update

.gitignore

@@ -68,6 +68,7 @@ backend/logs/
 .env
 .env.*
 !.env.example
+!.env.infr.example
 !**/.env.example
 !.env.docker
 !**/.env.docker
@@ -103,3 +104,6 @@ history.txt
 .cursor/
 backend/.env.docker
 backend/uploads/
+
+# Docker volumes 数据目录
+backend/volumes/

backend/.env.example

@@ -90,6 +90,15 @@ MODERATION_ENABLED=false
 
 
 
+# ==================== 网页抓取配置（crawl4ai）====================
+# 页面加载超时（毫秒），默认 30 秒
+CRAWLER_TIMEOUT_MS=30000
+# 等待 JS 渲染的额外延迟（毫秒），SPA 页面可适当加大，默认 2 秒
+CRAWLER_WAIT_FOR_JS_MS=2000
+# 是否启用 stealth 模式绕过反爬（UA/指纹伪装），默认开启
+CRAWLER_STEALTH_ENABLED=true
+
+
 DEEPSEEK_API_KEY=sk-修改为deepseek的api key
 DASHSCOPE_API_KEY=sk-修改为dashscope的api key
 #DEEPSEEK_API_BASE=https://api.deepseek.com/v1

backend/.env.infr.example

@@ -0,0 +1,31 @@
+# 基础设施环境变量配置
+# 使用说明：复制本文件为 .env.infr，填写实际值后启动
+# 启动命令：docker compose --env-file .env.infr -f docker-compose.infr.yml up -d
+
+# ==================== 全局 ====================
+# Docker Compose 项目名，同时作为网络名和容器名前缀（容器名格式：项目名-容器名）
+INFR_PROJECT_NAME=修改此项为项目名称
+
+# ==================== PostgreSQL ====================
+INFR_POSTGRESQL_VERSION=16.3
+INFR_POSTGRESQL_CONTAINER_NAME=postgresql
+INFR_POSTGRESQL_POSTGRES_PORT=51501
+INFR_POSTGRESQL_POSTGRES_USER=postgres
+INFR_POSTGRESQL_POSTGRES_PASSWORD=修改此项为数据库密码
+
+# ==================== Neo4j ====================
+INFR_NEO4J_VERSION=5.26-community
+INFR_NEO4J_CONTAINER_NAME=neo4j
+INFR_NEO4J_WEB_HTTP_PORT=51511
+INFR_NEO4J_BOLT_PORT=51521
+NEO4J_PASSWORD=修改此项为 Neo4j 密码
+
+# ==================== Redis ====================
+INFR_REDIS_VERSION=7.4
+INFR_REDIS_CONTAINER_NAME=redis
+INFR_REDIS_REDIS_PORT=51531
+INFR_REDIS_REDIS_PASSWORD=修改此项为 Redis 密码
+
+# ==================== ChromaDB ====================
+INFR_CHROMA_CONTAINER_NAME=chroma
+INFR_CHROMA_PORT=51541

backend/Dockerfile

@@ -72,6 +72,10 @@ RUN pip install --no-cache-dir uv
 COPY pyproject.toml uv.lock ./
 RUN uv sync --frozen --no-dev
 
+# 安装 Playwright Chromium 浏览器及系统依赖（crawl4ai 网页抓取功能依赖）
+RUN uv run playwright install chromium \
+    && uv run playwright install-deps chromium
+
 # 从编译阶段复制二进制模块（.so 文件）
 COPY --from=builder /compiled/ ./
 

backend/api/kb_file_router.py

@@ -275,14 +275,28 @@ async def process_url_background(file_id: int, url: str, knowledge_base_id: int)
 
             # 处理 URL
             vector_service = get_vector_service()
-            result = await vector_service.process_url(url, knowledge_base_id)
+            result = await vector_service.process_url(url, knowledge_base_id, file_id=file_id)
 
             # 检查处理结果
             if not result.success:
-                logger.warning(f"URL 处理失败 ID: {file_id}, 原因: {result.error_message}")
+                error_msg = result.error_message or "网页抓取失败"
+                logger.warning(f"URL 处理失败 ID: {file_id}, 原因: {error_msg}")
+                # 将失败原因写入 processing_stage（前 50 字符），便于前端展示
+                stage_hint = error_msg[:50] if error_msg else "failed"
+                await KnowledgeBaseFileService.update_file_progress(conn, file_id, 0, stage_hint)
                 await KnowledgeBaseFileService.update_file_status(conn, file_id, "failed", 0)
                 return
 
+            # 用网页标题更新 file_name（如果抓取到了标题）
+            page_title = (result.page_title or "").strip()
+            if page_title:
+                await conn.execute(
+                    "UPDATE knowledge_base_file SET file_name = $1 WHERE id = $2",
+                    page_title[:255],
+                    file_id,
+                )
+                logger.info(f"📄 URL 文件名已更新为网页标题: {page_title}")
+
             # 生成文件摘要
             summary_text = None
             try:
@@ -310,10 +324,6 @@ async def process_url_background(file_id: int, url: str, knowledge_base_id: int)
                 conn, file_id, knowledge_base_id, result.chunks, summary=summary_text
             )
 
-            # 更新 ChromaDB metadata（URL 暂不支持 file_id，跳过）
-            # if summary_text:
-            #     vector_service.update_kb_file_summary_in_vectors(...)
-            
             await KnowledgeBaseFileService.update_file_status(conn, file_id, "completed", result.chunk_count)
 
             logger.info(f"URL 处理完成 ID: {file_id}, 块数: {result.chunk_count}, 摘要: {'已生成' if summary_text else '未生成'}")
@@ -533,7 +543,11 @@ async def upload_url(
     current_user: User = Depends(get_current_user),
     conn: asyncpg.Connection = Depends(get_db)
 ):
-    """上传 URL 到知识库并进行向量化处理"""
+    """上传 URL 到知识库并进行向量化处理。
+    
+    - 若 URL 指向已支持的文件类型（pdf/docx/xlsx 等），自动下载后走文件处理流程
+    - 否则走网页抓取流程（crawl4ai，支持 JS 渲染）
+    """
     kb = await _check_kb_access(conn, kb_id, current_user)
     if not await can_upload_to_kb(conn, current_user, kb):
         raise BadRequestError("您的上传权限已被关闭，请联系部门领导或管理员")
@@ -542,8 +556,100 @@ async def upload_url(
     if not url.startswith(('http://', 'https://')):
         raise BadRequestError("URL 格式不正确，必须以 http:// 或 https:// 开头")
 
-    # 生成文件名
+    # ---------- 判断 URL 是否指向已支持的文件类型 ----------
     parsed_url = urlparse(url)
+    url_path_lower = parsed_url.path.lower().rstrip("/")
+    url_ext = Path(url_path_lower).suffix  # 例如 ".pdf"
+
+    if url_ext in FILE_TYPE_MAP:
+        # 静态文件 URL：下载到本地 / OSS，再走与上传文件相同的后台处理流程
+        file_type = FILE_TYPE_MAP[url_ext]
+        # 用 URL path 最后一段作为文件名，保留原始大小写
+        raw_filename = Path(parsed_url.path).name or f"file{url_ext}"
+
+        logger.info(f"📎 检测到文件类型 URL ({file_type}): {url}，走文件下载流程")
+
+        import httpx as _httpx
+        import os as _os
+        _sys_proxy = (
+            _os.environ.get("https_proxy") or _os.environ.get("HTTPS_PROXY")
+            or _os.environ.get("http_proxy") or _os.environ.get("HTTP_PROXY")
+        ) or None
+        _dl_kwargs: dict = dict(
+            follow_redirects=True,
+            timeout=60,
+            headers={"User-Agent": "Mozilla/5.0 (compatible; HuoyanBot/1.0)"},
+        )
+        if _sys_proxy:
+            _dl_kwargs["proxy"] = _sys_proxy
+        try:
+            async with _httpx.AsyncClient(**_dl_kwargs) as client:
+                resp = await client.get(url)
+                resp.raise_for_status()
+                content = resp.content
+        except Exception as e:
+            raise BadRequestError(f"文件下载失败: {e}")
+
+        file_size = len(content)
+        max_file_size = settings.max_upload_file_bytes
+        if file_size > max_file_size:
+            raise BadRequestError(
+                f"文件大小超过限制，当前: {file_size / 1024 / 1024:.2f}MB，"
+                f"最大允许: {max_file_size / 1024 / 1024:.0f}MB"
+            )
+
+        timestamp = int(time.time() * 1000)
+        unique_filename = f"{timestamp}_{raw_filename}"
+        oss_object_name = f"kb_{kb_id}/{unique_filename}"
+
+        oss_service = get_oss_service()
+        file_path = None
+        file_url_result = None
+
+        if oss_service.enabled:
+            file_url_result = oss_service.upload_file_from_bytes(content, oss_object_name, raw_filename)
+            if file_url_result:
+                file_path = file_url_result
+                logger.info(f"☁️  文件已上传到 OSS: {file_url_result}")
+
+        if not file_path:
+            kb_dir = Path(UPLOAD_DIR) / f"kb_{kb_id}"
+            kb_dir.mkdir(parents=True, exist_ok=True)
+            local_path = kb_dir / unique_filename
+            with open(local_path, "wb") as f:
+                f.write(content)
+            file_path = str(local_path)
+            logger.info(f"💾 文件已保存到本地: {file_path}")
+
+        file_record = await KnowledgeBaseFileService.create_file_record(
+            conn, kb_id, current_user.id, raw_filename, file_path, file_size, file_type
+        )
+
+        await KnowledgeBaseFileService.update_file_progress(
+            conn, file_record.id, 30, STAGE_PROCESSING
+        )
+        background_tasks.add_task(
+            process_file_background, file_record.id, file_path, kb_id, file_type
+        )
+
+        logger.info(f"文件 URL 已下载并记录: {url}, 文件 ID: {file_record.id}, 类型: {file_type}")
+        return BaseResponse(
+            code=200,
+            msg="文件下载成功，正在处理中",
+            data=FileUploadResponse(
+                id=file_record.id,
+                file_name=file_record.file_name,
+                file_size=file_record.file_size,
+                status=file_record.status,
+                chunk_count=file_record.chunk_count,
+                progress_percent=30,
+                processing_stage=STAGE_PROCESSING,
+                created_at=file_record.created_at,
+                file_url=file_url_result or file_path,
+            ).dict()
+        )
+
+    # ---------- 普通网页 URL：走 crawl4ai 抓取流程 ----------
     file_name = f"{parsed_url.netloc}{parsed_url.path}".replace('/', '_')[:200]
     if not file_name:
         file_name = "webpage"

backend/core/config.py

@@ -106,6 +106,23 @@ class Settings(BaseSettings):
     ocr_access_key_secret: Optional[str] = None
     ocr_endpoint: str = "ocr-api.cn-hangzhou.aliyuncs.com"  # OCR 服务端点
 
+    # 网页抓取配置（crawl4ai）
+    crawler_timeout_ms: int = Field(
+        default=30000,
+        validation_alias=AliasChoices("CRAWLER_TIMEOUT_MS", "crawler_timeout_ms"),
+        description="页面加载超时（毫秒），默认 30 秒",
+    )
+    crawler_wait_for_js_ms: int = Field(
+        default=2000,
+        validation_alias=AliasChoices("CRAWLER_WAIT_FOR_JS_MS", "crawler_wait_for_js_ms"),
+        description="等待 JS 渲染的额外延迟（毫秒），默认 2 秒",
+    )
+    crawler_stealth_enabled: bool = Field(
+        default=True,
+        validation_alias=AliasChoices("CRAWLER_STEALTH_ENABLED", "crawler_stealth_enabled"),
+        description="是否启用 stealth 模式绕过反爬，默认开启",
+    )
+
     # 微信小程序配置
     wechat_app_id: Optional[str] = None
     wechat_app_secret: Optional[str] = None

backend/docker-compose.infr.yml

@@ -0,0 +1,66 @@
+name: ${INFR_PROJECT_NAME}
+
+services:
+  postgresql:
+    image: postgres:${INFR_POSTGRESQL_VERSION}
+    container_name: ${INFR_PROJECT_NAME}-${INFR_POSTGRESQL_CONTAINER_NAME}
+    restart: always
+    environment:
+      - POSTGRES_USER=${INFR_POSTGRESQL_POSTGRES_USER}
+      - POSTGRES_PASSWORD=${INFR_POSTGRESQL_POSTGRES_PASSWORD}
+    ports:
+      - ${INFR_POSTGRESQL_POSTGRES_PORT}:5432
+    volumes:
+      - ./volumes/postgresql/data:/var/lib/postgresql/data
+    networks:
+      - infr
+    healthcheck:
+      test: ["CMD", "pg_isready", "-h", "127.0.0.1", "-p", "5432", "-q", "-U", "${INFR_POSTGRESQL_POSTGRES_USER}"]
+      start_period: 20s
+      interval: 30s
+      retries: 5
+      timeout: 5s
+
+  chroma:
+    image: chromadb/chroma:latest
+    container_name: ${INFR_PROJECT_NAME}-${INFR_CHROMA_CONTAINER_NAME}
+    volumes:
+      - ./volumes/chroma/data:/data
+    ports:
+      - ${INFR_CHROMA_PORT}:8000
+    networks:
+      - infr
+    restart: unless-stopped
+
+  neo4j:
+    image: neo4j:${INFR_NEO4J_VERSION}
+    container_name: ${INFR_PROJECT_NAME}-${INFR_NEO4J_CONTAINER_NAME}
+    restart: always
+    environment:
+      - TZ=Asia/Shanghai
+      - NEO4J_AUTH=neo4j/${NEO4J_PASSWORD:-graph123}
+    ports:
+      - ${INFR_NEO4J_WEB_HTTP_PORT}:7474
+      - ${INFR_NEO4J_BOLT_PORT}:7687
+    volumes:
+      - ./volumes/neo4j/data:/data
+      - ./volumes/neo4j/logs:/logs
+    networks:
+      - infr
+
+  redis:
+    image: redis:${INFR_REDIS_VERSION}
+    container_name: ${INFR_PROJECT_NAME}-${INFR_REDIS_CONTAINER_NAME}
+    restart: always
+    command: redis-server --requirepass ${INFR_REDIS_REDIS_PASSWORD}
+    ports:
+      - ${INFR_REDIS_REDIS_PORT}:6379
+    volumes:
+      - ./volumes/redis/data:/data
+    networks:
+      - infr
+
+networks:
+  infr:
+    name: ${INFR_PROJECT_NAME}
+    driver: bridge

backend/pyproject.toml

@@ -39,7 +39,8 @@ dependencies = [
     "python-multipart>=0.0.20",
     "requests>=2.32.5",
     "rich>=14.2.0",
-    "selenium>=4.0.0",
+    "crawl4ai>=0.9.0,<1.0.0",
+    "trafilatura>=1.12.0",
     "sse-starlette>=3.0.3",
     "streamlit>=1.52.0",
     "tavily-python>=0.7.13",

backend/restart.sh

@@ -0,0 +1,31 @@
+#!/bin/bash
+
+cd "$(dirname "$0")" || exit 1
+
+PID_FILE="$(dirname "$0")/app.pid"
+PORT=7862
+
+# 停止旧进程
+if [ -f "$PID_FILE" ]; then
+    PID=$(cat "$PID_FILE")
+    if kill -0 "$PID" 2>/dev/null; then
+        kill "$PID"
+        echo "Stopped old process (PID=$PID)."
+    fi
+    rm -f "$PID_FILE"
+fi
+
+sleep 2
+
+# 启动新进程
+nohup uv run uvicorn main:app \
+    --host 0.0.0.0 \
+    --port $PORT \
+    > nohup.out 2>&1 &
+
+echo $! > "$PID_FILE"
+echo "Started (PID=$!)."
+
+sleep 1
+
+ps -ef | grep "$PORT" | grep -v grep

backend/services/vector_service.py

@@ -16,7 +16,6 @@ from core.config import settings
 
 from langchain_community.document_loaders import (
     PyPDFLoader,
-    WebBaseLoader,
     UnstructuredWordDocumentLoader,
     UnstructuredExcelLoader,
     UnstructuredPowerPointLoader,
@@ -160,6 +159,7 @@ class ProcessResult:
     chunk_count: int
     error_message: Optional[str] = None
     extracted_image_paths: Optional[List[str]] = None  # DOCX 中提取的图片路径（供视觉模型使用）
+    page_title: Optional[str] = None  # 网页标题（URL 抓取时填充）
 
 
 class VectorService:
@@ -1244,7 +1244,8 @@ class VectorService:
     async def process_url(
         self,
         url: str,
-        knowledge_base_id: int
+        knowledge_base_id: int,
+        file_id: Optional[int] = None,
     ) -> ProcessResult:
         """
         处理 URL：加载网页内容、分割、向量化
@@ -1259,23 +1260,36 @@ class VectorService:
         try:
             logger.info(f"开始处理 URL: {url}")
 
-            # 1. 加载网页内容（放到线程池执行，避免阻塞事件循环）
-            # 使用 bs4 过滤，只保留主要内容（可以根据需要调整）
-            bs4_strainer = bs4.SoupStrainer()
-            loader = WebBaseLoader(
-                web_paths=(url,),
-                bs_kwargs={"parse_only": bs4_strainer}
+            # 1. 使用 crawl4ai 抓取网页内容（支持 JS 渲染 + stealth 反爬）
+            from services.web_crawler_service import fetch_url_content
+            crawl_result = await fetch_url_content(url)
+
+            if not crawl_result.success:
+                logger.warning(f"网页抓取失败: {url} | {crawl_result.error_message}")
+                return ProcessResult(
+                    success=False,
+                    chunks=[],
+                    chunk_count=0,
+                    error_message=crawl_result.error_message,
                 )
-            logger.info("🔄 在线程池中加载网页内容...")
-            docs = await asyncio.to_thread(loader.load)
-            logger.info(f"网页加载完成，共 {len(docs)} 个文档")
 
-            if not docs:
-                error_msg = "未能从 URL 加载到任何内容"
-                logger.warning(error_msg)
-                return ProcessResult(success=False, chunks=[], chunk_count=0, error_message=error_msg)
+            logger.info(f"网页抓取完成，内容长度: {len(crawl_result.markdown)} 字符")
 
-            total_chars = sum(len(d.page_content or "") for d in docs)
+            # 2. 将 Markdown 文本包装为 LangChain Document
+            from langchain_core.documents import Document
+            page_title = crawl_result.title or ""
+            docs = [
+                Document(
+                    page_content=crawl_result.markdown,
+                    metadata={
+                        "source": url,
+                        "title": page_title,
+                        "file_type": "url",
+                    },
+                )
+            ]
+
+            total_chars = len(crawl_result.markdown)
             try:
                 validate_kb_text_length(total_chars)
             except ValueError as e:
@@ -1283,11 +1297,10 @@ class VectorService:
                 logger.warning(error_msg)
                 return ProcessResult(success=False, chunks=[], chunk_count=0, error_message=error_msg)
 
-            # 2. 分割文本
+            # 3. 分割文本
             all_splits = self.text_splitter.split_documents(docs)
             logger.info(f"文本分割完成，共 {len(all_splits)} 个块")
 
-            # 检查是否有内容
             if not all_splits:
                 error_msg = "网页分割后没有内容，可能是空白页面或无法提取文本"
                 logger.warning(error_msg)
@@ -1300,25 +1313,30 @@ class VectorService:
                 logger.warning(error_msg)
                 return ProcessResult(success=False, chunks=[], chunk_count=0, error_message=error_msg)
 
-            # 3. 向量化并存储
+            # 4. 向量化前注入 file_id / chunk_index（与 process_document 保持一致，确保按文件删除向量可用）
+            for idx, doc in enumerate(all_splits):
+                if not doc.metadata:
+                    doc.metadata = {}
+                doc.metadata["chunk_index"] = idx
+                if file_id is not None:
+                    doc.metadata["file_id"] = file_id
+            if file_id is not None:
+                logger.info(f"✅ 已为 {len(all_splits)} 个 chunks 设置 file_id={file_id}")
+
+            # 5. 向量化并存储
             collection_name = f"kb_{knowledge_base_id}"
             vector_store = self.get_vector_store(collection_name)
 
-            # 添加文档到向量库
             vector_ids = vector_store.add_documents(documents=all_splits)
             logger.info(f"向量化完成，共 {len(vector_ids)} 个向量")
 
-            # 4. 准备返回数据
-            chunks = []
-            for idx, (doc, vector_id) in enumerate(zip(all_splits, vector_ids)):
-                chunks.append((
-                    idx,  # chunk_index
-                    doc.page_content,  # content
-                    doc.metadata,  # metadata
-                    vector_id  # vector_id
-                ))
+            # 6. 准备返回数据
+            chunks = [
+                (idx, doc.page_content, doc.metadata, vector_id)
+                for idx, (doc, vector_id) in enumerate(zip(all_splits, vector_ids))
+            ]
 
-            return ProcessResult(success=True, chunks=chunks, chunk_count=len(chunks))
+            return ProcessResult(success=True, chunks=chunks, chunk_count=len(chunks), page_title=page_title)
 
         except Exception as e:
             error_msg = f"处理 URL 失败: {str(e)}"
@@ -1360,16 +1378,31 @@ class VectorService:
             extracted_image_paths = []  # 用于保存 DOCX 中提取的图片路径
             ocr_stage = file_type.lower() in ("png", "jpg", "jpeg", "bmp", "pdf")
             
-            # 特殊处理 URL（放到线程池执行）
+            # 特殊处理 URL（使用 crawl4ai，支持 JS 渲染 + stealth 反爬）
             if file_type == "url":
-                bs4_strainer = bs4.SoupStrainer()
-                loader = WebBaseLoader(
-                    web_paths=(file_path,),
-                    bs_kwargs={"parse_only": bs4_strainer}
+                from services.web_crawler_service import fetch_url_content
+                from langchain_core.documents import Document as LcDocument
+                logger.info(f"🔄 crawl4ai 抓取网页内容: {file_path}")
+                crawl_result = await fetch_url_content(file_path)
+                if not crawl_result.success:
+                    logger.warning(f"网页抓取失败: {file_path} | {crawl_result.error_message}")
+                    return ProcessResult(
+                        success=False,
+                        chunks=[],
+                        chunk_count=0,
+                        error_message=crawl_result.error_message,
                     )
-                logger.info("🔄 在线程池中加载网页内容...")
-                docs = await asyncio.to_thread(loader.load)
-                logger.info(f"网页加载完成，共 {len(docs)} 个文档")
+                logger.info(f"网页抓取完成，内容长度: {len(crawl_result.markdown)} 字符")
+                docs = [
+                    LcDocument(
+                        page_content=crawl_result.markdown,
+                        metadata={
+                            "source": file_path,
+                            "title": crawl_result.title,
+                            "file_type": "url",
+                        },
+                    )
+                ]
             else:
                 # 使用统一的加载器选择逻辑
                 loader = self._get_loader_for_file(file_path, file_type)

backend/services/web_crawler_service.py

@@ -0,0 +1,346 @@
+"""
+网页抓取服务
+
+抓取策略（三级降级）：
+  1. crawl4ai stealth 模式   — 应对 JS 渲染 / 反爬检测
+  2. crawl4ai 普通模式       — stealth 失败时回退
+  3. httpx + trafilatura     — Playwright 无法导航时（JS 跳转、协议错误等）的最终兜底
+
+使用方式：
+    from services.web_crawler_service import fetch_url_content, CrawlResult
+    result = await fetch_url_content("https://example.com")
+    if result.success:
+        text = result.markdown
+"""
+
+from __future__ import annotations
+
+import asyncio
+import os
+import re
+from dataclasses import dataclass
+from typing import Optional
+
+from core.config import settings
+from logger.logging import get_logger
+
+logger = get_logger(__name__)
+
+# 限制并发 Chromium 进程数，避免多用户同时提交 URL 时资源耗尽
+# 每个 AsyncWebCrawler 实例对应一个 Chromium 子进程
+_PLAYWRIGHT_SEMAPHORE = asyncio.Semaphore(3)
+
+# ---------------------------------------------------------------------------
+# 拦截页面关键词列表（命中即视为被反爬拦截）
+# ---------------------------------------------------------------------------
+_BLOCK_PATTERNS: list[re.Pattern] = [
+    re.compile(p, re.IGNORECASE)
+    for p in [
+        r"环境异常",
+        r"完成验证后即可继续访问",
+        r"百度安全验证",
+        r"robot.*check",
+        r"security check",
+        r"access denied",
+        r"403 forbidden",
+        r"captcha",
+        r"请输入验证码",
+        r"人机验证",
+        r"滑动验证",
+        r"点击验证",
+        r"请证明.*不是机器人",
+    ]
+]
+
+# 内容最短有效长度（字符数）
+_MIN_CONTENT_LENGTH = 50
+
+# 通用浏览器 UA
+_CHROME_UA = (
+    "Mozilla/5.0 (Windows NT 10.0; Win64; x64) "
+    "AppleWebKit/537.36 (KHTML, like Gecko) "
+    "Chrome/124.0.0.0 Safari/537.36"
+)
+
+
+@dataclass
+class CrawlResult:
+    """网页抓取结果"""
+    success: bool
+    markdown: str = ""
+    error_message: str = ""
+    is_blocked: bool = False
+    url: str = ""
+    title: str = ""
+
+
+def _is_blocked_content(text: str) -> bool:
+    """判断内容是否为反爬拦截页面。
+
+    只扫描前 500 字符：拦截页面的特征词（验证码提示、安全验证等）通常出现在
+    页面最开头，扫全文会增加不必要的计算开销。
+    已知权衡：若 WAF 在前 500 字符放置正常内容、拦截词出现在后面，会漏判；
+    实际观察中此场景极少见，当前策略是合理的工程取舍。
+    """
+    if not text:
+        return False
+    return any(p.search(text[:500]) for p in _BLOCK_PATTERNS)
+
+
+def _validate(markdown: str, url: str, stealth: bool) -> CrawlResult | None:
+    """校验内容有效性，返回失败的 CrawlResult；内容有效时返回 None。"""
+    text = markdown.strip()
+    if len(text) < _MIN_CONTENT_LENGTH:
+        return CrawlResult(
+            success=False, url=url,
+            error_message=f"页面内容过短（{len(text)} 字符），可能是空白页或加载失败",
+        )
+    if _is_blocked_content(text):
+        mode_label = "stealth" if stealth else "普通"
+        return CrawlResult(
+            success=False, url=url, is_blocked=True,
+            error_message=(
+                f"该网页拒绝了自动抓取请求（{mode_label}模式）。"
+                "常见原因：微信公众号、百度百科等平台对非浏览器访问设有验证墙，"
+                "暂时无法自动获取内容。建议手动复制文本后通过「上传文本文件」导入知识库。"
+            ),
+        )
+    return None
+
+
+async def fetch_url_content(
+    url: str,
+    *,
+    stealth: Optional[bool] = None,
+    timeout_ms: Optional[int] = None,
+    wait_for_js_ms: Optional[int] = None,
+) -> CrawlResult:
+    """
+    抓取指定 URL 的正文内容，返回干净的 Markdown 文本。
+
+    三级降级策略：
+      1. crawl4ai stealth 模式
+      2. crawl4ai 普通模式
+      3. httpx 直接 HTTP 抓取 + trafilatura 正文提取
+    """
+    stealth = settings.crawler_stealth_enabled if stealth is None else stealth
+    timeout_ms = timeout_ms or settings.crawler_timeout_ms
+    wait_for_js_ms = wait_for_js_ms or settings.crawler_wait_for_js_ms
+
+    # --- 级别 1：crawl4ai（stealth 由配置决定）---
+    ran_stealth = stealth  # 记录本次 level 1 实际运行的模式
+    result = await _crawl_with_playwright(
+        url, stealth=stealth, timeout_ms=timeout_ms, wait_for_js_ms=wait_for_js_ms
+    )
+    if result.success:
+        return result
+
+    # --- 级别 2：crawl4ai 普通模式（仅当 level 1 以 stealth 运行但失败时才有意义）---
+    if ran_stealth:
+        logger.info(f"[WebCrawler] stealth 模式失败，尝试普通模式: {url}")
+        result = await _crawl_with_playwright(
+            url, stealth=False, timeout_ms=timeout_ms, wait_for_js_ms=wait_for_js_ms
+        )
+        if result.success:
+            return result
+
+    # --- 级别 3：httpx + trafilatura 兜底 ---
+    logger.info(f"[WebCrawler] Playwright 全部失败，尝试 httpx 兜底: {url}")
+    return await _crawl_with_httpx(url, timeout_ms=timeout_ms)
+
+
+async def _crawl_with_playwright(
+    url: str,
+    *,
+    stealth: bool,
+    timeout_ms: int,
+    wait_for_js_ms: int,
+) -> CrawlResult:
+    """用 crawl4ai (Playwright) 抓取。"""
+    try:
+        from crawl4ai import AsyncWebCrawler, BrowserConfig, CrawlerRunConfig
+        from crawl4ai.markdown_generation_strategy import DefaultMarkdownGenerator
+    except ImportError:
+        msg = "crawl4ai 未安装，请执行 `uv add crawl4ai` 并运行 `crawl4ai-setup` 安装浏览器"
+        logger.error(f"[WebCrawler] {msg}")
+        return CrawlResult(success=False, url=url, error_message=msg)
+
+    # 透传系统代理给 Chromium 子进程（用新版 proxy_config）
+    _sys_proxy = (
+        os.environ.get("https_proxy") or os.environ.get("HTTPS_PROXY")
+        or os.environ.get("http_proxy") or os.environ.get("HTTP_PROXY")
+    ) or None
+
+    from crawl4ai.async_configs import ProxyConfig
+    proxy_cfg = ProxyConfig(server=_sys_proxy) if _sys_proxy else None
+
+    browser_cfg = BrowserConfig(
+        headless=True,
+        enable_stealth=stealth,
+        proxy_config=proxy_cfg,
+        user_agent=_CHROME_UA,
+    )
+
+    # 统一等待 JS 渲染，不依赖页面特定 selector
+    # delay_before_return_html 在 domcontentloaded 后额外等待，保证动态内容渲染完成
+    run_cfg = CrawlerRunConfig(
+        markdown_generator=DefaultMarkdownGenerator(
+            options={"ignore_links": False, "body_width": 0},
+        ),
+        page_timeout=timeout_ms,
+        wait_until="domcontentloaded",
+        delay_before_return_html=wait_for_js_ms / 1000,
+        word_count_threshold=5,
+        remove_overlay_elements=True,
+        excluded_tags=["nav", "footer", "aside", "script", "style"],
+    )
+
+    try:
+        async with _PLAYWRIGHT_SEMAPHORE:
+            async with AsyncWebCrawler(config=browser_cfg) as crawler:
+                crawl_res = await crawler.arun(url=url, config=run_cfg)
+
+        if not crawl_res.success:
+            err = getattr(crawl_res, "error_message", "页面加载失败")
+            logger.warning(f"[WebCrawler] Playwright 抓取失败 (stealth={stealth}): {url} | {err}")
+            return CrawlResult(success=False, url=url, error_message=err)
+
+        fit = (crawl_res.markdown.fit_markdown or "").strip() if crawl_res.markdown else ""
+        raw = (crawl_res.markdown.raw_markdown or "").strip() if crawl_res.markdown else ""
+
+        # 优先用 trafilatura 从原始 HTML 提取正文（适用于任意网站结构）
+        # 回退顺序：trafilatura(html) > fit_markdown > raw_markdown
+        markdown = ""
+        if crawl_res.html:
+            markdown = _extract_text_from_html(crawl_res.html, url)
+        if len(markdown) < _MIN_CONTENT_LENGTH:
+            markdown = fit if len(fit) >= _MIN_CONTENT_LENGTH else raw
+        # title 在 crawl_res.metadata 字典里
+        meta = crawl_res.metadata or {}
+        title = (meta.get("title") or meta.get("og:title") or "").strip()
+        # metadata 没有时，从原始 HTML 提取
+        if not title and crawl_res.html:
+            title = _extract_title_from_html(crawl_res.html)
+
+        failed = _validate(markdown, url, stealth)
+        if failed:
+            logger.warning(f"[WebCrawler] 内容验证失败 (stealth={stealth}): {url}")
+            return failed
+
+        logger.info(f"[WebCrawler] Playwright 抓取成功 (stealth={stealth}): {url} | {len(markdown)} 字符")
+        return CrawlResult(success=True, url=url, markdown=markdown, title=title)
+
+    except Exception as exc:
+        logger.warning(f"[WebCrawler] Playwright 异常 (stealth={stealth}): {url} | {exc}")
+        return CrawlResult(success=False, url=url, error_message=str(exc))
+
+
+async def _crawl_with_httpx(url: str, *, timeout_ms: int) -> CrawlResult:
+    """
+    httpx 直接 HTTP 请求 + trafilatura 正文提取。
+    适用于：含 JS 跳转导致 Playwright 导航失败、但 HTML 本身已包含正文的页面。
+    """
+    try:
+        import httpx
+    except ImportError:
+        return CrawlResult(success=False, url=url, error_message="httpx 未安装")
+
+    # 读取系统代理（httpx 新版用 proxy 单数形式）
+    _sys_proxy = (
+        os.environ.get("https_proxy") or os.environ.get("HTTPS_PROXY")
+        or os.environ.get("http_proxy") or os.environ.get("HTTP_PROXY")
+    ) or None
+
+    try:
+        client_kwargs: dict = dict(
+            follow_redirects=True,
+            timeout=timeout_ms / 1000,
+            headers={
+                "User-Agent": _CHROME_UA,
+                "Accept": "text/html,application/xhtml+xml,*/*;q=0.9",
+                "Accept-Language": "zh-CN,zh;q=0.9,en;q=0.8",
+            },
+        )
+        if _sys_proxy:
+            client_kwargs["proxy"] = _sys_proxy
+
+        async with httpx.AsyncClient(**client_kwargs) as client:
+            resp = await client.get(url)
+            resp.raise_for_status()
+            html = resp.text
+    except Exception as exc:
+        error_msg = f"httpx 抓取失败: {exc}"
+        logger.warning(f"[WebCrawler] {error_msg} | url={url}")
+        return CrawlResult(success=False, url=url, error_message=error_msg)
+
+    # 用 trafilatura 提取正文（如未安装则退回 BeautifulSoup 简单提取）
+    markdown = _extract_text_from_html(html, url)
+    title = _extract_title_from_html(html)
+
+    if not markdown:
+        error_msg = "httpx 抓取成功但未能提取到正文内容"
+        logger.warning(f"[WebCrawler] {error_msg}: {url}")
+        return CrawlResult(success=False, url=url, error_message=error_msg)
+
+    failed = _validate(markdown, url, stealth=False)
+    if failed:
+        return failed
+
+    logger.info(f"[WebCrawler] httpx 兜底抓取成功: {url} | {len(markdown)} 字符")
+    return CrawlResult(success=True, url=url, markdown=markdown, title=title)
+
+
+def _extract_text_from_html(html: str, url: str) -> str:
+    """从 HTML 提取正文，优先用 trafilatura，降级用 BeautifulSoup。"""
+    # 优先：trafilatura（专为正文提取设计，过滤导航/广告效果好）
+    try:
+        import trafilatura
+        text = trafilatura.extract(
+            html,
+            include_comments=False,
+            include_tables=True,
+            no_fallback=False,
+            url=url,
+        )
+        if text and len(text.strip()) >= _MIN_CONTENT_LENGTH:
+            return text.strip()
+    except ImportError:
+        pass
+    except Exception as e:
+        logger.debug(f"[WebCrawler] trafilatura 提取失败，降级到 bs4: {e}")
+
+    # 降级：BeautifulSoup 去除脚本/样式后取全文
+    try:
+        from bs4 import BeautifulSoup
+        soup = BeautifulSoup(html, "html.parser")
+        for tag in soup(["script", "style", "nav", "footer", "header", "aside"]):
+            tag.decompose()
+        return soup.get_text(separator="\n", strip=True)
+    except Exception:
+        return ""
+
+
+def _extract_title_from_html(html: str) -> str:
+    """从 HTML 提取标题，依次尝试 <title>、og:title、h1。"""
+    try:
+        from bs4 import BeautifulSoup
+        soup = BeautifulSoup(html, "html.parser")
+        # 1. <title> 标签
+        tag = soup.find("title")
+        if tag:
+            t = tag.get_text(strip=True)
+            if t:
+                return t
+        # 2. Open Graph og:title
+        og = soup.find("meta", property="og:title")
+        if og and og.get("content"):
+            return og["content"].strip()
+        # 3. 第一个 <h1>
+        h1 = soup.find("h1")
+        if h1:
+            t = h1.get_text(strip=True)
+            if t:
+                return t
+    except Exception:
+        pass
+    return ""

backend/start.sh

@@ -0,0 +1,26 @@
+#!/bin/bash
+
+cd "$(dirname "$0")" || exit 1
+
+PID_FILE="$(dirname "$0")/app.pid"
+PORT=7862
+
+# 检查是否已在运行
+if [ -f "$PID_FILE" ]; then
+    OLD_PID=$(cat "$PID_FILE")
+    if kill -0 "$OLD_PID" 2>/dev/null; then
+        echo "Service is already running (PID=$OLD_PID)."
+        exit 0
+    else
+        echo "Stale PID file found, removing..."
+        rm -f "$PID_FILE"
+    fi
+fi
+
+nohup uv run uvicorn main:app \
+    --host 0.0.0.0 \
+    --port $PORT \
+    > nohup.out 2>&1 &
+
+echo $! > "$PID_FILE"
+echo "Started (PID=$!)."

backend/stop.sh

@@ -0,0 +1,17 @@
+#!/bin/bash
+
+PID_FILE="$(dirname "$0")/app.pid"
+
+if [ -f "$PID_FILE" ]; then
+    PID=$(cat "$PID_FILE")
+    if kill -0 "$PID" 2>/dev/null; then
+        kill "$PID"
+        rm -f "$PID_FILE"
+        echo "Stopped (PID=$PID)."
+    else
+        echo "Process $PID is not running, cleaning up stale PID file."
+        rm -f "$PID_FILE"
+    fi
+else
+    echo "No PID file found. Service may not be running."
+fi

backend/uv.lock

@@ -80,6 +80,15 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/fb/76/641ae371508676492379f16e2fa48f4e2c11741bd63c48be4b12a6b09cba/aiosignal-1.4.0-py3-none-any.whl", hash = "sha256:053243f8b92b990551949e63930a839ff0cf0b0ebbe0597b0f3fb19e1a0fe82e", size = 7490, upload-time = "2025-07-03T22:54:42.156Z" },
 ]
 
+[[package]]
+name = "aiosqlite"
+version = "0.22.1"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/4e/8a/64761f4005f17809769d23e518d915db74e6310474e733e3593cfc854ef1/aiosqlite-0.22.1.tar.gz", hash = "sha256:043e0bd78d32888c0a9ca90fc788b38796843360c855a7262a532813133a0650", size = 14821, upload-time = "2025-12-23T19:25:43.997Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/00/b7/e3bf5133d697a08128598c8d0abc5e16377b51465a33756de24fa7dee953/aiosqlite-0.22.1-py3-none-any.whl", hash = "sha256:21c002eb13823fad740196c5a2e9d8e62f6243bd9e7e4a1f87fb5e44ecb4fceb", size = 17405, upload-time = "2025-12-23T19:25:42.139Z" },
+]
+
 [[package]]
 name = "alibabacloud-credentials"
 version = "1.0.8"
@@ -236,6 +245,25 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/11/5c/0132193d7da2c735669a1ed103b142fd63c9455984d48c5a88a1a516efaa/aliyun_python_sdk_kms-2.16.5-py2.py3-none-any.whl", hash = "sha256:24b6cdc4fd161d2942619479c8d050c63ea9cd22b044fe33b60bbb60153786f0", size = 99495, upload-time = "2024-08-30T09:01:18.462Z" },
 ]
 
+[[package]]
+name = "alphashape"
+version = "1.3.1"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "click" },
+    { name = "click-log" },
+    { name = "networkx" },
+    { name = "numpy" },
+    { name = "rtree" },
+    { name = "scipy" },
+    { name = "shapely" },
+    { name = "trimesh" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/2e/83/67ff905694df5b34a777123b59fdfd05998d5a31766f188aafbf5b340055/alphashape-1.3.1.tar.gz", hash = "sha256:7a27340afc5f8ed301577acec46bb0cf2bada5410045f7289142e735ef6977ec", size = 26316, upload-time = "2021-04-16T17:47:19.486Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/e4/ad/77fad9d6f974ec58d837cb49fb9b483d6227a420c4f908c3578633de1d47/alphashape-1.3.1-py2.py3-none-any.whl", hash = "sha256:96a5ddd5f09534a35f03a8916aeeaac00fe4d6bec2f9ad78f87f57be3007f795", size = 13122, upload-time = "2021-04-16T17:47:17.773Z" },
+]
+
 [[package]]
 name = "altair"
 version = "6.1.0"
@@ -348,6 +376,15 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/64/b4/17d4b0b2a2dc85a6df63d1157e028ed19f90d4cd97c36717afef2bc2f395/attrs-26.1.0-py3-none-any.whl", hash = "sha256:c647aa4a12dfbad9333ca4e71fe62ddc36f4e63b2d260a37a8b83d2f043ac309", size = 67548, upload-time = "2026-03-19T14:22:23.645Z" },
 ]
 
+[[package]]
+name = "babel"
+version = "2.18.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/7d/b2/51899539b6ceeeb420d40ed3cd4b7a40519404f9baf3d4ac99dc413a834b/babel-2.18.0.tar.gz", hash = "sha256:b80b99a14bd085fcacfa15c9165f651fbb3406e66cc603abf11c5750937c992d", size = 9959554, upload-time = "2026-02-01T12:30:56.078Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl", hash = "sha256:e2b422b277c2b9a9630c1d7903c2a00d0830c409c59ac8cae9081c92f1aeba35", size = 10196845, upload-time = "2026-02-01T12:30:53.445Z" },
+]
+
 [[package]]
 name = "backoff"
 version = "1.11.1"
@@ -430,6 +467,24 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/9d/2a/9186535ce58db529927f6cf5990a849aa9e052eea3e2cfefe20b9e1802da/bracex-2.6-py3-none-any.whl", hash = "sha256:0b0049264e7340b3ec782b5cb99beb325f36c3782a32e36e876452fd49a09952", size = 11508, upload-time = "2025-06-22T19:12:29.781Z" },
 ]
 
+[[package]]
+name = "brotli"
+version = "1.2.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/f7/16/c92ca344d646e71a43b8bb353f0a6490d7f6e06210f8554c8f874e454285/brotli-1.2.0.tar.gz", hash = "sha256:e310f77e41941c13340a95976fe66a8a95b01e783d430eeaf7a2f87e0a57dd0a", size = 7388632, upload-time = "2025-11-05T18:39:42.86Z" }
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+[[package]]
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+version = "2.2.0"
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 version = "2.4.0"
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+[[package]]
+name = "tld"
+version = "0.13.2"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/5c/5d/76b4383ac4e5b5e254e50c09807b3e13820bed6d6c11cd540264988d6802/tld-0.13.2.tar.gz", hash = "sha256:d983fa92b9d717400742fca844e29d5e18271079c7bcfabf66d01b39b4a14345", size = 467175, upload-time = "2026-03-06T23:50:34.498Z" }
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+]
+
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 name = "tokenizers"
 version = "0.23.1"
@@ -3239,34 +3650,33 @@ wheels = [
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 [[package]]
-name = "trio"
-version = "0.33.0"
+name = "trafilatura"
+version = "2.0.0"
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-    { name = "cffi", marker = "implementation_name != 'pypy' and os_name == 'nt'" },
-    { name = "idna" },
-    { name = "outcome" },
-    { name = "sniffio" },
-    { name = "sortedcontainers" },
+    { name = "certifi" },
+    { name = "charset-normalizer" },
+    { name = "courlan" },
+    { name = "htmldate" },
+    { name = "justext" },
+    { name = "lxml" },
+    { name = "urllib3" },
 ]
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 [[package]]
-name = "trio-websocket"
-version = "0.12.2"
+name = "trimesh"
+version = "4.12.2"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "outcome" },
-    { name = "trio" },
-    { name = "wsproto" },
+    { name = "numpy" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/d1/3c/8b4358e81f2f2cfe71b66a267f023a91db20a817b9425dd964873796980a/trio_websocket-0.12.2.tar.gz", hash = "sha256:22c72c436f3d1e264d0910a3951934798dcc5b00ae56fc4ee079d46c7cf20fae", size = 33549, upload-time = "2025-02-25T05:16:58.947Z" }
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+    { url = "https://files.pythonhosted.org/packages/05/98/716a473cfb24750858ddd5d14e6527539dd206583a46408d08eeb2844a75/trimesh-4.12.2-py3-none-any.whl", hash = "sha256:b5b5afa63c5272345f2858f7676bc8c217dc8a89f4fadf6193fe10a81b5ff2aa", size = 741043, upload-time = "2026-05-01T00:57:40.763Z" },
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+[[package]]
+name = "unclecode-litellm"
+version = "1.81.13"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "aiohttp" },
+    { name = "click" },
+    { name = "fastuuid" },
+    { name = "httpx" },
+    { name = "importlib-metadata" },
+    { name = "jinja2" },
+    { name = "jsonschema" },
+    { name = "openai" },
+    { name = "pydantic" },
+    { name = "python-dotenv" },
+    { name = "tiktoken" },
+    { name = "tokenizers" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/ce/c4/93ed52c49c2347184f908c692ebb7c1f06303805910774c3282ac68033db/unclecode_litellm-1.81.13.tar.gz", hash = "sha256:db70e34e3e859c0a07f02cb02eaa644f8fa4b4ecc5e2f3be9a58bd7d1c3feedc", size = 16678208, upload-time = "2026-03-24T14:46:31.915Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/43/85/7b1e0bc5827bcb23dc572b17c447fb5825340f36a9e4405d4b777b862e0c/unclecode_litellm-1.81.13-py3-none-any.whl", hash = "sha256:5e1fbedbed92333b48e7371e0bacf86d1288020451bf34351703c3b159591399", size = 18008619, upload-time = "2026-03-24T14:46:28.009Z" },
+]
+
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 name = "unstructured"
 version = "0.18.27"
@@ -3411,11 +3844,6 @@ wheels = [
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-[package.optional-dependencies]
-socks = [
-    { name = "pysocks" },
-]
-
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 version = "0.14.1"
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-[[package]]
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-version = "1.3.2"
-source = { registry = "https://pypi.org/simple" }
-dependencies = [
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-
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 name = "xlrd"
 version = "2.0.2"

mcp-server-demo/uv.lock

@@ -300,7 +300,7 @@ wheels = [
 [[package]]
 name = "mcp-server-demo"
 version = "0.1.0"
-source = { virtual = "." }
+source = { editable = "." }
 dependencies = [
     { name = "httpx" },
     { name = "mcp" },

readme.md

@@ -73,7 +73,24 @@ uv sync --frozen
 uv sync --frozen --no-dev
 ```
 
-### 4.2 启动服务
+### 4.2 初始化网页抓取浏览器（crawl4ai，首次必做）
+
+知识库支持提交 URL 自动抓取网页内容，底层通过 crawl4ai 驱动 Playwright Chromium 完成。
+Playwright 是**进程内库**，不需要独立服务——程序运行时会直接 fork 一个 Chromium 子进程，通过本机 CDP 通信。
+
+首次部署或新环境克隆后，需安装 Chromium 浏览器及系统依赖（**只需执行一次**）：
+
+```bash
+cd backend
+uv run crawl4ai-setup
+# 若上面命令失败，手动执行：
+uv run playwright install chromium
+uv run playwright install-deps chromium
+```
+
+> Docker 环境无需手动执行，Dockerfile 中已包含这两步。
+
+### 4.3 启动服务
 
 在 **`backend` 目录**下执行（会读取 `backend/.env` 中的 `API.HOST` / `API.PORT`）：
 
@@ -91,7 +108,7 @@ uv run uvicorn main:app --reload --host 0.0.0.0 --port 7862
 
 > **注意**：若直接运行 `uvicorn main:app` 且未传 `--port`，默认端口为 **8000**，不会自动读取 `.env` 中的 `API.PORT`。生产环境请使用 `python -m main` 或显式传入 `--port`。
 
-### 4.3 验证
+### 4.4 验证
 
 - 健康：查看启动日志中是否有「数据库健康检查通过」
 - API 文档：浏览器打开 `http://<主机>:<端口>/docs`（根路径 `/` 会重定向到 Swagger）