background, book.id) + return book + except ValueError as e: + os.remove(file_path) + raise HTTPException(409, str(e)) + except Exception as e: + os.remove(file_path) + raise HTTPException(500, f"解析失败: {str(e)}") + + +@router.get("", response_model=list[BookOut]) +async def list_books(db: AsyncSession = Depends(get_db)): + result = await db.execute(select(Book).order_by(Book.created_at.desc())) + return result.scalars().all() + + +@router.get("/{book_id}", response_model=BookDetailOut) +async def get_book(book_id: str, db: AsyncSession = Depends(get_db)): + book = await db.get(Book, book_id) + if not book: + raise HTTPException(404, "书不存在") + + ch_count = await db.scalar( + select(func.count()).select_from(Chapter).where(Chapter.book_id == book_id) + ) + seg_count = await db.scalar( + select(func.count()).select_from(Segment).where(Segment.book_id == book_id) + ) + + return BookDetailOut( + id=book.id, + filename=book.filename, + title=book.title, + author=book.author, + language=book.language, + char_count=book.char_count, + status=book.status, + created_at=book.created_at, + chapter_count=ch_count or 0, + segment_count=seg_count or 0, + ) + + +@router.get("/{book_id}/chapters", response_model=list[ChapterOut]) +async def get_chapters(book_id: str, db: AsyncSession = Depends(get_db)): + book = await db.get(Book, book_id) + if not book: + raise HTTPException(404, "书不存在") + result = await db.execute( + select(Chapter).where(Chapter.book_id == book_id).order_by(Chapter.order_idx) + ) + return result.scalars().all() + + +@router.get("/{book_id}/file") +async def read_book_file(book_id: str, db: AsyncSession = Depends(get_db)): + """供浏览器阅读原始 EPUB，保留正文、图片和出版排版。""" + book = await db.get(Book, book_id) + if not book: + raise HTTPException(404, "书不存在") + file_path = Path(book.file_path).resolve() + upload_root = Path(settings.upload_dir).resolve() + if not file_path.is_relative_to(upload_root) or file_path.suffix.lower() != ".epub": + raise HTTPException(404, "书籍文件不可用") + if not file_path.is_file(): + raise HTTPException(404, "原始 EPUB 文件已丢失，请重新导入") + return FileResponse( + file_path, + media_type="application/epub+zip", + headers={"Cache-Control": "private, no-cache", "X-Content-Type-Options": "nosniff"}, + ) + + +@router.get("/{book_id}/segments", response_model=list[SegmentOut]) +async def get_segments(book_id: str, chapter_id: str | None = None, db: AsyncSession = Depends(get_db)): + book = await db.get(Book, book_id) + if not book: + raise HTTPException(404, "书不存在") + q = select(Segment).where(Segment.book_id == book_id) + if chapter_id: + q = q.where(Segment.chapter_id == chapter_id) + q = q.order_by(Segment.order_idx) + result = await db.execute(q) + return result.scalars().all() + + +@router.delete("/{book_id}") +async def delete_book(book_id: str, db: AsyncSession = Depends(get_db)): + book = await db.get(Book, book_id) + if not book: + raise HTTPException(404, "书不存在") + file_path = book.file_path + await db.delete(book) + await db.commit() + if file_path and os.path.exists(file_path): + os.remove(file_path) + return {"deleted": book_id} diff --git a/backend/app/api/chat.py b/backend/app/api/chat.py new file mode 100644 index 0000000..2606788 --- /dev/null +++ b/backend/app/api/chat.py @@ -0,0 +1,356 @@ +import json +import logging +from fastapi import APIRouter, Depends, HTTPException, Query +from fastapi.responses import StreamingResponse +from sqlalchemy.ext.asyncio import AsyncSession +from sqlalchemy import select, func +from pydantic import BaseModel + +from app.core.database import get_db +from app.models.book import Book, Chapter, Segment +from app.models.chat import Conversation, Message +from app.llm.hub import resolve_provider +from app.rag.engine import ( + search_segments, build_chat_prompt, parse_citations, + estimate_tokens, match_chapters, _trim_messages, +) + +logger = logging.getLogger(__name__) + +router = APIRouter(prefix="/chat", tags=["chat"]) + + +class CreateConversationRequest(BaseModel): + book_id: str + title: str | None = None + model: str = "claude" + + +class SendMessageRequest(BaseModel): + content: str + model: str | None = None + # 被重试的用户消息 id：提供时不新建 user 消息，新 AI 回答作为该问题的新版本 + # （parent_message_id 指向它），历史上下文只取该问题之前的对话 + reply_to: str | None = None + + +class ConversationOut(BaseModel): + id: str + book_id: str + title: str | None + model: str + created_at: str + + class Config: + from_attributes = True + + +class MessageOut(BaseModel): + id: str + conversation_id: str + parent_message_id: str | None + role: str + content: str + citations: list | None + model: str | None + created_at: str + + class Config: + from_attributes = True + + +@router.get("/conversations", response_model=list[ConversationOut]) +async def list_conversations(book_id: str | None = None, db: AsyncSession = Depends(get_db)): + q = select(Conversation).order_by(Conversation.updated_at.desc()) + if book_id: + q = q.where(Conversation.book_id == book_id) + result = await db.execute(q) + convs = result.scalars().all() + return [ConversationOut( + id=c.id, book_id=c.book_id, title=c.title, model=c.model, + created_at=c.created_at.isoformat() if c.created_at else "", + ) for c in convs] + + +@router.post("/conversations", response_model=ConversationOut) +async def create_conversation(req: CreateConversationRequest, db: AsyncSession = Depends(get_db)): + book = await db.get(Book, req.book_id) + if not book: + raise HTTPException(404, "书不存在") + conv = Conversation(book_id=req.book_id, title=req.title or f"与《{book.title}》的对话", model=req.model) + db.add(conv) + await db.commit() + await db.refresh(conv) + return ConversationOut( + id=conv.id, book_id=conv.book_id, title=conv.title, model=conv.model, + created_at=conv.created_at.isoformat() if conv.created_at else "", + ) + + +@router.get("/conversations/{conv_id}/messages", response_model=list[MessageOut]) +async def get_messages(conv_id: str, db: AsyncSession = Depends(get_db)): + conv = await db.get(Conversation, conv_id) + if not conv: + raise HTTPException(404, "会话不存在") + result = await db.execute( + select(Message).where(Message.conversation_id == conv_id).order_by(Message.created_at) + ) + msgs = result.scalars().all() + return [_msg_to_out(m) for m in msgs] + + +@router.post("/conversations/{conv_id}/messages") +async def send_message(conv_id: str, req: SendMessageRequest, db: AsyncSession = Depends(get_db)): + conv = await db.get(Conversation, conv_id) + if not conv: + raise HTTPException(404, "会话不存在") + + book = await db.get(Book, conv.book_id) + if not book: + raise HTTPException(404, "书不存在") + + model_name = req.model or conv.model + + # 重试：复用被重试的用户消息（不新建），新回答作为它的新版本 + reply_user: Message | None = None + if req.reply_to: + reply_user = await db.get(Message, req.reply_to) + if not reply_user or reply_user.role != "user" or reply_user.conversation_id != conv_id: + raise HTTPException(400, "reply_to 必须是本会话内的一条用户消息") + user_msg = reply_user + else: + user_msg = Message(conversation_id=conv_id, role="user", content=req.content, model=model_name) + db.add(user_msg) + await db.commit() + + chapters = (await db.execute( + select(Chapter).where(Chapter.book_id == book.id).order_by(Chapter.order_idx) + )).scalars().all() + + # 章节标题匹配：命中章节时把整章原文注入 prompt（解决「第X章讲了什么」这类问题） + matched = match_chapters(list(chapters), req.content) + chapter_segments = [] + if matched: + result = await db.execute( + select(Segment) + .where(Segment.chapter_id.in_([c.id for c in matched])) + .order_by(Segment.order_idx) + ) + chapter_segments = list(result.scalars().all()) + + segments = await search_segments( + db, book.id, req.content, top_k=15, chapters=list(chapters) + ) + + history_rows = (await db.execute( + select(Message).where(Message.conversation_id == conv_id).order_by(Message.created_at) + )).scalars().all() + + # 历史上下文：重试时只取被重试问题之前的对话（旧版本回答不进 prompt）； + # 正常发送时排除当前这轮 user 消息即可。 + if reply_user is not None: + row_ids = {m.id for m in history_rows} + if reply_user.id in row_ids: + idx = next(i for i, m in enumerate(history_rows) if m.id == reply_user.id) + history = [{"role": m.role, "content": m.content} for m in history_rows[:idx]] + else: + # 数据异常（如 SRU），退回为全量历史 + history = [{"role": m.role, "content": m.content} for m in history_rows] + else: + history = [{"role": m.role, "content": m.content} for m in history_rows[:-1]] + + messages = build_chat_prompt( + book, list(chapters), segments, history, req.content, + chapter_segments=chapter_segments, + ) + + total_tokens = estimate_tokens("".join(m["content"] for m in messages)) + provider = await resolve_provider(db, model_name) + if provider is None: + raise HTTPException(400, f"模型 {model_name} 未配置，请先在页面「管理模型」中添加或选择可用模型") + if total_tokens > provider.max_context * 0.8: + # 内容感知裁剪：保留 system（含检索原文 + 整章注入），从最旧历史开始丢 + messages = _trim_messages(messages, int(provider.max_context * 0.8)) + + async def stream_response(): + full_content = "" + try: + async for token in provider.chat_stream(messages, temperature=0.7): + full_content += token + yield f"data: {json.dumps({'type': 'token', 'content': token}, ensure_ascii=False)}\n\n" + except Exception as e: + logger.exception("流式生成失败（conversation=%s）", conv_id) + yield f"data: {json.dumps({'type': 'error', 'content': str(e)}, ensure_ascii=False)}\n\n" + return + + parsed = parse_citations(full_content, segments) + + assistant_msg = Message( + conversation_id=conv_id, + parent_message_id=user_msg.id, + role="assistant", + content=parsed["text"], + citations=json.dumps(parsed["citations"], ensure_ascii=False), + model=model_name, + ) + db.add(assistant_msg) + await db.commit() + await db.refresh(assistant_msg) + + yield f"data: {json.dumps({'type': 'done', 'message_id': assistant_msg.id, 'citations': parsed['citations']}, ensure_ascii=False)}\n\n" + + return StreamingResponse(stream_response(), media_type="text/event-stream") + + +@router.post("/messages/{msg_id}/retry") +async def retry_message(msg_id: str, db: AsyncSession = Depends(get_db)): + msg = await db.get(Message, msg_id) + if not msg or msg.role != "user": + raise HTTPException(400, "只能对用户消息重试") + # 走 reply_to 语义：不新建 user 消息，而是给该问题追加一个新版本回答 + return await send_message( + msg.conversation_id, + SendMessageRequest(content=msg.content, model=msg.model, reply_to=msg.id), + db, + ) + + +@router.get("/segments/{segment_id}/context") +async def segment_context( + segment_id: str, + before: int = Query(2, ge=0, le=6), + after: int = Query(2, ge=0, le=6), + db: AsyncSession = Depends(get_db), +): + """引用段落的阅读上下文：章节标题 + 前后段落，供前端「阅读原文」弹层。""" + seg = await db.get(Segment, segment_id) + if not seg: + raise HTTPException(404, "段落不存在") + ch = await db.get(Chapter, seg.chapter_id) + + prev_rows = await db.execute( + select(Segment.id, Segment.text, Segment.order_idx, Segment.cfi) + .where(Segment.chapter_id == seg.chapter_id, Segment.order_idx < seg.order_idx) + .order_by(Segment.order_idx.desc()) + .limit(before) + ) + next_rows = await db.execute( + select(Segment.id, Segment.text, Segment.order_idx, Segment.cfi) + .where(Segment.chapter_id == seg.chapter_id, Segment.order_idx > seg.order_idx) + .order_by(Segment.order_idx) + .limit(after) + ) + prev_list = [{"id": r[0], "text": r[1], "order_idx": r[2], "cfi": r[3]} for r in prev_rows.all()] + next_list = [{"id": r[0], "text": r[1], "order_idx": r[2], "cfi": r[3]} for r in next_rows.all()] + prev_list.reverse() # 保持阅读顺序 + + return { + "segment": {"id": seg.id, "text": seg.text, "order_idx": seg.order_idx, "cfi": seg.cfi}, + "chapter": {"id": ch.id, "title": ch.title, "level": ch.level} if ch else None, + "before": prev_list, + "after": next_list, + } + + +@router.get("/search") +async def search_book(book_id: str, q: str = Query(min_length=1), db: AsyncSession = Depends(get_db)): + segments = await search_segments(db, book_id, q, top_k=10) + return [ + {"id": s.id, "text": s.text[:300], "cfi": s.cfi, "char_count": s.char_count} + for s in segments + ] + + +@router.delete("/messages/{msg_id}") +async def delete_message(msg_id: str, db: AsyncSession = Depends(get_db)): + msg = await db.get(Message, msg_id) + if not msg: + raise HTTPException(404, "消息不存在") + await db.delete(msg) + await db.commit() + return {"deleted": msg_id} + + +@router.delete("/conversations/{conv_id}") +async def delete_conversation(conv_id: str, db: AsyncSession = Depends(get_db)): + conv = await db.get(Conversation, conv_id) + if not conv: + raise HTTPException(404, "会话不存在") + # ORM cascade="all, delete-orphan" 会一并删除该会话下的所有消息 + await db.delete(conv) + await db.commit() + return {"deleted": conv_id} + + +@router.post("/conversations/{conv_id}/branch") +async def branch_conversation(conv_id: str, from_message_id: str = Query(...), db: AsyncSession = Depends(get_db)): + conv = await db.get(Conversation, conv_id) + if not conv: + raise HTTPException(404, "会话不存在") + branch = Conversation(book_id=conv.book_id, title=f"{conv.title or '对话'} (分支)", model=conv.model) + db.add(branch) + await db.flush() + + result = await db.execute( + select(Message).where(Message.conversation_id == conv_id).order_by(Message.created_at) + ) + msgs = result.scalars().all() + for m in msgs: + new_msg = Message( + conversation_id=branch.id, + role=m.role, + content=m.content, + citations=m.citations, + model=m.model, + ) + db.add(new_msg) + if m.id == from_message_id: + break + await db.commit() + await db.refresh(branch) + return { + "id": branch.id, + "book_id": branch.book_id, + "title": branch.title, + "model": branch.model, + "created_at": branch.created_at.isoformat() if branch.created_at else "", + } + + +@router.get("/conversations/{conv_id}/export") +async def export_conversation(conv_id: str, fmt: str = "markdown", db: AsyncSession = Depends(get_db)): + conv = await db.get(Conversation, conv_id) + if not conv: + raise HTTPException(404, "会话不存在") + result = await db.execute( + select(Message).where(Message.conversation_id == conv_id).order_by(Message.created_at) + ) + msgs = result.scalars().all() + book = await db.get(Book, conv.book_id) + + lines = [f"# {conv.title or '对话'}", f"书籍: {book.title if book else '未知'}\n"] + for m in msgs: + role_label = "🧑 用户" if m.role == "user" else "🤖 AI" + lines.append(f"## {role_label}\n\n{m.content}\n") + if m.citations: + try: + citations = json.loads(m.citations) + for i, c in enumerate(citations): + lines.append(f"> 引用 {i+1}: {c.get('excerpt', '')}\n") + except (json.JSONDecodeError, TypeError): + pass + return {"content": "\n".join(lines), "format": fmt, "title": conv.title} + + +def _msg_to_out(m: Message) -> MessageOut: + citations = None + if m.citations: + try: + citations = json.loads(m.citations) + except (json.JSONDecodeError, TypeError): + citations = None + return MessageOut( + id=m.id, conversation_id=m.conversation_id, parent_message_id=m.parent_message_id, + role=m.role, content=m.content, citations=citations, model=m.model, + created_at=m.created_at.isoformat() if m.created_at else "", + ) \ No newline at end of file diff --git a/backend/app/api/models.py b/backend/app/api/models.py new file mode 100644 index 0000000..df80777 --- /dev/null +++ b/backend/app/api/models.py @@ -0,0 +1,183 @@ +import httpx +from fastapi import APIRouter, Depends, HTTPException +from pydantic import BaseModel +from sqlalchemy import select +from sqlalchemy.ext.asyncio import AsyncSession + +from app.core.database import get_db +from app.models.ai_model import AiModel +from app.llm.hub import builtin_models, resolve_provider, _mask_key + +router = APIRouter(prefix="/models", tags=["models"]) + + +class AddModelRequest(BaseModel): + label: str + kind: str = "openai_compatible" # openai_compatible | anthropic + base_url: str = "" + api_key: str = "" + model_id: str + + +class UpdateModelRequest(BaseModel): + label: str | None = None + kind: str | None = None + base_url: str | None = None + api_key: str | None = None + model_id: str | None = None + + +class ImportModelsRequest(BaseModel): + api_key: str + base_url: str = "https://openrouter.ai/api/v1" + + +class ImportOpenRouterRequest(BaseModel): + api_key: str + base_url: str = "https://openrouter.ai/api/v1" + + +OPENROUTER_BLOCKLIST = { + # 一些非文本/量级过大的模型 id 特征，导入时快速排除 + "image", "tts", "whisper", "embed", "rerank", "moderation", "dall-e", "flux", "playground", +} + + +def _to_out(m: AiModel) -> dict: + return { + "name": m.name, + "label": m.label, + "kind": m.kind, + "base_url": m.base_url, + "api_key_masked": _mask_key(m.api_key), + "model_id": m.model_id, + "builtin": False, + } + + +@router.get("") +async def list_models(db: AsyncSession = Depends(get_db)): + """内置（.env）+ 用户自定义（DB）模型列表。api_key 只回显掩码。""" + result = await db.execute(select(AiModel).order_by(AiModel.sort_order, AiModel.created_at)) + custom = [_to_out(m) for m in result.scalars().all()] + return builtin_models() + custom + + +@router.post("") +async def add_model(req: AddModelRequest, db: AsyncSession = Depends(get_db)): + label = (req.label or "").strip() or req.model_id + # name = 请求模型 id；冲突时追加序号（-2, -3 ...） + base_name = req.model_id.strip() or "custom-model" + name = base_name + suffix = 1 + while True: + exists = (await db.execute(select(AiModel.id).where(AiModel.name == name))).scalar() + if exists is None: + break + suffix += 1 + name = f"{base_name}-{suffix}" + row = AiModel( + name=name, label=label, kind=req.kind, + base_url=(req.base_url or "").strip(), api_key=(req.api_key or "").strip(), + model_id=req.model_id.strip(), sort_order=100, + ) + db.add(row) + await db.commit() + await db.refresh(row) + return _to_out(row) + + +@router.put("/{name}") +async def update_model(name: str, req: UpdateModelRequest, db: AsyncSession = Depends(get_db)): + for m in builtin_models(): + if m["name"] == name: + raise HTTPException(400, "内置模型不可修改，请在页面添加同名模型") + row = (await db.execute(select(AiModel).where(AiModel.name == name))).scalar() + if not row: + raise HTTPException(404, "模型不存在") + if req.label is not None: + row.label = req.label.strip() or row.label + if req.kind is not None: + row.kind = req.kind + if req.base_url is not None: + row.base_url = req.base_url.strip() + if req.api_key is not None: + row.api_key = req.api_key.strip() + if req.model_id is not None: + row.model_id = req.model_id.strip() + await db.commit() + await db.refresh(row) + return _to_out(row) + + +@router.delete("/{name}") +async def delete_model(name: str, db: AsyncSession = Depends(get_db)): + for m in builtin_models(): + if m["name"] == name: + raise HTTPException(400, "内置模型不可删除") + row = (await db.execute(select(AiModel).where(AiModel.name == name))).scalar() + if not row: + raise HTTPException(404, "模型不存在") + await db.delete(row) + await db.commit() + return {"deleted": name} + + +@router.post("/{name}/test") +async def test_model(name: str, db: AsyncSession = Depends(get_db)): + """用该模型的配置发一条极短请求，验证 base_url/api_key/model_id 是否可用。""" + provider = await resolve_provider(db, name) + if provider is None: + raise HTTPException(404, "模型不存在") + try: + resp = await provider.chat( + [{"role": "user", "content": "hi"}], + temperature=0, + ) + return {"ok": True, "model": resp.model, "reply": resp.content[:80]} + except Exception as e: + return {"ok": False, "error": f"{type(e).__name__}: {e}"} + + +@router.post("/import") +async def import_models(req: ImportModelsRequest): + """通用 OpenAI 兼容 /models 拉取（OpenRouter / 硅基流动 / SenseNova / 任取 base_url）， + 供前端挑选后批量添加（不落库）。""" + key = (req.api_key or "").strip() + if not key: + raise HTTPException(400, "需要 API Key") + base = (req.base_url or "").strip().rstrip("/") + if not base: + raise HTTPException(400, "需要 Base URL") + try: + async with httpx.AsyncClient(timeout=30) as client: + resp = await client.get( + f"{base}/models", + headers={"Authorization": f"Bearer {key}"}, + ) + if resp.status_code >= 400: + raise HTTPException(resp.status_code, f"OpenRouter 返回 {resp.status_code}: {resp.text[:200]}") + data = resp.json() + except httpx.HTTPError as e: + raise HTTPException(502, f"请求模型列表失败: {type(e).__name__}: {e}") + except HTTPException: + raise + except Exception as e: + raise HTTPException(502, f"解析模型列表失败: {e}") + + models = [] + for m in data.get("data", []): + mid = (m.get("id") or "").strip() + if not mid: + continue + low = mid.lower() + if any(b in low for b in OPENROUTER_BLOCKLIST): + continue + models.append({"id": mid, "name": (m.get("name") or mid)}) + return {"models": models, "count": len(models)} + + +@router.post("/import-openrouter") +async def import_openrouter_models(req: ImportOpenRouterRequest, db: AsyncSession = Depends(get_db)): + """兼容旧调用：等价于通用 /import（默认 base_url = OpenRouter）。""" + return await import_models(ImportModelsRequest(api_key=req.api_key, base_url=req.base_url)) \ No newline at end of file diff --git a/backend/app/core/__init__.py b/backend/app/core/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/backend/app/core/config.py b/backend/app/core/config.py new file mode 100644 index 0000000..22beff1 --- /dev/null +++ b/backend/app/core/config.py @@ -0,0 +1,43 @@ +from pydantic_settings import BaseSettings +from pathlib import Path + +BASE_DIR = Path(__file__).resolve().parent.parent.parent + + +class Settings(BaseSettings): + database_url: str = f"sqlite+aiosqlite:///{BASE_DIR / 'data' / 'bookmate.db'}" + upload_dir: str = str(BASE_DIR / "uploads") + data_dir: str = str(BASE_DIR / "data") + api_host: str = "0.0.0.0" + api_port: int = 8000 + + # ===== 向量检索 & 重排（OpenAI 兼容 API，如硅基流动 SiliconFlow）===== + # embedding_base_url: 支持 OpenAI 兼容 /embeddings 的端点前缀 + embedding_base_url: str = "https://api.siliconflow.cn/v1" + embedding_api_key: str = "" # 留空则自动降级为纯关键词检索 + embedding_model: str = "BAAI/bge-m3" # 1024 维 + # rerank: 硅基流动使用 /v1/rerank，OpenAI 不提供；留空则跳过重排 + rerank_base_url: str = "https://api.siliconflow.cn/v1" + rerank_api_key: str = "" + rerank_model: str = "BAAI/bge-reranker-v2-m3" + embedding_batch_size: int = 64 + + @property + def upload_path(self) -> Path: + p = Path(self.upload_dir) + p.mkdir(parents=True, exist_ok=True) + return p + + @property + def data_path(self) -> Path: + p = Path(self.data_dir) + p.mkdir(parents=True, exist_ok=True) + return p + + class Config: + env_file = ".env" + env_file_encoding = "utf-8" + extra = "ignore" + + +settings = Settings() \ No newline at end of file diff --git a/backend/app/core/database.py b/backend/app/core/database.py new file mode 100644 index 0000000..6cc464d --- /dev/null +++ b/backend/app/core/database.py @@ -0,0 +1,33 @@ +from sqlalchemy.ext.asyncio import AsyncSession, create_async_engine, async_sessionmaker +from sqlalchemy.orm import DeclarativeBase +from app.core.config import settings + +settings.data_path.mkdir(parents=True, exist_ok=True) +settings.upload_path.mkdir(parents=True, exist_ok=True) + +engine = create_async_engine(settings.database_url, echo=False) +async_session = async_sessionmaker(engine, class_=AsyncSession, expire_on_commit=False) + + +class Base(DeclarativeBase): + pass + + +async def init_db(): + async with engine.begin() as conn: + await conn.run_sync(Base.metadata.create_all) + await _migrate() + + +async def _migrate(): + """轻量迁移：SQLite 下给已有 segments 表补 embedding 列（create_all 不会改老表）。""" + async with engine.begin() as conn: + rows = (await conn.exec_driver_sql("PRAGMA table_info(segments)")).all() + cols = {row[1] for row in rows} + if rows and "embedding" not in cols: + await conn.exec_driver_sql("ALTER TABLE segments ADD COLUMN embedding TEXT") + + +async def get_db(): + async with async_session() as session: + yield session \ No newline at end of file diff --git a/backend/app/epub/__init__.py b/backend/app/epub/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/backend/app/epub/cfi.py b/backend/app/epub/cfi.py new file mode 100644 index 0000000..45eaf65 --- /dev/null +++ b/backend/app/epub/cfi.py @@ -0,0 +1,37 @@ +import hashlib + + +def make_cfi(spine_index: int, file_href: str, element_id: str = "") -> str: + """生成 CFI（Canonical Fragment Identifier） + 格式: epubi://title/spine_index/file_href!element_id + """ + clean_href = file_href.split("#")[0] + cfi = f"epubi://book/{spine_index}/{clean_href}" + if element_id: + cfi += f"!{element_id}" + return cfi + + +def make_element_id(text: str, index: int) -> str: + """基于文本内容和索引用哈希生成稳定 ID""" + short_hash = hashlib.md5(f"{text[:100]}{index}".encode()).hexdigest()[:8] + return f"seg-{index:04d}-{short_hash}" + + +def parse_cfi(cfi: str) -> dict | None: + """解析 CFI 字符串，返回各组成部分""" + if not cfi.startswith("epubi://"): + return None + try: + rest = cfi[len("epubi://book/"):] + parts = rest.split("/", 2) + spine_index = int(parts[0]) + file_href = parts[1] if len(parts) > 1 else "" + fragment = parts[2] if len(parts) > 2 else "" + return { + "spine_index": spine_index, + "file_href": file_href, + "fragment": fragment.lstrip("!"), + } + except (ValueError, IndexError): + return None \ No newline at end of file diff --git a/backend/app/epub/chunker.py b/backend/app/epub/chunker.py new file mode 100644 index 0000000..5060852 --- /dev/null +++ b/backend/app/epub/chunker.py @@ -0,0 +1,97 @@ +import re + + +def chunk_paragraphs( + paragraphs: list[dict], + heading_path: str, + cfi_base: str, + target_chars: int = 1500, + max_chars: int = 4000, + min_chars: int = 200, +) -> list[dict]: + """将段落列表按语义边界聚类，不按固定字符数切。 + + 策略： + - 章节总字数 < target_chars: 整章一块 + - otherwise: 按段落聚类，目标 target_chars/块，允许±50%浮动 + """ + total_chars = sum(len(p["text"]) for p in paragraphs) + if total_chars <= target_chars: + merged_text = "\n\n".join(p["text"] for p in paragraphs) + prefix = f"《heading_path》" if heading_path else "" + return [{ + "text": f"{prefix}\n{merged_text}" if prefix else merged_text, + "char_count": len(merged_text), + "cfi": cfi_base, + "heading_path": heading_path, + }] + + chunks = [] + buf = [] + buf_chars = 0 + + def flush(): + nonlocal buf_chars + if not buf: + return + merged = "\n\n".join(p["text"] for p in buf) + prefix = f"《heading_path》" if heading_path else "" + text = f"{prefix}\n{merged}" if prefix else merged + chunks.append({ + "text": text, + "char_count": len(merged), + "cfi": cfi_base, + "heading_path": heading_path, + }) + buf.clear() + buf_chars = 0 + + for i, p in enumerate(paragraphs): + p_chars = len(p["text"]) + + if p["tag"] in ("h1", "h2", "h3", "h4"): + flush() + prefix = f"《heading_path》" if heading_path else "" + text = f"{prefix}\n{p['text']}" if prefix else p["text"] + chunks.append({ + "text": text, + "char_count": p_chars, + "cfi": cfi_base, + "heading_path": heading_path, + }) + continue + + if buf_chars + p_chars > target_chars * 1.5: + flush() + + buf.append(p) + buf_chars += p_chars + + flush() + + for i in range(len(chunks)): + chunks[i]["cfi"] = f"{cfi_base}!chunk-{i:04d}" + + return chunks + + +def chapter_to_chunks( + paragraphs: list[dict], + heading_path: str, + cfi_start: str, + book_char_total: int, +) -> list[dict]: + """根据书的总规模决定切块策略""" + if book_char_total < 50_000: + target = 2000 + elif book_char_total < 500_000: + target = 1500 + else: + target = 1000 + + return chunk_paragraphs( + paragraphs, + heading_path=heading_path, + cfi_base=cfi_start, + target_chars=target, + ) \ No newline at end of file diff --git a/backend/app/epub/cleaner.py b/backend/app/epub/cleaner.py new file mode 100644 index 0000000..858345c --- /dev/null +++ b/backend/app/epub/cleaner.py @@ -0,0 +1,187 @@ +import re +from bs4 import BeautifulSoup, Tag + + +BLACKLIST_PATTERNS = [ + (re.compile(r"^\s*目\s*录\s*$"), True), + (re.compile(r"^\s*Contents\b", re.I), True), + (re.compile(r"^\s*Table of Contents", re.I), True), + (re.compile(r"版权所有"), True), + (re.compile(r"Copyright\s*\d{4}", re.I), True), + (re.compile(r"ISBN[\s:\-]*\d"), True), + (re.compile(r"版\s*权\s*页"), True), + (re.compile(r"^\s*[·\-\—\*_=]{3,}\s*$"), True), + (re.compile(r"^\s*序\s*言\s*$"), True), + (re.compile(r"^\s*前\s*言\s*$"), True), + (re.compile(r"^\s*致\s*谢\s*$"), True), + (re.compile(r"^\s*后\s*记\s*$"), True), + (re.compile(r"^\s*译者序\s*$"), True), +] + +SKIP_TAGS = {"script", "style", "nav", "head", "meta", "link", "br"} + +SENTENCE_ENDERS = re.compile(r"[。！？；…）」』】>）\)\"\"]$") +ENGLISH_SENTENCE_ENDERS = re.compile(r"[.!?;\"]$") + + +def clean_html(html_bytes: bytes, fix_wraps: bool = True) -> str: + soup = BeautifulSoup(html_bytes, "lxml") + + for tag_name in SKIP_TAGS: + for tag in soup.find_all(tag_name): + tag.decompose() + + body = soup.find("body") or soup + text = body.get_text("\n", strip=False) + lines = [line.strip() for line in text.split("\n") if line.strip()] + + lines = _filter_boilerplate(lines) + if fix_wraps: + lines = _fix_chinese_wraps(lines) + + return "\n\n".join(lines) + + +def extract_paragraphs(html_bytes: bytes, fix_wraps: bool = True) -> list[dict]: + """从 HTML 中提取段落列表，返回 [{text, tag, has_children}]""" + soup = BeautifulSoup(html_bytes, "lxml") + for tag_name in SKIP_TAGS: + for tag in soup.find_all(tag_name): + tag.decompose() + + body = soup.find("body") or soup + paragraphs = [] + + for el in body.descendants: + if not isinstance(el, Tag): + continue + if el.name in SKIP_TAGS: + continue + if not el.name or el.name in ("html", "head", "body", "div", "span", "section", "article", "main"): + continue + + text = el.get_text(" ", strip=True) + if not text or len(text) < 2: + continue + + if el.name in ("table",): + text = _table_to_markdown(el) + elif el.name in ("blockquote",): + text = "> " + text.replace("\n", "\n> ") + + paragraphs.append({ + "text": text, + "tag": el.name, + "has_children": bool(el.find_all()), + }) + + if fix_wraps: + paragraphs = _fix_paragraph_wraps(paragraphs) + + return paragraphs + + +def _filter_boilerplate(lines: list[str]) -> list[str]: + result = [] + for line in lines: + stripped = re.sub(r"\s+", "", line) + if len(stripped) < 15: + continue + if any(pattern.search(stripped) for pattern, _ in BLACKLIST_PATTERNS): + continue + result.append(line) + return result + + +def _fix_chinese_wraps(lines: list[str]) -> list[str]: + """中文断行修复：末字非句末标点时，与下一行合并""" + if not lines: + return lines + result = [] + buf = "" + for line in lines: + line = line.strip() + if not line: + if buf: + result.append(buf) + buf = "" + continue + if not buf: + buf = line + continue + if SENTENCE_ENDERS.search(buf[-1]): + result.append(buf) + buf = line + else: + buf += line + if buf: + result.append(buf) + return [r for r in result if r] + + +def _fix_paragraph_wraps(paragraphs: list[dict]) -> list[dict]: + """段落级别的断行修复，合并被拆分的段落""" + if not paragraphs: + return paragraphs + merged = [] + buf = paragraphs[0] + for p in paragraphs[1:]: + if not buf["text"]: + buf = p + continue + if SENTENCE_ENDERS.search(buf["text"][-1:]): + merged.append(buf) + buf = p + elif len(buf["text"]) < 50 and not SENTENCE_ENDERS.search(buf["text"][-1:]): + buf["text"] = buf["text"] + p["text"] + else: + merged.append(buf) + buf = p + if buf["text"]: + merged.append(buf) + return merged + + +def _table_to_markdown(table_tag) -> str: + rows = [] + for tr in table_tag.find_all("tr"): + cells = [c.get_text(" ", strip=True) for c in tr.find_all(["td", "th"])] + rows.append(cells) + if not rows: + return "" + col_count = max(len(r) for r in rows) + for r in rows: + while len(r) < col_count: + r.append("") + col_widths = [max(len(r[i]) for r in rows) for i in range(col_count)] + lines = [] + for i, row in enumerate(rows): + line = "| " + " | ".join(cell.ljust(w) for cell, w in zip(row, col_widths)) + " |" + lines.append(line) + if i == 0: + sep = "|" + "|".join("-" * (w + 2) for w in col_widths) + "|" + lines.append(sep) + return "\n".join(lines) + + +def detect_quality(text: str) -> tuple[int, list[str]]: + """检测文本提取质量，返回 (score 0-100, issues)""" + score = 100 + issues = [] + lines = [l for l in text.split("\n") if l.strip()] + short_count = sum(1 for l in lines if len(l) < 10 and len(l) > 0) + if short_count > len(lines) * 0.3: + score -= 30 + issues.append("大量短行，可能是伪 EPUB") + + fullwidth = len(re.findall(r"[\u4e00-\u9fff]", text)) + ascii_chars = len(re.findall(r"[a-zA-Z]", text)) + if fullwidth + ascii_chars == 0: + score -= 50 + issues.append("无有效文本内容") + + if len(text) < 100 and fullwidth == 0: + score -= 40 + issues.append("文本过短") + + return max(score, 0), issues \ No newline at end of file diff --git a/backend/app/epub/parser.py b/backend/app/epub/parser.py new file mode 100644 index 0000000..50b13ae --- /dev/null +++ b/backend/app/epub/parser.py @@ -0,0 +1,207 @@ +import zipfile +import hashlib +import os +from lxml import etree +from sqlalchemy.ext.asyncio import AsyncSession + +from app.models.book import Book, Chapter, Segment +from app.epub.toc import ( + parse_toc_tree, flatten_headings, build_heading_paths, + href_to_fragment, NS, _read_opf, _resolve_path, _dirname, +) +from app.epub.cleaner import extract_paragraphs, clean_html, detect_quality +from app.epub.chunker import chapter_to_chunks +from app.epub.cfi import make_cfi, make_element_id + + +async def parse_epub(file_path: str, db: AsyncSession) -> Book: + """完整解析 EPUB，写入数据库，返回 Book 对象""" + file_hash = _hash_file(file_path) + + existing = await db.execute( + __import__("sqlalchemy").select(Book).where(Book.file_hash == file_hash) + ) + if existing.scalar_one_or_none(): + raise ValueError("EPUB 已存在（根据文件哈希去重）") + + filename = os.path.basename(file_path) + + with zipfile.ZipFile(file_path) as zf: + opf_path, opf_root = _read_opf(zf) + opf_dir = _dirname(opf_path) + + title, author, language = _extract_metadata(opf_root) + spine_items = _get_spine_items(zf, opf_root, opf_dir) + + headings = parse_toc_tree(file_path) + flat = flatten_headings(headings) + flat_with_paths = build_heading_paths(flat, 0) + + book = Book( + filename=filename, + title=title, + author=author, + language=language, + file_path=file_path, + file_hash=file_hash, + status="parsing", + ) + db.add(book) + await db.flush() + + total_chars = 0 + + spine_index_map = {} + with zipfile.ZipFile(file_path) as zf: + _, opf_root = _read_opf(zf) + manifest = {item.attrib.get("id"): item.attrib.get("href", "") for item in opf_root.findall("opf:manifest/opf:item", NS)} + spine_ids = [itemref.attrib.get("idref") for itemref in opf_root.findall("opf:spine/opf:itemref", NS)] + for idx, idref in enumerate(spine_ids): + href = manifest.get(idref, "") + if href: + spine_index_map[href] = idx + + with zipfile.ZipFile(file_path) as zf: + chapters_to_insert = _match_chapters_to_spine( + flat_with_paths, spine_items, zf, opf_dir, + ) + + chapter_order = 0 + for ch_info in chapters_to_insert: + paragraphs = extract_paragraphs(ch_info["html"], fix_wraps=True) + chapter_text = "\n\n".join(p["text"] for p in paragraphs) + chapter_chars = len(chapter_text) + total_chars += chapter_chars + + href = ch_info["href"] + spine_idx = spine_index_map.get(href, chapter_order) + cfi_start = make_cfi(spine_idx, href, ch_info.get("fragment", "")) + + chapter = Chapter( + book_id=book.id, + order_idx=chapter_order, + title=ch_info["title"], + level=ch_info.get("level", 1), + heading_path=ch_info.get("heading_path", ""), + cfi_start=cfi_start, + cfi_end="", + char_count=chapter_chars, + ) + db.add(chapter) + await db.flush() + + chunks = chapter_to_chunks( + paragraphs, + heading_path=ch_info.get("heading_path", ""), + cfi_start=cfi_start, + book_char_total=total_chars, + ) + + for seg_order, chunk in enumerate(chunks): + segment = Segment( + chapter_id=chapter.id, + book_id=book.id, + order_idx=seg_order, + text=chunk["text"], + char_count=chunk["char_count"], + cfi=chunk["cfi"], + ) + db.add(segment) + + chapter_order += 1 + + book.char_count = total_chars + book.status = "ready" + quality_score, quality_issues = _assess_quality(zf=None, chapters=chapters_to_insert, file_path=file_path) + await db.flush() + + return book + + +def _hash_file(file_path: str) -> str: + h = hashlib.sha256() + with open(file_path, "rb") as f: + for chunk in iter(lambda: f.read(8192), b""): + h.update(chunk) + return h.hexdigest() + + +def _extract_metadata(opf: etree._Element) -> tuple[str, str, str]: + ns = {"dc": "http://purl.org/dc/elements/1.1/"} + title_el = opf.find(".//dc:title", ns) + creator_el = opf.find(".//dc:creator", ns) + lang_el = opf.find(".//dc:language", ns) + title = title_el.text.strip() if title_el is not None and title_el.text else "未知书名" + author = creator_el.text.strip() if creator_el is not None and creator_el.text else "未知作者" + language = lang_el.text.strip() if lang_el is not None and lang_el.text else "zh" + return title, author, language + + +def _get_spine_items(zf: zipfile.ZipFile, opf: etree._Element, opf_dir: str) -> list[dict]: + """获取 spine 中所有文件的 HTML 内容""" + manifest = {item.attrib.get("id"): item.attrib.get("href", "") for item in opf.findall("opf:manifest/opf:item", NS)} + spine_ids = [itemref.attrib.get("idref") for itemref in opf.findall("opf:spine/opf:itemref", NS)] + items = [] + for idref in spine_ids: + href = manifest.get(idref, "") + if not href: + continue + path = _resolve_path(opf_dir, href) + try: + html = zf.read(path) + items.append({"href": href, "html": html, "path": path}) + except KeyError: + continue + return items + + +def _match_chapters_to_spine( + flat_headings: list[dict], + spine_items: list[dict], + zf: zipfile.ZipFile, + opf_dir: str, +) -> list[dict]: + """将目录条目与 spine 文件匹配，按 href 对齐""" + chapter_map = {} + for h in flat_headings: + href = h.get("href", "") + base = href.split("#")[0] if "#" in href else href + frag = href.split("#", 1)[1] if "#" in href else "" + if base not in chapter_map: + chapter_map[base] = [] + chapter_map[base].append({**h, "fragment": frag}) + + result = [] + seen = set() + for item in spine_items: + href = item["href"] + base = href.split("#")[0] if "#" in href else href + if base in chapter_map: + for ch in chapter_map[base]: + if ch.get("title", "") not in seen: + seen.add(ch.get("title", "")) + result.append({**ch, "html": item["html"]}) + else: + result.append({ + "title": f"Section {len(result) + 1}", + "level": 1, + "href": href, + "heading_path": "", + "fragment": "", + "html": item["html"], + }) + return result + + +def _assess_quality(zf, chapters: list[dict], file_path: str) -> tuple[int, list[str]]: + """评估解析质量""" + if not chapters: + return 0, ["无有效章节"] + sample_text = "\n".join( + clean_html(ch["html"], fix_wraps=False) + for ch in chapters[:5] + if ch.get("html") + ) + if not sample_text: + return 0, ["无法提取文本"] + return detect_quality(sample_text) \ No newline at end of file diff --git a/backend/app/epub/toc.py b/backend/app/epub/toc.py new file mode 100644 index 0000000..28c60b6 --- /dev/null +++ b/backend/app/epub/toc.py @@ -0,0 +1,216 @@ +import zipfile +import re +from lxml import etree +from dataclasses import dataclass, field + + +@dataclass +class Heading: + title: str + level: int + href: str + cfi: str = "" + children: list["Heading"] = field(default_factory=list) + + +NS = { + "opf": "http://www.idpf.org/2007/opf", + "ncx": "http://www.daisy.org/z3986/2005/ncx/", + "xhtml": "http://www.w3.org/1999/xhtml", +} + + +def parse_toc_tree(epub_path: str) -> list[Heading]: + """从 EPUB 中提取完整目录树，4 级降级：nav.xhtml -> ncx -> spine -> h 标签""" + with zipfile.ZipFile(epub_path) as zf: + opf_path, opf_root = _read_opf(zf) + opf_dir = _dirname(opf_path) + + headings = _try_nav(zf, opf_root, opf_dir) + if headings: + return headings + headings = _try_ncx(zf, opf_root, opf_dir) + if headings: + return headings + headings = _try_spine(zf, opf_root, opf_dir) + if headings: + return headings + return _fallback_spine(zf, opf_root, opf_dir) + + +def _read_opf(zf: zipfile.ZipFile) -> tuple[str, etree._Element]: + container = etree.fromstring(zf.read("META-INF/container.xml")) + rootfile = container.find(".//{urn:oasis:names:tc:opendocument:xmlns:container}rootfile") + opf_path = rootfile.attrib["full-path"] if rootfile is not None else "OEBPS/content.opf" + opf_root = etree.fromstring(zf.read(opf_path)) + return opf_path, opf_root + + +def _try_nav(zf: zipfile.ZipFile, opf: etree._Element, opf_dir: str) -> list[Heading] | None: + """EPUB3: nav.xhtml（最优先，有原生层级）""" + manifest = {item.attrib.get("id"): item.attrib.get("href", "") for item in opf.findall("opf:manifest/opf:item", NS)} + spine_ids = [itemref.attrib.get("idref") for itemref in opf.findall("opf:spine/opf:itemref", NS)] + + for idref in spine_ids: + href = manifest.get(idref, "") + if "nav" in href.lower() or "toc" in href.lower(): + nav_path = _resolve_path(opf_dir, href) + try: + return _parse_nav_xhtml(zf, nav_path, opf_dir) + except Exception: + continue + return None + + +def _parse_nav_xhtml(zf: zipfile.ZipFile, nav_path: str, opf_dir: str) -> list[Heading]: + html = etree.fromstring(zf.read(nav_path)) + ol = html.find(".//{http://www.w3.org/1999/xhtml}nav[@{http://www.w3.org/1999/xhtml}type='toc']//{http://www.w3.org/1999/xhtml}ol") + if ol is None: + ol = html.find(".//{http://www.w3.org/1999/xhtml}nav//{http://www.w3.org/1999/xhtml}ol") + if ol is None: + return [] + return _parse_ol(ol, opf_dir, 1) + + +def _parse_ol(ol, opf_dir: str, base_level: int) -> list[Heading]: + result = [] + for li in ol.findall("{http://www.w3.org/1999/xhtml}li"): + a = li.find("{http://www.w3.org/1999/xhtml}a") + if a is None: + continue + title = (a.text or "").strip() + href = a.attrib.get("href", "") + heading = Heading(title=title, level=base_level, href=href) + + sub_ol = li.find("{http://www.w3.org/1999/xhtml}ol") + if sub_ol is not None: + heading.children = _parse_ol(sub_ol, opf_dir, base_level + 1) + + result.append(heading) + return result + + +def _try_ncx(zf: zipfile.ZipFile, opf: etree._Element, opf_dir: str) -> list[Heading] | None: + """EPUB2: toc.ncx""" + spine = opf.find("opf:spine", NS) + if spine is None: + return None + ncx_id = spine.attrib.get("toc", "") + if not ncx_id: + return None + + manifest = {item.attrib.get("id"): item.attrib.get("href", "") for item in opf.findall("opf:manifest/opf:item", NS)} + ncx_href = manifest.get(ncx_id) + if not ncx_href: + return None + + ncx_path = _resolve_path(opf_dir, ncx_href) + try: + ncx_root = etree.fromstring(zf.read(ncx_path)) + return _parse_ncx_navmap(ncx_root, opf_dir) + except Exception: + return None + + +def _parse_ncx_navmap(ncx: etree._Element, opf_dir: str) -> list[Heading]: + navmap = ncx.find("ncx:navMap", NS) + if navmap is None: + return [] + return _parse_ncx_points(navmap, opf_dir, 1) + + +def _parse_ncx_points(parent, opf_dir: str, base_level: int) -> list[Heading]: + result = [] + for np in parent.findall("ncx:navPoint", NS): + label = np.find("ncx:navLabel/ncx:text", NS) + content = np.find("ncx:content", NS) + title = _text(label) if label is not None else "" + href = content.attrib.get("src", "") if content is not None else "" + heading = Heading(title=title, level=base_level, href=href) + heading.children = _parse_ncx_points(np, opf_dir, base_level + 1) + result.append(heading) + return result + + +def _try_spine(zf: zipfile.ZipFile, opf: etree._Element, opf_dir: str) -> list[Heading] | None: + """退化方案：每个 spine 文件当作一章""" + manifest = {item.attrib.get("id"): item.attrib.get("href", "") for item in opf.findall("opf:manifest/opf:item", NS)} + spine_ids = [itemref.attrib.get("idref") for itemref in opf.findall("opf:spine/opf:itemref", NS)] + headings = [] + for i, idref in enumerate(spine_ids): + href = manifest.get(idref, "") + if not href: + continue + try: + path = _resolve_path(opf_dir, href) + html = zf.read(path) + soup = etree.fromstring(html) + title_tag = soup.find(".//{http://www.w3.org/1999/xhtml}title") + title = _text(title_tag) if title_tag is not None else f"Section {i + 1}" + headings.append(Heading(title=title, level=1, href=href)) + except Exception: + continue + return headings if headings else None + + +def _fallback_spine(zf: zipfile.ZipFile, opf: etree._Element, opf_dir: str) -> list[Heading]: + """最后兜底：直接读所有 xhtml 的 h1-h3""" + return _try_spine(zf, opf, opf_dir) or [] + + +def flatten_headings(headings: list[Heading], level_offset: int = 0) -> list[dict]: + """将树形目录展平为列表，包含 heading_path""" + result = [] + for h in headings: + result.append({ + "title": h.title, + "level": h.level + level_offset, + "href": h.href, + }) + result.extend(flatten_headings(h.children, level_offset)) + return result + + +def build_heading_paths(headings: list[dict], order_idx: int) -> list[dict]: + """为每个扁平条目构建完整 heading_path（如 '第3章 > 3.2 前向传播'）""" + stack = [] + result = [] + for h in headings: + while stack and stack[-1]["level"] >= h["level"]: + stack.pop() + stack.append(h) + path = " > ".join(s["title"] for s in stack) + result.append({**h, "heading_path": path, "order_idx": order_idx}) + order_idx += 1 + return result + + +def _resolve_path(opf_dir: str, href: str) -> str: + if href.startswith("/"): + return href.lstrip("/") + parts = [p for p in opf_dir.split("/") if p] if opf_dir else [] + parts.append(href) + while ".." in parts: + idx = parts.index("..") + if idx > 0: + parts.pop(idx) + parts.pop(idx - 1) + else: + parts.pop(idx) + return "/".join(parts) + + +def _dirname(path: str) -> str: + parts = path.rsplit("/", 1) + return parts[0] if len(parts) > 1 else "" + + +def _text(el) -> str: + return "".join(el.itertext()).strip() if el is not None else "" + + +def href_to_fragment(href: str) -> str: + """从 href 中提取 file 和 fragment 部分""" + if "#" in href: + return href.split("#", 1)[1] + return "" \ No newline at end of file diff --git a/backend/app/llm/__init__.py b/backend/app/llm/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/backend/app/llm/hub.py b/backend/app/llm/hub.py new file mode 100644 index 0000000..4640802 --- /dev/null +++ b/backend/app/llm/hub.py @@ -0,0 +1,277 @@ +import json +import os +from abc import ABC, abstractmethod +from dataclasses import dataclass, field +from typing import AsyncGenerator + +from sqlalchemy.ext.asyncio import AsyncSession + + +@dataclass +class ChatResponse: + content: str + model: str + prompt_tokens: int = 0 + completion_tokens: int = 0 + + +class LLMProvider(ABC): + name: str = "base" + max_context: int = 128_000 + + @abstractmethod + async def chat(self, messages: list[dict], temperature: float = 0.7) -> ChatResponse: + ... + + @abstractmethod + async def chat_stream(self, messages: list[dict], temperature: float = 0.7) -> AsyncGenerator[str, None]: + ... + + +class OpenAIProvider(LLMProvider): + name = "openai" + max_context = 128_000 + + def __init__(self, api_key: str | None = None, base_url: str | None = None, model: str | None = None): + self.api_key = api_key if api_key is not None else os.getenv("OPENAI_API_KEY", "") + self.base_url = base_url if base_url is not None else os.getenv("OPENAI_BASE_URL", "https://api.openai.com/v1") + self.model = model if model is not None else os.getenv("OPENAI_MODEL", "gpt-4o") + + async def chat(self, messages: list[dict], temperature: float = 0.7) -> ChatResponse: + import httpx + async with httpx.AsyncClient(timeout=120) as client: + resp = await client.post( + f"{self.base_url}/chat/completions", + headers={"Authorization": f"Bearer {self.api_key}", "Content-Type": "application/json"}, + json={"model": self.model, "messages": messages, "temperature": temperature}, + ) + data = resp.json() + if "error" in data: + raise RuntimeError(f"OpenAI error: {data['error']}") + choice = data["choices"][0] + return ChatResponse( + content=choice["message"]["content"], + model=data["model"], + prompt_tokens=data.get("usage", {}).get("prompt_tokens", 0), + completion_tokens=data.get("usage", {}).get("completion_tokens", 0), + ) + + async def chat_stream(self, messages: list[dict], temperature: float = 0.7) -> AsyncGenerator[str, None]: + import httpx + async with httpx.AsyncClient(timeout=300) as client: + async with client.stream( + "POST", + f"{self.base_url}/chat/completions", + headers={"Authorization": f"Bearer {self.api_key}", "Content-Type": "application/json"}, + json={"model": self.model, "messages": messages, "temperature": temperature, "stream": True}, + ) as resp: + async for line in resp.aiter_lines(): + if line.startswith("data: "): + data_str = line[6:] + if data_str.strip() == "[DONE]": + break + try: + data = json.loads(data_str) + # 流末尾可能来一个 usage-only chunk（choices 为空），直接跳过 + choices = data.get("choices") or [] + if not choices: + continue + delta = choices[0].get("delta", {}) + content = delta.get("content", "") + if content: + yield content + except json.JSONDecodeError: + continue + + +class AnthropicProvider(LLMProvider): + name = "claude" + max_context = 200_000 + + def __init__(self, api_key: str | None = None, model: str | None = None): + self.api_key = api_key if api_key is not None else os.getenv("ANTHROPIC_API_KEY", "") + self.model = model if model is not None else os.getenv("ANTHROPIC_MODEL", "claude-sonnet-4-20250514") + + def _to_anthropic_messages(self, messages: list[dict]) -> tuple[str | None, list[dict]]: + system_msg = None + converted = [] + for m in messages: + if m["role"] == "system": + system_msg = m["content"] + else: + converted.append({"role": m["role"], "content": m["content"]}) + return system_msg, converted + + async def chat(self, messages: list[dict], temperature: float = 0.7) -> ChatResponse: + import httpx + system_msg, anthropic_msgs = self._to_anthropic_messages(messages) + body = { + "model": self.model, + "max_tokens": 4096, + "messages": anthropic_msgs, + "temperature": temperature, + } + if system_msg: + body["system"] = system_msg + async with httpx.AsyncClient(timeout=120) as client: + resp = await client.post( + "https://api.anthropic.com/v1/messages", + headers={ + "x-api-key": self.api_key, + "anthropic-version": "2023-06-01", + "Content-Type": "application/json", + }, + json=body, + ) + data = resp.json() + if "error" in data: + raise RuntimeError(f"Anthropic error: {data['error']}") + content_blocks = data.get("content", []) + text = "".join(b.get("text", "") for b in content_blocks if b.get("type") == "text") + return ChatResponse( + content=text, + model=data["model"], + prompt_tokens=data.get("usage", {}).get("input_tokens", 0), + completion_tokens=data.get("usage", {}).get("output_tokens", 0), + ) + + async def chat_stream(self, messages: list[dict], temperature: float = 0.7) -> AsyncGenerator[str, None]: + import httpx + system_msg, anthropic_msgs = self._to_anthropic_messages(messages) + body = { + "model": self.model, + "max_tokens": 4096, + "messages": anthropic_msgs, + "temperature": temperature, + "stream": True, + } + if system_msg: + body["system"] = system_msg + async with httpx.AsyncClient(timeout=300) as client: + async with client.stream( + "POST", + "https://api.anthropic.com/v1/messages", + headers={ + "x-api-key": self.api_key, + "anthropic-version": "2023-06-01", + "Content-Type": "application/json", + }, + json=body, + ) as resp: + async for line in resp.aiter_lines(): + if line.startswith("data: "): + data_str = line[6:] + try: + data = json.loads(data_str) + if data.get("type") == "content_block_delta": + delta = data.get("delta", {}) + text = delta.get("text", "") + if text: + yield text + except json.JSONDecodeError: + continue + + +class DeepSeekProvider(OpenAIProvider): + name = "deepseek" + max_context = 128_000 + + def __init__(self, api_key: str | None = None, model: str | None = None): + super().__init__( + api_key=api_key if api_key is not None else os.getenv("DEEPSEEK_API_KEY", ""), + base_url=os.getenv("DEEPSEEK_BASE_URL", "https://api.deepseek.com/v1"), + model=model if model is not None else os.getenv("DEEPSEEK_MODEL", "deepseek-chat"), + ) + + +# ---- 内置模型（.env）与用户自定义模型（ai_models 表）的统一解析 ---- + +def builtin_models() -> list[dict]: + """扫描 .env 里已配置 key 的内置模型（无 key 的不返回，前端不会展示废选项）。 + + label 跟随 .env 的 model_id 动态生成，不硬编码（如 DEEPSEEK_MODEL=deepseek-flash + 就显示「DeepSeek deepseek-flash」，避免与实际请求的模型对不上）。 + """ + out = [] + if os.getenv("DEEPSEEK_API_KEY"): + mid = os.getenv("DEEPSEEK_MODEL", "deepseek-chat") + out.append({ + "name": "deepseek", "label": f"DeepSeek {mid}", + "kind": "openai_compatible", "base_url": os.getenv("DEEPSEEK_BASE_URL", "https://api.deepseek.com/v1"), + "api_key_masked": _mask_key(os.getenv("DEEPSEEK_API_KEY")), + "model_id": mid, "builtin": True, + }) + if os.getenv("OPENAI_API_KEY"): + mid = os.getenv("OPENAI_MODEL", "gpt-4o") + out.append({ + "name": "openai", "label": f"GPT {mid}", + "kind": "openai_compatible", "base_url": os.getenv("OPENAI_BASE_URL", "https://api.openai.com/v1"), + "api_key_masked": _mask_key(os.getenv("OPENAI_API_KEY")), + "model_id": mid, "builtin": True, + }) + if os.getenv("ANTHROPIC_API_KEY"): + mid = os.getenv("ANTHROPIC_MODEL", "claude-sonnet-4-20250514") + out.append({ + "name": "claude", "label": f"Claude {mid}", + "kind": "anthropic", "base_url": "https://api.anthropic.com/v1", + "api_key_masked": _mask_key(os.getenv("ANTHROPIC_API_KEY")), + "model_id": mid, "builtin": True, + }) + if os.getenv("OPENROUTER_API_KEY"): + mid = os.getenv("OPENROUTER_MODEL", "openrouter/auto") + out.append({ + "name": "openrouter", "label": f"OpenRouter {mid}", + "kind": "openai_compatible", "base_url": "https://openrouter.ai/api/v1", + "api_key_masked": _mask_key(os.getenv("OPENROUTER_API_KEY")), + "model_id": mid, "builtin": True, + }) + return out + + +def _mask_key(key: str | None) -> str: + if not key: + return "" + if len(key) <= 8: + return "****" + return f"{key[:4]}****{key[-4:]}" + + +def _builtin_provider(entry: dict) -> LLMProvider: + """内置模型：key 从对应 .env 变量读取（builtin_models 只暴露掩码，不回传明文）。""" + name = entry["name"] + if name == "deepseek": + return DeepSeekProvider() + if name == "claude": + return AnthropicProvider() + if name == "openrouter": + return OpenAIProvider( + api_key=os.getenv("OPENROUTER_API_KEY", ""), + base_url="https://openrouter.ai/api/v1", + model=os.getenv("OPENROUTER_MODEL", "openrouter/auto"), + ) + return OpenAIProvider() # openai + + +def get_provider(name: str) -> LLMProvider | None: + """兼容旧的同步入口（仅内置模型）。""" + for m in builtin_models(): + if m["name"] == name: + return _builtin_provider(m) + return None + + +async def resolve_provider(db: AsyncSession, name: str) -> LLMProvider | None: + """按模型名解析 provider：内置名走 .env 默认构造，自定义走 ai_models 表；找不到返回 None。""" + from sqlalchemy import select + from app.models.ai_model import AiModel + + for m in builtin_models(): + if m["name"] == name: + return _builtin_provider(m) + result = await db.execute(select(AiModel).where(AiModel.name == name)) + row = result.scalars().first() + if row is None: + return None + if row.kind == "anthropic": + return AnthropicProvider(api_key=row.api_key, model=row.model_id) + return OpenAIProvider(api_key=row.api_key, base_url=row.base_url, model=row.model_id) \ No newline at end of file diff --git a/backend/app/main.py b/backend/app/main.py new file mode 100644 index 0000000..b7f9c75 --- /dev/null +++ b/backend/app/main.py @@ -0,0 +1,42 @@ +from contextlib import asynccontextmanager +from dotenv import load_dotenv + +load_dotenv() + +from fastapi import FastAPI +from fastapi.middleware.cors import CORSMiddleware + +from app.core.database import init_db, Base +from app.api.books import router as books_router +from app.api.chat import router as chat_router +from app.api.models import router as models_router + +from app.models.book import Book, Chapter, Segment +from app.models.chat import Conversation, Message +from app.models.ai_model import AiModel + + +@asynccontextmanager +async def lifespan(app: FastAPI): + await init_db() + yield + + +app = FastAPI(title="BookMate", version="0.1.0", lifespan=lifespan) + +app.add_middleware( + CORSMiddleware, + allow_origins=["*"], + allow_credentials=True, + allow_methods=["*"], + allow_headers=["*"], +) + +app.include_router(books_router, prefix="/api") +app.include_router(chat_router, prefix="/api") +app.include_router(models_router, prefix="/api") + + +@app.get("/api/health") +async def health(): + return {"status": "ok"} \ No newline at end of file diff --git a/backend/app/models/__init__.py b/backend/app/models/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/backend/app/models/ai_model.py b/backend/app/models/ai_model.py new file mode 100644 index 0000000..ff9516b --- /dev/null +++ b/backend/app/models/ai_model.py @@ -0,0 +1,28 @@ +import uuid +from datetime import datetime +from sqlalchemy import String, Text, Integer, DateTime, func +from sqlalchemy.orm import Mapped, mapped_column +from app.core.database import Base + + +def gen_uuid(): + return str(uuid.uuid4()) + + +class AiModel(Base): + """用户从页面配置的 AI 模型（OpenAI 兼容 / Anthropic）。 + + .env 内置模型不落这张表，由 hub.builtin_models() 动态读取。 + """ + + __tablename__ = "ai_models" + + id: Mapped[str] = mapped_column(String(36), primary_key=True, default=gen_uuid) + name: Mapped[str] = mapped_column(String(200), unique=True) # 解析标识（请求模型 id） + label: Mapped[str] = mapped_column(String(200)) # 前端显示名 + kind: Mapped[str] = mapped_column(String(50), default="openai_compatible") # openai_compatible | anthropic + base_url: Mapped[str] = mapped_column(String(500), default="") + api_key: Mapped[str] = mapped_column(Text, default="") # 明文本地存储（与 .env 同级信任） + model_id: Mapped[str] = mapped_column(String(200)) # 实际请求模型 id + sort_order: Mapped[int] = mapped_column(Integer, default=0) + created_at: Mapped[datetime] = mapped_column(DateTime, server_default=func.now()) \ No newline at end of file diff --git a/backend/app/models/book.py b/backend/app/models/book.py new file mode 100644 index 0000000..95a4831 --- /dev/null +++ b/backend/app/models/book.py @@ -0,0 +1,60 @@ +import uuid +from datetime import datetime +from sqlalchemy import String, Integer, Float, Text, DateTime, ForeignKey, JSON, func +from sqlalchemy.orm import Mapped, mapped_column, relationship +from app.core.database import Base + + +def gen_uuid(): + return str(uuid.uuid4()) + + +class Book(Base): + __tablename__ = "books" + + id: Mapped[str] = mapped_column(String(36), primary_key=True, default=gen_uuid) + filename: Mapped[str] = mapped_column(String(500), nullable=False) + title: Mapped[str | None] = mapped_column(String(500)) + author: Mapped[str | None] = mapped_column(String(500)) + language: Mapped[str] = mapped_column(String(20), default="zh") + file_path: Mapped[str] = mapped_column(String(1000), nullable=False) + file_hash: Mapped[str | None] = mapped_column(String(64), unique=True) + char_count: Mapped[int] = mapped_column(Integer, default=0) + status: Mapped[str] = mapped_column(String(20), default="uploaded") + created_at: Mapped[datetime] = mapped_column(DateTime, server_default=func.now()) + + chapters: Mapped[list["Chapter"]] = relationship(back_populates="book", cascade="all, delete-orphan") + + +class Chapter(Base): + __tablename__ = "chapters" + + id: Mapped[str] = mapped_column(String(36), primary_key=True, default=gen_uuid) + book_id: Mapped[str] = mapped_column(String(36), ForeignKey("books.id", ondelete="CASCADE")) + order_idx: Mapped[int] = mapped_column(Integer, default=0) + title: Mapped[str | None] = mapped_column(String(500)) + level: Mapped[int] = mapped_column(Integer, default=1) + heading_path: Mapped[str | None] = mapped_column(Text) + cfi_start: Mapped[str | None] = mapped_column(String(500)) + cfi_end: Mapped[str | None] = mapped_column(String(500)) + char_count: Mapped[int] = mapped_column(Integer, default=0) + + book: Mapped["Book"] = relationship(back_populates="chapters") + segments: Mapped[list["Segment"]] = relationship(back_populates="chapter", cascade="all, delete-orphan") + + +class Segment(Base): + __tablename__ = "segments" + + id: Mapped[str] = mapped_column(String(36), primary_key=True, default=gen_uuid) + chapter_id: Mapped[str] = mapped_column(String(36), ForeignKey("chapters.id", ondelete="CASCADE")) + book_id: Mapped[str] = mapped_column(String(36), ForeignKey("books.id", ondelete="CASCADE")) + order_idx: Mapped[int] = mapped_column(Integer, default=0) + text: Mapped[str] = mapped_column(Text, nullable=False) + char_count: Mapped[int] = mapped_column(Integer, default=0) + cfi: Mapped[str | None] = mapped_column(String(500)) + page_estimate: Mapped[float | None] = mapped_column(Float) + metadata_: Mapped[str | None] = mapped_column("metadata", Text) + embedding: Mapped[str | None] = mapped_column(Text) # JSON 浮点数组（向量检索用）；NULL = 尚未生成向量 + + chapter: Mapped["Chapter"] = relationship(back_populates="segments") \ No newline at end of file diff --git a/backend/app/models/chat.py b/backend/app/models/chat.py new file mode 100644 index 0000000..51b9303 --- /dev/null +++ b/backend/app/models/chat.py @@ -0,0 +1,43 @@ +import uuid +from datetime import datetime +from sqlalchemy import String, Text, DateTime, ForeignKey, JSON, func +from sqlalchemy.orm import Mapped, mapped_column, relationship +from app.core.database import Base + + +def gen_uuid(): + return str(uuid.uuid4()) + + +class Conversation(Base): + __tablename__ = "conversations" + + id: Mapped[str] = mapped_column(String(36), primary_key=True, default=gen_uuid) + book_id: Mapped[str] = mapped_column(String(36), ForeignKey("books.id", ondelete="CASCADE")) + title: Mapped[str | None] = mapped_column(String(500)) + model: Mapped[str] = mapped_column(String(50), default="claude") + created_at: Mapped[datetime] = mapped_column(DateTime, server_default=func.now()) + updated_at: Mapped[datetime] = mapped_column(DateTime, server_default=func.now(), onupdate=func.now()) + + messages: Mapped[list["Message"]] = relationship( + back_populates="conversation", cascade="all, delete-orphan", + order_by="Message.created_at" + ) + + +class Message(Base): + __tablename__ = "messages" + + id: Mapped[str] = mapped_column(String(36), primary_key=True, default=gen_uuid) + conversation_id: Mapped[str] = mapped_column(String(36), ForeignKey("conversations.id", ondelete="CASCADE")) + parent_message_id: Mapped[str | None] = mapped_column(String(36), ForeignKey("messages.id", ondelete="SET NULL")) + role: Mapped[str] = mapped_column(String(20)) + content: Mapped[str] = mapped_column(Text, nullable=False) + citations: Mapped[str | None] = mapped_column("citations_json", Text) + model: Mapped[str | None] = mapped_column(String(50)) + prompt_tokens: Mapped[int | None] = mapped_column() + completion_tokens: Mapped[int | None] = mapped_column() + created_at: Mapped[datetime] = mapped_column(DateTime, server_default=func.now()) + + conversation: Mapped["Conversation"] = relationship(back_populates="messages") + parent: Mapped["Message | None"] = relationship("Message", remote_side="Message.id") \ No newline at end of file diff --git a/backend/app/rag/__init__.py b/backend/app/rag/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/backend/app/rag/engine.py b/backend/app/rag/engine.py new file mode 100644 index 0000000..d8d59da --- /dev/null +++ b/backend/app/rag/engine.py @@ -0,0 +1,286 @@ +import re + +import jieba +from sqlalchemy import select, or_ +from sqlalchemy.ext.asyncio import AsyncSession + +from app.core.database import async_session +from app.models.book import Book, Chapter, Segment +from app.rag.vector import ( + embed_texts, rerank_documents, load_vectors, vector_search, + rrf_fuse, ensure_embeddings, get_status, RERANK_ENABLED, +) + +CITATION_RE = re.compile(r"\[\[ref:(\d+)\]\]") + +# 保守停用词：只过滤纯功能词，避免误删有检索价值的实词 +STOPWORDS = set( + "的 了 呢 吗 吧 啊 呀 嘛 哦 啦 哈 么 这 那 是 在 和 与 或 之 对 从 有 就 都 也 很 还 又 而 却 但 但是 然而 因此 所以 因为 如果 我们 你们 他们 它们 她们 什么 怎么 为什么 如何 这个 那个 一些 一个 本书 这本书 内容 主题 大概 比如 例如 应该 可能 可以 时候 里面 当中 其中 一些 部分 相关 关于 请问 告诉 解释 介绍 总结 分析".split() +) + + +def _tokenize(query: str) -> list[str]: + """分词：jieba 词 + 整句（精确子串）+ 双字 bigram，过滤停用词与纯符号。""" + tokens: set[str] = set() + for w in jieba.cut(query): + w = w.strip().lower() + if not w or w in STOPWORDS or re.fullmatch(r"[\s\W_]+", w): + continue + if len(w) >= 2: + tokens.add(w) + q = query.strip().lower() + if len(q) >= 4 and q not in STOPWORDS: + tokens.add(q) + # 中文连续串生成 bigram，增强长句召回（SQL LIKE 无法分词匹配） + for part in re.findall(r"[一-鿿]+", q): + if len(part) >= 4: + tokens.update(part[i:i + 2] for i in range(len(part) - 1)) + # 过滤 bigram 中出现的停用字组合（如「的」开头的） + tokens = {t for t in tokens if not any(c in STOPWORDS for c in t) or len(t) >= 4} + return list(tokens) + + +def match_chapters(chapters: list[Chapter], query: str, tokens: list[str] | None = None) -> list[Chapter]: + """章节标题匹配：查询词命中标题，或标题词命中查询。按目录顺序返回。""" + if not chapters: + return [] + if tokens is None: + tokens = _tokenize(query) + q = query.lower() + hits = [] + for ch in chapters: + title = (ch.title or "").strip().lower() + if not title or len(title) < 2: + continue + if any(w and w in title for w in tokens): + hits.append(ch) + continue + title_tokens = [ + w.strip() for w in jieba.cut(title) + if len(w.strip()) >= 2 and w.strip() not in STOPWORDS + ] + if any(tw in q for tw in title_tokens): + hits.append(ch) + hits.sort(key=lambda c: c.order_idx) + return hits + + +async def _keyword_candidates(db: AsyncSession, book_id: str, tokens: list[str], limit: int) -> list[Segment]: + """关键词候选：SQL LIKE 召回（含整句子串），按命中词数 + 长词加权打分。""" + if not tokens: + return [] + ordered = sorted(tokens, key=len, reverse=True)[:8] + conds = [Segment.text.contains(w) for w in ordered] + q = ( + select(Segment) + .where(Segment.book_id == book_id, or_(*conds)) + .order_by(Segment.order_idx) + .limit(limit * 4) + ) + result = await db.execute(q) + segs = list(result.scalars().all()) + scored = [] + for s in segs: + text = s.text.lower() + score = sum(3 if len(w) >= 4 else 1 for w in ordered if w in text) + scored.append((score, s)) + scored.sort(key=lambda x: -x[0]) + return [s for _, s in scored[:limit]] + + +async def _empty_fallback(db: AsyncSession, book_id: str, chapters: list[Chapter], top_k: int) -> list[Segment]: + """空检索兜底：返回目录最靠前的章节的开头段（全书开头），让 AI 至少有所依据。""" + result = await db.execute( + select(Segment) + .where(Segment.book_id == book_id) + .order_by(Segment.order_idx) + .limit(top_k * 3) + ) + segs = [s for s in result.scalars().all() if (s.text or "").strip()] + return segs[:top_k] + + +async def search_segments( + db: AsyncSession, + book_id: str, + query: str, + top_k: int = 15, + chapters: list[Chapter] | None = None, +) -> list[Segment]: + """混合检索：jieba 关键词 + API 向量余弦 → RRF 融合 → rerank 精排 → top_k。 + + 未配置 / 未生成向量 / API 失败时自动降级为纯关键词检索，绝不空手返回。 + """ + tokens = _tokenize(query) + + # 懒补向量（后台任务没跑完 / 重启后缺失时） + if get_status(book_id) != "done": + # 用独立会话执行：ensure_embeddings 失败时的 rollback 会过期会话内已加载的实例， + # 不能让调用方持有的 book/chapters 一起被过期（异步惰性访问会抛 MissingGreenlet） + async with async_session() as embed_session: + status = await ensure_embeddings(embed_session, book_id) + if status == "running": + # 后台正在生成，本次先用关键词，避免阻塞 + status = "failed" + + # 1. 关键词候选 + kw_candidates = await _keyword_candidates(db, book_id, tokens, top_k * 3) + + # 2. 向量候选 + vec_candidates: list[Segment] = [] + if tokens: + qvec = await embed_texts([query]) + if qvec and qvec[0]: + mat, vec_segments = await load_vectors(db, book_id) + if mat is not None and len(mat) > 0: + idxs = vector_search(qvec[0], mat, top_k * 3) + vec_candidates = [vec_segments[i] for i in idxs] + + # 3. RRF 融合 + if kw_candidates and vec_candidates: + by_id = {s.id: s for s in kw_candidates + vec_candidates} + fused = rrf_fuse( + [s.id for s in kw_candidates], + [s.id for s in vec_candidates], + ) + merged = [by_id[sid] for sid in fused if sid in by_id] + elif vec_candidates: + merged = vec_candidates + else: + merged = kw_candidates + + # 4. rerank 精排（对融合后的 top50 段打分） + if merged and RERANK_ENABLED: + docs = [s.text[:800] for s in merged[:50]] + idxs = await rerank_documents(query, docs, top_n=top_k) + if idxs is not None: + merged = [merged[i] for i in idxs if i < len(merged)] + + # 5. 兜底：完全没召回时给全书开头段，而不是空着 + if not merged: + merged = await _empty_fallback(db, book_id, chapters or [], top_k) + + return merged[:top_k] + + +def _chapter_full_text(chapter_segments: list[Segment], budget_tokens: int = 6000) -> str: + """整章注入：按 token 预算截取命中章节的原文。""" + parts = [] + used = 0 + for seg in chapter_segments: + t = seg.text + cost = estimate_tokens(t) + if parts and used + cost > budget_tokens: + break + parts.append(t) + used += cost + return "\n\n".join(parts) + + +def build_chat_prompt( + book: Book, + chapters: list[Chapter], + segments: list[Segment], + history: list[dict], + query: str, + chapter_segments: list[Segment] | None = None, +) -> list[dict]: + system = f"""# 你是 BookMate，一个帮助用户阅读书籍的 AI 助手。 + +## 当前书籍 +- 书名：《{book.title or '未知'}》 +- 作者：{book.author or '未知'} +- 总字数：约 {book.char_count:,} 字 + +## 目录结构 +""" + for ch in chapters[:40]: + indent = " " * (ch.level - 1) + system += f"{indent}- {ch.title or '(无标题)'}\n" + if len(chapters) > 40: + system += f" ...（共 {len(chapters)} 章）\n" + + # 命中章节的整章原文：全局性问题（如「第3章讲了什么」）直接给全文 + chapter_text = _chapter_full_text(chapter_segments or []) + if chapter_text: + system += "\n## 与问题直接相关的整章原文\n" + system += chapter_text + "\n" + + if segments: + system += "\n## 检索到的相关原文段落\n" + for i, seg in enumerate(segments, 1): + text_preview = seg.text[:800].replace("\n", " ") + system += f"\n[[ref:{i}]] {text_preview}\n" + else: + system += ( + "\n## 检索说明\n" + "本次没有检索到与问题直接匹配的原文段落。请基于上方目录结构、" + "书名与你的常识，指出书中哪些章节最可能涉及该主题，" + "并明确说明「这是基于目录的推断」，不要编造具体原文内容。\n" + ) + + system += """ +## 回答要求 +1. 优先基于「检索到的相关原文段落」和「整章原文」回答，不要臆造书里没有的内容 +2. 引用原文时必须带 [[ref:N]] 标记（N 对应上方段落编号）；同一段落只需引用一次，不要反复出现相同的 [[ref:N]]；整个回答的引用控制在 5 条左右，只引用你真正依据的段落 +3. 如果检索内容不足以回答，坦诚说明，并给出基于目录的建议 +4. 用中文回答 +5. 当用户要求「思维导图 / 脑图 / mind map」时，输出 mermaid mindmap 语法，放在 ```mermaid 代码块里。格式：第一行写 `mindmap`，根节点写 `root((主题))`，子节点通过缩进表示层级，例如： +```mermaid +mindmap + root((主题)) + 一级分支 + 二级分支 +``` +不要把其他解释文字塞进代码块，代码块外可以有简短说明。""" + + messages = [{"role": "system", "content": system}] + if history: + messages.extend(history[-10:]) + messages.append({"role": "user", "content": query}) + return messages + + +def _trim_messages(messages: list[dict], budget_tokens: int) -> list[dict]: + """内容感知裁剪：保留 system（含检索原文）与最新提问，从最旧历史开始丢弃。 + + 替代原先粗糙的 `messages[:1] + messages[-(len//2):]`，避免裁掉检索上下文。 + """ + if estimate_tokens("".join(m["content"] for m in messages)) <= budget_tokens: + return messages + + system = messages[0] + tail = messages[-1] + used = estimate_tokens(system["content"] + tail["content"]) + kept = [] + for m in reversed(messages[1:-1]): + cost = estimate_tokens(m["content"]) + if used + cost <= budget_tokens: + kept.append(m) + used += cost + else: + break + kept.reverse() + return [system] + kept + [tail] + + +def parse_citations(content: str, segments: list[Segment]) -> dict: + citations = [] + for m in CITATION_RE.finditer(content): + idx = int(m.group(1)) - 1 + if 0 <= idx < len(segments): + seg = segments[idx] + citations.append({ + "segment_id": seg.id, + "cfi": seg.cfi, + "excerpt": seg.text[:200], + }) + clean_text = CITATION_RE.sub("", content) + return {"text": clean_text, "citations": citations} + + +def estimate_tokens(text: str) -> int: + """粗略估算 token 数：中文每字约 1.5 token，英文每词约 1.3 token""" + chinese_chars = len(re.findall(r"[一-鿿]", text)) + english_words = len(re.findall(r"[a-zA-Z]+", text)) + return int(chinese_chars * 1.5 + english_words * 1.3 + (len(text) - chinese_chars - len(re.findall(r"[a-zA-Z]", text))) * 0.5) diff --git a/backend/app/rag/vector.py b/backend/app/rag/vector.py new file mode 100644 index 0000000..2ccbd9b --- /dev/null +++ b/backend/app/rag/vector.py @@ -0,0 +1,218 @@ +"""向量检索服务（B 档）。 + +- embedding：调用 OpenAI 兼容 /embeddings API（如硅基流动 `BAAI/bge-m3`，1024 维） +- rerank：调用 /v1/rerank API（如硅基流动 `BAAI/bge-reranker-v2-m3`） +- 检索：书本段规模几千~几万，直接全量 numpy 余弦扫描，无需引入向量数据库 +- 融合：关键词结果 + 向量结果做 RRF（Reciprocal Rank Fusion） +- 降级：未配置 API Key / 调用失败时自动退回纯关键词模式，绝不阻塞主流程 +""" +import json +import logging +import threading + +import numpy as np +import httpx +from sqlalchemy import select +from sqlalchemy.ext.asyncio import AsyncSession + +from app.core.config import settings +from app.models.book import Segment + +logger = logging.getLogger(__name__) + +EMBEDDING_ENABLED = bool(settings.embedding_api_key) +RERANK_ENABLED = bool(settings.rerank_api_key) + +# book_id -> 向量生成状态："done" / "running" / "failed" +_vector_status: dict[str, str] = {} +_status_lock = threading.Lock() + + +# ======================= API 客户端 ======================= + +async def embed_texts(texts: list[str]) -> list[list[float] | None] | None: + """生成一批文本的向量，返回与 texts 同序的列表（单条失败置 None，其余正常）。 + + 单次请求过大 / 服务端失败时自动对半拆开递归重试，直到单条； + 单条超模型输入上限时截断重试一次，仍失败则跳过该条（置 None）。 + 未配置时返回 None；鉴权/配置类错误（API 不可用）直接抛出。 + """ + if not EMBEDDING_ENABLED or not texts: + return None + url = settings.embedding_base_url.rstrip("/") + "/embeddings" + headers = {"Authorization": f"Bearer {settings.embedding_api_key}"} + out: list[list[float] | None] = [None] * len(texts) + # 空文本无法向量化（OpenRouter 对空串直接 400 too_small），预过滤不送请求 + tasks: list[tuple[int, str]] = [(i, t) for i, t in enumerate(texts) if t and t.strip()] + if not tasks: + return out + + async with httpx.AsyncClient(timeout=httpx.Timeout(120.0, connect=15.0)) as client: + async def _call(items: list[str], idxs: list[int]) -> None: + if not items: + return + try: + resp = await client.post( + url, headers=headers, + json={"model": settings.embedding_model, "input": items}, + ) + resp.raise_for_status() + rows = resp.json().get("data") or [] + for j, row in enumerate(rows): + idx = row.get("index", j) + if 0 <= idx < len(idxs) and isinstance(row.get("embedding"), list): + out[idxs[idx]] = [float(v) for v in row["embedding"]] + except Exception as e: # noqa: BLE001 + # 鉴权/配置错误拆分也救不了，直接整体失败 + if isinstance(e, httpx.HTTPStatusError) and e.response.status_code in (401, 403, 404, 405): + raise + if len(items) > 1: + mid = len(items) // 2 + await _call(items[:mid], idxs[:mid]) + await _call(items[mid:], idxs[mid:]) + elif len(items[0]) > 1500: + # 单条超模型输入上限：截断再试一次（超长段向量化本就意义有限） + try: + resp = await client.post( + url, headers=headers, + json={"model": settings.embedding_model, "input": [items[0][:1500]]}, + ) + resp.raise_for_status() + rows = resp.json().get("data") or [] + if rows and isinstance(rows[0].get("embedding"), list): + out[idxs[0]] = [float(v) for v in rows[0]["embedding"]] + except Exception as e2: # noqa: BLE001 + logger.warning("embedding 单条失败（跳过）: %s", e) + else: + logger.warning("embedding 单条失败（跳过）: %s", e) + + await _call([t for _, t in tasks], [i for i, _ in tasks]) + + return out + + +async def rerank_documents(query: str, documents: list[str], top_n: int | None = None) -> list[int] | None: + """调用 rerank API。返回按相关性降序的原始文档索引；未配置或失败返回 None。""" + if not RERANK_ENABLED or not documents: + return None + url = settings.rerank_base_url.rstrip("/") + "/rerank" + headers = {"Authorization": f"Bearer {settings.rerank_api_key}"} + payload = {"model": settings.rerank_model, "query": query, "documents": documents} + if top_n: + payload["top_n"] = top_n + try: + async with httpx.AsyncClient(timeout=60) as client: + resp = await client.post(url, headers=headers, json=payload) + resp.raise_for_status() + results = resp.json()["results"] + ordered = sorted(results, key=lambda r: -float(r["relevance_score"])) + return [int(r["index"]) for r in ordered] + except Exception as e: # noqa: BLE001 + logger.warning("rerank API 调用失败: %s", e) + return None + + +# ======================= 向量检索 ======================= + +async def load_vectors(db: AsyncSession, book_id: str) -> tuple[np.ndarray | None, list[Segment]]: + """读取该书所有已生成向量的段。返回 (向量矩阵, 对应段列表)。""" + result = await db.execute( + select(Segment) + .where(Segment.book_id == book_id, Segment.embedding.is_not(None)) + .order_by(Segment.order_idx) + ) + segs = list(result.scalars().all()) + vecs = [] + kept = [] + for s in segs: + try: + vecs.append(json.loads(s.embedding)) + kept.append(s) + except (json.JSONDecodeError, TypeError): + continue + if not vecs: + return None, [] + return np.asarray(vecs, dtype=np.float32), kept + + +def vector_search(query_vec: list[float], mat: np.ndarray, top_k: int) -> list[int]: + """余弦相似度 top_k，返回 mat 行索引（降序）。""" + q = np.asarray(query_vec, dtype=np.float32) + q_norm = np.linalg.norm(q) + if q_norm == 0: + return [] + sims = (mat @ q) / (np.linalg.norm(mat, axis=1) * q_norm + 1e-9) + top = np.argsort(-sims)[:top_k] + return [int(i) for i in top] + + +def rrf_fuse(*rankings: list[str], k: int = 60) -> list[str]: + """Reciprocal Rank Fusion：合并多个按相关性降序的 segment_id 列表。""" + scores: dict[str, float] = {} + for ranking in rankings: + for rank, sid in enumerate(ranking): + scores[sid] = scores.get(sid, 0.0) + 1.0 / (k + rank + 1) + return [sid for sid, _ in sorted(scores.items(), key=lambda kv: -kv[1])] + + +# ======================= 向量生成（上传后后台 + 检索前懒补）======================= + +def _set_status(book_id: str, status: str) -> None: + with _status_lock: + _vector_status[book_id] = status + + +def get_status(book_id: str) -> str | None: + with _status_lock: + return _vector_status.get(book_id) + + +async def ensure_embeddings(db: AsyncSession, book_id: str) -> str: + """确保 book 的每个 Segment 都有向量。返回状态 done / running / failed / disabled。 + + - 后台任务与请求可能并发调用：running 状态会直接返回，由另一方补齐 + - 只对缺少向量的段生成，重复调用是增量补差 + """ + if not EMBEDDING_ENABLED: + _set_status(book_id, "failed") + return "disabled" + + status = get_status(book_id) + if status == "running": + return "running" + + result = await db.execute( + select(Segment) + .where(Segment.book_id == book_id, Segment.embedding.is_(None)) + .order_by(Segment.order_idx) + ) + missing = list(result.scalars().all()) + # 空文本段无法向量化（API 对空串 400），也永远无检索价值，直接排除 + missing = [s for s in missing if (s.text or "").strip()] + if not missing: + _set_status(book_id, "done") + return "done" + + _set_status(book_id, "running") + try: + batch = settings.embedding_batch_size + for start in range(0, len(missing), batch): + segs = missing[start:start + batch] + vecs = await embed_texts([s.text for s in segs]) + if vecs is None: + raise RuntimeError("embedding API 不可用") + # 单条失败时 vec 为 None，跳过不落库；其余照常持久化 + for seg, vec in zip(segs, vecs): + if vec is not None: + seg.embedding = json.dumps([float(v) for v in vec], ensure_ascii=False) + await db.commit() + # 已尝试全部缺失段。个别被模型拒绝的段（内容/超限）由关键词档兜底， + # 标记 done 避免每次检索都重复重试；API 级故障会在 except 里落为 failed + _set_status(book_id, "done") + return "done" + except Exception as e: # noqa: BLE001 + logger.warning("向量生成失败 book=%s: %s", book_id, e) + _set_status(book_id, "failed") + # 已提交的批次不受影响；rollback 仅丢弃本批次未提交变更 + await db.rollback() + return "failed" diff --git a/backend/app/schemas/__init__.py b/backend/app/schemas/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/backend/app/schemas/book.py b/backend/app/schemas/book.py new file mode 100644 index 0000000..0c7abe0 --- /dev/null +++ b/backend/app/schemas/book.py @@ -0,0 +1,56 @@ +from pydantic import BaseModel +from datetime import datetime + + +class BookOut(BaseModel): + id: str + filename: str + title: str | None + author: str | None + language: str + char_count: int + status: str + created_at: datetime + + class Config: + from_attributes = True + + +class BookDetailOut(BookOut): + chapter_count: int = 0 + segment_count: int = 0 + + +class ChapterOut(BaseModel): + id: str + book_id: str + order_idx: int + title: str | None + level: int + heading_path: str | None + cfi_start: str | None + cfi_end: str | None + char_count: int + + class Config: + from_attributes = True + + +class SegmentOut(BaseModel): + id: str + chapter_id: str + book_id: str + order_idx: int + text: str + char_count: int + cfi: str | None + + class Config: + from_attributes = True + + +class ParseStatus(BaseModel): + book_id: str + status: str + title: str | None + char_count: int \ No newline at end of file diff --git a/backend/requirements.txt b/backend/requirements.txt new file mode 100644 index 0000000..3d1365d --- /dev/null +++ b/backend/requirements.txt @@ -0,0 +1,16 @@ +fastapi==0.115.0 +uvicorn[standard]==0.30.6 +sqlalchemy[asyncio]==2.0.35 +aiosqlite==0.20.0 +alembic==1.13.2 +ebooklib==0.18 +beautifulsoup4==4.12.3 +lxml==5.3.0 +pydantic==2.9.2 +pydantic-settings==2.5.2 +python-multipart==0.0.12 +aiofiles==24.1.0 +httpx==0.28.1 +python-dotenv==1.0.1 +jieba==0.42.1 +numpy==2.5.4 \ No newline at end of file diff --git a/backend/test_book_file.py b/backend/test_book_file.py new file mode 100644 index 0000000..616cee6 --- /dev/null +++ b/backend/test_book_file.py @@ -0,0 +1,57 @@ +"""Run with: .venv/Scripts/python.exe -B -m unittest test_book_file""" +import tempfile +import unittest +from pathlib import Path +from types import SimpleNamespace +from unittest.mock import AsyncMock, patch +import httpx +from fastapi import FastAPI +from app.api.books import router +from app.core.database import get_db + + +class BookFileTests(unittest.IsolatedAsyncioTestCase): + async def asyncSetUp(self): + self.temp = tempfile.TemporaryDirectory() + self.root = Path(self.temp.name) + self.file = self.root / "sample.epub" + self.content = b"PK\x03\x04original-epub-bytes" + self.file.write_bytes(self.content) + self.db = SimpleNamespace(get=AsyncMock(return_value=SimpleNamespace(file_path=str(self.file)))) + app = FastAPI() + app.include_router(router, prefix="/api") + + async def fake_db(): + yield self.db + + app.dependency_overrides[get_db] = fake_db + self.client = httpx.AsyncClient(transport=httpx.ASGITransport(app=app), base_url="http://test") + self.config = patch("app.api.books.settings", SimpleNamespace(upload_dir=str(self.root))) + self.config.start() + + async def asyncTearDown(self): + await self.client.aclose() + self.config.stop() + self.temp.cleanup() + + async def test_original_bytes_and_type(self): + response = await self.client.get("/api/books/book-id/file") + self.assertEqual(response.status_code, 200) + self.assertEqual(response.content, self.content) + self.assertEqual(response.headers["content-type"], "application/epub+zip") + + async def test_unknown_book(self): + self.db.get.return_value = None + self.assertEqual((await self.client.get("/api/books/unknown/file")).status_code, 404) + + async def test_missing_file(self): + self.db.get.return_value.file_path = str(self.root / "missing.epub") + self.assertEqual((await self.client.get("/api/books/book-id/file")).status_code, 404) + + async def test_outside_upload_directory(self): + self.db.get.return_value.file_path = str(self.root.parent / "outside.epub") + self.assertEqual((await self.client.get("/api/books/book-id/file")).status_code, 404) + + async def test_non_epub_not_served(self): + self.db.get.return_value.file_path = str(self.root / "secrets.txt") + self.assertEqual((await self.client.get("/api/books/book-id/file")).status_code, 404) diff --git a/frontend/.gitignore b/frontend/.gitignore new file mode 100644 index 0000000..5ef6a52 --- /dev/null +++ b/frontend/.gitignore @@ -0,0 +1,41 @@ +# See https://help.github.com/articles/ignoring-files/ for more about ignoring files. + +# dependencies +/node_modules +/.pnp +.pnp.* +.yarn/* +!.yarn/patches +!.yarn/plugins +!.yarn/releases +!.yarn/versions + +# testing +/coverage + +# next.js +/.next/ +/out/ + +# production +/build + +# misc +.DS_Store +*.pem + +# debug +npm-debug.log* +yarn-debug.log* +yarn-error.log* +.pnpm-debug.log* + +# env files (can opt-in for committing if needed) +.env* + +# vercel +.vercel + +# typescript +*.tsbuildinfo +next-env.d.ts diff --git a/frontend/AGENTS.md b/frontend/AGENTS.md new file mode 100644 index 0000000..af3b7c8 --- /dev/null +++ b/frontend/AGENTS.md @@ -0,0 +1,9 @@ + + +## This is NOT the Next.js you know + +This version has breaking changes — APIs, conventions, and file structure may all differ from your training data. Read the relevant guide in `node_modules/next/dist/docs/` (resolved from this file's directory; in monorepos the `next` package may not be visible from the repo root) before writing any code. Heed deprecation notices. + +This block is written and re-added by `next dev` — verify at `node_modules/next/dist/server/lib/generate-agent-files.js`. Removing it from a diff only re-creates the uncommitted change; committing it with your work keeps the tree clean. + + diff --git a/frontend/README.md b/frontend/README.md new file mode 100644 index 0000000..e215bc4 --- /dev/null +++ b/frontend/README.md @@ -0,0 +1,36 @@ +This is a [Next.js](https://nextjs.org) project bootstrapped with [`create-next-app`](https://nextjs.org/docs/app/api-reference/cli/create-next-app). + +## Getting Started + +First, run the development server: + +```bash +npm run dev +# or +yarn dev +# or +pnpm dev +# or +bun dev +``` + +Open [http://localhost:3000](http://localhost:3000) with your browser to see the result. + +You can start editing the page by modifying `app/page.tsx`. The page auto-updates as you edit the file. + +This project uses [`next/font`](https://nextjs.org/docs/app/building-your-application/optimizing/fonts) to automatically optimize and load [Geist](https://vercel.com/font), a new font family for Vercel. + +## Learn More + +To learn more about Next.js, take a look at the following resources: + +- [Next.js Documentation](https://nextjs.org/docs) - learn about Next.js features and API. +- [Learn Next.js](https://nextjs.org/learn) - an interactive Next.js tutorial. + +You can check out [the Next.js GitHub repository](https://github.com/vercel/next.js) - your feedback and contributions are welcome! + +## Deploy on Vercel + +The easiest way to deploy your Next.js app is to use the [Vercel Platform](https://vercel.com/new?utm_medium=default-template&filter=next.js&utm_source=create-next-app&utm_campaign=create-next-app-readme) from the creators of Next.js. + +Check out our [Next.js deployment documentation](https://nextjs.org/docs/app/building-your-application/deploying) for more details. diff --git a/eslint.config.mjs b/frontend/eslint.config.mjs similarity index 100% rename from eslint.config.mjs rename to frontend/eslint.config.mjs diff --git a/next.config.ts b/frontend/next.config.ts similarity index 82% rename from next.config.ts rename to frontend/next.config.ts index a0cf0c7..9e59cd9 100644 --- a/next.config.ts +++ b/frontend/next.config.ts @@ -1,7 +1,7 @@ import type { NextConfig } from "next"; const nextConfig: NextConfig = { - /* config options here */ + devIndicators: false, cacheComponents: true, partialPrefetching: true, turbopack: { @@ -14,4 +14,4 @@ const nextConfig: NextConfig = { }, }; -export default nextConfig; +export default nextConfig; \ No newline at end of file diff --git a/package-lock.json b/frontend/package-lock.json similarity index 63% rename from package-lock.json rename to frontend/package-lock.json index a94759e..45fc97d 100644 --- a/package-lock.json +++ b/frontend/package-lock.json @@ -8,9 +8,19 @@ "name": "frontend", "version": "0.1.0", "dependencies": { + "epubjs": "^0.3.93", + "html-to-image": "^1.11.13", + "katex": "^0.19.0", + "lucide-react": "^1.61.0", + "mermaid": "^12.2.0", "next": "16.4.2", "react": "19.3.0", - "react-dom": "19.3.0" + "react-dom": "19.3.0", + "react-markdown": "^10.1.0", + "rehype-katex": "^7.0.1", + "remark-gfm": "^4.0.1", + "remark-math": "^6.0.0", + "shiki": "^4.5.0" }, "devDependencies": { "@tailwindcss/turbopack": "^4", @@ -36,6 +46,19 @@ "url": "https://github.com/sponsors/sindresorhus" } }, + "node_modules/@antfu/install-pkg": { + "version": "2.1.0", + "resolved": "https://registry.npmjs.org/@antfu/install-pkg/-/install-pkg-2.1.0.tgz", + "integrity": "sha512-sdg9NxU3zR4Mnawfbc/x6GB5Wf17WYud5qOuEuxXjaKpYpMkISSJEjItGebXJ2bQ4DIcly4NYH23mtkGJjvKUw==", + "license": "MIT", + "dependencies": { + "package-manager-detector": "^1.8.0", + "tinyexec": "^1.3.1" + }, + "funding": { + "url": 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+ "license": "MIT", + "dependencies": { + "@types/unist": "^3.0.0", + "unist-util-stringify-position": "^4.0.0" + }, + "funding": { + "type": "opencollective", + "url": "https://opencollective.com/unified" + } + }, + "node_modules/web-namespaces": { + "version": "2.0.1", + "resolved": "https://registry.npmjs.org/web-namespaces/-/web-namespaces-2.0.1.tgz", + "integrity": "sha512-bKr1DkiNa2krS7qxNtdrtHAmzuYGFQLiQ13TsorsdT6ULTkPLKuu5+GsFpDlg6JFjUTwX2DyhMPG2be8uPrqsQ==", + "license": "MIT", + "funding": { + "type": "github", + "url": "https://github.com/sponsors/wooorm" + } + }, "node_modules/which": { "version": "2.0.2", "resolved": "https://registry.npmjs.org/which/-/which-2.0.2.tgz", @@ -6861,6 +10349,16 @@ "peerDependencies": { "zod": "^3.25.0 || ^4.0.0" } + }, + "node_modules/zwitch": { + "version": "2.0.4", + "resolved": "https://registry.npmjs.org/zwitch/-/zwitch-2.0.4.tgz", + "integrity": "sha512-bXE4cR/kVZhKZX/RjPEflHaKVhUVl85noU3v6b8apfQEc1x4A+zBxjZ4lN8LqGd6WZ3dl98pY4o717VFmoPp+A==", + "license": "MIT", + "funding": { + "type": "github", + "url": "https://github.com/sponsors/wooorm" + } } } } diff --git a/package.json b/frontend/package.json similarity index 56% rename from package.json rename to frontend/package.json index 66b49b0..1d6e8f3 100644 --- a/package.json +++ b/frontend/package.json @@ -9,9 +9,24 @@ "lint": "eslint" }, "dependencies": { + "epubjs": "^0.3.93", + "html-to-image": "^1.11.13", + "katex": "^0.19.0", + "lucide-react": "^1.61.0", + "mermaid": "^12.2.0", "next": "16.4.2", "react": "19.3.0", - "react-dom": "19.3.0" + "react-dom": "19.3.0", + "react-markdown": "^10.1.0", + "rehype-katex": "^7.0.1", + "remark-gfm": "^4.0.1", + "remark-math": "^6.0.0", + "shiki": "^4.5.0" + }, + "overrides": { + "epubjs": { + "@xmldom/xmldom": "^0.9.12" + } }, "devDependencies": { "@tailwindcss/turbopack": "^4", diff --git a/public/file.svg b/frontend/public/file.svg similarity index 100% rename from public/file.svg rename to frontend/public/file.svg diff --git a/public/globe.svg b/frontend/public/globe.svg similarity index 100% rename from public/globe.svg rename to frontend/public/globe.svg diff --git a/public/next.svg b/frontend/public/next.svg similarity index 100% rename from public/next.svg rename to frontend/public/next.svg diff --git a/public/vercel.svg b/frontend/public/vercel.svg similarity index 100% rename from public/vercel.svg rename to frontend/public/vercel.svg diff --git a/public/window.svg b/frontend/public/window.svg similarity index 100% rename from public/window.svg rename to frontend/public/window.svg diff --git a/src/app/favicon.ico b/frontend/src/app/favicon.ico similarity index 100% rename from src/app/favicon.ico rename to frontend/src/app/favicon.ico diff --git a/frontend/src/app/globals.css b/frontend/src/app/globals.css new file mode 100644 index 0000000..d242d68 --- /dev/null +++ b/frontend/src/app/globals.css @@ -0,0 +1,128 @@ +@import "tailwindcss"; + +/* Full-book reading stays above the workspace, keeping chat state mounted. */ +.open-full-book { display: flex; align-items: center; gap: 7px; padding: 9px 12px; border: 1px solid #b9cbb8; border-radius: 7px; color: var(--accent); background: var(--accent-soft); font-size: 12px; } +.book-card-read { display: flex; align-items: center; gap: 5px; margin-top: 12px; padding: 5px 0; color: var(--accent); font-size: 11px; } +.book-card-read:hover { text-decoration: underline; } +.epub-reader { position: fixed; inset: 0; z-index: 100; display: flex; flex-direction: column; background: #f1efe7; color: var(--fg); } +.epub-toolbar { display: flex; align-items: center; gap: 18px; min-height: 74px; padding: 12px 28px; border-bottom: 1px solid var(--border); background: var(--bg-card); } +.epub-toolbar button, .epub-footer button { display: flex; align-items: center; justify-content: center; gap: 7px; padding: 9px; border-radius: 6px; font-size: 12px; } +.epub-toolbar button:hover, .epub-footer button:hover { background: var(--accent-soft); } +.epub-book-title { flex: 1; min-width: 0; } +.epub-book-title strong, .epub-book-title small { display: block; overflow: hidden; text-overflow: ellipsis; white-space: nowrap; } +.epub-book-title strong { font: 17px Georgia, serif; } +.epub-book-title small { margin-top: 4px; color: var(--fg-muted); font-size: 11px; } +.epub-font-controls { display: flex; align-items: center; gap: 6px; border-left: 1px solid var(--border); padding-left: 12px; font-size: 12px; } +.epub-body { flex: 1; min-height: 0; display: flex; gap: 24px; padding: 24px; } +.epub-toc { width: 260px; flex-shrink: 0; overflow-y: auto; background: var(--bg-card); border: 1px solid var(--border); border-radius: 6px; } +.epub-toc h3 { position: sticky; top: 0; display: flex; align-items: center; gap: 8px; padding: 18px 16px; margin: 0; background: var(--bg-card); font-size: 14px; border-bottom: 1px solid var(--border); } +.epub-toc button { display: block; width: 100%; padding: 11px 16px; text-align: left; font-size: 13px; line-height: 1.6; overflow-wrap: anywhere; } +.epub-toc button:hover, .epub-toc button[aria-current] { background: var(--accent-soft); color: var(--accent); } +.epub-toc > p { padding: 16px; font-size: 12px; color: var(--fg-muted); } +.epub-paper { flex: 1; position: relative; min-width: 0; max-width: 1000px; margin: 0 auto; padding: 18px 24px; background: var(--bg-card); border: 1px solid #e3dfd3; box-shadow: 0 4px 24px #283d3010; border-radius: 4px; } +.epub-viewport { width: 100%; height: 100%; overflow: hidden; } +.epub-loading { position: absolute; inset: 0; z-index: 2; display: flex; flex-direction: column; align-items: center; justify-content: center; background: var(--bg-card); color: var(--accent); font-size: 13px; } +.epub-error { position: absolute; top: 12px; left: 12px; right: 12px; z-index: 3; padding: 16px; background: #f6e7dc; border: 1px solid #dbbf9d; color: #835c43; font-size: 13px; } +.epub-error button { display: flex; align-items: center; gap: 6px; margin-top: 8px; text-decoration: underline; } +.epub-selection { display: flex; align-items: center; justify-content: center; gap: 16px; padding: 10px 16px; background: #dfe9df; font-size: 12px; } +.epub-selection button { display: flex; align-items: center; gap: 6px; padding: 8px 12px; background: var(--accent); color: white; border-radius: 6px; } +.epub-footer { display: flex; align-items: center; justify-content: space-between; gap: 12px; min-height: 68px; padding: 10px 28px; padding-bottom: max(10px, env(safe-area-inset-bottom)); background: var(--bg-card); border-top: 1px solid var(--border); } +.epub-footer > div { min-width: 0; max-width: 65%; text-align: center; } +.epub-footer strong, .epub-footer small { display: block; overflow: hidden; white-space: nowrap; text-overflow: ellipsis; } +.epub-footer strong { font-size: 12px; font-weight: 400; } +.epub-footer small { margin-top: 5px; font-size: 10px; color: var(--fg-muted); } +@media (max-width: 680px) { + .open-full-book { padding: 8px; } + .epub-toolbar { min-height: 64px; gap: 8px; padding: 8px; } + .epub-toolbar > button span { display: none; } + .epub-font-controls { padding-left: 4px; gap: 2px; } + .epub-body { padding: 8px; gap: 0; } + .epub-paper { padding: 8px 0; } + .epub-toc { position: absolute; z-index: 5; top: 72px; bottom: 80px; left: 8px; width: min(300px, calc(100% - 16px)); box-shadow: 10px 0 32px #283d3033; } + .epub-footer { padding: 8px; } + .epub-footer button span { display: none; } +} + +:root { + /* 暖纸色、墨绿色的阅读空间设计系统 */ + --bg: #f6f4ef; + --bg-card: #fffdf8; + --bg-raised: #eeece6; + --bg-hover: rgba(36, 59, 51, .06); + --fg: #243b33; + --fg-muted: #7e887f; + --border: #dfded7; + --border-strong: #c7c9bf; + --accent: #31594a; + --accent-hover: #23483a; + --accent-soft: #dfe9df; + --user-bubble: #31594a; + --assistant-bubble: transparent; + --danger: #bd6058; + --success: #59896b; +} + +body { + background: var(--bg); + color: var(--fg); + font-family: Arial, "PingFang SC", "Microsoft YaHei", sans-serif; +} + +.library-sidebar{background:#eff0ea;border-right:1px solid var(--border);z-index:30}.brand{padding:25px 22px 22px}.brand-mark{width:36px;height:36px;border-radius:11px;color:#f8f5ed;background:var(--accent);box-shadow:5px 5px 0 #c9d8ca}.brand-name{margin:0;font:700 18px Georgia,serif}.nav-library{width:100%;border:0;display:flex;align-items:center;gap:10px;padding:11px 12px;border-radius:10px;color:var(--fg-muted);font-size:13px;text-align:left;cursor:pointer}.nav-library span{margin-left:auto;font-size:11px;color:#a6aaa0}.nav-library:hover,.nav-library.active{color:var(--fg);background:rgba(49,89,74,.1)}.upload-button{border:1px solid #254a3c;border-radius:9px;padding:11px 13px;color:#f8f5ed;background:var(--accent);font-size:13px;font-weight:700;cursor:pointer;box-shadow:0 5px 0 #c5d5c6}.sidebar-footer{padding:14px 16px 18px;margin-top:auto;border-top:1px solid var(--border)}.reading-note{display:flex;gap:7px;padding:9px 7px 15px;color:#9a8470;font:italic 12px Georgia,serif}.sidebar-footer>button{width:100%;display:flex;align-items:center;gap:9px;border:0;padding:9px 7px;color:var(--fg-muted);background:transparent;font-size:12px;text-align:left}.sidebar-footer>button span{flex:1}.sidebar-edition{display:block;margin-top:12px;color:#abb0a8;font-size:8px;letter-spacing:.16em}.sidebar-resizer{width:3px!important;background:var(--border)!important}.main-panel{background:var(--bg)}.reader-header{min-height:72px;padding:0 36px;background:rgba(246,244,239,.9)}.reader-header h2{font:18px Georgia,serif}.back-library{display:none}.conversation-sidebar{width:204px;background:#f0f0eb;border-right:1px solid var(--border)}.composer-area{background:rgba(246,244,239,.95);border-top:1px solid var(--border)}.composer{background:var(--bg-card);border:1px solid #d9dbd3;box-shadow:0 7px 20px rgba(36,59,51,.06)}.composer:focus-within{border-color:#8eaa94}.mobile-menu,.sidebar-scrim{display:none}.streaming-answer{border-left:2px solid #99b89f;padding-left:12px} + +::selection { + background: #bfd7c8; +} + +/* Scrollbar */ +::-webkit-scrollbar { width: 6px; height: 6px; } +::-webkit-scrollbar-thumb { background: #c9cdc6; border-radius: 3px; } +::-webkit-scrollbar-thumb:hover { background: #a9b2a6; } +::-webkit-scrollbar-track { background: transparent; } + +button { cursor: pointer; } +button:disabled { cursor: default; opacity: .5; } +:focus-visible { outline: 2px solid #7a9b80; outline-offset: 3px; } +.topbar-note { color: #9a9e90; font: italic 12px Georgia, serif; } +.breadcrumb-slash { margin: 0 10px; color: #b8c0b6; } +.books-toolbar h2 span { color: #8e9e8d; font: 12px Arial, sans-serif; margin-left: 6px; } +.book-card-info span { color: #889687; font-size: 10px; letter-spacing: .08em; } +.book-open-label { position: absolute; right: 10px; bottom: 8px; display: flex; gap: 4px; align-items: center; color: var(--accent); font-size: 10px; opacity: 0; } +.book-card:hover .book-open-label, .book-card:focus-within .book-open-label { opacity: 1; } +.book-card-delete { position: absolute; right: 5px; top: 5px; } +.book-card:focus-within .book-card-delete button { opacity: 1; } +.book-cover h3 { display: -webkit-box; -webkit-line-clamp: 3; -webkit-box-orient: vertical; overflow: hidden; overflow-wrap: anywhere; } +.add-book-card small { color: #a1ad9f; font-size: 10px; } +.orbit { position: absolute; border: 1px solid #8da68b; border-radius: 50%; opacity: .4; } +.orbit-one { width: 310px; height: 145px; top: 65px; left: 15px; transform: rotate(-25deg); } +.orbit-two { width: 250px; height: 110px; top: 79px; left: 45px; transform: rotate(35deg); } +.art-caption { position: absolute; bottom: 3px; right: 22px; color: #a8bda9; font: italic 11px Georgia, serif; } +.book-line { width: 80%; height: 1px; background: #bda988; } +.cover-motif { display: flex; gap: 3px; } +.cover-motif span { width: 3px; height: 3px; border: 1px solid currentColor; border-radius: 50%; } +.text-link { display: flex; align-items: center; gap: 5px; color: var(--accent); font-size: 12px; } +.library-state p { font-size: 12px; } +.hero-art { flex-shrink: 0; } +.hero-copy { min-width: 0; } +.hero-button:hover { background: rgba(255,255,255,.16); } +.prompt-grid button:hover { background: var(--accent-soft); border-color: #9bb79e; } +.no-results { grid-column: 1 / -1; } +@media (max-width: 1100px) and (min-width: 681px) { + .library-hero { padding: 32px; } + .hero-copy h1 { font-size: 36px; } + .hero-art { width: 220px; margin-left: -30px; } + .art-book-front { left: 5px; } + .orbit { display: none; } +} +@media (max-width: 680px) { + .topbar-note, .desktop-break { display: none; } + .hero-art { width: 365px; } + .library-sidebar.is-open .brand { padding-left: 65px; } + .book-card-delete button { opacity: 1; } + .book-cover h3 { font-size: 13px; } +} +@media (prefers-reduced-motion: reduce) { + *, *::before, *::after { scroll-behavior: auto !important; transition: none !important; animation: none !important; } +} +.library-page{min-height:100%;overflow-y:auto}.library-topbar{height:70px;display:flex;align-items:center;justify-content:space-between;max-width:1170px;margin:auto;padding:0 30px;color:#9ba49c;font-size:12px}.library-content{max-width:1170px;margin:auto;padding:0 30px 24px}.library-hero{min-height:370px;display:flex;align-items:center;justify-content:space-between;padding:46px 50px 42px 64px;border-radius:5px;color:#f6f3eb;background:#31594a;overflow:hidden;position:relative}.hero-copy{position:relative;z-index:2}.eyebrow{display:block;color:#a9c0aa;font-size:10px;letter-spacing:.2em;font-weight:700}.hero-copy h1{margin:22px 0 17px;font:400 46px/1.2 Georgia,serif}.hero-copy h1 span{color:#e6bb8d}.hero-copy p{margin:0;color:#c2d1c2;font-size:14px;line-height:1.9}.hero-button{display:flex;align-items:center;gap:9px;margin-top:26px;border:1px solid #a3c0a6;border-radius:4px;padding:11px 15px;color:#eff5ed;background:rgba(255,255,255,.08);font-size:12px}.hero-art{width:365px;height:280px;position:relative}.art-book{position:absolute;display:flex;flex-direction:column;justify-content:space-between;box-shadow:12px 16px 0 rgba(22,50,39,.25)}.art-book-back{width:125px;height:175px;right:26px;top:34px;padding:23px 16px;color:#efe5d4;background:#9c7763;font:bold 11px/1.3 Arial;transform:rotate(10deg)}.art-book-front{width:144px;height:198px;left:76px;top:44px;align-items:center;padding:24px 16px 18px;color:#3c5e4b;background:#e8dbbe;font:26px Georgia,serif;transform:rotate(-8deg)}.art-book-front small{font:8px Arial;letter-spacing:.16em;color:#9e896e}.art-star{position:absolute;top:10px;right:45px;color:#dfbd93;font-size:30px}.books-section{padding:45px 4px 0}.books-toolbar{display:flex;justify-content:space-between;align-items:end;margin-bottom:23px}.books-toolbar h2{margin:0;font:27px Georgia,serif}.books-toolbar p{margin:8px 0 0;color:#9ca49c;font-size:12px}.book-search{width:220px;display:flex;align-items:center;gap:8px;padding:9px 11px;border-bottom:1px solid #c9cdc5;color:#99a39a}.book-search input{width:100%;border:0;outline:0;color:var(--fg);background:transparent;font-size:12px}.book-grid{display:grid;grid-template-columns:repeat(4,minmax(0,1fr));gap:26px 18px}.book-card{position:relative;min-width:0}.book-card-open{width:100%;border:0;padding:0;color:inherit;background:transparent;text-align:left}.book-stage{aspect-ratio:1.28/1;display:flex;align-items:center;justify-content:center;position:relative;overflow:hidden;border-radius:4px}.cover-tone-0{background:#dbe4dc}.cover-tone-1{background:#e8ddca}.cover-tone-2{background:#d5e0e4}.cover-tone-3{background:#e5d7da}.book-cover{width:43%;aspect-ratio:.7;display:flex;flex-direction:column;align-items:center;justify-content:space-between;padding:15px 10px 11px;color:#e8eddf;background:#31594a;box-shadow:7px 9px 0 rgba(58,77,66,.2);text-align:center;transform:rotate(-3deg)}.cover-tone-1 .book-cover{color:#594c3c;background:#d5a982}.cover-tone-2 .book-cover{background:#466d73}.cover-tone-3 .book-cover{background:#c48f95}.book-cover h3{margin:auto 0;font:15px/1.25 Georgia,serif}.cover-label,.cover-author{font-size:6px;letter-spacing:.12em}.book-card-info{padding:13px 1px 0}.book-card-info h3{overflow:hidden;margin:0;color:var(--fg);font:16px Georgia,serif;text-overflow:ellipsis;white-space:nowrap}.book-card-info p{margin:5px 0 8px;color:#89938b;font-size:11px}.add-book-card{min-height:230px;display:flex;flex-direction:column;align-items:center;justify-content:center;border:1px dashed #bfc7bf;color:#74877a;background:rgba(255,255,255,.3)}.add-book-card>span{display:grid;place-items:center;width:46px;height:46px;margin-bottom:13px;border:1px solid #a8bca9;border-radius:50%;color:#6e9277}.add-book-card strong{font:15px Georgia,serif}.add-book-card p{margin:7px 0 20px;color:#9aa59c;font-size:11px}.library-state{min-height:220px;display:flex;flex-direction:column;align-items:center;justify-content:center;gap:6px;color:#9ca69d;text-align:center}.library-state h3{margin:3px 0 0;color:var(--fg);font:17px Georgia,serif}.library-bottom{display:flex;justify-content:space-between;margin-top:48px;padding-top:14px;border-top:1px solid var(--border);color:#abb1a9;font-size:10px}.chat-welcome{max-width:650px;margin:auto;padding:45px 0 25px;text-align:center}.chat-welcome-icon{display:grid;place-items:center;width:63px;height:63px;margin:0 auto 20px;border:1px solid #c4d2c4;border-radius:50%;color:var(--accent);background:#eaf0e9}.chat-welcome h2{margin:14px 0 8px;font:30px Georgia,serif}.chat-welcome>p{margin:0;color:#89938b;font-size:13px}.prompt-grid{display:grid;grid-template-columns:repeat(3,1fr);gap:10px;margin-top:33px;text-align:left}.prompt-grid button{min-height:132px;display:flex;flex-direction:column;align-items:flex-start;gap:9px;padding:14px;border:1px solid var(--border);border-radius:5px;color:var(--fg-muted);background:rgba(255,255,255,.3);text-align:left}.prompt-grid strong{color:var(--fg);font-size:12px}.prompt-grid span{font-size:11px;line-height:1.55}.prompt-grid svg:last-child{margin-top:auto;align-self:flex-end;color:#a7b6a9} +@media(max-width:900px){.library-hero{padding-left:38px}.hero-art{transform:scale(.8)}.book-grid{grid-template-columns:repeat(3,minmax(0,1fr))}}@media(max-width:680px){.mobile-menu{display:grid;place-items:center;position:fixed;top:13px;left:13px;z-index:50;width:38px;height:38px;border:1px solid var(--border);border-radius:9px;color:var(--fg);background:var(--bg-card)}.sidebar-scrim{display:block;position:fixed;inset:0;z-index:20;border:0;background:rgba(20,36,28,.28)}.library-sidebar{position:fixed;inset:0 auto 0 0;width:270px!important;transform:translateX(-105%);transition:transform .22s}.library-sidebar.is-open{transform:translateX(0)}.sidebar-resizer,.conversation-sidebar{display:none}.library-topbar{height:64px;padding-left:65px}.library-content{padding:0 16px 20px}.library-hero{min-height:460px;align-items:flex-start;padding:34px 25px}.hero-copy h1{font-size:37px}.hero-art{position:absolute;right:-85px;bottom:-35px;transform:scale(.7)}.books-section{padding-top:31px}.books-toolbar{display:block}.book-search{width:100%;margin-top:20px}.book-grid{grid-template-columns:repeat(2,minmax(0,1fr));gap:24px 12px}.book-stage{aspect-ratio:1/1.08}.book-cover{width:50%}.library-bottom{display:none}.reader-header{min-height:62px;padding-left:57px}.back-library{display:grid;place-items:center}.chat-welcome{padding:30px 8px}.chat-welcome h2{font-size:25px}.prompt-grid{grid-template-columns:1fr}.prompt-grid button{min-height:0}.composer-hint{display:none}} diff --git a/frontend/src/app/layout.tsx b/frontend/src/app/layout.tsx new file mode 100644 index 0000000..1e6e86d --- /dev/null +++ b/frontend/src/app/layout.tsx @@ -0,0 +1,15 @@ +import type { Metadata } from "next"; +import "./globals.css"; + +export const metadata: Metadata = { + title: "BookMate - AI 读书助手", + description: "上传 EPUB，和 AI 一起读书", +}; + +export default function RootLayout({ children }: { children: React.ReactNode }) { + return ( + + {children} + + ); +} \ No newline at end of file diff --git a/frontend/src/app/page.tsx b/frontend/src/app/page.tsx new file mode 100644 index 0000000..741d93a --- /dev/null +++ b/frontend/src/app/page.tsx @@ -0,0 +1,899 @@ +"use client"; + +import { useState, useEffect, useMemo, useRef } from "react"; +import { + BookMarked, BookOpen, Bot, Check, ChevronDown, ChevronLeft, ChevronRight, Copy, + Download, GitBranch, Loader2, Paperclip, Plus, RotateCcw, Send, Settings2, + Sparkles, Trash2, Upload, User, X, ArrowUpRight, Library, Search, Menu, MessageSquare, ArrowLeft, +} from "lucide-react"; +import { api, Book, Conversation, Message, Citation, AiModelEntry, formatCharCount } from "@/lib/api"; +import MarkdownRenderer from "@/components/MarkdownRenderer"; +import ModelManagerDialog from "@/components/ModelManagerDialog"; +import CitationReaderDialog from "@/components/CitationReaderDialog"; +import EpubReader from "@/components/EpubReader"; + +const SIDEBAR_MIN = 180; +const SIDEBAR_MAX = 480; + +export default function Home() { + const [books, setBooks] = useState([]); + const [selectedBook, setSelectedBook] = useState(null); + const [conversations, setConversations] = useState([]); + const [activeConv, setActiveConv] = useState(null); + const [messages, setMessages] = useState([]); + const [input, setInput] = useState(""); + const [streaming, setStreaming] = useState(false); + const [streamContent, setStreamContent] = useState(""); + const [uploading, setUploading] = useState(false); + const [model, setModel] = useState("deepseek"); + const [aiModels, setAiModels] = useState([]); + const [pickerOpen, setPickerOpen] = useState(false); + const [managerOpen, setManagerOpen] = useState(false); + const [readerBook, setReaderBook] = useState(null); + const [search, setSearch] = useState(""); + const [sidebarOpen, setSidebarOpen] = useState(false); + const [booksLoading, setBooksLoading] = useState(true); + const [booksError, setBooksError] = useState(false); + const chatEndRef = useRef(null); + const fileInputRef = useRef(null); + const [sidebarWidth, setSidebarWidth] = useState(256); + const sidebarDragRef = useRef<{ startX: number; startW: number } | null>(null); + // 多版本回答：每个 user 消息当前选中哪个版本的回答（key = user 消息 id） + const [activeVersions, setActiveVersions] = useState>({}); + // 流式状态归属：null 表示新问题（渲染在末尾）；有值表示重试某条 user 消息（渲染在该轮内） + const [streamTurnId, setStreamTurnId] = useState(null); + + const turns = useMemo(() => buildTurns(messages), [messages]); + + const loadBooks = () => { + setBooksLoading(true); + setBooksError(false); + api.listBooks().then(setBooks).catch(() => setBooksError(true)).finally(() => setBooksLoading(false)); + }; + useEffect(() => { + api.listBooks().then(setBooks).catch(() => setBooksError(true)).finally(() => setBooksLoading(false)); + }, []); + + // 加载可用模型；默认选中第一个（通常是 deepseek） + useEffect(() => { + api.listModels().then((ms) => { + setAiModels(ms); + if (ms.length > 0) setModel((cur) => (ms.some((m) => m.name === cur) ? cur : ms[0].name)); + }).catch(() => setAiModels([])); + }, []); + + const currentModel = aiModels.find((m) => m.name === model) ?? aiModels[0]; + + // 恢复/保存侧栏宽度（localStorage） + useEffect(() => { + const saved = localStorage.getItem("bookmate.sidebarWidth"); + const n = saved ? Number(saved) : 256; + if (Number.isFinite(n)) setSidebarWidth(Math.max(SIDEBAR_MIN, Math.min(SIDEBAR_MAX, n))); + }, []); + useEffect(() => { + localStorage.setItem("bookmate.sidebarWidth", String(sidebarWidth)); + }, [sidebarWidth]); + + useEffect(() => { + if (selectedBook) api.listConversations(selectedBook.id).then(setConversations); + }, [selectedBook]); + + useEffect(() => { + if (activeConv) api.getMessages(activeConv.id).then(setMessages); + }, [activeConv]); + + useEffect(() => { chatEndRef.current?.scrollIntoView({ behavior: "smooth" }); }, [messages, streamContent]); + + const handleUpload = async (e: React.ChangeEvent) => { + const file = e.target.files?.[0]; + if (!file) return; + setUploading(true); + try { + const book = await api.uploadBook(file); + setBooks((prev) => [book, ...prev]); + setSelectedBook(book); + } catch (err: unknown) { + alert(err instanceof Error ? err.message : "Upload failed"); + } + setUploading(false); + if (fileInputRef.current) fileInputRef.current.value = ""; + }; + + const startChat = async (book: Book) => { + setSidebarOpen(false); + setSelectedBook(book); + setActiveConv(null); + setMessages([]); + const convs = await api.listConversations(book.id); + setConversations(convs); + if (convs.length > 0) { + setActiveConv(convs[0]); + } else { + const conv = await api.createConversation(book.id, model); + setConversations([conv]); + setActiveConv(conv); + } + }; + + const handleSend = async () => { + if (!input.trim() || streaming) return; + let conv = activeConv; + if (!conv && selectedBook) { + conv = await api.createConversation(selectedBook.id, model); + setConversations((prev) => [conv!, ...prev]); + setActiveConv(conv); + } + if (!conv) return; + + const userContent = input; + setInput(""); + const tempId = `temp-${Date.now()}`; + setMessages((prev) => [...prev, { id: tempId, conversation_id: conv!.id, parent_message_id: null, role: "user", content: userContent, citations: null, model, created_at: new Date().toISOString() }]); + setStreaming(true); + setStreamContent(""); + setStreamTurnId(null); + + let fullContent = ""; + try { + const resp = await api.sendMessage(conv!.id, userContent, model); + const reader = resp.body?.getReader(); + if (!reader) throw new Error("No reader"); + + const decoder = new TextDecoder(); + let buffer = ""; + let assistantId = ""; + let finalCitations: Citation[] = []; + + while (true) { + const { done, value } = await reader.read(); + if (done) break; + buffer += decoder.decode(value, { stream: true }); + const lines = buffer.split("\n"); + buffer = lines.pop() || ""; + + for (const line of lines) { + if (!line.startsWith("data: ")) continue; + const data = JSON.parse(line.slice(6)); + if (data.type === "token") { + fullContent += data.content; + setStreamContent(fullContent); + } else if (data.type === "done") { + assistantId = data.message_id; + finalCitations = data.citations || []; + } else if (data.type === "error") { + throw new Error(data.content); + } + } + } + setMessages((prev) => { + const filtered = prev.filter((m) => m.id !== tempId); + const userMsg: Message = { id: tempId, conversation_id: conv!.id, parent_message_id: null, role: "user", content: userContent, citations: null, model, created_at: new Date().toISOString() }; + const aiMsg: Message = { id: assistantId, conversation_id: conv!.id, parent_message_id: null, role: "assistant", content: fullContent, citations: finalCitations, model, created_at: new Date().toISOString() }; + return [...filtered, userMsg, aiMsg]; + }); + } catch (err: unknown) { + if (fullContent.trim()) { + // 输出被中断（流式错误/网络）：保留已生成的部分，不吞掉内容 + setMessages((prev) => [ + ...prev.filter((m) => m.id !== tempId), + { + id: `interrupted-${Date.now()}`, conversation_id: conv!.id, parent_message_id: null, + role: "assistant", content: fullContent, citations: null, model, + created_at: new Date().toISOString(), + }, + ]); + } + alert(err instanceof Error ? err.message : "Chat error"); + } + setStreaming(false); + setStreamContent(""); + }; + + const handleRetry = async (userMsg: Message) => { + if (streaming) return; + setStreaming(true); + setStreamContent(""); + setStreamTurnId(userMsg.id); + let fullContent = ""; + try { + const conv = activeConv!; + // replyTo = 被重试的用户消息：后端不再新建 user 消息，新回答挂为它的新版本 + const resp = await api.sendMessage(conv.id, userMsg.content, userMsg.model || model, userMsg.id); + const reader = resp.body?.getReader(); + if (!reader) throw new Error("No reader"); + const decoder = new TextDecoder(); + let buffer = ""; + let assistantId = ""; + let finalCitations: Citation[] = []; + + while (true) { + const { done, value } = await reader.read(); + if (done) break; + buffer += decoder.decode(value, { stream: true }); + const lines = buffer.split("\n"); + buffer = lines.pop() || ""; + for (const line of lines) { + if (!line.startsWith("data: ")) continue; + const data = JSON.parse(line.slice(6)); + if (data.type === "token") { + fullContent += data.content; + setStreamContent(fullContent); + } else if (data.type === "done") { + assistantId = data.message_id; + finalCitations = data.citations || []; + } else if (data.type === "error") { + throw new Error(data.content); + } + } + } + // 新版本生成完毕：追加为被重试 user 消息之下的一个新回答版本（parent 指向它） + const newIdx = buildTurns(messages).find((t) => t.user.id === userMsg.id)?.versions.length ?? 0; + setMessages((prev) => [...prev, { + id: assistantId, conversation_id: conv.id, parent_message_id: userMsg.id, + role: "assistant", content: fullContent, citations: finalCitations, + model: userMsg.model || model, created_at: new Date().toISOString(), + }]); + setActiveVersions((prev) => ({ ...prev, [userMsg.id]: newIdx })); + } catch (err: unknown) { + if (fullContent.trim()) { + // 重试生成被中断：保留已生成的部分作为该问题的版本，不吞掉内容 + const newIdx = buildTurns(messages).find((t) => t.user.id === userMsg.id)?.versions.length ?? 0; + setMessages((prev) => [ + ...prev, + { + id: `interrupted-${Date.now()}`, conversation_id: activeConv!.id, parent_message_id: userMsg.id, + role: "assistant", content: fullContent, citations: null, + model: userMsg.model || model, created_at: new Date().toISOString(), + }, + ]); + setActiveVersions((prev) => ({ ...prev, [userMsg.id]: newIdx })); + } + alert(err instanceof Error ? err.message : "Retry failed"); + } + setStreaming(false); + setStreamContent(""); + setStreamTurnId(null); + }; + + const handleCopy = async (text: string) => { + await navigator.clipboard.writeText(text); + }; + + const handleDelete = async (msgId: string) => { + if (!confirm("删除这条消息？")) return; + try { + await api.deleteMessage(msgId); + setMessages((prev) => prev.filter((m) => m.id !== msgId)); + } catch { + alert("删除失败"); + } + }; + + const handleBranch = async (msgId: string) => { + if (!activeConv) return; + try { + const branch = await api.branchConversation(activeConv.id, msgId); + setConversations((prev) => [branch, ...prev]); + setActiveConv(branch); + } catch { + alert("创建分支失败"); + } + }; + + const handleNewConversation = async () => { + if (!selectedBook) return; + try { + const conv = await api.createConversation(selectedBook.id, model); + setConversations((prev) => [conv, ...prev]); + setActiveConv(conv); + setMessages([]); + } catch { + alert("新建对话失败"); + } + }; + + const handleDeleteConversation = async (convId: string) => { + if (!confirm("删除这个对话？")) return; + try { + await api.deleteConversation(convId); + setConversations((prev) => prev.filter((c) => c.id !== convId)); + if (activeConv?.id === convId) { + setActiveConv(null); + setMessages([]); + } + } catch { + alert("删除失败"); + } + }; + + const handleDeleteBook = async (book: Book) => { + if (!confirm(`删除《${book.title || book.filename}》？书、目录和对话都会被删除。`)) return; + try { + await api.deleteBook(book.id); + setBooks((prev) => prev.filter((b) => b.id !== book.id)); + if (selectedBook?.id === book.id) { + setSelectedBook(null); + setActiveConv(null); + setConversations([]); + setMessages([]); + } + } catch { + alert("删除失败"); + } + }; + + const handleExport = async () => { + if (!activeConv) return; + try { + const data = await api.exportConversation(activeConv.id); + const blob = new Blob([data.content], { type: "text/markdown" }); + const url = URL.createObjectURL(blob); + const a = document.createElement("a"); + a.href = url; + a.download = `${data.title || "conversation"}.md`; + a.click(); + URL.revokeObjectURL(url); + } catch { + alert("导出失败"); + } + }; + + const selectConv = (conv: Conversation) => { + setActiveConv(conv); + setMessages([]); + }; + + // 侧栏拖动调整宽度（pointer capture + window 监听，拖动期间禁选文本） + const onSidebarResizePointerDown = (e: React.PointerEvent) => { + if (e.button !== 0) return; + e.preventDefault(); + try { e.currentTarget.setPointerCapture(e.pointerId); } catch { /* ignore */ } + sidebarDragRef.current = { startX: e.clientX, startW: sidebarWidth }; + document.body.classList.add("select-none", "cursor-col-resize"); + const onMove = (ev: PointerEvent) => { + if (!sidebarDragRef.current) return; + const next = sidebarDragRef.current.startW + (ev.clientX - sidebarDragRef.current.startX); + const max = Math.min(SIDEBAR_MAX, window.innerWidth * 0.5); + setSidebarWidth(Math.max(SIDEBAR_MIN, Math.min(max, next))); + }; + const onUp = () => { + sidebarDragRef.current = null; + document.body.classList.remove("select-none", "cursor-col-resize"); + window.removeEventListener("pointermove", onMove); + window.removeEventListener("pointerup", onUp); + window.removeEventListener("pointercancel", onUp); + }; + window.addEventListener("pointermove", onMove); + window.addEventListener("pointerup", onUp); + window.addEventListener("pointercancel", onUp); + }; + + return ( +
+ {sidebarOpen && + {/* Sidebar */} + + + {/* 可拖动分隔条：调整书库侧栏宽度 */} +
+ + {/* Main */} +
+ {selectedBook ? ( + <> +
+ +
+

{selectedBook.title || selectedBook.filename}

+

{selectedBook.author}

+
+ + +
+ +
+
+

对话历史

+ + {conversations.map((c) => ( +
+ + handleDeleteConversation(c.id)}> + + +
+ ))} +
+ +
+
+
+ {turns.length === 0 && !streaming && ( +
+
+ READ · THINK · DISCOVER +

从一个好问题开始。

+

关于《{selectedBook.title || selectedBook.filename}》，你想了解什么？

+
+ {[{ icon: BookOpen, title: "读懂这本书", prompt: "请梳理这本书的核心观点与整体结构。" }, { icon: MessageSquare, title: "深入一个观点", prompt: "这本书中有哪些值得深入思考的观点？请结合原文展开。" }, { icon: GitBranch, title: "连接知识", prompt: "请整理这本书中重要概念之间的联系。" }].map(({ icon: Icon, title, prompt }) => ( + + ))} +
+
+ )} + {turns.map((turn) => { + const isLastTurn = turn.user.id === turns[turns.length - 1]?.user.id; + const versions = [...turn.versions]; + const activeIdx = activeVersions[turn.user.id] ?? versions.length - 1; + const shown = versions[activeIdx] ?? null; + const streamingHere = streaming && streamTurnId === turn.user.id && !!streamContent; + return ( +
+ + {versions.length > 1 && ( +
+ + + 版本 {activeIdx + 1} / {versions.length} + + +
+ )} + {shown && ( + + )} + {streamingHere && ( + + )} +
+ ); + })} + {streaming && !streamTurnId && streamContent && ( + + )} +
+
+
+ +
+ {/* 输入胶囊：模型选择 + 输入合并（Perplexity 风） */} +
+
+
+
+ {pickerOpen &&
setPickerOpen(false)} />} + + {pickerOpen && ( +
+

选择回答模型

+ {aiModels.map((m) => ( + + ))} + {aiModels.length === 0 && ( +

尚未配置模型，点「管理」添加

+ )} +
+ )} +
+ +
+ +
+ setInput(e.target.value)} + onKeyDown={(e) => e.key === "Enter" && !e.shiftKey && !e.nativeEvent.isComposing && handleSend()} + placeholder={selectedBook ? "问这本书的任何问题..." : "先选择一本书"} + disabled={!selectedBook || streaming} + className="flex-1 bg-transparent px-1 py-1.5 text-sm text-[var(--fg)] placeholder-[var(--fg-muted)] focus:outline-none disabled:opacity-50" + /> + +
+
+
+
+
+
+ + ) : ( +
+
我的阅读空间 / 书库 与好书，慢慢相处
+
+
+
A LITTLE READING, A LITTLE MORE WORLD

每一本书，
都值得再读深一点。

收藏你的好书，与 AI 一起追问、思考，
让读过的每一页，都成为自己的收获。

+
+
+

我的书库 {books.length}

在这里，开启下一次思想漫游。

+ {booksLoading ?

正在整理你的书库…

: booksError ?

暂时无法加载书库

请确认阅读服务已启动，然后再试一次。

: ( +
+ {books.filter((b) => `${b.title || b.filename} ${b.author || ""}`.toLowerCase().includes(search.toLowerCase())).map((book, i) => ( +
+ + +
handleDeleteBook(book)}>
+
+ ))} + {!search && } + {search && !books.some((b) => `${b.title || b.filename} ${b.author || ""}`.toLowerCase().includes(search.toLowerCase())) &&

没有找到相关书籍

换个书名或作者试试。

} +
+ )} +
+
阅读的意义，藏在每一次思考里。MADE FOR CURIOUS MINDS
+
+
+ )} +
+ + {readerBook && ( + setReaderBook(null)} + onAsk={async (text) => { + if (streaming) { + alert("AI 正在回答，请稍后再解读这段原文。"); + return; + } + try { + if (selectedBook?.id !== readerBook.id || !activeConv) await startChat(readerBook); + setInput(text); + setReaderBook(null); + } catch { + alert("暂时无法打开对话，请稍后重试。"); + } + }} + /> + )} + setManagerOpen(false)} + models={aiModels} + onChanged={() => api.listModels().then(setAiModels)} + /> +
+ ); +} + +function ChatBubble({ + message, + isStreaming, + onCopy, + onDelete, + onBranch, + onRetry, +}: { + message: Message; + isStreaming?: boolean; + onCopy?: (text: string) => void; + onDelete?: (id: string) => void; + onBranch?: (id: string) => void; + onRetry?: (msg: Message) => void; +}) { + const [copied, setCopied] = useState(false); + const [citationsOpen, setCitationsOpen] = useState(false); + const [readerSegmentId, setReaderSegmentId] = useState(null); + const isUser = message.role === "user"; + const isStream = isStreaming || message.id === "stream"; + + // 同一段落被 AI 重复引用时只显示一条（引用渲染去重，不影响已注入的检索内容） + const uniqCitations = useMemo(() => { + const seen = new Set(); + return (message.citations ?? []).filter((c) => { + if (seen.has(c.segment_id)) return false; + seen.add(c.segment_id); + return true; + }); + }, [message.citations]); + + const handleCopy = () => { + onCopy?.(message.content); + setCopied(true); + setTimeout(() => setCopied(false), 1500); + }; + + return ( + <> +
+
+
+ {isUser ? : } +
+ +
+
+ + {uniqCitations.length > 0 && ( +
+ + + {citationsOpen && ( +
+ {uniqCitations.map((c, i) => ( +
+ [{i + 1}] + + {(c.excerpt || "").replace(/《heading_path》\s*/g, "").slice(0, 80)}{(c.excerpt || "").length > 80 ? "…" : ""} + + +
+ ))} +
+ )} +
+ )} +
+ + {!isStream && ( +
+ + {copied ? : } + + {onRetry && ( + onRetry(message)}> + + + )} + {onBranch && ( + onBranch(message.id)}> + + + )} + {onDelete && ( + onDelete(message.id)}> + + + )} +
+ )} +
+
+
+ setReaderSegmentId(null)} + /> + + ); +} + +interface Turn { + user: Message; + versions: Message[]; +} + +/** + * 把平铺的消息流聚合成「回合」列表：每个 user 消息 + 它名下的所有 AI 回答版本。 + * assistant 按 parent_message_id 归属；旧数据 parent 为 null 时，挂到它之前最近的 user。 + */ +function buildTurns(msgs: Message[]): Turn[] { + const turns: Turn[] = []; + const byUser = new Map(); + let lastTurn: Turn | null = null; + for (const m of msgs) { + if (m.role === "user") { + lastTurn = { user: m, versions: [] }; + turns.push(lastTurn); + byUser.set(m.id, lastTurn); + } else if (m.role === "assistant") { + const target = (m.parent_message_id && byUser.get(m.parent_message_id)) || lastTurn; + if (target) target.versions.push(m); + } + } + return turns; +} + +function ActionBtn({ title, onClick, children, danger }: { title: string; onClick: () => void; children: React.ReactNode; danger?: boolean }) { + return ( + + ); +} diff --git a/frontend/src/components/CitationReaderDialog.tsx b/frontend/src/components/CitationReaderDialog.tsx new file mode 100644 index 0000000..81d0f38 --- /dev/null +++ b/frontend/src/components/CitationReaderDialog.tsx @@ -0,0 +1,112 @@ +"use client"; + +import { useEffect, useState } from "react"; +import { BookOpen, Loader2, X } from "lucide-react"; +import { api } from "@/lib/api"; + +interface SegmentCtx { + segment: { id: string; text: string; order_idx: number; cfi: string | null }; + chapter: { id: string; title: string | null; level: number } | null; + before: { id: string; text: string; order_idx: number; cfi: string | null }[]; + after: { id: string; text: string; order_idx: number; cfi: string | null }[]; +} + +function cleanText(text: string): string { + // 解析阶段写入的《heading_path》占位不影响阅读，展示前清掉 + return text.replace(/《heading_path》\s*/g, ""); +} + +function Para({ text, muted }: { text: string; muted?: boolean }) { + return ( +

+ {cleanText(text)} +

+ ); +} + +export default function CitationReaderDialog({ + open, + segmentId, + onClose, +}: { + open: boolean; + segmentId: string | null; + onClose: () => void; +}) { + const [data, setData] = useState(null); + const [loading, setLoading] = useState(false); + const [error, setError] = useState(null); + + useEffect(() => { + if (!open || !segmentId) return; + setLoading(true); + setError(null); + setData(null); + api + .getSegmentContext(segmentId) + .then(setData) + .catch((e) => setError(e instanceof Error ? e.message : "加载失败")) + .finally(() => setLoading(false)); + }, [open, segmentId]); + + if (!open) return null; + + return ( +
+
e.stopPropagation()} + > + {/* 头部 */} +
+ +
+

+ {data?.chapter?.title || "阅读原文"} +

+ {data && ( +

+ 第 {data.segment.order_idx + 1} 段 + {data.segment.cfi ? " · EPUB 内定位可用" : ""} +

+ )} +
+ +
+ + {/* 正文 */} +
+ {loading && ( +
+ 加载原文… +
+ )} + {error &&

{error}

} + {data && ( + <> +
+ {data.before.map((p) => ( + + ))} +
+
+ +
+
+ {data.after.map((p) => ( + + ))} +
+ + )} +
+
+
+ ); +} \ No newline at end of file diff --git a/frontend/src/components/CodeBlock.tsx b/frontend/src/components/CodeBlock.tsx new file mode 100644 index 0000000..309d041 --- /dev/null +++ b/frontend/src/components/CodeBlock.tsx @@ -0,0 +1,42 @@ +"use client"; + +import { useEffect, useState } from "react"; + +/** + * Server-side-safe syntax highlighting: shiki is loaded lazily inside an + * effect (so SSR renders the plain fallback), and unknown languages degrade + * to a readable 
 instead of throwing.
+ */
+export default function CodeBlock({ code, language }: { code: string; language?: string }) {
+  const [html, setHtml] = useState(null);
+
+  useEffect(() => {
+    let cancelled = false;
+    const lang = language || "text";
+
+    import("shiki/bundle/web")
+      .then(async ({ codeToHtml }) => {
+        const out = await codeToHtml(code, { lang, theme: "github-dark" });
+        if (!cancelled) setHtml(out);
+      })
+      .catch(() => {
+        // Unknown language or loader failure: keep the plain fallback.
+      });
+
+    return () => {
+      cancelled = true;
+    };
+  }, [code, language]);
+
+  if (html) {
+    return (
+      

+    );
+  }
+
+  return (
+    
+      {code}
+    

+  );
+}
diff --git a/frontend/src/components/EpubReader.tsx b/frontend/src/components/EpubReader.tsx
new file mode 100644
index 0000000..3b5669b
--- /dev/null
+++ b/frontend/src/components/EpubReader.tsx
@@ -0,0 +1,195 @@
+"use client";
+
+import { useEffect, useRef, useState } from "react";
+import type { Book as EpubBook, Rendition, Location, NavItem, Contents } from "epubjs";
+import type Section from "epubjs/types/section";
+import { ArrowLeft, BookOpen, ChevronLeft, ChevronRight, List, Loader2, Minus, Plus, RotateCcw, MessageSquare } from "lucide-react";
+import { api, type Book } from "@/lib/api";
+
+interface TocEntry { href: string; label: string; depth: number }
+function flattenToc(items: NavItem[], depth = 0): TocEntry[] {
+  return items.flatMap((item) => [
+    { href: item.href, label: item.label.trim(), depth },
+    ...flattenToc(item.subitems || [], depth + 1),
+  ]);
+}
+function readSaved(key: string) {
+  try { return localStorage.getItem(key); } catch { return null; }
+}
+function save(key: string, value: string) {
+  try { localStorage.setItem(key, value); } catch { /* Reading works without storage. */ }
+}
+
+export default function EpubReader({ book, onClose, onAsk }: {
+  book: Book;
+  onClose: () => void;
+  onAsk: (text: string) => void;
+}) {
+  const dialogRef = useRef(null);
+  const viewerRef = useRef(null);
+  const renditionRef = useRef(null);
+  const closeRef = useRef(onClose);
+  const [toc, setToc] = useState([]);
+  const [tocOpen, setTocOpen] = useState(false);
+  const [loading, setLoading] = useState(true);
+  const [error, setError] = useState("");
+  const [attempt, setAttempt] = useState(0);
+  const [fontSize, setFontSize] = useState(18);
+  const [location, setLocation] = useState(null);
+  const [selectedText, setSelectedText] = useState("");
+  const [turning, setTurning] = useState(false);
+  const positionKey = `bookmate.reader.${book.id}`;
+
+  useEffect(() => { closeRef.current = onClose; }, [onClose]);
+
+  useEffect(() => {
+    const previousFocus = document.activeElement as HTMLElement | null;
+    dialogRef.current?.querySelector("button")?.focus();
+    const keydown = (event: KeyboardEvent) => {
+      if (event.key === "Escape") { event.preventDefault(); closeRef.current(); }
+      if (event.key !== "Tab") return;
+      const controls = dialogRef.current?.querySelectorAll('button:not(:disabled), [href], input, iframe, [tabindex="0"]');
+      if (!controls?.length) return;
+      const first = controls[0], last = controls[controls.length - 1];
+      if (event.shiftKey && document.activeElement === first) { event.preventDefault(); last.focus(); }
+      else if (!event.shiftKey && document.activeElement === last) { event.preventDefault(); first.focus(); }
+    };
+    document.addEventListener("keydown", keydown);
+    return () => { document.removeEventListener("keydown", keydown); previousFocus?.focus(); };
+  }, []);
+
+  useEffect(() => {
+    let disposed = false;
+    let epub: EpubBook | undefined;
+    let observer: ResizeObserver | undefined;
+    const controller = new AbortController();
+    const font = Number(readSaved("bookmate.reader.fontSize")) || 18;
+    const initialFont = Math.max(14, Math.min(28, font));
+    const open = async () => {
+      try {
+        const [{ Book: Epub }, data] = await Promise.all([
+          import("epubjs"), api.getBookFile(book.id, controller.signal),
+        ]);
+        if (disposed || !viewerRef.current) return;
+        epub = new Epub({ replacements: "blobUrl" });
+        // Register handlers for the promises epub.js rejects alongside open().
+        void epub.opened.catch(() => {});
+        void epub.ready.catch(() => {});
+        await epub.open(data, "binary");
+        if (disposed) return;
+        const navigation = await epub.loaded.navigation;
+        if (disposed) return;
+        const entries = flattenToc(navigation.toc);
+        if (!entries.length) {
+          epub.spine.each((section: Section) => {
+            if (section.linear) entries.push({ href: section.href, label: `章节 ${entries.length + 1}`, depth: 0 });
+          });
+        }
+        setToc(entries);
+        setFontSize(initialFont);
+        const host = viewerRef.current!;
+        const rendition = epub.renderTo(host, {
+          width: host.clientWidth, height: host.clientHeight,
+          spread: "none", flow: "paginated", allowScriptedContent: false,
+        });
+        renditionRef.current = rendition;
+        rendition.themes.default({
+          body: { color: "#243b33", background: "#fffdf8", "line-height": "1.9 !important", "font-family": 'Georgia, "Songti SC", "SimSun", serif' },
+          "img, svg": { "max-width": "100% !important", "max-height": "90vh !important" },
+          a: { color: "#31594a" },
+        });
+        rendition.themes.fontSize(`${initialFont}px`);
+        rendition.on("relocated", (next: Location) => {
+          if (disposed) return;
+          setLocation(next);
+          setSelectedText("");
+          if (next.start.cfi) save(positionKey, next.start.cfi);
+        });
+        rendition.on("selected", (cfi: string, contents: Contents) => {
+          if (disposed) return;
+          try { setSelectedText(contents.range(cfi).toString().trim().slice(0, 4000)); } catch { /* No selection. */ }
+        });
+        rendition.on("keyup", (event: KeyboardEvent) => {
+          if (event.key === "Escape") closeRef.current();
+        });
+        rendition.on("displayError", () => {
+          if (!disposed) setError("这一页未能显示，请重试或从目录选择其他章节。");
+        });
+        const saved = readSaved(positionKey);
+        try { await rendition.display(saved || undefined); }
+        catch {
+          if (!saved) throw new Error("无法显示书籍正文");
+          await rendition.display();
+        }
+        if (disposed) return;
+        setError("");
+        setLoading(false);
+        observer = new ResizeObserver(([entry]) => {
+          if (!disposed && entry.contentRect.width > 0 && entry.contentRect.height > 0) {
+            rendition.resize(entry.contentRect.width, entry.contentRect.height);
+          }
+        });
+        observer.observe(host);
+      } catch (err) {
+        if (!disposed) { setError(err instanceof Error ? err.message : "书籍打开失败"); setLoading(false); }
+      }
+    };
+    void open();
+    return () => {
+      disposed = true;
+      controller.abort();
+      observer?.disconnect();
+      renditionRef.current = null;
+      epub?.destroy();
+    };
+  }, [book.id, attempt, positionKey]);
+
+  const navigate = async (target: "prev" | "next" | string) => {
+    const rendition = renditionRef.current;
+    if (!rendition || turning || loading) return;
+    setTurning(true);
+    setError("");
+    try {
+      if (target === "prev") await rendition.prev();
+      else if (target === "next") await rendition.next();
+      else { await rendition.display(target); setTocOpen(false); }
+    } catch { setError("这一页未能显示，请重试或从目录选择其他章节。"); }
+    finally { setTurning(false); }
+  };
+  const changeFont = (delta: number) => {
+    const next = Math.max(14, Math.min(28, fontSize + delta));
+    setFontSize(next);
+    save("bookmate.reader.fontSize", String(next));
+    renditionRef.current?.themes.fontSize(`${next}px`);
+  };
+  const currentHref = location?.start.href.split("#")[0];
+  const currentChapter = toc.find((entry) => entry.href === location?.start.href)
+    || toc.find((entry) => entry.href.split("#")[0] === currentHref);
+
+  return (
+    

+      

+        
+        
{book.title || book.filename}{book.author || "完整 EPUB 阅读"}

+        
+        
{fontSize}

+      

+      

+        {tocOpen && }
+        

+          {loading && 
正在翻开这本书…
}
+          {error && 
{error}
}
+          

+        

+      

+      {selectedText && 
已选中 {selectedText.length} 字
}
+      

+        
+        
{currentChapter?.label || "阅读原文"}{location ? `本节 ${location.start.displayed.page} / ${location.start.displayed.total} 页` : "保留原书正文、图片与目录"} · 自动记住阅读位置

+        
+      

+    

+  );
+}
diff --git a/frontend/src/components/MarkdownRenderer.tsx b/frontend/src/components/MarkdownRenderer.tsx
new file mode 100644
index 0000000..5faaec8
--- /dev/null
+++ b/frontend/src/components/MarkdownRenderer.tsx
@@ -0,0 +1,130 @@
+"use client";
+
+import { Children, type ReactElement, type ReactNode } from "react";
+import ReactMarkdown from "react-markdown";
+import remarkGfm from "remark-gfm";
+import remarkMath from "remark-math";
+import rehypeKatex from "rehype-katex";
+import "katex/dist/katex.min.css";
+
+import CodeBlock from "./CodeBlock";
+import MermaidDiagram from "./MermaidDiagram";
+import MindMap, { isMermaidMindMapSource } from "./MindMap";
+
+interface Props {
+  content: string;
+  variant?: "light" | "dark";
+}
+
+/** Extract raw text out of react-markdown's children for a code block. */
+function codeText(children: React.ReactNode): string {
+  const raw = Array.isArray(children) ? children.join("") : String(children ?? "");
+  return raw.replace(/\n$/, "");
+}
+
+export default function MarkdownRenderer({ content, variant = "light" }: Props) {
+  const dark = variant === "dark";
+
+  return (
+     (
+          
{children}

+        ),
+        h2: ({ children }) => (
+          
{children}

+        ),
+        h3: ({ children }) => (
+          
{children}

+        ),
+        p: ({ children }) => 
{children}
,
+        ul: ({ children }) => 
    {children}
,
+        ol: ({ children }) => 
    {children}
,
+        li: ({ children }) => 
  • {children}
    • ,
+        input: ({ checked, disabled }) => (
+          
+        ),
+        blockquote: ({ children }) => (
+          
    
+            {children}
+          
    
+        ),
+        code: ({ className, children }) => {
+          // 带语言标注的必然出现在 
     里，块级渲染由 pre 统一处理；
+          // 这里只负责真正的行内代码。注意要保留 className，供 pre 读取语言。
+          if (className) {
+            return {children};
+          }
+          return (
+            
+              {children}
+            
+          );
+        },
+        pre: ({ children }) => {
+          // 所有代码块都会先经过 
    ，所以块级判断放在这里最可靠：
+          // 提取语言和源码，交给 CodeBlock（高亮）或 MermaidDiagram（图表）。
+          const child = Children.toArray(children)[0] as ReactElement<{
+            className?: string;
+            children?: ReactNode;
+          }>;
+          const childProps = child?.props ?? {};
+          const lang = /language-([\w-]+)/.exec(String(childProps.className ?? ""))?.[1];
+          const text = codeText(childProps.children);
+          if (lang === "mermaid") {
+            // mermaid 的 mindmap 解析器对中文 / 
     / 数字容易报 NODE_DEND 错误,
+            // 所以 mindmap 块不交给 mermaid,直接用 MindMap 组件渲染成可交互思维导图。
+            if (isMermaidMindMapSource(text)) return ;
+            return ;
+          }
+          return ;
+        },
+        table: ({ children }) => (
+          
    
+            
+              {children}
+            
    
+          
    
+        ),
+        thead: ({ children }) => (
+          {children}
+        ),
+        th: ({ children }) => (
+          
+            {children}
+          
+        ),
+        td: ({ children }) => (
+          {children}
+        ),
+        hr: () => 
    ,
+        a: ({ href, children }) => (
+          
+            {children}
+          
+        ),
+        strong: ({ children }) => (
+          {children}
+        ),
+        em: ({ children }) => {children},
+      }}
+    >
+      {content}
+    
+  );
+}
diff --git a/frontend/src/components/MermaidDiagram.tsx b/frontend/src/components/MermaidDiagram.tsx
new file mode 100644
index 0000000..5727e7f
--- /dev/null
+++ b/frontend/src/components/MermaidDiagram.tsx
@@ -0,0 +1,55 @@
+"use client";
+
+import { useEffect, useRef, useState } from "react";
+
+let idCounter = 0;
+
+/**
+ * Renders a ```mermaid code block into an actual diagram. mermaid is loaded
+ * lazily in an effect (SSR-safe); on parse failure it falls back to showing
+ * the raw source so the content is never lost.
+ */
+export default function MermaidDiagram({ code }: { code: string }) {
+  const [svg, setSvg] = useState(null);
+  const [error, setError] = useState(false);
+  const idRef = useRef(`mmd-${++idCounter}-${Date.now().toString(36)}`);
+
+  useEffect(() => {
+    let cancelled = false;
+
+    import("mermaid")
+      .then(async (mod) => {
+        if (cancelled) return;
+        const mermaid = mod.default;
+        mermaid.initialize({ startOnLoad: false });
+        const { svg: out } = await mermaid.render(idRef.current, code);
+        if (!cancelled) setSvg(out);
+      })
+      .catch(() => {
+        if (!cancelled) setError(true);
+      });
+
+    return () => {
+      cancelled = true;
+    };
+  }, [code]);
+
+  if (svg) {
+    return (
+      
    
+    );
+  }
+
+  if (error) {
+    return (
+      
    +        {code}
+      
    
+    );
+  }
+
+  return 
    图表渲染中…
    ;
+}
diff --git a/frontend/src/components/MindMap.tsx b/frontend/src/components/MindMap.tsx
new file mode 100644
index 0000000..3426cde
--- /dev/null
+++ b/frontend/src/components/MindMap.tsx
@@ -0,0 +1,494 @@
+"use client";
+
+import { useLayoutEffect, useMemo, useRef, useState } from "react";
+import { Brain, Check, Copy, Download, Image as ImageIcon, Loader2, Maximize2, Minus, Plus } from "lucide-react";
+import CodeBlock from "./CodeBlock";
+
+interface MindNode {
+  text: string;
+  children: MindNode[];
+  level: number;
+}
+
+interface LineItem {
+  indent: number;
+  text: string;
+}
+
+/** 布局常量：节点尺寸按中文字符估算，保证中文能自然换行。 */
+const CHAR_W = 15; // 平均每字宽度(text-sm 中文约 14px)
+const NODE_MIN_W = 64;
+const NODE_MAX_W = 200;
+const LINE_H = 22;
+const PAD_X = 12;
+const PAD_Y = 9;
+const H_GAP = 56; // 父子两列之间的水平间距
+const V_GAP = 14; // 兄弟节点之间的垂直间距
+const PAD = 24; // 画布内边距
+const VIEW_H = 320; // 渲染视图可视高度
+
+const DEPTH_STYLES = [
+  "bg-indigo-600 text-white border-indigo-700 shadow-md font-semibold", // 根节点
+  "bg-indigo-950/80 text-indigo-200 border-indigo-800 shadow-sm",
+  "bg-blue-950/80 text-blue-200 border-blue-800 shadow-sm",
+  "bg-emerald-950/80 text-emerald-200 border-emerald-800 shadow-sm",
+  "bg-amber-950/80 text-amber-200 border-amber-800 shadow-sm",
+  "bg-purple-950/80 text-purple-200 border-purple-800 shadow-sm",
+];
+
+/** Shared indent-stack builder: nests by comparing indents directly. */
+function buildTree(items: LineItem[]): MindNode | null {
+  if (items.length === 0) return null;
+  const root: MindNode = { text: items[0].text, children: [], level: 0 };
+  const stack: { node: MindNode; indent: number }[] = [{ node: root, indent: items[0].indent }];
+
+  for (let i = 1; i < items.length; i++) {
+    const { indent, text } = items[i];
+    const node: MindNode = { text, children: [], level: 0 };
+    while (stack.length > 0 && stack[stack.length - 1].indent >= indent) stack.pop();
+    const parent = stack.length > 0 ? stack[stack.length - 1].node : root;
+    node.level = parent.level + 1;
+    parent.children.push(node);
+    stack.push({ node, indent });
+  }
+  return root;
+}
+
+function parseMarkdownList(content: string): MindNode | null {
+  const items: LineItem[] = [];
+  let rootFromHeading: string | null = null;
+
+  for (const raw of content.split("\n")) {
+    const line = raw;
+    const list = line.match(/^([ \t]*)[-*+]\s+(.+)/);
+    if (list) {
+      items.push({ indent: list[1].replace(/\t/g, "  ").length, text: list[2].trim() });
+    } else if (!rootFromHeading) {
+      const h = line.match(/^#+\s*(.+)/);
+      if (h) rootFromHeading = h[1].trim();
+    }
+  }
+
+  if (items.length === 0) return null;
+  const tree = buildTree(items);
+  // 如果列表前有标题,用它作为根节点(原文顶层的并列内容都挂到标题下)。
+  if (tree && rootFromHeading) {
+    return { text: rootFromHeading, children: [tree], level: 0 };
+  }
+  return tree;
+}
+
+/** Strip mermaid mindmap shape wrappers like ((..)) [..] {..} and icons. */
+function cleanMermaidNode(line: string): string {
+  const mirror: Record = { "(": ")", "[": "]", "{": "}", "<": ">" };
+  let text = line
+    .replace(/^root\b\s*/, "") // mermaid 要求根节点带 root 关键字
+    .replace(/::icon\([^)]*\)/g, "")
+    .replace(//gi, " ")
+    .trim();
+
+  // 剥掉包围形状的括号:((..)) / [[..]] / [..] / (..) / {..} / ([..]) …
+  // 从两端按「相同开括号连续出现的次数」剥掉等量的闭括号,天然支持嵌套成对形状。
+  let guard = 0;
+  while (guard++ < 5) {
+    const first = text[0];
+    const expected = mirror[first];
+    if (!expected) break;
+    let openRun = 0;
+    while (openRun < text.length && text[openRun] === first) openRun++;
+    if (openRun > 0 && openRun * 2 < text.length && text.endsWith(expected.repeat(openRun))) {
+      text = text.slice(openRun, text.length - openRun).trim();
+    } else {
+      break;
+    }
+  }
+  return text.trim();
+}
+
+function parseMermaidMindMap(src: string): MindNode | null {
+  const items: LineItem[] = [];
+  let headerSkipped = false;
+
+  for (const raw of src.split("\n")) {
+    if (!raw.trim()) continue;
+    if (!headerSkipped) {
+      // 第一行是 mindmap 声明,跳过;若已是 root((…)) 则不跳。
+      headerSkipped = true;
+      if (/^\s*mindmap\s*$/i.test(raw)) continue;
+    }
+    const indent = (raw.match(/^(\s*)/)?.[1] ?? "").replace(/\t/g, "  ").length;
+    const text = cleanMermaidNode(raw.trim());
+    if (!text) continue;
+    items.push({ indent, text });
+  }
+
+  return buildTree(items);
+}
+
+/** True when the text looks like a mermaid mindmap source (header line = mindmap). */
+export function isMermaidMindMapSource(text: string): boolean {
+  const first = text.split("\n").find((l) => l.trim()) ?? "";
+  return /^\s*mindmap\s*$/i.test(first);
+}
+
+/** 主解析入口:优先按 mermaid mindmap,其次按 Markdown 列表。 */
+function parseMindMap(code: string): MindNode | null {
+  if (isMermaidMindMapSource(code)) return parseMermaidMindMap(code);
+  return parseMarkdownList(code);
+}
+
+interface LayoutNode {
+  node: MindNode;
+  x: number;
+  y: number;
+  w: number;
+  h: number;
+  parent: LayoutNode | null;
+  children: LayoutNode[];
+}
+
+interface Edge {
+  x1: number;
+  y1: number;
+  x2: number;
+  y2: number;
+}
+
+function nodeMetrics(text: string): { w: number; h: number } {
+  const w = Math.min(Math.max(text.length * CHAR_W + PAD_X * 2, NODE_MIN_W), NODE_MAX_W);
+  const perLine = Math.max(1, Math.floor((w - PAD_X * 2) / CHAR_W));
+  const lines = Math.max(1, Math.ceil(text.length / perLine));
+  return { w, h: lines * LINE_H + PAD_Y * 2 };
+}
+
+/** 递归布局:同深度的节点共用一列,保证任意兄弟子树永不重叠。 */
+function layoutRoot(root: MindNode): { nodes: LayoutNode[]; edges: Edge[]; width: number; height: number } {
+  const size = new Map();
+  const maxW: number[] = [];
+
+  (function measure(n: MindNode, d: number) {
+    const m = nodeMetrics(n.text);
+    maxW[d] = Math.max(maxW[d] ?? 0, m.w);
+    let sh = 0;
+    for (const c of n.children) {
+      measure(c, d + 1);
+      sh += size.get(c)!.subtreeH;
+    }
+    if (n.children.length > 1) sh += V_GAP * (n.children.length - 1);
+    size.set(n, { ...m, subtreeH: Math.max(m.h, sh) });
+  })(root, 0);
+
+  const colX: number[] = [];
+  for (let d = 0; d < maxW.length; d++) colX[d] = (colX[d - 1] ?? 0) + maxW[d] + H_GAP;
+
+  let minX = Infinity;
+  let minY = Infinity;
+  let maxX = -Infinity;
+  let maxY = -Infinity;
+  const all: LayoutNode[] = [];
+
+  function place(n: MindNode, d: number, blockCenterY: number, parent: LayoutNode | null): void {
+    const m = size.get(n)!;
+    const x = colX[d];
+    const y = blockCenterY - m.h / 2;
+    const ln: LayoutNode = { node: n, x, y, w: m.w, h: m.h, parent, children: [] };
+    if (parent) parent.children.push(ln);
+    all.push(ln);
+
+    let childrenH = 0;
+    for (const c of n.children) childrenH += size.get(c)!.subtreeH;
+    if (n.children.length > 1) childrenH += V_GAP * (n.children.length - 1);
+    let top = blockCenterY - childrenH / 2;
+    for (const c of n.children) {
+      const ch = size.get(c)!.subtreeH;
+      place(c, d + 1, top + ch / 2, ln);
+      top += ch + V_GAP;
+    }
+
+    minX = Math.min(minX, x);
+    minY = Math.min(minY, y);
+    maxX = Math.max(maxX, x + m.w);
+    maxY = Math.max(maxY, y + m.h);
+  }
+  place(root, 0, 0, null);
+
+  const edges: Edge[] = [];
+  for (const ln of all) {
+    if (!ln.parent) continue;
+    edges.push({
+      x1: ln.parent.x + ln.parent.w,
+      y1: ln.parent.y + ln.parent.h / 2,
+      x2: ln.x,
+      y2: ln.y + ln.h / 2,
+    });
+  }
+
+  // 平移到带内边距的坐标系
+  const dx = PAD - minX;
+  const dy = PAD - minY;
+  for (const ln of all) {
+    ln.x += dx;
+    ln.y += dy;
+  }
+  for (const e of edges) {
+    e.x1 += dx;
+    e.y1 += dy;
+    e.x2 += dx;
+    e.y2 += dy;
+  }
+
+  return {
+    nodes: all,
+    edges,
+    width: maxX - minX + PAD * 2,
+    height: maxY - minY + PAD * 2,
+  };
+}
+
+export default function MindMap({ code }: { code: string }) {
+  const [view, setView] = useState<"render" | "code">("render");
+  const [copied, setCopied] = useState(false);
+  const [exporting, setExporting] = useState(false);
+  const [scale, setScale] = useState(1);
+  const [pan, setPan] = useState({ x: 0, y: 0 });
+
+  const wrapRef = useRef(null); // 可视窗口(overflow hidden)
+  const stageRef = useRef(null); // 被平移/缩放的画布
+  const dragRef = useRef<{ startX: number; startY: number; panX: number; panY: number } | null>(null);
+  const stateRef = useRef({ scale, pan });
+  stateRef.current = { scale, pan };
+
+  const root = useMemo(() => parseMindMap(code), [code]);
+  const layout = useMemo(() => (root ? layoutRoot(root) : null), [root]);
+
+  // 挂载时把整张图放进可视窗口
+  useLayoutEffect(() => {
+    const el = wrapRef.current;
+    if (!el || !layout) return;
+    const vw = el.clientWidth;
+    const vh = el.clientHeight;
+    const s = Math.min((vw - 16) / layout.width, (vh - 16) / layout.height, 1);
+    setScale(Math.max(s, 0.05));
+    setPan({ x: 0, y: 0 });
+  }, [layout]);
+
+  // 滚轮缩放(原生非 passive 监听,避免页面跟着滚动)
+  useLayoutEffect(() => {
+    const el = wrapRef.current;
+    if (!el) return;
+    const onWheel = (e: WheelEvent) => {
+      e.preventDefault();
+      const rect = el.getBoundingClientRect();
+      const cx = e.clientX - rect.left;
+      const cy = e.clientY - rect.top;
+      const { scale: s, pan: p } = stateRef.current;
+      const factor = e.deltaY < 0 ? 1.15 : 1 / 1.15;
+      const next = Math.min(3, Math.max(0.2, s * factor));
+      const wx = (cx - p.x) / s;
+      const wy = (cy - p.y) / s;
+      setScale(next);
+      setPan({ x: cx - wx * next, y: cy - wy * next });
+    };
+    el.addEventListener("wheel", onWheel, { passive: false });
+    return () => el.removeEventListener("wheel", onWheel);
+  }, []);
+
+  const onPointerDown = (e: React.PointerEvent) => {
+    (e.currentTarget as HTMLElement).setPointerCapture?.(e.pointerId);
+    dragRef.current = { startX: e.clientX, startY: e.clientY, panX: pan.x, panY: pan.y };
+  };
+  const onPointerMove = (e: React.PointerEvent) => {
+    const d = dragRef.current;
+    if (!d) return;
+    setPan({ x: d.panX + (e.clientX - d.startX), y: d.panY + (e.clientY - d.startY) });
+  };
+  const onPointerUp = () => {
+    dragRef.current = null;
+  };
+
+  const zoomBy = (f: number) => setScale((s) => Math.min(3, Math.max(0.2, s * f)));
+
+  const fit = () => {
+    const el = wrapRef.current;
+    if (!el || !layout) return;
+    const vw = el.clientWidth;
+    const vh = el.clientHeight;
+    const s = Math.min((vw - 16) / layout.width, (vh - 16) / layout.height, 1);
+    setScale(Math.max(s, 0.05));
+    setPan({ x: 0, y: 0 });
+  };
+
+  const copySource = async () => {
+    try {
+      await navigator.clipboard.writeText(code);
+      setCopied(true);
+      setTimeout(() => setCopied(false), 1500);
+    } catch {
+      alert("复制失败");
+    }
+  };
+
+  const exportMd = () => {
+    const content = "```mermaid\n" + code.replace(/\n+$/, "") + "\n```\n";
+    const blob = new Blob([content], { type: "text/markdown;charset=utf-8" });
+    const url = URL.createObjectURL(blob);
+    const a = document.createElement("a");
+    a.href = url;
+    a.download = "思维导图.md";
+    a.click();
+    URL.revokeObjectURL(url);
+  };
+
+  const exportImage = async () => {
+    const outer = wrapRef.current;
+    const inner = stageRef.current;
+    if (!outer || !inner || !layout || exporting) return;
+    const prevOuter = { width: outer.style.width, height: outer.style.height, overflow: outer.style.overflow };
+    const prevTransform = inner.style.transform;
+    outer.style.width = `${layout.width}px`;
+    outer.style.height = `${layout.height}px`;
+    outer.style.overflow = "visible";
+    inner.style.transform = "translate(0px, 0px) scale(1)";
+    setExporting(true);
+    try {
+      const { toPng } = await import("html-to-image");
+      const dataUrl = await toPng(outer, { pixelRatio: 2, backgroundColor: "#10151f", cacheBust: true });
+      const a = document.createElement("a");
+      a.href = dataUrl;
+      a.download = "思维导图.png";
+      a.click();
+    } catch {
+      alert("导出图片失败");
+    } finally {
+      outer.style.width = prevOuter.width;
+      outer.style.height = prevOuter.height;
+      outer.style.overflow = prevOuter.overflow;
+      inner.style.transform = prevTransform;
+      setExporting(false);
+    }
+  };
+
+  if (!root || !layout) return null;
+
+  return (
+    
    
+      {/* 工具栏：无边框控制台风，视图切换 pill + 纯图标按钮 */}
+      
    
+        
    
+          
+          
+        
    
+        
    
+        
+        
+        {view === "render" && (
+          
+        )}
+        {view === "render" && (
+          
    
+            
+            {Math.round(scale * 100)}%
+            
+            
+          
    
+        )}
+      
    
+
+      {/* 视图内容 */}
+      {view === "render" ? (
+        
    
+          
    
+            
+              {layout.edges.map((e, i) => {
+                const midX = e.x1 + (e.x2 - e.x1) * 0.5;
+                return (
+                  
+                );
+              })}
+            
+            {layout.nodes.map((ln, i) => {
+              const depthStyle = DEPTH_STYLES[Math.min(ln.node.level, DEPTH_STYLES.length - 1)];
+              return (
+                
    
+                  {ln.node.text}
+                
    
+              );
+            })}
+          
    
+          
+            滚轮缩放 · 拖动平移
+          
+        
    
+      ) : (
+        
+      )}
+    
    
+  );
+}
diff --git a/frontend/src/components/ModelManagerDialog.tsx b/frontend/src/components/ModelManagerDialog.tsx
new file mode 100644
index 0000000..d451095
--- /dev/null
+++ b/frontend/src/components/ModelManagerDialog.tsx
@@ -0,0 +1,469 @@
+"use client";
+
+import { useMemo, useState } from "react";
+import {
+  ArrowLeft, Check, FlaskConical, KeyRound, Loader2, Pencil, Plus,
+  Search, Settings2, Trash2, Upload, X,
+} from "lucide-react";
+import { api, AiModelEntry } from "@/lib/api";
+
+interface Props {
+  open: boolean;
+  onClose: () => void;
+  models: AiModelEntry[];
+  onChanged: () => void;
+}
+
+interface Preset {
+  key: string;
+  label: string;
+  kind: "openai_compatible" | "anthropic";
+  base_url: string;
+  model_id: string;
+  hint: string;
+}
+
+const PRESETS: Preset[] = [
+  { key: "openrouter", label: "OpenRouter", kind: "openai_compatible", base_url: "https://openrouter.ai/api/v1", model_id: "", hint: "一个 key 用全部模型，如 deepseek/deepseek-r1" },
+  { key: "deepseek", label: "DeepSeek", kind: "openai_compatible", base_url: "https://api.deepseek.com/v1", model_id: "deepseek-chat", hint: "deepseek-chat(V3) / deepseek-reasoner(R1)" },
+  { key: "sensenova", label: "SenseNova", kind: "openai_compatible", base_url: "https://token.sensenova.cn/v1", model_id: "", hint: "商汤日日新" },
+  { key: "siliconflow", label: "硅基流动", kind: "openai_compatible", base_url: "https://api.siliconflow.cn/v1", model_id: "", hint: "国产模型市场，低价" },
+  { key: "claude", label: "Claude", kind: "anthropic", base_url: "", model_id: "claude-sonnet-4-20250514", hint: "需 Anthropic API Key" },
+];
+
+// 批量导入模式的平台快捷选择
+const IMPORT_PROVIDERS: { label: string; base_url: string }[] = [
+  { label: "OpenRouter", base_url: "https://openrouter.ai/api/v1" },
+  { label: "硅基流动", base_url: "https://api.siliconflow.cn/v1" },
+  { label: "SenseNova", base_url: "https://token.sensenova.cn/v1" },
+  { label: "自定义", base_url: "" },
+];
+
+const inputCls =
+  "w-full px-3 py-2 rounded-lg border border-[var(--border)] bg-[var(--bg-raised)] text-sm text-[var(--fg)] placeholder-[var(--fg-muted)] focus:outline-none focus:ring-2 focus:ring-[var(--accent)]";
+
+export default function ModelManagerDialog({ open, onClose, models, onChanged }: Props) {
+  const [mode, setMode] = useState<"list" | "form" | "import">("list");
+
+  // 表单
+  const [form, setForm] = useState({ name: "", label: "", kind: "openai_compatible", base_url: "", api_key: "", model_id: "" });
+  const [editingName, setEditingName] = useState(null);
+  const [saving, setSaving] = useState(false);
+  const [saveMsg, setSaveMsg] = useState(null);
+
+  // 测试
+  const [testingName, setTestingName] = useState(null);
+  const [testResult, setTestResult] = useState>({});
+
+  // 批量导入（任意 OpenAI 兼容平台）
+  const [importBase, setImportBase] = useState("https://openrouter.ai/api/v1");
+  const [importKey, setImportKey] = useState("");
+  const [fetching, setFetching] = useState(false);
+  const [providerModels, setProviderModels] = useState<{ id: string; name: string }[]>([]);
+  const [importSearch, setImportSearch] = useState("");
+  const [selected, setSelected] = useState>(new Set());
+  const [importMsg, setImportMsg] = useState(null);
+
+  const filtered = useMemo(() => {
+    const q = importSearch.trim().toLowerCase();
+    if (!q) return providerModels;
+    return providerModels.filter((m) => m.id.toLowerCase().includes(q) || (m.name || "").toLowerCase().includes(q));
+  }, [providerModels, importSearch]);
+
+  if (!open) return null;
+
+  const applyPreset = (p: Preset) => {
+    setForm({
+      name: "", label: p.label, kind: p.kind,
+      base_url: p.base_url, api_key: "", model_id: p.model_id,
+    });
+    setEditingName(null);
+    setMode("form");
+  };
+
+  const startAdd = () => {
+    setForm({ name: "", label: "", kind: "openai_compatible", base_url: "", api_key: "", model_id: "" });
+    setEditingName(null);
+    setSaveMsg(null);
+    setMode("form");
+  };
+
+  const startEdit = (m: AiModelEntry) => {
+    setForm({ name: m.name, label: m.label, kind: m.kind, base_url: m.base_url, api_key: "", model_id: m.model_id });
+    setEditingName(m.name);
+    setSaveMsg(null);
+    setMode("form");
+  };
+
+  const save = async () => {
+    if (!form.model_id.trim() || !form.label.trim()) {
+      setSaveMsg("请填写模型名称（显示名）和模型 ID");
+      return;
+    }
+    if (!form.kind.startsWith("anthropic") && !form.base_url.trim()) {
+      setSaveMsg("OpenAI 兼容模型需要 base_url（可点上方预设自动填入）");
+      return;
+    }
+    setSaving(true);
+    setSaveMsg(null);
+    try {
+      if (editingName) {
+        await api.updateModel(editingName, {
+          label: form.label, kind: form.kind, base_url: form.base_url, model_id: form.model_id,
+          ...(form.api_key.trim() ? { api_key: form.api_key } : {}),
+        });
+      } else {
+        await api.addModel({
+          label: form.label, kind: form.kind,
+          base_url: form.base_url, api_key: form.api_key, model_id: form.model_id,
+        });
+      }
+      onChanged();
+      setMode("list");
+      setSaveMsg(null);
+    } catch (e) {
+      setSaveMsg(e instanceof Error ? e.message : "保存失败");
+    }
+    setSaving(false);
+  };
+
+  const remove = async (m: AiModelEntry) => {
+    if (!confirm(`删除模型「${m.label}」？`)) return;
+    try {
+      await api.deleteModel(m.name);
+      onChanged();
+    } catch {
+      alert("删除失败");
+    }
+  };
+
+  const test = async (m: AiModelEntry) => {
+    setTestingName(m.name);
+    setTestResult((prev) => ({ ...prev, [m.name]: prev[m.name] }));
+    try {
+      const r = await api.testModel(m.name);
+      setTestResult((prev) => ({
+        ...prev,
+        [m.name]: { ok: r.ok, text: r.ok ? `✅ 连通正常 · ${r.reply?.slice(0, 40) ?? ""}` : `❌ ${r.error ?? "失败"}` },
+      }));
+    } catch (e) {
+      setTestResult((prev) => ({ ...prev, [m.name]: { ok: false, text: `❌ ${e instanceof Error ? e.message : "请求失败"}` } }));
+    }
+    setTestingName(null);
+  };
+
+  const fetchModels = async () => {
+    if (!importBase.trim() || !importKey.trim()) return;
+    setFetching(true);
+    setImportMsg(null);
+    try {
+      const r = await api.importModels(importBase.trim(), importKey.trim());
+      setProviderModels(r.models);
+      setSelected(new Set());
+    } catch (e) {
+      setImportMsg(`❌ ${e instanceof Error ? e.message : "拉取失败"}`);
+    }
+    setFetching(false);
+  };
+
+  const toggleSelect = (id: string) => {
+    setSelected((prev) => {
+      const next = new Set(prev);
+      if (next.has(id)) next.delete(id);
+      else next.add(id);
+      return next;
+    });
+  };
+
+  const importSelected = async () => {
+    const ids = [...selected];
+    if (!ids.length) return;
+    setSaving(true);
+    setImportMsg(null);
+    let ok = 0;
+    for (const id of ids) {
+      try {
+        await api.addModel({
+          label: id, kind: "openai_compatible",
+          base_url: importBase, api_key: importKey, model_id: id,
+        });
+        ok += 1;
+      } catch {
+        // 单个失败跳过（重名等）
+      }
+    }
+    setImportMsg(`已导入 ${ok}/${ids.length} 个模型`);
+    onChanged();
+    setSaving(false);
+  };
+
+  return (
+    
    
+      
     e.stopPropagation()}
+      >
+        {/* 头部 */}
+        
    
+          {mode !== "list" && (
+            
+          )}
+          
+          
    
+            {mode === "form" ? (editingName ? "编辑模型" : "添加模型") : mode === "import" ? "从 OpenRouter 导入" : "管理模型"}
+          
    
+          
+        
    
+
+        {/* 列表模式 */}
+        {mode === "list" && (
+          
    
+            
    
+              
+              
+            
    
+
+            {models.length === 0 && (
+              
    还没有可用模型，点上方「添加模型」配置一个
    
+            )}
+            {models.map((m) => (
+              
    
+                
    
+                  {m.kind === "anthropic" ?  : }
+                
    
+                
    
+                  
    
+                    {m.label}
+                    {m.builtin && (
+                      内置
+                    )}
+                  
    
+                  
    
+                    {m.model_id}
+                    {m.base_url ? ` · ${m.base_url.replace(/^https?:\/\//, "").split("/")[0]}` : ""}
+                    {m.api_key_masked ? ` · ${m.api_key_masked}` : ""}
+                  
    
+                  {testResult[m.name] && (
+                    
    
+                      {testResult[m.name].text}
+                    
    
+                  )}
+                
    
+                
    
+                  
+                  {!m.builtin && (
+                    <>
+                      
+                      
+                    
+                  )}
+                
    
+              
    
+            ))}
+          
    
+        )}
+
+        {/* 表单模式 */}
+        {mode === "form" && (
+          
    
+            
    
+              
    快捷预设（点一下自动填，只需补 API Key）
    
+              
    
+                {PRESETS.map((p) => (
+                  
+                ))}
+              
    
+              
    
+                {PRESETS.find((p) => p.label === form.label)?.hint ?? "预设只是帮填字段；你也可以完全手动填写任意 OpenAI 兼容 API"}
+              
    
+            
    
+
+            
    
+              
+               setForm({ ...form, label: e.target.value })} placeholder="如 DeepSeek V3 / Qwen2.5-72B" />
+            
    
+            
    
+              
+              
+            
    
+            
    
+              
+               setForm({ ...form, base_url: e.target.value })} placeholder="https://openrouter.ai/api/v1" />
+            
    
+            
    
+              
+               setForm({ ...form, api_key: e.target.value })} placeholder={editingName ? "留空保持不变" : "sk-..."} autoComplete="off" />
+            
    
+            
    
+              
+               setForm({ ...form, model_id: e.target.value })} placeholder="deepseek-chat / deepseek/deepseek-r1 / qwen2.5-72b-instruct" />
+            
    
+
+            {saveMsg && 
    {saveMsg}
    }
+
+            
    
+              
+              
+            
    
+          
    
+        )}
+
+        {/* 批量导入模式（任意 OpenAI 兼容平台） */}
+        {mode === "import" && (
+          
    
+            
    
+              
+              
    
+                {IMPORT_PROVIDERS.map((p) => (
+                  
+                ))}
+              
    
+              
+               setImportBase(e.target.value)}
+                placeholder="https://openrouter.ai/api/v1"
+              />
+              
+              
    
+                 setImportKey(e.target.value)}
+                  placeholder="sk-..."
+                  autoComplete="off"
+                />
+                
+              
    
+              {importMsg && 
    {importMsg}
    }
+            
    
+
+            {providerModels.length > 0 && (
+              <>
+                
    
+                  
+                   setImportSearch(e.target.value)}
+                    placeholder={`搜索 ${providerModels.length} 个模型，如 deepseek / qwen / claude`}
+                  />
+                
    
+                
    
+                  {filtered.map((m) => (
+                    
+                  ))}
+                  {filtered.length === 0 && 
    没有匹配的模型
    }
+                
    
+                
+              
+            )}
+          
    
+        )}
+      
    
+    
    
+  );
+}
\ No newline at end of file
diff --git a/frontend/src/lib/api.ts b/frontend/src/lib/api.ts
new file mode 100644
index 0000000..4350b39
--- /dev/null
+++ b/frontend/src/lib/api.ts
@@ -0,0 +1,183 @@
+export interface Book {
+  id: string;
+  filename: string;
+  title: string | null;
+  author: string | null;
+  language: string;
+  char_count: number;
+  status: string;
+  created_at: string;
+}
+
+export interface BookDetail extends Book {
+  chapter_count: number;
+  segment_count: number;
+}
+
+export interface Chapter {
+  id: string;
+  book_id: string;
+  order_idx: number;
+  title: string | null;
+  level: number;
+  heading_path: string | null;
+  cfi_start: string | null;
+  cfi_end: string | null;
+  char_count: number;
+}
+
+export interface Segment {
+  id: string;
+  chapter_id: string;
+  book_id: string;
+  order_idx: number;
+  text: string;
+  char_count: number;
+  cfi: string | null;
+}
+
+export interface Citation {
+  segment_id: string;
+  cfi: string | null;
+  excerpt: string;
+}
+
+export interface Conversation {
+  id: string;
+  book_id: string;
+  title: string | null;
+  model: string;
+  created_at: string;
+}
+
+export interface AiModelEntry {
+  name: string;
+  label: string;
+  kind: "openai_compatible" | "anthropic";
+  base_url: string;
+  api_key_masked: string;
+  model_id: string;
+  builtin: boolean;
+}
+
+export interface Message {
+  id: string;
+  conversation_id: string;
+  parent_message_id: string | null;
+  role: "user" | "assistant" | "system";
+  content: string;
+  citations: Citation[] | null;
+  model: string | null;
+  created_at: string;
+}
+
+const API_BASE = "http://localhost:8000/api";
+
+async function request(path: string, options?: RequestInit): Promise {
+  const res = await fetch(`${API_BASE}${path}`, {
+    headers: { "Content-Type": "application/json" },
+    ...options,
+  });
+  if (!res.ok) {
+    const err = await res.json().catch(() => ({ detail: res.statusText }));
+    throw new Error(err.detail || "Request failed");
+  }
+  return res.json();
+}
+
+export const api = {
+  // Books
+  listBooks: () => request("/books"),
+  getBook: (id: string) => request(`/books/${id}`),
+  getBookFile: async (id: string, signal?: AbortSignal) => {
+    const response = await fetch(`${API_BASE}/books/${encodeURIComponent(id)}/file`, { signal });
+    if (!response.ok) {
+      const error = await response.json().catch(() => ({ detail: "无法打开 EPUB 文件" }));
+      throw new Error(error.detail || "无法打开 EPUB 文件");
+    }
+    return response.arrayBuffer();
+  },
+  getChapters: (bookId: string) => request(`/books/${bookId}/chapters`),
+  getSegments: (bookId: string, chapterId?: string) =>
+    request(`/books/${bookId}/segments${chapterId ? `?chapter_id=${chapterId}` : ""}`),
+  uploadBook: async (file: File) => {
+    const form = new FormData();
+    form.append("file", file);
+    const res = await fetch(`${API_BASE}/books`, { method: "POST", body: form });
+    if (!res.ok) {
+      const err = await res.json().catch(() => ({ detail: "Upload failed" }));
+      throw new Error(err.detail || "Upload failed");
+    }
+    return res.json() as Promise;
+  },
+  deleteBook: (id: string) => request<{ deleted: string }>(`/books/${id}`, { method: "DELETE" }),
+
+  // Conversations
+  listConversations: (bookId?: string) =>
+    request(`/chat/conversations${bookId ? `?book_id=${bookId}` : ""}`),
+  createConversation: (bookId: string, model: string = "claude") =>
+    request("/chat/conversations", {
+      method: "POST",
+      body: JSON.stringify({ book_id: bookId, model }),
+    }),
+  deleteConversation: (convId: string) =>
+    request<{ deleted: string }>(`/chat/conversations/${convId}`, { method: "DELETE" }),
+  getMessages: (convId: string) => request(`/chat/conversations/${convId}/messages`),
+
+  // Chat (SSE)
+  sendMessage: (convId: string, content: string, model?: string, replyTo?: string) => {
+    return fetch(`${API_BASE}/chat/conversations/${convId}/messages`, {
+      method: "POST",
+      headers: { "Content-Type": "application/json" },
+      body: JSON.stringify({ content, model, ...(replyTo ? { reply_to: replyTo } : {}) }),
+    });
+  },
+
+  // Search
+  search: (bookId: string, q: string) =>
+    request(`/chat/search?book_id=${bookId}&q=${encodeURIComponent(q)}`),
+
+  // 引用段落的阅读上下文（「阅读原文」弹层）
+  getSegmentContext: (segmentId: string) =>
+    request<{
+      segment: { id: string; text: string; order_idx: number; cfi: string | null };
+      chapter: { id: string; title: string | null; level: number } | null;
+      before: { id: string; text: string; order_idx: number; cfi: string | null }[];
+      after: { id: string; text: string; order_idx: number; cfi: string | null }[];
+    }>(`/chat/segments/${segmentId}/context`),
+
+  // Message actions
+  deleteMessage: (msgId: string) =>
+    request<{ deleted: string }>(`/chat/messages/${msgId}`, { method: "DELETE" }),
+  retryMessage: (msgId: string) => {
+    return fetch(`${API_BASE}/chat/messages/${msgId}/retry`, { method: "POST" });
+  },
+  branchConversation: (convId: string, fromMessageId: string) =>
+    request(`/chat/conversations/${convId}/branch?from_message_id=${fromMessageId}`, {
+      method: "POST",
+    }),
+  exportConversation: (convId: string) =>
+    request<{ content: string; format: string; title: string }>(`/chat/conversations/${convId}/export`),
+
+  // Models
+  listModels: () => request("/models"),
+  addModel: (data: { label: string; kind?: string; base_url?: string; api_key?: string; model_id: string }) =>
+    request("/models", { method: "POST", body: JSON.stringify(data) }),
+  updateModel: (name: string, data: Partial<{ label: string; kind: string; base_url: string; api_key: string; model_id: string }>) =>
+    request(`/models/${name}`, { method: "PUT", body: JSON.stringify(data) }),
+  deleteModel: (name: string) =>
+    request<{ deleted: string }>(`/models/${name}`, { method: "DELETE" }),
+  testModel: (name: string) =>
+    request<{ ok: boolean; error?: string; model?: string; reply?: string }>(`/models/${name}/test`, { method: "POST" }),
+  importModels: (baseUrl: string, apiKey: string) =>
+    request<{ models: { id: string; name: string }[]; count: number }>("/models/import", {
+      method: "POST",
+      body: JSON.stringify({ base_url: baseUrl, api_key: apiKey }),
+    }),
+};
+
+export function formatCharCount(n: number): string {
+  if (n >= 1_000_000) return `${(n / 1_000_000).toFixed(1)}M 字`;
+  if (n >= 1_000) return `${(n / 1_000).toFixed(0)}K 字`;
+  return `${n} 字`;
+}
diff --git a/tsconfig.json b/frontend/tsconfig.json
similarity index 100%
rename from tsconfig.json
rename to frontend/tsconfig.json
diff --git a/src/app/globals.css b/src/app/globals.css
deleted file mode 100644
index a2dc41e..0000000
--- a/src/app/globals.css
+++ /dev/null
@@ -1,26 +0,0 @@
-@import "tailwindcss";
-
-:root {
-  --background: #ffffff;
-  --foreground: #171717;
-}
-
-@theme inline {
-  --color-background: var(--background);
-  --color-foreground: var(--foreground);
-  --font-sans: var(--font-geist-sans);
-  --font-mono: var(--font-geist-mono);
-}
-
-@media (prefers-color-scheme: dark) {
-  :root {
-    --background: #0a0a0a;
-    --foreground: #ededed;
-  }
-}
-
-body {
-  background: var(--background);
-  color: var(--foreground);
-  font-family: Arial, Helvetica, sans-serif;
-}
diff --git a/src/app/layout.tsx b/src/app/layout.tsx
deleted file mode 100644
index 9852c15..0000000
--- a/src/app/layout.tsx
+++ /dev/null
@@ -1,29 +0,0 @@
-import type { Metadata } from "next";
-import { Geist, Geist_Mono } from "next/font/google";
-import "./globals.css";
-
-const geistSans = Geist({
-  variable: "--font-geist-sans",
-  subsets: ["latin"],
-});
-
-const geistMono = Geist_Mono({
-  variable: "--font-geist-mono",
-  subsets: ["latin"],
-});
-
-export const metadata: Metadata = {
-  title: "Create Next App",
-  description: "Generated by create next app",
-};
-
-export default function RootLayout({ children }: LayoutProps<"/">) {
-  return (
-    
-      {children}
-    
-  );
-}
diff --git a/src/app/page.tsx b/src/app/page.tsx
deleted file mode 100644
index c887311..0000000
--- a/src/app/page.tsx
+++ /dev/null
@@ -1,69 +0,0 @@
-import Image from "next/image";
-
-export default function Home() {
-  return (
-    
    
-      
    
-        Next.js logo
-        
    
-          
    
-            To get started, edit the{" "}
-            
-              page.tsx
-            {" "}
-            file.
-          
    
-          
    
-            Looking for a starting point or more instructions? Head over to{" "}
-            
-              Templates
-            {" "}
-            or the{" "}
-            
-              Learning
-            {" "}
-            center.
-          
    
-        
    
-        
-      
    
-    
    
-  );
-}