commit

.github/workflows/release.yml

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+name: Release Client
+
+on:
+  push:
+    tags:
+      - 'v*'
+  workflow_dispatch:
+    inputs:
+      tag_name:
+        description: '要发布的 tag，例如 v2.0.1'
+        required: true
+        type: string
+
+permissions:
+  contents: write
+
+jobs:
+  create-release:
+    name: Create GitHub Release
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+          ref: ${{ inputs.tag_name || github.ref }}
+
+      - name: Create release notes from commits
+        env:
+          TAG_NAME: ${{ inputs.tag_name || github.ref_name }}
+        run: |
+          PREVIOUS_TAG="$(git describe --tags --abbrev=0 "${TAG_NAME}^" 2>/dev/null || true)"
+          if [ -n "$PREVIOUS_TAG" ]; then
+            RANGE="$PREVIOUS_TAG..$TAG_NAME"
+            COMPARE_URL="https://github.com/${{ github.repository }}/compare/${PREVIOUS_TAG}...${TAG_NAME}"
+          else
+            RANGE="$TAG_NAME"
+            COMPARE_URL="https://github.com/${{ github.repository }}/commits/${TAG_NAME}"
+          fi
+
+          {
+            echo "## 更新内容"
+            echo
+            git log "$RANGE" --no-merges --pretty=format:'- %s (%h)' || true
+            echo
+            echo
+            echo "**Full Changelog**: $COMPARE_URL"
+          } > release_notes.md
+
+      - name: Create or update GitHub Release
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+          TAG_NAME: ${{ inputs.tag_name || github.ref_name }}
+        run: |
+          if gh release view "$TAG_NAME" >/dev/null 2>&1; then
+            gh release edit "$TAG_NAME" --title "$TAG_NAME" --notes-file release_notes.md
+          else
+            gh release create "$TAG_NAME" --title "$TAG_NAME" --notes-file release_notes.md
+          fi
+
+  build:
+    name: Build ${{ matrix.os }}
+    needs: create-release
+    runs-on: ${{ matrix.os }}
+    strategy:
+      fail-fast: false
+      matrix:
+        os: [windows-latest, macos-latest]
+
+    defaults:
+      run:
+        working-directory: client
+        shell: bash
+
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+        with:
+          ref: ${{ inputs.tag_name || github.ref }}
+
+      - name: Setup Node.js
+        uses: actions/setup-node@v4
+        with:
+          node-version: 22
+          cache: npm
+          cache-dependency-path: client/package-lock.json
+
+      - name: Cache Electron build downloads
+        if: runner.os == 'macOS'
+        uses: actions/cache@v4
+        with:
+          path: |
+            ~/Library/Caches/electron
+            ~/Library/Caches/electron-builder
+          key: ${{ runner.os }}-electron-${{ hashFiles('client/package-lock.json') }}
+          restore-keys: |
+            ${{ runner.os }}-electron-
+
+      - name: Install dependencies
+        run: npm ci
+
+      - name: Install build type dependencies
+        run: npm install --no-save @types/plist
+
+      - name: Sync package version from tag
+        env:
+          TAG_NAME: ${{ inputs.tag_name || github.ref_name }}
+        run: |
+          VERSION="${TAG_NAME#v}"
+          npm version "$VERSION" --no-git-tag-version --allow-same-version
+
+      - name: Generate macOS icon
+        if: runner.os == 'macOS'
+        run: |
+          rm -rf assets/icon.iconset
+          mkdir -p assets/icon.iconset
+          sips -z 16 16 assets/icon_256.png --out assets/icon.iconset/icon_16x16.png
+          sips -z 32 32 assets/icon_256.png --out assets/icon.iconset/icon_16x16@2x.png
+          sips -z 32 32 assets/icon_256.png --out assets/icon.iconset/icon_32x32.png
+          sips -z 64 64 assets/icon_256.png --out assets/icon.iconset/icon_32x32@2x.png
+          sips -z 128 128 assets/icon_256.png --out assets/icon.iconset/icon_128x128.png
+          sips -z 256 256 assets/icon_256.png --out assets/icon.iconset/icon_128x128@2x.png
+          sips -z 256 256 assets/icon_256.png --out assets/icon.iconset/icon_256x256.png
+          sips -z 512 512 assets/icon_256.png --out assets/icon.iconset/icon_256x256@2x.png
+          sips -z 512 512 assets/icon_256.png --out assets/icon.iconset/icon_512x512.png
+          sips -z 1024 1024 assets/icon_256.png --out assets/icon.iconset/icon_512x512@2x.png
+          iconutil -c icns assets/icon.iconset -o assets/icon.icns
+
+      - name: Build renderer
+        run: npm run build
+
+      - name: Preload Electron macOS runtimes
+        if: runner.os == 'macOS'
+        run: |
+          export ELECTRON_CACHE="$HOME/Library/Caches/electron"
+          ELECTRON_VERSION="$(node -p "require('./node_modules/electron/package.json').version")"
+          cache_dir="$ELECTRON_CACHE"
+          mkdir -p "$cache_dir"
+
+          for arch in x64 arm64; do
+            file="$cache_dir/electron-v${ELECTRON_VERSION}-darwin-${arch}.zip"
+            if [ -f "$file" ] && unzip -tq "$file" >/dev/null 2>&1; then
+              echo "Electron ${ELECTRON_VERSION} darwin-${arch} already cached."
+              continue
+            fi
+
+            tmp="${file}.tmp"
+            rm -f "$file" "$tmp"
+            curl --fail --location --retry 5 --retry-all-errors --retry-delay 10 \
+              "https://github.com/electron/electron/releases/download/v${ELECTRON_VERSION}/electron-v${ELECTRON_VERSION}-darwin-${arch}.zip" \
+              --output "$tmp"
+            unzip -tq "$tmp" >/dev/null
+            mv "$tmp" "$file"
+          done
+
+      - name: Build Windows NSIS and ZIP artifacts
+        if: runner.os == 'Windows'
+        run: npx electron-builder --win nsis zip --publish never
+
+      - name: Build Windows MSI artifact
+        if: runner.os == 'Windows'
+        run: npx electron-builder --win msi --publish never -c.productName=OpenBidKit_Yibiao -c.extraMetadata.author=mark -c.copyright="Copyright (c) 2026 mark"
+
+      - name: Build and publish macOS artifacts
+        if: runner.os == 'macOS'
+        run: |
+          export ELECTRON_CACHE="$HOME/Library/Caches/electron"
+          export ELECTRON_BUILDER_CACHE="$HOME/Library/Caches/electron-builder"
+
+          for attempt in 1 2 3; do
+            echo "Build macOS artifacts, attempt ${attempt}/3."
+            if npx electron-builder --mac --publish never; then
+              exit 0
+            fi
+
+            if [ "$attempt" -eq 3 ]; then
+              exit 1
+            fi
+
+            sleep $((attempt * 20))
+          done
+
+      - name: Package macOS DMG with instructions
+        if: runner.os == 'macOS'
+        run: |
+          shopt -s nullglob
+          for dmg in release/*.dmg; do
+            base="$(basename "$dmg" .dmg)"
+            package_dir="release/${base}-package"
+            rm -rf "$package_dir"
+            mkdir -p "$package_dir"
+            cp "$dmg" "$package_dir/"
+            cat > "$package_dir/macOS使用说明.txt" <<'EOF'
+          macOS 使用说明
+
+          如果双击 App 提示“已损坏，无法打开”或“无法验证开发者”，这是因为本软件未进行 Apple 官方签名和公证，并不代表文件真的损坏。
+
+          使用步骤：
+
+          1. 双击 dmg 文件。
+          2. 将“易标投标工具箱.app”拖到“应用程序”文件夹。
+          3. 打开“终端”App。
+          4. 执行下面命令：
+
+          xattr -dr com.apple.quarantine /Applications/易标投标工具箱.app
+
+          5. 再从“应用程序”中打开“易标投标工具箱”。
+
+          如果仍无法打开，请右键点击 App，选择“打开”，再确认打开。
+          EOF
+            (cd release && ditto -c -k --sequesterRsrc --keepParent "$(basename "$package_dir")" "${base}-package.zip")
+            rm -rf "$package_dir"
+            rm -f "$dmg"
+          done
+
+      - name: Upload release assets
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+          TAG_NAME: ${{ inputs.tag_name || github.ref_name }}
+        run: |
+          shopt -s nullglob
+          files=(release/*.exe release/*.msi release/*.zip release/*.blockmap release/latest*.yml)
+          if [ ${#files[@]} -eq 0 ]; then
+            echo "No release assets found."
+            exit 1
+          fi
+          gh release upload "$TAG_NAME" "${files[@]}" --clobber

.gitignore

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+# 项目特定的忽略文件
+# ===================
+
+# 用户配置文件
+user_config.json
+config.json
+*.private.md
+
+# 上传文件目录
+uploads/
+*.docx
+*.pdf
+
+# 构建和打包相关
+dist/
+build/
+*.spec
+requirements_build.txt
+
+# 前端构建文件（保留源码，忽略构建产物）
+frontend/build/
+backend/static/
+client/release/
+
+# 临时和缓存文件
+*.tmp
+*.temp
+.DS_Store
+Thumbs.db
+
+# Node.js相关
+node_modules/
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*
+package-lock.json.backup
+
+# IDE和编辑器文件（根据需要调整）
+.vscode/settings.json
+.vscode/extensions.json
+# 保留launch.json和tasks.json用于项目配置
+
+# 原有的gitignore内容保持不变
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[codz]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+# *.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py.cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# UV
+#   Similar to Pipfile.lock, it is generally recommended to include uv.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#uv.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+#poetry.toml
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#   pdm recommends including project-wide configuration in pdm.toml, but excluding .pdm-python.
+#   https://pdm-project.org/en/latest/usage/project/#working-with-version-control
+#pdm.lock
+#pdm.toml
+.pdm-python
+.pdm-build/
+
+# pixi
+#   Similar to Pipfile.lock, it is generally recommended to include pixi.lock in version control.
+#pixi.lock
+#   Pixi creates a virtual environment in the .pixi directory, just like venv module creates one
+#   in the .venv directory. It is recommended not to include this directory in version control.
+.pixi
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.envrc
+.dev.vars
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/
+
+# Abstra
+# Abstra is an AI-powered process automation framework.
+# Ignore directories containing user credentials, local state, and settings.
+# Learn more at https://abstra.io/docs
+.abstra/
+
+# Visual Studio Code
+#  Visual Studio Code specific template is maintained in a separate VisualStudioCode.gitignore 
+#  that can be found at https://github.com/github/gitignore/blob/main/Global/VisualStudioCode.gitignore
+#  and can be added to the global gitignore or merged into this file. However, if you prefer, 
+#  you could uncomment the following to ignore the entire vscode folder
+# .vscode/
+
+# Ruff stuff:
+.ruff_cache/
+
+# Cloudflare Wrangler local state
+.wrangler/
+
+# PyPI configuration file
+.pypirc
+
+# Cursor
+#  Cursor is an AI-powered code editor. `.cursorignore` specifies files/directories to
+#  exclude from AI features like autocomplete and code analysis. Recommended for sensitive data
+#  refer to https://docs.cursor.com/context/ignore-files
+.cursorignore
+.cursorindexingignore
+
+# Marimo
+marimo/_static/
+marimo/_lsp/
+__marimo__/
+
+
+AGENTS.md
+
+tools/测试文件/
+tools/对比结果/

.vscode/launch.json

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+{
+    "version": "0.2.0",
+    "configurations": [
+        {
+            "name": "后端服务 (FastAPI)",
+            "type": "python",
+            "request": "launch",
+            "module": "uvicorn",
+            "args": [
+                "app.main:app",
+                "--host=127.0.0.1",
+                "--port=8000",
+                "--reload",
+                "--log-level=info"
+            ],
+            "console": "integratedTerminal",
+            "cwd": "${workspaceFolder}/backend",
+            "env": {
+                "PYTHONPATH": "${workspaceFolder}/backend"
+            }
+        },
+        {
+            "name": "前端服务 (React)",
+            "type": "node",
+            "request": "launch",
+            "runtimeExecutable": "npm",
+            "runtimeArgs": ["start"],
+            "console": "integratedTerminal",
+            "cwd": "${workspaceFolder}/frontend",
+            "env": {
+                "BROWSER": "none"
+            }
+        }
+    ],
+    "compounds": [
+        {
+            "name": "🚀 启动前后端项目",
+            "configurations": [
+                "后端服务 (FastAPI)",
+                "前端服务 (React)"
+            ],
+            "stopAll": true
+        }
+    ]
+}

.vscode/tasks.json

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+{
+    "version": "2.0.0",
+    "tasks": [
+        {
+            "label": "启动前端开发服务器",
+            "type": "shell",
+            "command": "npm",
+            "args": ["start"],
+            "options": {
+                "cwd": "${workspaceFolder}/frontend"
+            },
+            "group": {
+                "kind": "build",
+                "isDefault": false
+            },
+            "presentation": {
+                "echo": true,
+                "reveal": "always",
+                "focus": false,
+                "panel": "new",
+                "showReuseMessage": true,
+                "clear": false
+            },
+
+            "isBackground": true,
+            "problemMatcher": {
+                "owner": "webpack",
+                "source": "webpack",
+                "fileLocation": "relative",
+                "pattern": {
+                    "regexp": "ERROR in (.*)",
+                    "file": 1
+                },
+                "background": {
+                    "activeOnStart": true,
+                    "beginsPattern": ".*webpack.*",
+                    "endsPattern": ".*compiled.*"
+                }
+            }
+        },
+        {
+            "label": "构建前端",
+            "type": "shell", 
+            "command": "npm",
+            "args": ["run", "build"],
+            "options": {
+                "cwd": "${workspaceFolder}/frontend"
+            },
+            "group": {
+                "kind": "build",
+                "isDefault": true
+            },
+            "presentation": {
+                "echo": true,
+                "reveal": "always",
+                "focus": false,
+                "panel": "shared",
+                "showReuseMessage": true,
+                "clear": false
+            }
+        },
+        {
+            "label": "复制前端构建到后端",
+            "type": "shell",
+            "command": "python",
+            "args": [
+                "-c", 
+                "import shutil; shutil.copytree('frontend/build', 'backend/static', dirs_exist_ok=True); print('前端构建文件已复制到backend/static')"
+            ],
+            "options": {
+                "cwd": "${workspaceFolder}"
+            },
+            "group": "build",
+            "dependsOn": "构建前端"
+        },
+        {
+            "label": "完整构建流程",
+            "dependsOrder": "sequence",
+            "dependsOn": [
+                "构建前端",
+                "复制前端构建到后端"
+            ]
+        }
+    ]
+}

LICENSE

@@ -0,0 +1,661 @@
+                    GNU AFFERO GENERAL PUBLIC LICENSE
+                       Version 3, 19 November 2007
+
+ Copyright (C) 2007 Free Software Foundation, Inc. <https://fsf.org/>
+ Everyone is permitted to copy and distribute verbatim copies
+ of this license document, but changing it is not allowed.
+
+                            Preamble
+
+  The GNU Affero General Public License is a free, copyleft license for
+software and other kinds of works, specifically designed to ensure
+cooperation with the community in the case of network server software.
+
+  The licenses for most software and other practical works are designed
+to take away your freedom to share and change the works.  By contrast,
+our General Public Licenses are intended to guarantee your freedom to
+share and change all versions of a program--to make sure it remains free
+software for all its users.
+
+  When we speak of free software, we are referring to freedom, not
+price.  Our General Public Licenses are designed to make sure that you
+have the freedom to distribute copies of free software (and charge for
+them if you wish), that you receive source code or can get it if you
+want it, that you can change the software or use pieces of it in new
+free programs, and that you know you can do these things.
+
+  Developers that use our General Public Licenses protect your rights
+with two steps: (1) assert copyright on the software, and (2) offer
+you this License which gives you legal permission to copy, distribute
+and/or modify the software.
+
+  A secondary benefit of defending all users' freedom is that
+improvements made in alternate versions of the program, if they
+receive widespread use, become available for other developers to
+incorporate.  Many developers of free software are heartened and
+encouraged by the resulting cooperation.  However, in the case of
+software used on network servers, this result may fail to come about.
+The GNU General Public License permits making a modified version and
+letting the public access it on a server without ever releasing its
+source code to the public.
+
+  The GNU Affero General Public License is designed specifically to
+ensure that, in such cases, the modified source code becomes available
+to the community.  It requires the operator of a network server to
+provide the source code of the modified version running there to the
+users of that server.  Therefore, public use of a modified version, on
+a publicly accessible server, gives the public access to the source
+code of the modified version.
+
+  An older license, called the Affero General Public License and
+published by Affero, was designed to accomplish similar goals.  This is
+a different license, not a version of the Affero GPL, but Affero has
+released a new version of the Affero GPL which permits relicensing under
+this license.
+
+  The precise terms and conditions for copying, distribution and
+modification follow.
+
+                       TERMS AND CONDITIONS
+
+  0. Definitions.
+
+  "This License" refers to version 3 of the GNU Affero General Public License.
+
+  "Copyright" also means copyright-like laws that apply to other kinds of
+works, such as semiconductor masks.
+
+  "The Program" refers to any copyrightable work licensed under this
+License.  Each licensee is addressed as "you".  "Licensees" and
+"recipients" may be individuals or organizations.
+
+  To "modify" a work means to copy from or adapt all or part of the work
+in a fashion requiring copyright permission, other than the making of an
+exact copy.  The resulting work is called a "modified version" of the
+earlier work or a work "based on" the earlier work.
+
+  A "covered work" means either the unmodified Program or a work based
+on the Program.
+
+  To "propagate" a work means to do anything with it that, without
+permission, would make you directly or secondarily liable for
+infringement under applicable copyright law, except executing it on a
+computer or modifying a private copy.  Propagation includes copying,
+distribution (with or without modification), making available to the
+public, and in some countries other activities as well.
+
+  To "convey" a work means any kind of propagation that enables other
+parties to make or receive copies.  Mere interaction with a user through
+a computer network, with no transfer of a copy, is not conveying.
+
+  An interactive user interface displays "Appropriate Legal Notices"
+to the extent that it includes a convenient and prominently visible
+feature that (1) displays an appropriate copyright notice, and (2)
+tells the user that there is no warranty for the work (except to the
+extent that warranties are provided), that licensees may convey the
+work under this License, and how to view a copy of this License.  If
+the interface presents a list of user commands or options, such as a
+menu, a prominent item in the list meets this criterion.
+
+  1. Source Code.
+
+  The "source code" for a work means the preferred form of the work
+for making modifications to it.  "Object code" means any non-source
+form of a work.
+
+  A "Standard Interface" means an interface that either is an official
+standard defined by a recognized standards body, or, in the case of
+interfaces specified for a particular programming language, one that
+is widely used among developers working in that language.
+
+  The "System Libraries" of an executable work include anything, other
+than the work as a whole, that (a) is included in the normal form of
+packaging a Major Component, but which is not part of that Major
+Component, and (b) serves only to enable use of the work with that
+Major Component, or to implement a Standard Interface for which an
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NOTICE

@@ -0,0 +1,52 @@
+OpenBidKit / 易标投标工具箱
+
+中文声明
+
+原始仓库:
+https://github.com/FB208/OpenBidKit_Yibiao
+
+作者:
+mark / yibiaoai
+
+微信公众号:
+生产力Mark
+
+联系邮箱:
+fb208@outlook.com
+
+版权声明:
+Copyright (C) 2025-2026 mark / yibiaoai
+
+许可证:
+GNU Affero General Public License v3.0 only
+
+本项目基于 GNU Affero General Public License v3.0 授权。
+本 NOTICE 文件中的归属信息属于 GNU Affero General Public License v3.0
+第 7(b) 条下要求保留的作者归属声明，在重新分发的副本、修改版本和
+对应源代码中均必须保留。
+
+English Notice
+
+Original repository:
+https://github.com/FB208/OpenBidKit_Yibiao
+
+Author:
+mark / yibiaoai
+
+WeChat official account:
+生产力Mark
+
+Contact:
+fb208@outlook.com
+
+Copyright:
+Copyright (C) 2025-2026 mark / yibiaoai
+
+License:
+GNU Affero General Public License v3.0 only
+
+This project is licensed under the GNU Affero General Public License v3.0.
+The attribution information in this NOTICE file is a required author
+attribution notice under Section 7(b) of the GNU Affero General Public
+License v3.0 and must be preserved in redistributed copies, modified
+versions, and corresponding source code.

README.en.md

@@ -0,0 +1,171 @@
+# OpenBidKit Yibiao - Open-Source AI Bid Proposal Writing Assistant
+
+<p align="center">
+  <a href="./README.md">简体中文</a> | <strong>English</strong>
+</p>
+
+<p align="center">
+  <img src="https://img.shields.io/badge/Electron-41+-47848f.svg" alt="Electron">
+  <img src="https://img.shields.io/badge/React-19+-61dafb.svg" alt="React">
+  <img src="https://img.shields.io/badge/TypeScript-5.9+-3178c6.svg" alt="TypeScript">
+  <img src="https://img.shields.io/badge/Vite-7+-646cff.svg" alt="Vite">
+</p>
+
+<p align="left">
+  <strong>🚀 An out-of-the-box open-source AI bid proposal writing tool for AI proposal writing, bid AI, AI bid generation, and technical proposal drafting.</strong>
+  <br>
+  Yibiao Bid Toolbox is an intelligent bid document creation tool for tendering and bidding workflows. It is designed for proposal writers, presales engineers, project managers, and bid teams. The product covers the full workflow from importing tender documents to exporting editable Word proposals, including tender document parsing, scoring-point extraction, proposal outline generation, technical proposal drafting, expansion and rewriting, knowledge base reuse, duplicate-check workspace, and rejection-risk checklist workspace.
+  <br>
+  If you are looking for an AI proposal writing tool, bid AI assistant, AI bid generation software, tender response generator, or technical proposal drafting assistant, Yibiao can be used as an open-source reference to improve proposal writing efficiency and reduce repetitive writing, manual scoring-point organization, and rejection-risk checking costs.
+</p>
+
+## 🌐 Official Website
+
+**Online Experience**: [https://yibiao.pro](https://yibiao.pro)
+
+Visit the website for product information, online demos, and support.
+
+> **Ad Slot · Partnership**
+>
+> **Looking for an API relay provider that supports image-and-text APIs~~~**
+>
+> Image generation / multimodal models / OpenAI-like APIs are welcome for integration.
+
+<h2 align="center">✨ Features & Advantages</h2>
+
+<p align="center">
+  <strong>AI Proposal Writing · Bid AI · AI Bid Generation · Technical Proposal Drafting · Tender Response Generation</strong><br>
+  <sub>More than proposal draft generation: open-source control, local workspace, reusable knowledge, visual expression, and recoverable workflows.</sub>
+</p>
+
+<table>
+  <tr>
+    <td width="33%" valign="top">
+      <strong>🧩 Open Source & Controllable</strong><br>
+      An open-source AI bid proposal project that can be self-hosted, customized, and adapted to team workflows.
+    </td>
+    <td width="33%" valign="top">
+      <strong>💻 Local Desktop Workspace</strong><br>
+      Configurations, caches, and generated results are stored locally, suitable for Windows bid-document workflows.
+    </td>
+    <td width="33%" valign="top">
+      <strong>📄 Multiple Parsing Options</strong><br>
+      Supports local parsing and MinerU parser configuration for both regular documents and more complex files.
+    </td>
+  </tr>
+  <tr>
+    <td width="33%" valign="top">
+      <strong>📚 Knowledge Base Reuse</strong><br>
+      Store company materials, historical cases, and proposal assets so bid AI output better matches your business context.
+    </td>
+    <td width="33%" valign="top">
+      <strong>🧩 Images & Diagrams</strong><br>
+      Supports Mermaid preview, generated illustrations, and diagram conversion for Word export.
+    </td>
+    <td width="33%" valign="top">
+      <strong>🔄 Background Task Recovery</strong><br>
+      Long-running parsing and generation tasks are persisted, so progress can be restored after switching pages.
+    </td>
+  </tr>
+  <tr>
+    <td width="33%" valign="top">
+      <strong>🛡️ Risk Check Workspaces</strong><br>
+      Duplicate-check and rejection-risk checklist workspaces are reserved for repeated wording and response-completeness checks.
+    </td>
+    <td width="33%" valign="top">
+      <strong>⚙️ Custom AI Configuration</strong><br>
+      Configure text models, image models, and file parsing providers to fit your team's preferred stack.
+    </td>
+    <td width="33%" valign="top">
+      <strong>✏️ Editable Workflow</strong><br>
+      Outlines, generated content, and expansion results remain editable for human review and final polishing.
+    </td>
+  </tr>
+</table>
+
+## 📦 Download & Usage
+
+### ⬇️ Download
+
+Download the latest release from [GitHub Releases](https://github.com/yibiaoai/yibiao-simple/releases), then run the installer or executable file.
+
+### 🎬 Usage Demo
+
+<a href="https://www.youtube.com/watch?v=9id3AJBQz8U">
+  <img src="./screenshots/new_home.png" alt="Yibiao usage demo video" width="100%">
+</a>
+
+[Watch the usage demo on YouTube](https://www.youtube.com/watch?v=9id3AJBQz8U)
+
+## 🛠️ Technical Architecture
+
+The current product is an independent desktop client under `client/`. It does not depend on the legacy `frontend/` or `backend/` structure.
+
+- **Desktop**: Electron Main / Preload provides local file access, configuration, export, and background task capabilities.
+- **Renderer**: Vite + React + TypeScript, with global CSS and Radix UI primitives.
+- **Features**: Technical proposal, knowledge base, duplicate-check workspace, rejection-risk checklist workspace, and settings.
+- **Local Data**: Configuration, workspace data, and generated caches are stored under Electron `userData`.
+- **Packaging**: Built for Windows / macOS with electron-builder.
+
+### 🏗️ Project Structure
+
+```
+Yibiao Bid Toolbox/
+├── client/                    # Current desktop client
+│   ├── electron/              # Main, Preload, IPC, and local services
+│   ├── src/                   # Renderer source code
+│   │   ├── app/               # Routing, menu, and providers
+│   │   ├── features/          # Technical proposal, knowledge base, and other modules
+│   │   └── shared/            # Shared types, AI helpers, UI, and utilities
+│   ├── assets/                # Icons and static assets
+│   └── package.json           # Client dependencies and packaging config
+├── analytics/                 # Independent analytics service
+├── tools/                     # Independent document parsing and MinerU validation tools
+└── README.md                  # Chinese README
+```
+
+## 🤝 Contributing
+
+Contributions are welcome.
+
+1. **🐛 Bug Reports**: Report bugs in [Issues](https://github.com/yibiaoai/yibiao-simple/issues).
+2. **💡 Feature Requests**: Suggest new features and improvements.
+3. **🔧 Code Contributions**: Fork the repository and submit a pull request.
+4. **📖 Documentation**: Help improve documentation and usage guides.
+
+## 📄 License
+
+This project is released under the [GNU Affero General Public License v3.0](LICENSE).
+
+You may use, modify, distribute, and commercialize this project, but modified versions, redistributed copies, and network-accessible services must comply with the AGPL-3.0 source-sharing obligations and preserve the [NOTICE](NOTICE) attribution notice, original repository link, and author information.
+
+## 🙋‍♂️ Contact
+
+- **Official Website**: [https://yibiao.pro](https://yibiao.pro)
+- **Feedback**: [GitHub Issues](https://github.com/yibiaoai/yibiao-simple/issues)
+- **Email**: support@yibiao.pro
+
+<p>
+  <strong>WeCom</strong><br>
+  <img src="./screenshots/企业微信.png" alt="WeCom QR code" width="180">
+</p>
+
+## Star History
+
+<a href="https://www.star-history.com/?repos=FB208%2FOpenBidKit_Yibiao&type=timeline&legend=top-left">
+ <picture>
+   <source media="(prefers-color-scheme: dark)" srcset="https://api.star-history.com/chart?repos=FB208/OpenBidKit_Yibiao&type=timeline&theme=dark&legend=top-left" />
+   <source media="(prefers-color-scheme: light)" srcset="https://api.star-history.com/chart?repos=FB208/OpenBidKit_Yibiao&type=timeline&legend=top-left" />
+   <img alt="Star History Chart" src="https://api.star-history.com/chart?repos=FB208/OpenBidKit_Yibiao&type=timeline&legend=top-left" />
+ </picture>
+</a>
+
+---
+
+<p align="center">
+  ⭐ If this project helps you, please give it a Star.
+</p>
+
+<p align="center">
+  Made with ❤️ by the Yibiao Team
+</p>

README.md

@@ -1,92 +1,178 @@
-# biaoshu-ai
-
-
-
-## Getting started
-
-To make it easy for you to get started with GitLab, here's a list of recommended next steps.
-
-Already a pro? Just edit this README.md and make it your own. Want to make it easy? [Use the template at the bottom](#editing-this-readme)!
-
-## Add your files
-
-- [ ] [Create](https://docs.gitlab.com/ee/user/project/repository/web_editor.html#create-a-file) or [upload](https://docs.gitlab.com/ee/user/project/repository/web_editor.html#upload-a-file) files
-- [ ] [Add files using the command line](https://docs.gitlab.com/ee/gitlab-basics/add-file.html#add-a-file-using-the-command-line) or push an existing Git repository with the following command:
+# 易标投标工具箱 - AI智能标书写作助手
+
+<p align="center">
+  <strong>简体中文</strong> | <a href="./README.en.md">English</a>
+</p>
+
+<p align="center">
+  <img src="https://img.shields.io/badge/Electron-41+-47848f.svg" alt="Electron">
+  <img src="https://img.shields.io/badge/React-19+-61dafb.svg" alt="React">
+  <img src="https://img.shields.io/badge/TypeScript-5.9+-3178c6.svg" alt="TypeScript">
+  <img src="https://img.shields.io/badge/Vite-7+-646cff.svg" alt="Vite">
+</p>
+
+
+<p align="left">
+  <strong>🚀 开箱即用的开源AI标书编写工具，专注 AI写标书、标书AI、AI标书生成和技术标编写</strong>
+  <br>
+  易标投标工具箱是一款面向招投标场景的智能标书制作工具，适合标书人员、售前工程师、项目经理和投标团队使用。项目围绕“上传招标文件到导出 Word 标书”的完整流程，提供招标文件解析、评分点提取、标书目录生成、技术方案正文生成、内容扩写改写、知识库素材复用、标书查重、废标项检查等能力，帮助用户更快完成结构完整、响应清晰、可继续编辑的投标方案、技术标和标书初稿。
+  <br>
+  如果你正在寻找 AI写标书 工具、标书AI 助手、AI标书 生成软件、投标文件生成工具或技术标编写助手，易标可以作为开源方案参考，用于提升标书制作效率，减少重复编写、人工整理评分点和检查废标风险的时间成本。
+</p>
+
+## 🌐 官方网站
+
+**在线体验**: [https://yibiao.pro](https://yibiao.pro)
+
+获取更多产品信息、在线体验和技术支持。
+
+> **广告位 · 合作招募**
+>
+> **有没有支持图文API的中转站合作下呀~~~**
+>
+> 支持生图 / 图文模型 / OpenAI Like API，欢迎合作接入。
+
+
+<h2 align="center">✨ 核心功能与优势</h2>
+
+<p align="center">
+  <strong>AI写标书 · 标书AI · AI标书生成 · 技术标编写 · 投标文件生成</strong><br>
+  <sub>不止生成标书初稿，更强调开源可控、本地工作区、素材复用、图文表达和流程可恢复。</sub>
+</p>
+
+<table>
+  <tr>
+    <td width="33%" valign="top">
+      <strong>🧩 开源可控</strong><br>
+      开源 AI标书 项目，可自行部署、二次开发和适配团队流程。
+    </td>
+    <td width="33%" valign="top">
+      <strong>💻 本地桌面工作区</strong><br>
+      配置、缓存和生成结果保存在本机，适合 Windows 标书文件处理。
+    </td>
+    <td width="33%" valign="top">
+      <strong>📄 多方式文档解析</strong><br>
+      支持本地解析与 MinerU 解析配置，兼顾常规文档和复杂文件。
+    </td>
+  </tr>
+  <tr>
+    <td width="33%" valign="top">
+      <strong>📚 知识库复用</strong><br>
+      沉淀企业资料、历史案例和方案素材，让标书AI更贴合业务。
+    </td>
+    <td width="33%" valign="top">
+      <strong>🧩 图文与图表</strong><br>
+      支持 Mermaid 预览、正文配图和图表转 Word，增强方案表达。
+    </td>
+    <td width="33%" valign="top">
+      <strong>🔄 后台任务恢复</strong><br>
+      解析、生成等耗时任务持续落盘，切换页面后仍可恢复进度。
+    </td>
+  </tr>
+  <tr>
+    <td width="33%" valign="top">
+      <strong>🛡️ 风险检查入口</strong><br>
+      预留标书查重、废标项检查工作区，聚焦重复表达和响应完整性。
+    </td>
+    <td width="33%" valign="top">
+      <strong>⚙️ 自定义AI配置</strong><br>
+      支持文本模型、生图模型和文件解析方式配置，适配团队习惯。
+    </td>
+    <td width="33%" valign="top">
+      <strong>✏️ 可编辑工作流</strong><br>
+      目录、正文和扩写结果可持续调整，方便 AI写标书 后人工定稿。
+    </td>
+  </tr>
+</table>
+
+
+
+## 📦 下载与使用
+
+### ⬇️ 下载方式
+
+从 [GitHub Releases](https://github.com/yibiaoai/yibiao-simple/releases) 下载最新版本，运行安装包或可执行文件即可启动。
+
+### 🎬 使用方式
+
+<a href="https://www.bilibili.com/video/BV1sC5i6SE74">
+  <img src="./screenshots/new_home.png" alt="易标使用演示视频" width="100%">
+</a>
+
+[点击前往 Bilibili 观看使用演示视频](https://www.bilibili.com/video/BV1sC5i6SE74)
+
+## 🛠️ 技术架构
+
+当前产品主体是 `client/` 下的独立桌面客户端，不依赖旧 `frontend/`、`backend/` 结构。
+
+- **桌面端**：Electron Main / Preload 提供本地文件、配置、导出和后台任务能力
+- **界面层**：Vite + React + TypeScript，使用全局 CSS 和 Radix UI 基础组件
+- **业务模块**：技术方案、知识库、标书查重、废标项检查、设置页
+- **本地数据**：配置、工作区、生成缓存保存在 Electron `userData` 目录
+- **打包发布**：使用 electron-builder 构建 Windows / macOS 客户端
+
+### 🏗️ 项目结构
 
 ```
-cd existing_repo
-git remote add origin https://www.gitcc.com/matcha/biaoshu-ai.git
-git branch -M main
-git push -uf origin main
+易标投标工具箱/
+├── client/                    # 当前桌面客户端主体
+│   ├── electron/              # Main、Preload、IPC、本地服务
+│   ├── src/                   # Renderer 应用源码
+│   │   ├── app/               # 路由、菜单、Provider
+│   │   ├── features/          # 技术方案、知识库等业务模块
+│   │   └── shared/            # 通用类型、AI、UI、工具函数
+│   ├── assets/                # 图标与静态资源
+│   └── package.json           # 客户端依赖和打包配置
+├── analytics/                 # 独立埋点服务
+├── tools/                     # 独立文档解析与 MinerU 验证工具
+└── README.md                  # 项目文档
 ```
 
-## Integrate with your tools
-
-- [ ] [Set up project integrations](https://www.gitcc.com/matcha/biaoshu-ai/-/settings/integrations)
-
-## Collaborate with your team
-
-- [ ] [Invite team members and collaborators](https://docs.gitlab.com/ee/user/project/members/)
-- [ ] [Create a new merge request](https://docs.gitlab.com/ee/user/project/merge_requests/creating_merge_requests.html)
-- [ ] [Automatically close issues from merge requests](https://docs.gitlab.com/ee/user/project/issues/managing_issues.html#closing-issues-automatically)
-- [ ] [Enable merge request approvals](https://docs.gitlab.com/ee/user/project/merge_requests/approvals/)
-- [ ] [Set auto-merge](https://docs.gitlab.com/ee/user/project/merge_requests/merge_when_pipeline_succeeds.html)
-
-## Test and Deploy
-
-Use the built-in continuous integration in GitLab.
-
-- [ ] [Get started with GitLab CI/CD](https://docs.gitlab.com/ee/ci/quick_start/index.html)
-- [ ] [Analyze your code for known vulnerabilities with Static Application Security Testing(SAST)](https://docs.gitlab.com/ee/user/application_security/sast/)
-- [ ] [Deploy to Kubernetes, Amazon EC2, or Amazon ECS using Auto Deploy](https://docs.gitlab.com/ee/topics/autodevops/requirements.html)
-- [ ] [Use pull-based deployments for improved Kubernetes management](https://docs.gitlab.com/ee/user/clusters/agent/)
-- [ ] [Set up protected environments](https://docs.gitlab.com/ee/ci/environments/protected_environments.html)
-
-***
-
-# Editing this README
+## 🤝 贡献指南
 
-When you're ready to make this README your own, just edit this file and use the handy template below (or feel free to structure it however you want - this is just a starting point!). Thank you to [makeareadme.com](https://www.makeareadme.com/) for this template.
+欢迎各种形式的贡献！
 
-## Suggestions for a good README
-Every project is different, so consider which of these sections apply to yours. The sections used in the template are suggestions for most open source projects. Also keep in mind that while a README can be too long and detailed, too long is better than too short. If you think your README is too long, consider utilizing another form of documentation rather than cutting out information.
+1. **🐛 问题反馈**: 在 [Issues](https://github.com/yibiaoai/yibiao-simple/issues) 中报告bug
+2. **💡 功能建议**: 提出新功能需求和改进建议  
+3. **🔧 代码贡献**: Fork项目，提交Pull Request
+4. **📖 文档完善**: 帮助改进文档和使用说明
 
-## Name
-Choose a self-explaining name for your project.
 
-## Description
-Let people know what your project can do specifically. Provide context and add a link to any reference visitors might be unfamiliar with. A list of Features or a Background subsection can also be added here. If there are alternatives to your project, this is a good place to list differentiating factors.
+## 📄 许可证
 
-## Badges
-On some READMEs, you may see small images that convey metadata, such as whether or not all the tests are passing for the project. You can use Shields to add some to your README. Many services also have instructions for adding a badge.
+本项目基于 [GNU Affero General Public License v3.0](LICENSE) 开源协议发布。
 
-## Visuals
-Depending on what you are making, it can be a good idea to include screenshots or even a video (you'll frequently see GIFs rather than actual videos). Tools like ttygif can help, but check out Asciinema for a more sophisticated method.
+你可以自由使用、修改、分发和商用本项目，但修改版、分发版和通过网络提供服务的版本必须遵守 AGPL-3.0 的开源义务，并保留本项目的 [NOTICE](NOTICE) 归属声明、原始仓库链接和作者信息。
 
-## Installation
-Within a particular ecosystem, there may be a common way of installing things, such as using Yarn, NuGet, or Homebrew. However, consider the possibility that whoever is reading your README is a novice and would like more guidance. Listing specific steps helps remove ambiguity and gets people to using your project as quickly as possible. If it only runs in a specific context like a particular programming language version or operating system or has dependencies that have to be installed manually, also add a Requirements subsection.
+## 🙋‍♂️ 联系我们
 
-## Usage
-Use examples liberally, and show the expected output if you can. It's helpful to have inline the smallest example of usage that you can demonstrate, while providing links to more sophisticated examples if they are too long to reasonably include in the README.
+- **官方网站**: [https://yibiao.pro](https://yibiao.pro)
+- **问题反馈**: [GitHub Issues](https://github.com/yibiaoai/yibiao-simple/issues)
+- **邮箱联系**: support@yibiao.pro
 
-## Support
-Tell people where they can go to for help. It can be any combination of an issue tracker, a chat room, an email address, etc.
+<p>
+  <strong>企业微信</strong><br>
+  <img src="./screenshots/企业微信.png" alt="企业微信二维码" width="180">
+</p>
 
-## Roadmap
-If you have ideas for releases in the future, it is a good idea to list them in the README.
+## Star History
 
-## Contributing
-State if you are open to contributions and what your requirements are for accepting them.
+<a href="https://www.star-history.com/?repos=FB208%2FOpenBidKit_Yibiao&type=timeline&legend=top-left">
+ <picture>
+   <source media="(prefers-color-scheme: dark)" srcset="https://api.star-history.com/chart?repos=FB208/OpenBidKit_Yibiao&type=timeline&theme=dark&legend=top-left" />
+   <source media="(prefers-color-scheme: light)" srcset="https://api.star-history.com/chart?repos=FB208/OpenBidKit_Yibiao&type=timeline&legend=top-left" />
+   <img alt="Star History Chart" src="https://api.star-history.com/chart?repos=FB208/OpenBidKit_Yibiao&type=timeline&legend=top-left" />
+ </picture>
+</a>
 
-For people who want to make changes to your project, it's helpful to have some documentation on how to get started. Perhaps there is a script that they should run or some environment variables that they need to set. Make these steps explicit. These instructions could also be useful to your future self.
+---
 
-You can also document commands to lint the code or run tests. These steps help to ensure high code quality and reduce the likelihood that the changes inadvertently break something. Having instructions for running tests is especially helpful if it requires external setup, such as starting a Selenium server for testing in a browser.
+<p align="center">
+  ⭐ 如果这个项目对您有帮助，请给我们一个Star支持！
+</p>
 
-## Authors and acknowledgment
-Show your appreciation to those who have contributed to the project.
 
-## License
-For open source projects, say how it is licensed.
 
-## Project status
-If you have run out of energy or time for your project, put a note at the top of the README saying that development has slowed down or stopped completely. Someone may choose to fork your project or volunteer to step in as a maintainer or owner, allowing your project to keep going. You can also make an explicit request for maintainers.
+<p align="center">
+  Made with ❤️ by 易标团队 
+</p>

analytics/README.md

@@ -0,0 +1,372 @@
+# 埋点统计部署手册
+
+本目录维护通用匿名埋点统计服务，采用 `Cloudflare Workers + Analytics Engine + Workers Static Assets`。
+
+公开仓库只保存源码，不保存 `ACCOUNT_ID`、`ADMIN_TOKEN`、`ANALYTICS_API_TOKEN` 等密钥。
+
+## 一、使用说明
+
+服务地址：
+
+| 项目 | 地址 |
+| --- | --- |
+| API 地址 | `https://analytics.agnet.top` |
+| 统计页面地址 | `https://static.analytics.agnet.top` |
+
+目录结构：
+
+```text
+analytics/
+  worker/      # 上报与查询 API Worker
+  dashboard/   # 统计看板 Worker Static Assets
+```
+
+`worker/src/` 采用模块化结构：`index.js` 只负责路由分发，`routes/` 放接口处理，`services/` 放 Analytics Engine 与 KV 访问，`http.js`、`utils.js`、`constants.js` 放公共能力。
+
+`dashboard/public/` 是无需构建的静态看板：`index.html` 负责页面骨架，`styles.css` 负责样式，`src/` 下使用原生 ES Module 拆分 API、渲染、标签页和各标签页逻辑。
+
+核心接口：
+
+| 接口 | 用途 | 鉴权 |
+| --- | --- | --- |
+| `GET /health` | 检查 API Worker | 无 |
+| `POST /track` | 上报埋点 | 无 |
+| `GET /notice` | 客户端读取最新公告 | 无 |
+| `GET /api/projects` | 查询最近 90 天出现过的项目名 | `ADMIN_TOKEN` |
+| `GET /api/summary` | 查询每日统计、页面排行、版本分布 | `ADMIN_TOKEN` |
+| `GET /api/latest` | 查询最近事件 | `ADMIN_TOKEN` |
+| `GET /api/notice` | 读取当前项目公告 | `ADMIN_TOKEN` |
+| `POST /api/notice` | 发布或更新当前项目公告 | `ADMIN_TOKEN` |
+| `DELETE /api/notice` | 停用当前项目公告 | `ADMIN_TOKEN` |
+
+事件类型：
+
+| event | 说明 | page 是否必填 |
+| --- | --- | --- |
+| `app_open` | 应用打开 | 否 |
+| `page_view` | 页面访问 | 是 |
+| `config_usage` | 配置使用快照 | 否 |
+| `ai_request` | AI 接口请求 | 否 |
+
+`ai_request` 只统计模型名称和请求类型，不采集 API Key、Base URL、Prompt、响应内容或错误详情。
+
+统计页面使用：
+
+1. 打开 `https://static.analytics.agnet.top`。
+2. API 地址填写 `https://analytics.agnet.top`。
+3. 输入 Worker Secret 中配置的 `ADMIN_TOKEN`。
+4. 输入项目名，例如 `yibiao-client`。
+5. 点击“刷新”。
+6. 如需发布客户端公告，在“公告管理”中填写标题和 Markdown 内容后点击“发布公告”。
+
+## 二、首次部署
+
+### 1. 启用 Analytics Engine
+
+1. 登录 Cloudflare Dashboard。
+2. 进入 `存储和数据库 -> Analytics Engine`。
+3. 点击 `Enable`。
+
+Dataset 不需要手动创建，第一次写入后会自动创建 `agnet_analytics`。
+
+### 1.1 创建公告 KV
+
+客户端公告保存到 Cloudflare KV，绑定名固定为 `NOTICE_STORE`。
+
+KV namespace 只需要创建一次。自动创建要求执行脚本的环境具备 Cloudflare 凭据：
+
+| 变量 | 说明 |
+| --- | --- |
+| `CLOUDFLARE_API_TOKEN` | 需要具备 Workers KV namespace 读写和 Worker 部署权限 |
+| `CLOUDFLARE_ACCOUNT_ID` | Cloudflare Account ID，避免 Wrangler 在非交互环境选择账号 |
+
+`analytics/worker` 部署前会检查 `wrangler.jsonc` 是否已经配置 `NOTICE_STORE`。已配置时直接部署；未配置时才运行 `setup:notice-kv`，创建或复用已有 KV namespace，并把 id 写入本次部署使用的 `wrangler.jsonc`。
+
+本地首次启用时，也可以在登录 Wrangler 后手动运行：
+
+```powershell
+cd analytics\worker
+npm run setup:notice-kv
+```
+
+脚本会优先查询并复用现有 namespace；不存在时才执行 `wrangler kv namespace create NOTICE_STORE`，并把 namespace id 写入 `analytics/worker/wrangler.jsonc` 的 `kv_namespaces`。
+
+如果需要手动配置，也可以运行：
+
+```powershell
+cd analytics\worker
+npx wrangler kv namespace create NOTICE_STORE
+```
+
+然后在 `analytics/worker/wrangler.jsonc` 中加入：
+
+```jsonc
+"kv_namespaces": [
+  {
+    "binding": "NOTICE_STORE",
+    "id": "<上一步输出的 namespace id>"
+  }
+]
+```
+
+### 2. 创建 Analytics API Token
+
+1. 进入 Cloudflare `My Profile -> API Tokens`。
+2. 点击 `Create Token`。
+3. 选择 `Create Custom Token`。
+4. 权限选择 `Account -> Account Analytics -> Read`。
+5. Account Resources 选择当前账号。
+6. 创建后复制 Token，后续配置为 Worker Secret `ANALYTICS_API_TOKEN`。
+
+### 3. 部署 API Worker
+
+在 Cloudflare 创建 Worker，并连接当前 GitHub 仓库。
+
+配置：
+
+| 项目 | 值 |
+| --- | --- |
+| Worker 名称 | `agnet-analytics-api` |
+| Root directory | `analytics/worker` |
+| Build command | `npm install` |
+| Deploy command | `npm run deploy` |
+
+`analytics/worker/wrangler.jsonc` 已包含：
+
+| 配置 | 值 |
+| --- | --- |
+| 自定义域名 | `analytics.agnet.top` |
+| Analytics Engine binding | `ANALYTICS` |
+| Analytics Engine dataset | `agnet_analytics` |
+| 公告 KV binding | `NOTICE_STORE`（首次部署时创建或复用） |
+| 变量保留 | `keep_vars: true`，避免部署覆盖后台配置 |
+
+部署后在 Worker 的 `Settings -> Variables and Secrets` 配置 Secret：
+
+| Secret | 说明 |
+| --- | --- |
+| `ACCOUNT_ID` | Cloudflare Account ID |
+| `ADMIN_TOKEN` | 统计看板查询密码 |
+| `ANALYTICS_API_TOKEN` | 上一步创建的 API Token |
+
+注意：不要在 `wrangler.jsonc` 里声明 `secrets.required`。首次 GitHub 部署时 Secret 还没配置，Wrangler 会在部署前校验并失败。正确流程是先部署 Worker，再到 Cloudflare 后台配置这些 Secret，然后重新部署或直接访问验证。
+
+确认绑定：
+
+1. 进入 Worker `agnet-analytics-api`。
+2. 打开 `Settings -> Bindings`。
+3. 确认存在 `ANALYTICS -> Analytics Engine -> agnet_analytics`。
+4. 如不存在，手动添加同名绑定。
+
+验证：
+
+```powershell
+Invoke-RestMethod -Uri "https://analytics.agnet.top/health"
+```
+
+### 4. 部署统计看板 Worker
+
+统计看板使用 Workers Static Assets，同样创建 Worker 并连接当前 GitHub 仓库。
+
+配置：
+
+| 项目 | 值 |
+| --- | --- |
+| Worker 名称 | `agnet-analytics-dashboard` |
+| Root directory | `analytics/dashboard` |
+| Build command | `npm install` |
+| Deploy command | `npm run deploy` |
+
+`analytics/dashboard/wrangler.jsonc` 已包含：
+
+| 配置 | 值 |
+| --- | --- |
+| 自定义域名 | `static.analytics.agnet.top` |
+| 静态资源目录 | `./public` |
+
+部署后访问：
+
+```text
+https://static.analytics.agnet.top
+```
+
+### 5. 测试上报和查询
+
+上报应用打开：
+
+```powershell
+Invoke-RestMethod `
+  -Uri "https://analytics.agnet.top/track" `
+  -Method Post `
+  -ContentType "application/json" `
+  -Body '{"projectName":"yibiao-client","event":"app_open","version":"0.1.0","platform":"win32","arch":"x64","client_id":"test-client"}'
+```
+
+上报页面访问：
+
+```powershell
+Invoke-RestMethod `
+  -Uri "https://analytics.agnet.top/track" `
+  -Method Post `
+  -ContentType "application/json" `
+  -Body '{"projectName":"yibiao-client","event":"page_view","page":"knowledge-base","version":"0.1.0","platform":"win32","arch":"x64","client_id":"test-client"}'
+```
+
+查询统计：
+
+```powershell
+Invoke-RestMethod `
+  -Uri "https://analytics.agnet.top/api/summary?projectName=yibiao-client&days=30" `
+  -Method Get `
+  -Headers @{ Authorization = "Bearer <ADMIN_TOKEN>" }
+```
+
+Analytics Engine 写入后可能需要等待几十秒才能查到。
+
+概览指标口径：
+
+| 指标 | 说明 |
+| --- | --- |
+| 新增客户端 | 所选时间范围内创建、并且期间有过事件上报的去重客户端数 |
+| 老客户端活跃 | 所选时间范围内活跃客户端数减去新增客户端数 |
+| 每日统计中的客户端数 | 当天有任意打开或页面访问事件上报的去重客户端数 |
+| 版本分布中的活跃客户端数 | 所选时间范围内该版本上报过事件的去重客户端数 |
+| 配置使用中的文本模型和生图模型 | 所选时间范围内真实 AI 接口请求使用的模型名称、去重客户端数和请求次数 |
+| 留存概览中的当日回访客户端 | 创建后 D1/D3/D7 当天再次打开 App 的客户端数 |
+
+配置使用只采集模型名称、开关和枚举类配置，不采集 `api_key`、`base_url`、`mineru_token`、Prompt、响应内容、错误详情等敏感数据。
+
+发布公告：
+
+```powershell
+Invoke-RestMethod `
+  -Uri "https://analytics.agnet.top/api/notice" `
+  -Method Post `
+  -ContentType "application/json" `
+  -Headers @{ Authorization = "Bearer <ADMIN_TOKEN>" } `
+  -Body '{"projectName":"yibiao-client","title":"公告标题","content":"## Markdown 公告内容","enabled":true}'
+```
+
+客户端读取公告：
+
+```powershell
+Invoke-RestMethod -Uri "https://analytics.agnet.top/notice?projectName=yibiao-client"
+```
+
+### 6. 查看 Worker 错误日志
+
+本地登录 Cloudflare 后，可实时查看 API Worker 日志：
+
+```powershell
+cd analytics\worker
+npx wrangler tail agnet-analytics-api --format pretty
+```
+
+如果尚未登录，先执行：
+
+```powershell
+cd analytics\worker
+npx wrangler login
+```
+
+查询接口失败时，Worker 会输出类似 `[analytics] summary query failed ...` 的错误日志。
+
+## 三、接入新项目
+
+不需要修改 Worker 配置。任意合法 `projectName` 都可以直接上报和查询。
+
+项目名规则：
+
+1. 只使用英文字母、数字、点、下划线、中划线。
+2. 长度不超过 80。
+3. 不要使用中文、空格、引号。
+
+前端封装示例：
+
+```ts
+const ANALYTICS_ENDPOINT = 'https://analytics.agnet.top/track';
+const PROJECT_NAME = 'my-other-app';
+
+export async function track(event: 'app_open' | 'page_view', data: Record<string, string> = {}) {
+  try {
+    const enabled = localStorage.getItem('telemetry_enabled') !== 'false';
+    if (!enabled) return;
+
+    await fetch(ANALYTICS_ENDPOINT, {
+      method: 'POST',
+      headers: {
+        'Content-Type': 'application/json',
+      },
+      body: JSON.stringify({
+        projectName: PROJECT_NAME,
+        event,
+        page: data.page || '',
+        version: data.version || '',
+        platform: data.platform || '',
+        arch: data.arch || '',
+        client_id: getOrCreateAnonymousClientId(),
+      }),
+    });
+  } catch {
+    // 埋点失败不能影响业务。
+  }
+}
+
+function getOrCreateAnonymousClientId() {
+  const key = 'analytics_client_id';
+  const existing = localStorage.getItem(key);
+  if (existing) return existing;
+
+  const id = crypto.randomUUID();
+  localStorage.setItem(key, id);
+  return id;
+}
+```
+
+页面访问示例：
+
+```ts
+track('page_view', {
+  page: 'settings',
+  version: appVersion,
+  platform: window.yibiao?.platform || '',
+  arch: 'x64',
+});
+```
+
+## 四、排查
+
+| 问题 | 处理 |
+| --- | --- |
+| `unauthorized` | 检查统计页面输入的 `ADMIN_TOKEN` 是否与 Worker Secret 一致 |
+| `NOTICE_STORE is not configured` | 先确认 Worker 的 `Settings -> Bindings` 存在 `NOTICE_STORE`，或本地运行 `cd analytics\worker; npm run setup:notice-kv` 后提交更新后的 `wrangler.jsonc` 并重新部署 Worker |
+| 公告无法发布或读取 | 访问 `https://analytics.agnet.top/health`，确认 `noticeStoreConfigured` 为 `true` 后再测试公告发布 |
+| `invalid projectName` | 检查项目名格式 |
+| `invalid event` | 仅支持 `app_open`、`page_view` |
+| `missing page` | `page_view` 必须传 `page` |
+| 查询为空 | 先上报测试数据，等待几十秒再查 |
+| 自定义域名未生效 | 检查对应 Worker 的 `Settings -> Domains & Routes` 和 `wrangler.jsonc` |
+| 绑定不存在 | 检查 API Worker 的 `Settings -> Bindings` 是否存在 `ANALYTICS` |
+
+## 五、自动部署触发规则
+
+Cloudflare Workers Builds 会在生产分支推送时触发构建。仓库里已将两个项目的 `deploy` 命令改为按目录校验：
+
+| Worker | 监听目录 |
+| --- | --- |
+| `agnet-analytics-api` | `analytics/worker` |
+| `agnet-analytics-dashboard` | `analytics/dashboard` |
+
+如果本次提交没有修改对应目录，构建会成功结束，但不会执行 `wrangler deploy`。
+
+如果需要强制重新部署，在 Cloudflare 的 Deploy command 临时改为：
+
+```text
+FORCE_DEPLOY=1 npm run deploy
+```
+
+重试成功后再改回：
+
+```text
+npm run deploy
+```

analytics/dashboard/package.json

@@ -0,0 +1,13 @@
+{
+  "name": "agnet-analytics-dashboard",
+  "version": "0.1.0",
+  "private": true,
+  "type": "module",
+  "scripts": {
+    "dev": "wrangler dev",
+    "deploy": "node ../scripts/deploy-if-changed.mjs analytics/dashboard"
+  },
+  "devDependencies": {
+    "wrangler": "^4.13.2"
+  }
+}

analytics/dashboard/public/index.html

@@ -0,0 +1,154 @@
+<!doctype html>
+<html lang="zh-CN">
+<head>
+  <meta charset="utf-8" />
+  <meta name="viewport" content="width=device-width, initial-scale=1" />
+  <title>埋点统计看板</title>
+  <link rel="stylesheet" href="./styles.css" />
+</head>
+<body>
+  <main>
+    <header class="hero">
+      <div>
+        <h1>埋点统计看板</h1>
+        <p>Cloudflare Workers + Analytics Engine + Workers Static Assets</p>
+      </div>
+      <div class="status">
+        <span id="statusDot" class="dot"></span>
+        <span id="statusText">未连接</span>
+      </div>
+    </header>
+
+    <section class="panel controls">
+      <label>
+        API 地址
+        <input id="apiBase" value="https://analytics.agnet.top" />
+      </label>
+      <label>
+        ADMIN_TOKEN
+        <input id="adminToken" type="password" placeholder="输入 Worker Secret 中的 ADMIN_TOKEN" />
+      </label>
+      <label>
+        项目
+        <input id="projectName" value="yibiao-client" placeholder="输入项目名，例如 yibiao-client" list="projectOptions" />
+        <datalist id="projectOptions"></datalist>
+      </label>
+      <label>
+        时间范围
+        <select id="days">
+          <option value="7">最近 7 天</option>
+          <option value="30" selected>最近 30 天</option>
+          <option value="90">最近 90 天</option>
+        </select>
+      </label>
+      <button id="refreshButton">刷新当前页</button>
+    </section>
+
+    <div class="panel hint">Token 只保存在当前浏览器 localStorage，不写入仓库，也不会提交到服务端。</div>
+    <div id="errorBox" class="error"></div>
+
+    <nav class="tabs" aria-label="看板标签页">
+      <button class="tab-button" type="button" data-tab-button="overview">概览</button>
+      <button class="tab-button" type="button" data-tab-button="traffic">访问分析</button>
+      <button class="tab-button" type="button" data-tab-button="config">配置使用</button>
+      <button class="tab-button" type="button" data-tab-button="latest">最近事件</button>
+      <button class="tab-button" type="button" data-tab-button="notice">公告管理</button>
+    </nav>
+
+    <section id="tab-overview" class="tab-panel" data-tab-panel="overview">
+      <section class="cards">
+        <div class="panel card"><span>打开量</span><strong id="totalOpen">0</strong></div>
+        <div class="panel card"><span>页面访问量</span><strong id="totalView">0</strong></div>
+        <div class="panel card"><span>总客户端数</span><strong id="totalClients">0</strong></div>
+        <div class="panel card"><span>今日活跃客户端</span><strong id="todayActiveClients">0</strong></div>
+        <div class="panel card"><span>近 7 天活跃</span><strong id="wau">0</strong></div>
+        <div class="panel card"><span>近 30 天活跃</span><strong id="mau">0</strong></div>
+        <div class="panel card"><span>新增客户端</span><strong id="newClients">0</strong></div>
+        <div class="panel card"><span>老客户端活跃</span><strong id="returningClients">0</strong></div>
+      </section>
+
+      <section class="grid">
+        <div class="panel section">
+          <h2>每日统计</h2>
+          <div id="dailyTable"></div>
+        </div>
+        <div class="panel section">
+          <h2>留存概览</h2>
+          <div id="retentionTable"></div>
+        </div>
+      </section>
+    </section>
+
+    <section id="tab-traffic" class="tab-panel" data-tab-panel="traffic">
+      <section class="grid">
+        <div class="panel section">
+          <h2>页面访问排行</h2>
+          <div id="pagesTable"></div>
+        </div>
+        <div class="panel section">
+          <h2>版本分布</h2>
+          <div id="versionsTable"></div>
+        </div>
+      </section>
+    </section>
+
+    <section id="tab-config" class="tab-panel" data-tab-panel="config">
+      <section class="panel section">
+        <h2>配置使用情况</h2>
+        <div id="configUsage"></div>
+      </section>
+    </section>
+
+    <section id="tab-latest" class="tab-panel" data-tab-panel="latest">
+      <section class="panel section">
+        <div class="section-head">
+          <h2>最近事件</h2>
+          <div class="pager">
+            <button id="prevLatestPage" type="button">上一页</button>
+            <span id="latestPageInfo">第 1 页</span>
+            <button id="nextLatestPage" type="button">下一页</button>
+          </div>
+        </div>
+        <div id="latestTable"></div>
+      </section>
+    </section>
+
+    <section id="tab-notice" class="tab-panel" data-tab-panel="notice">
+      <section class="panel section notice-panel">
+        <div class="section-head">
+          <div>
+            <h2>公告管理</h2>
+            <p>发布后客户端会在启动和每 30 分钟轮询时拉取最新 Markdown 公告。同一公告关闭后不再显示，重新发布会生成新的公告 ID。</p>
+          </div>
+          <button id="loadNoticeButton" type="button">读取公告</button>
+        </div>
+        <div id="noticeMeta" class="notice-meta">当前未读取公告。</div>
+        <div class="notice-form">
+          <label>
+            公告标题
+            <input id="noticeTitle" maxlength="120" placeholder="例如：开源许可证提醒" />
+          </label>
+          <label>
+            状态
+            <select id="noticeEnabled">
+              <option value="true" selected>启用</option>
+              <option value="false">保存但不展示</option>
+            </select>
+          </label>
+          <label class="notice-field-wide">
+            Markdown 内容
+            <textarea id="noticeContent" maxlength="20000" placeholder="输入 Markdown 公告内容。支持标题、列表、链接、加粗等语法。"></textarea>
+          </label>
+        </div>
+        <div class="notice-actions">
+          <button id="disableNoticeButton" class="danger-button" type="button">停用公告</button>
+          <button id="publishNoticeButton" type="button">发布公告</button>
+        </div>
+        <div id="noticeStatus" class="notice-status"></div>
+      </section>
+    </section>
+  </main>
+
+  <script type="module" src="./src/main.js"></script>
+</body>
+</html>

analytics/dashboard/public/src/api.js

@@ -0,0 +1,76 @@
+import { state } from './state.js';
+
+export function normalizeApiBase(value) {
+  return String(value || '').trim().replace(/\/+$/, '');
+}
+
+export function saveSettings() {
+  localStorage.setItem('analytics_api_base', normalizeApiBase(state.apiBase.value));
+  localStorage.setItem('analytics_admin_token', state.adminToken.value.trim());
+  localStorage.setItem('analytics_project_name', state.projectName.value);
+  localStorage.setItem('analytics_days', state.days.value);
+}
+
+export function loadSettings() {
+  state.apiBase.value = localStorage.getItem('analytics_api_base') || state.apiBase.value;
+  state.adminToken.value = localStorage.getItem('analytics_admin_token') || '';
+  state.projectName.value = localStorage.getItem('analytics_project_name') || state.projectName.value;
+  state.days.value = localStorage.getItem('analytics_days') || '30';
+}
+
+export function getSelectedProjectName() {
+  return state.projectName.value.trim();
+}
+
+export function getEncodedProjectAndDays() {
+  return {
+    projectName: encodeURIComponent(getSelectedProjectName()),
+    days: encodeURIComponent(state.days.value),
+  };
+}
+
+export function assertReady() {
+  if (!state.adminToken.value.trim()) {
+    throw new Error('请先输入 ADMIN_TOKEN');
+  }
+  if (!getSelectedProjectName()) {
+    throw new Error('请先输入项目名');
+  }
+}
+
+export async function requestJson(path, options = {}) {
+  const apiBase = normalizeApiBase(state.apiBase.value);
+  const headers = {
+    Authorization: `Bearer ${state.adminToken.value.trim()}`,
+  };
+  if (options.body !== undefined) {
+    headers['Content-Type'] = 'application/json';
+  }
+
+  const response = await fetch(`${apiBase}${path}`, {
+    method: options.method || 'GET',
+    headers,
+    body: options.body !== undefined ? JSON.stringify(options.body) : undefined,
+  });
+
+  const data = await response.json().catch(() => null);
+  if (!response.ok || !data || data.code !== 0) {
+    throw new Error(data?.message || `请求失败：${response.status}`);
+  }
+  return data;
+}
+
+export async function loadProjectOptions() {
+  try {
+    const data = await requestJson('/api/projects');
+    state.projectOptions.innerHTML = '';
+
+    for (const project of data.projects || []) {
+      const option = document.createElement('option');
+      option.value = project;
+      state.projectOptions.appendChild(option);
+    }
+  } catch {
+    // 项目列表只是输入提示，失败不影响按项目名查询。
+  }
+}

analytics/dashboard/public/src/main.js

@@ -0,0 +1,71 @@
+import { loadSettings, saveSettings } from './api.js';
+import { loadConfigUsage } from './pages/configUsage.js';
+import { loadLatest } from './pages/latest.js';
+import { disableNotice, loadNotice, publishNotice } from './pages/notice.js';
+import { loadOverview } from './pages/overview.js';
+import { loadTraffic } from './pages/traffic.js';
+import { setError, setStatus, updateLatestPager } from './render.js';
+import { appState, state } from './state.js';
+import { activateTab, getInitialTab } from './tabs.js';
+
+const tabLoaders = {
+  overview: () => loadOverview(),
+  traffic: () => loadTraffic(),
+  config: () => loadConfigUsage(),
+  latest: (options = {}) => loadLatest(options),
+  notice: () => loadNotice(),
+};
+
+async function refreshActiveTab(options = {}) {
+  setError('');
+  setStatus('', '加载中');
+  state.refreshButton.disabled = true;
+
+  try {
+    const loader = tabLoaders[appState.activeTab] || tabLoaders.overview;
+    await loader(options);
+    setStatus('ok', '已连接');
+  } catch (error) {
+    setStatus('error', '连接失败');
+    setError(error?.message || String(error));
+  } finally {
+    state.refreshButton.disabled = false;
+    updateLatestPager();
+  }
+}
+
+function bindEvents() {
+  state.refreshButton.addEventListener('click', () => refreshActiveTab({ resetLatestPage: true }));
+  state.loadNoticeButton.addEventListener('click', () => loadNotice().catch(() => undefined));
+  state.publishNoticeButton.addEventListener('click', publishNotice);
+  state.disableNoticeButton.addEventListener('click', disableNotice);
+  state.prevLatestPage.addEventListener('click', () => {
+    appState.latestPage = Math.max(1, appState.latestPage - 1);
+    void refreshActiveTab();
+  });
+  state.nextLatestPage.addEventListener('click', () => {
+    appState.latestPage += 1;
+    void refreshActiveTab();
+  });
+
+  for (const button of state.tabButtons) {
+    button.addEventListener('click', () => {
+      activateTab(button.dataset.tabButton);
+      void refreshActiveTab({ resetLatestPage: true });
+    });
+  }
+
+  state.apiBase.addEventListener('change', saveSettings);
+  state.adminToken.addEventListener('change', saveSettings);
+  state.projectName.addEventListener('change', saveSettings);
+  state.days.addEventListener('change', saveSettings);
+}
+
+loadSettings();
+activateTab(getInitialTab());
+updateLatestPager();
+bindEvents();
+
+if (state.adminToken.value.trim()) {
+  void refreshActiveTab({ resetLatestPage: true });
+}

analytics/dashboard/public/src/pages/configUsage.js

@@ -0,0 +1,63 @@
+import { assertReady, getEncodedProjectAndDays, loadProjectOptions, requestJson, saveSettings } from '../api.js';
+import { escapeHtml, formatNumber } from '../render.js';
+import { state } from '../state.js';
+
+function labelConfigValue(groupKey, value) {
+  const labels = {
+    fileParserProviders: {
+      local: '本地解析',
+      'mineru-accurate-api': 'MinerU 精准解析 API',
+      'mineru-agent-api': 'MinerU-Agent 轻量解析 API',
+    },
+    realTimeRender: { true: '开启', false: '关闭' },
+    imageProviders: { volcengine: '火山方舟', 'google-ai-studio': 'Google AI Studio' },
+    imageModelStatuses: { untested: '未测试', available: '可用', unavailable: '不可用' },
+    bidAnalysisModes: { key: '只解析关键项', full: '完整解析' },
+    outlineModes: { free: '自由生成', aligned: '按评分项对齐' },
+    tableRequirements: { none: '不要', light: '少量', moderate: '适中', heavy: '大量' },
+    useMermaidImages: { true: '开启', false: '关闭' },
+    useAiImages: { true: '开启', false: '关闭' },
+  };
+
+  return labels[groupKey]?.[value] || value || '-';
+}
+
+function renderConfigUsage(usage) {
+  const groups = [
+    ['fileParserProviders', '文件解析方式'],
+    ['realTimeRender', '实时渲染'],
+    ['imageProviders', '生图服务商'],
+    ['imageModelStatuses', '生图模型状态'],
+    ['textModelNames', '文本模型请求'],
+    ['imageModelNames', '生图模型请求'],
+    ['bidAnalysisModes', 'Step 02 解析模式'],
+    ['outlineModes', 'Step 03 目录模式'],
+    ['tableRequirements', '正文表格需求'],
+    ['useMermaidImages', 'Mermaid 图片'],
+    ['useAiImages', 'AI 生图'],
+  ];
+
+  state.configUsage.innerHTML = `<div class="usage-grid">${groups.map(([key, label]) => {
+    const rows = usage?.[key] || [];
+    const body = rows.length
+      ? `<table><thead><tr><th>取值</th><th>客户端</th><th>次数</th></tr></thead><tbody>${rows.map((row) => `
+          <tr>
+            <td><code>${escapeHtml(labelConfigValue(key, row.value))}</code></td>
+            <td>${formatNumber(row.clients)}</td>
+            <td>${formatNumber(row.events)}</td>
+          </tr>
+        `).join('')}</tbody></table>`
+      : '<div class="empty">暂无数据</div>';
+    return `<div class="usage-card"><h3>${escapeHtml(label)}</h3>${body}</div>`;
+  }).join('')}</div>`;
+}
+
+export async function loadConfigUsage() {
+  assertReady();
+  await loadProjectOptions();
+  saveSettings();
+
+  const { projectName, days } = getEncodedProjectAndDays();
+  const data = await requestJson(`/api/config-usage?projectName=${projectName}&days=${days}`);
+  renderConfigUsage(data.usage || {});
+}

analytics/dashboard/public/src/pages/latest.js

@@ -0,0 +1,31 @@
+import { assertReady, getEncodedProjectAndDays, loadProjectOptions, requestJson, saveSettings } from '../api.js';
+import { renderTable, updateLatestPager } from '../render.js';
+import { appState, state } from '../state.js';
+
+export async function loadLatest(options = {}) {
+  if (options.resetLatestPage) {
+    appState.latestPage = 1;
+  }
+
+  assertReady();
+  await loadProjectOptions();
+  saveSettings();
+
+  const { projectName } = getEncodedProjectAndDays();
+  const latest = await requestJson(`/api/latest?projectName=${projectName}&page=${appState.latestPage}`);
+
+  appState.latestTotal = Number(latest.total || 0);
+  appState.latestPage = Number(latest.page || appState.latestPage);
+  updateLatestPager();
+
+  renderTable(state.latestTable, latest.events || [], [
+    { key: 'timestamp', label: '时间' },
+    { key: 'event', label: '事件', code: true },
+    { key: 'page', label: '页面', code: true },
+    { key: 'version', label: '版本', code: true },
+    { key: 'platform', label: '平台' },
+    { key: 'arch', label: '架构' },
+    { key: 'clientCreatedAt', label: '创建日期' },
+    { key: 'clientId', label: '客户端ID', code: true },
+  ], '暂无最近事件');
+}

analytics/dashboard/public/src/pages/notice.js

@@ -0,0 +1,89 @@
+import { assertReady, getSelectedProjectName, requestJson, saveSettings } from '../api.js';
+import { setNoticeStatus } from '../render.js';
+import { state } from '../state.js';
+
+function renderNoticeMeta(notice) {
+  if (!notice) {
+    state.noticeMeta.textContent = '当前项目暂无公告。';
+    return;
+  }
+
+  const enabledText = notice.enabled === false ? '停用' : '启用';
+  state.noticeMeta.textContent = `公告 ID：${notice.id || '-'}\n状态：${enabledText}\n公告时间：${notice.updatedAt || '-'}\n项目：${notice.projectName || '-'}`;
+}
+
+function fillNoticeForm(notice) {
+  state.noticeTitle.value = notice?.title || '';
+  state.noticeEnabled.value = notice?.enabled === false ? 'false' : 'true';
+  state.noticeContent.value = notice?.content || '';
+  renderNoticeMeta(notice);
+}
+
+export async function loadNotice(options = {}) {
+  try {
+    assertReady();
+    saveSettings();
+
+    const projectName = getSelectedProjectName();
+    const data = await requestJson(`/api/notice?projectName=${encodeURIComponent(projectName)}`);
+    fillNoticeForm(data.notice || null);
+    if (!options.quiet) {
+      setNoticeStatus(data.notice ? '公告已读取。' : '当前项目暂无公告。', 'ok');
+    }
+  } catch (error) {
+    if (!options.quiet) {
+      setNoticeStatus(error?.message || String(error), 'error');
+    }
+    throw error;
+  }
+}
+
+export async function publishNotice() {
+  setNoticeStatus('');
+  try {
+    assertReady();
+    const projectName = getSelectedProjectName();
+    const title = state.noticeTitle.value.trim();
+    const content = state.noticeContent.value.trim();
+    if (!title) {
+      throw new Error('请先填写公告标题');
+    }
+    if (!content) {
+      throw new Error('请先填写 Markdown 内容');
+    }
+
+    state.publishNoticeButton.disabled = true;
+    const data = await requestJson('/api/notice', {
+      method: 'POST',
+      body: {
+        projectName,
+        title,
+        content,
+        enabled: state.noticeEnabled.value !== 'false',
+      },
+    });
+    fillNoticeForm(data.notice || null);
+    setNoticeStatus('公告已发布。客户端会在下一次轮询时拉取新公告。', 'ok');
+  } catch (error) {
+    setNoticeStatus(error?.message || String(error), 'error');
+  } finally {
+    state.publishNoticeButton.disabled = false;
+  }
+}
+
+export async function disableNotice() {
+  setNoticeStatus('');
+  try {
+    assertReady();
+    const projectName = getSelectedProjectName();
+
+    state.disableNoticeButton.disabled = true;
+    await requestJson(`/api/notice?projectName=${encodeURIComponent(projectName)}`, { method: 'DELETE' });
+    fillNoticeForm(null);
+    setNoticeStatus('公告已停用。客户端后续不会再拉取到该公告。', 'ok');
+  } catch (error) {
+    setNoticeStatus(error?.message || String(error), 'error');
+  } finally {
+    state.disableNoticeButton.disabled = false;
+  }
+}

analytics/dashboard/public/src/pages/overview.js

@@ -0,0 +1,66 @@
+import { assertReady, getEncodedProjectAndDays, loadProjectOptions, requestJson, saveSettings } from '../api.js';
+import { state } from '../state.js';
+import { formatNumber, formatPercent, renderTable } from '../render.js';
+
+function normalizeDaily(rows, clientRows) {
+  const map = new Map();
+  for (const row of rows || []) {
+    const date = String(row.date || '').slice(0, 10);
+    if (!date) continue;
+    if (!map.has(date)) map.set(date, { date, clients: 0, appOpen: 0, pageView: 0 });
+    const item = map.get(date);
+    if (row.event === 'app_open') item.appOpen += Number(row.count || 0);
+    if (row.event === 'page_view') item.pageView += Number(row.count || 0);
+  }
+
+  for (const row of clientRows || []) {
+    const date = String(row.date || '').slice(0, 10);
+    if (!date) continue;
+    if (!map.has(date)) map.set(date, { date, clients: 0, appOpen: 0, pageView: 0 });
+    map.get(date).clients = Number(row.clients || 0);
+  }
+
+  return Array.from(map.values()).sort((a, b) => a.date.localeCompare(b.date));
+}
+
+export async function loadOverview() {
+  assertReady();
+  await loadProjectOptions();
+  saveSettings();
+
+  const { projectName, days } = getEncodedProjectAndDays();
+  const [summary, retention] = await Promise.all([
+    requestJson(`/api/summary?projectName=${projectName}&days=${days}`),
+    requestJson(`/api/retention?projectName=${projectName}&days=${days}`),
+  ]);
+
+  const daily = normalizeDaily(summary.daily || [], summary.dailyClients || []);
+  const totalOpen = daily.reduce((sum, row) => sum + row.appOpen, 0);
+  const totalView = daily.reduce((sum, row) => sum + row.pageView, 0);
+
+  state.totalOpen.textContent = formatNumber(totalOpen);
+  state.totalView.textContent = formatNumber(totalView);
+  state.totalClients.textContent = formatNumber(summary.totalClients);
+  state.todayActiveClients.textContent = formatNumber(summary.todayActiveClients);
+  state.wau.textContent = formatNumber(summary.wau);
+  state.mau.textContent = formatNumber(summary.mau);
+  state.newClients.textContent = formatNumber(summary.newClients);
+  state.returningClients.textContent = formatNumber(summary.returningClients);
+
+  renderTable(state.dailyTable, daily, [
+    { key: 'date', label: '日期' },
+    { key: 'clients', label: '客户端数' },
+    { key: 'appOpen', label: '打开量' },
+    { key: 'pageView', label: '页面访问量' },
+  ], '暂无每日统计数据');
+
+  renderTable(state.retentionTable, (retention.retention || []).map((row) => ({
+    ...row,
+    retentionRate: formatPercent(row.retentionRate),
+  })), [
+    { key: 'day', label: '留存日' },
+    { key: 'cohortClients', label: '可观察客户端' },
+    { key: 'retainedClients', label: '当日回访客户端' },
+    { key: 'retentionRate', label: '留存率' },
+  ], '暂无留存数据');
+}

analytics/dashboard/public/src/pages/traffic.js

@@ -0,0 +1,23 @@
+import { assertReady, getEncodedProjectAndDays, loadProjectOptions, requestJson, saveSettings } from '../api.js';
+import { renderTable } from '../render.js';
+import { state } from '../state.js';
+
+export async function loadTraffic() {
+  assertReady();
+  await loadProjectOptions();
+  saveSettings();
+
+  const { projectName, days } = getEncodedProjectAndDays();
+  const summary = await requestJson(`/api/summary?projectName=${projectName}&days=${days}`);
+
+  renderTable(state.pagesTable, summary.pages || [], [
+    { key: 'page', label: '页面', code: true },
+    { key: 'count', label: '访问量' },
+  ], '暂无页面访问数据');
+
+  renderTable(state.versionsTable, summary.versions || [], [
+    { key: 'version', label: '版本', code: true },
+    { key: 'clients', label: '活跃客户端数' },
+    { key: 'count', label: '事件数' },
+  ], '暂无版本数据');
+}

analytics/dashboard/public/src/render.js

@@ -0,0 +1,59 @@
+import { appState, state } from './state.js';
+
+export function escapeHtml(value) {
+  return String(value ?? '')
+    .replaceAll('&', '&')
+    .replaceAll('<', '&lt;')
+    .replaceAll('>', '&gt;')
+    .replaceAll('"', '&quot;')
+    .replaceAll("'", '&#039;');
+}
+
+export function formatNumber(value) {
+  return Number(value || 0).toLocaleString('zh-CN');
+}
+
+export function formatPercent(value) {
+  return `${(Number(value || 0) * 100).toFixed(1)}%`;
+}
+
+export function setStatus(type, text) {
+  state.statusDot.className = type === 'ok' ? 'dot ok' : type === 'error' ? 'dot error' : 'dot';
+  state.statusText.textContent = text;
+}
+
+export function setError(message) {
+  state.errorBox.style.display = message ? 'block' : 'none';
+  state.errorBox.textContent = message || '';
+}
+
+export function renderTable(target, rows, columns, emptyText) {
+  if (!rows || rows.length === 0) {
+    target.innerHTML = `<div class="empty">${escapeHtml(emptyText)}</div>`;
+    return;
+  }
+
+  const head = columns.map((column) => `<th>${escapeHtml(column.label)}</th>`).join('');
+  const body = rows.map((row) => {
+    const cells = columns.map((column) => {
+      const value = row[column.key] == null || row[column.key] === '' ? '-' : row[column.key];
+      const content = column.code ? `<code>${escapeHtml(value)}</code>` : escapeHtml(value);
+      return `<td>${content}</td>`;
+    }).join('');
+    return `<tr>${cells}</tr>`;
+  }).join('');
+
+  target.innerHTML = `<table><thead><tr>${head}</tr></thead><tbody>${body}</tbody></table>`;
+}
+
+export function updateLatestPager() {
+  const totalPages = Math.max(1, Math.ceil(appState.latestTotal / appState.latestPageSize));
+  state.latestPageInfo.textContent = `第 ${appState.latestPage} / ${totalPages} 页，共 ${formatNumber(appState.latestTotal)} 条`;
+  state.prevLatestPage.disabled = appState.latestPage <= 1;
+  state.nextLatestPage.disabled = appState.latestPage >= totalPages;
+}
+
+export function setNoticeStatus(message, type = '') {
+  state.noticeStatus.className = type ? `notice-status ${type}` : 'notice-status';
+  state.noticeStatus.textContent = message || '';
+}

analytics/dashboard/public/src/state.js

@@ -0,0 +1,47 @@
+export const $ = (id) => document.getElementById(id);
+
+export const state = {
+  apiBase: $('apiBase'),
+  adminToken: $('adminToken'),
+  projectName: $('projectName'),
+  projectOptions: $('projectOptions'),
+  days: $('days'),
+  refreshButton: $('refreshButton'),
+  errorBox: $('errorBox'),
+  statusDot: $('statusDot'),
+  statusText: $('statusText'),
+  tabButtons: Array.from(document.querySelectorAll('[data-tab-button]')),
+  tabPanels: Array.from(document.querySelectorAll('[data-tab-panel]')),
+  totalOpen: $('totalOpen'),
+  totalView: $('totalView'),
+  totalClients: $('totalClients'),
+  todayActiveClients: $('todayActiveClients'),
+  wau: $('wau'),
+  mau: $('mau'),
+  newClients: $('newClients'),
+  returningClients: $('returningClients'),
+  dailyTable: $('dailyTable'),
+  pagesTable: $('pagesTable'),
+  versionsTable: $('versionsTable'),
+  retentionTable: $('retentionTable'),
+  configUsage: $('configUsage'),
+  latestTable: $('latestTable'),
+  prevLatestPage: $('prevLatestPage'),
+  nextLatestPage: $('nextLatestPage'),
+  latestPageInfo: $('latestPageInfo'),
+  loadNoticeButton: $('loadNoticeButton'),
+  publishNoticeButton: $('publishNoticeButton'),
+  disableNoticeButton: $('disableNoticeButton'),
+  noticeMeta: $('noticeMeta'),
+  noticeStatus: $('noticeStatus'),
+  noticeTitle: $('noticeTitle'),
+  noticeEnabled: $('noticeEnabled'),
+  noticeContent: $('noticeContent'),
+};
+
+export const appState = {
+  activeTab: 'overview',
+  latestPage: 1,
+  latestTotal: 0,
+  latestPageSize: 10,
+};

analytics/dashboard/public/src/tabs.js

@@ -0,0 +1,21 @@
+import { appState, state } from './state.js';
+
+const validTabs = new Set(['overview', 'traffic', 'config', 'latest', 'notice']);
+
+export function getInitialTab() {
+  const tab = window.location.hash.replace(/^#/, '');
+  return validTabs.has(tab) ? tab : 'overview';
+}
+
+export function activateTab(tab) {
+  appState.activeTab = validTabs.has(tab) ? tab : 'overview';
+  window.location.hash = appState.activeTab;
+
+  for (const button of state.tabButtons) {
+    button.classList.toggle('active', button.dataset.tabButton === appState.activeTab);
+  }
+
+  for (const panel of state.tabPanels) {
+    panel.classList.toggle('active', panel.dataset.tabPanel === appState.activeTab);
+  }
+}

analytics/dashboard/public/styles.css

@@ -0,0 +1,403 @@
+:root {
+  --bg: #f6f8fb;
+  --panel: #ffffff;
+  --panel-soft: #f9fafb;
+  --text: #172033;
+  --muted: #667085;
+  --border: #e5e7eb;
+  --primary: #2563eb;
+  --primary-soft: #dbeafe;
+  --danger: #dc2626;
+  --green: #16a34a;
+  --shadow: 0 12px 30px rgba(15, 23, 42, 0.08);
+}
+
+* {
+  box-sizing: border-box;
+}
+
+body {
+  margin: 0;
+  min-height: 100vh;
+  background: radial-gradient(circle at top left, #e0ecff 0, transparent 34rem), var(--bg);
+  color: var(--text);
+  font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", "Microsoft YaHei", sans-serif;
+}
+
+main {
+  max-width: 1180px;
+  margin: 0 auto;
+  padding: 28px 16px 48px;
+}
+
+.hero {
+  display: flex;
+  justify-content: space-between;
+  gap: 18px;
+  align-items: flex-start;
+  margin-bottom: 20px;
+}
+
+h1 {
+  margin: 0 0 8px;
+  font-size: 30px;
+  letter-spacing: -0.03em;
+}
+
+p {
+  margin: 0;
+  color: var(--muted);
+}
+
+.status {
+  display: inline-flex;
+  align-items: center;
+  gap: 8px;
+  padding: 8px 12px;
+  border: 1px solid var(--border);
+  border-radius: 999px;
+  background: var(--panel);
+  color: var(--muted);
+  box-shadow: var(--shadow);
+  white-space: nowrap;
+}
+
+.dot {
+  width: 8px;
+  height: 8px;
+  border-radius: 999px;
+  background: var(--muted);
+}
+
+.dot.ok { background: var(--green); }
+.dot.error { background: var(--danger); }
+
+.panel {
+  background: rgba(255, 255, 255, 0.9);
+  border: 1px solid rgba(229, 231, 235, 0.95);
+  border-radius: 18px;
+  box-shadow: var(--shadow);
+  backdrop-filter: blur(12px);
+}
+
+.controls {
+  display: grid;
+  grid-template-columns: 1.3fr 1.5fr 0.9fr 0.7fr auto;
+  gap: 12px;
+  padding: 16px;
+  margin-bottom: 16px;
+}
+
+label {
+  display: grid;
+  gap: 6px;
+  color: var(--muted);
+  font-size: 13px;
+}
+
+input,
+select,
+textarea,
+button {
+  border-radius: 12px;
+  border: 1px solid #d0d5dd;
+  font: inherit;
+}
+
+input,
+select,
+button {
+  height: 40px;
+}
+
+input,
+select,
+textarea {
+  width: 100%;
+  padding: 0 12px;
+  background: #fff;
+  color: var(--text);
+  outline: none;
+}
+
+textarea {
+  min-height: 180px;
+  padding: 12px;
+  line-height: 1.65;
+  resize: vertical;
+}
+
+input:focus,
+select:focus,
+textarea:focus {
+  border-color: var(--primary);
+  box-shadow: 0 0 0 3px var(--primary-soft);
+}
+
+button {
+  align-self: end;
+  padding: 0 18px;
+  background: var(--primary);
+  border-color: var(--primary);
+  color: #fff;
+  cursor: pointer;
+  font-weight: 600;
+}
+
+button:disabled {
+  opacity: 0.6;
+  cursor: not-allowed;
+}
+
+.hint {
+  margin-bottom: 16px;
+  padding: 12px 16px;
+  color: var(--muted);
+  font-size: 13px;
+  line-height: 1.7;
+}
+
+.error {
+  display: none;
+  margin-bottom: 16px;
+  padding: 12px 14px;
+  background: #fef2f2;
+  border: 1px solid #fecaca;
+  border-radius: 12px;
+  color: #991b1b;
+  white-space: pre-wrap;
+}
+
+.tabs {
+  display: flex;
+  flex-wrap: wrap;
+  gap: 10px;
+  margin-bottom: 16px;
+}
+
+.tab-button {
+  align-self: auto;
+  height: 38px;
+  color: var(--muted);
+  background: rgba(255, 255, 255, 0.74);
+  border-color: var(--border);
+}
+
+.tab-button.active {
+  color: #fff;
+  background: var(--primary);
+  border-color: var(--primary);
+}
+
+.tab-panel {
+  display: none;
+}
+
+.tab-panel.active {
+  display: block;
+}
+
+.cards {
+  display: grid;
+  grid-template-columns: repeat(4, 1fr);
+  gap: 12px;
+  margin-bottom: 16px;
+}
+
+.card {
+  padding: 16px;
+}
+
+.card span {
+  display: block;
+  margin-bottom: 8px;
+  color: var(--muted);
+  font-size: 13px;
+}
+
+.card strong {
+  font-size: 28px;
+  letter-spacing: -0.04em;
+}
+
+.grid {
+  display: grid;
+  grid-template-columns: 1fr 1fr;
+  gap: 16px;
+  margin-bottom: 16px;
+}
+
+.section {
+  padding: 16px;
+}
+
+.section h2 {
+  margin: 0 0 12px;
+  font-size: 18px;
+}
+
+.section-head {
+  display: flex;
+  align-items: center;
+  justify-content: space-between;
+  gap: 12px;
+  margin-bottom: 12px;
+}
+
+.section-head h2 {
+  margin: 0;
+}
+
+.pager {
+  display: inline-flex;
+  align-items: center;
+  gap: 8px;
+  color: var(--muted);
+  font-size: 13px;
+}
+
+.pager button {
+  align-self: auto;
+  height: 32px;
+  padding: 0 10px;
+  border-radius: 10px;
+}
+
+.usage-grid {
+  display: grid;
+  grid-template-columns: repeat(3, 1fr);
+  gap: 12px;
+}
+
+.usage-card {
+  min-width: 0;
+  padding: 12px;
+  border: 1px solid var(--border);
+  border-radius: 14px;
+  background: var(--panel-soft);
+}
+
+.usage-card h3 {
+  margin: 0 0 10px;
+  font-size: 15px;
+}
+
+.notice-panel {
+  margin-bottom: 16px;
+}
+
+.notice-form {
+  display: grid;
+  grid-template-columns: 1fr 220px;
+  gap: 12px;
+  margin-top: 14px;
+}
+
+.notice-field-wide {
+  grid-column: 1 / -1;
+}
+
+.notice-meta,
+.notice-status {
+  padding: 10px 12px;
+  color: var(--muted);
+  font-size: 13px;
+  line-height: 1.65;
+  background: var(--panel-soft);
+  border: 1px solid var(--border);
+  border-radius: 12px;
+  white-space: pre-wrap;
+}
+
+.notice-status {
+  display: none;
+  margin-top: 12px;
+}
+
+.notice-status.ok {
+  display: block;
+  color: #166534;
+  background: #f0fdf4;
+  border-color: #bbf7d0;
+}
+
+.notice-status.error {
+  display: block;
+  color: #991b1b;
+  background: #fef2f2;
+  border-color: #fecaca;
+}
+
+.notice-actions {
+  display: flex;
+  justify-content: flex-end;
+  gap: 10px;
+  margin-top: 12px;
+}
+
+.notice-actions button {
+  align-self: auto;
+}
+
+.notice-actions .danger-button {
+  color: #991b1b;
+  background: #fef2f2;
+  border-color: #fecaca;
+}
+
+table {
+  width: 100%;
+  border-collapse: collapse;
+  font-size: 13px;
+}
+
+th,
+td {
+  padding: 9px 8px;
+  border-bottom: 1px solid var(--border);
+  text-align: left;
+  vertical-align: top;
+}
+
+th {
+  color: var(--muted);
+  background: var(--panel-soft);
+  font-weight: 600;
+}
+
+code {
+  padding: 2px 6px;
+  border-radius: 8px;
+  background: #eef2f7;
+  color: #344054;
+  word-break: break-all;
+}
+
+.empty {
+  padding: 24px;
+  border: 1px dashed #d0d5dd;
+  border-radius: 12px;
+  color: var(--muted);
+  text-align: center;
+  background: var(--panel-soft);
+}
+
+@media (max-width: 900px) {
+  .hero,
+  .controls,
+  .cards,
+  .grid,
+  .usage-grid,
+  .notice-form {
+    grid-template-columns: 1fr;
+    display: grid;
+  }
+
+  .notice-actions {
+    display: grid;
+  }
+
+  button {
+    width: 100%;
+  }
+}

analytics/dashboard/wrangler.jsonc

@@ -0,0 +1,16 @@
+{
+  "$schema": "node_modules/wrangler/config-schema.json",
+  "name": "agnet-analytics-dashboard",
+  "compatibility_date": "2026-05-14",
+  "workers_dev": true,
+  "routes": [
+    {
+      "pattern": "static.analytics.agnet.top",
+      "custom_domain": true
+    }
+  ],
+  "assets": {
+    "directory": "./public",
+    "not_found_handling": "404-page"
+  }
+}

analytics/scripts/deploy-if-changed.mjs

@@ -0,0 +1,103 @@
+import { spawnSync } from 'node:child_process';
+import { readFileSync } from 'node:fs';
+import { fileURLToPath } from 'node:url';
+import { dirname, resolve } from 'node:path';
+
+const watchPath = process.argv[2];
+const isWorkersBuild = Boolean(process.env.WORKERS_CI || process.env.WORKERS_CI_COMMIT_SHA);
+const forceDeploy = process.env.FORCE_DEPLOY === '1';
+const __dirname = dirname(fileURLToPath(import.meta.url));
+const noticeBindingName = 'NOTICE_STORE';
+
+if (!watchPath) {
+  console.error('Usage: node deploy-if-changed.mjs <watch-path>');
+  process.exit(1);
+}
+
+function run(command, args, options = {}) {
+  return spawnSync(command, args, {
+    encoding: 'utf8',
+    shell: process.platform === 'win32',
+    ...options,
+  });
+}
+
+function deploy() {
+  runPreDeploySetupIfNeeded();
+  console.log(`Running wrangler deploy for ${watchPath}.`);
+
+  const result = spawnSync('npx', ['wrangler', 'deploy'], {
+    stdio: 'inherit',
+    shell: process.platform === 'win32',
+  });
+
+  process.exit(result.status ?? 1);
+}
+
+function runPreDeploySetupIfNeeded() {
+  if (String(watchPath || '').replace(/\\/g, '/') !== 'analytics/worker') {
+    return;
+  }
+
+  const workerConfigPath = resolve(__dirname, '../worker/wrangler.jsonc');
+  const source = readFileSync(workerConfigPath, 'utf8');
+  if (hasNoticeStoreBinding(source)) {
+    console.log('NOTICE_STORE KV namespace already configured; skipping setup.');
+    return;
+  }
+
+  console.log('NOTICE_STORE KV namespace is not configured; running setup.');
+  const setupScript = resolve(__dirname, 'setup-notice-kv.mjs');
+  const result = spawnSync(process.execPath, [setupScript], {
+    stdio: 'inherit',
+    shell: process.platform === 'win32',
+  });
+
+  if (result.status !== 0) {
+    process.exit(result.status ?? 1);
+  }
+}
+
+function hasNoticeStoreBinding(source) {
+  const escapedBinding = noticeBindingName.replace(/[.*+?^${}()|[\]\\]/g, '\\$&');
+  const pattern = new RegExp(`\\{[\\s\\S]*?"binding"\\s*:\\s*"${escapedBinding}"[\\s\\S]*?"id"\\s*:\\s*"[^"<]+"[\\s\\S]*?\\}`);
+  return pattern.test(source);
+}
+
+function getTrimmedStdout(result) {
+  return String(result.stdout || '').trim();
+}
+
+if (!isWorkersBuild || forceDeploy) {
+  deploy();
+}
+
+const repoRootResult = run('git', ['rev-parse', '--show-toplevel']);
+if (repoRootResult.status !== 0) {
+  console.warn('Unable to find git root, deploying normally.');
+  deploy();
+}
+
+const repoRoot = getTrimmedStdout(repoRootResult);
+const parentResult = run('git', ['rev-parse', 'HEAD^'], { cwd: repoRoot });
+if (parentResult.status !== 0) {
+  console.warn('Unable to find parent commit, deploying normally.');
+  deploy();
+}
+
+const parentCommit = getTrimmedStdout(parentResult);
+const diffResult = run('git', ['diff', '--name-only', parentCommit, 'HEAD', '--', watchPath], { cwd: repoRoot });
+if (diffResult.status !== 0) {
+  console.warn('Unable to inspect changed files, deploying normally.');
+  deploy();
+}
+
+const changedFiles = getTrimmedStdout(diffResult);
+if (!changedFiles) {
+  console.log(`No changes under ${watchPath}; skipping wrangler deploy.`);
+  process.exit(0);
+}
+
+console.log(`Changes detected under ${watchPath}:`);
+console.log(changedFiles);
+deploy();

analytics/scripts/setup-notice-kv.mjs

@@ -0,0 +1,219 @@
+import { readFileSync, writeFileSync } from 'node:fs';
+import { spawnSync } from 'node:child_process';
+import { fileURLToPath } from 'node:url';
+import { dirname, resolve } from 'node:path';
+
+const __dirname = dirname(fileURLToPath(import.meta.url));
+const workerConfigPath = resolve(__dirname, '../worker/wrangler.jsonc');
+const bindingName = 'NOTICE_STORE';
+
+function readConfig() {
+  return readFileSync(workerConfigPath, 'utf8');
+}
+
+function getWorkerName(source) {
+  return source.match(/"name"\s*:\s*"([^"]+)"/)?.[1] || '';
+}
+
+function getConfiguredNamespaceId(source) {
+  const escapedBinding = bindingName.replace(/[.*+?^${}()|[\]\\]/g, '\\$&');
+  const pattern = new RegExp(`\\{[\\s\\S]*?"binding"\\s*:\\s*"${escapedBinding}"[\\s\\S]*?"id"\\s*:\\s*"([^"]*)"[\\s\\S]*?\\}`);
+  const id = source.match(pattern)?.[1]?.trim() || '';
+  return id && !id.includes('<') ? id : '';
+}
+
+function runWrangler(args) {
+  const result = spawnSync('npx', ['wrangler', ...args], {
+    encoding: 'utf8',
+    shell: process.platform === 'win32',
+  });
+  const output = `${result.stdout || ''}\n${result.stderr || ''}`.trim();
+
+  return {
+    status: result.status ?? 1,
+    output,
+  };
+}
+
+function parseNamespaceId(output) {
+  const patterns = [
+    /id\s*=\s*"([^"]+)"/i,
+    /"id"\s*:\s*"([^"]+)"/i,
+    /id[:=]\s*([0-9a-f]{32})/i,
+  ];
+
+  for (const pattern of patterns) {
+    const match = output.match(pattern);
+    if (match?.[1]) {
+      return match[1];
+    }
+  }
+
+  return '';
+}
+
+function parseNamespaceList(output, workerName) {
+  const preferredTitles = new Set([
+    bindingName,
+    workerName ? `${workerName}-${bindingName}` : '',
+  ].filter(Boolean));
+  let namespaces;
+
+  try {
+    namespaces = JSON.parse(output);
+  } catch {
+    const start = output.indexOf('[');
+    const end = output.lastIndexOf(']');
+    if (start === -1 || end === -1 || end <= start) {
+      return parseTextNamespaceList(output, preferredTitles);
+    }
+
+    try {
+      namespaces = JSON.parse(output.slice(start, end + 1));
+    } catch {
+      return parseTextNamespaceList(output, preferredTitles);
+    }
+  }
+
+  const items = Array.isArray(namespaces) ? namespaces : [];
+
+  const exact = items.find((item) => preferredTitles.has(String(item.title || '')));
+  if (exact?.id) {
+    return exact.id;
+  }
+
+  const suffix = items.find((item) => String(item.title || '').endsWith(`-${bindingName}`));
+  if (suffix?.id) {
+    return suffix.id;
+  }
+
+  const textId = parseTextNamespaceList(output, preferredTitles);
+  if (textId) {
+    return textId;
+  }
+
+  return '';
+}
+
+function parseTextNamespaceList(output, preferredTitles) {
+  const lines = String(output || '').split(/\r?\n/);
+  const hexIdPattern = /\b[0-9a-f]{32}\b/i;
+
+  for (const title of preferredTitles) {
+    for (const line of lines) {
+      if (!line.includes(title)) {
+        continue;
+      }
+
+      const id = line.match(hexIdPattern)?.[0] || '';
+      if (id) {
+        return id;
+      }
+    }
+  }
+
+  for (const line of lines) {
+    const cells = line.split('│').map((cell) => cell.trim()).filter(Boolean);
+    const id = cells.find((cell) => hexIdPattern.test(cell))?.match(hexIdPattern)?.[0] || '';
+    if (!id) {
+      continue;
+    }
+
+    const title = cells.find((cell) => preferredTitles.has(cell) || cell.endsWith(`-${bindingName}`));
+    if (title) {
+      return id;
+    }
+  }
+
+  return '';
+}
+
+function updateWranglerConfig(namespaceId) {
+  const source = readConfig();
+  const escapedBinding = bindingName.replace(/[.*+?^${}()|[\]\\]/g, '\\$&');
+  const bindingObjectPattern = new RegExp(`(\\{[\\s\\S]*?"binding"\\s*:\\s*"${escapedBinding}"[\\s\\S]*?"id"\\s*:\\s*")[^"]*("[\\s\\S]*?\\})`);
+
+  if (bindingObjectPattern.test(source)) {
+    writeFileSync(workerConfigPath, source.replace(bindingObjectPattern, `$1${namespaceId}$2`), 'utf8');
+    return;
+  }
+
+  const namespaceBlock = `  "kv_namespaces": [\n    {\n      "binding": "${bindingName}",\n      "id": "${namespaceId}"\n    }\n  ]`;
+  const existingKvPattern = /"kv_namespaces"\s*:\s*\[/;
+  if (existingKvPattern.test(source)) {
+    const updated = source.replace(existingKvPattern, `"kv_namespaces": [\n    {\n      "binding": "${bindingName}",\n      "id": "${namespaceId}"\n    },`);
+    writeFileSync(workerConfigPath, updated, 'utf8');
+    return;
+  }
+
+  const insertAt = source.lastIndexOf('\n}');
+  if (insertAt === -1) {
+    throw new Error('Unable to locate closing brace in wrangler.jsonc');
+  }
+
+  const updated = `${source.slice(0, insertAt)},\n${namespaceBlock}${source.slice(insertAt)}`;
+  writeFileSync(workerConfigPath, updated, 'utf8');
+}
+
+function printCredentialHelp(output) {
+  if (output) {
+    console.error(output);
+  }
+  console.error([
+    'Unable to create or find Cloudflare KV namespace NOTICE_STORE.',
+    'For CI, set CLOUDFLARE_API_TOKEN and CLOUDFLARE_ACCOUNT_ID in the environment that runs analytics/worker deployment.',
+    'For local setup, run `npx wrangler login` or set CLOUDFLARE_API_TOKEN before `npm run setup:notice-kv`.',
+  ].join('\n'));
+}
+
+const source = readConfig();
+const configuredId = getConfiguredNamespaceId(source);
+if (configuredId) {
+  console.log(`NOTICE_STORE KV namespace already configured: ${configuredId}`);
+  process.exit(0);
+}
+
+const envNamespaceId = String(process.env.NOTICE_STORE_ID || '').trim();
+if (envNamespaceId) {
+  updateWranglerConfig(envNamespaceId);
+  console.log(`NOTICE_STORE KV namespace configured from NOTICE_STORE_ID: ${envNamespaceId}`);
+  process.exit(0);
+}
+
+const workerName = getWorkerName(source);
+const listResult = runWrangler(['kv', 'namespace', 'list']);
+if (listResult.status === 0) {
+  const existingId = parseNamespaceList(listResult.output, workerName);
+  if (existingId) {
+    updateWranglerConfig(existingId);
+    console.log(`NOTICE_STORE KV namespace reused: ${existingId}`);
+    process.exit(0);
+  }
+}
+
+const createResult = runWrangler(['kv', 'namespace', 'create', bindingName]);
+if (createResult.status !== 0) {
+  if (/already exists/i.test(createResult.output)) {
+    const retryListResult = runWrangler(['kv', 'namespace', 'list']);
+    if (retryListResult.status === 0) {
+      const existingId = parseNamespaceList(retryListResult.output, workerName);
+      if (existingId) {
+        updateWranglerConfig(existingId);
+        console.log(`NOTICE_STORE KV namespace reused after create conflict: ${existingId}`);
+        process.exit(0);
+      }
+    }
+  }
+
+  printCredentialHelp(createResult.output || listResult.output);
+  process.exit(createResult.status || 1);
+}
+
+const namespaceId = parseNamespaceId(createResult.output);
+if (!namespaceId) {
+  console.error(createResult.output);
+  throw new Error('Unable to parse KV namespace id from Wrangler output.');
+}
+
+updateWranglerConfig(namespaceId);
+console.log(`NOTICE_STORE KV namespace created and configured: ${namespaceId}`);

analytics/worker/package.json

@@ -0,0 +1,14 @@
+{
+  "name": "agnet-analytics-worker",
+  "version": "0.1.0",
+  "private": true,
+  "type": "module",
+  "scripts": {
+    "dev": "wrangler dev",
+    "deploy": "node ../scripts/deploy-if-changed.mjs analytics/worker",
+    "setup:notice-kv": "node ../scripts/setup-notice-kv.mjs"
+  },
+  "devDependencies": {
+    "wrangler": "^4.13.2"
+  }
+}

analytics/worker/src/constants.js

@@ -0,0 +1,21 @@
+export const DATASET = 'agnet_analytics';
+export const ALLOWED_EVENTS = new Set(['app_open', 'page_view', 'config_usage', 'ai_request']);
+export const PROJECT_NAME_PATTERN = /^[a-zA-Z0-9._-]{1,80}$/;
+export const NOTICE_KEY_PREFIX = 'project_notice:';
+export const NOTICE_TITLE_MAX_LENGTH = 120;
+export const NOTICE_CONTENT_MAX_LENGTH = 20000;
+export const WORKER_CODE_VERSION = 'notice-time-readable-v1';
+
+export const CONFIG_USAGE_FIELDS = [
+  { key: 'fileParserProviders', blob: 'blob9' },
+  { key: 'realTimeRender', blob: 'blob10' },
+  { key: 'imageProviders', blob: 'blob11' },
+  { key: 'imageModelStatuses', blob: 'blob12' },
+  { key: 'bidAnalysisModes', blob: 'blob13' },
+  { key: 'outlineModes', blob: 'blob14' },
+  { key: 'tableRequirements', blob: 'blob15' },
+  { key: 'useMermaidImages', blob: 'blob16' },
+  { key: 'useAiImages', blob: 'blob17' },
+  { key: 'textModelNames', blob: 'blob18', event: 'ai_request', requestType: 'text' },
+  { key: 'imageModelNames', blob: 'blob19', event: 'ai_request', requestType: 'image' },
+];

analytics/worker/src/http.js

@@ -0,0 +1,30 @@
+export const corsHeaders = {
+  'Access-Control-Allow-Origin': '*',
+  'Access-Control-Allow-Methods': 'GET, POST, DELETE, OPTIONS',
+  'Access-Control-Allow-Headers': 'Content-Type, Authorization',
+  'Access-Control-Max-Age': '86400',
+};
+
+export function json(data, init = {}) {
+  return Response.json(data, {
+    ...init,
+    headers: {
+      ...corsHeaders,
+      ...(init.headers || {}),
+    },
+  });
+}
+
+export function methodNotAllowed() {
+  return json({ code: 405, message: 'method not allowed' }, { status: 405 });
+}
+
+export function unauthorized() {
+  return json({ code: 401, message: 'unauthorized' }, { status: 401 });
+}
+
+export function requireAdmin(request, env) {
+  const token = String(env.ADMIN_TOKEN || '');
+  const authorization = request.headers.get('Authorization') || '';
+  return Boolean(token) && authorization === `Bearer ${token}`;
+}

analytics/worker/src/index.js

@@ -0,0 +1,37 @@
+import { corsHeaders, json } from './http.js';
+import { handleConfigUsage } from './routes/configUsage.js';
+import { handleHealth } from './routes/health.js';
+import { handleLatest } from './routes/latest.js';
+import { handleAdminNotice, handlePublicNotice } from './routes/notice.js';
+import { handleProjects } from './routes/projects.js';
+import { handleRetention } from './routes/retention.js';
+import { handleSummary } from './routes/summary.js';
+import { handleTrack } from './routes/track.js';
+
+const routes = new Map([
+  ['/health', (request, env) => handleHealth(env)],
+  ['/track', handleTrack],
+  ['/notice', handlePublicNotice],
+  ['/api/projects', handleProjects],
+  ['/api/notice', handleAdminNotice],
+  ['/api/summary', handleSummary],
+  ['/api/latest', handleLatest],
+  ['/api/retention', handleRetention],
+  ['/api/config-usage', handleConfigUsage],
+]);
+
+export default {
+  async fetch(request, env) {
+    if (request.method === 'OPTIONS') {
+      return new Response(null, { status: 204, headers: corsHeaders });
+    }
+
+    const url = new URL(request.url);
+    const handler = routes.get(url.pathname);
+    if (handler) {
+      return handler(request, env, url);
+    }
+
+    return json({ code: 404, message: 'not found' }, { status: 404 });
+  },
+};

analytics/worker/src/routes/configUsage.js

@@ -0,0 +1,61 @@
+import { CONFIG_USAGE_FIELDS, DATASET } from '../constants.js';
+import { json, methodNotAllowed, requireAdmin, unauthorized } from '../http.js';
+import { queryAnalytics } from '../services/analyticsQuery.js';
+import { isValidProjectName, logQueryError, normalizeText, safeDays, sqlString } from '../utils.js';
+
+function buildConfigUsageSql(project, days, field) {
+  const event = field.event || 'config_usage';
+  const requestTypeFilter = field.requestType ? `\n      AND blob20 = ${sqlString(field.requestType)}` : '';
+
+  return `
+    SELECT
+      ${field.blob} AS value,
+      COUNT(DISTINCT blob7) AS clients,
+      SUM(_sample_interval) AS events
+    FROM ${DATASET}
+    WHERE blob1 = ${project}
+      AND blob2 = ${sqlString(event)}${requestTypeFilter}
+      AND ${field.blob} != ''
+      AND timestamp >= NOW() - INTERVAL '${days}' DAY
+    GROUP BY value
+    ORDER BY clients DESC, events DESC, value ASC
+    LIMIT 50
+  `;
+}
+
+export async function handleConfigUsage(request, env, url) {
+  if (request.method !== 'GET') {
+    return methodNotAllowed();
+  }
+
+  if (!requireAdmin(request, env)) {
+    return unauthorized();
+  }
+
+  const projectName = normalizeText(url.searchParams.get('projectName'), 80);
+  const days = safeDays(url.searchParams.get('days'));
+
+  if (!isValidProjectName(projectName)) {
+    return json({ code: 400, message: 'invalid projectName' }, { status: 400 });
+  }
+
+  const project = sqlString(projectName);
+
+  try {
+    const results = await Promise.all(CONFIG_USAGE_FIELDS.map((field) => queryAnalytics(env, buildConfigUsageSql(project, days, field))));
+    const usage = {};
+    CONFIG_USAGE_FIELDS.forEach((field, index) => {
+      usage[field.key] = results[index].data || [];
+    });
+
+    return json({
+      code: 0,
+      projectName,
+      days,
+      usage,
+    });
+  } catch (error) {
+    logQueryError('config-usage', error);
+    return json({ code: 500, message: 'query failed' }, { status: 500 });
+  }
+}

analytics/worker/src/routes/health.js

@@ -0,0 +1,12 @@
+import { WORKER_CODE_VERSION } from '../constants.js';
+import { json } from '../http.js';
+
+export function handleHealth(env) {
+  return json({
+    code: 0,
+    ok: true,
+    workerCodeVersion: WORKER_CODE_VERSION,
+    noticeTimeFormat: 'YYYY-MM-DD HH:mm:ss Asia/Shanghai',
+    noticeStoreConfigured: Boolean(env.NOTICE_STORE),
+  });
+}

analytics/worker/src/routes/latest.js

@@ -0,0 +1,66 @@
+import { DATASET } from '../constants.js';
+import { json, methodNotAllowed, requireAdmin, unauthorized } from '../http.js';
+import { queryAnalytics } from '../services/analyticsQuery.js';
+import { isValidProjectName, logQueryError, normalizeText, safePage, sqlString } from '../utils.js';
+
+export async function handleLatest(request, env, url) {
+  if (request.method !== 'GET') {
+    return methodNotAllowed();
+  }
+
+  if (!requireAdmin(request, env)) {
+    return unauthorized();
+  }
+
+  const projectName = normalizeText(url.searchParams.get('projectName'), 80);
+  const page = safePage(url.searchParams.get('page'));
+  const pageSize = 10;
+  const offset = (page - 1) * pageSize;
+
+  if (!isValidProjectName(projectName)) {
+    return json({ code: 400, message: 'invalid projectName' }, { status: 400 });
+  }
+
+  const project = sqlString(projectName);
+
+  const totalSql = `
+    SELECT
+      COUNT() AS total
+    FROM ${DATASET}
+    WHERE blob1 = ${project}
+  `;
+
+  const sql = `
+    SELECT
+      timestamp,
+      blob1 AS projectName,
+      blob2 AS event,
+      blob3 AS page,
+      blob4 AS version,
+      blob5 AS platform,
+      blob6 AS arch,
+      blob7 AS clientId,
+      blob8 AS clientCreatedAt
+    FROM ${DATASET}
+    WHERE blob1 = ${project}
+    ORDER BY timestamp DESC
+    LIMIT ${pageSize} OFFSET ${offset}
+  `;
+
+  try {
+    const [latest, total] = await Promise.all([
+      queryAnalytics(env, sql),
+      queryAnalytics(env, totalSql),
+    ]);
+    return json({
+      code: 0,
+      page,
+      pageSize,
+      total: Number(total.data?.[0]?.total || 0),
+      events: latest.data || [],
+    });
+  } catch (error) {
+    logQueryError('latest', error);
+    return json({ code: 500, message: 'query failed' }, { status: 500 });
+  }
+}

analytics/worker/src/routes/notice.js

@@ -0,0 +1,109 @@
+import { NOTICE_CONTENT_MAX_LENGTH, NOTICE_TITLE_MAX_LENGTH } from '../constants.js';
+import { json, methodNotAllowed, requireAdmin, unauthorized } from '../http.js';
+import { buildNoticeKey, createNoticeId, readProjectNotice } from '../services/noticeStore.js';
+import { formatNoticeTime, isValidProjectName, normalizeText } from '../utils.js';
+
+export async function handlePublicNotice(request, env, url) {
+  if (request.method !== 'GET') {
+    return methodNotAllowed();
+  }
+
+  const projectName = normalizeText(url.searchParams.get('projectName'), 80);
+  if (!isValidProjectName(projectName)) {
+    return json({ code: 400, message: 'invalid projectName' }, { status: 400 });
+  }
+
+  try {
+    const notice = await readProjectNotice(env, projectName);
+    return json({
+      code: 0,
+      notice: notice?.enabled && notice.content ? notice : null,
+    }, { headers: { 'Cache-Control': 'no-store' } });
+  } catch (error) {
+    console.error('[analytics] public notice failed', error?.message || String(error));
+    return json({ code: 0, notice: null }, { headers: { 'Cache-Control': 'no-store' } });
+  }
+}
+
+export async function handleAdminNotice(request, env, url) {
+  if (!requireAdmin(request, env)) {
+    return unauthorized();
+  }
+
+  if (!env.NOTICE_STORE) {
+    return json({ code: 500, message: 'NOTICE_STORE is not configured' }, { status: 500 });
+  }
+
+  if (request.method === 'GET') {
+    return handleAdminGetNotice(env, url);
+  }
+
+  if (request.method === 'POST') {
+    return handleAdminSaveNotice(request, env);
+  }
+
+  if (request.method === 'DELETE') {
+    return handleAdminDeleteNotice(env, url);
+  }
+
+  return methodNotAllowed();
+}
+
+async function handleAdminGetNotice(env, url) {
+  const projectName = normalizeText(url.searchParams.get('projectName'), 80);
+  if (!isValidProjectName(projectName)) {
+    return json({ code: 400, message: 'invalid projectName' }, { status: 400 });
+  }
+
+  const notice = await readProjectNotice(env, projectName);
+  return json({ code: 0, notice }, { headers: { 'Cache-Control': 'no-store' } });
+}
+
+async function handleAdminSaveNotice(request, env) {
+  let body;
+  try {
+    body = await request.json();
+  } catch {
+    return json({ code: 400, message: 'invalid json body' }, { status: 400 });
+  }
+
+  const projectName = normalizeText(body.projectName || body.project_name, 80);
+  const title = normalizeText(body.title, NOTICE_TITLE_MAX_LENGTH);
+  const content = normalizeText(body.content || body.markdown, NOTICE_CONTENT_MAX_LENGTH);
+
+  if (!isValidProjectName(projectName)) {
+    return json({ code: 400, message: 'invalid projectName' }, { status: 400 });
+  }
+
+  if (!title) {
+    return json({ code: 400, message: 'missing title' }, { status: 400 });
+  }
+
+  if (!content) {
+    return json({ code: 400, message: 'missing content' }, { status: 400 });
+  }
+
+  const now = formatNoticeTime();
+  const notice = {
+    id: createNoticeId(now),
+    projectName,
+    enabled: body.enabled !== false,
+    title,
+    content,
+    createdAt: now,
+    updatedAt: now,
+  };
+
+  await env.NOTICE_STORE.put(buildNoticeKey(projectName), JSON.stringify(notice));
+  return json({ code: 0, notice });
+}
+
+async function handleAdminDeleteNotice(env, url) {
+  const projectName = normalizeText(url.searchParams.get('projectName'), 80);
+  if (!isValidProjectName(projectName)) {
+    return json({ code: 400, message: 'invalid projectName' }, { status: 400 });
+  }
+
+  await env.NOTICE_STORE.delete(buildNoticeKey(projectName));
+  return json({ code: 0, notice: null });
+}

analytics/worker/src/routes/projects.js

@@ -0,0 +1,34 @@
+import { DATASET } from '../constants.js';
+import { json, methodNotAllowed, requireAdmin, unauthorized } from '../http.js';
+import { queryAnalytics } from '../services/analyticsQuery.js';
+import { logQueryError } from '../utils.js';
+
+export async function handleProjects(request, env) {
+  if (request.method !== 'GET') {
+    return methodNotAllowed();
+  }
+
+  if (!requireAdmin(request, env)) {
+    return unauthorized();
+  }
+
+  const sql = `
+    SELECT
+      blob1 AS projectName
+    FROM ${DATASET}
+    WHERE timestamp >= NOW() - INTERVAL '90' DAY
+    GROUP BY projectName
+    ORDER BY projectName ASC
+  `;
+
+  try {
+    const result = await queryAnalytics(env, sql);
+    return json({
+      code: 0,
+      projects: (result.data || []).map((item) => item.projectName).filter(Boolean),
+    });
+  } catch (error) {
+    logQueryError('projects', error);
+    return json({ code: 500, message: 'query failed' }, { status: 500 });
+  }
+}

analytics/worker/src/routes/retention.js

@@ -0,0 +1,94 @@
+import { DATASET } from '../constants.js';
+import { json, methodNotAllowed, requireAdmin, unauthorized } from '../http.js';
+import { queryAnalytics } from '../services/analyticsQuery.js';
+import { addIsoDays, datePart, daysSinceIsoDate, isValidProjectName, isoDateDaysAgo, logQueryError, normalizeText, safeDays, sqlString } from '../utils.js';
+
+export async function handleRetention(request, env, url) {
+  if (request.method !== 'GET') {
+    return methodNotAllowed();
+  }
+
+  if (!requireAdmin(request, env)) {
+    return unauthorized();
+  }
+
+  const projectName = normalizeText(url.searchParams.get('projectName'), 80);
+  const days = safeDays(url.searchParams.get('days'));
+
+  if (!isValidProjectName(projectName)) {
+    return json({ code: 400, message: 'invalid projectName' }, { status: 400 });
+  }
+
+  const project = sqlString(projectName);
+  const sql = `
+    SELECT
+      timestamp,
+      blob7 AS clientId,
+      blob8 AS clientCreatedAt
+    FROM ${DATASET}
+    WHERE blob1 = ${project}
+      AND blob2 = 'app_open'
+      AND blob7 != ''
+      AND blob8 != ''
+      AND blob8 >= ${sqlString(isoDateDaysAgo(days))}
+    ORDER BY timestamp ASC
+    LIMIT 50000
+  `;
+
+  try {
+    const result = await queryAnalytics(env, sql);
+    const clients = new Map();
+
+    for (const row of result.data || []) {
+      const clientId = String(row.clientId || '');
+      const clientCreatedAt = datePart(row.clientCreatedAt);
+      const activeDate = datePart(row.timestamp);
+      const age = daysSinceIsoDate(clientCreatedAt);
+      if (!clientId || !clientCreatedAt || !activeDate || !Number.isFinite(age) || age < 0 || age > days) {
+        continue;
+      }
+
+      const client = clients.get(clientId) || { clientCreatedAt, activeDates: new Set() };
+      client.activeDates.add(activeDate);
+      clients.set(clientId, client);
+    }
+
+    const buildRow = (day) => {
+      let cohortClients = 0;
+      let retainedClients = 0;
+
+      for (const client of clients.values()) {
+        const age = daysSinceIsoDate(client.clientCreatedAt);
+        if (!Number.isFinite(age) || age < day || age > days) {
+          continue;
+        }
+
+        cohortClients += 1;
+        if (client.activeDates.has(addIsoDays(client.clientCreatedAt, day))) {
+          retainedClients += 1;
+        }
+      }
+
+      return {
+        day: `D${day}`,
+        cohortClients,
+        retainedClients,
+        retentionRate: cohortClients > 0 ? retainedClients / cohortClients : 0,
+      };
+    };
+
+    return json({
+      code: 0,
+      projectName,
+      days,
+      retention: [
+        buildRow(1),
+        buildRow(3),
+        buildRow(7),
+      ],
+    });
+  } catch (error) {
+    logQueryError('retention', error);
+    return json({ code: 500, message: 'query failed' }, { status: 500 });
+  }
+}

analytics/worker/src/routes/summary.js

@@ -0,0 +1,174 @@
+import { DATASET } from '../constants.js';
+import { json, methodNotAllowed, requireAdmin, unauthorized } from '../http.js';
+import { queryAnalytics } from '../services/analyticsQuery.js';
+import { isValidProjectName, isoDateDaysAgo, logQueryError, normalizeText, safeDays, sqlString } from '../utils.js';
+
+export async function handleSummary(request, env, url) {
+  if (request.method !== 'GET') {
+    return methodNotAllowed();
+  }
+
+  if (!requireAdmin(request, env)) {
+    return unauthorized();
+  }
+
+  const projectName = normalizeText(url.searchParams.get('projectName'), 80);
+  const days = safeDays(url.searchParams.get('days'));
+
+  if (!isValidProjectName(projectName)) {
+    return json({ code: 400, message: 'invalid projectName' }, { status: 400 });
+  }
+
+  const project = sqlString(projectName);
+  const dailySql = `
+    SELECT
+      toDate(timestamp) AS date,
+      blob2 AS event,
+      SUM(_sample_interval) AS count
+    FROM ${DATASET}
+    WHERE blob1 = ${project}
+      AND blob2 IN ('app_open', 'page_view')
+      AND timestamp >= NOW() - INTERVAL '${days}' DAY
+    GROUP BY date, event
+    ORDER BY date ASC, event ASC
+  `;
+
+  const dailyClientsSql = `
+    SELECT
+      toDate(timestamp) AS date,
+      COUNT(DISTINCT blob7) AS clients
+    FROM ${DATASET}
+    WHERE blob1 = ${project}
+      AND blob2 IN ('app_open', 'page_view')
+      AND blob7 != ''
+      AND timestamp >= NOW() - INTERVAL '${days}' DAY
+    GROUP BY date
+    ORDER BY date ASC
+  `;
+
+  const pagesSql = `
+    SELECT
+      blob3 AS page,
+      SUM(_sample_interval) AS count
+    FROM ${DATASET}
+    WHERE blob1 = ${project}
+      AND blob2 = 'page_view'
+      AND timestamp >= NOW() - INTERVAL '${days}' DAY
+    GROUP BY page
+    ORDER BY count DESC
+    LIMIT 100
+  `;
+
+  const versionsSql = `
+    SELECT
+      blob4 AS version,
+      COUNT(DISTINCT blob7) AS clients,
+      SUM(_sample_interval) AS count
+    FROM ${DATASET}
+    WHERE blob1 = ${project}
+      AND blob4 != ''
+      AND blob7 != ''
+      AND timestamp >= NOW() - INTERVAL '${days}' DAY
+    GROUP BY version
+    ORDER BY version DESC
+    LIMIT 50
+  `;
+
+  const totalClientsSql = `
+    SELECT
+      COUNT(DISTINCT blob7) AS totalClients
+    FROM ${DATASET}
+    WHERE blob1 = ${project}
+      AND blob7 != ''
+  `;
+
+  const todayActiveClientsSql = `
+    SELECT
+      COUNT(DISTINCT blob7) AS todayActiveClients
+    FROM ${DATASET}
+    WHERE blob1 = ${project}
+      AND blob7 != ''
+      AND toDate(timestamp) = toDate(NOW())
+  `;
+
+  const wauSql = `
+    SELECT
+      COUNT(DISTINCT blob7) AS wau
+    FROM ${DATASET}
+    WHERE blob1 = ${project}
+      AND blob7 != ''
+      AND timestamp >= NOW() - INTERVAL '7' DAY
+  `;
+
+  const mauSql = `
+    SELECT
+      COUNT(DISTINCT blob7) AS mau
+    FROM ${DATASET}
+    WHERE blob1 = ${project}
+      AND blob7 != ''
+      AND timestamp >= NOW() - INTERVAL '30' DAY
+  `;
+
+  const activeClientsSql = `
+    SELECT
+      COUNT(DISTINCT blob7) AS activeClients
+    FROM ${DATASET}
+    WHERE blob1 = ${project}
+      AND blob7 != ''
+      AND timestamp >= NOW() - INTERVAL '${days}' DAY
+  `;
+
+  const newClientsSql = `
+    SELECT
+      COUNT(DISTINCT blob7) AS newClients
+    FROM ${DATASET}
+    WHERE blob1 = ${project}
+      AND blob7 != ''
+      AND blob8 != ''
+      AND blob8 >= ${sqlString(isoDateDaysAgo(days))}
+      AND timestamp >= NOW() - INTERVAL '${days}' DAY
+  `;
+
+  try {
+    const [daily, dailyClients, pages, versions, totalClients, todayActiveClients, wau, mau, activeClients, newClients] = await Promise.all([
+      queryAnalytics(env, dailySql),
+      queryAnalytics(env, dailyClientsSql),
+      queryAnalytics(env, pagesSql),
+      queryAnalytics(env, versionsSql),
+      queryAnalytics(env, totalClientsSql),
+      queryAnalytics(env, todayActiveClientsSql),
+      queryAnalytics(env, wauSql),
+      queryAnalytics(env, mauSql),
+      queryAnalytics(env, activeClientsSql),
+      queryAnalytics(env, newClientsSql),
+    ]);
+    const clientStats = {
+      totalClients: Number(totalClients.data?.[0]?.totalClients || 0),
+      todayActiveClients: Number(todayActiveClients.data?.[0]?.todayActiveClients || 0),
+      wau: Number(wau.data?.[0]?.wau || 0),
+      mau: Number(mau.data?.[0]?.mau || 0),
+      activeClients: Number(activeClients.data?.[0]?.activeClients || 0),
+      newClients: Number(newClients.data?.[0]?.newClients || 0),
+    };
+
+    return json({
+      code: 0,
+      projectName,
+      days,
+      totalClients: clientStats.totalClients,
+      todayActiveClients: clientStats.todayActiveClients,
+      wau: clientStats.wau,
+      mau: clientStats.mau,
+      activeClients: clientStats.activeClients,
+      newClients: clientStats.newClients,
+      returningClients: Math.max(0, clientStats.activeClients - clientStats.newClients),
+      daily: daily.data || [],
+      dailyClients: dailyClients.data || [],
+      pages: pages.data || [],
+      versions: versions.data || [],
+    });
+  } catch (error) {
+    logQueryError('summary', error);
+    return json({ code: 500, message: 'query failed' }, { status: 500 });
+  }
+}

analytics/worker/src/routes/track.js

@@ -0,0 +1,76 @@
+import { ALLOWED_EVENTS } from '../constants.js';
+import { json, methodNotAllowed } from '../http.js';
+import { isValidProjectName, normalizeMetricValue, normalizeText } from '../utils.js';
+
+export async function handleTrack(request, env) {
+  if (request.method !== 'POST') {
+    return methodNotAllowed();
+  }
+
+  try {
+    const body = await request.json();
+    const projectName = normalizeText(body.projectName || body.project_name, 80);
+    const event = normalizeText(body.event, 50);
+    const page = normalizeText(body.page, 120);
+    const version = normalizeText(body.version, 50);
+    const platform = normalizeText(body.platform, 50);
+    const arch = normalizeText(body.arch, 50);
+    const clientId = normalizeText(body.client_id || body.clientId, 120);
+    const clientCreatedAt = normalizeText(body.client_created_at || body.clientCreatedAt, 20);
+    const fileParserProvider = normalizeText(body.file_parser_provider || body.fileParserProvider, 50);
+    const realTimeRender = normalizeMetricValue(body.real_time_render ?? body.realTimeRender, 20);
+    const imageProvider = normalizeText(body.image_provider || body.imageProvider, 50);
+    const imageModelStatus = normalizeText(body.image_model_status || body.imageModelStatus, 50);
+    const bidAnalysisMode = normalizeText(body.bid_analysis_mode || body.bidAnalysisMode, 50);
+    const outlineMode = normalizeText(body.outline_mode || body.outlineMode, 50);
+    const tableRequirement = normalizeText(body.table_requirement || body.tableRequirement, 50);
+    const useMermaidImages = normalizeMetricValue(body.use_mermaid_images ?? body.useMermaidImages, 20);
+    const useAiImages = normalizeMetricValue(body.use_ai_images ?? body.useAiImages, 20);
+    const textModelName = normalizeText(body.text_model_name || body.textModelName, 120);
+    const imageModelName = normalizeText(body.image_model_name || body.imageModelName, 120);
+    const aiRequestType = normalizeText(body.ai_request_type || body.aiRequestType, 20);
+
+    if (!isValidProjectName(projectName)) {
+      return json({ code: 400, message: 'invalid projectName' }, { status: 400 });
+    }
+
+    if (!ALLOWED_EVENTS.has(event)) {
+      return json({ code: 400, message: 'invalid event' }, { status: 400 });
+    }
+
+    if (event === 'page_view' && !page) {
+      return json({ code: 400, message: 'missing page' }, { status: 400 });
+    }
+
+    env.ANALYTICS.writeDataPoint({
+      blobs: [
+        projectName,
+        event,
+        page,
+        version,
+        platform,
+        arch,
+        clientId,
+        clientCreatedAt,
+        fileParserProvider,
+        realTimeRender,
+        imageProvider,
+        imageModelStatus,
+        bidAnalysisMode,
+        outlineMode,
+        tableRequirement,
+        useMermaidImages,
+        useAiImages,
+        textModelName,
+        imageModelName,
+        aiRequestType,
+      ],
+      doubles: [1],
+      indexes: [projectName],
+    });
+
+    return json({ code: 0 });
+  } catch {
+    return json({ code: 500, message: 'internal error' }, { status: 500 });
+  }
+}

analytics/worker/src/services/analyticsQuery.js

@@ -0,0 +1,20 @@
+export async function queryAnalytics(env, sql) {
+  if (!env.ACCOUNT_ID || !env.ANALYTICS_API_TOKEN) {
+    throw new Error('missing analytics api config');
+  }
+
+  const api = `https://api.cloudflare.com/client/v4/accounts/${env.ACCOUNT_ID}/analytics_engine/sql`;
+  const response = await fetch(api, {
+    method: 'POST',
+    headers: {
+      Authorization: `Bearer ${env.ANALYTICS_API_TOKEN}`,
+    },
+    body: sql,
+  });
+
+  if (!response.ok) {
+    throw new Error(await response.text());
+  }
+
+  return response.json();
+}

analytics/worker/src/services/noticeStore.js

@@ -0,0 +1,47 @@
+import { NOTICE_CONTENT_MAX_LENGTH, NOTICE_KEY_PREFIX, NOTICE_TITLE_MAX_LENGTH } from '../constants.js';
+import { normalizeText } from '../utils.js';
+
+export function buildNoticeKey(projectName) {
+  return `${NOTICE_KEY_PREFIX}${projectName}`;
+}
+
+export function createNoticeId(now) {
+  const timestamp = now.replace(/[-: ]/g, '').slice(0, 14);
+  const random = typeof globalThis.crypto?.randomUUID === 'function'
+    ? globalThis.crypto.randomUUID().slice(0, 8)
+    : Math.random().toString(36).slice(2, 10);
+  return `notice-${timestamp}-${random}`;
+}
+
+export function normalizeNoticeForResponse(notice) {
+  if (!notice || typeof notice !== 'object') {
+    return null;
+  }
+
+  return {
+    id: normalizeText(notice.id, 80),
+    projectName: normalizeText(notice.projectName, 80),
+    enabled: notice.enabled !== false,
+    title: normalizeText(notice.title, NOTICE_TITLE_MAX_LENGTH),
+    content: normalizeText(notice.content, NOTICE_CONTENT_MAX_LENGTH),
+    createdAt: normalizeText(notice.createdAt, 40),
+    updatedAt: normalizeText(notice.updatedAt, 40),
+  };
+}
+
+export async function readProjectNotice(env, projectName) {
+  if (!env.NOTICE_STORE) {
+    return null;
+  }
+
+  const raw = await env.NOTICE_STORE.get(buildNoticeKey(projectName));
+  if (!raw) {
+    return null;
+  }
+
+  try {
+    return normalizeNoticeForResponse(JSON.parse(raw));
+  } catch {
+    return null;
+  }
+}

analytics/worker/src/utils.js

@@ -0,0 +1,77 @@
+import { PROJECT_NAME_PATTERN } from './constants.js';
+
+export function normalizeText(value, maxLength) {
+  return String(value || '').trim().slice(0, maxLength);
+}
+
+export function normalizeMetricValue(value, maxLength) {
+  if (value === true) return 'true';
+  if (value === false) return 'false';
+  return normalizeText(value, maxLength);
+}
+
+export function isValidProjectName(projectName) {
+  return PROJECT_NAME_PATTERN.test(projectName);
+}
+
+export function safeDays(value) {
+  const days = Number(value || 30);
+  if (!Number.isFinite(days)) return 30;
+  return Math.max(1, Math.min(Math.floor(days), 90));
+}
+
+export function safePage(value) {
+  const page = Number(value || 1);
+  if (!Number.isFinite(page)) return 1;
+  return Math.max(1, Math.floor(page));
+}
+
+export function isoDateDaysAgo(days) {
+  const date = new Date();
+  date.setUTCDate(date.getUTCDate() - days);
+  return date.toISOString().slice(0, 10);
+}
+
+export function daysSinceIsoDate(value) {
+  const date = new Date(`${String(value || '').slice(0, 10)}T00:00:00.000Z`);
+  if (Number.isNaN(date.getTime())) return NaN;
+
+  const now = new Date();
+  const todayUtc = Date.UTC(now.getUTCFullYear(), now.getUTCMonth(), now.getUTCDate());
+  return Math.floor((todayUtc - date.getTime()) / 86400000);
+}
+
+export function addIsoDays(value, days) {
+  const date = new Date(`${String(value || '').slice(0, 10)}T00:00:00.000Z`);
+  if (Number.isNaN(date.getTime())) return '';
+
+  date.setUTCDate(date.getUTCDate() + days);
+  return date.toISOString().slice(0, 10);
+}
+
+export function datePart(value) {
+  return String(value || '').slice(0, 10);
+}
+
+export function logQueryError(scope, error) {
+  console.error(`[analytics] ${scope} query failed`, error?.message || String(error));
+}
+
+export function sqlString(value) {
+  return `'${String(value).replace(/\\/g, '\\\\').replace(/'/g, "\\'")}'`;
+}
+
+export function formatNoticeTime(date = new Date()) {
+  const parts = new Intl.DateTimeFormat('zh-CN', {
+    timeZone: 'Asia/Shanghai',
+    year: 'numeric',
+    month: '2-digit',
+    day: '2-digit',
+    hour: '2-digit',
+    minute: '2-digit',
+    second: '2-digit',
+    hour12: false,
+  }).formatToParts(date);
+  const values = Object.fromEntries(parts.map((part) => [part.type, part.value]));
+  return `${values.year}-${values.month}-${values.day} ${values.hour}:${values.minute}:${values.second}`;
+}

analytics/worker/wrangler.jsonc

@@ -0,0 +1,20 @@
+{
+  "$schema": "node_modules/wrangler/config-schema.json",
+  "name": "agnet-analytics-api",
+  "main": "src/index.js",
+  "compatibility_date": "2026-05-14",
+  "workers_dev": true,
+  "keep_vars": true,
+  "routes": [
+    {
+      "pattern": "analytics.agnet.top",
+      "custom_domain": true
+    }
+  ],
+  "analytics_engine_datasets": [
+    {
+      "binding": "ANALYTICS",
+      "dataset": "agnet_analytics"
+    }
+  ]
+}

archive/app_launcher.py

@@ -0,0 +1,171 @@
+"""应用启动器 - 适配backend结构的统一启动文件"""
+import os
+import sys
+import time
+import threading
+import webbrowser
+import signal
+import atexit
+from pathlib import Path
+
+# 设置工作目录和模块路径
+if getattr(sys, 'frozen', False):
+    # 打包后的环境
+    if hasattr(sys, '_MEIPASS'):
+        base_dir = Path(sys._MEIPASS)
+        backend_dir = base_dir / "backend"
+    else:
+        base_dir = Path(sys.executable).parent
+        backend_dir = base_dir / "backend"
+else:
+    # 开发环境
+    base_dir = Path(__file__).parent
+    backend_dir = base_dir / "backend"
+
+if backend_dir.exists():
+    os.chdir(backend_dir)
+    sys.path.insert(0, str(backend_dir))
+else:
+    print(f"ERROR: backend目录不存在: {backend_dir}")
+    input("按回车键退出...")
+
+# 全局变量用于进程管理
+uvicorn_server = None
+server_thread = None
+server_should_stop = False
+
+def cleanup_server():
+    """清理服务器进程"""
+    global uvicorn_server, server_thread, server_should_stop
+    
+    print("正在关闭服务器...")
+    server_should_stop = True
+    
+    # 尝试优雅关闭uvicorn服务器
+    if uvicorn_server:
+        try:
+            uvicorn_server.should_exit = True
+            print("服务器已设置关闭标志")
+        except:
+            pass
+    
+    # 强制终止占用8000端口的进程
+    try:
+        import subprocess
+        # 查找占用8000端口的进程
+        result = subprocess.run(['netstat', '-ano'], capture_output=True, text=True)
+        for line in result.stdout.split('\n'):
+            if ':8000' in line and 'LISTENING' in line:
+                parts = line.split()
+                if len(parts) >= 5:
+                    pid = parts[-1]
+                    try:
+                        subprocess.run(['taskkill', '/F', '/PID', pid], 
+                                     capture_output=True, check=True)
+                        print(f"已终止占用8000端口的进程 PID: {pid}")
+                    except:
+                        pass
+    except:
+        pass
+
+def signal_handler(signum, frame):
+    """信号处理器"""
+    print(f"\n收到信号 {signum}，正在关闭服务...")
+    cleanup_server()
+    sys.exit(0)
+
+def main():
+    """主函数"""
+    global uvicorn_server, server_thread, server_should_stop
+    
+    print("="*50)
+    print("AI写标书助手 - 启动中...")
+    print("="*50)
+    
+    # 注册信号处理器
+    if hasattr(signal, 'SIGTERM'):
+        signal.signal(signal.SIGTERM, signal_handler)
+    if hasattr(signal, 'SIGINT'):
+        signal.signal(signal.SIGINT, signal_handler)
+    
+    # 注册退出处理器
+    atexit.register(cleanup_server)
+    
+    try:
+        print("OK: 切换到backend目录")
+        print("启动服务器...")
+        
+        def start_server():
+            global uvicorn_server, server_should_stop
+            try:
+                import uvicorn
+                # 动态导入app.main模块
+                try:
+                    from app.main import app
+                except ImportError as ie:
+                    print(f"ERROR: 无法导入app.main: {ie}")
+                    print(f"当前工作目录: {os.getcwd()}")
+                    print(f"Python路径: {sys.path[:3]}")
+                    raise ie
+                
+                # 创建uvicorn配置
+                config = uvicorn.Config(app, host="127.0.0.1", port=8000, log_level="warning")
+                uvicorn_server = uvicorn.Server(config)
+                
+                # 运行服务器
+                uvicorn_server.run()
+                
+            except Exception as e:
+                if not server_should_stop:
+                    print(f"ERROR: 服务启动失败: {e}")
+                    import traceback
+                    traceback.print_exc()
+        
+        # 创建非守护线程，但添加退出处理
+        server_thread = threading.Thread(target=start_server, daemon=False)
+        server_thread.start()
+        
+        print("等待服务启动...")
+        time.sleep(5)
+        
+        def open_browser():
+            if not server_should_stop:
+                time.sleep(2)
+                try:
+                    webbrowser.open('http://localhost:8000')
+                    print("浏览器已打开")
+                except Exception as e:
+                    print(f"打开浏览器失败: {e}")
+        
+        browser_thread = threading.Thread(target=open_browser, daemon=True)
+        browser_thread.start()
+        
+        print("\n" + "="*50)
+        print("服务启动完成！")
+        print("访问地址: http://localhost:8000")
+        print("API文档: http://localhost:8000/docs")
+        print("健康检查: http://localhost:8000/health")
+        print("="*50)
+        print("\n完整功能已集成，关闭此窗口会自动停止服务")
+        print("按 Ctrl+C 可以安全退出")
+        print("="*50)
+        
+        # 等待服务器线程，或者直到收到退出信号
+        try:
+            while server_thread.is_alive() and not server_should_stop:
+                time.sleep(1)
+        except KeyboardInterrupt:
+            print("\n收到退出信号...")
+            
+    except KeyboardInterrupt:
+        print("\n服务已关闭")
+    except Exception as e:
+        print(f"运行时错误: {e}")
+        import traceback
+        traceback.print_exc()
+    finally:
+        cleanup_server()
+        print("程序已退出")
+
+if __name__ == "__main__":
+    main()

archive/backend/.env.example

@@ -0,0 +1 @@
+# ENABLE_FILE_LOGGING=true

archive/backend/app/config.py

@@ -0,0 +1,48 @@
+"""应用配置管理"""
+
+try:
+    from pydantic_settings import BaseSettings
+except ImportError:
+    from pydantic import BaseSettings
+from typing import Optional
+import os
+
+
+class Settings(BaseSettings):
+    """应用设置"""
+
+    app_name: str = "AI写标书助手"
+    app_version: str = "2.0.0"
+    debug: bool = False
+    enable_file_logging: bool = False
+
+    # CORS设置
+    cors_origins: list = [
+        "http://localhost:3000",
+        "http://127.0.0.1:3000",
+        "http://localhost:3001",
+        "http://127.0.0.1:3001",
+        "http://localhost:3002",
+        "http://127.0.0.1:3002",
+        "http://localhost:3003",
+        "http://127.0.0.1:3003",
+        "http://localhost:3004",
+        "http://127.0.0.1:3004",
+    ]
+
+    # 文件上传设置
+    max_file_size: int = 10 * 1024 * 1024  # 10MB
+    upload_dir: str = "uploads"
+
+    # OpenAI默认设置
+    default_model: str = "gpt-3.5-turbo"
+
+    class Config:
+        env_file = ".env"
+
+
+# 全局设置实例
+settings = Settings()
+
+# 确保上传目录存在
+os.makedirs(settings.upload_dir, exist_ok=True)

archive/backend/app/main.py

@@ -0,0 +1,94 @@
+"""FastAPI应用主入口"""
+
+import os
+
+from fastapi import FastAPI
+from fastapi.middleware.cors import CORSMiddleware
+from fastapi.responses import FileResponse
+from fastapi.staticfiles import StaticFiles
+
+from .config import settings
+from .utils.logging_setup import setup_logging
+
+setup_logging(settings.enable_file_logging)
+
+from .routers import config, document, outline, content, expand
+
+# 创建FastAPI应用实例
+app = FastAPI(
+    title=settings.app_name,
+    version=settings.app_version,
+    description="基于FastAPI的AI写标书助手后端API",
+)
+
+# 添加CORS中间件
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=settings.cors_origins,
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+# 注册路由
+app.include_router(config.router)
+app.include_router(document.router)
+app.include_router(outline.router)
+app.include_router(content.router)
+app.include_router(expand.router)
+
+
+# 健康检查端点
+@app.get("/health")
+async def health_check():
+    """健康检查"""
+    return {
+        "status": "healthy",
+        "app_name": settings.app_name,
+        "version": settings.app_version,
+    }
+
+
+# 静态文件服务（用于服务前端构建文件）
+if os.path.exists("static"):
+    # 挂载静态资源文件夹
+    app.mount("/static", StaticFiles(directory="static/static"), name="static")
+
+    # 处理React应用的路由（SPA路由支持）
+    @app.get("/")
+    async def read_index():
+        """根路径，返回前端首页"""
+        return FileResponse("static/index.html")
+
+    @app.get("/{full_path:path}")
+    async def serve_react_app(full_path: str):
+        """处理React路由，所有非API路径都返回index.html"""
+        # 排除API路径
+        if (
+            full_path.startswith("api/")
+            or full_path.startswith("docs")
+            or full_path.startswith("health")
+        ):
+            # 这些路径应该由FastAPI处理，如果到这里说明404
+            from fastapi import HTTPException
+
+            raise HTTPException(status_code=404, detail="接口不存在")
+
+        # 检查是否是静态文件
+        static_file_path = os.path.join("static", full_path)
+        if os.path.exists(static_file_path) and os.path.isfile(static_file_path):
+            return FileResponse(static_file_path)
+
+        # 对于其他所有路径，返回React应用的index.html（SPA路由）
+        return FileResponse("static/index.html")
+else:
+    # 如果没有静态文件，返回API信息
+    @app.get("/")
+    async def read_root():
+        """根路径，返回API信息"""
+        return {
+            "message": f"欢迎使用 {settings.app_name} API",
+            "version": settings.app_version,
+            "docs": "/docs",
+            "health": "/health",
+        }

archive/backend/app/models/schemas.py

@@ -0,0 +1,173 @@
+"""数据模型定义"""
+
+from enum import Enum
+from typing import Any, Dict, List, Optional
+
+from pydantic import BaseModel, Field
+
+
+class ConfigRequest(BaseModel):
+    """OpenAI配置请求"""
+
+    model_config = {"protected_namespaces": ()}
+
+    api_key: str = Field(..., description="OpenAI API密钥")
+    base_url: Optional[str] = Field(None, description="Base URL")
+    model_name: str = Field("gpt-3.5-turbo", description="模型名称")
+
+
+class ConfigResponse(BaseModel):
+    """配置响应"""
+
+    success: bool
+    message: str
+
+
+class ModelListResponse(BaseModel):
+    """模型列表响应"""
+
+    models: List[str]
+    success: bool
+    message: str = ""
+
+
+class FileUploadResponse(BaseModel):
+    """文件上传响应"""
+
+    success: bool
+    message: str
+    file_content: Optional[str] = None
+    old_outline: Optional[str] = None
+
+
+class AnalysisType(str, Enum):
+    """分析类型"""
+
+    OVERVIEW = "overview"
+    REQUIREMENTS = "requirements"
+
+
+class OutlineMode(str, Enum):
+    """目录生成模式。"""
+
+    FREE = "free"
+    ALIGNED = "aligned"
+
+
+class AnalysisRequest(BaseModel):
+    """文档分析请求"""
+
+    file_content: str = Field(..., description="文档内容")
+    analysis_type: AnalysisType = Field(..., description="分析类型")
+
+
+class OutlineItem(BaseModel):
+    """目录项"""
+
+    id: str
+    title: str
+    description: str
+    source_requirement_id: Optional[str] = None
+    source_requirement_title: Optional[str] = None
+    children: Optional[List["OutlineItem"]] = None
+    content: Optional[str] = None
+
+
+# 解决循环引用
+OutlineItem.model_rebuild()
+
+
+class OutlineResponse(BaseModel):
+    """目录响应"""
+
+    outline: List[OutlineItem]
+
+
+class OutlineChildrenResponse(BaseModel):
+    """指定一级目录下的子目录响应。"""
+
+    children: List[OutlineItem]
+
+
+class OutlineReviewResponse(BaseModel):
+    """目录审核响应。"""
+
+    passed: bool
+    suggestions: List[str] = Field(default_factory=list)
+
+
+class TechnicalRequirementGroup(BaseModel):
+    """技术评分大类。"""
+
+    requirement_id: str
+    title: str
+    description: str
+    detail_points: List[str] = Field(default_factory=list)
+
+
+class TechnicalRequirementGroupResponse(BaseModel):
+    """技术评分大类提取响应。"""
+
+    groups: List[TechnicalRequirementGroup]
+
+
+class OutlineRequest(BaseModel):
+    """目录生成请求"""
+
+    overview: str = Field(..., description="项目概述")
+    requirements: str = Field(..., description="技术评分要求")
+    mode: OutlineMode = Field(OutlineMode.FREE, description="目录生成模式")
+    uploaded_expand: Optional[bool] = Field(False, description="是否已上传方案扩写文件")
+    old_outline: Optional[str] = Field(
+        None, description="上传的方案扩写文件解析出的旧目录JSON"
+    )
+    old_document: Optional[str] = Field(
+        None, description="上传的方案扩写文件解析出的旧文档"
+    )
+
+
+class ContentGenerationRequest(BaseModel):
+    """内容生成请求"""
+
+    outline: Dict[str, Any] = Field(..., description="目录结构")
+    project_overview: str = Field("", description="项目概述")
+
+
+class ChapterContentRequest(BaseModel):
+    """单章节内容生成请求"""
+
+    chapter: Dict[str, Any] = Field(..., description="章节信息")
+    parent_chapters: Optional[List[Dict[str, Any]]] = Field(
+        None, description="上级章节列表"
+    )
+    sibling_chapters: Optional[List[Dict[str, Any]]] = Field(
+        None, description="同级章节列表"
+    )
+    project_overview: str = Field("", description="项目概述")
+
+
+class ErrorResponse(BaseModel):
+    """错误响应"""
+
+    error: str
+    detail: Optional[str] = None
+
+
+class WordExportOutlineItem(BaseModel):
+    """Word 导出用目录项。"""
+
+    id: str
+    title: str
+    description: Optional[str] = None
+    children: Optional[List["WordExportOutlineItem"]] = None
+    content: Optional[str] = None
+
+
+WordExportOutlineItem.model_rebuild()
+
+
+class WordExportRequest(BaseModel):
+    """Word导出请求"""
+
+    project_name: Optional[str] = Field(None, description="项目名称")
+    outline: List[WordExportOutlineItem] = Field(..., description="目录结构，包含内容")

archive/backend/app/routers/config.py

@@ -0,0 +1,83 @@
+"""配置相关API路由"""
+
+import logging
+
+from fastapi import APIRouter, HTTPException
+from ..models.schemas import ConfigRequest, ConfigResponse, ModelListResponse
+from ..services.model_service import ModelService
+from ..utils.config_manager import config_manager
+from ..utils.errors import AppError
+
+logger = logging.getLogger(__name__)
+
+router = APIRouter(prefix="/api/config", tags=["配置管理"])
+
+
+@router.post("/save", response_model=ConfigResponse)
+async def save_config(config: ConfigRequest):
+    """保存OpenAI配置"""
+    try:
+        success = config_manager.save_config(
+            api_key=config.api_key,
+            base_url=config.base_url or "",
+            model_name=config.model_name,
+        )
+
+        if success:
+            return ConfigResponse(success=True, message="配置保存成功")
+        else:
+            return ConfigResponse(success=False, message="配置保存失败")
+
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"保存配置时发生错误: {str(e)}")
+
+
+@router.get("/load", response_model=ConfigRequest)
+async def load_config():
+    """加载保存的配置"""
+    try:
+        config = config_manager.load_config()
+        return config
+    except Exception as e:
+        logger.exception("加载配置失败")
+        raise HTTPException(status_code=500, detail=f"加载配置时发生错误: {str(e)}")
+
+
+@router.post("/models", response_model=ModelListResponse)
+async def get_available_models(config: ConfigRequest):
+    """获取可用的模型列表"""
+    try:
+        if not config.api_key:
+            return ModelListResponse(
+                models=[], success=False, message="请先输入API Key"
+            )
+
+        # 临时保存配置以供模型服务使用
+        temp_saved = config_manager.save_config(
+            api_key=config.api_key,
+            base_url=config.base_url,
+            model_name=config.model_name,
+        )
+
+        if not temp_saved:
+            return ModelListResponse(
+                models=[], success=False, message="保存临时配置失败"
+            )
+
+        # 创建模型服务实例
+        model_service = ModelService()
+
+        # 获取模型列表
+        models = await model_service.get_available_models()
+
+        return ModelListResponse(
+            models=models, success=True, message=f"获取到 {len(models)} 个模型"
+        )
+
+    except AppError as e:
+        return ModelListResponse(models=[], success=False, message=e.message)
+    except Exception as e:
+        logger.exception("获取模型列表失败")
+        return ModelListResponse(
+            models=[], success=False, message=f"获取模型列表失败: {str(e)}"
+        )

archive/backend/app/routers/content.py

@@ -0,0 +1,61 @@
+"""内容相关 API 路由。"""
+
+import logging
+
+from fastapi import APIRouter, HTTPException
+
+from ..models.schemas import ChapterContentRequest
+from ..services.content_service import ContentService
+from ..utils.errors import AppError
+from ..utils.sse import sse_chunk, sse_done, sse_error, sse_response
+
+logger = logging.getLogger(__name__)
+
+router = APIRouter(prefix="/api/content", tags=["内容管理"])
+
+
+@router.post("/generate-chapter")
+async def generate_chapter_content(request: ChapterContentRequest):
+    """为单个章节生成完整内容。"""
+    try:
+        content_service = ContentService()
+        content = await content_service.generate_chapter_content(
+            chapter=request.chapter,
+            parent_chapters=request.parent_chapters,
+            sibling_chapters=request.sibling_chapters,
+            project_overview=request.project_overview,
+        )
+        return {"success": True, "content": content}
+    except AppError as exc:
+        raise HTTPException(status_code=exc.status_code, detail=exc.message) from exc
+    except Exception as exc:
+        logger.exception("章节内容生成失败")
+        raise HTTPException(status_code=500, detail=f"章节内容生成失败: {exc}") from exc
+
+
+@router.post("/generate-chapter-stream")
+async def generate_chapter_content_stream(request: ChapterContentRequest):
+    """流式生成单章节内容。"""
+    try:
+        content_service = ContentService()
+    except AppError as exc:
+        raise HTTPException(status_code=exc.status_code, detail=exc.message) from exc
+
+    async def generate():
+        try:
+            async for chunk in content_service.stream_chapter_content(
+                chapter=request.chapter,
+                parent_chapters=request.parent_chapters,
+                sibling_chapters=request.sibling_chapters,
+                project_overview=request.project_overview,
+            ):
+                yield sse_chunk(chunk)
+        except AppError as exc:
+            yield sse_error(exc.message)
+        except Exception:
+            logger.exception("章节内容流式生成失败")
+            yield sse_error("章节内容生成失败，请稍后重试")
+        finally:
+            yield sse_done()
+
+    return sse_response(generate())

archive/backend/app/routers/document.py

@@ -0,0 +1,78 @@
+"""文档处理相关 API 路由。"""
+
+import logging
+
+from fastapi import APIRouter, File, HTTPException, UploadFile
+from fastapi.responses import StreamingResponse
+
+from ..models.schemas import AnalysisRequest, FileUploadResponse, WordExportRequest
+from ..services.file_service import FileService
+from ..services.analysis_service import AnalysisService
+from ..services.word_export_service import WordExportService
+from ..utils.errors import AppError
+from ..utils.sse import sse_chunk, sse_done, sse_error, sse_response
+
+logger = logging.getLogger(__name__)
+
+router = APIRouter(prefix="/api/document", tags=["文档处理"])
+
+
+@router.post("/upload", response_model=FileUploadResponse)
+async def upload_file(file: UploadFile = File(...)):
+    """上传文档文件并提取文本内容。"""
+    try:
+        if not FileService.is_supported_document(file.content_type):
+            return FileUploadResponse(
+                success=False, message="不支持的文件类型，请上传PDF或Word文档"
+            )
+
+        file_content = await FileService.process_uploaded_file(file)
+        return FileUploadResponse(
+            success=True,
+            message=f"文件 {file.filename} 上传成功",
+            file_content=file_content,
+        )
+    except Exception as exc:
+        logger.exception("文件上传失败")
+        return FileUploadResponse(success=False, message=f"文件处理失败: {exc}")
+
+
+@router.post("/analyze-stream")
+async def analyze_document_stream(request: AnalysisRequest):
+    """流式分析文档内容。"""
+    try:
+        analysis_service = AnalysisService()
+    except AppError as exc:
+        raise HTTPException(status_code=exc.status_code, detail=exc.message) from exc
+
+    async def generate():
+        try:
+            async for chunk in analysis_service.stream_document_analysis(
+                file_content=request.file_content,
+                analysis_type=request.analysis_type.value,
+            ):
+                yield sse_chunk(chunk)
+        except AppError as exc:
+            yield sse_error(exc.message)
+        except Exception:
+            logger.exception("文档分析失败")
+            yield sse_error("文档分析失败，请稍后重试")
+        finally:
+            yield sse_done()
+
+    return sse_response(generate())
+
+
+@router.post("/export-word")
+async def export_word(request: WordExportRequest):
+    """根据目录数据导出 Word 文档。"""
+    try:
+        buffer, headers = WordExportService.export_outline(request)
+        return StreamingResponse(
+            buffer,
+            media_type="application/vnd.openxmlformats-officedocument.wordprocessingml.document",
+            headers=headers,
+        )
+    except Exception as exc:
+        logger.exception("导出 Word 失败")
+        raise HTTPException(status_code=500, detail=f"导出Word失败: {exc}") from exc

archive/backend/app/routers/expand.py

@@ -0,0 +1,40 @@
+"""标书扩写相关 API 路由。"""
+
+import json
+import logging
+
+from fastapi import APIRouter, File, UploadFile
+
+from ..models.schemas import FileUploadResponse
+from ..services.expand_service import ExpandService
+from ..services.file_service import FileService
+from ..utils.errors import AppError
+
+logger = logging.getLogger(__name__)
+
+router = APIRouter(prefix="/api/expand", tags=["标书扩写"])
+
+
+@router.post("/upload", response_model=FileUploadResponse)
+async def upload_file(file: UploadFile = File(...)):
+    """上传扩写参考文档并提取旧目录。"""
+    try:
+        if not FileService.is_supported_document(file.content_type):
+            return FileUploadResponse(
+                success=False, message="不支持的文件类型，请上传PDF或Word文档"
+            )
+
+        file_content = await FileService.process_uploaded_file(file)
+        expand_service = ExpandService()
+        outline = await expand_service.generate_expand_outline(file_content)
+        return FileUploadResponse(
+            success=True,
+            message=f"文件 {file.filename} 上传成功",
+            file_content=file_content,
+            old_outline=json.dumps(outline, ensure_ascii=False),
+        )
+    except AppError as exc:
+        return FileUploadResponse(success=False, message=exc.message)
+    except Exception as exc:
+        logger.exception("方案扩写文件处理失败")
+        return FileUploadResponse(success=False, message=f"文件处理失败: {exc}")

archive/backend/app/routers/outline.py

@@ -0,0 +1,98 @@
+"""目录相关 API 路由。"""
+
+import asyncio
+import logging
+
+from fastapi import APIRouter, HTTPException
+
+from ..models.schemas import OutlineRequest, OutlineResponse
+from ..services.outline_service import OutlineService
+from ..utils.errors import AppError
+from ..utils.sse import (
+    sse_done,
+    sse_error,
+    sse_progress,
+    sse_response,
+    sse_result,
+)
+
+logger = logging.getLogger(__name__)
+
+router = APIRouter(prefix="/api/outline", tags=["目录管理"])
+
+
+@router.post("/generate", response_model=OutlineResponse)
+async def generate_outline(request: OutlineRequest):
+    """生成完整目录结构。"""
+    try:
+        outline_service = OutlineService()
+        return await outline_service.generate_outline(
+            overview=request.overview,
+            requirements=request.requirements,
+            mode=request.mode,
+            uploaded_expand=bool(request.uploaded_expand),
+            old_outline=request.old_outline,
+        )
+    except AppError as exc:
+        raise HTTPException(status_code=exc.status_code, detail=exc.message) from exc
+    except Exception as exc:
+        logger.exception("目录生成失败")
+        raise HTTPException(status_code=500, detail=f"目录生成失败: {exc}") from exc
+
+
+@router.post("/generate-stream")
+async def generate_outline_stream(request: OutlineRequest):
+    """流式生成目录结构。"""
+    try:
+        outline_service = OutlineService()
+    except AppError as exc:
+        raise HTTPException(status_code=exc.status_code, detail=exc.message) from exc
+
+    async def generate():
+        queue: asyncio.Queue[str | None] = asyncio.Queue()
+        client_disconnected = False
+
+        async def progress_callback(message: str) -> None:
+            await queue.put(sse_progress(message))
+
+        async def run_workflow() -> None:
+            try:
+                outline = await outline_service.generate_outline(
+                    overview=request.overview,
+                    requirements=request.requirements,
+                    mode=request.mode,
+                    uploaded_expand=bool(request.uploaded_expand),
+                    old_outline=request.old_outline,
+                    progress_callback=progress_callback,
+                )
+                await queue.put(sse_result({"outline": outline}))
+            except AppError as exc:
+                await queue.put(sse_error(exc.message))
+            except Exception:
+                logger.exception("目录流式生成失败")
+                await queue.put(sse_error("目录生成失败，请稍后重试"))
+            finally:
+                await queue.put(None)
+
+        task = asyncio.create_task(run_workflow())
+        try:
+            while True:
+                event = await queue.get()
+                if event is None:
+                    break
+                yield event
+        except asyncio.CancelledError:
+            client_disconnected = True
+            raise
+        finally:
+            if not task.done():
+                task.cancel()
+            try:
+                await task
+            except asyncio.CancelledError:
+                pass
+            finally:
+                if not client_disconnected:
+                    yield sse_done()
+
+    return sse_response(generate())

archive/backend/app/services/analysis_service.py

@@ -0,0 +1,37 @@
+"""标书解析服务。"""
+
+from typing import AsyncGenerator
+
+from ..utils.openai_util import OpenAIUtil
+from ..utils.prompts.analysis_prompts import build_analysis_messages
+
+
+class AnalysisService:
+    """负责标书解析与文档分析。"""
+
+    def __init__(self, ai: OpenAIUtil | None = None):
+        self.ai = ai or OpenAIUtil()
+
+    async def stream_document_analysis(
+        self,
+        file_content: str,
+        analysis_type: str,
+    ) -> AsyncGenerator[str, None]:
+        """流式分析文档内容。"""
+        messages = build_analysis_messages(file_content, analysis_type)
+        async for chunk in self.ai.stream_chat_completion(messages, temperature=0.3):
+            yield chunk
+
+    async def stream_chat_completion(
+        self,
+        messages: list[dict[str, str]],
+        temperature: float = 0.7,
+        response_format: dict | None = None,
+    ) -> AsyncGenerator[str, None]:
+        """兼容直接透传底层聊天接口。"""
+        async for chunk in self.ai.stream_chat_completion(
+            messages,
+            temperature=temperature,
+            response_format=response_format,
+        ):
+            yield chunk

archive/backend/app/services/content_service.py

@@ -0,0 +1,48 @@
+"""正文生成服务。"""
+
+from typing import Any, AsyncGenerator
+
+from ..utils.openai_util import OpenAIUtil
+from ..utils.prompts.content_prompts import build_chapter_content_messages
+
+
+class ContentService:
+    """负责目录叶子章节的正文生成。"""
+
+    def __init__(self, ai: OpenAIUtil | None = None):
+        self.ai = ai or OpenAIUtil()
+
+    async def stream_chapter_content(
+        self,
+        chapter: dict[str, Any],
+        parent_chapters: list[dict[str, Any]] | None = None,
+        sibling_chapters: list[dict[str, Any]] | None = None,
+        project_overview: str = "",
+    ) -> AsyncGenerator[str, None]:
+        """流式生成单章节内容。"""
+        messages = build_chapter_content_messages(
+            chapter=chapter,
+            parent_chapters=parent_chapters,
+            sibling_chapters=sibling_chapters,
+            project_overview=project_overview,
+        )
+        async for chunk in self.ai.stream_chat_completion(messages, temperature=0.7):
+            yield chunk
+
+    async def generate_chapter_content(
+        self,
+        chapter: dict[str, Any],
+        parent_chapters: list[dict[str, Any]] | None = None,
+        sibling_chapters: list[dict[str, Any]] | None = None,
+        project_overview: str = "",
+    ) -> str:
+        """生成单章节完整正文。"""
+        return await self.ai.collect_chat_completion(
+            build_chapter_content_messages(
+                chapter=chapter,
+                parent_chapters=parent_chapters,
+                sibling_chapters=sibling_chapters,
+                project_overview=project_overview,
+            ),
+            temperature=0.7,
+        )

archive/backend/app/services/expand_service.py

@@ -0,0 +1,22 @@
+"""标书扩写服务。"""
+
+from typing import Any, Dict
+
+from ..models.schemas import OutlineResponse
+from ..utils.openai_util import OpenAIUtil
+from ..utils.prompts.expand_prompts import build_expand_outline_messages
+
+
+class ExpandService:
+    """负责从已有技术方案中提取旧目录。"""
+
+    def __init__(self, ai: OpenAIUtil | None = None):
+        self.ai = ai or OpenAIUtil()
+
+    async def generate_expand_outline(self, file_content: str) -> Dict[str, Any]:
+        """从已有技术方案中提取目录结构。"""
+        return await self.ai.collect_json_response(
+            messages=build_expand_outline_messages(file_content),
+            temperature=0.7,
+            schema=OutlineResponse,
+        )

archive/backend/app/services/file_service.py

@@ -0,0 +1,611 @@
+"""文件处理服务"""
+
+import aiofiles
+import os
+import time
+import gc
+import io
+import logging
+from datetime import datetime
+from typing import Optional, List, Dict, Tuple
+import PyPDF2
+import docx
+from fastapi import UploadFile
+import aiohttp
+import asyncio
+from ..config import settings
+
+logger = logging.getLogger(__name__)
+
+# 新增的第三方库
+try:
+    import pdfplumber
+    import fitz  # PyMuPDF
+    from docx2python import docx2python
+    from PIL import Image
+
+    HAS_ADVANCED_LIBS = True
+except ImportError as e:
+    HAS_ADVANCED_LIBS = False
+    logger.warning("高级文档处理库未安装: %s", e)
+
+
+class FileService:
+    """文件处理服务"""
+
+    ALLOWED_DOCUMENT_TYPES = {
+        "application/pdf",
+        "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
+    }
+
+    # 图片上传配置
+    IMAGE_UPLOAD_URL = "https://mt.agnet.top/image/upload"
+    IMAGE_UPLOAD_TIMEOUT = 30  # 超时时间（秒）
+
+    @staticmethod
+    def is_supported_document(content_type: str | None) -> bool:
+        """判断上传文件类型是否受支持。"""
+        return bool(content_type and content_type in FileService.ALLOWED_DOCUMENT_TYPES)
+
+    @staticmethod
+    async def upload_image_to_server(image_data: bytes, filename: str) -> Optional[str]:
+        """上传图片到外部服务器"""
+        try:
+            # 准备multipart/form-data格式的数据
+            form_data = aiohttp.FormData()
+            form_data.add_field(
+                "file",
+                io.BytesIO(image_data),
+                filename=filename,
+                content_type="image/jpeg",
+            )
+
+            timeout = aiohttp.ClientTimeout(total=FileService.IMAGE_UPLOAD_TIMEOUT)
+            async with aiohttp.ClientSession(timeout=timeout) as session:
+                async with session.post(
+                    FileService.IMAGE_UPLOAD_URL, data=form_data
+                ) as response:
+                    if response.status == 200:
+                        result = await response.json()
+                        # 根据实际API返回格式获取图片URL
+                        return result.get("file_url")
+                    else:
+                        logger.warning("图片上传失败，状态码: %s", response.status)
+                        return None
+        except Exception as e:
+            logger.warning("图片上传异常: %s", e)
+            return None
+
+    @staticmethod
+    def extract_images_from_pdf(file_path: str) -> List[Tuple[bytes, str, int, int]]:
+        """从PDF提取图片，返回 (图片数据, 扩展名, 页码, 图片索引) 列表"""
+        if not HAS_ADVANCED_LIBS:
+            return []
+
+        images = []
+        try:
+            doc = fitz.open(file_path)
+
+            for page_num in range(doc.page_count):
+                page = doc[page_num]
+                image_list = page.get_images(full=True)
+
+                for img_index, img in enumerate(image_list):
+                    try:
+                        # 获取图片数据
+                        xref = img[0]
+                        pix = fitz.Pixmap(doc, xref)
+
+                        # 转换为RGB格式（如果是CMYK）
+                        if pix.n - pix.alpha < 4:
+                            img_data = pix.tobytes("jpeg")
+                            ext = "jpg"
+                        else:
+                            pix1 = fitz.Pixmap(fitz.csRGB, pix)
+                            img_data = pix1.tobytes("jpeg")
+                            ext = "jpg"
+                            pix1 = None
+
+                        pix = None
+                        images.append((img_data, ext, page_num + 1, img_index + 1))
+
+                    except Exception as e:
+                        logger.warning(
+                            "提取PDF第%s页图片%s失败: %s",
+                            page_num + 1,
+                            img_index + 1,
+                            e,
+                        )
+                        continue
+
+            doc.close()
+            return images
+
+        except Exception as e:
+            logger.warning("PDF图片提取失败: %s", e)
+            return []
+
+    @staticmethod
+    def extract_images_from_docx(file_path: str) -> List[Tuple[bytes, str, int]]:
+        """从Word文档提取图片，返回 (图片数据, 扩展名, 图片索引) 列表"""
+        images = []
+        doc = None
+        try:
+            doc = docx.Document(file_path)
+
+            # 获取文档中的所有关系
+            rels = doc.part.rels
+            img_index = 0
+
+            for rel in rels.values():
+                if "image" in rel.target_ref:
+                    try:
+                        # 读取图片数据
+                        img_data = rel.target_part.blob
+
+                        # 根据content_type确定扩展名
+                        content_type = rel.target_part.content_type
+                        if "jpeg" in content_type:
+                            ext = "jpg"
+                        elif "png" in content_type:
+                            ext = "png"
+                        elif "gif" in content_type:
+                            ext = "gif"
+                        elif "bmp" in content_type:
+                            ext = "bmp"
+                        else:
+                            ext = "jpg"  # 默认
+
+                        img_index += 1
+                        images.append((img_data, ext, img_index))
+
+                    except Exception as e:
+                        logger.warning("提取Word文档图片%s失败: %s", img_index + 1, e)
+                        continue
+
+            if doc:
+                del doc
+            gc.collect()
+            return images
+
+        except Exception as e:
+            if doc:
+                del doc
+            gc.collect()
+            logger.warning("Word文档图片提取失败: %s", e)
+            return []
+
+    @staticmethod
+    def _safe_file_cleanup(file_path: str, max_retries: int = 3) -> bool:
+        """安全删除文件，带重试机制"""
+        for attempt in range(max_retries):
+            try:
+                if os.path.exists(file_path):
+                    # 强制垃圾回收，释放可能的文件句柄
+                    gc.collect()
+                    time.sleep(0.1 * (attempt + 1))  # 递增延迟
+                    os.remove(file_path)
+                return True
+            except OSError as e:
+                if attempt == max_retries - 1:
+                    logger.warning("无法删除文件 %s: %s", file_path, e)
+                    return False
+                time.sleep(0.5)  # 等待后重试
+        return True
+
+    @staticmethod
+    async def save_uploaded_file(file: UploadFile) -> str:
+        """保存上传的文件并返回文件路径"""
+        # 创建上传目录
+        os.makedirs(settings.upload_dir, exist_ok=True)
+
+        # 生成带时间戳的文件名，防止重复
+        timestamp = datetime.now().strftime("%Y%m%d_%H%M%S_%f")[:-3]  # 精确到毫秒
+        filename = file.filename or "unknown_file"
+
+        # 分离文件名和扩展名
+        name, ext = os.path.splitext(filename)
+
+        # 生成新的文件名：原文件名_时间戳.扩展名
+        new_filename = f"{name}_{timestamp}{ext}"
+        file_path = os.path.join(settings.upload_dir, new_filename)
+
+        # 异步保存文件
+        async with aiofiles.open(file_path, "wb") as f:
+            content = await file.read()
+            await f.write(content)
+
+        return file_path
+
+    @staticmethod
+    async def extract_text_from_pdf(file_path: str) -> str:
+        """从PDF文件提取文本，支持表格内容和图片"""
+        if HAS_ADVANCED_LIBS:
+            return await FileService._extract_pdf_with_pdfplumber(file_path)
+        else:
+            # 降级到原来的PyPDF2方法
+            return FileService._extract_pdf_with_pypdf2(file_path)
+
+    @staticmethod
+    async def _extract_pdf_with_pdfplumber(file_path: str) -> str:
+        """使用pdfplumber提取PDF文本，包含表格和图片（确保及时释放文件句柄）"""
+        try:
+            extracted_text = []
+            image_references = []  # 存储图片引用映射
+            global_img_counter = 1
+
+            # 获取PDF文档的所有图片信息，用于后续匹配
+            all_images = FileService.extract_images_from_pdf(file_path)
+            page_images_map = {}
+            for img_data, ext, page_num, img_index in all_images:
+                if page_num not in page_images_map:
+                    page_images_map[page_num] = []
+                page_images_map[page_num].append((img_data, ext, img_index))
+
+            # 使用上下文管理器，避免在Windows上产生文件锁
+            with pdfplumber.open(file_path) as pdf:
+                for page_num, page in enumerate(pdf.pages, 1):
+                    # 添加页码标识
+                    extracted_text.append(f"\n--- 第 {page_num} 页 ---\n")
+
+                    # 提取普通文本
+                    text = page.extract_text()
+                    if text:
+                        # 检查文本中是否有图片标记
+                        import re
+
+                        img_pattern = r"----.*?(?:image|img|media).*?----"
+                        img_matches = list(
+                            re.finditer(img_pattern, text, re.IGNORECASE)
+                        )
+
+                        if img_matches and page_num in page_images_map:
+                            # 按顺序处理页面中的图片
+                            page_images = page_images_map[page_num]
+                            processed_text = text
+
+                            for i, match in enumerate(img_matches):
+                                if i < len(page_images):
+                                    # 获取对应的图片数据
+                                    img_data, ext, img_index = page_images[i]
+                                    filename = (
+                                        f"pdf_page{page_num}_img{img_index}.{ext}"
+                                    )
+
+                                    # 上传图片
+                                    image_url = (
+                                        await FileService.upload_image_to_server(
+                                            img_data, filename
+                                        )
+                                    )
+
+                                    if image_url:
+                                        # 替换图片标记
+                                        old_mark = match.group()
+                                        new_mark = f"[图片{global_img_counter}]"
+                                        processed_text = processed_text.replace(
+                                            old_mark, new_mark, 1
+                                        )
+
+                                        # 记录图片引用
+                                        image_references.append(
+                                            f"[图片{global_img_counter}]: {image_url}"
+                                        )
+                                        global_img_counter += 1
+
+                            extracted_text.append(processed_text)
+                        else:
+                            extracted_text.append(text)
+
+                    # 提取表格
+                    tables = page.extract_tables()
+                    for table_num, table in enumerate(tables, 1):
+                        extracted_text.append(f"\n[表格 {table_num}]")
+                        for row in table:
+                            if row:  # 跳过空行
+                                # 过滤空值并连接单元格
+                                row_text = " | ".join(
+                                    [str(cell) if cell else "" for cell in row]
+                                )
+                                extracted_text.append(row_text)
+                        extracted_text.append("[表格结束]\n")
+
+            # 在文档末尾添加图片引用映射
+            if image_references:
+                extracted_text.append(f"\n\n--- 图片引用 ---")
+                extracted_text.extend(image_references)
+
+            result = "\n".join(extracted_text).strip()
+            gc.collect()
+            return result
+        except Exception as e:
+            gc.collect()
+            # 如果pdfplumber失败，尝试PyMuPDF
+            try:
+                return await FileService._extract_pdf_with_pymupdf(file_path)
+            except Exception:
+                raise Exception(f"PDF文件读取失败: {str(e)}")
+
+    @staticmethod
+    async def _extract_pdf_with_pymupdf(file_path: str) -> str:
+        """使用PyMuPDF提取PDF文本和图片"""
+        try:
+            doc = fitz.open(file_path)
+            extracted_text = []
+
+            for page_num in range(doc.page_count):
+                page = doc[page_num]
+                extracted_text.append(f"\n--- 第 {page_num + 1} 页 ---\n")
+
+                # 提取文本
+                text = page.get_text()
+                if text:
+                    extracted_text.append(text)
+
+                # 尝试提取表格
+                try:
+                    tables = page.find_tables()
+                    for table_num, table in enumerate(tables, 1):
+                        extracted_text.append(f"\n[表格 {table_num}]")
+                        table_data = table.extract()
+                        for row in table_data:
+                            if row:
+                                row_text = " | ".join(
+                                    [str(cell) if cell else "" for cell in row]
+                                )
+                                extracted_text.append(row_text)
+                        extracted_text.append("[表格结束]\n")
+                except:
+                    # 如果表格提取失败，跳过
+                    pass
+
+            doc.close()
+            return "\n".join(extracted_text).strip()
+        except Exception as e:
+            raise Exception(f"PDF文件读取失败: {str(e)}")
+
+    @staticmethod
+    def _extract_pdf_with_pypdf2(file_path: str) -> str:
+        """使用PyPDF2提取PDF文本（原方法）"""
+        try:
+            with open(file_path, "rb") as file:
+                pdf_reader = PyPDF2.PdfReader(file)
+                text = ""
+                for page in pdf_reader.pages:
+                    text += page.extract_text() + "\n"
+                return text.strip()
+        except Exception as e:
+            raise Exception(f"PDF文件读取失败: {str(e)}")
+
+    @staticmethod
+    async def extract_text_from_docx(file_path: str) -> str:
+        """从Word文档提取文本，支持表格内容和图片"""
+        if HAS_ADVANCED_LIBS:
+            return await FileService._extract_docx_with_docx2python(file_path)
+        else:
+            # 降级到原来的python-docx方法，但增强表格处理
+            return await FileService._extract_docx_with_python_docx(file_path)
+
+    @staticmethod
+    async def _extract_docx_with_docx2python(file_path: str) -> str:
+        """使用docx2python提取Word文档内容和图片（确保及时释放文件句柄）"""
+        try:
+            extracted_text = []
+            image_references = []  # 存储图片引用映射
+            global_img_counter = 1
+
+            # 获取Word文档的所有图片信息
+            all_images = FileService.extract_images_from_docx(file_path)
+
+            # 使用上下文管理器确保文件及时关闭，避免Windows上的锁定
+            with docx2python(file_path) as content:
+                # 处理文档内容
+                if hasattr(content, "document"):
+                    for section in content.document:
+                        for element in section:
+                            if isinstance(element, list):
+                                # 这可能是表格
+                                extracted_text.append("\n[表格内容]")
+                                for row in element:
+                                    if isinstance(row, list):
+                                        row_text = " | ".join(
+                                            [str(cell).strip() for cell in row if cell]
+                                        )
+                                        if row_text:
+                                            extracted_text.append(row_text)
+                                    else:
+                                        extracted_text.append(str(row))
+                                extracted_text.append("[表格结束]\n")
+                            else:
+                                # 普通文本，检查是否包含图片标记
+                                text = str(element).strip()
+                                if text:
+                                    # 检查文本中是否有图片标记
+                                    import re
+
+                                    img_pattern = r"----.*?(?:image|img|media).*?----"
+                                    img_matches = list(
+                                        re.finditer(img_pattern, text, re.IGNORECASE)
+                                    )
+
+                                    if img_matches and all_images:
+                                        processed_text = text
+
+                                        for match in img_matches:
+                                            if global_img_counter <= len(all_images):
+                                                # 获取对应的图片数据
+                                                img_data, ext, img_index = all_images[
+                                                    global_img_counter - 1
+                                                ]
+                                                filename = f"docx_img{global_img_counter}.{ext}"
+
+                                                # 上传图片
+                                                image_url = await FileService.upload_image_to_server(
+                                                    img_data, filename
+                                                )
+
+                                                if image_url:
+                                                    # 替换图片标记
+                                                    old_mark = match.group()
+                                                    new_mark = (
+                                                        f"[图片{global_img_counter}]"
+                                                    )
+                                                    processed_text = (
+                                                        processed_text.replace(
+                                                            old_mark, new_mark, 1
+                                                        )
+                                                    )
+
+                                                    # 记录图片引用
+                                                    image_references.append(
+                                                        f"[图片{global_img_counter}]: {image_url}"
+                                                    )
+                                                    global_img_counter += 1
+
+                                        extracted_text.append(processed_text)
+                                    else:
+                                        extracted_text.append(text)
+
+            # 在文档末尾添加图片引用映射
+            if image_references:
+                extracted_text.append(f"\n\n--- 图片引用 ---")
+                extracted_text.extend(image_references)
+
+            result = "\n".join(extracted_text).strip()
+            gc.collect()
+            return result
+        except Exception as e:
+            gc.collect()
+            # 如果docx2python失败，回退到增强的python-docx
+            try:
+                return await FileService._extract_docx_with_python_docx(file_path)
+            except Exception:
+                raise Exception(f"Word文档读取失败: {str(e)}")
+
+    @staticmethod
+    async def _extract_docx_with_python_docx(file_path: str) -> str:
+        """使用python-docx提取Word文档内容和图片（增强版）"""
+        doc = None
+        try:
+            doc = docx.Document(file_path)
+            extracted_text = []
+            image_references = []  # 存储图片引用映射
+            global_img_counter = 1
+
+            # 获取Word文档的所有图片信息
+            all_images = FileService.extract_images_from_docx(file_path)
+
+            # 提取段落文本，同时处理图片
+            for paragraph in doc.paragraphs:
+                text = paragraph.text.strip()
+                if text:
+                    # 检查文本中是否有图片标记
+                    import re
+
+                    img_pattern = r"----.*?(?:image|img|media).*?----"
+                    img_matches = list(re.finditer(img_pattern, text, re.IGNORECASE))
+
+                    if img_matches and all_images:
+                        processed_text = text
+
+                        for match in img_matches:
+                            if global_img_counter <= len(all_images):
+                                # 获取对应的图片数据
+                                img_data, ext, img_index = all_images[
+                                    global_img_counter - 1
+                                ]
+                                filename = f"docx_img{global_img_counter}.{ext}"
+
+                                # 上传图片
+                                image_url = await FileService.upload_image_to_server(
+                                    img_data, filename
+                                )
+
+                                if image_url:
+                                    # 替换图片标记
+                                    old_mark = match.group()
+                                    new_mark = f"[图片{global_img_counter}]"
+                                    processed_text = processed_text.replace(
+                                        old_mark, new_mark, 1
+                                    )
+
+                                    # 记录图片引用
+                                    image_references.append(
+                                        f"[图片{global_img_counter}]: {image_url}"
+                                    )
+                                    global_img_counter += 1
+
+                        extracted_text.append(processed_text)
+                    else:
+                        extracted_text.append(text)
+
+            # 提取表格内容
+            for table_num, table in enumerate(doc.tables, 1):
+                extracted_text.append(f"\n[表格 {table_num}]")
+                for row in table.rows:
+                    row_data = []
+                    for cell in row.cells:
+                        cell_text = cell.text.strip()
+                        row_data.append(cell_text if cell_text else "")
+                    row_text = " | ".join(row_data)
+                    if row_text.strip():
+                        extracted_text.append(row_text)
+                extracted_text.append("[表格结束]\n")
+
+            # 在文档末尾添加图片引用映射
+            if image_references:
+                extracted_text.append(f"\n\n--- 图片引用 ---")
+                extracted_text.extend(image_references)
+
+            result = "\n".join(extracted_text).strip()
+
+            # 确保释放资源
+            if doc:
+                del doc
+            gc.collect()
+
+            return result
+        except Exception as e:
+            # 确保释放资源
+            if doc:
+                del doc
+            gc.collect()
+            raise Exception(f"Word文档读取失败: {str(e)}")
+
+    @staticmethod
+    async def process_uploaded_file(file: UploadFile) -> str:
+        """处理上传的文件并提取文本内容"""
+        # 检查文件大小
+        content = await file.read()
+        if len(content) > settings.max_file_size:
+            raise Exception(
+                f"文件大小超过限制 ({settings.max_file_size / 1024 / 1024}MB)"
+            )
+
+        # 重置文件指针
+        await file.seek(0)
+
+        # 保存文件
+        file_path = await FileService.save_uploaded_file(file)
+
+        try:
+            # 根据文件类型提取文本和图片
+            if file.content_type == "application/pdf":
+                text = await FileService.extract_text_from_pdf(file_path)
+            elif (
+                file.content_type
+                == "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
+            ):
+                text = await FileService.extract_text_from_docx(file_path)
+            else:
+                raise Exception("不支持的文件类型，请上传PDF或Word文档")
+
+            # 成功提取后，使用安全的文件清理方法
+            FileService._safe_file_cleanup(file_path)
+
+            return text
+
+        except Exception as e:
+            # 异常情况下也使用安全的文件清理方法
+            FileService._safe_file_cleanup(file_path)
+            raise e

archive/backend/app/services/model_service.py

@@ -0,0 +1,16 @@
+"""模型查询服务。"""
+
+from typing import List
+
+from ..utils.openai_util import OpenAIUtil
+
+
+class ModelService:
+    """负责读取可用模型列表。"""
+
+    def __init__(self, ai: OpenAIUtil | None = None):
+        self.ai = ai or OpenAIUtil()
+
+    async def get_available_models(self) -> List[str]:
+        """获取可用模型列表。"""
+        return await self.ai.get_available_models()

archive/backend/app/services/outline_service.py

@@ -0,0 +1,742 @@
+"""目录生成服务。"""
+
+import json
+from typing import Any, Dict
+
+from ..models.schemas import (
+    OutlineChildrenResponse,
+    OutlineMode,
+    OutlineResponse,
+    OutlineReviewResponse,
+    TechnicalRequirementGroupResponse,
+)
+from ..utils.openai_util import OpenAIUtil, ProgressCallback
+from ..utils.errors import AppError
+from ..utils.prompts.outline_prompts import (
+    extract_requirement_groups_messages,
+    generate_aligned_children_outline_prompt,
+    generate_aligned_children_outline_with_old_prompt,
+    generate_children_outline_prompt,
+    generate_children_outline_with_old_prompt,
+    generate_outline_prompt,
+    generate_outline_with_old_prompt,
+    generate_top_level_outline_prompt,
+    generate_top_level_outline_with_old_prompt,
+    review_aligned_outline_messages,
+    review_outline_messages,
+)
+
+
+class OutlineService:
+    """负责目录生成、审核与技术评分项对齐。"""
+
+    def __init__(self, ai: OpenAIUtil | None = None):
+        self.ai = ai or OpenAIUtil()
+
+    async def generate_outline(
+        self,
+        overview: str,
+        requirements: str,
+        mode: OutlineMode = OutlineMode.FREE,
+        uploaded_expand: bool = False,
+        old_outline: str | None = None,
+        progress_callback: ProgressCallback | None = None,
+    ) -> Dict[str, Any]:
+        """生成目录结构。"""
+        if mode == OutlineMode.ALIGNED:
+            return await self._generate_aligned_outline_workflow(
+                overview=overview,
+                requirements=requirements,
+                uploaded_expand=uploaded_expand,
+                old_outline=old_outline,
+                progress_callback=progress_callback,
+            )
+
+        return await self._generate_outline_workflow(
+            overview=overview,
+            requirements=requirements,
+            uploaded_expand=uploaded_expand,
+            old_outline=old_outline,
+            progress_callback=progress_callback,
+        )
+
+    async def _generate_outline_workflow(
+        self,
+        overview: str,
+        requirements: str,
+        uploaded_expand: bool,
+        old_outline: str | None,
+        progress_callback: ProgressCallback | None = None,
+    ) -> Dict[str, Any]:
+        """执行目录生成、审核与回退工作流。"""
+        await self.ai.emit_progress(progress_callback, "开始生成目录结构。")
+        first_outline, generation_mode = await self._generate_outline_by_mode(
+            overview=overview,
+            requirements=requirements,
+            uploaded_expand=uploaded_expand,
+            old_outline=old_outline,
+            mode="auto",
+            progress_callback=progress_callback,
+        )
+
+        await self.ai.emit_progress(
+            progress_callback, "首次目录生成完成，开始审核目录质量。"
+        )
+        first_review = await self._review_outline(
+            overview=overview,
+            requirements=requirements,
+            outline=first_outline,
+            progress_callback=progress_callback,
+            stage_label="首次审核",
+        )
+        if first_review["passed"]:
+            await self.ai.emit_progress(
+                progress_callback, "目录审核通过，准备返回结果。"
+            )
+            return first_outline
+
+        suggestions = first_review.get("suggestions") or [
+            "请根据项目概述和技术评分要求补全目录覆盖范围，并修正不合理章节。"
+        ]
+        await self.ai.emit_progress(
+            progress_callback,
+            "目录审核未通过，正在根据修改建议重新生成。",
+        )
+
+        try:
+            second_outline, _ = await self._generate_outline_by_mode(
+                overview=overview,
+                requirements=requirements,
+                uploaded_expand=uploaded_expand,
+                old_outline=old_outline,
+                mode=generation_mode,
+                progress_callback=progress_callback,
+                suggestions=suggestions,
+            )
+        except AppError:
+            await self.ai.emit_progress(
+                progress_callback,
+                "根据审核建议重新生成失败，已回退到首次生成结果。",
+            )
+            return first_outline
+
+        await self.ai.emit_progress(progress_callback, "二次生成完成，开始最终审核。")
+        second_review = await self._review_outline(
+            overview=overview,
+            requirements=requirements,
+            outline=second_outline,
+            progress_callback=progress_callback,
+            stage_label="最终审核",
+        )
+        if second_review["passed"]:
+            await self.ai.emit_progress(
+                progress_callback, "最终审核通过，准备返回修正后的结果。"
+            )
+        else:
+            await self.ai.emit_progress(
+                progress_callback,
+                "最终审核未完全通过，已返回修正后的第二次结果。",
+            )
+
+        return second_outline
+
+    async def _generate_aligned_outline_workflow(
+        self,
+        overview: str,
+        requirements: str,
+        uploaded_expand: bool,
+        old_outline: str | None,
+        progress_callback: ProgressCallback | None = None,
+    ) -> Dict[str, Any]:
+        """按技术评分大类一一对应生成目录。"""
+        await self.ai.emit_progress(progress_callback, "开始提取技术评分大类。")
+        groups = await self._extract_requirement_groups(
+            requirements=requirements,
+            progress_callback=progress_callback,
+        )
+
+        await self.ai.emit_progress(
+            progress_callback, "技术评分大类提取完成，正在构建一级目录。"
+        )
+        first_outline = await self._generate_aligned_outline(
+            overview=overview,
+            requirements=requirements,
+            groups=groups,
+            uploaded_expand=uploaded_expand,
+            old_outline=old_outline,
+            progress_callback=progress_callback,
+        )
+
+        await self.ai.emit_progress(
+            progress_callback,
+            "目录生成完成，正在审核与技术评分项的对应关系。",
+        )
+        first_review = await self._review_aligned_outline(
+            overview=overview,
+            requirements=requirements,
+            groups=groups,
+            outline=first_outline,
+            progress_callback=progress_callback,
+            stage_label="首次审核",
+        )
+        if first_review["passed"]:
+            await self.ai.emit_progress(
+                progress_callback, "目录审核通过，准备返回结果。"
+            )
+            return first_outline
+
+        suggestions = first_review.get("suggestions") or [
+            "请保持一级目录与技术评分大类标题完全一致，并补全各大类下遗漏的评分细项。"
+        ]
+        await self.ai.emit_progress(
+            progress_callback,
+            "目录审核未通过，正在根据修改建议重新提取技术评分大类并重新生成目录。",
+        )
+
+        try:
+            revised_groups = await self._extract_requirement_groups(
+                requirements=requirements,
+                progress_callback=progress_callback,
+                suggestions=suggestions,
+            )
+            second_outline = await self._generate_aligned_outline(
+                overview=overview,
+                requirements=requirements,
+                groups=revised_groups,
+                uploaded_expand=uploaded_expand,
+                old_outline=old_outline,
+                progress_callback=progress_callback,
+                suggestions=suggestions,
+            )
+        except AppError:
+            await self.ai.emit_progress(
+                progress_callback,
+                "根据审核建议重新生成失败，已回退到首次生成结果。",
+            )
+            return first_outline
+
+        await self.ai.emit_progress(progress_callback, "二次生成完成，开始最终审核。")
+        second_review = await self._review_aligned_outline(
+            overview=overview,
+            requirements=requirements,
+            groups=revised_groups,
+            outline=second_outline,
+            progress_callback=progress_callback,
+            stage_label="最终审核",
+        )
+        if second_review["passed"]:
+            await self.ai.emit_progress(
+                progress_callback, "最终审核通过，准备返回修正后的结果。"
+            )
+        else:
+            await self.ai.emit_progress(
+                progress_callback,
+                "最终审核未完全通过，已返回修正后的第二次结果。",
+            )
+
+        return second_outline
+
+    async def _extract_requirement_groups(
+        self,
+        requirements: str,
+        progress_callback: ProgressCallback | None = None,
+        suggestions: list[str] | None = None,
+    ) -> list[dict[str, Any]]:
+        """提取适合作为一级目录的技术评分大类。"""
+        response = await self.ai.collect_json_response(
+            messages=extract_requirement_groups_messages(
+                requirements=requirements,
+                suggestions=suggestions,
+            ),
+            temperature=0.3,
+            schema=TechnicalRequirementGroupResponse,
+            validator=self._validate_requirement_groups,
+            progress_callback=progress_callback,
+            progress_label="技术评分大类",
+            failure_message="模型返回的技术评分大类格式无效",
+        )
+        return response.get("groups") or []
+
+    @staticmethod
+    def _validate_requirement_groups(payload: Dict[str, Any]) -> None:
+        """校验技术评分大类提取结果。"""
+        groups = payload.get("groups") or []
+        if not groups:
+            raise ValueError("技术评分大类不能为空")
+
+        requirement_ids: list[str] = []
+        titles: list[str] = []
+        for index, group in enumerate(groups, start=1):
+            requirement_id = str(group.get("requirement_id") or "").strip()
+            title = str(group.get("title") or "").strip()
+            description = str(group.get("description") or "").strip()
+            if not requirement_id:
+                raise ValueError(f"第 {index} 个技术评分大类缺少 requirement_id")
+            if not title:
+                raise ValueError(f"第 {index} 个技术评分大类缺少标题")
+            if not description:
+                raise ValueError(f"第 {index} 个技术评分大类缺少描述")
+            requirement_ids.append(requirement_id)
+            titles.append(title)
+
+        if len(set(requirement_ids)) != len(requirement_ids):
+            raise ValueError("技术评分大类 requirement_id 不能重复")
+        if len(set(titles)) != len(titles):
+            raise ValueError("技术评分大类标题不能重复")
+
+    @staticmethod
+    def _build_top_level_outline_from_groups(
+        groups: list[dict[str, Any]],
+    ) -> list[dict[str, Any]]:
+        """根据技术评分大类直接构造一级目录。"""
+        outline: list[dict[str, Any]] = []
+        for index, group in enumerate(groups, start=1):
+            title = str(group.get("title") or "").strip()
+            outline.append(
+                {
+                    "id": str(index),
+                    "title": title,
+                    "description": str(group.get("description") or title).strip(),
+                    "source_requirement_id": str(
+                        group.get("requirement_id") or f"R{index}"
+                    ).strip(),
+                    "source_requirement_title": title,
+                }
+            )
+        return outline
+
+    @staticmethod
+    def _validate_aligned_top_level_mapping(
+        outline_items: list[dict[str, Any]],
+        groups: list[dict[str, Any]],
+    ) -> None:
+        """校验一级目录与技术评分大类是否严格对齐。"""
+        if len(outline_items) != len(groups):
+            raise ValueError("一级目录数量必须与技术评分大类数量一致")
+
+        for index, (item, group) in enumerate(zip(outline_items, groups), start=1):
+            expected_title = str(group.get("title") or "").strip()
+            actual_title = str(item.get("title") or "").strip()
+            if actual_title != expected_title:
+                raise ValueError(
+                    f"第 {index} 个一级目录标题必须严格等于技术评分大类标题：{expected_title}"
+                )
+
+            expected_requirement_id = str(group.get("requirement_id") or "").strip()
+            actual_requirement_id = str(item.get("source_requirement_id") or "").strip()
+            if actual_requirement_id != expected_requirement_id:
+                raise ValueError(
+                    f"第 {index} 个一级目录映射的技术评分大类ID不正确：{expected_requirement_id}"
+                )
+
+    async def _generate_aligned_outline(
+        self,
+        overview: str,
+        requirements: str,
+        groups: list[dict[str, Any]],
+        uploaded_expand: bool,
+        old_outline: str | None,
+        progress_callback: ProgressCallback | None,
+        suggestions: list[str] | None = None,
+    ) -> Dict[str, Any]:
+        """基于技术评分大类生成严格对齐的完整目录。"""
+        top_level_items = self._build_top_level_outline_from_groups(groups)
+        self._validate_aligned_top_level_mapping(top_level_items, groups)
+
+        assembled_items: list[dict[str, Any]] = []
+        for index, (item, group) in enumerate(zip(top_level_items, groups), start=1):
+            await self.ai.emit_progress(
+                progress_callback,
+                f"正在生成第 {index}/{len(top_level_items)} 个评分大类的二三级目录：{item.get('title', '未命名章节')}。",
+            )
+            merged_item = dict(item)
+            children_response = await self._generate_outline_children_for_group(
+                overview=overview,
+                requirements=requirements,
+                parent_item=item,
+                requirement_group=group,
+                uploaded_expand=uploaded_expand,
+                old_outline=old_outline,
+                suggestions=suggestions,
+                progress_callback=progress_callback,
+            )
+            children = children_response.get("children") or []
+            if children:
+                merged_item["children"] = children
+            assembled_items.append(merged_item)
+
+        outline = self._renumber_outline({"outline": assembled_items})
+        validated = OutlineResponse.model_validate(outline)
+        normalized = validated.model_dump(exclude_none=True)
+        self._validate_complete_outline(normalized)
+        self._validate_aligned_top_level_mapping(
+            normalized.get("outline") or [], groups
+        )
+        return normalized
+
+    async def _generate_outline_children_for_group(
+        self,
+        overview: str,
+        requirements: str,
+        parent_item: Dict[str, Any],
+        requirement_group: Dict[str, Any],
+        uploaded_expand: bool,
+        old_outline: str | None,
+        suggestions: list[str] | None,
+        progress_callback: ProgressCallback | None,
+    ) -> Dict[str, Any]:
+        """为指定技术评分大类生成二三级目录。"""
+        if uploaded_expand:
+            messages = generate_aligned_children_outline_with_old_prompt(
+                overview=overview,
+                requirements=requirements,
+                parent_item=parent_item,
+                requirement_group=requirement_group,
+                old_outline=old_outline,
+                suggestions=suggestions,
+            )
+        else:
+            messages = generate_aligned_children_outline_prompt(
+                overview=overview,
+                requirements=requirements,
+                parent_item=parent_item,
+                requirement_group=requirement_group,
+                suggestions=suggestions,
+            )
+
+        return await self.ai.collect_json_response(
+            messages=messages,
+            temperature=0.7,
+            schema=OutlineChildrenResponse,
+            validator=self._validate_children_outline,
+            progress_callback=progress_callback,
+            progress_label=f"章节 {parent_item.get('title', '未命名章节')} 子目录",
+            failure_message="模型返回的目录数据格式无效",
+        )
+
+    async def _review_aligned_outline(
+        self,
+        overview: str,
+        requirements: str,
+        groups: list[dict[str, Any]],
+        outline: Dict[str, Any],
+        progress_callback: ProgressCallback | None,
+        stage_label: str,
+    ) -> Dict[str, Any]:
+        """审核目录是否与技术评分大类一一对应。"""
+        messages = review_aligned_outline_messages(
+            overview=overview,
+            requirements=requirements,
+            groups_json=json.dumps({"groups": groups}, ensure_ascii=False),
+            outline_json=json.dumps(outline, ensure_ascii=False),
+        )
+        return await self.ai.collect_json_response(
+            messages=messages,
+            temperature=0.3,
+            schema=OutlineReviewResponse,
+            progress_callback=progress_callback,
+            progress_label=stage_label,
+            failure_message="模型返回的审核结果格式无效",
+        )
+
+    async def _generate_outline_by_mode(
+        self,
+        overview: str,
+        requirements: str,
+        uploaded_expand: bool,
+        old_outline: str | None,
+        mode: str,
+        progress_callback: ProgressCallback | None = None,
+        suggestions: list[str] | None = None,
+    ) -> tuple[Dict[str, Any], str]:
+        """根据指定模式生成目录。"""
+        if mode == "full":
+            outline = await self._generate_outline_full(
+                overview=overview,
+                requirements=requirements,
+                uploaded_expand=uploaded_expand,
+                old_outline=old_outline,
+                suggestions=suggestions,
+                progress_callback=progress_callback,
+            )
+            return outline, "full"
+
+        if mode == "fallback":
+            outline = await self._generate_outline_fallback(
+                overview=overview,
+                requirements=requirements,
+                uploaded_expand=uploaded_expand,
+                old_outline=old_outline,
+                suggestions=suggestions,
+                progress_callback=progress_callback,
+            )
+            return outline, "fallback"
+
+        try:
+            outline = await self._generate_outline_full(
+                overview=overview,
+                requirements=requirements,
+                uploaded_expand=uploaded_expand,
+                old_outline=old_outline,
+                suggestions=suggestions,
+                progress_callback=progress_callback,
+            )
+            return outline, "full"
+        except AppError as exc:
+            if exc.message != "模型返回的目录数据格式无效":
+                raise
+            await self.ai.emit_progress(
+                progress_callback,
+                "一次性生成完整目录失败，切换为分步生成模式。",
+            )
+            outline = await self._generate_outline_fallback(
+                overview=overview,
+                requirements=requirements,
+                uploaded_expand=uploaded_expand,
+                old_outline=old_outline,
+                suggestions=suggestions,
+                progress_callback=progress_callback,
+            )
+            return outline, "fallback"
+
+    async def _generate_outline_full(
+        self,
+        overview: str,
+        requirements: str,
+        uploaded_expand: bool,
+        old_outline: str | None,
+        suggestions: list[str] | None,
+        progress_callback: ProgressCallback | None,
+    ) -> Dict[str, Any]:
+        """一次性生成完整目录。"""
+        await self.ai.emit_progress(progress_callback, "正在一次性生成完整目录。")
+        if uploaded_expand:
+            messages = generate_outline_with_old_prompt(
+                overview,
+                requirements,
+                old_outline,
+                suggestions=suggestions,
+            )
+        else:
+            messages = generate_outline_prompt(
+                overview,
+                requirements,
+                suggestions=suggestions,
+            )
+
+        return await self.ai.collect_json_response(
+            messages=messages,
+            temperature=0.7,
+            schema=OutlineResponse,
+            validator=self._validate_complete_outline,
+            progress_callback=progress_callback,
+            progress_label="完整目录",
+            failure_message="模型返回的目录数据格式无效",
+        )
+
+    async def _generate_outline_fallback(
+        self,
+        overview: str,
+        requirements: str,
+        uploaded_expand: bool,
+        old_outline: str | None,
+        suggestions: list[str] | None,
+        progress_callback: ProgressCallback | None,
+    ) -> Dict[str, Any]:
+        """分步生成目录：先一级目录，再逐个生成二三级目录。"""
+        await self.ai.emit_progress(
+            progress_callback, "正在分步生成目录，先生成一级目录。"
+        )
+        top_level_outline = await self._generate_top_level_outline(
+            overview=overview,
+            requirements=requirements,
+            uploaded_expand=uploaded_expand,
+            old_outline=old_outline,
+            suggestions=suggestions,
+            progress_callback=progress_callback,
+        )
+
+        top_level_items = top_level_outline.get("outline", [])
+        assembled_items: list[dict[str, Any]] = []
+        for index, item in enumerate(top_level_items, start=1):
+            await self.ai.emit_progress(
+                progress_callback,
+                f"正在生成第 {index}/{len(top_level_items)} 个一级目录的二三级目录：{item.get('title', '未命名章节')}。",
+            )
+            merged_item = {
+                "id": item.get("id", str(index)),
+                "title": item.get("title", "未命名章节"),
+                "description": item.get("description", ""),
+            }
+            children_response = await self._generate_outline_children(
+                overview=overview,
+                requirements=requirements,
+                parent_item=item,
+                uploaded_expand=uploaded_expand,
+                old_outline=old_outline,
+                suggestions=suggestions,
+                progress_callback=progress_callback,
+            )
+            children = children_response.get("children") or []
+            if children:
+                merged_item["children"] = children
+            assembled_items.append(merged_item)
+
+        outline = self._renumber_outline({"outline": assembled_items})
+        validated = OutlineResponse.model_validate(outline)
+        normalized = validated.model_dump(exclude_none=True)
+        self._validate_complete_outline(normalized)
+        return normalized
+
+    async def _generate_top_level_outline(
+        self,
+        overview: str,
+        requirements: str,
+        uploaded_expand: bool,
+        old_outline: str | None,
+        suggestions: list[str] | None,
+        progress_callback: ProgressCallback | None,
+    ) -> Dict[str, Any]:
+        """生成一级目录。"""
+        if uploaded_expand:
+            messages = generate_top_level_outline_with_old_prompt(
+                overview=overview,
+                requirements=requirements,
+                old_outline=old_outline,
+                suggestions=suggestions,
+            )
+        else:
+            messages = generate_top_level_outline_prompt(
+                overview=overview,
+                requirements=requirements,
+                suggestions=suggestions,
+            )
+
+        return await self.ai.collect_json_response(
+            messages=messages,
+            temperature=0.7,
+            schema=OutlineResponse,
+            validator=self._validate_top_level_outline,
+            progress_callback=progress_callback,
+            progress_label="一级目录",
+            failure_message="模型返回的目录数据格式无效",
+        )
+
+    async def _generate_outline_children(
+        self,
+        overview: str,
+        requirements: str,
+        parent_item: Dict[str, Any],
+        uploaded_expand: bool,
+        old_outline: str | None,
+        suggestions: list[str] | None,
+        progress_callback: ProgressCallback | None,
+    ) -> Dict[str, Any]:
+        """生成某个一级目录下的二三级目录。"""
+        if uploaded_expand:
+            messages = generate_children_outline_with_old_prompt(
+                overview=overview,
+                requirements=requirements,
+                parent_item=parent_item,
+                old_outline=old_outline,
+                suggestions=suggestions,
+            )
+        else:
+            messages = generate_children_outline_prompt(
+                overview=overview,
+                requirements=requirements,
+                parent_item=parent_item,
+                suggestions=suggestions,
+            )
+
+        return await self.ai.collect_json_response(
+            messages=messages,
+            temperature=0.7,
+            schema=OutlineChildrenResponse,
+            validator=self._validate_children_outline,
+            progress_callback=progress_callback,
+            progress_label=f"章节 {parent_item.get('title', '未命名章节')} 子目录",
+            failure_message="模型返回的目录数据格式无效",
+        )
+
+    async def _review_outline(
+        self,
+        overview: str,
+        requirements: str,
+        outline: Dict[str, Any],
+        progress_callback: ProgressCallback | None,
+        stage_label: str,
+    ) -> Dict[str, Any]:
+        """审核目录是否符合招标要求。"""
+        messages = review_outline_messages(
+            overview=overview,
+            requirements=requirements,
+            outline_json=json.dumps(outline, ensure_ascii=False),
+        )
+        return await self.ai.collect_json_response(
+            messages=messages,
+            temperature=0.3,
+            schema=OutlineReviewResponse,
+            progress_callback=progress_callback,
+            progress_label=stage_label,
+            failure_message="模型返回的审核结果格式无效",
+        )
+
+    @classmethod
+    def _renumber_outline(cls, outline: Dict[str, Any]) -> Dict[str, Any]:
+        """统一重排目录编号，避免分步生成时编号错乱。"""
+        return {"outline": cls._renumber_items(outline.get("outline", []))}
+
+    @classmethod
+    def _renumber_items(
+        cls,
+        items: list[dict[str, Any]],
+        parent_prefix: str = "",
+    ) -> list[dict[str, Any]]:
+        """递归重排目录项编号。"""
+        normalized_items: list[dict[str, Any]] = []
+        for index, item in enumerate(items, start=1):
+            item_id = f"{parent_prefix}.{index}" if parent_prefix else str(index)
+            normalized_item = {**item, "id": item_id}
+            children = item.get("children") or []
+            if children:
+                normalized_item["children"] = cls._renumber_items(children, item_id)
+            else:
+                normalized_item.pop("children", None)
+            normalized_items.append(normalized_item)
+
+        return normalized_items
+
+    @staticmethod
+    def _outline_depth(items: list[dict[str, Any]]) -> int:
+        """计算目录的最大层级深度。"""
+        if not items:
+            return 0
+
+        return 1 + max(
+            OutlineService._outline_depth(item.get("children") or []) for item in items
+        )
+
+    @classmethod
+    def _validate_complete_outline(cls, payload: Dict[str, Any]) -> None:
+        """校验完整目录至少达到三级结构。"""
+        outline = payload.get("outline") or []
+        if not outline:
+            raise ValueError("目录不能为空")
+
+        if cls._outline_depth(outline) < 3:
+            raise ValueError("完整目录至少需要三级结构")
+
+    @staticmethod
+    def _validate_top_level_outline(payload: Dict[str, Any]) -> None:
+        """校验一级目录结果非空。"""
+        outline = payload.get("outline") or []
+        if not outline:
+            raise ValueError("一级目录不能为空")
+
+    @classmethod
+    def _validate_children_outline(cls, payload: Dict[str, Any]) -> None:
+        """校验一级目录下至少生成出二级目录。"""
+        children = payload.get("children") or []
+        if not children:
+            raise ValueError("二级目录不能为空")

archive/backend/app/services/word_export_service.py

@@ -0,0 +1,247 @@
+"""Word 导出服务。"""
+
+import io
+import re
+from urllib.parse import quote
+
+import docx
+from docx.enum.text import WD_ALIGN_PARAGRAPH
+from docx.oxml.ns import qn
+from docx.shared import Pt
+
+from ..models.schemas import WordExportOutlineItem, WordExportRequest
+
+
+def _set_run_font_simsun(run: docx.text.run.Run) -> None:
+    run.font.name = "宋体"
+    rpr = run._element.rPr
+    if rpr is not None and rpr.rFonts is not None:
+        rpr.rFonts.set(qn("w:eastAsia"), "宋体")
+
+
+def _set_paragraph_font_simsun(paragraph: docx.text.paragraph.Paragraph) -> None:
+    for run in paragraph.runs:
+        _set_run_font_simsun(run)
+
+
+class WordExportService:
+    """负责将目录数据导出为 Word 文档。"""
+
+    @staticmethod
+    def export_outline(request: WordExportRequest) -> tuple[io.BytesIO, dict[str, str]]:
+        doc = docx.Document()
+        WordExportService._init_document_styles(doc)
+        WordExportService._add_document_intro(doc, request.project_name)
+        WordExportService._add_outline_items(doc, request.outline)
+
+        buffer = io.BytesIO()
+        doc.save(buffer)
+        buffer.seek(0)
+
+        filename = f"{request.project_name or '标书文档'}.docx"
+        headers = {
+            "Content-Disposition": f"attachment; filename*=UTF-8''{quote(filename)}",
+        }
+        return buffer, headers
+
+    @staticmethod
+    def _init_document_styles(doc: docx.Document) -> None:
+        try:
+            styles = doc.styles
+            base_styles = ["Normal", "Heading 1", "Heading 2", "Heading 3", "Title"]
+            for style_name in base_styles:
+                if style_name not in styles:
+                    continue
+                style = styles[style_name]
+                font = style.font
+                font.name = "宋体"
+                if style._element.rPr is None:
+                    style._element._add_rPr()
+                style._element.rPr.rFonts.set(qn("w:eastAsia"), "宋体")
+                if style_name == "Normal":
+                    font.bold = False
+        except Exception:
+            pass
+
+    @staticmethod
+    def _add_document_intro(
+        doc: docx.Document, project_name: str | None
+    ) -> None:
+        declaration = doc.add_paragraph()
+        declaration_run = declaration.add_run("内容由AI生成")
+        declaration_run.italic = True
+        declaration_run.font.size = Pt(9)
+        _set_run_font_simsun(declaration_run)
+        declaration.alignment = WD_ALIGN_PARAGRAPH.CENTER
+
+        title_paragraph = doc.add_paragraph()
+        title_run = title_paragraph.add_run(project_name or "投标技术文件")
+        title_run.bold = True
+        title_run.font.size = Pt(16)
+        _set_run_font_simsun(title_run)
+        title_paragraph.alignment = WD_ALIGN_PARAGRAPH.CENTER
+
+
+    @staticmethod
+    def _add_markdown_runs(para: docx.text.paragraph.Paragraph, text: str) -> None:
+        pattern = r"(\*\*.*?\*\*|\*.*?\*|`.*?`)"
+        parts = re.split(pattern, text)
+        for part in parts:
+            if not part:
+                continue
+            run = para.add_run()
+            if part.startswith("**") and part.endswith("**") and len(part) > 4:
+                run.text = part[2:-2]
+                run.bold = True
+            elif part.startswith("*") and part.endswith("*") and len(part) > 2:
+                run.text = part[1:-1]
+                run.italic = True
+            elif part.startswith("`") and part.endswith("`") and len(part) > 2:
+                run.text = part[1:-1]
+            else:
+                run.text = part
+            _set_run_font_simsun(run)
+
+    @staticmethod
+    def _add_markdown_paragraph(doc: docx.Document, text: str) -> None:
+        para = doc.add_paragraph()
+        WordExportService._add_markdown_runs(para, text)
+        para.paragraph_format.space_after = Pt(6)
+
+    @staticmethod
+    def _parse_markdown_blocks(content: str) -> list[tuple]:
+        blocks: list[tuple] = []
+        lines = content.split("\n")
+        i = 0
+
+        while i < len(lines):
+            line = lines[i].rstrip("\r").strip()
+            if not line:
+                i += 1
+                continue
+
+            if (
+                line.startswith("- ")
+                or line.startswith("* ")
+                or re.match(r"^\d+\.\s", line)
+            ):
+                items: list[tuple] = []
+                while i < len(lines):
+                    raw = lines[i].rstrip("\r")
+                    stripped = raw.strip()
+                    if stripped.startswith("- ") or stripped.startswith("* "):
+                        text = re.sub(r"^[-*]\s+", "", stripped).strip()
+                        if text:
+                            items.append(("unordered", None, text))
+                        i += 1
+                        continue
+                    match_number = re.match(r"^(\d+)\.\s+(.*)$", stripped)
+                    if match_number:
+                        num_str, text = match_number.groups()
+                        if text.strip():
+                            items.append(("ordered", num_str, text.strip()))
+                        i += 1
+                        continue
+                    break
+                if items:
+                    blocks.append(("list", items))
+                continue
+
+            if "|" in line:
+                rows: list[str] = []
+                while i < len(lines):
+                    stripped = lines[i].rstrip("\r").strip()
+                    if "|" not in stripped:
+                        break
+                    if not re.match(r"^\|?[-\s\|]+\|?$", stripped):
+                        cells = [cell.strip() for cell in stripped.split("|")]
+                        row_text = " | ".join([cell for cell in cells if cell])
+                        if row_text:
+                            rows.append(row_text)
+                    i += 1
+                if rows:
+                    blocks.append(("table", rows))
+                continue
+
+            if line.startswith("#"):
+                match_heading = re.match(r"^(#+)\s*(.*)$", line)
+                if match_heading:
+                    level_marks, title_text = match_heading.groups()
+                    blocks.append(
+                        ("heading", min(len(level_marks), 3), title_text.strip())
+                    )
+                i += 1
+                continue
+
+            para_lines: list[str] = []
+            while i < len(lines):
+                stripped = lines[i].rstrip("\r").strip()
+                if (
+                    stripped
+                    and not stripped.startswith("-")
+                    and not stripped.startswith("*")
+                    and "|" not in stripped
+                    and not stripped.startswith("#")
+                ):
+                    para_lines.append(stripped)
+                    i += 1
+                else:
+                    break
+            if para_lines:
+                blocks.append(("paragraph", " ".join(para_lines)))
+            else:
+                i += 1
+
+        return blocks
+
+    @staticmethod
+    def _render_markdown_blocks(doc: docx.Document, blocks: list[tuple]) -> None:
+        for block in blocks:
+            kind = block[0]
+            if kind == "list":
+                for item_kind, num_str, text in block[1]:
+                    paragraph = doc.add_paragraph()
+                    prefix = "• " if item_kind == "unordered" else f"{num_str}. "
+                    run = paragraph.add_run(prefix)
+                    _set_run_font_simsun(run)
+                    WordExportService._add_markdown_runs(paragraph, text)
+            elif kind == "table":
+                for row in block[1]:
+                    WordExportService._add_markdown_paragraph(doc, row)
+            elif kind == "heading":
+                _, level, text = block
+                heading = doc.add_heading(text, level=level)
+                heading.alignment = WD_ALIGN_PARAGRAPH.LEFT
+                _set_paragraph_font_simsun(heading)
+            elif kind == "paragraph":
+                WordExportService._add_markdown_paragraph(doc, block[1])
+
+    @staticmethod
+    def _add_markdown_content(doc: docx.Document, content: str) -> None:
+        blocks = WordExportService._parse_markdown_blocks(content)
+        WordExportService._render_markdown_blocks(doc, blocks)
+
+    @staticmethod
+    def _add_outline_items(
+        doc: docx.Document, items: list[WordExportOutlineItem], level: int = 1
+    ) -> None:
+        for item in items:
+            if level <= 3:
+                heading = doc.add_heading(f"{item.id} {item.title}", level=level)
+                heading.alignment = WD_ALIGN_PARAGRAPH.LEFT
+                _set_paragraph_font_simsun(heading)
+            else:
+                para = doc.add_paragraph()
+                run = para.add_run(f"{item.id} {item.title}")
+                run.bold = True
+                _set_run_font_simsun(run)
+                para.paragraph_format.space_before = Pt(6)
+                para.paragraph_format.space_after = Pt(3)
+
+            if not item.children:
+                content = item.content or ""
+                if content.strip():
+                    WordExportService._add_markdown_content(doc, content)
+                continue
+
+            WordExportService._add_outline_items(doc, item.children, level + 1)

archive/backend/app/utils/config_manager.py

@@ -0,0 +1,50 @@
+"""配置管理工具"""
+
+import json
+import logging
+import os
+from typing import Dict, Optional
+
+logger = logging.getLogger(__name__)
+
+
+class ConfigManager:
+    """用户配置管理器"""
+
+    def __init__(self):
+        # 配置文件路径 - 存储到用户家目录中
+        self.config_dir = os.path.join(os.path.expanduser("~"), ".ai_write_helper")
+        self.config_file = os.path.join(self.config_dir, "user_config.json")
+
+        # 确保配置目录存在
+        os.makedirs(self.config_dir, exist_ok=True)
+
+    def load_config(self) -> Dict:
+        """从本地JSON文件加载配置"""
+        default_config = {"api_key": "", "base_url": "", "model_name": "gpt-3.5-turbo"}
+
+        if os.path.exists(self.config_file):
+            try:
+                with open(self.config_file, "r", encoding="utf-8") as f:
+                    loaded_config = json.load(f)
+                    default_config.update(loaded_config)
+            except Exception as exc:
+                logger.warning("读取配置文件失败，使用默认配置: %s", exc)
+
+        return default_config
+
+    def save_config(self, api_key: str, base_url: str, model_name: str) -> bool:
+        """保存配置到本地JSON文件"""
+        config = {"api_key": api_key, "base_url": base_url, "model_name": model_name}
+
+        try:
+            with open(self.config_file, "w", encoding="utf-8") as f:
+                json.dump(config, f, ensure_ascii=False, indent=2)
+            return True
+        except Exception as exc:
+            logger.warning("保存配置文件失败: %s", exc)
+            return False
+
+
+# 全局配置管理器实例
+config_manager = ConfigManager()

archive/backend/app/utils/errors.py

@@ -0,0 +1,10 @@
+"""应用级异常定义。"""
+
+
+class AppError(Exception):
+    """用于在 service 层传递可预期的业务错误。"""
+
+    def __init__(self, message: str, status_code: int = 500):
+        super().__init__(message)
+        self.message = message
+        self.status_code = status_code

archive/backend/app/utils/logging_setup.py

@@ -0,0 +1,42 @@
+"""日志初始化工具。"""
+
+from __future__ import annotations
+
+import logging
+import os
+from datetime import datetime
+from pathlib import Path
+
+
+_FILE_HANDLER_FLAG = "_yibiao_file_logging_enabled"
+
+
+def _backend_dir() -> Path:
+    return Path(__file__).resolve().parents[2]
+
+
+def setup_logging(enable_file_logging: bool) -> None:
+    """初始化通用日志配置。"""
+    if not enable_file_logging:
+        return
+
+    root_logger = logging.getLogger()
+    if getattr(root_logger, _FILE_HANDLER_FLAG, False):
+        return
+
+    logs_dir = _backend_dir() / "logs"
+    logs_dir.mkdir(parents=True, exist_ok=True)
+
+    file_name = f"app-{datetime.now():%Y%m%d}-{os.getpid()}.log"
+    file_handler = logging.FileHandler(logs_dir / file_name, encoding="utf-8")
+    file_handler.setLevel(logging.DEBUG)
+    file_handler.setFormatter(
+        logging.Formatter(
+            "%(asctime)s [%(levelname)s] %(name)s: %(message)s",
+            datefmt="%Y-%m-%d %H:%M:%S",
+        )
+    )
+
+    root_logger.setLevel(logging.DEBUG)
+    root_logger.addHandler(file_handler)
+    setattr(root_logger, _FILE_HANDLER_FLAG, True)

archive/backend/app/utils/openai_util.py

@@ -0,0 +1,489 @@
+"""OpenAI 调用公共工具。"""
+
+import json
+import logging
+import uuid
+from typing import Any, AsyncGenerator, Awaitable, Callable, Dict, List
+
+import openai
+from pydantic import BaseModel, ValidationError
+
+from ..config import settings
+from ..utils.config_manager import config_manager
+from ..utils.errors import AppError
+from .prompts.json_repair_prompts import build_json_repair_messages
+
+logger = logging.getLogger(__name__)
+
+ProgressCallback = Callable[[str], Awaitable[None]]
+JsonValidator = Callable[[Dict[str, Any]], None]
+
+
+class OpenAIUtil:
+    """封装 OpenAI SDK 调用、日志与 JSON 修复能力。"""
+
+    def __init__(self):
+        config = config_manager.load_config()
+        self.api_key = config.get("api_key", "")
+        self.base_url = config.get("base_url", "")
+        self.model_name = config.get("model_name", "gpt-3.5-turbo")
+        if not self.api_key:
+            raise AppError("请先配置OpenAI API密钥", status_code=400)
+        self.client = openai.AsyncOpenAI(
+            api_key=self.api_key,
+            base_url=self.base_url or None,
+        )
+
+    def _chat_endpoint_url(self) -> str:
+        """获取聊天完成接口地址。"""
+        base_url = (self.base_url or "https://api.openai.com/v1").rstrip("/")
+        return f"{base_url}/chat/completions"
+
+    def _log_ai_request(
+        self,
+        request_id: str,
+        messages: list[dict[str, str]],
+        temperature: float,
+        response_format: dict | None,
+    ) -> None:
+        """记录 AI 请求日志。"""
+        if not settings.enable_file_logging:
+            return
+
+        logger.debug(
+            "AI_REQUEST %s",
+            json.dumps(
+                {
+                    "request_id": request_id,
+                    "url": self._chat_endpoint_url(),
+                    "model": self.model_name,
+                    "temperature": temperature,
+                    "response_format": response_format,
+                    "messages": messages,
+                },
+                ensure_ascii=False,
+            ),
+        )
+
+    def _log_ai_response(self, request_id: str, content: str) -> None:
+        """记录 AI 响应日志。"""
+        if not settings.enable_file_logging:
+            return
+
+        logger.debug(
+            "AI_RESPONSE %s",
+            json.dumps(
+                {
+                    "request_id": request_id,
+                    "url": self._chat_endpoint_url(),
+                    "model": self.model_name,
+                    "content": content,
+                },
+                ensure_ascii=False,
+            ),
+        )
+
+    def _log_ai_raw_response(
+        self,
+        request_id: str,
+        raw_chunks: list[dict[str, Any]],
+        content: str,
+    ) -> None:
+        """记录 AI 接口原始响应日志。"""
+        if not settings.enable_file_logging:
+            return
+
+        logger.debug(
+            "AI_RAW_RESPONSE %s",
+            json.dumps(
+                {
+                    "request_id": request_id,
+                    "url": self._chat_endpoint_url(),
+                    "model": self.model_name,
+                    "raw_chunks": raw_chunks,
+                    "content": content,
+                },
+                ensure_ascii=False,
+                default=str,
+            ),
+        )
+
+    def _log_ai_error(
+        self,
+        request_id: str,
+        messages: list[dict[str, str]],
+        temperature: float,
+        response_format: dict | None,
+        partial_content: str,
+        raw_chunks: list[dict[str, Any]],
+        error: Exception,
+    ) -> None:
+        """记录 AI 异常日志。"""
+        if not settings.enable_file_logging:
+            return
+
+        logger.debug(
+            "AI_ERROR %s",
+            json.dumps(
+                {
+                    "request_id": request_id,
+                    "url": self._chat_endpoint_url(),
+                    "model": self.model_name,
+                    "temperature": temperature,
+                    "response_format": response_format,
+                    "messages": messages,
+                    "partial_content": partial_content,
+                    "raw_chunks": raw_chunks,
+                    "error": str(error),
+                },
+                ensure_ascii=False,
+                default=str,
+            ),
+        )
+
+    @staticmethod
+    def _dump_chunk(chunk: Any) -> dict[str, Any]:
+        """序列化 OpenAI SDK 返回的 chunk。"""
+        if hasattr(chunk, "model_dump"):
+            return chunk.model_dump(mode="json")
+        return {"raw": str(chunk)}
+
+    @staticmethod
+    def _extract_json_content(content: str) -> str:
+        """提取模型响应中的 JSON 内容，兼容 Markdown 代码块包裹。"""
+        normalized = content.strip()
+        if not normalized.startswith("```"):
+            return normalized
+
+        lines = normalized.splitlines()
+        if not lines:
+            return normalized
+
+        first_line = lines[0].strip().lower()
+        last_line = lines[-1].strip()
+        if not last_line.startswith("```"):
+            return normalized
+
+        if first_line in {"```", "```json", "```javascript", "```js"}:
+            return "\n".join(lines[1:-1]).strip()
+
+        return normalized
+
+    @staticmethod
+    def _is_response_format_unsupported_error(message: str) -> bool:
+        """判断当前错误是否表示模型不支持 response_format。"""
+        normalized = message.lower()
+        if "response_format" not in normalized:
+            return False
+
+        return any(
+            marker in normalized
+            for marker in (
+                "not supported",
+                "does not support",
+                "not support",
+                "unsupported",
+                "unknown parameter",
+                "invalid parameter",
+            )
+        )
+
+    @staticmethod
+    async def emit_progress(
+        progress_callback: ProgressCallback | None,
+        message: str,
+    ) -> None:
+        """发送进度消息。"""
+        if progress_callback is None:
+            return
+
+        await progress_callback(message)
+
+    async def get_available_models(self) -> List[str]:
+        """获取可用模型列表。"""
+        try:
+            models = await self.client.models.list()
+        except Exception as exc:
+            raise AppError(f"获取模型列表失败: {exc}", status_code=502) from exc
+
+        chat_models: list[str] = []
+        for model in models.data:
+            model_id = model.id.lower()
+            if any(
+                keyword in model_id
+                for keyword in ["gpt", "claude", "chat", "llama", "qwen", "deepseek"]
+            ):
+                chat_models.append(model.id)
+        return sorted(set(chat_models))
+
+    async def stream_chat_completion(
+        self,
+        messages: list[dict[str, str]],
+        temperature: float = 0.7,
+        response_format: dict | None = None,
+    ) -> AsyncGenerator[str, None]:
+        """流式调用聊天完成接口。"""
+        request_id = uuid.uuid4().hex
+        parts: list[str] = []
+        raw_chunks: list[dict[str, Any]] = []
+        self._log_ai_request(request_id, messages, temperature, response_format)
+
+        try:
+            stream = await self.client.chat.completions.create(
+                model=self.model_name,
+                messages=messages,
+                temperature=temperature,
+                stream=True,
+                **(
+                    {"response_format": response_format}
+                    if response_format is not None
+                    else {}
+                ),
+            )
+        except Exception as exc:
+            self._log_ai_error(
+                request_id,
+                messages,
+                temperature,
+                response_format,
+                "",
+                raw_chunks,
+                exc,
+            )
+            raise AppError(f"模型调用失败: {exc}", status_code=502) from exc
+
+        try:
+            async for chunk in stream:
+                raw_chunks.append(self._dump_chunk(chunk))
+                if not chunk.choices:
+                    continue
+                content = chunk.choices[0].delta.content
+                if content is not None:
+                    parts.append(content)
+                    yield content
+        except Exception as exc:
+            self._log_ai_error(
+                request_id,
+                messages,
+                temperature,
+                response_format,
+                "".join(parts),
+                raw_chunks,
+                exc,
+            )
+            raise AppError(f"模型调用失败: {exc}", status_code=502) from exc
+
+        self._log_ai_response(request_id, "".join(parts))
+        self._log_ai_raw_response(request_id, raw_chunks, "".join(parts))
+
+    async def collect_chat_completion(
+        self,
+        messages: list[dict[str, str]],
+        temperature: float = 0.7,
+        response_format: dict | None = None,
+    ) -> str:
+        """收集流式输出并拼接为完整文本。"""
+        parts: list[str] = []
+        async for chunk in self.stream_chat_completion(
+            messages,
+            temperature=temperature,
+            response_format=response_format,
+        ):
+            parts.append(chunk)
+        return "".join(parts)
+
+    async def _collect_chat_completion_with_json_mode_fallback(
+        self,
+        messages: list[dict[str, str]],
+        temperature: float,
+        use_response_format: bool,
+        progress_callback: ProgressCallback | None = None,
+    ) -> tuple[str, bool]:
+        """优先使用 JSON 模式请求，不支持时自动降级为普通请求。"""
+        try:
+            content = await self.collect_chat_completion(
+                messages,
+                temperature=temperature,
+                response_format={"type": "json_object"}
+                if use_response_format
+                else None,
+            )
+            return content, use_response_format
+        except AppError as exc:
+            if (
+                not use_response_format
+                or not self._is_response_format_unsupported_error(exc.message)
+            ):
+                raise
+
+            await self.emit_progress(
+                progress_callback,
+                "当前模型不支持结构化 JSON 响应，已降级为普通请求解析。",
+            )
+            content = await self.collect_chat_completion(
+                messages,
+                temperature=temperature,
+                response_format=None,
+            )
+            return content, False
+
+    @staticmethod
+    def _normalize_json_response(
+        content: str,
+        schema: type[BaseModel] | None = None,
+        validator: JsonValidator | None = None,
+    ) -> Dict[str, Any]:
+        """解析、校验并标准化 JSON 响应。"""
+        json_content = OpenAIUtil._extract_json_content(content)
+        parsed = json.loads(json_content)
+
+        if schema is None:
+            normalized = parsed
+        else:
+            validated = schema.model_validate(parsed)
+            normalized = validated.model_dump(exclude_none=True)
+
+        if validator is not None:
+            validator(normalized)
+
+        return normalized
+
+    @staticmethod
+    def _format_json_issues(error: Exception) -> list[str]:
+        """格式化 JSON 解析或校验问题。"""
+        if isinstance(error, json.JSONDecodeError):
+            return [
+                f"JSON 语法错误：第 {error.lineno} 行第 {error.colno} 列附近 {error.msg}。"
+            ]
+
+        if isinstance(error, ValidationError):
+            issues: list[str] = []
+            for item in error.errors():
+                location = ".".join(str(part) for part in item.get("loc", [])) or "root"
+                message = item.get("msg", "字段校验失败")
+                issues.append(f"{location}: {message}")
+            return issues or [str(error)]
+
+        return [str(error)]
+
+    async def _repair_json_response(
+        self,
+        invalid_content: str,
+        issues: list[str],
+        temperature: float,
+        use_response_format: bool,
+        progress_callback: ProgressCallback | None,
+        progress_label: str,
+    ) -> tuple[str, bool]:
+        """基于当前结果发起一次定向 JSON 修复。"""
+        await self.emit_progress(
+            progress_callback,
+            f"{progress_label}格式校验失败，正在基于当前结果进行修复。",
+        )
+        repair_messages = build_json_repair_messages(
+            invalid_content=invalid_content,
+            issues=issues,
+            target_description=progress_label,
+        )
+        return await self._collect_chat_completion_with_json_mode_fallback(
+            messages=repair_messages,
+            temperature=temperature,
+            use_response_format=use_response_format,
+            progress_callback=progress_callback,
+        )
+
+    async def collect_json_response(
+        self,
+        messages: list[dict[str, str]],
+        temperature: float = 0.7,
+        schema: type[BaseModel] | None = None,
+        validator: JsonValidator | None = None,
+        progress_callback: ProgressCallback | None = None,
+        progress_label: str = "JSON结果",
+        failure_message: str = "模型返回的 JSON 数据格式无效",
+    ) -> Dict[str, Any]:
+        """收集并校验 JSON 响应。"""
+        max_retries = 2
+        total_attempts = max_retries + 1
+        use_response_format = True
+
+        for attempt in range(total_attempts):
+            try:
+                (
+                    content,
+                    use_response_format,
+                ) = await self._collect_chat_completion_with_json_mode_fallback(
+                    messages=messages,
+                    temperature=temperature,
+                    use_response_format=use_response_format,
+                    progress_callback=progress_callback,
+                )
+                normalized = self._normalize_json_response(
+                    content,
+                    schema=schema,
+                    validator=validator,
+                )
+                return normalized
+            except (json.JSONDecodeError, ValidationError, ValueError) as exc:
+                issues = self._format_json_issues(exc)
+                logger.warning(
+                    "模型返回非法 JSON，第 %s/%s 次尝试: %s；问题: %s",
+                    attempt + 1,
+                    total_attempts,
+                    content,
+                    " | ".join(issues),
+                )
+
+                try:
+                    (
+                        repaired_content,
+                        use_response_format,
+                    ) = await self._repair_json_response(
+                        invalid_content=content,
+                        issues=issues,
+                        temperature=temperature,
+                        use_response_format=use_response_format,
+                        progress_callback=progress_callback,
+                        progress_label=progress_label,
+                    )
+                    normalized = self._normalize_json_response(
+                        repaired_content,
+                        schema=schema,
+                        validator=validator,
+                    )
+                    return normalized
+                except AppError as repair_error:
+                    logger.warning(
+                        "JSON 修复请求失败，第 %s/%s 次尝试: %s",
+                        attempt + 1,
+                        total_attempts,
+                        repair_error.message,
+                    )
+                    exc = repair_error
+                except (
+                    json.JSONDecodeError,
+                    ValidationError,
+                    ValueError,
+                ) as repair_error:
+                    logger.warning(
+                        "JSON 修复后仍校验失败，第 %s/%s 次尝试: %s；问题: %s",
+                        attempt + 1,
+                        total_attempts,
+                        repaired_content,
+                        " | ".join(self._format_json_issues(repair_error)),
+                    )
+                    exc = repair_error
+
+                if attempt == max_retries:
+                    await self.emit_progress(
+                        progress_callback,
+                        f"{progress_label}连续 {total_attempts} 次校验失败。",
+                    )
+                    raise AppError(failure_message, status_code=502) from exc
+
+                await self.emit_progress(
+                    progress_callback,
+                    f"{progress_label}第 {attempt + 1}/{total_attempts} 次校验失败，正在重试。",
+                )
+
+        raise AppError(failure_message, status_code=502)

archive/backend/app/utils/prompts/__init__.py

@@ -0,0 +1,38 @@
+"""提示词模块导出。"""
+
+from .analysis_prompts import build_analysis_messages
+from .content_prompts import build_chapter_content_messages
+from .expand_prompts import build_expand_outline_messages, read_expand_outline_prompt
+from .json_repair_prompts import build_json_repair_messages
+from .outline_prompts import (
+    extract_requirement_groups_messages,
+    generate_aligned_children_outline_prompt,
+    generate_aligned_children_outline_with_old_prompt,
+    generate_children_outline_prompt,
+    generate_children_outline_with_old_prompt,
+    generate_outline_prompt,
+    generate_outline_with_old_prompt,
+    generate_top_level_outline_prompt,
+    generate_top_level_outline_with_old_prompt,
+    review_aligned_outline_messages,
+    review_outline_messages,
+)
+
+__all__ = [
+    "build_analysis_messages",
+    "build_chapter_content_messages",
+    "build_expand_outline_messages",
+    "build_json_repair_messages",
+    "extract_requirement_groups_messages",
+    "generate_aligned_children_outline_prompt",
+    "generate_aligned_children_outline_with_old_prompt",
+    "generate_children_outline_prompt",
+    "generate_children_outline_with_old_prompt",
+    "generate_outline_prompt",
+    "generate_outline_with_old_prompt",
+    "generate_top_level_outline_prompt",
+    "generate_top_level_outline_with_old_prompt",
+    "read_expand_outline_prompt",
+    "review_aligned_outline_messages",
+    "review_outline_messages",
+]

archive/backend/app/utils/prompts/analysis_prompts.py

@@ -0,0 +1,72 @@
+"""标书解析相关提示词。"""
+
+from typing import Dict, List
+
+
+def build_analysis_messages(
+    file_content: str, analysis_type: str
+) -> List[Dict[str, str]]:
+    """构建文档分析消息。"""
+    system_prompt = """你是一名专业的招标文件分析助手。请严格基于用户提供的招标文件原文完成分析任务。
+
+通用要求：
+1. 保持提取信息的全面性和准确性，尽量使用原文内容，不要自行编造
+2. 只输出最终分析结果，不要输出额外说明、过程、提示语或客套话
+3. 如果文档内容不足以支持某项结论，应明确说明原文未提及，不要凭空补充
+"""
+
+    file_prompt = f"""以下是完整招标文件全文，请先完整阅读，并仅基于原文完成后续任务：
+
+{file_content}"""
+
+    if analysis_type == "overview":
+        task_prompt = """任务：提取并总结项目概述信息。
+
+请重点关注以下方面：
+1. 项目名称和基本信息
+2. 项目背景和目的
+3. 项目规模和预算
+4. 项目时间安排
+5. 项目要实施的具体内容
+6. 主要技术特点
+7. 其他关键要求
+
+工作要求：
+1. 保持提取信息的全面性和准确性，尽量使用原文内容，不要自己编写
+2. 只关注与项目实施有关的内容，不提取商务信息
+3. 直接返回整理好的项目概述，除此之外不返回任何其他内容
+"""
+    else:
+        task_prompt = """任务：提取技术评分要求。
+
+你是一名专业的招标文件分析师，擅长从复杂的招标文档中高效提取“技术评分项”相关内容。请严格按照以下步骤和规则执行任务：
+### 1. 目标定位
+- 重点识别文档中与“技术评分”、“评标方法”、“评分标准”、“技术参数”、“技术要求”、“技术方案”、“技术部分”或“评审要素”相关的章节（如“第X章 评标方法”或“附件X：技术评分表”）。
+- 一定不要提取商务、价格、资质等与技术类评分项无关的条目。
+### 2. 提取内容要求
+对每一项技术评分项，按以下结构化格式输出（若信息缺失，标注“未提及”），如果评分项不够明确，你需要根据上下文分析并也整理成如下格式：
+【评分项名称】：<原文描述，保留专业术语>
+【权重/分值】：<具体分值或占比，如“30分”或“40%”>
+【评分标准】：<详细规则，如“≥95%得满分，每低1%扣0.5分”>
+【数据来源】：<文档中的位置，如“第5.2.3条”或“附件3-表2”>
+
+### 3. 处理规则
+- 模糊表述：有些招标文件格式不是很标准，没有明确的“技术评分表”，但一定都会有“技术评分”相关内容，请根据上下文判断评分项。
+- 表格处理：若评分项以表格形式呈现，按行提取，并标注“[表格数据]”。
+- 分层结构：若存在二级评分项（如“技术方案→子项1、子项2”），用缩进或编号体现层级关系。
+- 单位统一：将所有分值统一为“分”或“%”，并注明原文单位。
+
+### 4. 验证步骤
+提取完成后，执行以下自检：
+- [ ] 所有技术评分项是否覆盖（无遗漏）？
+- [ ] 是否错误提取商务、价格、资质等与技术类评分项无关的条目？
+- [ ] 权重总和是否与文档声明的技术分总分一致（如“技术部分共60分”）？
+
+直接返回提取结果，除此之外不输出任何其他内容
+"""
+
+    return [
+        {"role": "system", "content": system_prompt},
+        {"role": "user", "content": file_prompt},
+        {"role": "user", "content": task_prompt},
+    ]

archive/backend/app/utils/prompts/content_prompts.py

@@ -0,0 +1,70 @@
+"""正文生成相关提示词。"""
+
+from typing import Any, Dict, List
+
+
+def build_chapter_content_messages(
+    chapter: Dict[str, Any],
+    parent_chapters: List[Dict[str, Any]] | None = None,
+    sibling_chapters: List[Dict[str, Any]] | None = None,
+    project_overview: str = "",
+) -> List[Dict[str, str]]:
+    """构建章节正文生成消息。"""
+    chapter_id = chapter.get("id", "unknown")
+    chapter_title = chapter.get("title", "未命名章节")
+    chapter_description = chapter.get("description", "")
+
+    system_prompt = """你是一个专业的标书编写专家，负责为投标文件的技术标部分生成具体内容。
+
+要求：
+1. 内容要专业、准确，与章节标题和描述保持一致。
+2. 这是技术方案，不是宣传报告，注意朴实无华，不要假大空。
+3. 语言要正式、规范，符合标书写作要求，但不要使用奇怪的连接词，不要让人觉得内容像是 AI 生成的。
+4. 内容要详细具体，避免空泛的描述。
+5. 注意避免与同级章节内容重复，保持内容的独特性和互补性。
+6. 直接返回章节内容，不生成标题，不要任何额外说明或格式标记。
+"""
+
+    messages: list[dict[str, str]] = [{"role": "system", "content": system_prompt}]
+
+    if project_overview.strip():
+        messages.append(
+            {"role": "user", "content": f"项目概述信息：\n{project_overview}"}
+        )
+
+    if parent_chapters:
+        parent_lines = ["上级章节信息："]
+        for parent in parent_chapters:
+            parent_lines.append(
+                f"- {parent.get('id', 'unknown')} {parent.get('title', '未命名章节')}\n  {parent.get('description', '')}"
+            )
+        messages.append({"role": "user", "content": "\n".join(parent_lines)})
+
+    if sibling_chapters:
+        sibling_lines = ["同级章节信息（请避免内容重复）："]
+        for sibling in sibling_chapters:
+            if sibling.get("id") == chapter_id:
+                continue
+            sibling_lines.append(
+                f"- {sibling.get('id', 'unknown')} {sibling.get('title', '未命名章节')}\n  {sibling.get('description', '')}"
+            )
+        if len(sibling_lines) > 1:
+            messages.append({"role": "user", "content": "\n".join(sibling_lines)})
+
+    messages.append(
+        {
+            "role": "user",
+            "content": f"""请为以下标书章节生成具体内容：
+
+当前章节信息：
+章节ID: {chapter_id}
+章节标题: {chapter_title}
+章节描述: {chapter_description}
+
+请根据项目概述信息和上述章节层级关系，生成详细的专业内容，确保与上级章节的内容逻辑相承，同时避免与同级章节内容重复，突出本章节的独特性和技术方案优势。
+正文中不要重复章节标题。
+直接返回编写的正文内容，不要输出标题、解释、总结等任何其他内容""",
+        }
+    )
+
+    return messages

archive/backend/app/utils/prompts/expand_prompts.py

@@ -0,0 +1,56 @@
+"""扩写目录提取相关提示词。"""
+
+from typing import Dict, List
+
+
+def read_expand_outline_prompt() -> str:
+    """从简版技术方案中提取目录的系统提示词。"""
+    return """你是一个专业的标书编写专家。请严格基于用户提交的标书技术方案原文完成目录提取任务。
+
+要求：
+1. 目录结构要全面覆盖技术标的所有必要目录，包含多级目录
+2. 如果技术方案中有章节名称，则直接使用技术方案中的章节名称
+3. 如果技术方案中没有章节名称，则结合全文，总结出章节名称
+4. 返回标准 JSON 格式，包含章节编号、标题、描述和子章节，注意编号要连贯
+5. 除了 JSON 结果外，不要输出任何其他内容
+
+JSON 格式要求：
+{
+  "outline": [
+    {
+      "id": "1",
+      "title": "",
+      "description": "",
+      "children": [
+        {
+          "id": "1.1",
+          "title": "",
+          "description": "",
+          "children": [
+            {
+              "id": "1.1.1",
+              "title": "",
+              "description": ""
+            }
+          ]
+        }
+      ]
+    }
+  ]
+}
+"""
+
+
+def build_expand_outline_messages(file_content: str) -> List[Dict[str, str]]:
+    """构建方案扩写目录提取消息。"""
+    return [
+        {"role": "system", "content": read_expand_outline_prompt()},
+        {
+            "role": "user",
+            "content": f"以下是完整技术方案全文，请先完整阅读，并仅基于原文完成后续任务：\n\n{file_content}",
+        },
+        {
+            "role": "user",
+            "content": "请从上述技术方案中提取完整目录结构，确保覆盖技术标的所有必要目录，并按要求返回标准 JSON。",
+        },
+    ]

archive/backend/app/utils/prompts/json_repair_prompts.py

@@ -0,0 +1,36 @@
+"""JSON 修复相关提示词。"""
+
+from typing import Dict, List
+
+
+def build_json_repair_messages(
+    invalid_content: str,
+    issues: list[str],
+    target_description: str,
+) -> List[Dict[str, str]]:
+    """构建 JSON 定向修复消息。"""
+    issue_lines = [f"{index}. {item}" for index, item in enumerate(issues, start=1)]
+
+    system_prompt = """你是一个严格的 JSON 修复助手。请根据给出的原始内容和校验问题，修复现有结果。
+
+要求：
+1. 优先在原结果基础上做最小必要修改，不要整体重写
+2. 尽量保留原有结构、字段值、节点顺序和已生成内容
+3. 若缺少必填字段，应结合现有上下文补齐合理内容，不要用空字符串敷衍
+4. 若存在多余说明、代码块包裹、字段名错误、children 结构不规范或顶层包裹错误，应修正为合法 JSON
+5. 只返回修复后的完整 JSON，不要输出任何解释
+"""
+
+    return [
+        {"role": "system", "content": system_prompt},
+        {"role": "user", "content": f"目标结果类型：{target_description}"},
+        {"role": "user", "content": "当前校验问题：\n" + "\n".join(issue_lines)},
+        {
+            "role": "user",
+            "content": f"待修复内容：\n```json\n{invalid_content}\n```",
+        },
+        {
+            "role": "user",
+            "content": "请在保留原有正确内容的前提下，仅修复上述问题，并返回完整 JSON。",
+        },
+    ]

archive/backend/app/utils/prompts/outline_prompts.py

@@ -0,0 +1,397 @@
+"""目录生成相关提示词。"""
+
+from typing import Any, Dict, List
+
+
+def _build_outline_system_prompt() -> str:
+    """构建目录生成的共享系统提示词。"""
+    return """你是一个专业的标书编写专家。根据提供的项目概述和技术评分要求，生成投标文件中技术标部分的目录结构。
+如果用户提供了自己编写的目录，你要保证目录满足技术评分要求，并充分结合用户自己编写的目录。
+
+要求：
+1. 目录结构要全面覆盖技术标的所有必要章节
+2. 章节名称要专业、准确，符合投标文件规范
+3. 一级目录名称要与技术评分要求中的章节名称一致；如果技术评分要求中没有明确章节名称，则结合内容总结一级目录名称
+4. 一共包括三级目录
+5. 返回标准 JSON 格式，包含章节编号、标题、描述和子章节
+6. 除了 JSON 结果外，不要输出任何其他内容
+
+JSON 格式要求：
+{
+  "outline": [
+    {
+      "id": "1",
+      "title": "",
+      "description": "",
+      "children": [
+        {
+          "id": "1.1",
+          "title": "",
+          "description": "",
+          "children": [
+            {
+              "id": "1.1.1",
+              "title": "",
+              "description": ""
+            }
+          ]
+        }
+      ]
+    }
+  ]
+}
+"""
+
+
+def _build_top_level_outline_system_prompt() -> str:
+    """构建仅生成一级目录的系统提示词。"""
+    return """你是一个专业的标书编写专家。根据提供的项目概述和技术评分要求，生成投标文件中技术标部分的一级目录结构。
+如果用户提供了自己编写的目录，你要保证一级目录满足技术评分要求，并充分结合用户自己编写的目录。
+
+要求：
+1. 只生成一级目录，不要生成二级和三级目录
+2. 一级目录名称要专业、准确，符合投标文件规范
+3. 一级目录名称要尽量与技术评分要求中的章节名称一致；如果技术评分要求中没有明确章节名称，则结合内容总结一级目录名称
+4. 返回标准 JSON 格式，使用 outline 字段，每个一级目录必须包含 id、title、description
+5. 除了 JSON 结果外，不要输出任何其他内容
+
+JSON 格式要求：
+{
+  "outline": [
+    {
+      "id": "1",
+      "title": "",
+      "description": ""
+    }
+  ]
+}
+"""
+
+
+def _format_revision_suggestions(suggestions: list[str] | None) -> str:
+    """格式化目录修正建议。"""
+    if not suggestions:
+        return ""
+
+    suggestion_lines = [
+        f"{index}. {item}" for index, item in enumerate(suggestions, start=1)
+    ]
+    return "\n\n本轮修正建议：\n" + "\n".join(suggestion_lines)
+
+
+def generate_outline_prompt(
+    overview: str,
+    requirements: str,
+    suggestions: list[str] | None = None,
+) -> List[Dict[str, str]]:
+    """生成标准目录的提示词。"""
+    return [
+        {"role": "system", "content": _build_outline_system_prompt()},
+        {"role": "user", "content": f"项目概述：\n{overview}"},
+        {"role": "user", "content": f"技术评分要求：\n{requirements}"},
+        {
+            "role": "user",
+            "content": "请生成完整的技术标目录结构，确保覆盖所有技术评分要点。"
+            + _format_revision_suggestions(suggestions),
+        },
+    ]
+
+
+def generate_outline_with_old_prompt(
+    overview: str,
+    requirements: str,
+    old_outline: str | None,
+    suggestions: list[str] | None = None,
+) -> List[Dict[str, str]]:
+    """生成基于旧目录扩写的提示词。"""
+    return [
+        {"role": "system", "content": _build_outline_system_prompt()},
+        {"role": "user", "content": f"项目概述：\n{overview}"},
+        {"role": "user", "content": f"技术评分要求：\n{requirements}"},
+        {"role": "user", "content": f"用户自己编写的目录：\n{old_outline or ''}"},
+        {
+            "role": "user",
+            "content": "请在满足技术评分要求的前提下，充分结合用户自己编写的目录，生成完整的技术标目录结构。"
+            + _format_revision_suggestions(suggestions),
+        },
+    ]
+
+
+def generate_top_level_outline_prompt(
+    overview: str,
+    requirements: str,
+    suggestions: list[str] | None = None,
+) -> List[Dict[str, str]]:
+    """生成仅包含一级目录的提示词。"""
+    return [
+        {"role": "system", "content": _build_top_level_outline_system_prompt()},
+        {"role": "user", "content": f"项目概述：\n{overview}"},
+        {"role": "user", "content": f"技术评分要求：\n{requirements}"},
+        {
+            "role": "user",
+            "content": "请仅生成一级目录列表，不要生成二级和三级目录。返回的 JSON 仍然使用 outline 字段，每个一级目录都必须包含 id、title、description。"
+            + _format_revision_suggestions(suggestions),
+        },
+    ]
+
+
+def generate_top_level_outline_with_old_prompt(
+    overview: str,
+    requirements: str,
+    old_outline: str | None,
+    suggestions: list[str] | None = None,
+) -> List[Dict[str, str]]:
+    """生成结合旧目录的一级目录提示词。"""
+    return [
+        {"role": "system", "content": _build_top_level_outline_system_prompt()},
+        {"role": "user", "content": f"项目概述：\n{overview}"},
+        {"role": "user", "content": f"技术评分要求：\n{requirements}"},
+        {"role": "user", "content": f"用户自己编写的目录：\n{old_outline or ''}"},
+        {
+            "role": "user",
+            "content": "请在满足技术评分要求的前提下，充分结合用户自己编写的目录，仅生成一级目录，不要生成二级和三级目录。返回的 JSON 使用 outline 字段，每个一级目录都必须包含 id、title、description。"
+            + _format_revision_suggestions(suggestions),
+        },
+    ]
+
+
+def extract_requirement_groups_messages(
+    requirements: str,
+    suggestions: list[str] | None = None,
+) -> List[Dict[str, str]]:
+    """提取适合作为一级目录的技术评分大类。"""
+    system_prompt = """你是一个专业的招标文件分析专家。请从技术评分要求中提取适合作为技术标一级目录的评分大类。
+
+要求：
+1. 只提取技术评分大类，不要提取商务、报价、资质、售后服务等非技术类条目
+2. 每个大类都必须适合作为技术标一级目录标题，标题要专业、简洁、完整
+3. 同一大类下的细项、子项、分值说明、评分标准要归入 detail_points，不要拆成多个一级目录
+4. requirement_id 必须唯一，使用 R1、R2、R3 这种格式
+5. description 需要概括该大类关注的核心内容
+6. detail_points 中保留该大类下的关键评分细项，使用简洁短句
+7. 只返回 JSON，格式必须为 {"groups": [...]}，不要输出任何其他内容
+
+JSON 格式要求：
+{
+  "groups": [
+    {
+      "requirement_id": "R1",
+      "title": "",
+      "description": "",
+      "detail_points": ["", ""]
+    }
+  ]
+}
+"""
+
+    return [
+        {"role": "system", "content": system_prompt},
+        {"role": "user", "content": f"技术评分要求：\n{requirements}"},
+        {
+            "role": "user",
+            "content": "请提取所有适合作为技术标一级目录的技术评分大类，保持顺序稳定，并把每个大类下的评分细项归入 detail_points。"
+            + _format_revision_suggestions(suggestions),
+        },
+    ]
+
+
+def generate_aligned_children_outline_prompt(
+    overview: str,
+    requirements: str,
+    parent_item: Dict[str, Any],
+    requirement_group: Dict[str, Any],
+    suggestions: list[str] | None = None,
+) -> List[Dict[str, str]]:
+    """围绕指定技术评分大类生成二三级目录。"""
+    parent_id = parent_item.get("id", "1")
+    parent_title = parent_item.get("title", "未命名一级目录")
+    parent_description = parent_item.get("description", "")
+    requirement_id = requirement_group.get("requirement_id", "R1")
+    detail_points = requirement_group.get("detail_points") or []
+    detail_lines = "\n".join(
+        f"- {item}" for item in detail_points if isinstance(item, str) and item.strip()
+    )
+
+    system_prompt = """你是一个专业的标书编写专家。请围绕指定的技术评分大类，为已经固定好的一级目录生成二级和三级目录。
+
+要求：
+1. 一级目录标题和顺序已经固定，不能修改、重命名、合并或删除一级目录
+2. 只输出当前一级目录下的二级和三级目录，不要重复输出一级目录本身
+3. 二级和三级目录要覆盖当前技术评分大类及其细项，不能越界写入其他评分大类内容
+4. 返回标准 JSON，格式为 {"children": [...]}，children 中只能包含当前一级目录的直接子目录
+5. 每个节点必须包含 id、title、description，三级目录继续使用 children 字段
+6. 章节编号必须以给定的一级目录编号为前缀，例如父级是 2，则二级目录编号从 2.1 开始，三级目录编号从 2.1.1 开始
+7. 除了 JSON 结果外，不要输出任何其他内容
+"""
+
+    detail_content = detail_lines or "- 未提供明确细项，请根据评分大类描述合理展开"
+
+    return [
+        {"role": "system", "content": system_prompt},
+        {"role": "user", "content": f"项目概述：\n{overview}"},
+        {"role": "user", "content": f"技术评分要求原文：\n{requirements}"},
+        {
+            "role": "user",
+            "content": f"当前固定一级目录：\n编号：{parent_id}\n标题：{parent_title}\n描述：{parent_description}",
+        },
+        {
+            "role": "user",
+            "content": f"当前对应的技术评分大类：\nrequirement_id：{requirement_id}\n标题：{requirement_group.get('title', '')}\n描述：{requirement_group.get('description', '')}\n细项：\n{detail_content}",
+        },
+        {
+            "role": "user",
+            "content": '请仅生成该一级目录下的二级、三级目录，一级目录标题必须保持为当前给定标题，返回格式必须是 {"children": [...]}。'
+            + _format_revision_suggestions(suggestions),
+        },
+    ]
+
+
+def generate_aligned_children_outline_with_old_prompt(
+    overview: str,
+    requirements: str,
+    parent_item: Dict[str, Any],
+    requirement_group: Dict[str, Any],
+    old_outline: str | None,
+    suggestions: list[str] | None = None,
+) -> List[Dict[str, str]]:
+    """结合旧目录参考，为指定评分大类生成二三级目录。"""
+    messages = generate_aligned_children_outline_prompt(
+        overview=overview,
+        requirements=requirements,
+        parent_item=parent_item,
+        requirement_group=requirement_group,
+        suggestions=suggestions,
+    )
+    messages.insert(
+        5, {"role": "user", "content": f"用户自己编写的目录参考：\n{old_outline or ''}"}
+    )
+    messages[-1] = {
+        "role": "user",
+        "content": '请在覆盖当前技术评分大类细项的前提下，参考用户目录优化当前一级目录下的二级、三级目录，但不得修改当前一级目录标题，返回格式必须是 {"children": [...]}。'
+        + _format_revision_suggestions(suggestions),
+    }
+    return messages
+
+
+def generate_children_outline_prompt(
+    overview: str,
+    requirements: str,
+    parent_item: Dict[str, Any],
+    suggestions: list[str] | None = None,
+) -> List[Dict[str, str]]:
+    """为指定一级目录生成二三级目录。"""
+    parent_id = parent_item.get("id", "1")
+    parent_title = parent_item.get("title", "未命名一级目录")
+    parent_description = parent_item.get("description", "")
+
+    system_prompt = """你是一个专业的标书编写专家。请围绕指定的一级目录，生成其下属的二级目录和三级目录。
+
+要求：
+1. 只输出当前一级目录下的二级和三级目录，不要重复输出一级目录本身
+2. 返回标准 JSON，格式为 {"children": [...]} 
+3. children 中只能包含当前一级目录的直接子目录，每个节点必须包含 id、title、description
+4. 二级目录下如有三级目录，同样使用 children 字段
+5. 章节编号必须以给定的一级目录编号为前缀，例如父级是 2，则二级目录编号从 2.1 开始，三级目录编号从 2.1.1 开始
+6. 除了 JSON 结果外，不要输出任何其他内容
+"""
+
+    return [
+        {"role": "system", "content": system_prompt},
+        {"role": "user", "content": f"项目概述：\n{overview}"},
+        {"role": "user", "content": f"技术评分要求：\n{requirements}"},
+        {
+            "role": "user",
+            "content": f"当前一级目录：\n编号：{parent_id}\n标题：{parent_title}\n描述：{parent_description}",
+        },
+        {
+            "role": "user",
+            "content": '请仅生成该一级目录下的二级、三级目录，返回格式必须是 {"children": [...]}。'
+            + _format_revision_suggestions(suggestions),
+        },
+    ]
+
+
+def generate_children_outline_with_old_prompt(
+    overview: str,
+    requirements: str,
+    parent_item: Dict[str, Any],
+    old_outline: str | None,
+    suggestions: list[str] | None = None,
+) -> List[Dict[str, str]]:
+    """为指定一级目录生成二三级目录，并结合旧目录参考。"""
+    messages = generate_children_outline_prompt(
+        overview=overview,
+        requirements=requirements,
+        parent_item=parent_item,
+        suggestions=suggestions,
+    )
+    messages.insert(
+        4, {"role": "user", "content": f"用户自己编写的目录：\n{old_outline or ''}"}
+    )
+    messages[-1] = {
+        "role": "user",
+        "content": '请在满足技术评分要求的前提下，充分结合用户自己编写的目录，仅生成该一级目录下的二级、三级目录，返回格式必须是 {"children": [...]}。'
+        + _format_revision_suggestions(suggestions),
+    }
+    return messages
+
+
+def review_outline_messages(
+    overview: str,
+    requirements: str,
+    outline_json: str,
+) -> List[Dict[str, str]]:
+    """构建目录审核消息。"""
+    system_prompt = """你是一个严格的招标文件目录审核专家。请审核目录是否符合项目概述和技术评分要求。
+
+要求：
+1. 重点检查目录是否完整覆盖技术评分要点
+2. 检查一级目录名称是否专业、准确，是否尽量与评分项原文保持一致
+3. 检查目录层级是否清晰，是否达到三级目录要求，是否存在明显遗漏、错位、重复或不合理章节
+4. 只返回 JSON，格式为：{"passed": true, "suggestions": []}
+5. 若不通过，suggestions 中必须给出具体、可执行的修改建议
+6. 除了 JSON 外，不要输出任何其他内容
+"""
+
+    return [
+        {"role": "system", "content": system_prompt},
+        {"role": "user", "content": f"项目概述：\n{overview}"},
+        {"role": "user", "content": f"技术评分要求：\n{requirements}"},
+        {"role": "user", "content": f"待审核目录 JSON：\n{outline_json}"},
+        {
+            "role": "user",
+            "content": "请判断该目录是否满足要求。若满足则返回 passed=true；若不满足则返回 passed=false，并给出具体修改建议。",
+        },
+    ]
+
+
+def review_aligned_outline_messages(
+    overview: str,
+    requirements: str,
+    groups_json: str,
+    outline_json: str,
+) -> List[Dict[str, str]]:
+    """构建一一对应模式的目录审核消息。"""
+    system_prompt = """你是一个严格的招标文件目录审核专家。请审核目录是否与技术评分大类一一对应，并判断二三级目录是否覆盖各评分大类的细项。
+
+要求：
+1. 一级目录必须与提供的技术评分大类一一对应，数量一致、顺序一致、标题必须完全一致
+2. 不允许缺失技术评分大类，也不允许新增、合并、改写一级目录
+3. 二级和三级目录要围绕各自对应的技术评分大类与细项展开，避免错位、遗漏和明显重复
+4. 检查完整目录是否层级清晰，整体是否达到三级目录要求
+5. 只返回 JSON，格式为：{"passed": true, "suggestions": []}
+6. 若不通过，suggestions 中必须给出具体、可执行的修改建议，重点说明哪个评分大类覆盖不足或结构不合理
+7. 除了 JSON 外，不要输出任何其他内容
+"""
+
+    return [
+        {"role": "system", "content": system_prompt},
+        {"role": "user", "content": f"项目概述：\n{overview}"},
+        {"role": "user", "content": f"技术评分要求：\n{requirements}"},
+        {"role": "user", "content": f"技术评分大类 JSON：\n{groups_json}"},
+        {"role": "user", "content": f"待审核目录 JSON：\n{outline_json}"},
+        {
+            "role": "user",
+            "content": "请判断该目录是否满足一一对应要求。若满足则返回 passed=true；若不满足则返回 passed=false，并给出具体修改建议。",
+        },
+    ]

archive/backend/app/utils/sse.py

@@ -0,0 +1,67 @@
+"""SSE (Server-Sent Events) 相关工具。"""
+
+import json
+from typing import AsyncGenerator, Any, Dict, Optional
+
+from fastapi.responses import StreamingResponse
+
+
+DEFAULT_SSE_HEADERS: Dict[str, str] = {
+    "Cache-Control": "no-cache",
+    "Connection": "keep-alive",
+    "Content-Type": "text/event-stream",
+}
+
+
+def sse_response(
+    generator: AsyncGenerator[str, Any],
+    media_type: str = "text/event-stream",
+    extra_headers: Optional[Dict[str, str]] = None,
+) -> StreamingResponse:
+    """
+    包装 SSE 异步生成器为 StreamingResponse，统一 headers 和 media_type。
+
+    Args:
+        generator: 异步生成器，yield 已经带好 "data: ..." 和 "\n\n" 的字符串
+        media_type: 响应的 media_type，默认使用 text/event-stream
+        extra_headers: 额外需要添加或覆盖的响应头
+    """
+    headers = DEFAULT_SSE_HEADERS.copy()
+    if extra_headers:
+        headers.update(extra_headers)
+
+    return StreamingResponse(
+        generator,
+        media_type=media_type,
+        headers=headers,
+    )
+
+
+def sse_data(payload: Dict[str, Any]) -> str:
+    """将 payload 包装为标准 SSE data 事件。"""
+    return f"data: {json.dumps(payload, ensure_ascii=False)}\n\n"
+
+
+def sse_chunk(chunk: str) -> str:
+    """输出增量文本块。"""
+    return sse_data({"chunk": chunk})
+
+
+def sse_progress(message: str) -> str:
+    """输出进度事件。"""
+    return sse_data({"type": "progress", "message": message})
+
+
+def sse_result(payload: Dict[str, Any]) -> str:
+    """输出结果事件。"""
+    return sse_data({"type": "result", **payload})
+
+
+def sse_error(message: str) -> str:
+    """输出统一错误事件。"""
+    return sse_data({"error": True, "message": message})
+
+
+def sse_done() -> str:
+    """输出结束标记。"""
+    return "data: [DONE]\n\n"

archive/backend/requirements.txt

@@ -0,0 +1,18 @@
+fastapi==0.116.1
+uvicorn[standard]==0.35.0
+python-multipart==0.0.20
+openai==1.106.1
+python-docx==1.2.0
+PyPDF2==3.0.1
+pydantic==2.11.7
+pydantic-settings==2.10.1
+python-dotenv==1.1.1
+aiofiles==24.1.0
+# 版本兼容性（放宽范围给依赖解析）
+anyio>=4,<5
+# 新增的文档处理库
+pdfplumber==0.11.7
+pymupdf==1.26.4
+docx2python==3.5.0
+aiohttp==3.10.11
+Pillow==10.4.0

archive/backend/run.py

@@ -0,0 +1,17 @@
+"""后端服务启动脚本"""
+import uvicorn
+import os
+import multiprocessing
+
+if __name__ == "__main__":
+    # 确保在正确的目录中运行
+    os.chdir(os.path.dirname(os.path.abspath(__file__)))
+    
+    uvicorn.run(
+        "app.main:app",
+        host="127.0.0.1",
+        port=8000,
+        reload=False,  # 多进程模式下不支持reload
+        log_level="info",
+        workers=multiprocessing.cpu_count() * 2  # CPU核心数的2倍，最大化并发能力
+    )

archive/backend/static/asset-manifest.json

@@ -0,0 +1,13 @@
+{
+  "files": {
+    "main.css": "/static/css/main.e43156b5.css",
+    "main.js": "/static/js/main.5f85d736.js",
+    "index.html": "/index.html",
+    "main.e43156b5.css.map": "/static/css/main.e43156b5.css.map",
+    "main.5f85d736.js.map": "/static/js/main.5f85d736.js.map"
+  },
+  "entrypoints": [
+    "static/css/main.e43156b5.css",
+    "static/js/main.5f85d736.js"
+  ]
+}

archive/backend/static/index.html

@@ -0,0 +1 @@
+<!doctype html><html lang="en"><head><meta charset="utf-8"/><link rel="icon" href="/favicon.ico"/><meta name="viewport" content="width=device-width,initial-scale=1"/><meta name="theme-color" content="#000000"/><meta name="description" content="Web site created using create-react-app"/><link rel="apple-touch-icon" href="/logo192.png"/><link rel="manifest" href="/manifest.json"/><title>易标AI</title><script defer="defer" src="/static/js/main.5f85d736.js"></script><link href="/static/css/main.e43156b5.css" rel="stylesheet"></head><body><noscript>You need to enable JavaScript to run this app.</noscript><div id="root"></div></body></html>

archive/backend/static/manifest.json

@@ -0,0 +1,25 @@
+{
+  "short_name": "易标AI",
+  "name": "易标AI-标书智写",
+  "icons": [
+    {
+      "src": "favicon.ico",
+      "sizes": "64x64 32x32 24x24 16x16",
+      "type": "image/x-icon"
+    },
+    {
+      "src": "logo192.png",
+      "type": "image/png",
+      "sizes": "192x192"
+    },
+    {
+      "src": "logo512.png",
+      "type": "image/png",
+      "sizes": "512x512"
+    }
+  ],
+  "start_url": ".",
+  "display": "standalone",
+  "theme_color": "#000000",
+  "background_color": "#ffffff"
+}

archive/backend/static/robots.txt

@@ -0,0 +1,3 @@
+# https://www.robotstxt.org/robotstxt.html
+User-agent: *
+Disallow:

archive/backend/static/static/js/main.5f85d736.js.LICENSE.txt

@@ -0,0 +1,49 @@
+/**
+ * @license React
+ * react-dom-client.production.js
+ *
+ * Copyright (c) Meta Platforms, Inc. and affiliates.
+ *
+ * This source code is licensed under the MIT license found in the
+ * LICENSE file in the root directory of this source tree.
+ */
+
+/**
+ * @license React
+ * react-dom.production.js
+ *
+ * Copyright (c) Meta Platforms, Inc. and affiliates.
+ *
+ * This source code is licensed under the MIT license found in the
+ * LICENSE file in the root directory of this source tree.
+ */
+
+/**
+ * @license React
+ * react-jsx-runtime.production.js
+ *
+ * Copyright (c) Meta Platforms, Inc. and affiliates.
+ *
+ * This source code is licensed under the MIT license found in the
+ * LICENSE file in the root directory of this source tree.
+ */
+
+/**
+ * @license React
+ * react.production.js
+ *
+ * Copyright (c) Meta Platforms, Inc. and affiliates.
+ *
+ * This source code is licensed under the MIT license found in the
+ * LICENSE file in the root directory of this source tree.
+ */
+
+/**
+ * @license React
+ * scheduler.production.js
+ *
+ * Copyright (c) Meta Platforms, Inc. and affiliates.
+ *
+ * This source code is licensed under the MIT license found in the
+ * LICENSE file in the root directory of this source tree.
+ */

archive/build.bat

@@ -0,0 +1,47 @@
+@echo off
+cd /d "%~dp0"
+chcp 65001 >nul
+echo ================================================
+echo AI写标书助手 - 构建exe
+echo ================================================
+echo.
+echo 检查Python环境...
+python --version
+if %errorlevel% neq 0 (
+    echo Python未安装或不在PATH中
+    pause
+    exit /b 1
+)
+echo.
+echo 检查Node.js环境...
+node --version
+if %errorlevel% neq 0 (
+    echo Node.js未安装或不在PATH中
+    pause
+    exit /b 1
+)
+echo.
+echo 开始构建...
+echo 构建前将自动清理以下目录和文件:
+echo   - dist/
+echo   - build/
+echo   - frontend/build/
+echo   - backend/static/
+echo   - __pycache__/
+echo   - *.spec
+echo.
+python -X utf8 build.py
+if errorlevel 1 (
+    echo.
+    echo ================================================
+    echo 构建失败！请检查上方的错误信息
+    echo ================================================
+) else (
+    echo.
+    echo ================================================
+    echo 构建成功！
+    echo exe文件位于: dist\yibiao-simple.exe
+    echo ================================================
+)
+echo.
+pause

archive/build.py

@@ -0,0 +1,217 @@
+"""构建脚本 - 用于打包exe"""
+
+import os
+import sys
+import subprocess
+import shutil
+from pathlib import Path
+import glob
+
+
+def run_command(cmd, cwd=None):
+    """运行命令"""
+    print(f"执行命令: {cmd}")
+    result = subprocess.run(cmd, shell=True, cwd=cwd, capture_output=True, text=True)
+    if result.returncode != 0:
+        print(f"命令执行失败: {result.stderr}")
+        return False
+    print(result.stdout)
+    return True
+
+
+def clean_build_files():
+    """清理构建相关的文件和文件夹"""
+    print("=" * 50)
+    print("清理构建文件...")
+    print("=" * 50)
+
+    # 要清理的文件夹列表
+    folders_to_clean = [
+        "dist",  # PyInstaller输出目录
+        "build",  # PyInstaller构建缓存
+        "frontend/build",  # React构建输出
+        "backend/static",  # 后端静态文件（前端构建产物）
+    ]
+
+    # 要清理的文件模式
+    files_to_clean = [
+        "*.spec",  # PyInstaller spec文件
+        "requirements_build.txt",  # 临时requirements文件
+    ]
+
+    # 清理文件夹
+    for folder in folders_to_clean:
+        folder_path = Path(folder)
+        if folder_path.exists():
+            print(f"删除文件夹: {folder}")
+            try:
+                shutil.rmtree(folder_path)
+                print(f"[OK] 已删除 {folder}")
+            except Exception as e:
+                print(f"[FAIL] 删除 {folder} 失败: {e}")
+        else:
+            print(f"- 文件夹不存在: {folder}")
+
+    # 清理文件
+    for file_pattern in files_to_clean:
+        for file_path in glob.glob(file_pattern):
+            try:
+                os.remove(file_path)
+                print(f"[OK] 已删除文件: {file_path}")
+            except Exception as e:
+                print(f"[FAIL] 删除文件 {file_path} 失败: {e}")
+
+    # 清理Python缓存文件
+    print("清理Python缓存文件...")
+    for root, dirs, files in os.walk("."):
+        # 删除__pycache__文件夹
+        if "__pycache__" in dirs:
+            pycache_path = Path(root) / "__pycache__"
+            try:
+                shutil.rmtree(pycache_path)
+                print(f"[OK] 已删除: {pycache_path}")
+            except Exception as e:
+                print(f"[FAIL] 删除 {pycache_path} 失败: {e}")
+            dirs.remove("__pycache__")  # 避免继续遍历已删除的目录
+
+        # 删除.pyc文件
+        for file in files:
+            if file.endswith(".pyc"):
+                pyc_path = Path(root) / file
+                try:
+                    pyc_path.unlink()
+                    print(f"[OK] 已删除: {pyc_path}")
+                except Exception as e:
+                    print(f"[FAIL] 删除 {pyc_path} 失败: {e}")
+
+    # 清理node_modules中的构建缓存（如果存在）
+    node_modules_cache = Path("frontend/node_modules/.cache")
+    if node_modules_cache.exists():
+        try:
+            shutil.rmtree(node_modules_cache)
+            print(f"[OK] 已删除Node.js缓存: {node_modules_cache}")
+        except Exception as e:
+            print(f"[FAIL] 删除Node.js缓存失败: {e}")
+
+    print("文件清理完成！")
+    return True
+
+
+def build_frontend():
+    """构建前端"""
+    print("=" * 50)
+    print("构建前端...")
+    print("=" * 50)
+
+    frontend_dir = Path("frontend")
+    if not frontend_dir.exists():
+        print("前端目录不存在")
+        return False
+
+    # 安装依赖
+    if not run_command("npm install", cwd=frontend_dir):
+        print("安装前端依赖失败")
+        return False
+
+    # 构建前端
+    if not run_command("npm run build", cwd=frontend_dir):
+        print("构建前端失败")
+        return False
+
+    # 复制构建文件到后端静态目录
+    build_dir = frontend_dir / "build"
+    static_dir = Path("backend") / "static"
+
+    if static_dir.exists():
+        shutil.rmtree(static_dir)
+
+    shutil.copytree(build_dir, static_dir)
+    print("前端构建文件已复制到后端静态目录")
+
+    return True
+
+
+def build_exe():
+    """构建exe文件"""
+    print("=" * 50)
+    print("构建exe文件...")
+    print("=" * 50)
+
+    # 安装所需依赖
+    print("安装构建依赖...")
+    if not run_command(f"{sys.executable} -m pip install pyinstaller"):
+        print("安装PyInstaller失败")
+        return False
+
+    # 安装应用依赖
+    if not run_command(f"{sys.executable} -m pip install -r backend/requirements.txt"):
+        print("安装应用依赖失败")
+        return False
+
+    # 构建exe - 使用更详细的参数，增加进程管理相关导入
+    pyinstaller_cmd = (
+        'pyinstaller --onefile --name="yibiao-simple" '
+        '--add-data="backend;backend" '
+        "--hidden-import=uvicorn --hidden-import=uvicorn.logging --hidden-import=uvicorn.loops "
+        "--hidden-import=uvicorn.loops.auto --hidden-import=uvicorn.protocols "
+        "--hidden-import=uvicorn.protocols.http --hidden-import=uvicorn.protocols.http.auto "
+        "--hidden-import=uvicorn.protocols.websockets --hidden-import=uvicorn.protocols.websockets.auto "
+        "--hidden-import=uvicorn.lifespan --hidden-import=uvicorn.lifespan.on --hidden-import=uvicorn.server "
+        "--hidden-import=fastapi --hidden-import=fastapi.staticfiles --hidden-import=fastapi.responses "
+        "--hidden-import=fastapi.middleware --hidden-import=fastapi.middleware.cors --hidden-import=fastapi.routing "
+        "--hidden-import=fastapi.exceptions --hidden-import=starlette --hidden-import=starlette.middleware "
+        "--hidden-import=starlette.middleware.cors --hidden-import=starlette.applications "
+        "--hidden-import=starlette.routing --hidden-import=starlette.responses --hidden-import=starlette.staticfiles "
+        "--hidden-import=starlette.types --hidden-import=openai --hidden-import=docx --hidden-import=docx.oxml "
+        "--hidden-import=docx.oxml.ns --hidden-import=PyPDF2 --hidden-import=PyPDF2.generic "
+        "--hidden-import=pdfplumber --hidden-import=pdfplumber.page --hidden-import=pdfplumber.table "
+        "--hidden-import=pdfplumber.utils --hidden-import=fitz --hidden-import=pymupdf "
+        "--hidden-import=docx2python --hidden-import=docx2python.iterators --hidden-import=paragraphs "
+        "--hidden-import=pydantic --hidden-import=pydantic_settings --hidden-import=multipart "
+        "--hidden-import=aiofiles --hidden-import=dotenv --hidden-import=json --hidden-import=pathlib "
+        "--hidden-import=asyncio --hidden-import=signal --hidden-import=atexit "
+        "--console app_launcher.py"
+    )
+
+    if not run_command(pyinstaller_cmd):
+        print("构建exe失败")
+        return False
+
+    print("exe文件构建完成，位于 dist/ 目录中")
+    return True
+
+
+def main():
+    """主函数"""
+    print("AI写标书助手 - 构建脚本")
+    print("=" * 50)
+
+    # 确保在项目根目录
+    if not Path("backend").exists() or not Path("frontend").exists():
+        print("请在项目根目录运行此脚本")
+        return False
+
+    # 清理构建文件
+    if not clean_build_files():
+        return False
+
+    # 构建前端
+    if not build_frontend():
+        return False
+
+    # 构建exe
+    if not build_exe():
+        return False
+
+    print("\n" + "=" * 50)
+    print("构建完成！")
+    print("exe文件位于: dist/yibiao-simple.exe")
+    print("=" * 50)
+
+    return True
+
+
+if __name__ == "__main__":
+    success = main()
+    if not success:
+        sys.exit(1)

archive/frontend/.env.example

@@ -0,0 +1,2 @@
+REACT_APP_API_URL=http://localhost:8000
+PORT=3002

archive/frontend/.gitignore

@@ -0,0 +1,23 @@
+# See https://help.github.com/articles/ignoring-files/ for more about ignoring files.
+
+# dependencies
+/node_modules
+/.pnp
+.pnp.js
+
+# testing
+/coverage
+
+# production
+/build
+
+# misc
+.DS_Store
+.env.local
+.env.development.local
+.env.test.local
+.env.production.local
+
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*

archive/frontend/README.md

@@ -0,0 +1,46 @@
+# Getting Started with Create React App
+
+This project was bootstrapped with [Create React App](https://github.com/facebook/create-react-app).
+
+## Available Scripts
+
+In the project directory, you can run:
+
+### `npm start`
+
+Runs the app in the development mode.\
+Open [http://localhost:3000](http://localhost:3000) to view it in the browser.
+
+The page will reload if you make edits.\
+You will also see any lint errors in the console.
+
+### `npm test`
+
+Launches the test runner in the interactive watch mode.\
+See the section about [running tests](https://facebook.github.io/create-react-app/docs/running-tests) for more information.
+
+### `npm run build`
+
+Builds the app for production to the `build` folder.\
+It correctly bundles React in production mode and optimizes the build for the best performance.
+
+The build is minified and the filenames include the hashes.\
+Your app is ready to be deployed!
+
+See the section about [deployment](https://facebook.github.io/create-react-app/docs/deployment) for more information.
+
+### `npm run eject`
+
+**Note: this is a one-way operation. Once you `eject`, you can’t go back!**
+
+If you aren’t satisfied with the build tool and configuration choices, you can `eject` at any time. This command will remove the single build dependency from your project.
+
+Instead, it will copy all the configuration files and the transitive dependencies (webpack, Babel, ESLint, etc) right into your project so you have full control over them. All of the commands except `eject` will still work, but they will point to the copied scripts so you can tweak them. At this point you’re on your own.
+
+You don’t have to ever use `eject`. The curated feature set is suitable for small and middle deployments, and you shouldn’t feel obligated to use this feature. However we understand that this tool wouldn’t be useful if you couldn’t customize it when you are ready for it.
+
+## Learn More
+
+You can learn more in the [Create React App documentation](https://facebook.github.io/create-react-app/docs/getting-started).
+
+To learn React, check out the [React documentation](https://reactjs.org/).

archive/frontend/package-lock.json

@@ -0,0 +1,19808 @@
+{
+  "name": "frontend",
+  "version": "0.1.0",
+  "lockfileVersion": 3,
+  "requires": true,
+  "packages": {
+    "": {
+      "name": "frontend",
+      "version": "0.1.0",
+      "dependencies": {
+        "@headlessui/react": "^2.2.7",
+        "@heroicons/react": "^2.2.0",
+        "@tailwindcss/typography": "^0.5.16",
+        "@testing-library/dom": "^10.4.1",
+        "@testing-library/jest-dom": "^6.8.0",
+        "@testing-library/react": "^16.3.0",
+        "@testing-library/user-event": "^13.5.0",
+        "@types/jest": "^27.5.2",
+        "@types/node": "^16.18.126",
+        "@types/react": "^19.1.11",
+        "@types/react-dom": "^19.1.7",
+        "axios": "^1.11.0",
+        "docx": "^9.5.1",
+        "file-saver": "^2.0.5",
+        "html-to-docx": "^1.8.0",
+        "prism-react-renderer": "^2.4.1",
+        "react": "^19.1.1",
+        "react-dom": "^19.1.1",
+        "react-markdown": "^10.1.0",
+        "react-scripts": "5.0.1",
+        "rehype-highlight": "^7.0.2",
+        "typescript": "^4.9.5",
+        "web-vitals": "^2.1.4"
+      },
+      "devDependencies": {
+        "@tailwindcss/forms": "^0.5.9",
+        "@types/file-saver": "^2.0.7",
+        "autoprefixer": "^10.4.21",
+        "postcss": "^8.5.6",
+        "tailwindcss": "^3.4.17"
+      }
+    },
+    "node_modules/@adobe/css-tools": {
+      "version": "4.4.4",
+      "resolved": "https://registry.npmjs.org/@adobe/css-tools/-/css-tools-4.4.4.tgz",
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+    "node_modules/@alloc/quick-lru": {
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archive/frontend/package.json

@@ -0,0 +1,61 @@
+{
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+  "private": true,
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+    "@testing-library/jest-dom": "^6.8.0",
+    "@testing-library/react": "^16.3.0",
+    "@testing-library/user-event": "^13.5.0",
+    "@types/jest": "^27.5.2",
+    "@types/node": "^16.18.126",
+    "@types/react": "^19.1.11",
+    "@types/react-dom": "^19.1.7",
+    "axios": "^1.11.0",
+    "docx": "^9.5.1",
+    "file-saver": "^2.0.5",
+    "html-to-docx": "^1.8.0",
+    "prism-react-renderer": "^2.4.1",
+    "react": "^19.1.1",
+    "react-dom": "^19.1.1",
+    "react-markdown": "^10.1.0",
+    "react-scripts": "5.0.1",
+    "rehype-highlight": "^7.0.2",
+    "typescript": "^4.9.5",
+    "web-vitals": "^2.1.4"
+  },
+  "scripts": {
+    "start": "react-scripts start",
+    "build": "react-scripts build",
+    "test": "react-scripts test",
+    "eject": "react-scripts eject"
+  },
+  "eslintConfig": {
+    "extends": [
+      "react-app",
+      "react-app/jest"
+    ]
+  },
+  "browserslist": {
+    "production": [
+      ">0.2%",
+      "not dead",
+      "not op_mini all"
+    ],
+    "development": [
+      "last 1 chrome version",
+      "last 1 firefox version",
+      "last 1 safari version"
+    ]
+  },
+  "devDependencies": {
+    "@tailwindcss/forms": "^0.5.9",
+    "@types/file-saver": "^2.0.7",
+    "autoprefixer": "^10.4.21",
+    "postcss": "^8.5.6",
+    "tailwindcss": "^3.4.17"
+  }
+}

archive/frontend/postcss.config.js

@@ -0,0 +1,6 @@
+module.exports = {
+  plugins: {
+    tailwindcss: {},
+    autoprefixer: {},
+  },
+}