feat: add error handling for disabled sandbox runtime in get_booter function

feat: add video message support and enhance message type descriptions in SendMessageToUserTool
fix(docs): add official developer group ID to multiple language READMEs and enhance regex description in config metadata
2026-03-12 00:28:45 +08:00 · 2026-03-12 00:26:56 +08:00 · 2026-03-11 21:26:11 +08:00 · 2026-03-11 17:42:42 +08:00 · 2026-03-11 16:41:08 +08:00 · 2026-03-11 15:14:16 +08:00
968 changed files with 141707 additions and 19472 deletions
@@ -17,7 +17,6 @@ ENV/
 .conda/
 dashboard/
 data/
-changelogs/
 tests/
 .ruff_cache/
 .astrbot
@@ -1,46 +1,44 @@
-name: '🐛 报告 Bug'
+name: '🐛 Report Bug / 报告 Bug'
 title: '[Bug]'
-description: 提交报告帮助我们改进。
+description: Submit bug report to help us improve. / 提交报告帮助我们改进。
 labels: [ 'bug' ]
 body:
  - type: markdown
    attributes:
      value: |
-        感谢您抽出时间报告问题！请准确解释您的问题。如果可能，请提供一个可复现的片段（这有助于更快地解决问题）。请注意，不详细 / 没有日志的 issue 会被直接关闭，谢谢理解。
+        Thank you for taking the time to report this issue! Please describe your problem accurately. If possible, please provide a reproducible snippet (this will help resolve the issue more quickly). Please note that issues that are not detailed or have no logs will be closed immediately. Thank you for your understanding. / 感谢您抽出时间报告问题！请准确解释您的问题。如果可能，请提供一个可复现的片段（这有助于更快地解决问题）。请注意，不详细 / 没有日志的 issue 会被直接关闭，谢谢理解。
  - type: textarea
    attributes:
-      label: 发生了什么
-      description: 描述你遇到的异常
+      label: What happened / 发生了什么
+      description: Description
      placeholder: >
-        一个清晰且具体的描述这个异常是什么。请注意，不详细 / 没有日志的 issue 会被直接关闭，谢谢理解。
+        Please provide a clear and specific description of what this exception is. Please note that issues that are not detailed or have no logs will be closed immediately. Thank you for your understanding. / 一个清晰且具体的描述这个异常是什么。请注意，不详细 / 没有日志的 issue 会被直接关闭，谢谢理解。
    validations:
      required: true

  - type: textarea
    attributes:
-      label: 如何复现？
+      label: Reproduce / 如何复现？
      description: >
-        复现该问题的步骤
+        The steps to reproduce the issue. / 复现该问题的步骤
      placeholder: >
-        如: 1. 打开 '...'
+        Example: 1. Open '...'
    validations:
      required: true

  - type: textarea
    attributes:
-      label: AstrBot 版本、部署方式（如 Windows Docker Desktop 部署）、使用的提供商、使用的消息平台适配器
-      description: >
-        请提供您的 AstrBot 版本和部署方式。
+      label: AstrBot version, deployment method (e.g., Windows Docker Desktop deployment), provider used, and messaging platform used. / AstrBot 版本、部署方式（如 Windows Docker Desktop 部署）、使用的提供商、使用的消息平台适配器
      placeholder: >
-        如: 3.1.8 Docker, 3.1.7 Windows启动器
+        Example: 4.5.7 Docker, 3.1.7 Windows Launcher
    validations:
      required: true

  - type: dropdown
    attributes:
-      label: 操作系统
+      label: OS
      description: |
-        你在哪个操作系统上遇到了这个问题？
+        On which operating system did you encounter this problem? / 你在哪个操作系统上遇到了这个问题？
      multiple: false
      options:
        - 'Windows'
@@ -53,30 +51,30 @@ body:

  - type: textarea
    attributes:
-      label: 报错日志
+      label: Logs / 报错日志
      description: >
-        如报错日志、截图等。请提供完整的 Debug 级别的日志，不要介意它很长！请注意，不详细 / 没有日志的 issue 会被直接关闭，谢谢理解。
+        Please provide complete Debug-level logs, such as error logs and screenshots. Don't worry if they're long! Please note that issues with insufficient details or no logs will be closed immediately. Thank you for your understanding. / 如报错日志、截图等。请提供完整的 Debug 级别的日志，不要介意它很长！请注意，不详细 / 没有日志的 issue 会被直接关闭，谢谢理解。
      placeholder: >
-        请提供完整的报错日志或截图。
+        Please provide a complete error log or screenshot. / 请提供完整的报错日志或截图。
    validations:
      required: true

  - type: checkboxes
    attributes:
-      label: 你愿意提交 PR 吗？
+      label: Are you willing to submit a PR? / 你愿意提交 PR 吗？
      description: >
-        这不是必需的，但我们很乐意在贡献过程中为您提供指导特别是如果你已经很好地理解了如何实现修复。
+        This is not required, but we would be happy to provide guidance during the contribution process, especially if you already have a good understanding of how to implement the fix. / 这不是必需的，但我们很乐意在贡献过程中为您提供指导特别是如果你已经很好地理解了如何实现修复。
      options:
-        - label: 是的，我愿意提交 PR!
+        - label: Yes!

  - type: checkboxes
    attributes:
      label: Code of Conduct
      options:
        - label: >
-            我已阅读并同意遵守该项目的 [行为准则](https://docs.github.com/zh/site-policy/github-terms/github-community-code-of-conduct)。
+            I have read and agree to abide by the project's [Code of Conduct](https://docs.github.com/zh/site-policy/github-terms/github-community-code-of-conduct)。
          required: true

  - type: markdown
    attributes:
-      value: "感谢您填写我们的表单！"
+      value: "Thank you for filling out our form! / 感谢您填写我们的表单！"
@@ -1,42 +1,40 @@

-name: '🎉 功能建议'
+name: '🎉 Feature Request / 功能建议'
 title: "[Feature]"
-description: 提交建议帮助我们改进。
+description: Submit a suggestion to help us improve. / 提交建议帮助我们改进。
 labels: [ "enhancement" ]
 body:
  - type: markdown
    attributes:
      value: |
-        感谢您抽出时间提出新功能建议，请准确解释您的想法。
+        Thank you for taking the time to suggest a new feature! Please explain your idea clearly and accurately. / 感谢您抽出时间提出新功能建议，请准确解释您的想法。

  - type: textarea
    attributes:
-      label: 描述
-      description: 简短描述您的功能建议。
+      label: Description / 描述
+      description: Please describe the feature you want to be added in detail. / 请详细描述您希望添加的功能。

  - type: textarea
    attributes:
-      label: 使用场景
-      description: 你想要发生什么？
-      placeholder: >
-        一个清晰且具体的描述这个功能的使用场景。
+      label: Use Case / 使用场景
+      description: Please describe the use case for this feature. / 请描述这个功能的使用场景。

  - type: checkboxes
    attributes:
-      label: 你愿意提交PR吗?
+      label: Willing to Submit PR? / 是否愿意提交PR？
      description: >
-        这不是必须的，但我们欢迎您的贡献。
+        This is not required, but if you are willing to submit a PR to implement this feature, it would be greatly appreciated! / 这不是必需的，但如果您愿意提交 PR 来实现这个功能，我们将不胜感激！
      options:
-        - label: 是的, 我愿意提交PR!
+        - label: Yes, I am willing to submit a PR. / 是的，我愿意提交 PR。

  - type: checkboxes
    attributes:
      label: Code of Conduct
      options:
        - label: >
-            我已阅读并同意遵守该项目的 [行为准则](https://docs.github.com/zh/site-policy/github-terms/github-community-code-of-conduct)。
+            I have read and agree to abide by the project's [Code of Conduct](https://docs.github.com/zh/site-policy/github-terms/github-community-code-of-conduct). /
          required: true

  - type: markdown
    attributes:
-      value: "感谢您填写我们的表单！"
+      value: "Thank you for filling out our form!"
@@ -1,44 +1,25 @@
-<!-- 如果有的话，请指定此 PR 旨在解决的 ISSUE 编号。 -->
-<!-- If applicable, please specify the ISSUE number this PR aims to resolve. -->
-
-fixes #XYZ
-
---
-
-### Motivation / 动机
-
-<!--请描述此项更改的动机：它解决了什么问题？（例如：修复了 XX 错误，添加了 YY 功能）-->
-<!--Please describe the motivation for this change: What problem does it solve? (e.g., Fixes XX bug, adds YY feature)-->
+<!--Please describe the motivation for this change: What problem does it solve? (e.g., Fixes XX issue, adds YY feature)-->
+<!--请描述此项更改的动机：它解决了什么问题？（例如：修复了 XX issue，添加了 YY 功能）-->

 ### Modifications / 改动点

 <!--请总结你的改动：哪些核心文件被修改了？实现了什么功能？-->
 <!--Please summarize your changes: What core files were modified? What functionality was implemented?-->

-### Verification Steps / 验证步骤
-
-<!--请为审查者 (Reviewer) 提供清晰、可复现的验证步骤（例如：1. 导航到... 2. 点击...）。-->
-<!--Please provide clear and reproducible verification steps for the Reviewer (e.g., 1. Navigate to... 2. Click...).-->
+- [x] This is NOT a breaking change. / 这不是一个破坏性变更。
+<!-- If your changes is a breaking change, please uncheck the checkbox above -->

 ### Screenshots or Test Results / 运行截图或测试结果

-<!--请粘贴截图、GIF 或测试日志，作为执行“验证步骤”的证据，证明此改动有效。-->
 <!--Please paste screenshots, GIFs, or test logs here as evidence of executing the "Verification Steps" to prove this change is effective.-->
-
-### Compatibility & Breaking Changes / 兼容性与破坏性变更
-
-<!--请说明此变更的兼容性：哪些是破坏性变更？哪些地方做了向后兼容处理？是否提供了数据迁移方法？-->
-<!--Please explain the compatibility of this change: What are the breaking changes? What backward-compatible measures were taken? Are data migration paths provided?-->
-
- [ ] 这是一个破坏性变更 (Breaking Change)。/ This is a breaking change.
- [ ] 这不是一个破坏性变更。/ This is NOT a breaking change.
+<!--请粘贴截图、GIF 或测试日志，作为执行“验证步骤”的证据，证明此改动有效。-->

 ---

 ### Checklist / 检查清单

-<!--如果分支被合并，您的代码将服务于数万名用户！在提交前，请核查一下几点内容。-->
 <!--If merged, your code will serve tens of thousands of users! Please double-check the following items before submitting.-->
+<!--如果分支被合并，您的代码将服务于数万名用户！在提交前，请核查一下几点内容。-->

 - [ ] 😊 如果 PR 中有新加入的功能，已经通过 Issue / 邮件等方式和作者讨论过。/ If there are new features added in the PR, I have discussed it with the authors through issues/emails, etc.
 - [ ] 👀 我的更改经过了良好的测试，**并已在上方提供了“验证步骤”和“运行截图”**。/ My changes have been well-tested, **and "Verification Steps" and "Screenshots" have been provided above**.
@@ -15,7 +15,6 @@ Always reference these instructions first and fallback to search or bash command
 ### Running the Application
 - Run main application: `uv run main.py` -- starts in ~3 seconds
 - Application creates WebUI on http://localhost:6185 (default credentials: `astrbot`/`astrbot`)
- Application loads plugins automatically from `packages/` and `data/plugins/` directories

 ### Dashboard Build (Vue.js/Node.js)
 - **Prerequisites**: Node.js 20+ and npm 10+ required
@@ -35,7 +34,7 @@ Always reference these instructions first and fallback to search or bash command
 - **ALWAYS** run `uv run ruff check .` and `uv run ruff format .` before committing changes

 ### Plugin Development
- Plugins load from `packages/` (built-in) and `data/plugins/` (user-installed)
+- Plugins load from `astrbot/builtin_stars/` (built-in) and `data/plugins/` (user-installed)
 - Plugin system supports function tools and message handlers
 - Key plugins: python_interpreter, web_searcher, astrbot, reminder, session_controller

@@ -1,92 +0,0 @@
-on:
-  push:
-    tags:
-      - 'v*'
-  workflow_dispatch:
-
-name: Auto Release
-
-jobs:
-  build-and-publish-to-github-release:
-    runs-on: ubuntu-latest
-    permissions:
-      contents: write
-    steps:
-      - name: Checkout repository
-        uses: actions/checkout@v5
-
-      - name: Dashboard Build
-        run: |
-          cd dashboard
-          npm install
-          npm run build
-          echo "COMMIT_SHA=$(git rev-parse HEAD)" >> $GITHUB_ENV
-          echo ${{ github.ref_name }} > dist/assets/version
-          zip -r dist.zip dist
-      
-      - name: Upload to Cloudflare R2
-        env:
-          R2_ACCOUNT_ID: ${{ secrets.R2_ACCOUNT_ID }}
-          R2_ACCESS_KEY_ID: ${{ secrets.R2_ACCESS_KEY_ID }}
-          R2_SECRET_ACCESS_KEY: ${{ secrets.R2_SECRET_ACCESS_KEY }}
-          R2_BUCKET_NAME: "astrbot"
-          R2_OBJECT_NAME: "astrbot-webui-latest.zip"
-          VERSION_TAG: ${{ github.ref_name }}
-        run: |
-          echo "Installing rclone..."
-          curl https://rclone.org/install.sh | sudo bash
-
-          echo "Configuring rclone remote..."
-          mkdir -p ~/.config/rclone
-          cat <<EOF > ~/.config/rclone/rclone.conf
-          [r2]
-          type = s3
-          provider = Cloudflare
-          access_key_id = $R2_ACCESS_KEY_ID
-          secret_access_key = $R2_SECRET_ACCESS_KEY
-          endpoint = https://${R2_ACCOUNT_ID}.r2.cloudflarestorage.com
-          EOF
-
-          echo "Uploading dist.zip to R2 bucket: $R2_BUCKET_NAME/$R2_OBJECT_NAME"
-          mv dashboard/dist.zip dashboard/$R2_OBJECT_NAME
-          rclone copy dashboard/$R2_OBJECT_NAME r2:$R2_BUCKET_NAME --progress
-          mv dashboard/$R2_OBJECT_NAME dashboard/astrbot-webui-${VERSION_TAG}.zip
-          rclone copy dashboard/astrbot-webui-${VERSION_TAG}.zip r2:$R2_BUCKET_NAME --progress
-          mv dashboard/astrbot-webui-${VERSION_TAG}.zip dashboard/dist.zip
-
-      - name: Fetch Changelog
-        run: |
-          echo "changelog=changelogs/${{github.ref_name}}.md" >> "$GITHUB_ENV"
-
-      - name: Create GitHub Release
-        uses: ncipollo/release-action@v1
-        with:
-          bodyFile: ${{ env.changelog }}
-          artifacts: "dashboard/dist.zip"
-      
-  build-and-publish-to-pypi:
-    # 构建并发布到 PyPI
-    runs-on: ubuntu-latest
-    needs: build-and-publish-to-github-release
-    steps:
-      - name: Checkout repository
-        uses: actions/checkout@v5
-
-      - name: Set up Python
-        uses: actions/setup-python@v6
-        with:
-          python-version: '3.10'
-
-      - name: Install uv
-        run: |
-          python -m pip install uv
-
-      - name: Build package
-        run: |
-          uv build
-
-      - name: Publish to PyPI
-        env:
-          UV_PUBLISH_TOKEN: ${{ secrets.PYPI_TOKEN }}
-        run: |
-          uv publish
@@ -0,0 +1,43 @@
+name: release
+
+on:
+  push:
+    tags:
+      - 'v*'
+  workflow_dispatch:
+
+jobs:
+  build:
+    runs-on: ubuntu-latest # 运行环境
+    steps:
+      - name: checkout
+        uses: actions/checkout@master
+      - name: nodejs installation
+        uses: actions/setup-node@v6
+        with:
+          node-version: "18"
+      - name: npm install
+        run: npm add -D vitepress
+        working-directory: './docs' # working-directory 指定 shell 命令运行目录
+      - name: npm run build
+        run: npm run docs:build
+        working-directory: './docs'
+      - name: scp
+        uses: appleboy/scp-action@master
+        with:
+          host: ${{ secrets.HOST_NEKO }}
+          username: ${{ secrets.USERNAME }}
+          password: ${{ secrets.PASSWORDNEKO }}
+          source: 'docs/.vitepress/dist/*'
+          target: '/tmp/'
+      - name: script
+        uses: appleboy/ssh-action@master
+        with:
+          host: ${{ secrets.HOST_NEKO }}
+          username: ${{ secrets.USERNAME }}
+          password: ${{ secrets.PASSWORDNEKO }}
+          script: |
+            mkdir -p /root/docker_data/caddy/caddy_data/static_site/abv4/
+            rm -rf /root/docker_data/caddy/caddy_data/static_site/abv4/*
+            mv /tmp/docs/.vitepress/dist/* /root/docker_data/caddy/caddy_data/static_site/abv4/
+            rm -rf /tmp/docs/
@@ -12,12 +12,12 @@ jobs:
    
    steps:
    - name: Checkout code
-      uses: actions/checkout@v5
+      uses: actions/checkout@v6
      
    - name: Set up Python
      uses: actions/setup-python@v6
      with:
-        python-version: '3.10'
+        python-version: '3.12'
        
    - name: Install UV
      run: pip install uv
@@ -56,7 +56,7 @@ jobs:
        # your codebase is analyzed, see https://docs.github.com/en/code-security/code-scanning/creating-an-advanced-setup-for-code-scanning/codeql-code-scanning-for-compiled-languages
    steps:
    - name: Checkout repository
-      uses: actions/checkout@v5
+      uses: actions/checkout@v6

    # Initializes the CodeQL tools for scanning.
    - name: Initialize CodeQL
@@ -17,7 +17,7 @@ jobs:
    runs-on: ubuntu-latest
    steps:
      - name: Checkout
-        uses: actions/checkout@v5
+        uses: actions/checkout@v6
        with:
          fetch-depth: 0

@@ -37,7 +37,7 @@ jobs:
          mkdir -p data/temp
          export TESTING=true
          export ZHIPU_API_KEY=${{ secrets.OPENAI_API_KEY }}
-          pytest --cov=. -v -o log_cli=true -o log_level=DEBUG
+          pytest --cov=astrbot -v -o log_cli=true -o log_level=DEBUG

      - name: Upload results to Codecov
        uses: codecov/codecov-action@v5
@@ -11,12 +11,12 @@ jobs:
    runs-on: ubuntu-latest
    steps:
      - name: Checkout repository
-        uses: actions/checkout@v5
+        uses: actions/checkout@v6

      - name: Setup Node.js
        uses: actions/setup-node@v6
        with:
-          node-version: 'latest'
+          node-version: '24.13.0'

      - name: npm install, build
        run: |
@@ -36,7 +36,7 @@ jobs:
          zip -r dist.zip dist

      - name: Archive production artifacts
-        uses: actions/upload-artifact@v5
+        uses: actions/upload-artifact@v7
        with:
          name: dist-without-markdown
          path: |
@@ -52,4 +52,4 @@ jobs:
          repo: astrbot-release-harbour
          body: "Automated release from commit ${{ github.sha }}"
          token: ${{ secrets.ASTRBOT_HARBOUR_TOKEN }}
-          artifacts: "dashboard/dist.zip"
+          artifacts: "dashboard/dist.zip"
@@ -3,18 +3,125 @@ name: Docker Image CI/CD
 on:
  push:
    tags:
-      - 'v*'
+      - "v*"
+  schedule:
+    # Run at 00:00 UTC every day
+    - cron: "0 0 * * *"
  workflow_dispatch:

 jobs:
-  publish-docker:
+  build-nightly-image:
+    if: github.event_name == 'schedule'
    runs-on: ubuntu-latest
+    env:
+      DOCKER_HUB_USERNAME: ${{ secrets.DOCKER_HUB_USERNAME }}
+      GHCR_OWNER: astrbotdevs
+      HAS_GHCR_TOKEN: ${{ secrets.GHCR_GITHUB_TOKEN != '' }}

    steps:
-      - name: Pull The Codes
-        uses: actions/checkout@v5
+      - name: Checkout
+        uses: actions/checkout@v6
        with:
-          fetch-depth: 0  # Must be 0 so we can fetch tags
+          fetch-depth: 1
+          fetch-tag: true
+
+      - name: Check for new commits today
+        if: github.event_name == 'schedule'
+        id: check-commits
+        run: |
+          # Get commits from the last 24 hours
+          commits=$(git log --since="24 hours ago" --oneline)
+          if [ -z "$commits" ]; then
+            echo "No commits in the last 24 hours, skipping build"
+            echo "has_commits=false" >> $GITHUB_OUTPUT
+          else
+            echo "Found commits in the last 24 hours:"
+            echo "$commits"
+            echo "has_commits=true" >> $GITHUB_OUTPUT
+          fi
+
+      - name: Exit if no commits
+        if: github.event_name == 'schedule' && steps.check-commits.outputs.has_commits == 'false'
+        run: exit 0
+
+      - name: Build Dashboard
+        run: |
+          cd dashboard
+          npm install
+          npm run build
+          mkdir -p dist/assets
+          echo $(git rev-parse HEAD) > dist/assets/version
+          cd ..
+          mkdir -p data
+          cp -r dashboard/dist data/
+
+      - name: Determine test image tags
+        id: test-meta
+        run: |
+          short_sha=$(echo "${GITHUB_SHA}" | cut -c1-12)
+          build_date=$(date +%Y%m%d)
+          echo "short_sha=$short_sha" >> $GITHUB_OUTPUT
+          echo "build_date=$build_date" >> $GITHUB_OUTPUT
+
+      - name: Set QEMU
+        uses: docker/setup-qemu-action@v4
+
+      - name: Set Docker Buildx
+        uses: docker/setup-buildx-action@v4
+
+      - name: Log in to DockerHub
+        uses: docker/login-action@v4
+        with:
+          username: ${{ secrets.DOCKER_HUB_USERNAME }}
+          password: ${{ secrets.DOCKER_HUB_PASSWORD }}
+
+      - name: Login to GitHub Container Registry
+        if: env.HAS_GHCR_TOKEN == 'true'
+        uses: docker/login-action@v4
+        with:
+          registry: ghcr.io
+          username: ${{ env.GHCR_OWNER }}
+          password: ${{ secrets.GHCR_GITHUB_TOKEN }}
+
+      - name: Build nightly image tags list
+        id: test-tags
+        run: |
+          TAGS="${{ env.DOCKER_HUB_USERNAME }}/astrbot:nightly-latest
+          ${{ env.DOCKER_HUB_USERNAME }}/astrbot:nightly-${{ steps.test-meta.outputs.build_date }}-${{ steps.test-meta.outputs.short_sha }}"
+          if [ "${{ env.HAS_GHCR_TOKEN }}" = "true" ]; then
+            TAGS="$TAGS
+          ghcr.io/${{ env.GHCR_OWNER }}/astrbot:nightly-latest
+          ghcr.io/${{ env.GHCR_OWNER }}/astrbot:nightly-${{ steps.test-meta.outputs.build_date }}-${{ steps.test-meta.outputs.short_sha }}"
+          fi
+          echo "tags<<EOF" >> $GITHUB_OUTPUT
+          echo "$TAGS" >> $GITHUB_OUTPUT
+          echo "EOF" >> $GITHUB_OUTPUT
+
+      - name: Build and Push Nightly Image
+        uses: docker/build-push-action@v7
+        with:
+          context: .
+          platforms: linux/amd64,linux/arm64
+          push: true
+          tags: ${{ steps.test-tags.outputs.tags }}
+
+      - name: Post build notifications
+        run: echo "Test Docker image has been built and pushed successfully"
+
+  build-release-image:
+    if: github.event_name == 'workflow_dispatch' || (github.event_name == 'push' && startsWith(github.ref, 'refs/tags/v'))
+    runs-on: ubuntu-latest
+    env:
+      DOCKER_HUB_USERNAME: ${{ secrets.DOCKER_HUB_USERNAME }}
+      GHCR_OWNER: astrbotdevs
+      HAS_GHCR_TOKEN: ${{ secrets.GHCR_GITHUB_TOKEN != '' }}
+
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v6
+        with:
+          fetch-depth: 1
+          fetch-tag: true

      - name: Get latest tag (only on manual trigger)
        id: get-latest-tag
@@ -27,21 +134,22 @@ jobs:
        if: github.event_name == 'workflow_dispatch'
        run: git checkout ${{ steps.get-latest-tag.outputs.latest_tag }}

-      - name: Check if version is pre-release
-        id: check-prerelease
+      - name: Compute release metadata
+        id: release-meta
        run: |
-          if [ "${{ github.event_name }}" == "workflow_dispatch" ]; then
+          if [ "${{ github.event_name }}" = "workflow_dispatch" ]; then
            version="${{ steps.get-latest-tag.outputs.latest_tag }}"
          else
-            version="${{ github.ref_name }}"
+            version="${GITHUB_REF#refs/tags/}"
          fi
          if [[ "$version" == *"beta"* ]] || [[ "$version" == *"alpha"* ]]; then
            echo "is_prerelease=true" >> $GITHUB_OUTPUT
-            echo "Version $version is a pre-release, will not push latest tag"
+            echo "Version $version marked as pre-release"
          else
            echo "is_prerelease=false" >> $GITHUB_OUTPUT
-            echo "Version $version is a stable release, will push latest tag"
+            echo "Version $version marked as stable"
          fi
+          echo "version=$version" >> $GITHUB_OUTPUT

      - name: Build Dashboard
        run: |
@@ -55,35 +163,36 @@ jobs:
          cp -r dashboard/dist data/

      - name: Set QEMU
-        uses: docker/setup-qemu-action@v3
+        uses: docker/setup-qemu-action@v4

      - name: Set Docker Buildx
-        uses: docker/setup-buildx-action@v3
+        uses: docker/setup-buildx-action@v4

      - name: Log in to DockerHub
-        uses: docker/login-action@v3
+        uses: docker/login-action@v4
        with:
          username: ${{ secrets.DOCKER_HUB_USERNAME }}
          password: ${{ secrets.DOCKER_HUB_PASSWORD }}

      - name: Login to GitHub Container Registry
-        uses: docker/login-action@v3
+        if: env.HAS_GHCR_TOKEN == 'true'
+        uses: docker/login-action@v4
        with:
          registry: ghcr.io
-          username: Soulter
+          username: ${{ env.GHCR_OWNER }}
          password: ${{ secrets.GHCR_GITHUB_TOKEN }}

-      - name: Build and Push Docker to DockerHub and Github GHCR
-        uses: docker/build-push-action@v6
+      - name: Build and Push Release Image
+        uses: docker/build-push-action@v7
        with:
          context: .
          platforms: linux/amd64,linux/arm64
          push: true
          tags: |
-            ${{ steps.check-prerelease.outputs.is_prerelease == 'false' && format('{0}/astrbot:latest', secrets.DOCKER_HUB_USERNAME) || '' }}
-            ${{ secrets.DOCKER_HUB_USERNAME }}/astrbot:${{ github.event_name == 'workflow_dispatch' && steps.get-latest-tag.outputs.latest_tag || github.ref_name }}
-            ${{ steps.check-prerelease.outputs.is_prerelease == 'false' && 'ghcr.io/soulter/astrbot:latest' || '' }}
-            ghcr.io/soulter/astrbot:${{ github.event_name == 'workflow_dispatch' && steps.get-latest-tag.outputs.latest_tag || github.ref_name }}
+            ${{ steps.release-meta.outputs.is_prerelease == 'false' && format('{0}/astrbot:latest', env.DOCKER_HUB_USERNAME) || '' }}
+            ${{ steps.release-meta.outputs.is_prerelease == 'false' && env.HAS_GHCR_TOKEN == 'true' && format('ghcr.io/{0}/astrbot:latest', env.GHCR_OWNER) || '' }}
+            ${{ format('{0}/astrbot:{1}', env.DOCKER_HUB_USERNAME, steps.release-meta.outputs.version) }}
+            ${{ env.HAS_GHCR_TOKEN == 'true' && format('ghcr.io/{0}/astrbot:{1}', env.GHCR_OWNER, steps.release-meta.outputs.version) || '' }}

      - name: Post build notifications
-        run: echo "Docker image has been built and pushed successfully"
+        run: echo "Release Docker image has been built and pushed successfully"
@@ -0,0 +1,245 @@
+name: Release
+
+on:
+  push:
+    tags:
+      - "v*"
+  workflow_dispatch:
+    inputs:
+      ref:
+        description: "Git ref to build (branch/tag/SHA)"
+        required: false
+        default: "master"
+      tag:
+        description: "Release tag to publish assets to (for example: v4.14.6)"
+        required: false
+
+permissions:
+  contents: write
+
+jobs:
+  build-dashboard:
+    name: Build Dashboard
+    runs-on: ubuntu-24.04
+    env:
+      R2_ACCOUNT_ID: ${{ secrets.R2_ACCOUNT_ID }}
+      R2_ACCESS_KEY_ID: ${{ secrets.R2_ACCESS_KEY_ID }}
+      R2_SECRET_ACCESS_KEY: ${{ secrets.R2_SECRET_ACCESS_KEY }}
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v6
+        with:
+          fetch-depth: 0
+          ref: ${{ inputs.ref || github.ref }}
+
+      - name: Resolve tag
+        id: tag
+        shell: bash
+        run: |
+          if [ "${{ github.event_name }}" = "push" ]; then
+            tag="${GITHUB_REF_NAME}"
+          elif [ -n "${{ inputs.tag }}" ]; then
+            tag="${{ inputs.tag }}"
+          else
+            tag="$(git describe --tags --abbrev=0)"
+          fi
+          if [ -z "$tag" ]; then
+            echo "Failed to resolve tag." >&2
+            exit 1
+          fi
+          echo "tag=$tag" >> "$GITHUB_OUTPUT"
+
+      - name: Setup pnpm
+        uses: pnpm/action-setup@v4
+        with:
+          version: 10.28.2
+
+      - name: Setup Node.js
+        uses: actions/setup-node@v6
+        with:
+          node-version: '24.13.0'
+          cache: "pnpm"
+          cache-dependency-path: dashboard/pnpm-lock.yaml
+
+      - name: Build dashboard dist
+        shell: bash
+        run: |
+          pnpm --dir dashboard install --frozen-lockfile
+          pnpm --dir dashboard run build
+          echo "${{ steps.tag.outputs.tag }}" > dashboard/dist/assets/version
+          cd dashboard
+          zip -r "AstrBot-${{ steps.tag.outputs.tag }}-dashboard.zip" dist
+
+      - name: Upload dashboard artifact
+        uses: actions/upload-artifact@v7
+        with:
+          name: Dashboard-${{ steps.tag.outputs.tag }}
+          if-no-files-found: error
+          path: dashboard/AstrBot-${{ steps.tag.outputs.tag }}-dashboard.zip
+
+      - name: Upload dashboard package to Cloudflare R2
+        if: ${{ env.R2_ACCOUNT_ID != '' && env.R2_ACCESS_KEY_ID != '' && env.R2_SECRET_ACCESS_KEY != '' }}
+        env:
+          R2_BUCKET_NAME: "astrbot"
+          R2_OBJECT_NAME: "astrbot-webui-latest.zip"
+          VERSION_TAG: ${{ steps.tag.outputs.tag }}
+        shell: bash
+        run: |
+          curl https://rclone.org/install.sh | sudo bash
+
+          mkdir -p ~/.config/rclone
+          cat <<EOF > ~/.config/rclone/rclone.conf
+          [r2]
+          type = s3
+          provider = Cloudflare
+          access_key_id = $R2_ACCESS_KEY_ID
+          secret_access_key = $R2_SECRET_ACCESS_KEY
+          endpoint = https://${R2_ACCOUNT_ID}.r2.cloudflarestorage.com
+          EOF
+
+          cp "dashboard/AstrBot-${VERSION_TAG}-dashboard.zip" "dashboard/${R2_OBJECT_NAME}"
+          rclone copy "dashboard/${R2_OBJECT_NAME}" "r2:${R2_BUCKET_NAME}" --progress
+          cp "dashboard/AstrBot-${VERSION_TAG}-dashboard.zip" "dashboard/astrbot-webui-${VERSION_TAG}.zip"
+          rclone copy "dashboard/astrbot-webui-${VERSION_TAG}.zip" "r2:${R2_BUCKET_NAME}" --progress
+
+  publish-release:
+    name: Publish GitHub Release
+    runs-on: ubuntu-24.04
+    needs:
+      - build-dashboard
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v6
+        with:
+          fetch-depth: 0
+          ref: ${{ inputs.ref || github.ref }}
+
+      - name: Resolve tag
+        id: tag
+        shell: bash
+        run: |
+          if [ "${{ github.event_name }}" = "push" ]; then
+            tag="${GITHUB_REF_NAME}"
+          elif [ -n "${{ inputs.tag }}" ]; then
+            tag="${{ inputs.tag }}"
+          else
+            tag="$(git describe --tags --abbrev=0)"
+          fi
+          if [ -z "$tag" ]; then
+            echo "Failed to resolve tag." >&2
+            exit 1
+          fi
+          echo "tag=$tag" >> "$GITHUB_OUTPUT"
+
+      - name: Download dashboard artifact
+        uses: actions/download-artifact@v8
+        with:
+          name: Dashboard-${{ steps.tag.outputs.tag }}
+          path: release-assets
+
+
+      - name: Resolve release notes
+        id: notes
+        shell: bash
+        run: |
+          note_file="changelogs/${{ steps.tag.outputs.tag }}.md"
+          if [ ! -f "$note_file" ]; then
+            note_file="$(mktemp)"
+            echo "Release ${{ steps.tag.outputs.tag }}" > "$note_file"
+          fi
+          echo "file=$note_file" >> "$GITHUB_OUTPUT"
+
+      - name: Ensure release exists
+        env:
+          GH_TOKEN: ${{ github.token }}
+        shell: bash
+        run: |
+          tag="${{ steps.tag.outputs.tag }}"
+          if ! gh release view "$tag" >/dev/null 2>&1; then
+            gh release create "$tag" --title "$tag" --notes-file "${{ steps.notes.outputs.file }}"
+          fi
+
+      - name: Remove stale assets from release
+        env:
+          GH_TOKEN: ${{ github.token }}
+        shell: bash
+        run: |
+          tag="${{ steps.tag.outputs.tag }}"
+          while IFS= read -r asset; do
+            case "$asset" in
+              *.AppImage|*.dmg|*.zip|*.exe|*.blockmap)
+                gh release delete-asset "$tag" "$asset" -y || true
+                ;;
+            esac
+          done < <(gh release view "$tag" --json assets --jq '.assets[].name')
+
+      - name: Upload assets to release
+        env:
+          GH_TOKEN: ${{ github.token }}
+        shell: bash
+        run: |
+          tag="${{ steps.tag.outputs.tag }}"
+          gh release upload "$tag" release-assets/* --clobber
+
+  publish-pypi:
+    name: Publish PyPI
+    runs-on: ubuntu-24.04
+    needs:
+      - publish-release
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v6
+        with:
+          fetch-depth: 0
+          ref: ${{ inputs.ref || github.ref }}
+
+      - name: Resolve tag
+        id: tag
+        shell: bash
+        run: |
+          if [ "${{ github.event_name }}" = "push" ]; then
+            tag="${GITHUB_REF_NAME}"
+          elif [ -n "${{ inputs.tag }}" ]; then
+            tag="${{ inputs.tag }}"
+          else
+            tag="$(git describe --tags --abbrev=0)"
+          fi
+          if [ -z "$tag" ]; then
+            echo "Failed to resolve tag." >&2
+            exit 1
+          fi
+          echo "tag=$tag" >> "$GITHUB_OUTPUT"
+
+      - name: Download dashboard artifact
+        uses: actions/download-artifact@v8
+        with:
+          name: Dashboard-${{ steps.tag.outputs.tag }}
+          path: dashboard-artifact
+
+      - name: Unpack dashboard dist into package tree
+        shell: bash
+        run: |
+          mkdir -p astrbot/dashboard/dist
+          unzip -q "dashboard-artifact/AstrBot-${{ steps.tag.outputs.tag }}-dashboard.zip" -d dashboard-artifact/unpacked
+          cp -r dashboard-artifact/unpacked/dist/. astrbot/dashboard/dist/
+
+      - name: Set up Python
+        uses: actions/setup-python@v6
+        with:
+          python-version: "3.10"
+
+      - name: Install uv
+        shell: bash
+        run: python -m pip install uv
+
+      - name: Build package
+        shell: bash
+        # Dashboard assets are already in astrbot/dashboard/dist/;
+        # ASTRBOT_BUILD_DASHBOARD is intentionally unset so the hatch hook skips npm.
+        run: uv build
+
+      - name: Publish to PyPI
+        env:
+          UV_PUBLISH_TOKEN: ${{ secrets.PYPI_TOKEN }}
+        shell: bash
+        run: uv publish
@@ -0,0 +1,58 @@
+name: Smoke Test
+
+on:
+  push:
+    branches:
+      - master
+    paths-ignore:
+      - 'README*.md'
+      - 'changelogs/**'
+      - 'dashboard/**'
+  pull_request:
+  workflow_dispatch:
+
+jobs:
+  smoke-test:
+    name: Run smoke tests
+    runs-on: ubuntu-latest
+    timeout-minutes: 10
+    
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v6
+        with:
+          fetch-depth: 0
+
+      - name: Set up Python
+        uses: actions/setup-python@v6
+        with:
+          python-version: '3.12'
+      
+      - name: Install UV package manager
+        run: |
+          pip install uv
+
+      - name: Install dependencies
+        run: |
+          uv sync
+        timeout-minutes: 15
+
+      - name: Run smoke tests
+        run: |
+          uv run main.py &
+          APP_PID=$!
+
+          echo "Waiting for application to start..."
+          for i in {1..60}; do
+            if curl -f http://localhost:6185 > /dev/null 2>&1; then
+              echo "Application started successfully!"
+              kill $APP_PID
+              exit 0
+            fi
+            sleep 1
+          done
+
+          echo "Application failed to start within 30 seconds"
+          kill $APP_PID 2>/dev/null || true
+          exit 1
+        timeout-minutes: 2
@@ -1,27 +1,64 @@
-# This workflow warns and then closes issues and PRs that have had no activity for a specified amount of time.
+# 本工作流用于标记并关闭长期不活跃的 Issue。
+# 目前仅针对带 `bug` 标签的 Issue 生效，不会处理 PR。
 #
-# You can adjust the behavior by modifying this file.
-# For more information, see:
-# https://github.com/actions/stale
-name: Mark stale issues and pull requests
+# 文档: https://github.com/actions/stale
+name: Mark stale bug issues

 on:
  schedule:
-  - cron: '21 23 * * *'
+    # 每天 UTC 08:30 执行 (北京时间 16:30)
+    - cron: '30 8 * * *'
+  workflow_dispatch:
+    inputs:
+      dry-run:
+        description: '仅预览, 不实际执行 (Dry run mode)'
+        required: false
+        default: true
+        type: boolean

 jobs:
  stale:
-
    runs-on: ubuntu-latest
    permissions:
      issues: write
-      pull-requests: write

    steps:
-    - uses: actions/stale@v10
-      with:
-        repo-token: ${{ secrets.GITHUB_TOKEN }}
-        stale-issue-message: 'Stale issue message'
-        stale-pr-message: 'Stale pull request message'
-        stale-issue-label: 'no-issue-activity'
-        stale-pr-label: 'no-pr-activity'
+      - uses: actions/stale@v10
+        with:
+          repo-token: ${{ secrets.GITHUB_TOKEN }}
+          operations-per-run: 200
+
+          # 只处理带 bug 标签的 Issue
+          any-of-labels: 'bug'
+
+          # 不处理 PR
+          days-before-pr-stale: -1
+          days-before-pr-close: -1
+
+          # 不活跃判定与关闭策略: 先标记 stale, 再延迟关闭
+          days-before-issue-stale: 60
+          days-before-issue-close: 30
+
+          stale-issue-label: 'stale'
+          stale-issue-message: |
+            This issue has been automatically marked as **stale** because it has not had any activity.
+            It will be closed in a certain period of time if no further activity occurs.
+            If this issue is still relevant, please leave a comment.
+
+            ---
+
+            该 Issue 已较长时间无活动, 已被标记为 `stale`。
+            如无后续活动, 将在一段时间后自动关闭。
+            如仍需跟进, 请回复评论。
+          close-issue-message: |
+            This issue has been automatically closed due to inactivity.
+            If the problem still exists, feel free to reopen or create a new issue with updated information.
+
+            ---
+
+            该 Issue 因长期无活动已自动关闭。
+            如问题仍存在, 欢迎补充复现信息并重新打开或新建 Issue。
+
+          remove-stale-when-updated: true
+
+          debug-only: ${{ github.event_name == 'workflow_dispatch' && inputs.dry-run }}
@@ -0,0 +1,68 @@
+name: sync wiki
+
+on:
+  workflow_dispatch:
+  push:
+    branches:
+      - master
+    paths:
+      - '.github/workflows/sync-wiki.yml'
+      - 'docs/scripts/sync_docs_to_wiki.py'
+      - 'docs/tests/test_sync_docs_to_wiki.py'
+      - 'docs/zh/**'
+      - 'docs/en/**'
+
+concurrency:
+  group: sync-wiki-${{ github.ref }}
+  cancel-in-progress: true
+
+jobs:
+  sync:
+    runs-on: ubuntu-latest
+    permissions:
+      contents: read
+
+    steps:
+      - name: Validate manual ref
+        if: github.event_name == 'workflow_dispatch' && github.ref != 'refs/heads/master'
+        run: |
+          echo "This workflow only publishes from refs/heads/master. Re-run it from the master branch."
+          exit 1
+
+      - name: Check out docs repository
+        uses: actions/checkout@v6
+
+      - name: Set up Python
+        uses: actions/setup-python@v6
+        with:
+          python-version: '3.11'
+
+      - name: Run sync unit tests
+        working-directory: docs
+        run: python -m unittest discover -s tests -p 'test_sync_docs_to_wiki.py' -v
+
+      - name: Validate internal doc links
+        run: python docs/scripts/sync_docs_to_wiki.py --source-root docs --check-links-only
+
+      - name: Clone AstrBot wiki
+        env:
+          WIKI_TOKEN: ${{ secrets.ASTRBOT_WIKI_TOKEN }}
+        run: |
+          test -n "$WIKI_TOKEN"
+          git clone "https://x-access-token:${WIKI_TOKEN}@github.com/AstrBotDevs/AstrBot.wiki.git" wiki
+
+      - name: Generate wiki pages
+        run: python docs/scripts/sync_docs_to_wiki.py --source-root docs --wiki-root wiki
+
+      - name: Commit and push wiki changes
+        working-directory: wiki
+        run: |
+          git config user.name "github-actions[bot]"
+          git config user.email "41898282+github-actions[bot]@users.noreply.github.com"
+          git add .
+          if git diff --cached --quiet; then
+            echo "No wiki changes to push"
+            exit 0
+          fi
+          git commit -m "docs: sync wiki from AstrBot-1/docs"
+          git push
@@ -24,16 +24,20 @@ configs/session
 configs/config.yaml
 cmd_config.json

-# Plugins and packages
+# Plugins
 addons/plugins
-packages/python_interpreter/workplace
+astrbot/builtin_stars/python_interpreter/workplace
 tests/astrbot_plugin_openai

 # Dashboard
 dashboard/node_modules/
 dashboard/dist/
+.pnpm-store/
 package-lock.json
-package.json
+yarn.lock
+
+# Bundled dashboard dist (generated by hatch_build.py during pip wheel build)
+astrbot/dashboard/dist/

 # Operating System
 **/.DS_Store
@@ -47,3 +51,15 @@ astrbot.lock
 chroma
 venv/*
 pytest.ini
+AGENTS.md
+IFLOW.md
+
+# genie_tts data
+CharacterModels/
+GenieData/
+.agent/
+.codex/
+.opencode/
+.kilocode/
+.worktrees/
+docs/plans/
@@ -1 +1 @@
-3.10
+3.12
@@ -0,0 +1,34 @@
+## Setup commands
+
+### Core
+
+```
+uv sync
+uv run main.py
+```
+
+Exposed an API server on `http://localhost:6185` by default.
+
+### Dashboard(WebUI)
+
+```
+cd dashboard
+pnpm install # First time only. Use npm install -g pnpm if pnpm is not installed.
+pnpm dev
+```
+
+Runs on `http://localhost:3000` by default.
+
+## Dev environment tips
+
+1. When modifying the WebUI, be sure to maintain componentization and clean code. Avoid duplicate code.
+2. Do not add any report files such as xxx_SUMMARY.md.
+3. After finishing, use `ruff format .` and `ruff check .` to format and check the code.
+4. When committing, ensure to use conventional commits messages, such as `feat: add new agent for data analysis` or `fix: resolve bug in provider manager`.
+5. Use English for all new comments.
+6. For path handling, use `pathlib.Path` instead of string paths, and use `astrbot.core.utils.path_utils` to get the AstrBot data and temp directory.
+
+## PR instructions
+
+1. Title format: use conventional commit messages
+2. Use English to write PR title and descriptions.
@@ -0,0 +1,142 @@
+# CONTRIBUTING
+
+## 贡献指南
+
+首先，感谢您花时间做出贡献！❤️
+
+所有类型的贡献都受到鼓励和重视。有关不同的帮助方式和处理方式的详细信息，请参阅[目录](#目录)。在做出贡献之前，请确保阅读相关部分。这将使我们维护人员的工作变得更加容易，并为所有参与者带来顺畅的体验。社区期待您的贡献。🎉
+
+### 目录
+
+- [报告问题](#报告问题)
+- [提交代码更改](#提交代码更改)
+
+### 报告问题
+
+如果您在使用 AstrBot 时遇到任何问题，请按照以下步骤报告：
+
+1. **检查现有问题**：在提交新问题之前，请先检查 [Issues](https://github.com/AstrBotDevs/AstrBot/issues) 中是否已经存在类似的问题。
+2. **创建新问题**：如果没有类似的问题，请创建一个新问题。请确保提供以下信息：
+   - 问题的简要描述
+   - 重现问题的步骤
+   - 预期结果和实际结果
+   - 相关日志或错误消息
+
+### 提交代码更改
+
+#### 分支命名
+
+我们使用 `fix/` 前缀来修复错误，使用 `feat/` 前缀来添加新功能。对于 `fix/` 分支，请使用简短的描述，或者直接使用 Issue 编号。例如：`fix/1234` 或者 `fix/1234-login-typo`。对于 `feat/` 分支，请使用简短的描述，例如：`feat/add-user-profile`。
+
+#### PR 描述
+
+- 请使用英文描述您的 PR。
+- 标题请使用 `fix: `, `feat: `, `docs: `, `style: `, `refactor: `, `test: `, `chore: ` 等语义化前缀，并简要描述更改内容。如：`fix: correct login page typo`。
+
+#### 代码规范
+
+##### Core
+
+我们使用 Ruff 作为代码格式化和静态分析工具。在提交代码之前，请运行以下命令以确保代码符合规范：
+
+```bash
+ruff format .
+ruff check .
+```
+
+如果您使用 VSCode，可以安装 `Ruff` 插件。
+
+##### PR 功能完整性验证（推荐）
+
+如果您希望在本地做一套接近 CI 的完整验证，可使用：
+
+```bash
+make pr-test-neo
+```
+
+该命令会执行：
+- `uv sync --group dev`
+- `ruff format --check .` 与 `ruff check .`
+- Neo 相关关键测试
+- `main.py` 启动 smoke test（检测 `http://localhost:6185`）
+
+需要全量验证时可使用：
+
+```bash
+make pr-test-full
+```
+
+如果只想快速重复执行（跳过依赖同步和 dashboard 构建）：
+
+```bash
+make pr-test-full-fast
+```
+
+
+## Contributing Guide
+
+First off, thanks for taking the time to contribute! ❤️
+
+All types of contributions are encouraged and valued. See the [Table of Contents](#table-of-contents) for different ways to help and details about how this project handles them. Please make sure to read the relevant section before making your contribution. It will make it a lot easier for us maintainers and smooth out the experience for all involved. The community looks forward to your contributions. 🎉
+
+### Table of Contents
+
+- [Reporting Issues](#reporting-issues)
+- [Pull Requests](#pull-requests)
+
+### Reporting Issues
+
+If you encounter any issues while using AstrBot, please follow these steps to report them:
+1. **Check Existing Issues**: Before submitting a new issue, please check if a similar issue already exists in the [Issues](https://github.com/AstrBotDevs/AstrBot/issues) section of the repository.
+2. **Create a New Issue**: If no similar issue exists, please create a new issue. Make sure to provide the following information:
+   - A brief description of the issue
+   - Steps to reproduce the issue
+   - Expected and actual results
+   - Relevant logs or error messages
+
+### Pull Requests
+
+#### Branch Naming
+
+We use the `fix/` prefix for bug fixes and the `feat/` prefix for new features. For `fix/` branches, please use a short description or directly use the Issue number, e.g., `fix/1234` or `fix/1234-login-typo`. For `feat/` branches, please use a short description, e.g., `feat/add-user-profile`.
+
+#### PR Description
+- Please use English to describe your PR.
+- Use semantic prefixes like `fix: `, `feat: `, `docs: `, `style: `, `refactor: `, `test: `, `chore: ` in the title, followed by a brief description of the changes, e.g., `fix: correct login page typo`.
+
+#### Code Style
+
+##### Core
+
+We use Ruff as our code formatter and static analysis tool. Before submitting your code, please run the following commands to ensure your code adheres to the style guidelines:
+
+```bash
+ruff format .
+ruff check .
+```
+
+##### PR completeness checks (recommended)
+
+To run a local validation flow close to CI, use:
+
+```bash
+make pr-test-neo
+```
+
+This command runs:
+- `uv sync --group dev`
+- `ruff format --check .` and `ruff check .`
+- Neo-related critical tests
+- a startup smoke test against `http://localhost:6185`
+
+For full validation, use:
+
+```bash
+make pr-test-full
+```
+
+For faster repeated runs (skip dependency sync and dashboard build), use:
+
+```bash
+make pr-test-full-fast
+```
@@ -1,4 +1,4 @@
-FROM python:3.11-slim
+FROM python:3.12-slim
 WORKDIR /AstrBot

 COPY . /AstrBot/
@@ -15,17 +15,17 @@ RUN apt-get update && apt-get install -y --no-install-recommends \
    curl \
    gnupg \
    git \
+    && curl -fsSL https://deb.nodesource.com/setup_lts.x | bash - \
+    && apt-get install -y --no-install-recommends nodejs \
    && apt-get clean \
    && rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/*

-RUN apt-get update && apt-get install -y curl gnupg \
-    && curl -fsSL https://deb.nodesource.com/setup_lts.x | bash - \
-    && apt-get install -y nodejs
-
 RUN python -m pip install uv \
-    && echo "3.11" > .python-version
-RUN uv pip install -r requirements.txt --no-cache-dir --system
-RUN uv pip install socksio uv pilk --no-cache-dir --system
+    && echo "3.12" > .python-version \
+    && uv lock \
+    && uv export --format requirements.txt --output-file requirements.txt --frozen \
+    && uv pip install -r requirements.txt --no-cache-dir --system \
+    && uv pip install socksio uv pilk --no-cache-dir --system

 EXPOSE 6185

@@ -0,0 +1,244 @@
+# 最终用户许可协议（EULA）
+
+> 我们热爱开源软件，并始终致力于为所有用户提供健康、安全、可靠的使用体验。 ❤️
+
+For English edition, please refer to the section below the Chinese version.
+
+**最后更新：** 2026-01-12
+
+感谢您使用 **AstrBot**。
+在使用本项目之前，请仔细阅读以下声明内容。
+
+**您一旦安装、运行或使用本项目，即表示您已阅读、理解并同意本声明中的全部内容。**
+
+## 1. 项目性质
+
+AstrBot 是一个遵循 **GNU Affero General Public License v3（AGPLv3）** 协议发布的**免费开源软件项目**。
+
+* 截至目前，AstrBot 项目未开展任何形式的商业化服务，AstrBot 团队也未通过本项目向用户提供任何收费服务。若您因使用 AstrBot 被要求付费，请务必提高警惕，谨防诈骗行为。
+* AstrBot 的代码实现未对任何第三方系统进行逆向工程、破解、反编译或绕过安全机制等行为。AstrBot 仅使用并支持各即时通讯（IM）平台官方公开提供的机器人接入接口、开放平台能力或相关通信协议进行集成与通信。
+
+## 2. 无担保声明
+
+AstrBot 按“**现状（as is）**”提供，不附带任何形式的明示或暗示担保。
+
+AstrBot 团队不对以下内容作出任何保证：
+
+* 系统本身的安全性、可靠性或稳定性；
+* 任何第三方插件的安全性、正确性或可信度；
+* 任何第三方 AI 模型或外部服务 API 的可用性、质量、准确性或安全性；
+* 本软件对任何特定用途的适用性。
+
+**您使用本软件所产生的一切风险均由您自行承担。**
+
+## 3. 第三方插件与服务
+
+* AstrBot 支持第三方插件及外部 AI 服务接入；
+* AstrBot 团队**不对任何第三方插件、扩展或服务进行审计、控制、背书或担保**；
+* 因使用第三方插件或服务所产生的任何风险、损失、数据泄露或法律后果，均由用户自行承担。
+* 第三方插件指代的是非 AstrBot 自带的插件，AstrBot 自带的插件指代的是插件实现代码已经包含在 AstrBotDevs/AstrBot 代码库中的插件。插件市场中的插件都是第三方插件。
+
+## 4. 使用与内容限制
+
+您同意不会将 AstrBot 用于以下行为：
+
+* 输入、生成、传播或处理任何违法、极端、暴力、色情、仇恨、辱骂或其他有害内容；
+* 从事违反您所在国家或地区法律法规，或任何适用国际法律的行为；
+* 试图绕过、关闭、削弱或破坏本系统内置的安全机制或内容限制。
+* 任何侵犯他人合法权益、损害他人和自己身心健康、涉及个人隐私、个人信息等敏感内容的内容。
+
+## 5. 项目用途说明
+
+AstrBot 是一个**工具型对话与 Agent 系统**，在**安全、健康、友善**的前提下提供有限的人性化交互能力。
+
+项目的主要目标是：
+
+* 提供 Agent 能力与自动化辅助；
+* 帮助用户提升工作、学习和信息处理效率；
+* 在合理范围内提供友好的人机交互体验。
+* 辅助用户成长，提供有益于用户身心健康的内容。
+
+## 6. 安全措施说明
+
+AstrBot 团队**已尽合理努力在技术和策略层面设置安全与内容约束机制**，以引导系统输出健康、友善、安全的内容。
+
+但请理解：
+
+* 世界上任何的系统均无法保证完全无误、绝对安全或无法被滥用；
+* 用户仍有责任自行合理配置、监督并正确使用本系统。
+
+如果您要关闭 AstrBot 默认启用的“健康模式”，请在 cmd_config.json 中将 `provider_settings.llm_safety_mode` 设置为 `False`。但请注意，关闭健康模式不是推荐的使用方式，可能导致系统输出不安全或不适当的内容。关闭该功能所产生的任何风险与后果，均由用户自行承担，AstrBot 团队不对此承担任何责任。
+
+## 7. 心理健康提示
+
+如果您在使用本项目过程中因系统输出内容而感到心理不适、情绪困扰，  
+或您本身正处于心理压力较大、情绪不稳定、焦虑、抑郁等状态并因此使用本项目，  
+请优先考虑寻求来自专业人士的帮助，例如心理咨询师、心理医生或当地心理援助机构。
+
+如遇紧急情况（例如存在自伤或他伤风险），请立即联系当地的紧急救助电话或专业机构。
+
+## 8. 统计信息与隐私说明
+
+AstrBot 可能会收集有限的匿名统计信息，用于了解系统使用情况、发现问题以及持续改进项目。
+
+所收集的统计信息仅包括与系统运行和功能使用相关的基础技术指标，例如功能使用频率、错误信息等。
+
+AstrBot **不会收集、上传或存储您的对话内容、消息正文、输入文本，或任何能够识别您个人身份的敏感信息**。
+
+您可以手动关闭此项功能，通过在系统环境变量中设置 `ASTRBOT_DISABLE_METRICS=1` 来禁用匿名统计信息收集。
+
+## 9. 责任限制
+
+在法律允许的最大范围内，AstrBot 团队不对因以下原因导致的任何直接或间接损失承担责任，包括但不限于：
+
+* 使用或无法使用本软件；
+* 使用第三方插件或服务；
+* 系统生成的内容或输出；
+* 数据丢失、服务中断或安全事件。
+
+## 10. 条款的接受
+
+您一旦安装、运行、修改或使用 AstrBot，即确认：
+
+* 您已阅读并理解本声明内容；
+* 您同意并接受上述所有条款；
+* 您对自身使用行为承担全部责任。
+
+如您不同意本声明的任何内容，请勿使用本项目。
+
+## 11. 许可与版权
+
+AstrBot 的源代码、文档及相关内容受版权法及相关法律保护。
+
+在遵守本声明及 AGPLv3 协议的前提下，AstrBot 授予您一项非独占、不可转让、不可再许可的许可，用于下载、安装、运行、修改和分发本软件。
+
+除非法律另有规定或本声明另有明确说明，AstrBot 团队保留本项目的所有未明确授予的权利。
+
+## 12. 适用法律
+
+本声明的解释与适用应遵循您所在地或项目发布地适用的法律法规。
+
+如本声明的任何条款被认定为无效或不可执行，其余条款仍然有效。
+
+---
+
+# EULA
+
+> We love open-source software and are always committed to providing all users with a healthy, safe, and reliable experience. ❤️
+
+**Last updated:** January 12, 2026
+
+Thank you for using **AstrBot**.
+Please read the following notice carefully before using this project.
+
+**By installing, running, or using this project, you acknowledge that you have read, understood, and agreed to all the terms stated below.**
+
+## 1. Nature of the Project
+
+AstrBot is a **free and open-source software project** released under the **GNU Affero General Public License v3 (AGPLv3)**.
+
+* AstrBot does not constitute any form of commercial service;
+* The AstrBot Team does not provide any paid services through this project;
+* AstrBot’s implementation does not involve reverse engineering, cracking, decompilation, or circumvention of security mechanisms of any third-party systems. AstrBot only uses and supports officially published bot integration interfaces, open platform capabilities, or related communication protocols provided by instant messaging (IM) platforms for integration and communication.
+
+## 2. No Warranty
+
+AstrBot is provided **“as is”**, without any express or implied warranties.
+
+The AstrBot Team makes no guarantees regarding:
+
+* The security, reliability, or stability of the system;
+* The security, correctness, or trustworthiness of any third-party plugins;
+* The availability, quality, accuracy, or safety of any third-party AI model APIs or external services;
+* The fitness of the software for any particular purpose.
+
+**All risks arising from the use of this software are borne solely by the user.**
+
+## 3. Third-Party Plugins and Services
+
+* AstrBot supports third-party plugins and external AI services;
+* The AstrBot Team does **not audit, control, endorse, or guarantee** any third-party plugins, extensions, or services;
+* Any risks, losses, data leaks, or legal consequences arising from the use of third-party plugins or services are solely the responsibility of the user;
+* “Third-party plugins” refer to plugins that are not built into AstrBot. Built-in plugins are those whose implementation code is included in the AstrBotDevs/AstrBot repository. All plugins available in the plugin marketplace are third-party plugins.
+
+## 4. Usage and Content Restrictions
+
+You agree not to use AstrBot for any of the following activities:
+
+* Inputting, generating, distributing, or processing any illegal, extremist, violent, pornographic, hateful, abusive, or otherwise harmful content;
+* Engaging in activities that violate the laws or regulations of your country or region, or any applicable international laws;
+* Attempting to bypass, disable, weaken, or undermine the built-in safety mechanisms or content restrictions of the system;
+* Any activities that infringe upon the legitimate rights and interests of others, harm the physical or mental well-being of yourself or others, or involve personal privacy or sensitive personal information.
+
+## 5. Intended Use
+
+AstrBot is a **tool-oriented conversational and agent system** that provides limited human-like interaction capabilities under the principles of **safety, health, and friendliness**.
+
+The primary goals of the project are to:
+
+* Provide agent capabilities and automation assistance;
+* Help users improve efficiency in work, study, and information processing;
+* Offer a friendly human–computer interaction experience within reasonable boundaries;
+* Support user growth and provide content beneficial to users’ physical and mental well-being.
+
+## 6. Safety Measures
+
+The AstrBot Team has made **reasonable efforts** at both technical and policy levels to implement safety and content restriction mechanisms, guiding the system to produce healthy, friendly, and safe outputs.
+
+However, please understand that:
+
+* No system in the world can be guaranteed to be completely error-free, absolutely secure, or immune to misuse;
+* Users remain responsible for properly configuring, supervising, and using the system.
+
+If you wish to disable AstrBot’s default “Safety Mode,” please set `provider_settings.llm_safety_mode` to `False` in `cmd_config.json`. However, please note that disabling Safety Mode is not recommended and may lead to unsafe or inappropriate outputs. Any risks or consequences arising from disabling this feature are solely borne by the user, and the AstrBot Team assumes no responsibility.
+
+## 7. Mental Health Notice
+
+If you experience psychological discomfort or emotional distress due to system outputs during use,
+or if you are experiencing significant psychological stress, emotional instability, anxiety, or depression and are using this project for such reasons,
+please prioritize seeking help from qualified professionals, such as psychologists, psychiatrists, or local mental health support services.
+
+In case of emergency (for example, if there is a risk of self-harm or harm to others), please immediately contact your local emergency number or professional crisis support services.
+
+## 8. Metrics and Privacy
+
+AstrBot may collect a limited amount of anonymous usage statistics to understand system usage, identify issues, and continuously improve the project.
+
+Collected metrics are limited to basic technical indicators related to system operation and feature usage, such as feature usage frequency and error information.
+
+AstrBot **does not collect, upload, or store your conversation content, message bodies, input text, or any personally identifiable or sensitive information**.
+
+You may manually disable this feature by setting the environment variable `ASTRBOT_DISABLE_METRICS=1` to turn off anonymous metrics collection.
+
+## 9. Limitation of Liability
+
+To the maximum extent permitted by law, the AstrBot Team shall not be liable for any direct or indirect losses arising from, including but not limited to:
+
+* The use or inability to use this software;
+* The use of third-party plugins or services;
+* Generated content or system outputs;
+* Data loss, service interruptions, or security incidents.
+
+## 10. Acceptance of Terms
+
+By installing, running, modifying, or using AstrBot, you confirm that:
+
+* You have read and understood this Notice;
+* You agree to and accept all the terms stated above;
+* You assume full responsibility for your use of the software.
+
+If you do not agree with any part of this Notice, please do not use this project.
+
+## 11. License and Copyright
+
+The source code, documentation, and related materials of AstrBot are protected by copyright laws and applicable regulations.
+
+Subject to compliance with this Notice and the AGPLv3 license, AstrBot grants you a non-exclusive, non-transferable, non-sublicensable license to download, install, run, modify, and distribute this software.
+
+Unless otherwise required by law or expressly stated in this Notice, the AstrBot Team reserves all rights not expressly granted.
+
+## 12. Governing Law
+
+The interpretation and application of this Notice shall be governed by the laws and regulations applicable in your jurisdiction or the jurisdiction where the project is released.
+
+If any provision of this Notice is held to be invalid or unenforceable, the remaining provisions shall remain in full force and effect.
@@ -0,0 +1,14 @@
+## Welcome to AstrBot
+
+🌟 Thank you for using AstrBot!
+
+AstrBot is an Agentic AI assistant for personal and group chats, with support for multiple IM platforms and a wide range of built-in features. We hope it brings you an efficient and enjoyable experience. ❤️
+
+Important notice:
+
+AstrBot is a **free and open-source software project** protected by the AGPLv3 license. You can find the full source code and related resources on our [**official website**](https://astrbot.app) and [**GitHub**](https://github.com/astrbotdevs/astrbot).
+As of now, AstrBot has **no commercial services of any kind**, and the official team **will never charge users any fees** under any name.
+
+If anyone asks you to pay while using AstrBot, **you are likely being scammed**. Please request a refund immediately and report it to us by email.
+
+📮 Official email: [community@astrbot.app](mailto:community@astrbot.app)
@@ -0,0 +1,14 @@
+## 欢迎使用 AstrBot
+
+🌟 感谢您使用 AstrBot！
+
+AstrBot 是一款可接入多种 IM 平台的 Agentic AI 个人 / 群聊助手，内置多项强大功能，希望能为您带来高效、愉快的使用体验。❤️
+
+我们想特别说明：
+
+AstrBot 是受 AGPLv3 开源协议保护的**免费开源软件项目**，您可以在[**官方网站**](https://astrbot.app)、[**GitHub**](https://github.com/astrbotdevs/astrbot) 上找到 AstrBot 的全部源代码及相关资源。
+截至目前，AstrBot 项目**未开展任何形式的商业化服务**，官方**不会以任何名义向用户收取费用**。
+
+如果您在使用 AstrBot 的过程中被要求付费，**表明您已经遭遇诈骗行为**。请立即向相关方申请退款，并及时通过邮件向我们反馈。
+
+📮 官方邮箱：[community@astrbot.app](mailto:community@astrbot.app)
@@ -0,0 +1,41 @@
+.PHONY: worktree worktree-add worktree-rm pr-test-neo pr-test-full pr-test-full-fast
+
+WORKTREE_DIR ?= ../astrbot_worktree
+BRANCH ?= $(word 2,$(MAKECMDGOALS))
+BASE ?= $(word 3,$(MAKECMDGOALS))
+BASE ?= master
+
+worktree:
+	@echo "Usage:"
+	@echo "  make worktree-add <branch> [base-branch]"
+	@echo "  make worktree-rm  <branch>"
+
+worktree-add:
+ifeq ($(strip $(BRANCH)),)
+	$(error Branch name required. Usage: make worktree-add <branch> [base-branch])
+endif
+	@mkdir -p $(WORKTREE_DIR)
+	git worktree add $(WORKTREE_DIR)/$(BRANCH) -b $(BRANCH) $(BASE)
+
+worktree-rm:
+ifeq ($(strip $(BRANCH)),)
+	$(error Branch name required. Usage: make worktree-rm <branch>)
+endif
+	@if [ -d "$(WORKTREE_DIR)/$(BRANCH)" ]; then \
+		git worktree remove $(WORKTREE_DIR)/$(BRANCH); \
+	else \
+		echo "Worktree $(WORKTREE_DIR)/$(BRANCH) not found."; \
+	fi
+
+pr-test-neo:
+	./scripts/pr_test_env.sh --profile neo
+
+pr-test-full:
+	./scripts/pr_test_env.sh --profile full
+
+pr-test-full-fast:
+	./scripts/pr_test_env.sh --profile full --skip-sync --no-dashboard
+
+# Swallow extra args (branch/base) so make doesn't treat them as targets
+%:
+	@true
@@ -1,9 +1,13 @@
 ![AstrBot-Logo-Simplified](https://github.com/user-attachments/assets/ffd99b6b-3272-4682-beaa-6fe74250f7d9)

-</p>
-
 <div align="center">

+<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_zh.md">简体中文</a> ｜
+<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_zh-TW.md">繁體中文</a> ｜
+<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_ja.md">日本語</a> ｜
+<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_fr.md">Français</a> ｜
+<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_ru.md">Русский</a>
+
 <br>

 <div>
@@ -14,190 +18,201 @@
 <br>

 <div>
-<img src="https://img.shields.io/github/v/release/AstrBotDevs/AstrBot?style=for-the-badge&color=76bad9" href="https://github.com/AstrBotDevs/AstrBot/releases/latest">
-<img src="https://img.shields.io/badge/python-3.10+-blue.svg?style=for-the-badge&color=76bad9" alt="python">
-<a href="https://hub.docker.com/r/soulter/astrbot"><img alt="Docker pull" src="https://img.shields.io/docker/pulls/soulter/astrbot.svg?style=for-the-badge&color=76bad9"/></a>
-<a href="https://qm.qq.com/cgi-bin/qm/qr?k=wtbaNx7EioxeaqS9z7RQWVXPIxg2zYr7&jump_from=webapi&authKey=vlqnv/AV2DbJEvGIcxdlNSpfxVy+8vVqijgreRdnVKOaydpc+YSw4MctmEbr0k5"><img alt="QQ_community" src="https://img.shields.io/badge/QQ群-775869627-purple?style=for-the-badge&color=76bad9"></a>
-<a href="https://t.me/+hAsD2Ebl5as3NmY1"><img alt="Telegram_community" src="https://img.shields.io/badge/Telegram-AstrBot-purple?style=for-the-badge&color=76bad9"></a>
-<img src="https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fapi.soulter.top%2Fastrbot%2Fplugin-num&query=%24.result&suffix=%E4%B8%AA&style=for-the-badge&label=%E6%8F%92%E4%BB%B6%E5%B8%82%E5%9C%BA&cacheSeconds=3600">
+<img src="https://img.shields.io/github/v/release/AstrBotDevs/AstrBot?color=76bad9" href="https://github.com/AstrBotDevs/AstrBot/releases/latest">
+<img src="https://img.shields.io/badge/python-3.10+-blue.svg" alt="python">
+<img src="https://deepwiki.com/badge.svg" href="https://deepwiki.com/AstrBotDevs/AstrBot">
+<a href="https://zread.ai/AstrBotDevs/AstrBot" target="_blank"><img src="https://img.shields.io/badge/Ask_Zread-_.svg?style=flat&color=00b0aa&labelColor=000000&logo=data%3Aimage%2Fsvg%2Bxml%3Bbase64%2CPHN2ZyB3aWR0aD0iMTYiIGhlaWdodD0iMTYiIHZpZXdCb3g9IjAgMCAxNiAxNiIgZmlsbD0ibm9uZSIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KPHBhdGggZD0iTTQuOTYxNTYgMS42MDAxSDIuMjQxNTZDMS44ODgxIDEuNjAwMSAxLjYwMTU2IDEuODg2NjQgMS42MDE1NiAyLjI0MDFWNC45NjAxQzEuNjAxNTYgNS4zMTM1NiAxLjg4ODEgNS42MDAxIDIuMjQxNTYgNS42MDAxSDQuOTYxNTZDNS4zMTUwMiA1LjYwMDEgNS42MDE1NiA1LjMxMzU2IDUuNjAxNTYgNC45NjAxVjIuMjQwMUM1LjYwMTU2IDEuODg2NjQgNS4zMTUwMiAxLjYwMDEgNC45NjE1NiAxLjYwMDFaIiBmaWxsPSIjZmZmIi8%2BCjxwYXRoIGQ9Ik00Ljk2MTU2IDEwLjM5OTlIMi4yNDE1NkMxLjg4ODEgMTAuMzk5OSAxLjYwMTU2IDEwLjY4NjQgMS42MDE1NiAxMS4wMzk5VjEzLjc1OTlDMS42MDE1NiAxNC4xMTM0IDEuODg4MSAxNC4zOTk5IDIuMjQxNTYgMTQuMzk5OUg0Ljk2MTU2QzUuMzE1MDIgMTQuMzk5OSA1LjYwMTU2IDE0LjExMzQgNS42MDE1NiAxMy43NTk5VjExLjAzOTlDNS42MDE1NiAxMC42ODY0IDUuMzE1MDIgMTAuMzk5OSA0Ljk2MTU2IDEwLjM5OTlaIiBmaWxsPSIjZmZmIi8%2BCjxwYXRoIGQ9Ik0xMy43NTg0IDEuNjAwMUgxMS4wMzg0QzEwLjY4NSAxLjYwMDEgMTAuMzk4NCAxLjg4NjY0IDEwLjM5ODQgMi4yNDAxVjQuOTYwMUMxMC4zOTg0IDUuMzEzNTYgMTAuNjg1IDUuNjAwMSAxMS4wMzg0IDUuNjAwMUgxMy43NTg0QzE0LjExMTkgNS42MDAxIDE0LjM5ODQgNS4zMTM1NiAxNC4zOTg0IDQuOTYwMVYyLjI0MDFDMTQuMzk4NCAxLjg4NjY0IDE0LjExMTkgMS42MDAxIDEzLjc1ODQgMS42MDAxWiIgZmlsbD0iI2ZmZiIvPgo8cGF0aCBkPSJNNCAxMkwxMiA0TDQgMTJaIiBmaWxsPSIjZmZmIi8%2BCjxwYXRoIGQ9Ik00IDEyTDEyIDQiIHN0cm9rZT0iI2ZmZiIgc3Ryb2tlLXdpZHRoPSIxLjUiIHN0cm9rZS1saW5lY2FwPSJyb3VuZCIvPgo8L3N2Zz4K&logoColor=ffffff" alt="zread"/></a>
+<a href="https://hub.docker.com/r/soulter/astrbot"><img alt="Docker pull" src="https://img.shields.io/docker/pulls/soulter/astrbot.svg?color=76bad9"/></a>
+<img src="https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fapi.soulter.top%2Fastrbot%2Fplugin-num&query=%24.result&suffix=%20plugins&label=Marketplace&cacheSeconds=3600">
+<img src="https://gitcode.com/Soulter/AstrBot/star/badge.svg" href="https://gitcode.com/Soulter/AstrBot">
 </div>

 <br>

-<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_en.md">English</a> ｜
-<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_ja.md">日本語</a> ｜
-<a href="https://astrbot.app/">文档</a> ｜
+<a href="https://astrbot.app/">Documentation</a> ｜
 <a href="https://blog.astrbot.app/">Blog</a> ｜
-<a href="https://astrbot.featurebase.app/roadmap">路线图</a> ｜
-<a href="https://github.com/AstrBotDevs/AstrBot/issues">问题提交</a>
+<a href="https://astrbot.featurebase.app/roadmap">Roadmap</a> ｜
+<a href="https://github.com/AstrBotDevs/AstrBot/issues">Issue Tracker</a>
+<a href="mailto:community@astrbot.app">Email Support</a>
 </div>

-AstrBot 是一个开源的一站式 Agent 聊天机器人平台及开发框架。
+AstrBot is an open-source all-in-one Agent chatbot platform that integrates with mainstream instant messaging apps. It provides reliable and scalable conversational AI infrastructure for individuals, developers, and teams. Whether you're building a personal AI companion, intelligent customer service, automation assistant, or enterprise knowledge base, AstrBot enables you to quickly build production-ready AI applications within your IM platform workflows.

-## 主要功能
+![screenshot_1 5x_postspark_2026-02-27_22-37-45](https://github.com/user-attachments/assets/f17cdb90-52d7-4773-be2e-ff64b566af6b)

-1. **大模型对话**。支持接入多种大模型服务。支持多模态、工具调用、MCP、原生知识库、人设等功能。
-2. **多消息平台支持**。支持接入 QQ、企业微信、微信公众号、飞书、Telegram、钉钉、Discord、KOOK 等平台。支持速率限制、白名单、百度内容审核。
-3. **Agent**。完善适配的 Agentic 能力。支持多轮工具调用、内置沙盒代码执行器、网页搜索等功能。
-4. **插件扩展**。深度优化的插件机制，支持[开发插件](https://astrbot.app/dev/plugin.html)扩展功能，社区插件生态丰富。
-5. **WebUI**。可视化配置和管理机器人，功能齐全。
+## Key Features

-## 部署方式
+1. 💯 Free & Open Source.
+2. ✨ AI LLM Conversations, Multimodal, Agent, MCP, Skills, Knowledge Base, Persona Settings, Auto Context Compression.
+3. 🤖 Supports integration with Dify, Alibaba Cloud Bailian, Coze, and other agent platforms.
+4. 🌐 Multi-Platform: QQ, WeChat Work, Feishu, DingTalk, WeChat Official Accounts, Telegram, Slack, and [more](#supported-messaging-platforms).
+5. 📦 Plugin Extensions with 1000+ plugins available for one-click installation.
+6. 🛡️ [Agent Sandbox](https://docs.astrbot.app/use/astrbot-agent-sandbox.html) for isolated, safe execution of code, shell calls, and session-level resource reuse.
+7. 💻 WebUI Support.
+8. 🌈 Web ChatUI Support with built-in agent sandbox and web search.
+9. 🌐 Internationalization (i18n) Support.

-#### Docker 部署(推荐 🥳)
+<br>

-推荐使用 Docker / Docker Compose 方式部署 AstrBot。
+<table align="center">
+  <tr align="center">
+    <th>💙 Role-playing & Emotional Companionship</th>
+    <th>✨ Proactive Agent</th>
+    <th>🚀 General Agentic Capabilities</th>
+    <th>🧩 1000+ Community Plugins</th>
+  </tr>
+  <tr>
+    <td align="center"><p align="center"><img width="984" height="1746" alt="99b587c5d35eea09d84f33e6cf6cfd4f" src="https://github.com/user-attachments/assets/89196061-3290-458d-b51f-afa178049f84" /></p></td>
+    <td align="center"><p align="center"><img width="976" height="1612" alt="c449acd838c41d0915cc08a3824025b1" src="https://github.com/user-attachments/assets/f75368b4-e022-41dc-a9e0-131c3e73e32e" /></p></td>
+    <td align="center"><p align="center"><img width="974" height="1732" alt="image" src="https://github.com/user-attachments/assets/e22a3968-87d7-4708-a7cd-e7f198c7c32e" /></p></td>
+    <td align="center"><p align="center"><img width="976" height="1734" alt="image" src="https://github.com/user-attachments/assets/0952b395-6b4a-432a-8a50-c294b7f89750" /></p></td>
+  </tr>
+</table>

-请参阅官方文档 [使用 Docker 部署 AstrBot](https://astrbot.app/deploy/astrbot/docker.html#%E4%BD%BF%E7%94%A8-docker-%E9%83%A8%E7%BD%B2-astrbot) 。
+## Quick Start

-#### 宝塔面板部署
+### One-Click Deployment

-AstrBot 与宝塔面板合作，已上架至宝塔面板。
+For users who want to quickly experience AstrBot, are familiar with command-line usage, and can install a `uv` environment on their own, we recommend the `uv` one-click deployment method ⚡️:

-请参阅官方文档 [宝塔面板部署](https://astrbot.app/deploy/astrbot/btpanel.html) 。
+```bash
+uv tool install astrbot
+astrbot init # Only execute this command for the first time to initialize the environment
+astrbot
+```

-#### 1Panel 部署
+> Requires [uv](https://docs.astral.sh/uv/) to be installed.

-AstrBot 已由 1Panel 官方上架至 1Panel 面板。
+> [!NOTE]
+> For macOS user: due to macOS security checks, the first run of the `astrbot` command may take longer (about 10-20s).

-请参阅官方文档 [1Panel 部署](https://astrbot.app/deploy/astrbot/1panel.html) 。
+Update `astrbot`:

-#### 在 雨云 上部署
+```bash
+uv tool upgrade astrbot
+```

-AstrBot 已由雨云官方上架至云应用平台，可一键部署。
+### Docker Deployment
+
+For users familiar with containers and looking for a more stable, production-ready deployment method, we recommend deploying AstrBot with Docker / Docker Compose.
+
+Please refer to the official documentation: [Deploy AstrBot with Docker](https://astrbot.app/deploy/astrbot/docker.html#%E4%BD%BF%E7%94%A8-docker-%E9%83%A8%E7%BD%B2-astrbot).
+
+### Deploy on RainYun
+
+For users who want one-click deployment and do not want to manage servers themselves, we recommend RainYun's one-click cloud deployment service ☁️:

 [![Deploy on RainYun](https://rainyun-apps.cn-nb1.rains3.com/materials/deploy-on-rainyun-en.svg)](https://app.rainyun.com/apps/rca/store/5994?ref=NjU1ODg0)

-#### 在 Replit 上部署
+### Desktop Application Deployment

-社区贡献的部署方式。
+For users who want to use AstrBot on desktop and mainly use ChatUI, we recommend AstrBot App.
+
+Visit [AstrBot-desktop](https://github.com/AstrBotDevs/AstrBot-desktop) to download and install; this method is designed for desktop usage and is not recommended for server scenarios.
+
+### Launcher Deployment
+
+For desktop users who also want fast deployment and isolated multi-instance usage, we recommend AstrBot Launcher.
+
+Visit [AstrBot Launcher](https://github.com/Raven95676/astrbot-launcher) to download and install.
+
+### Deploy on Replit
+
+Replit deployment is maintained by the community and is suitable for online demos and lightweight trials.

 [![Run on Repl.it](https://repl.it/badge/github/AstrBotDevs/AstrBot)](https://repl.it/github/AstrBotDevs/AstrBot)

-#### Windows 一键安装器部署
+### AUR

-请参阅官方文档 [使用 Windows 一键安装器部署 AstrBot](https://astrbot.app/deploy/astrbot/windows.html) 。
+AUR deployment targets Arch Linux users who prefer installing AstrBot through the system package workflow.

-#### CasaOS 部署
-
-社区贡献的部署方式。
-
-请参阅官方文档 [CasaOS 部署](https://astrbot.app/deploy/astrbot/casaos.html) 。
-
-#### 手动部署
-
-首先安装 uv：
+Run the command below to install `astrbot-git`, then start AstrBot in your local environment.

 ```bash
-pip install uv
+yay -S astrbot-git
 ```

-通过 Git Clone 安装 AstrBot：
+**More deployment methods**

-```bash
-git clone https://github.com/AstrBotDevs/AstrBot && cd AstrBot
-uv run main.py
-```
+If you need panel-based management or deeper customization, see [BT-Panel Deployment](https://astrbot.app/deploy/astrbot/btpanel.html) for BT Panel app-store setup, [1Panel Deployment](https://astrbot.app/deploy/astrbot/1panel.html) for 1Panel app-market deployment, [CasaOS Deployment](https://astrbot.app/deploy/astrbot/casaos.html) for NAS/home-server visual deployment, and [Manual Deployment](https://astrbot.app/deploy/astrbot/cli.html) for fully custom source-based installation with `uv`.

-或者请参阅官方文档 [通过源码部署 AstrBot](https://astrbot.app/deploy/astrbot/cli.html) 。
+## Supported Messaging Platforms

-## 🌍 社区
+Connect AstrBot to your favorite chat platform.

-### QQ 群组
+| Platform | Maintainer |
+|---------|---------------|
+| QQ | Official |
+| OneBot v11 protocol implementation | Official |
+| Telegram | Official |
+| Wecom & Wecom AI Bot | Official |
+| WeChat Official Accounts | Official |
+| Feishu (Lark) | Official |
+| DingTalk | Official |
+| Slack | Official |
+| Discord | Official |
+| LINE | Official |
+| Satori | Official |
+| Misskey | Official |
+| WhatsApp (Coming Soon) | Official |
+| [Matrix](https://github.com/stevessr/astrbot_plugin_matrix_adapter) | Community |
+| [KOOK](https://github.com/wuyan1003/astrbot_plugin_kook_adapter) | Community |
+| [VoceChat](https://github.com/HikariFroya/astrbot_plugin_vocechat) | Community |

- 1 群：322154837
- 3 群：630166526
- 5 群：822130018
- 6 群：753075035
- 开发者群：975206796
+## Supported Model Services

-### Telegram 群组
+| Service | Type |
+|---------|---------------|
+| OpenAI and Compatible Services | LLM Services |
+| Anthropic | LLM Services |
+| Google Gemini | LLM Services |
+| Moonshot AI | LLM Services |
+| Zhipu AI | LLM Services |
+| DeepSeek | LLM Services |
+| Ollama (Self-hosted) | LLM Services |
+| LM Studio (Self-hosted) | LLM Services |
+| [AIHubMix](https://aihubmix.com/?aff=4bfH) | LLM Services (API Gateway, supports all models) |
+| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_astrbot&referral_code=FV7DcGowN4hB5UuXKgpE74) | LLM Services |
+| [302.AI](https://share.302.ai/rr1M3l) | LLM Services |
+| [TokenPony](https://www.tokenpony.cn/3YPyf) | LLM Services |
+| [SiliconFlow](https://docs.siliconflow.cn/cn/usercases/use-siliconcloud-in-astrbot) | LLM Services |
+| [PPIO Cloud](https://ppio.com/user/register?invited_by=AIOONE) | LLM Services |
+| ModelScope | LLM Services |
+| OneAPI | LLM Services |
+| Dify | LLMOps Platforms |
+| Alibaba Cloud Bailian Applications | LLMOps Platforms |
+| Coze | LLMOps Platforms |
+| OpenAI Whisper | Speech-to-Text Services |
+| SenseVoice | Speech-to-Text Services |
+| OpenAI TTS | Text-to-Speech Services |
+| Gemini TTS | Text-to-Speech Services |
+| GPT-Sovits-Inference | Text-to-Speech Services |
+| GPT-Sovits | Text-to-Speech Services |
+| FishAudio | Text-to-Speech Services |
+| Edge TTS | Text-to-Speech Services |
+| Alibaba Cloud Bailian TTS | Text-to-Speech Services |
+| Azure TTS | Text-to-Speech Services |
+| Minimax TTS | Text-to-Speech Services |
+| Volcano Engine TTS | Text-to-Speech Services |

-<a href="https://t.me/+hAsD2Ebl5as3NmY1"><img alt="Telegram_community" src="https://img.shields.io/badge/Telegram-AstrBot-purple?style=for-the-badge&color=76bad9"></a>
+## ❤️ Sponsors

-### Discord 群组
+<p align="center">
+  <img alt="sponsors" src="https://sponsors.astrbot.app/?v=1">
+</p>

-<a href="https://discord.gg/hAVk6tgV36"><img alt="Discord_community" src="https://img.shields.io/badge/Discord-AstrBot-purple?style=for-the-badge&color=76bad9"></a>

-## 支持的消息平台
+## ❤️ Contributing

-**官方维护**
+Issues and Pull Requests are always welcome! Feel free to submit your changes to this project :)

- QQ (官方平台 & OneBot)
- Telegram
- 企微应用 & 企微智能机器人
- 微信客服 & 微信公众号
- 飞书
- 钉钉
- Slack
- Discord
- Satori
- Misskey
- Whatsapp (将支持)
- LINE (将支持)
+### How to Contribute

-**社区维护**
+You can contribute by reviewing issues or helping with pull request reviews. Any issues or PRs are welcome to encourage community participation. Of course, these are just suggestions—you can contribute in any way you like. For adding new features, please discuss through an Issue first.

- [KOOK](https://github.com/wuyan1003/astrbot_plugin_kook_adapter)
- [VoceChat](https://github.com/HikariFroya/astrbot_plugin_vocechat)
- [Bilibili 私信](https://github.com/Hina-Chat/astrbot_plugin_bilibili_adapter)
- [wxauto](https://github.com/luosheng520qaq/wxauto-repost-onebotv11)
+### Development Environment

-## 支持的模型服务
-
-**大模型服务**
-
- OpenAI 及兼容服务
- Anthropic
- Google Gemini
- Moonshot AI
- 智谱 AI
- DeepSeek
- Ollama (本地部署)
- LM Studio (本地部署)
- [优云智算](https://www.compshare.cn/?ytag=GPU_YY-gh_astrbot&referral_code=FV7DcGowN4hB5UuXKgpE74)
- [302.AI](https://share.302.ai/rr1M3l)
- [小马算力](https://www.tokenpony.cn/3YPyf)
- [硅基流动](https://docs.siliconflow.cn/cn/usercases/use-siliconcloud-in-astrbot)
- [PPIO 派欧云](https://ppio.com/user/register?invited_by=AIOONE)
- ModelScope
- OneAPI
-
-**LLMOps 平台**
-
- Dify
- 阿里云百炼应用
- Coze
-
-**语音转文本服务**
-
- OpenAI Whisper
- SenseVoice
-
-**文本转语音服务**
-
- OpenAI TTS
- Gemini TTS
- GPT-Sovits-Inference
- GPT-Sovits
- FishAudio
- Edge TTS
- 阿里云百炼 TTS
- Azure TTS
- Minimax TTS
- 火山引擎 TTS
-
-## ❤️ 贡献
-
-欢迎任何 Issues/Pull Requests！只需要将你的更改提交到此项目 ：)
-
-### 如何贡献
-
-你可以通过查看问题或帮助审核 PR（拉取请求）来贡献。任何问题或 PR 都欢迎参与，以促进社区贡献。当然，这些只是建议，你可以以任何方式进行贡献。对于新功能的添加，请先通过 Issue 讨论。
-
-### 开发环境
-
-AstrBot 使用 `ruff` 进行代码格式化和检查。
+AstrBot uses `ruff` for code formatting and linting.

 ```bash
 git clone https://github.com/AstrBotDevs/AstrBot
@@ -205,22 +220,43 @@ pip install pre-commit
 pre-commit install
 ```

+
+## 🌍 Community
+
+### QQ Groups
+
+- Group 9: 1076659624 (New)
+- Group 10: 1078079676 (New)
+- Group 1: 322154837
+- Group 3: 630166526
+- Group 5: 822130018
+- Group 6: 753075035
+- Group 7: 743746109
+- Group 8: 1030353265
+
+- Developer Group(Chit-chat): 975206796
+- Developer Group(Formal): 1039761811
+
+### Discord Server
+
+<a href="https://discord.gg/hAVk6tgV36"><img alt="Discord_community" src="https://img.shields.io/badge/Discord-AstrBot-purple?style=for-the-badge&color=76bad9"></a>
+
 ## ❤️ Special Thanks

-特别感谢所有 Contributors 和插件开发者对 AstrBot 的贡献 ❤️
+Special thanks to all Contributors and plugin developers for their contributions to AstrBot ❤️

 <a href="https://github.com/AstrBotDevs/AstrBot/graphs/contributors">
-  <img src="https://contrib.rocks/image?repo=AstrBotDevs/AstrBot" />
+  <img src="https://contrib.rocks/image?repo=AstrBotDevs/AstrBot&max=200&columns=14" />
 </a>

-此外，本项目的诞生离不开以下开源项目的帮助：
+Additionally, the birth of this project would not have been possible without the help of the following open-source projects:

- [NapNeko/NapCatQQ](https://github.com/NapNeko/NapCatQQ) - 伟大的猫猫框架
+- [NapNeko/NapCatQQ](https://github.com/NapNeko/NapCatQQ) - The amazing cat framework

 ## ⭐ Star History

 > [!TIP]
-> 如果本项目对您的生活 / 工作产生了帮助，或者您关注本项目的未来发展，请给项目 Star，这是我们维护这个开源项目的动力 <3
+> If this project has helped you in your life or work, or if you're interested in its future development, please give the project a Star. It's the driving force behind maintaining this open-source project <3

 <div align="center">

@@ -228,6 +264,11 @@ pre-commit install

 </div>

-</details>
+<div align="center">
+
+_Companionship and capability should never be at odds. What we aim to create is a robot that can understand emotions, provide genuine companionship, and reliably accomplish tasks._

 _私は、高性能ですから!_
+
+<img src="https://files.astrbot.app/watashiwa-koseino-desukara.gif" width="100"/>
+</div>
@@ -1,182 +0,0 @@
-<p align="center">
-    
-![6e1279651f16d7fdf4727558b72bbaf1](https://github.com/user-attachments/assets/ead4c551-fc3c-48f7-a6f7-afbfdb820512)
-
-</p>
-
-<div align="center">
-
-_✨ Easy-to-use Multi-platform LLM Chatbot & Development Framework ✨_
-
-<a href="https://trendshift.io/repositories/12875" target="_blank"><img src="https://trendshift.io/api/badge/repositories/12875" alt="Soulter%2FAstrBot | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
-
-[![GitHub release (latest by date)](https://img.shields.io/github/v/release/AstrBotDevs/AstrBot)](https://github.com/AstrBotDevs/AstrBot/releases/latest)
-<img src="https://img.shields.io/badge/python-3.10+-blue.svg" alt="python">
-<a href="https://hub.docker.com/r/soulter/astrbot"><img alt="Docker pull" src="https://img.shields.io/docker/pulls/soulter/astrbot"/></a>
-<a  href="https://qm.qq.com/cgi-bin/qm/qr?k=wtbaNx7EioxeaqS9z7RQWVXPIxg2zYr7&jump_from=webapi&authKey=vlqnv/AV2DbJEvGIcxdlNSpfxVy+8vVqijgreRdnVKOaydpc+YSw4MctmEbr0k5"><img alt="Static Badge" src="https://img.shields.io/badge/QQ群-630166526-purple"></a>
-[![wakatime](https://wakatime.com/badge/user/915e5316-99c6-4563-a483-ef186cf000c9/project/018e705a-a1a7-409a-a849-3013485e6c8e.svg)](https://wakatime.com/badge/user/915e5316-99c6-4563-a483-ef186cf000c9/project/018e705a-a1a7-409a-a849-3013485e6c8e)
-![Dynamic JSON Badge](https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fapi.soulter.top%2Fastrbot%2Fstats&query=v&label=7%E6%97%A5%E6%B6%88%E6%81%AF%E4%B8%8A%E8%A1%8C%E9%87%8F&cacheSeconds=3600)
-[![codecov](https://codecov.io/gh/AstrBotDevs/AstrBot/graph/badge.svg?token=FF3P5967B8)](https://codecov.io/gh/AstrBotDevs/AstrBot)
-
-<a href="https://astrbot.app/">Documentation</a> ｜
-<a href="https://github.com/AstrBotDevs/AstrBot/issues">Issue Tracking</a>
-</div>
-
-AstrBot is a loosely coupled, asynchronous chatbot and development framework that supports multi-platform deployment, featuring an easy-to-use plugin system and comprehensive Large Language Model (LLM) integration capabilities.
-
-## ✨ Key Features
-
-1. **LLM Conversations** - Supports various LLMs including OpenAI API, Google Gemini, Llama, Deepseek, ChatGLM, etc. Enables local model deployment via Ollama/LLMTuner. Features multi-turn dialogues, personality contexts, multimodal capabilities (image understanding), and speech-to-text (Whisper).
-2. **Multi-platform Integration** - Supports QQ (OneBot), QQ Channels, WeChat (Gewechat), Feishu, and Telegram. Planned support for DingTalk, Discord, WhatsApp, and Xiaomi Smart Speakers. Includes rate limiting, whitelisting, keyword filtering, and Baidu content moderation.
-3. **Agent Capabilities** - Native support for code execution, natural language TODO lists, web search. Integrates with [Dify Platform](https://dify.ai/) for easy access to Dify assistants/knowledge bases/workflows.
-4. **Plugin System** - Optimized plugin mechanism with minimal development effort. Supports multiple installed plugins.
-5. **Web Dashboard** - Visual configuration management, plugin controls, logging, and WebChat interface for direct LLM interaction.
-6. **High Stability & Modularity** - Event bus and pipeline architecture ensures high modularization and loose coupling.
-
-> [!TIP]
-> Dashboard Demo: [https://demo.astrbot.app/](https://demo.astrbot.app/)  
-> Username: `astrbot`, Password: `astrbot` (LLM not configured for chat page)
-
-## ✨ Deployment
-
-#### Docker Deployment
-
-See docs: [Deploy with Docker](https://astrbot.app/deploy/astrbot/docker.html#docker-deployment)
-
-#### Windows Installer
-
-Requires Python (>3.10). See docs: [Windows Installer Guide](https://astrbot.app/deploy/astrbot/windows.html)
-
-#### Replit Deployment
-
-[![Run on Repl.it](https://repl.it/badge/github/AstrBotDevs/AstrBot)](https://repl.it/github/AstrBotDevs/AstrBot)
-
-#### CasaOS Deployment
-
-Community-contributed method.  
-See docs: [CasaOS Deployment](https://astrbot.app/deploy/astrbot/casaos.html)
-
-#### Manual Deployment
-
-See docs: [Source Code Deployment](https://astrbot.app/deploy/astrbot/cli.html)
-
-## ⚡ Platform Support
-
-| Platform                                                       | Status | Details             | Message Types       |
-| -------------------------------------------------------------- | ------ | ------------------- | ------------------- |
-| QQ (Official Bot)                                              | ✔      | Private/Group chats | Text, Images        |
-| QQ (OneBot)                                                    | ✔      | Private/Group chats | Text, Images, Voice |
-| WeChat (Personal)                                              | ✔      | Private/Group chats | Text, Images, Voice |
-| [Telegram](https://github.com/AstrBotDevs/AstrBot_plugin_telegram) | ✔      | Private/Group chats | Text, Images        |
-| [WeChat Work](https://github.com/AstrBotDevs/AstrBot_plugin_wecom) | ✔      | Private chats       | Text, Images, Voice |
-| Feishu                                                         | ✔      | Group chats         | Text, Images        |
-| WeChat Open Platform                                           | 🚧      | Planned             | -                   |
-| Discord                                                        | 🚧      | Planned             | -                   |
-| WhatsApp                                                       | 🚧      | Planned             | -                   |
-| Xiaomi Speakers                                                | 🚧      | Planned             | -                   |
-
-## Provider Support Status
-
-| Name                      | Support | Type                   | Notes                                                                 |
-|---------------------------|---------|------------------------|-----------------------------------------------------------------------|
-| OpenAI API                | ✔       | Text Generation        | Supports all OpenAI API-compatible services including DeepSeek, Google Gemini, GLM, Moonshot, Alibaba Cloud Bailian, Silicon Flow, xAI, etc. |
-| Claude API                | ✔       | Text Generation        |                                                                       |
-| Google Gemini API         | ✔       | Text Generation        |                                                                       |
-| Dify                      | ✔       | LLMOps                 |                                                                       |
-| DashScope (Alibaba Cloud) | ✔       | LLMOps                 |                                                                       |
-| Ollama                    | ✔       | Model Loader           | Local deployment for open-source LLMs (DeepSeek, Llama, etc.)         |
-| LM Studio                 | ✔       | Model Loader           | Local deployment for open-source LLMs (DeepSeek, Llama, etc.)         |
-| LLMTuner                  | ✔       | Model Loader           | Local loading of fine-tuned models (e.g. LoRA)                        |
-| OneAPI                    | ✔       | LLM Distribution       |                                                                       |
-| Whisper                   | ✔       | Speech-to-Text         | Supports API and local deployment                                    |
-| SenseVoice                | ✔       | Speech-to-Text         | Local deployment                                                     |
-| OpenAI TTS API            | ✔       | Text-to-Speech         |                                                                       |
-| Fishaudio                 | ✔       | Text-to-Speech         | Project involving GPT-Sovits author                                  |
-
-# 🦌 Roadmap
-
-> [!TIP]
-> Suggestions welcome via Issues <3
-
- [ ] Ensure feature parity across all platform adapters
- [ ] Optimize plugin APIs
- [ ] Add default TTS services (e.g., GPT-Sovits)
- [ ] Enhance chat features with persistent memory
- [ ] i18n Planning
-
-## ❤️ Contributions
-
-All Issues/PRs welcome! Simply submit your changes to this project :)
-
-For major features, please discuss via Issues first.
-
-## 🌟 Support
-
- Star this project!
- Support via [Afdian](https://afdian.com/a/soulter)
- WeChat support: [QR Code](https://drive.soulter.top/f/pYfA/d903f4fa49a496fda3f16d2be9e023b5.png)
-
-## ✨ Demos
-
-> [!NOTE]
-> Code executor file I/O currently tested with Napcat(QQ)/Lagrange(QQ)
-
-<div align='center'>
-
-<img src="https://github.com/user-attachments/assets/4ee688d9-467d-45c8-99d6-368f9a8a92d8" width="600">
-
-_✨ Docker-based Sandboxed Code Executor (Beta) ✨_
-
-<img src="https://github.com/user-attachments/assets/0378f407-6079-4f64-ae4c-e97ab20611d2" height=500>
-
-_✨ Multimodal Input, Web Search, Text-to-Image ✨_
-
-<img src="https://github.com/user-attachments/assets/8ec12797-e70f-460a-959e-48eca39ca2bb" height=100>
-
-_✨ Natural Language TODO Lists ✨_
-
-<img src="https://github.com/user-attachments/assets/e137a9e1-340a-4bf2-bb2b-771132780735" height=150>
-<img src="https://github.com/user-attachments/assets/480f5e82-cf6a-4955-a869-0d73137aa6e1" height=150>
-
-_✨ Plugin System Showcase ✨_
-
-<img src="https://github.com/user-attachments/assets/592a8630-14c7-4e06-b496-9c0386e4f36c" width=600>
-
-_✨ Web Dashboard ✨_
-
-![webchat](https://drive.soulter.top/f/vlsA/ezgif-5-fb044b2542.gif)
-
-_✨ Built-in Web Chat Interface ✨_
-
-</div>
-
-## ⭐ Star History
-
-> [!TIP] 
-> If this project helps you, please give it a star <3
-
-<div align="center">
-    
-[![Star History Chart](https://api.star-history.com/svg?repos=AstrBotDevs/AstrBot&type=Date)](https://star-history.com/#AstrBotDevs/AstrBot&Date)
-
-</div>
-
-## Disclaimer
-
-1. Licensed under `AGPL-v3`.
-2. WeChat integration uses [Gewechat](https://github.com/Devo919/Gewechat). Use at your own risk with non-critical accounts.
-3. Users must comply with local laws and regulations.
-
-<!-- ## ✨ ATRI [Beta]
-
-Available as plugin: [astrbot_plugin_atri](https://github.com/AstrBotDevs/AstrBot_plugin_atri)
-
-1. Qwen1.5-7B-Chat Lora model fine-tuned with ATRI character data
-2. Long-term memory
-3. Meme understanding & responses
-4. TTS integration
-    -->
-
-
-_私は、高性能ですから!_
-
@@ -0,0 +1,262 @@
+![AstrBot-Logo-Simplified](https://github.com/user-attachments/assets/ffd99b6b-3272-4682-beaa-6fe74250f7d9)
+
+<div align="center">
+
+<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_zh.md">简体中文</a> ｜
+<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README.md">English</a> ｜
+<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_zh-TW.md">繁體中文</a> ｜
+<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_ja.md">日本語</a> ｜
+<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_ru.md">Русский</a>
+
+<br>
+
+<div>
+<a href="https://trendshift.io/repositories/12875" target="_blank"><img src="https://trendshift.io/api/badge/repositories/12875" alt="Soulter%2FAstrBot | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
+<a href="https://hellogithub.com/repository/AstrBotDevs/AstrBot" target="_blank"><img src="https://api.hellogithub.com/v1/widgets/recommend.svg?rid=d127d50cd5e54c5382328acc3bb25483&claim_uid=ZO9by7qCXgSd6Lp&t=2" alt="Featured｜HelloGitHub" style="width: 250px; height: 54px;" width="250" height="54" /></a>
+</div>
+
+<br>
+
+<div>
+<img src="https://img.shields.io/github/v/release/AstrBotDevs/AstrBot?color=76bad9" href="https://github.com/AstrBotDevs/AstrBot/releases/latest">
+<img src="https://img.shields.io/badge/python-3.10+-blue.svg" alt="python">
+<img src="https://deepwiki.com/badge.svg" href="https://deepwiki.com/AstrBotDevs/AstrBot">
+<a href="https://zread.ai/AstrBotDevs/AstrBot" target="_blank"><img src="https://img.shields.io/badge/Ask_Zread-_.svg?style=flat&color=00b0aa&labelColor=000000&logo=data%3Aimage%2Fsvg%2Bxml%3Bbase64%2CPHN2ZyB3aWR0aD0iMTYiIGhlaWdodD0iMTYiIHZpZXdCb3g9IjAgMCAxNiAxNiIgZmlsbD0ibm9uZSIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KPHBhdGggZD0iTTQuOTYxNTYgMS42MDAxSDIuMjQxNTZDMS44ODgxIDEuNjAwMSAxLjYwMTU2IDEuODg2NjQgMS42MDE1NiAyLjI0MDFWNC45NjAxQzEuNjAxNTYgNS4zMTM1NiAxLjg4ODEgNS42MDAxIDIuMjQxNTYgNS42MDAxSDQuOTYxNTZDNS4zMTUwMiA1LjYwMDEgNS42MDE1NiA1LjMxMzU2IDUuNjAxNTYgNC45NjAxVjIuMjQwMUM1LjYwMTU2IDEuODg2NjQgNS4zMTUwMiAxLjYwMDEgNC45NjE1NiAxLjYwMDFZIiBmaWxsPSIjZmZmIi8%2BCjxwYXRoIGQ9Ik00Ljk2MTU2IDEwLjM5OTlIMi4yNDE1NkMxLjg4ODEgMTAuMzk5OSAxLjYwMTU2IDEwLjY4NjQgMS42MDE1NiAxMS4wMzk5VjEzLjc1OTlDMS42MDE1NiAxNC4xMTM0IDEuODg4MSAxNC4zOTk5IDIuMjQxNTYgMTQuMzk5OUg0Ljk2MTU2QzUuMzE1MDIgMTQuMzk5OSA1LjYwMTU2IDE0LjExMzQgNS42MDE1NiAxMy43NTk5VjExLjAzOTlDNS42MDE1NiAxMC42ODY0IDUuMzE1MDIgMTAuMzk5OSA0Ljk2MTU2IDEwLjM5OTlaIiBmaWxsPSIjZmZmIi8%2BCjxwYXRoIGQ9Ik0xMy43NTg0IDEuNjAwMUgxMS4wMzg0QzEwLjY4NSAxLjYwMDEgMTAuMzk4NCAxLjg4NjY0IDEwLjM5ODQgMi4yNDAxVjQuOTYwMUMxMC4zOTg0IDUuMzEzNTYgMTAuNjg1IDUuNjAwMSAxMS4wMzg0IDUuNjAwMUgxMy43NTg0QzE0LjExMTkgNS42MDAxIDE0LjM5ODQgNS4zMTM1NiAxNC4zOTg0IDQuOTYwMVYyLjI0MDFDMTQuMzk4NCAxLjg4NjY0IDE0LjExMTkgMS42MDAxIDEzLjc1ODQgMS42MDAxWiIgZmlsbD0iI2ZmZiIvPgo8cGF0aCBkPSJNNCAxMkwxMiA0TDQgMTJaIiBmaWxsPSIjZmZmIi8%2BCjxwYXRoIGQ9Ik00IDEyTDEyIDQiIHN0cm9rZT0iI2ZmZiIgc3Ryb2tlLXdpZHRoPSIxLjUiIHN0cm9rZS1saW5lY2FwPSJyb3VuZCIvPgo8L3N2Zz4K&logoColor=ffffff" alt="zread"/></a>
+<a href="https://hub.docker.com/r/soulter/astrbot"><img alt="Docker pull" src="https://img.shields.io/docker/pulls/soulter/astrbot.svg?color=76bad9"/></a>
+<img src="https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fapi.soulter.top%2Fastrbot%2Fplugin-num&query=%24.result&suffix=%20&label=Marketplace&cacheSeconds=3600">
+<img src="https://gitcode.com/Soulter/AstrBot/star/badge.svg" href="https://gitcode.com/Soulter/AstrBot">
+</div>
+
+<br>
+
+<a href="https://astrbot.app/">Documentation</a> ｜
+<a href="https://blog.astrbot.app/">Blog</a> ｜
+<a href="https://astrbot.featurebase.app/roadmap">Feuille de route</a> ｜
+<a href="https://github.com/AstrBotDevs/AstrBot/issues">Signaler un problème</a>
+<a href="mailto:community@astrbot.app">Email Support</a>
+</div>
+
+AstrBot est une plateforme de chatbot Agent tout-en-un open source qui s'intègre aux principales applications de messagerie instantanée. Elle fournit une infrastructure d'IA conversationnelle fiable et évolutive pour les particuliers, les développeurs et les équipes. Que vous construisiez un compagnon IA personnel, un service client intelligent, un assistant d'automatisation ou une base de connaissances d'entreprise, AstrBot vous permet de créer rapidement des applications d'IA prêtes pour la production dans les flux de travail de votre plateforme de messagerie.
+
+![521771166-00782c4c-4437-4d97-aabc-605e3738da5c (1)](https://github.com/user-attachments/assets/61e7b505-f7db-41aa-a75f-4ef8f079b8ba)
+
+## Fonctionnalités principales
+
+1. 💯 Gratuit & Open Source.
+2. ✨ Dialogue avec de grands modèles d'IA, multimodal, Agent, MCP, Skills, Base de connaissances, Paramétrage de personnalité, compression automatique des dialogues.
+3. 🤖 Prise en charge de l'accès aux plateformes d'Agents telles que Dify, Alibaba Cloud Bailian, Coze, etc.
+4. 🌐 Multiplateforme : supporte QQ, WeChat Enterprise, Feishu, DingTalk, Comptes officiels WeChat, Telegram, Slack et [plus encore](#plateformes-de-messagerie-prises-en-charge).
+5. 📦 Extension par plugins, avec plus de 1000 plugins déjà disponibles pour une installation en un clic.
+6. 🛡️  Environnement isolé [Agent Sandbox](https://docs.astrbot.app/use/astrbot-agent-sandbox.html) : exécution sécurisée de code, appels Shell et réutilisation des ressources au niveau de la session.
+7. 💻 Support WebUI.
+8. 🌈 Support Web ChatUI, avec sandbox d'agent intégrée, recherche web, etc.
+9. 🌐 Support de l'internationalisation (i18n).
+
+<br>
+
+<table align="center">
+  <tr align="center">
+    <th>💙 Jeux de rôle & Accompagnement émotionnel</th>
+    <th>✨ Agent proactif</th>
+    <th>🚀 Capacités agentiques générales</th>
+    <th>🧩 1000+ Plugins de communauté</th>
+  </tr>
+  <tr>
+    <td align="center"><p align="center"><img width="984" height="1746" alt="99b587c5d35eea09d84f33e6cf6cfd4f" src="https://github.com/user-attachments/assets/89196061-3290-458d-b51f-afa178049f84" /></p></td>
+    <td align="center"><p align="center"><img width="976" height="1612" alt="c449acd838c41d0915cc08a3824025b1" src="https://github.com/user-attachments/assets/f75368b4-e022-41dc-a9e0-131c3e73e32e" /></p></td>
+    <td align="center"><p align="center"><img width="974" height="1732" alt="image" src="https://github.com/user-attachments/assets/e22a3968-87d7-4708-a7cd-e7f198c7c32e" /></p></td>
+    <td align="center"><p align="center"><img width="976" height="1734" alt="image" src="https://github.com/user-attachments/assets/0952b395-6b4a-432a-8a50-c294b7f89750" /></p></td>
+  </tr>
+</table>
+
+## Démarrage rapide
+
+### Déploiement en un clic
+
+Pour les utilisateurs qui veulent découvrir AstrBot rapidement, qui sont familiers avec la ligne de commande et peuvent installer eux-mêmes l'environnement `uv`, nous recommandons la méthode de déploiement en un clic avec `uv` ⚡️ :
+
+```bash
+uv tool install astrbot
+astrbot init # Exécutez cette commande uniquement la première fois pour initialiser l'environnement
+astrbot
+```
+
+> [uv](https://docs.astral.sh/uv/) doit être installé.
+
+> [!NOTE]
+> Pour les utilisateurs macOS : en raison des vérifications de sécurité de macOS, la première exécution de la commande `astrbot` peut prendre plus de temps (environ 10-20s).
+
+Mettre à jour `astrbot` :
+
+```bash
+uv tool upgrade astrbot
+```
+
+### Déploiement Docker
+
+Pour les utilisateurs familiers avec les conteneurs et qui souhaitent une méthode plus stable et adaptée à la production, nous recommandons de déployer AstrBot avec Docker / Docker Compose.
+
+Veuillez consulter la documentation officielle [Déployer AstrBot avec Docker](https://astrbot.app/deploy/astrbot/docker.html#%E4%BD%BF%E7%94%A8-docker-%E9%83%A8%E7%BD%B2-astrbot).
+
+### Déployer sur RainYun
+
+Pour les utilisateurs qui souhaitent déployer AstrBot en un clic sans gérer le serveur eux-mêmes, nous recommandons le service de déploiement cloud en un clic de RainYun ☁️ :
+
+[![Deploy on RainYun](https://rainyun-apps.cn-nb1.rains3.com/materials/deploy-on-rainyun-en.svg)](https://app.rainyun.com/apps/rca/store/5994?ref=NjU1ODg0)
+
+### Déploiement de l'application de bureau
+
+Pour les utilisateurs qui veulent utiliser AstrBot sur desktop et passer principalement par ChatUI, nous recommandons AstrBot App.
+
+Accédez à [AstrBot-desktop](https://github.com/AstrBotDevs/AstrBot-desktop) pour télécharger et installer l'application ; cette méthode est conçue pour un usage desktop et n'est pas recommandée pour les scénarios serveur.
+
+### Déploiement avec le lanceur
+
+Également sur desktop, pour les utilisateurs qui souhaitent un déploiement rapide avec isolation d'environnement et multi-instances, nous recommandons AstrBot Launcher.
+
+Accédez à [AstrBot Launcher](https://github.com/Raven95676/astrbot-launcher) pour télécharger et installer.
+
+### Déployer sur Replit
+
+Le déploiement sur Replit est maintenu par la communauté et convient aux démonstrations en ligne et aux essais légers.
+
+[![Run on Repl.it](https://repl.it/badge/github/AstrBotDevs/AstrBot)](https://repl.it/github/AstrBotDevs/AstrBot)
+
+### AUR
+
+Le mode AUR s'adresse aux utilisateurs Arch Linux qui préfèrent installer AstrBot via le gestionnaire de paquets système.
+
+Exécutez la commande ci-dessous pour installer `astrbot-git`, puis lancez AstrBot localement.
+
+```bash
+yay -S astrbot-git
+```
+
+**Autres méthodes de déploiement**
+
+Si vous avez besoin d'une gestion par panneau ou d'une personnalisation plus poussée, consultez [Déploiement BT-Panel](https://astrbot.app/deploy/astrbot/btpanel.html) pour une installation via BT Panel, [Déploiement 1Panel](https://astrbot.app/deploy/astrbot/1panel.html) pour le marketplace 1Panel, [Déploiement CasaOS](https://astrbot.app/deploy/astrbot/casaos.html) pour un déploiement visuel sur NAS/serveur domestique, et [Déploiement manuel](https://astrbot.app/deploy/astrbot/cli.html) pour une installation complète depuis les sources avec `uv`.
+
+## Plateformes de messagerie prises en charge
+
+Connectez AstrBot à vos plateformes de chat préférées.
+
+| Plateforme | Maintenance |
+|---------|---------------|
+| QQ | Officielle |
+| Implémentation du protocole OneBot v11 | Officielle |
+| Telegram | Officielle |
+| Application WeChat Work & Bot intelligent WeChat Work | Officielle |
+| Service client WeChat & Comptes officiels WeChat | Officielle |
+| Feishu (Lark) | Officielle |
+| DingTalk | Officielle |
+| Slack | Officielle |
+| Discord | Officielle |
+| LINE | Officielle |
+| Satori | Officielle |
+| Misskey | Officielle |
+| WhatsApp (Bientôt disponible) | Officielle |
+| [Matrix](https://github.com/stevessr/astrbot_plugin_matrix_adapter) | Communauté |
+| [KOOK](https://github.com/wuyan1003/astrbot_plugin_kook_adapter) | Communauté |
+| [VoceChat](https://github.com/HikariFroya/astrbot_plugin_vocechat) | Communauté |
+
+## Services de modèles pris en charge
+
+| Service | Type |
+|---------|---------------|
+| OpenAI et services compatibles | Services LLM |
+| Anthropic | Services LLM |
+| Google Gemini | Services LLM |
+| Moonshot AI | Services LLM |
+| Zhipu AI | Services LLM |
+| DeepSeek | Services LLM |
+| Ollama (Auto-hébergé) | Services LLM |
+| LM Studio (Auto-hébergé) | Services LLM |
+| [AIHubMix](https://aihubmix.com/?aff=4bfH) | Services LLM (Passerelle API, prend en charge tous les modèles) |
+| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_astrbot&referral_code=FV7DcGowN4hB5UuXKgpE74) | Services LLM |
+| [302.AI](https://share.302.ai/rr1M3l) | Services LLM |
+| [TokenPony](https://www.tokenpony.cn/3YPyf) | Services LLM |
+| [SiliconFlow](https://docs.siliconflow.cn/cn/usercases/use-siliconcloud-in-astrbot) | Services LLM |
+| [PPIO Cloud](https://ppio.com/user/register?invited_by=AIOONE) | Services LLM |
+| ModelScope | Services LLM |
+| OneAPI | Services LLM |
+| Dify | Plateformes LLMOps |
+| Applications Alibaba Cloud Bailian | Plateformes LLMOps |
+| Coze | Plateformes LLMOps |
+| OpenAI Whisper | Services de reconnaissance vocale |
+| SenseVoice | Services de reconnaissance vocale |
+| OpenAI TTS | Services de synthèse vocale |
+| Gemini TTS | Services de synthèse vocale |
+| GPT-Sovits-Inference | Services de synthèse vocale |
+| GPT-Sovits | Services de synthèse vocale |
+| FishAudio | Services de synthèse vocale |
+| Edge TTS | Services de synthèse vocale |
+| Alibaba Cloud Bailian TTS | Services de synthèse vocale |
+| Azure TTS | Services de synthèse vocale |
+| Minimax TTS | Services de synthèse vocale |
+| Volcano Engine TTS | Services de synthèse vocale |
+
+## ❤️ Contribuer
+
+Les Issues et Pull Requests sont toujours les bienvenues ! N'hésitez pas à soumettre vos modifications à ce projet :)
+
+### Comment contribuer
+
+Vous pouvez contribuer en examinant les issues ou en aidant à la revue des pull requests. Toutes les issues ou PRs sont les bienvenues pour encourager la participation de la communauté. Bien sûr, ce ne sont que des suggestions - vous pouvez contribuer de la manière que vous souhaitez. Pour l'ajout de nouvelles fonctionnalités, veuillez d'abord en discuter via une Issue.
+
+### Environnement de développement
+
+AstrBot utilise `ruff` pour le formatage et le linting du code.
+
+```bash
+git clone https://github.com/AstrBotDevs/AstrBot
+pip install pre-commit
+pre-commit install
+```
+
+## 🌍 Communauté
+
+### Groupes QQ
+
+- Groupe 1 : 322154837
+- Groupe 3 : 630166526
+- Groupe 5 : 822130018
+- Groupe 6 : 753075035
+- Groupe développeurs : 975206796
+- Groupe développeurs (officiel) : 1039761811
+
+### Serveur Discord
+
+<a href="https://discord.gg/hAVk6tgV36"><img alt="Discord_community" src="https://img.shields.io/badge/Discord-AstrBot-purple?style=for-the-badge&color=76bad9"></a>
+
+## ❤️ Remerciements spéciaux
+
+Un grand merci à tous les contributeurs et développeurs de plugins pour leurs contributions à AstrBot ❤️
+
+<a href="https://github.com/AstrBotDevs/AstrBot/graphs/contributors">
+  <img src="https://contrib.rocks/image?repo=AstrBotDevs/AstrBot&max=200&columns=14" />
+</a>
+
+De plus, la naissance de ce projet n'aurait pas été possible sans l'aide des projets open source suivants :
+
+- [NapNeko/NapCatQQ](https://github.com/NapNeko/NapCatQQ) - L'incroyable framework chat
+
+## ⭐ Historique des étoiles
+
+> [!TIP]
+> Si ce projet vous a aidé dans votre vie ou votre travail, ou si vous êtes intéressé par son développement futur, veuillez donner une étoile au projet. C'est la force motrice derrière la maintenance de ce projet open source <3
+
+<div align="center">
+
+[![Star History Chart](https://api.star-history.com/svg?repos=astrbotdevs/astrbot&type=Date)](https://star-history.com/#astrbotdevs/astrbot&Date)
+
+</div>
+
+<div align="center">
+
+_La compagnie et la capacité ne devraient jamais être des opposés. Nous souhaitons créer un robot capable à la fois de comprendre les émotions, d'offrir de la présence, et d'accomplir des tâches de manière fiable._
+
+_私は、高性能ですから!_
+
+<img src="https://files.astrbot.app/watashiwa-koseino-desukara.gif" width="100"/>
+
+</div>
@@ -1,167 +1,263 @@
-<p align="center">
-
-![6e1279651f16d7fdf4727558b72bbaf1](https://github.com/user-attachments/assets/ead4c551-fc3c-48f7-a6f7-afbfdb820512)
-
-</p>
+![AstrBot-Logo-Simplified](https://github.com/user-attachments/assets/ffd99b6b-3272-4682-beaa-6fe74250f7d9)

 <div align="center">

-_✨ 簡単に使えるマルチプラットフォーム LLM チャットボットおよび開発フレームワーク ✨_
+<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_zh.md">简体中文</a> ｜
+<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README.md">English</a> ｜
+<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_zh-TW.md">繁體中文</a> ｜
+<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_fr.md">Français</a> ｜
+<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_ru.md">Русский</a>

+<br>
+
+<div>
 <a href="https://trendshift.io/repositories/12875" target="_blank"><img src="https://trendshift.io/api/badge/repositories/12875" alt="Soulter%2FAstrBot | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
-
-[![GitHub release (latest by date)](https://img.shields.io/github/v/release/AstrBotDevs/AstrBot)](https://github.com/AstrBotDevs/AstrBot/releases/latest)
-<img src="https://img.shields.io/badge/python-3.10+-blue.svg" alt="python">
-<a href="https://hub.docker.com/r/soulter/astrbot"><img alt="Docker pull" src="https://img.shields.io/docker/pulls/soulter/astrbot.svg"/></a>
-<img alt="Static Badge" src="https://img.shields.io/badge/QQ群-630166526-purple">
-[![wakatime](https://wakatime.com/badge/user/915e5316-99c6-4563-a483-ef186cf000c9/project/018e705a-a1a7-409a-a849-3013485e6c8e.svg)](https://wakatime.com/badge/user/915e5316-99c6-4563-a483-ef186cf000c9/project/018e705a-a1a7-409a-a849-3013485e6c8e)
-![Dynamic JSON Badge](https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fapi.soulter.top%2Fastrbot%2Fstats&query=v&label=7%E6%97%A5%E6%B6%88%E6%81%AF%E4%B8%8A%E8%A1%8C%E9%87%8F&cacheSeconds=3600)
-[![codecov](https://codecov.io/gh/AstrBotDevs/AstrBot/graph/badge.svg?token=FF3P5967B8)](https://codecov.io/gh/AstrBotDevs/AstrBot)
-
-<a href="https://astrbot.app/">ドキュメントを見る</a> ｜
-<a href="https://github.com/AstrBotDevs/AstrBot/issues">問題を報告する</a>
+<a href="https://hellogithub.com/repository/AstrBotDevs/AstrBot" target="_blank"><img src="https://api.hellogithub.com/v1/widgets/recommend.svg?rid=d127d50cd5e54c5382328acc3bb25483&claim_uid=ZO9by7qCXgSd6Lp&t=2" alt="Featured｜HelloGitHub" style="width: 250px; height: 54px;" width="250" height="54" /></a>
 </div>

-AstrBot は、疎結合、非同期、複数のメッセージプラットフォームに対応したデプロイ、使いやすいプラグインシステム、および包括的な大規模言語モデル（LLM）接続機能を備えたチャットボットおよび開発フレームワークです。
+<br>

-## ✨ 主な機能
+<div>
+<img src="https://img.shields.io/github/v/release/AstrBotDevs/AstrBot?color=76bad9" href="https://github.com/AstrBotDevs/AstrBot/releases/latest">
+<img src="https://img.shields.io/badge/python-3.10+-blue.svg" alt="python">
+<img src="https://deepwiki.com/badge.svg" href="https://deepwiki.com/AstrBotDevs/AstrBot">
+<a href="https://zread.ai/AstrBotDevs/AstrBot" target="_blank"><img src="https://img.shields.io/badge/Ask_Zread-_.svg?style=flat&color=00b0aa&labelColor=000000&logo=data%3Aimage%2Fsvg%2Bxml%3Bbase64%2CPHN2ZyB3aWR0aD0iMTYiIGhlaWdodD0iMTYiIHZpZXdCb3g9IjAgMCAxNiAxNiIgZmlsbD0ibm9uZSIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KPHBhdGggZD0iTTQuOTYxNTYgMS42MDAxSDIuMjQxNTZDMS44ODgxIDEuNjAwMSAxLjYwMTU2IDEuODg2NjQgMS42MDE1NiAyLjI0MDFWNC45NjAxQzEuNjAxNTYgNS4zMTM1NiAxLjg4ODEgNS42MDAxIDIuMjQxNTYgNS42MDAxSDQuOTYxNTZDNS4zMTUwMiA1LjYwMDEgNS42MDE1NiA1LjMxMzU2IDUuNjAxNTYgNC45NjAxVjIuMjQwMUM1LjYwMTU2IDEuODg2NjQgNS4zMTUwMiAxLjYwMDEgNC45NjE1NiAxLjYwMDFZIiBmaWxsPSIjZmZmIi8%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%2BCjxwYXRoIGQ9Ik00IDEyTDEyIDRMNCAxMlpFIiBmaWxsPSIjZmZmIi8%2BCjxwYXRoIGQ9Ik00IDEyTDEyIDQiIHN0cm9rZT0iI2ZmZiIgc3Ryb2tlLXdpZHRoPSIxLjUiIHN0cm9rZS1saW5lY2FwPSJyb3VuZCIvPgo8L3N2Zz4K&logoColor=ffffff" alt="zread"/></a>
+<a href="https://hub.docker.com/r/soulter/astrbot"><img alt="Docker pull" src="https://img.shields.io/docker/pulls/soulter/astrbot.svg?color=76bad9"/></a>
+<img src="https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fapi.soulter.top%2Fastrbot%2Fplugin-num&query=%24.result&suffix=%20&label=%E3%83%97%E3%83%A9%E3%82%B0%E3%82%A4%E3%83%B3%E3%83%9E%E3%83%BC%E3%82%B1%E3%83%83%E3%83%88&cacheSeconds=3600">
+<img src="https://gitcode.com/Soulter/AstrBot/star/badge.svg" href="https://gitcode.com/Soulter/AstrBot">
+</div>

-1. **大規模言語モデルの対話**。OpenAI API、Google Gemini、Llama、Deepseek、ChatGLM など、さまざまな大規模言語モデルをサポートし、Ollama、LLMTuner を介してローカルにデプロイされた大規模モデルをサポートします。多輪対話、人格シナリオ、多モーダル機能を備え、画像理解、音声からテキストへの変換（Whisper）をサポートします。
-2. **複数のメッセージプラットフォームの接続**。QQ（OneBot）、QQ チャンネル、Feishu、Telegram への接続をサポートします。今後、DingTalk、Discord、WhatsApp、Xiaoai 音響をサポートする予定です。レート制限、ホワイトリスト、キーワードフィルタリング、Baidu コンテンツ監査をサポートします。
-3. **エージェント**。一部のエージェント機能をネイティブにサポートし、コードエグゼキューター、自然言語タスク、ウェブ検索などを提供します。[Dify プラットフォーム](https://dify.ai/)と連携し、Dify スマートアシスタント、ナレッジベース、Dify ワークフローを簡単に接続できます。
-4. **プラグインの拡張**。深く最適化されたプラグインメカニズムを備え、[プラグインの開発](https://astrbot.app/dev/plugin.html)をサポートし、機能を拡張できます。複数のプラグインのインストールをサポートします。
-5. **ビジュアル管理パネル**。設定の視覚的な変更、プラグイン管理、ログの表示などをサポートし、設定の難易度を低減します。WebChat を統合し、パネル上で大規模モデルと対話できます。
-6. **高い安定性と高いモジュール性**。イベントバスとパイプラインに基づくアーキテクチャ設計により、高度にモジュール化され、低結合です。
+<br>

-> [!TIP]
-> 管理パネルのオンラインデモを体験する: [https://demo.astrbot.app/](https://demo.astrbot.app/)
->
-> ユーザー名: `astrbot`, パスワード: `astrbot`。LLM が設定されていないため、チャットページで大規模モデルを使用することはできません。（デモのログインパスワードを変更しないでください 😭）
+<a href="https://astrbot.app/">ドキュメント</a> ｜
+<a href="https://blog.astrbot.app/">Blog</a> ｜
+<a href="https://astrbot.featurebase.app/roadmap">ロードマップ</a> ｜
+<a href="https://github.com/AstrBotDevs/AstrBot/issues">Issue</a>
+<a href="mailto:community@astrbot.app">Email Support</a>
+</div>

-## ✨ 使用方法
+AstrBot は、主要なインスタントメッセージングアプリと統合できるオープンソースのオールインワン Agent チャットボットプラットフォームです。個人、開発者、チームに信頼性が高くスケーラブルな会話型 AI インフラストラクチャを提供します。パーソナル AI コンパニオン、インテリジェントカスタマーサービス、オートメーションアシスタント、エンタープライズナレッジベースなど、AstrBot を使用すると、IM プラットフォームのワークフロー内で本番環境対応の AI アプリケーションを迅速に構築できます。

-#### Docker デプロイ
+![screenshot_1 5x_postspark_2026-02-27_22-37-45](https://github.com/user-attachments/assets/f17cdb90-52d7-4773-be2e-ff64b566af6b)

-公式ドキュメント [Docker を使用して AstrBot をデプロイする](https://astrbot.app/deploy/astrbot/docker.html#%E4%BD%BF%E7%94%A8-docker-%E9%83%A8%E7%BD%B2-astrbot) を参照してください。
+## 主な機能

-#### Windows ワンクリックインストーラーのデプロイ
+1. 💯 無料 & オープンソース。
+2. ✨ AI大規模言語モデル対話、マルチモーダル、Agent、MCP、Skills、ナレッジベース、ペルソナ設定、対話の自動圧縮。
+3. 🤖 Dify、Alibaba Cloud Bailian（百煉）、Coze などのAgentプラットフォームへの接続をサポート。
+4. 🌐 マルチプラットフォーム：QQ、企業微信（WeCom）、飛書（Lark）、釘釘（DingTalk）、WeChat公式アカウント、Telegram、Slack、[その他](#サポートされているメッセージプラットフォーム)に対応。
+5. 📦 プラグイン拡張：1000を超える既存プラグインをワンクリックでインストール可能。
+6. 🛡️  隔離環境[Agent Sandbox](https://docs.astrbot.app/use/astrbot-agent-sandbox.html)：コードの安全な実行、Shell呼び出し、セッションレベルのリソース再利用。
+7. 💻 WebUI 対応。
+8. 🌈 Web ChatUI 対応：ChatUI内にAgent Sandboxやウェブ検索などを内蔵。
+9. 🌐 多言語対応（i18n）。

-コンピュータに Python（>3.10）がインストールされている必要があります。公式ドキュメント [Windows ワンクリックインストーラーを使用して AstrBot をデプロイする](https://astrbot.app/deploy/astrbot/windows.html) を参照してください。
+<br>

-#### Replit デプロイ
+<table align="center">
+  <tr align="center">
+    <th>💙 ロールプレイ & 感情的な対話</th>
+    <th>✨ プロアクティブ・エージェント (Proactive Agent)</th>
+    <th>🚀 汎用 エージェント的能力</th>
+    <th>🧩 1000+ コミュニティプラグイン</th>
+  </tr>
+  <tr>
+    <td align="center"><p align="center"><img width="984" height="1746" alt="99b587c5d35eea09d84f33e6cf6cfd4f" src="https://github.com/user-attachments/assets/89196061-3290-458d-b51f-afa178049f84" /></p></td>
+    <td align="center"><p align="center"><img width="976" height="1612" alt="c449acd838c41d0915cc08a3824025b1" src="https://github.com/user-attachments/assets/f75368b4-e022-41dc-a9e0-131c3e73e32e" /></p></td>
+    <td align="center"><p align="center"><img width="974" height="1732" alt="image" src="https://github.com/user-attachments/assets/e22a3968-87d7-4708-a7cd-e7f198c7c32e" /></p></td>
+    <td align="center"><p align="center"><img width="976" height="1734" alt="image" src="https://github.com/user-attachments/assets/0952b395-6b4a-432a-8a50-c294b7f89750" /></p></td>
+  </tr>
+</table>
+
+## クイックスタート
+
+### ワンクリックデプロイ
+
+AstrBot を素早く試したいユーザーで、コマンドラインに慣れており `uv` 環境を自分でインストールできる場合は、`uv` のワンクリックデプロイをおすすめします ⚡️:
+
+```bash
+uv tool install astrbot
+astrbot init # 初回のみ実行して環境を初期化します
+astrbot
+```
+
+> [uv](https://docs.astral.sh/uv/) のインストールが必要です。
+
+> [!NOTE]
+> macOS ユーザーの場合：macOS のセキュリティチェックにより、`astrbot` コマンドの初回実行に時間がかかる場合があります（約 10〜20 秒）。
+
+`astrbot` の更新：
+
+```bash
+uv tool upgrade astrbot
+```
+
+### Docker デプロイ
+
+コンテナ運用に慣れており、より安定した本番向けのデプロイ方法を求めるユーザーには、Docker / Docker Compose での AstrBot デプロイをおすすめします。
+
+公式ドキュメント [Docker を使用した AstrBot のデプロイ](https://astrbot.app/deploy/astrbot/docker.html#%E4%BD%BF%E7%94%A8-docker-%E9%83%A8%E7%BD%B2-astrbot) をご参照ください。
+
+### 雨云でのデプロイ
+
+AstrBot をワンクリックでデプロイしたく、サーバーを自分で管理したくないユーザーには、雨云のワンクリッククラウドデプロイサービスをおすすめします ☁️:
+
+[![Deploy on RainYun](https://rainyun-apps.cn-nb1.rains3.com/materials/deploy-on-rainyun-en.svg)](https://app.rainyun.com/apps/rca/store/5994?ref=NjU1ODg0)
+
+### デスクトップアプリのデプロイ
+
+デスクトップで AstrBot を使い、主に ChatUI を入口として利用するユーザーには、AstrBot App をおすすめします。
+
+[AstrBot-desktop](https://github.com/AstrBotDevs/AstrBot-desktop) からダウンロードしてインストールしてください。この方式はデスクトップ向けであり、サーバー用途には推奨されません。
+
+### ランチャーのデプロイ
+
+同じくデスクトップで、素早くデプロイしつつ環境を分離して多重起動したいユーザーには、AstrBot Launcher をおすすめします。
+
+[AstrBot Launcher](https://github.com/Raven95676/astrbot-launcher) からダウンロードしてインストールしてください。
+
+### Replit でのデプロイ
+
+Replit デプロイはコミュニティ提供の方式で、オンラインデモや軽量な試用に向いています。

 [![Run on Repl.it](https://repl.it/badge/github/AstrBotDevs/AstrBot)](https://repl.it/github/AstrBotDevs/AstrBot)

-#### CasaOS デプロイ
+### AUR

-コミュニティが提供するデプロイ方法です。
+AUR 方式は Arch Linux ユーザー向けで、システムのパッケージ運用に合わせて AstrBot を導入したい場合に適しています。

-公式ドキュメント [ソースコードを使用して AstrBot をデプロイする](https://astrbot.app/deploy/astrbot/casaos.html) を参照してください。
+次のコマンドで `astrbot-git` をインストールし、ローカル環境で AstrBot を起動してください。

-#### 手動デプロイ
+```bash
+yay -S astrbot-git
+```

-公式ドキュメント [ソースコードを使用して AstrBot をデプロイする](https://astrbot.app/deploy/astrbot/cli.html) を参照してください。
+**その他のデプロイ方法**

-## ⚡ メッセージプラットフォームのサポート状況
+パネル操作での導入やより高度なカスタマイズが必要な場合は、[宝塔パネルデプロイ](https://astrbot.app/deploy/astrbot/btpanel.html)（BT Panel 経由の導入）、[1Panel デプロイ](https://astrbot.app/deploy/astrbot/1panel.html)（1Panel アプリマーケット経由）、[CasaOS デプロイ](https://astrbot.app/deploy/astrbot/casaos.html)（NAS / ホームサーバー向け可視化導入）、[手動デプロイ](https://astrbot.app/deploy/astrbot/cli.html)（`uv` とソースベースのフルカスタム導入）を参照してください。

-| プラットフォーム    | サポート状況 | 詳細 | メッセージタイプ |
-| -------- | ------- | ------- | ------ |
-| QQ(公式ロボットインターフェース) | ✔    | プライベートチャット、グループチャット、QQ チャンネルプライベートチャット、グループチャット | テキスト、画像 |
-| QQ(OneBot)      | ✔    | プライベートチャット、グループチャット | テキスト、画像、音声 |
-| WeChat(個人アカウント)    | ✔    | WeChat 個人アカウントのプライベートチャット、グループチャット | テキスト、画像、音声 |
-| [Telegram](https://github.com/Soulter/astrbot_plugin_telegram)   | ✔    | プライベートチャット、グループチャット | テキスト、画像 |
-| [WeChat(企業 WeChat)](https://github.com/Soulter/astrbot_plugin_wecom)    | ✔    | プライベートチャット | テキスト、画像、音声 |
-| Feishu   | ✔    | グループチャット | テキスト、画像 |
-| WeChat 対話オープンプラットフォーム | 🚧    | 計画中 | - |
-| Discord   | 🚧    | 計画中 | - |
-| WhatsApp   | 🚧    | 計画中 | - |
-| Xiaoai 音響   | 🚧    | 計画中 | - |
+## サポートされているメッセージプラットフォーム

-# 🦌 今後のロードマップ
+AstrBot をよく使うチャットプラットフォームに接続できます。

-> [!TIP]
-> Issue でさらに多くの提案を歓迎します <3
+| プラットフォーム | 保守 |
+|---------|---------------|
+| QQ | 公式 |
+| OneBot v11 プロトコル実装 | 公式 |
+| Telegram | 公式 |
+| WeChat Work アプリケーション & WeChat Work インテリジェントボット | 公式 |
+| WeChat カスタマーサービス & WeChat 公式アカウント | 公式 |
+| Feishu (Lark) | 公式 |
+| DingTalk | 公式 |
+| Slack | 公式 |
+| Discord | 公式 |
+| LINE | 公式 |
+| Satori | 公式 |
+| Misskey | 公式 |
+| WhatsApp (近日対応予定) | 公式 |
+| [Matrix](https://github.com/stevessr/astrbot_plugin_matrix_adapter) | コミュニティ |
+| [KOOK](https://github.com/wuyan1003/astrbot_plugin_kook_adapter) | コミュニティ |
+| [VoceChat](https://github.com/HikariFroya/astrbot_plugin_vocechat) | コミュニティ |

- [ ] 現在のすべてのプラットフォームアダプターの機能の一貫性を確保し、改善する
- [ ] プラグインインターフェースの最適化
- [ ] GPT-Sovits などの TTS サービスをデフォルトでサポート
- [ ] "チャット強化" 部分を完成させ、永続的な記憶をサポート
- [ ] i18n の計画

-## ❤️ 貢献
+## サポートされているモデルサービス

-Issue や Pull Request を歓迎します！このプロジェクトに変更を加えるだけです :)
+| サービス | 種類 |
+|---------|---------------|
+| OpenAI および互換サービス | 大規模言語モデルサービス |
+| Anthropic | 大規模言語モデルサービス |
+| Google Gemini | 大規模言語モデルサービス |
+| Moonshot AI | 大規模言語モデルサービス |
+| 智谱 AI | 大規模言語モデルサービス |
+| DeepSeek | 大規模言語モデルサービス |
+| Ollama (セルフホスト) | 大規模言語モデルサービス |
+| LM Studio (セルフホスト) | 大規模言語モデルサービス |
+| [AIHubMix](https://aihubmix.com/?aff=4bfH) | 大規模言語モデルサービス（APIゲートウェイ、全モデル対応） |
+| [優云智算](https://www.compshare.cn/?ytag=GPU_YY-gh_astrbot&referral_code=FV7DcGowN4hB5UuXKgpE74) | 大規模言語モデルサービス |
+| [302.AI](https://share.302.ai/rr1M3l) | 大規模言語モデルサービス |
+| [小馬算力](https://www.tokenpony.cn/3YPyf) | 大規模言語モデルサービス |
+| [硅基流動](https://docs.siliconflow.cn/cn/usercases/use-siliconcloud-in-astrbot) | 大規模言語モデルサービス |
+| [PPIO 派欧云](https://ppio.com/user/register?invited_by=AIOONE) | 大規模言語モデルサービス |
+| ModelScope | 大規模言語モデルサービス |
+| OneAPI | 大規模言語モデルサービス |
+| Dify | LLMOps プラットフォーム |
+| Alibaba Cloud 百炼アプリケーション | LLMOps プラットフォーム |
+| Coze | LLMOps プラットフォーム |
+| OpenAI Whisper | 音声認識サービス |
+| SenseVoice | 音声認識サービス |
+| OpenAI TTS | 音声合成サービス |
+| Gemini TTS | 音声合成サービス |
+| GPT-Sovits-Inference | 音声合成サービス |
+| GPT-Sovits | 音声合成サービス |
+| FishAudio | 音声合成サービス |
+| Edge TTS | 音声合成サービス |
+| Alibaba Cloud 百炼 TTS | 音声合成サービス |
+| Azure TTS | 音声合成サービス |
+| Minimax TTS | 音声合成サービス |
+| Volcano Engine TTS | 音声合成サービス |

-新機能の追加については、まず Issue で議論してください。
+## ❤️ コントリビューション

-## 🌟 サポート
+Issue や Pull Request は大歓迎です!このプロジェクトに変更を送信してください :)

- このプロジェクトに Star を付けてください！
- [愛発電](https://afdian.com/a/soulter)で私をサポートしてください！
- [WeChat](https://drive.soulter.top/f/pYfA/d903f4fa49a496fda3f16d2be9e023b5.png)で私をサポートしてください~
+### コントリビュート方法

-## ✨ デモ
+Issue を確認したり、PR(プルリクエスト)のレビューを手伝うことで貢献できます。どんな Issue や PR への参加も歓迎され、コミュニティ貢献を促進します。もちろん、これらは提案に過ぎず、どんな方法でも貢献できます。新機能の追加については、まず Issue で議論してください。

-> [!NOTE]
-> コードエグゼキューターのファイル入力/出力は現在 Napcat(QQ)、Lagrange(QQ) でのみテストされています
+### 開発環境

-<div align='center'>
+AstrBot はコードのフォーマットとチェックに `ruff` を使用しています。

-<img src="https://github.com/user-attachments/assets/4ee688d9-467d-45c8-99d6-368f9a8a92d8" width="600">
+```bash
+git clone https://github.com/AstrBotDevs/AstrBot
+pip install pre-commit
+pre-commit install
+```

-_✨ Docker ベースのサンドボックス化されたコードエグゼキューター（ベータテスト中）✨_
+## 🌍 コミュニティ

-<img src="https://github.com/user-attachments/assets/0378f407-6079-4f64-ae4c-e97ab20611d2" height=500>
+### QQ グループ

-_✨ 多モーダル、ウェブ検索、長文の画像変換（設定可能）✨_
+- 1群: 322154837
+- 3群: 630166526
+- 5群: 822130018
+- 6群: 753075035
+- 開発者群: 975206796
+- 開発者群（正式）: 1039761811

-<img src="https://github.com/user-attachments/assets/8ec12797-e70f-460a-959e-48eca39ca2bb" height=100>
+### Discord サーバー

-_✨ 自然言語タスク ✨_
+<a href="https://discord.gg/hAVk6tgV36"><img alt="Discord_community" src="https://img.shields.io/badge/Discord-AstrBot-purple?style=for-the-badge&color=76bad9"></a>

-<img src="https://github.com/user-attachments/assets/e137a9e1-340a-4bf2-bb2b-771132780735" height=150>
-<img src="https://github.com/user-attachments/assets/480f5e82-cf6a-4955-a869-0d73137aa6e1" height=150>
+## ❤️ Special Thanks

-_✨ プラグインシステム - 一部のプラグインの展示 ✨_
+AstrBot への貢献をしていただいたすべてのコントリビューターとプラグイン開発者に特別な感謝を ❤️

-<img src="https://github.com/user-attachments/assets/592a8630-14c7-4e06-b496-9c0386e4f36c" width="600">
+<a href="https://github.com/AstrBotDevs/AstrBot/graphs/contributors">
+  <img src="https://contrib.rocks/image?repo=AstrBotDevs/AstrBot&max=200&columns=14" />
+</a>

-_✨ 管理パネル ✨_
+また、このプロジェクトの誕生は以下のオープンソースプロジェクトの助けなしには実現できませんでした:

-![webchat](https://drive.soulter.top/f/vlsA/ezgif-5-fb044b2542.gif)
-
-_✨ 内蔵 Web Chat、オンラインでボットと対話 ✨_
-
-</div>
+- [NapNeko/NapCatQQ](https://github.com/NapNeko/NapCatQQ) - 素晴らしい猫猫フレームワーク

 ## ⭐ Star History

 > [!TIP]
-> このプロジェクトがあなたの生活や仕事に役立った場合、またはこのプロジェクトの将来の発展に関心がある場合は、プロジェクトに Star を付けてください。これはこのオープンソースプロジェクトを維持するためのモチベーションです <3
+> このプロジェクトがあなたの生活や仕事に役立ったり、このプロジェクトの今後の発展に関心がある場合は、プロジェクトに Star をください。これがこのオープンソースプロジェクトを維持する原動力です <3

 <div align="center">

-[![Star History Chart](https://api.star-history.com/svg?repos=soulter/astrbot&type=Date)](https://star-history.com/#soulter/astrbot&Date)
+[![Star History Chart](https://api.star-history.com/svg?repos=astrbotdevs/astrbot&type=Date)](https://star-history.com/#astrbotdevs/astrbot&Date)

 </div>

-## スポンサー
+<div align="center">

-[<img src="https://api.gitsponsors.com/api/badge/img?id=575865240" height="20">](https://api.gitsponsors.com/api/badge/link?p=XEpbdGxlitw/RbcwiTX93UMzNK/jgDYC8NiSzamIPMoKvG2lBFmyXhSS/b0hFoWlBBMX2L5X5CxTDsUdyvcIEHTOfnkXz47UNOZvMwyt5CzbYpq0SEzsSV1OJF1cCo90qC/ZyYKYOWedal3MhZ3ikw==)
-
-## 免責事項
-
-1. このプロジェクトは `AGPL-v3` オープンソースライセンスの下で保護されています。
-2. このプロジェクトを使用する際は、現地の法律および規制を遵守してください。
-
-<!-- ## ✨ ATRI [ベータテスト]
-
-この機能はプラグインとしてロードされます。プラグインリポジトリのアドレス：[astrbot_plugin_atri](https://github.com/Soulter/astrbot_plugin_atri)
-
-1. 《ATRI ~ My Dear Moments》の主人公 ATRI のキャラクターセリフを微調整データセットとして使用した `Qwen1.5-7B-Chat Lora` 微調整モデル。
-2. 長期記憶
-3. ミームの理解と返信
-4. TTS
-    -->
+_共感力と能力は決して対立するものではありません。私たちが目指すのは、感情を理解し、心の支えとなるだけでなく、確実に仕事をこなせるロボットの創造です。_

 _私は、高性能ですから!_
+
+<img src="https://files.astrbot.app/watashiwa-koseino-desukara.gif" width="100"/>
+
+</div>
@@ -0,0 +1,263 @@
+![AstrBot-Logo-Simplified](https://github.com/user-attachments/assets/ffd99b6b-3272-4682-beaa-6fe74250f7d9)
+
+<div align="center">
+
+<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_zh.md">简体中文</a> ｜
+<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README.md">English</a> ｜
+<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_zh-TW.md">繁體中文</a> ｜
+<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_ja.md">日本語</a> ｜
+<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_fr.md">Français</a>
+
+<br>
+
+<div>
+<a href="https://trendshift.io/repositories/12875" target="_blank"><img src="https://trendshift.io/api/badge/repositories/12875" alt="Soulter%2FAstrBot | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
+<a href="https://hellogithub.com/repository/AstrBotDevs/AstrBot" target="_blank"><img src="https://api.hellogithub.com/v1/widgets/recommend.svg?rid=d127d50cd5e54c5382328acc3bb25483&claim_uid=ZO9by7qCXgSd6Lp&t=2" alt="Featured｜HelloGitHub" style="width: 250px; height: 54px;" width="250" height="54" /></a>
+</div>
+
+<br>
+
+<div>
+<img src="https://img.shields.io/github/v/release/AstrBotDevs/AstrBot?color=76bad9" href="https://github.com/AstrBotDevs/AstrBot/releases/latest">
+<img src="https://img.shields.io/badge/python-3.10+-blue.svg" alt="python">
+<img src="https://deepwiki.com/badge.svg" href="https://deepwiki.com/AstrBotDevs/AstrBot">
+<a href="https://zread.ai/AstrBotDevs/AstrBot" target="_blank"><img src="https://img.shields.io/badge/Ask_Zread-_.svg?style=flat&color=00b0aa&labelColor=000000&logo=data%3Aimage%2Fsvg%2Bxml%3Bbase64%2CPHN2ZyB3aWR0aD0iMTYiIGhlaWdodD0iMTYiIHZpZXdCb3g9IjAgMCAxNiAxNiIgZmlsbD0ibm9uZSIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KPHBhdGggZD0iTTQuOTYxNTYgMS42MDAxSDIuMjQxNTZDMS44ODgxIDEuNjAwMSAxLjYwMTU2IDEuODg2NjQgMS42MDE1NiAyLjI0MDFWNC45NjAxQzEuNjAxNTYgNS4zMTM1NiAxLjg4ODEgNS42MDAxIDIuMjQxNTYgNS42MDAxSDQuOTYxNTZDNS4zMTUwMiA1LjYwMDEgNS42MDE1NiA1LjMxMzU2IDUuNjAxNTYgNC45NjAxVjIuMjQwMUM1LjYwMTU2IDEuODg2NjQgNS4zMTUwMiAxLjYwMDEgNC45NjE1NiAxLjYwMDFZIiBmaWxsPSIjZmZmIi8%2BCjxwYXRoIGQ9Ik00Ljk2MTU2IDEwLjM5OTlIMi4yNDE1NkMxLjg4ODEgMTAuMzk5OSAxLjYwMTU2IDEwLjY4NjQgMS42MDE1NiAxMS4wMzk5VjEzLjc1OTlDMS42MDE1NiAxNC4xMTM0IDEuODg4MSAxNC4zOTk5IDIuMjQxNTYgMTQuMzk5OUg0Ljk2MTU2QzUuMzE1MDIgMTQuMzk5OSA1LjYwMTU2IDE0LjExMzQgNS42MDE1NiAxMy43NTk5VjExLjAzOTlDNS42MDE1NiAxMC42ODY0IDUuMzE1MDIgMTAuMzk5OSA0Ljk2MTU2IDEwLjM5OTlaIiBmaWxsPSIjZmZmIi8%2BCjxwYXRoIGQ9Ik0xMy43NTg0IDEuNjAwMUgxMS4wMzg0QzEwLjY4NSAxLjYwMDEgMTAuMzk4NCAxLjg4NjY0IDEwLjM5ODQgMi4yNDAxVjQuOTYwMUMxMC4zOTg0IDUuMzEzNTYgMTAuNjg1IDUuNjAwMSAxMS4wMzg0IDUuNjAwMUgxMy43NTg0QzE0LjExMTkgNS42MDAxIDE0LjM5ODQgNS4zMTM1NiAxNC4zOTg0IDQuOTYwMVYyLjI0MDFDMTQuMzk4NCAxLjg4NjY0IDE0LjExMTkgMS42MDAxIDEzLjczODQgMS42MDAxWiIgZmlsbD0iI2ZmZiIvPgo8cGF0aCBkPSJNNCAxMkwxMiA0TDQgMTJaIiBmaWxsPSIjZmZmIi8%2BCjxwYXRoIGQ9Ik00IDEyTDEyIDQiIHN0cm9rZT0iI2ZmZiIgc3Ryb2tlLXdpZHRoPSIxLjUiIHN0cm9rZS1saW5lY2FwPSJyb3VuZCIvPgo8L3N2Zz4K&logoColor=ffffff" alt="zread"/></a>
+<a href="https://hub.docker.com/r/soulter/astrbot"><img alt="Docker pull" src="https://img.shields.io/docker/pulls/soulter/astrbot.svg?color=76bad9"/></a>
+<img src="https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fapi.soulter.top%2Fastrbot%2Fplugin-num&query=%24.result&suffix=%20&label=%D0%9C%D0%B0%D1%80%D0%BA%D0%B5%D1%82%D0%BF%D0%BB%D0%B5%D0%B9%D1%81&cacheSeconds=3600">
+<img src="https://gitcode.com/Soulter/AstrBot/star/badge.svg" href="https://gitcode.com/Soulter/AstrBot">
+</div>
+
+<br>
+
+<a href="https://astrbot.app/">Документация</a> ｜
+<a href="https://blog.astrbot.app/">Блог</a> ｜
+<a href="https://astrbot.featurebase.app/roadmap">Дорожная карта</a> ｜
+<a href="https://github.com/AstrBotDevs/AstrBot/issues">Сообщить о проблеме</a>
+<a href="mailto:community@astrbot.app">Email Support</a>
+</div>
+
+AstrBot — это универсальная платформа Agent-чатботов с открытым исходным кодом, которая интегрируется с основными приложениями для обмена мгновенными сообщениями. Она предоставляет надёжную и масштабируемую инфраструктуру разговорного ИИ для частных лиц, разработчиков и команд. Будь то персональный ИИ-компаньон, интеллектуальная служба поддержки, автоматизированный помощник или корпоративная база знаний — AstrBot позволяет быстро создавать готовые к использованию ИИ-приложения в рабочих процессах вашей платформы обмена сообщениями.
+
+![521771166-00782c4c-4437-4d97-aabc-605e3738da5c (1)](https://github.com/user-attachments/assets/61e7b505-f7db-41aa-a75f-4ef8f079b8ba)
+
+## Основные возможности
+
+1. 💯 Бесплатно & Открытый исходный код.
+2. ✨ Диалоги с ИИ-моделями, мультимодальность, Agent, MCP, Skills, База знаний, Настройка личности, автоматическое сжатие диалогов.
+3. 🤖 Поддержка интеграции с платформами Agents, такими как Dify, Alibaba Cloud Bailian, Coze и др.
+4. 🌐 Мультиплатформенность: поддержка QQ, WeChat для предприятий, Feishu, DingTalk, публичных аккаунтов WeChat, Telegram, Slack и [других](#Поддерживаемые-платформы-обмена-сообщениями).
+5. 📦 Расширение плагинами: доступно более 1000 плагинов для установки в один клик.
+6. 🛡️  Изолированная среда[Agent Sandbox](https://docs.astrbot.app/use/astrbot-agent-sandbox.html): безопасное выполнение любого кода, вызов Shell, повторное использование ресурсов на уровне сессии.
+7. 💻 Поддержка WebUI.
+8. 🌈 Поддержка Web ChatUI: встроенная песочница агента, веб-поиск и др.
+9. 🌐 Поддержка интернационализации (i18n).
+
+<br>
+
+<table align="center">
+  <tr align="center">
+    <th>💙 Ролевые игры & Эмоциональная поддержка</th>
+    <th>✨ Проактивный Агент (Agent)</th>
+    <th>🚀 Универсальные возможности Агента</th>
+    <th>🧩 1000+ плагинов сообщества</th>
+  </tr>
+  <tr>
+    <td align="center"><p align="center"><img width="984" height="1746" alt="99b587c5d35eea09d84f33e6cf6cfd4f" src="https://github.com/user-attachments/assets/89196061-3290-458d-b51f-afa178049f84" /></p></td>
+    <td align="center"><p align="center"><img width="976" height="1612" alt="c449acd838c41d0915cc08a3824025b1" src="https://github.com/user-attachments/assets/f75368b4-e022-41dc-a9e0-131c3e73e32e" /></p></td>
+    <td align="center"><p align="center"><img width="974" height="1732" alt="image" src="https://github.com/user-attachments/assets/e22a3968-87d7-4708-a7cd-e7f198c7c32e" /></p></td>
+    <td align="center"><p align="center"><img width="976" height="1734" alt="image" src="https://github.com/user-attachments/assets/0952b395-6b4a-432a-8a50-c294b7f89750" /></p></td>
+  </tr>
+</table>
+
+## Быстрый старт
+
+### Развёртывание в один клик
+
+Для пользователей, которые хотят быстро попробовать AstrBot, знакомы с командной строкой и могут самостоятельно установить окружение `uv`, мы рекомендуем использовать развёртывание в один клик через `uv` ⚡️:
+
+```bash
+uv tool install astrbot
+astrbot init # Выполните эту команду только при первом запуске для инициализации окружения
+astrbot
+```
+
+> Требуется установленный [uv](https://docs.astral.sh/uv/).
+
+> [!NOTE]
+> Для пользователей macOS: из-за проверок безопасности macOS первый запуск команды `astrbot` может занять больше времени (около 10-20 секунд).
+
+Обновить `astrbot`:
+
+```bash
+uv tool upgrade astrbot
+```
+
+### Развёртывание Docker
+
+Для пользователей, знакомых с контейнерами и которым нужен более стабильный и подходящий для production способ, мы рекомендуем разворачивать AstrBot через Docker / Docker Compose.
+
+См. официальную документацию [Развёртывание AstrBot с Docker](https://astrbot.app/deploy/astrbot/docker.html#%E4%BD%BF%E7%94%A8-docker-%E9%83%A8%E7%BD%B2-astrbot).
+
+### Развёртывание на RainYun
+
+Для пользователей, которые хотят развернуть AstrBot в один клик и не хотят самостоятельно управлять сервером, мы рекомендуем облачный сервис развёртывания в один клик от RainYun ☁️:
+
+[![Deploy on RainYun](https://rainyun-apps.cn-nb1.rains3.com/materials/deploy-on-rainyun-en.svg)](https://app.rainyun.com/apps/rca/store/5994?ref=NjU1ODg0)
+
+### Развёртывание десктопного приложения
+
+Для пользователей, которые хотят использовать AstrBot на десктопе и в основном работают через ChatUI, мы рекомендуем AstrBot App.
+
+Перейдите в [AstrBot-desktop](https://github.com/AstrBotDevs/AstrBot-desktop), скачайте и установите приложение; этот вариант предназначен для десктопа и не рекомендуется для серверных сценариев.
+
+### Развёртывание через лаунчер
+
+Также на десктопе, для пользователей, которым нужен быстрый запуск и мультиинстанс с изоляцией окружений, мы рекомендуем AstrBot Launcher.
+
+Перейдите в [AstrBot Launcher](https://github.com/Raven95676/astrbot-launcher), чтобы скачать и установить.
+
+### Развёртывание на Replit
+
+Развёртывание через Replit поддерживается сообществом и подходит для онлайн-демо и лёгких тестовых запусков.
+
+[![Run on Repl.it](https://repl.it/badge/github/AstrBotDevs/AstrBot)](https://repl.it/github/AstrBotDevs/AstrBot)
+
+### AUR
+
+AUR-вариант предназначен для пользователей Arch Linux, которым удобна установка через системный менеджер пакетов.
+
+Выполните команду ниже для установки `astrbot-git`, затем запустите AstrBot локально.
+
+```bash
+yay -S astrbot-git
+```
+
+**Другие способы развёртывания**
+
+Если вам нужна панельная установка или более глубокая кастомизация, смотрите [Развёртывание BT-Panel](https://astrbot.app/deploy/astrbot/btpanel.html) (установка через BT Panel), [Развёртывание 1Panel](https://astrbot.app/deploy/astrbot/1panel.html) (развёртывание через маркетплейс 1Panel), [Развёртывание CasaOS](https://astrbot.app/deploy/astrbot/casaos.html) (визуальный вариант для NAS и домашних серверов) и [Ручное развёртывание](https://astrbot.app/deploy/astrbot/cli.html) (полностью настраиваемая установка из исходников через `uv`).
+
+## Поддерживаемые платформы обмена сообщениями
+
+Подключите AstrBot к вашим любимым чат-платформам.
+
+| Платформа | Поддержка |
+|---------|---------------|
+| QQ | Официальная |
+| Реализация протокола OneBot v11 | Официальная |
+| Telegram | Официальная |
+| Приложение WeChat Work и интеллектуальный бот WeChat Work | Официальная |
+| Служба поддержки WeChat и официальные аккаунты WeChat | Официальная |
+| Feishu (Lark) | Официальная |
+| DingTalk | Официальная |
+| Slack | Официальная |
+| Discord | Официальная |
+| LINE | Официальная |
+| Satori | Официальная |
+| Misskey | Официальная |
+| WhatsApp (Скоро) | Официальная |
+| [Matrix](https://github.com/stevessr/astrbot_plugin_matrix_adapter) | Сообщество |
+| [KOOK](https://github.com/wuyan1003/astrbot_plugin_kook_adapter) | Сообщество |
+| [VoceChat](https://github.com/HikariFroya/astrbot_plugin_vocechat) | Сообщество |
+
+## Поддерживаемые сервисы моделей
+
+| Сервис | Тип |
+|---------|---------------|
+| OpenAI и совместимые сервисы | Сервисы LLM |
+| Anthropic | Сервисы LLM |
+| Google Gemini | Сервисы LLM |
+| Moonshot AI | Сервисы LLM |
+| Zhipu AI | Сервисы LLM |
+| DeepSeek | Сервисы LLM |
+| Ollama (Самостоятельное размещение) | Сервисы LLM |
+| LM Studio (Самостоятельное размещение) | Сервисы LLM |
+| [AIHubMix](https://aihubmix.com/?aff=4bfH) | Сервисы LLM (API-шлюз, поддерживает все модели) |
+| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_astrbot&referral_code=FV7DcGowN4hB5UuXKgpE74) | Сервисы LLM |
+| [302.AI](https://share.302.ai/rr1M3l) | Сервисы LLM |
+| [TokenPony](https://www.tokenpony.cn/3YPyf) | Сервисы LLM |
+| [SiliconFlow](https://docs.siliconflow.cn/cn/usercases/use-siliconcloud-in-astrbot) | Сервисы LLM |
+| [PPIO Cloud](https://ppio.com/user/register?invited_by=AIOONE) | Сервисы LLM |
+| ModelScope | Сервисы LLM |
+| OneAPI | Сервисы LLM |
+| Dify | Платформы LLMOps |
+| Приложения Alibaba Cloud Bailian | Платформы LLMOps |
+| Coze | Платформы LLMOps |
+| OpenAI Whisper | Сервисы распознавания речи |
+| SenseVoice | Сервисы распознавания речи |
+| OpenAI TTS | Сервисы синтеза речи |
+| Gemini TTS | Сервисы синтеза речи |
+| GPT-Sovits-Inference | Сервисы синтеза речи |
+| GPT-Sovits | Сервисы синтеза речи |
+| FishAudio | Сервисы синтеза речи |
+| Edge TTS | Сервисы синтеза речи |
+| Alibaba Cloud Bailian TTS | Сервисы синтеза речи |
+| Azure TTS | Сервисы синтеза речи |
+| Minimax TTS | Сервисы синтеза речи |
+| Volcano Engine TTS | Сервисы синтеза речи |
+
+## ❤️ Вклад в проект
+
+Issues и Pull Request всегда приветствуются! Не стесняйтесь отправлять свои изменения в этот проект :)
+
+### Как внести вклад
+
+Вы можете внести вклад, просматривая issues или помогая с ревью pull request. Любые issues или PR приветствуются для поощрения участия сообщества. Конечно, это лишь предложения — вы можете вносить вклад любым удобным для вас способом. Для добавления новых функций сначала обсудите это через Issue.
+
+### Среда разработки
+
+AstrBot использует `ruff` для форматирования и линтинга кода.
+
+```bash
+git clone https://github.com/AstrBotDevs/AstrBot
+pip install pre-commit
+pre-commit install
+```
+
+## 🌍 Сообщество
+
+### Группы QQ
+
+- Группа 1: 322154837
+- Группа 3: 630166526
+- Группа 5: 822130018
+- Группа 6: 753075035
+- Группа разработчиков: 975206796
+- Группа разработчиков (официальная): 1039761811
+
+### Сервер Discord
+
+<a href="https://discord.gg/hAVk6tgV36"><img alt="Discord_community" src="https://img.shields.io/badge/Discord-AstrBot-purple?style=for-the-badge&color=76bad9"></a>
+
+## ❤️ Особая благодарность
+
+Особая благодарность всем контрибьюторам и разработчикам плагинов за их вклад в AstrBot ❤️
+
+<a href="https://github.com/AstrBotDevs/AstrBot/graphs/contributors">
+  <img src="https://contrib.rocks/image?repo=AstrBotDevs/AstrBot&max=200&columns=14" />
+</a>
+
+Кроме того, рождение этого проекта было бы невозможно без помощи следующих проектов с открытым исходным кодом:
+
+- [NapNeko/NapCatQQ](https://github.com/NapNeko/NapCatQQ) - Замечательный кошачий фреймворк
+
+## ⭐ История звёзд
+
+> [!TIP]
+> Если этот проект помог вам в жизни или работе, или если вас интересует его будущее развитие, пожалуйста, поставьте проекту звезду. Это движущая сила поддержки этого проекта с открытым исходным кодом <3
+
+
+<div align="center">
+
+[![Star History Chart](https://api.star-history.com/svg?repos=astrbotdevs/astrbot&type=Date)](https://star-history.com/#astrbotdevs/astrbot&Date)
+
+</div>
+
+<div align="center">
+
+_Сопровождение и способности никогда не должны быть противоположностями. Мы стремимся создать робота, который сможет как понимать эмоции, оказывать душевную поддержку, так и надёжно выполнять работу._
+
+_私は、高性能ですから!_
+
+<img src="https://files.astrbot.app/watashiwa-koseino-desukara.gif" width="100"/>
+
+</div>
@@ -0,0 +1,266 @@
+![AstrBot-Logo-Simplified](https://github.com/user-attachments/assets/ffd99b6b-3272-4682-beaa-6fe74250f7d9)
+
+<div align="center">
+
+<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_zh.md">简体中文</a> ｜
+<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README.md">English</a> ｜
+<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_ja.md">日本語</a> ｜
+<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_fr.md">Français</a> ｜
+<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_ru.md">Русский</a>
+
+<br>
+
+<div>
+<a href="https://trendshift.io/repositories/12875" target="_blank"><img src="https://trendshift.io/api/badge/repositories/12875" alt="Soulter%2FAstrBot | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
+<a href="https://hellogithub.com/repository/AstrBotDevs/AstrBot" target="_blank"><img src="https://api.hellogithub.com/v1/widgets/recommend.svg?rid=d127d50cd5e54c5382328acc3bb25483&claim_uid=ZO9by7qCXgSd6Lp&t=2" alt="Featured｜HelloGitHub" style="width: 250px; height: 54px;" width="250" height="54" /></a>
+</div>
+
+<br>
+
+<div>
+<img src="https://img.shields.io/github/v/release/AstrBotDevs/AstrBot?color=76bad9" href="https://github.com/AstrBotDevs/AstrBot/releases/latest">
+<img src="https://img.shields.io/badge/python-3.10+-blue.svg" alt="python">
+<img src="https://deepwiki.com/badge.svg" href="https://deepwiki.com/AstrBotDevs/AstrBot">
+<a href="https://zread.ai/AstrBotDevs/AstrBot" target="_blank"><img src="https://img.shields.io/badge/Ask_Zread-_.svg?style=flat&color=00b0aa&labelColor=000000&logo=data%3Aimage%2Fsvg%2Bxml%3Bbase64%2CPHN2ZyB3aWR0aD0iMTYiIGhlaWdodD0iMTYiIHZpZXdCb3g9IjAgMCAxNiAxNiIgZmlsbD0ibm9uZSIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KPHBhdGggZD0iTTQuOTYxNTYgMS42MDAxSDIuMjQxNTZDMS44ODgxIDEuNjAwMSAxLjYwMTU2IDEuODg2NjQgMS42MDE1NiAyLjI0MDFWNC45NjAxQzEuNjAxNTYgNS4zMTM1NiAxLjg4ODEgNS42MDAxIDIuMjQxNTYgNS42MDAxSDQuOTYxNTZDNS4zMTUwMiA1LjYwMDEgNS42MDE1NiA1LjMxMzU2IDUuNjAxNTYgNC45NjAxVjIuMjQwMUM1LjYwMTU2IDEuODg2NjQgNS4zMTUwMiAxLjYwMDEgNC45NjE1NiAxLjYwMDFaIiBmaWxsPSIjZmZmIi8%2BCjxwYXRoIGQ9Ik00Ljk2MTU2IDEwLjM5OTlIMi4yNDE1NkMxLjg4ODEgMTAuMzk5OSAxLjYwMTU2IDEwLjY4NjQgMS42MDE1NiAxMS4wMzk5VjEzLjc1OTlDMS42MDE1NiAxNC4xMTM0IDEuODg4MSAxNC4zOTk5IDIuMjQxNTYgMTQuMzk5OUg0Ljk2MTU2QzUuMzE1MDIgMTQuMzk5OSA1LjYwMTU2IDE0LjExMzQgNS42MDE1NiAxMy43NTk5VjExLjAzOTlDNS42MDE1NiAxMC42ODY0IDUuMzE1MDIgMTAuMzk5OSA0Ljk2MTU2IDEwLjM5OTlaIiBmaWxsPSIjZmZmIi8%2BCjxwYXRoIGQ9Ik0xMy43NTg0IDEuNjAwMUgxMS4wMzg0QzEwLjY4NSAxLjYwMDEgMTAuMzk4NCAxLjg4NjY0IDEwLjM5ODQgMi4yNDAxVjQuOTYwMUMxMC4zOTg0IDUuMzEzNTYgMTAuNjg1IDUuNjAwMSAxMS4wMzg0IDUuNjAwMUgxMy43NTg0QzE0LjExMTkgNS42MDAxIDE0LjM5ODQgNS4zMTM1NiAxNC4zOTg0IDQuOTYwMVYyLjI0MDFDMTQuMzk4NCAxLjg4NjY0IDE0LjExMTkgMS42MDAxIDEzLjc1ODQgMS42MDAxWiIgZmlsbD0iI2ZmZiIvPgo8cGF0aCBkPSJNNCAxMkwxMiA0TDQgMTJaIiBmaWxsPSIjZmZmIi8%2BCjxwYXRoIGQ9Ik00IDEyTDEyIDQiIHN0cm9rZT0iI2ZmZiIgc3Ryb2tlLXdpZHRoPSIxLjUiIHN0cm9rZS1saW5lY2FwPSJyb3VuZCIvPgo8L3N2Zz4K&logoColor=ffffff" alt="zread"/></a>
+<a href="https://hub.docker.com/r/soulter/astrbot"><img alt="Docker pull" src="https://img.shields.io/docker/pulls/soulter/astrbot.svg?color=76bad9"/></a>
+<img src="https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fapi.soulter.top%2Fastrbot%2Fplugin-num&query=%24.result&suffix=%E5%80%8B&label=%E6%8F%92%E4%BB%B6%E5%B8%82%E5%A0%B4&cacheSeconds=3600">
+<img src="https://gitcode.com/Soulter/AstrBot/star/badge.svg" href="https://gitcode.com/Soulter/AstrBot">
+</div>
+
+<br>
+
+<a href="https://astrbot.app/">文件</a> ｜
+<a href="https://blog.astrbot.app/">Blog</a> ｜
+<a href="https://astrbot.featurebase.app/roadmap">路線圖</a> ｜
+<a href="https://github.com/AstrBotDevs/AstrBot/issues">問題回報</a>
+<a href="mailto:community@astrbot.app">Email</a>
+</div>
+
+AstrBot 是一個開源的一站式 Agent 聊天機器人平台，可接入主流即時通訊軟體，為個人、開發者和團隊打造可靠、可擴展的對話式智慧基礎設施。無論是個人 AI 夥伴、智慧客服、自動化助手，還是企業知識庫，AstrBot 都能在您的即時通訊軟體平台的工作流程中快速構建生產可用的 AI 應用程式。
+
+![screenshot_1 5x_postspark_2026-02-27_22-37-45](https://github.com/user-attachments/assets/f17cdb90-52d7-4773-be2e-ff64b566af6b)
+
+## 主要功能
+
+1. 💯 免費 & 開源。
+2. ✨ AI 大模型對話，多模態，Agent，MCP，Skills，知識庫，人格設定，自動壓縮對話。
+3. 🤖 支援接入 Dify、阿里雲百煉、Coze 等智慧體 (Agent) 平台。
+4. 🌐 多平台，支援 QQ、企業微信、飛書、釘釘、微信公眾號、Telegram、Slack 以及[更多](#支援的訊息平台)。
+5. 📦 插件擴展，已有 1000+ 個插件可一鍵安裝。
+6. 🛡️ [Agent Sandbox](https://docs.astrbot.app/use/astrbot-agent-sandbox.html) 隔離化環境，安全地執行任何代碼、調用 Shell、會話級資源複用。
+7. 💻 WebUI 支援。
+8. 🌈 Web ChatUI 支援，ChatUI 內置代理沙盒 (Agent Sandbox)、網頁搜尋等。
+9. 🌐 國際化（i18n）支援。
+
+<br>
+
+<table align="center">
+  <tr align="center">
+    <th>💙 角色扮演 & 情感陪伴</th>
+    <th>✨ 主動式 Agent</th>
+    <th>🚀 通用 Agentic 能力</th>
+    <th>🧩 1000+ 社區外掛程式</th>
+  </tr>
+  <tr>
+    <td align="center"><p align="center"><img width="984" height="1746" alt="99b587c5d35eea09d84f33e6cf6cfd4f" src="https://github.com/user-attachments/assets/89196061-3290-458d-b51f-afa178049f84" /></p></td>
+    <td align="center"><p align="center"><img width="976" height="1612" alt="c449acd838c41d0915cc08a3824025b1" src="https://github.com/user-attachments/assets/f75368b4-e022-41dc-a9e0-131c3e73e32e" /></p></td>
+    <td align="center"><p align="center"><img width="974" height="1732" alt="image" src="https://github.com/user-attachments/assets/e22a3968-87d7-4708-a7cd-e7f198c7c32e" /></p></td>
+    <td align="center"><p align="center"><img width="976" height="1734" alt="image" src="https://github.com/user-attachments/assets/0952b395-6b4a-432a-8a50-c294b7f89750" /></p></td>
+  </tr>
+</table>
+
+## 快速開始
+
+### 一鍵部署
+
+對於想快速體驗 AstrBot、且熟悉命令列並能自行安裝 `uv` 環境的使用者，我們推薦使用 `uv` 一鍵部署方式 ⚡️。
+
+```bash
+uv tool install astrbot
+astrbot init # 僅首次執行此命令以初始化環境
+astrbot
+```
+
+> 需要安裝 [uv](https://docs.astral.sh/uv/)。
+
+> [!NOTE]
+> 對於 macOS 使用者：由於 macOS 安全性檢查，首次執行 `astrbot` 指令可能需要較長時間（約 10-20 秒）。
+
+更新 `astrbot`：
+
+```bash
+uv tool upgrade astrbot
+```
+
+### Docker 部署
+
+對於熟悉容器、希望獲得更穩定且更適合正式環境部署方式的使用者，我們推薦使用 Docker / Docker Compose 部署 AstrBot。
+
+請參考官方文件 [使用 Docker 部署 AstrBot](https://astrbot.app/deploy/astrbot/docker.html#%E4%BD%BF%E7%94%A8-docker-%E9%83%A8%E7%BD%B2-astrbot)。
+
+### 在雨雲上部署
+
+對於希望一鍵部署 AstrBot 且不想自行管理伺服器的使用者，我們推薦使用雨雲的一鍵雲端部署服務 ☁️：
+
+[![Deploy on RainYun](https://rainyun-apps.cn-nb1.rains3.com/materials/deploy-on-rainyun-en.svg)](https://app.rainyun.com/apps/rca/store/5994?ref=NjU1ODg0)
+
+### 桌面客戶端部署
+
+對於希望在桌面端使用 AstrBot、並以 ChatUI 為主要入口的使用者，我們推薦使用 AstrBot App。
+
+前往 [AstrBot-desktop](https://github.com/AstrBotDevs/AstrBot-desktop) 下載並安裝；此方式面向桌面使用，不建議伺服器場景。
+
+### 啟動器部署
+
+同樣在桌面端，對於希望快速部署並實現環境隔離多開的使用者，我們推薦使用 AstrBot Launcher。
+
+前往 [AstrBot Launcher](https://github.com/Raven95676/astrbot-launcher) 下載並安裝。
+
+### 在 Replit 上部署
+
+Replit 部署由社群維護，適合線上示範與輕量試用情境。
+
+[![Run on Repl.it](https://repl.it/badge/github/AstrBotDevs/AstrBot)](https://repl.it/github/AstrBotDevs/AstrBot)
+
+### AUR
+
+AUR 方式面向 Arch Linux 使用者，適合希望透過系統套件管理器安裝 AstrBot 的場景。
+
+在終端執行下方命令安裝 `astrbot-git` 套件，安裝完成後即可啟動使用。
+
+```bash
+yay -S astrbot-git
+```
+
+**更多部署方式**
+
+若你需要面板化或更高自訂程度的部署，可參考 [寶塔面板](https://astrbot.app/deploy/astrbot/btpanel.html)（BT Panel 應用商店安裝）、[1Panel](https://astrbot.app/deploy/astrbot/1panel.html)（1Panel 應用商店安裝）、[CasaOS](https://astrbot.app/deploy/astrbot/casaos.html)（NAS / 家用伺服器可視化部署）與 [手動部署](https://astrbot.app/deploy/astrbot/cli.html)（基於原始碼與 `uv` 的完整自訂安裝）。
+
+## 支援的訊息平台
+
+將 AstrBot 連接到你常用的聊天平台。
+
+| 平台 | 維護方 |
+|---------|---------------|
+| QQ | 官方維護 |
+| OneBot v11 協議實作 | 官方維護 |
+| Telegram | 官方維護 |
+| 企微應用 & 企微智慧機器人 | 官方維護 |
+| 微信客服 & 微信公眾號 | 官方維護 |
+| 飛書 | 官方維護 |
+| 釘釘 | 官方維護 |
+| Slack | 官方維護 |
+| Discord | 官方維護 |
+| LINE | 官方維護 |
+| Satori | 官方維護 |
+| Misskey | 官方維護 |
+| Whatsapp（即將支援） | 官方維護 |
+| [Matrix](https://github.com/stevessr/astrbot_plugin_matrix_adapter) | 社群維護 |
+| [KOOK](https://github.com/wuyan1003/astrbot_plugin_kook_adapter) | 社群維護 |
+| [VoceChat](https://github.com/HikariFroya/astrbot_plugin_vocechat) | 社群維護 |
+
+## 支援的模型服務
+
+| 服務 | 類型 |
+|---------|---------------|
+| OpenAI 及相容服務 | 大型模型服務 |
+| Anthropic | 大型模型服務 |
+| Google Gemini | 大型模型服務 |
+| Moonshot AI | 大型模型服務 |
+| 智譜 AI | 大型模型服務 |
+| DeepSeek | 大型模型服務 |
+| Ollama（本機部署） | 大型模型服務 |
+| LM Studio（本機部署） | 大型模型服務 |
+| [AIHubMix](https://aihubmix.com/?aff=4bfH) | 大型模型服務（API 閘道，支援所有模型） |
+| [優雲智算](https://www.compshare.cn/?ytag=GPU_YY-gh_astrbot&referral_code=FV7DcGowN4hB5UuXKgpE74) | 大型模型服務 |
+| [302.AI](https://share.302.ai/rr1M3l) | 大型模型服務 |
+| [小馬算力](https://www.tokenpony.cn/3YPyf) | 大型模型服務 |
+| [矽基流動](https://docs.siliconflow.cn/cn/usercases/use-siliconcloud-in-astrbot) | 大型模型服務 |
+| [PPIO 派歐雲](https://ppio.com/user/register?invited_by=AIOONE) | 大型模型服務 |
+| ModelScope | 大型模型服務 |
+| OneAPI | 大型模型服務 |
+| Dify | LLMOps 平台 |
+| 阿里雲百煉應用 | LLMOps 平台 |
+| Coze | LLMOps 平台 |
+| OpenAI Whisper | 語音轉文字服務 |
+| SenseVoice | 語音轉文字服務 |
+| OpenAI TTS | 文字轉語音服務 |
+| Gemini TTS | 文字轉語音服務 |
+| GPT-Sovits-Inference | 文字轉語音服務 |
+| GPT-Sovits | 文字轉語音服務 |
+| FishAudio | 文字轉語音服務 |
+| Edge TTS | 文字轉語音服務 |
+| 阿里雲百煉 TTS | 文字轉語音服務 |
+| Azure TTS | 文字轉語音服務 |
+| Minimax TTS | 文字轉語音服務 |
+| 火山引擎 TTS | 文字轉語音服務 |
+
+## ❤️ 貢獻
+
+歡迎任何 Issues/Pull Requests！只需要將您的變更提交到此專案 ：)
+
+### 如何貢獻
+
+您可以透過檢視問題或協助審核 PR（拉取請求）來貢獻。任何問題或 PR 都歡迎參與，以促進社群貢獻。當然，這些只是建議，您可以以任何方式進行貢獻。對於新功能的新增，請先透過 Issue 討論。
+
+### 開發環境
+
+AstrBot 使用 `ruff` 進行程式碼格式化和檢查。
+
+```bash
+git clone https://github.com/AstrBotDevs/AstrBot
+pip install pre-commit
+pre-commit install
+```
+
+## 🌍 社群
+
+### QQ 群組
+
+- 9 群: 1076659624 (新)
+- 10 群: 1078079676 (新)
+- 1 群：322154837
+- 3 群：630166526
+- 5 群：822130018
+- 6 群：753075035
+- 7 群：743746109
+- 8 群：1030353265
+- 開發者群（闲聊吹水）：975206796
+- 開發者群（正式）：1039761811
+
+### Discord 群組
+
+<a href="https://discord.gg/hAVk6tgV36"><img alt="Discord_community" src="https://img.shields.io/badge/Discord-AstrBot-purple?style=for-the-badge&color=76bad9"></a>
+
+## ❤️ Special Thanks
+
+特別感謝所有 Contributors 和外掛開發者對 AstrBot 的貢獻 ❤️
+
+<a href="https://github.com/AstrBotDevs/AstrBot/graphs/contributors">
+  <img src="https://contrib.rocks/image?repo=AstrBotDevs/AstrBot&max=200&columns=14" />
+</a>
+
+此外，本專案的誕生離不開以下開源專案的幫助：
+
+- [NapNeko/NapCatQQ](https://github.com/NapNeko/NapCatQQ) - 偉大的貓貓框架
+
+## ⭐ Star History
+
+> [!TIP]
+> 如果本專案對您的生活 / 工作產生了幫助，或者您關注本專案的未來發展，請給專案 Star，這是我們維護這個開源專案的動力 <3
+
+<div align="center">
+
+[![Star History Chart](https://api.star-history.com/svg?repos=astrbotdevs/astrbot&type=Date)](https://star-history.com/#astrbotdevs/astrbot&Date)
+
+</div>
+
+<div align="center">
+
+_陪伴與能力從來不應該是對立面。我們希望創造的是一個既能理解情緒、給予陪伴，也能可靠完成工作的機器人。_
+
+_私は、高性能ですから!_
+
+<img src="https://files.astrbot.app/watashiwa-koseino-desukara.gif" width="100"/>
+
+</div>
@@ -0,0 +1,277 @@
+![AstrBot-Logo-Simplified](https://github.com/user-attachments/assets/ffd99b6b-3272-4682-beaa-6fe74250f7d9)
+
+<div align="center">
+
+<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README.md">English</a> ｜
+<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_zh-TW.md">繁體中文</a> ｜
+<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_ja.md">日本語</a> ｜
+<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_fr.md">Français</a> ｜
+<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_ru.md">Русский</a>
+
+<div>
+<a href="https://trendshift.io/repositories/12875" target="_blank"><img src="https://trendshift.io/api/badge/repositories/12875" alt="Soulter%2FAstrBot | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
+<a href="https://hellogithub.com/repository/AstrBotDevs/AstrBot" target="_blank"><img src="https://api.hellogithub.com/v1/widgets/recommend.svg?rid=d127d50cd5e54c5382328acc3bb25483&claim_uid=ZO9by7qCXgSd6Lp&t=2" alt="Featured｜HelloGitHub" style="width: 250px; height: 54px;" width="250" height="54" /></a>
+</div>
+
+<br>
+
+<div>
+<img src="https://img.shields.io/github/v/release/AstrBotDevs/AstrBot?color=76bad9" href="https://github.com/AstrBotDevs/AstrBot/releases/latest">
+<img src="https://img.shields.io/badge/python-3.10+-blue.svg" alt="python">
+<img src="https://deepwiki.com/badge.svg" href="https://deepwiki.com/AstrBotDevs/AstrBot">
+<a href="https://zread.ai/AstrBotDevs/AstrBot" target="_blank"><img src="https://img.shields.io/badge/Ask_Zread-_.svg?style=flat&color=00b0aa&labelColor=000000&logo=data%3Aimage%2Fsvg%2Bxml%3Bbase64%2CPHN2ZyB3aWR0aD0iMTYiIGhlaWdodD0iMTYiIHZpZXdCb3g9IjAgMCAxNiAxNiIgZmlsbD0ibm9uZSIgeG1sbnM9Imh0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnIj4KPHBhdGggZD0iTTQuOTYxNTYgMS42MDAxSDIuMjQxNTZDMS44ODgxIDEuNjAwMSAxLjYwMTU2IDEuODg2NjQgMS42MDE1NiAyLjI0MDFWNC45NjAxQzEuNjAxNTYgNS4zMTM1NiAxLjg4ODEgNS42MDAxIDIuMjQxNTYgNS42MDAxSDQuOTYxNTZDNS4zMTUwMiA1LjYwMDEgNS42MDE1NiA1LjMxMzU2IDUuNjAxNTYgNC45NjAxVjIuMjQwMUM1LjYwMTU2IDEuODg2NjQgNS4zMTUwMiAxLjYwMDEgNC45NjE1NiAxLjYwMDFaIiBmaWxsPSIjZmZmIi8%2BCjxwYXRoIGQ9Ik00Ljk2MTU2IDEwLjM5OTlIMi4yNDE1NkMxLjg4ODEgMTAuMzk5OSAxLjYwMTU2IDEwLjY4NjQgMS42MDE1NiAxMS4wMzk5VjEzLjc1OTlDMS42MDE1NiAxNC4xMTM0IDEuODg4MSAxNC4zOTk5IDIuMjQxNTYgMTQuMzk5OUg0Ljk2MTU2QzUuMzE1MDIgMTQuMzk5OSA1LjYwMTU2IDE0LjExMzQgNS42MDE1NiAxMy43NTk5VjExLjAzOTlDNS42MDE1NiAxMC42ODY0IDUuMzE1MDIgMTAuMzk5OSA0Ljk2MTU2IDEwLjM5OTlaIiBmaWxsPSIjZmZmIi8%2BCjxwYXRoIGQ9Ik0xMy43NTg0IDEuNjAwMUgxMS4wMzg0QzEwLjY4NSAxLjYwMDEgMTAuMzk4NCAxLjg4NjY0IDEwLjM5ODQgMi4yNDAxVjQuOTYwMUMxMC4zOTg0IDUuMzEzNTYgMTAuNjg1IDUuNjAwMSAxMS4wMzg0IDUuNjAwMUgxMy43NTg0QzE0LjExMTkgNS42MDAxIDE0LjM5ODQgNS4zMTM1NiAxNC4zOTg0IDQuOTYwMVYyLjI0MDFDMTQuMzk4NCAxLjg4NjY0IDE0LjExMTkgMS42MDAxIDEzLjc1ODQgMS42MDAxWiIgZmlsbD0iI2ZmZiIvPgo8cGF0aCBkPSJNNCAxMkwxMiA0TDQgMTJaIiBmaWxsPSIjZmZmIi8%2BCjxwYXRoIGQ9Ik00IDEyTDEyIDQiIHN0cm9rZT0iI2ZmZiIgc3Ryb2tlLXdpZHRoPSIxLjUiIHN0cm9rZS1saW5lY2FwPSJyb3VuZCIvPgo8L3N2Zz4K&logoColor=ffffff" alt="zread"/></a>
+<a href="https://hub.docker.com/r/soulter/astrbot"><img alt="Docker pull" src="https://img.shields.io/docker/pulls/soulter/astrbot.svg?color=76bad9"/></a>
+<img src="https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fapi.soulter.top%2Fastrbot%2Fplugin-num&query=%24.result&suffix=%E4%B8%AA&label=%E6%8F%92%E4%BB%B6%E5%B8%82%E5%9C%BA&cacheSeconds=3600">
+<img src="https://gitcode.com/Soulter/AstrBot/star/badge.svg" href="https://gitcode.com/Soulter/AstrBot">
+</div>
+
+<br>
+
+<a href="https://astrbot.app/">主页</a> ｜
+<a href="https://astrbot.app/">文档</a> ｜
+<a href="https://blog.astrbot.app/">博客</a> ｜
+<a href="https://astrbot.featurebase.app/roadmap">路线图</a> ｜
+<a href="https://github.com/AstrBotDevs/AstrBot/issues">问题提交</a>
+<a href="mailto:community@astrbot.app">Email</a>
+
+</div>
+
+AstrBot 是一个开源的一站式 Agentic 个人和群聊助手，可在 QQ、Telegram、企业微信、飞书、钉钉、Slack、等数十款主流即时通讯软件上部署，此外还内置类似 OpenWebUI 的轻量化 ChatUI，为个人、开发者和团队打造可靠、可扩展的对话式智能基础设施。无论是个人 AI 伙伴、智能客服、自动化助手，还是企业知识库，AstrBot 都能在你的即时通讯软件平台的工作流中快速构建 AI 应用。
+
+![landingpage](https://github.com/user-attachments/assets/45fc5699-cddf-4e21-af35-13040706f6c0)
+
+## 主要功能
+
+1. 💯 免费 & 开源。
+2. ✨ AI 大模型对话，多模态，Agent，MCP，Skills，知识库，人格设定，自动压缩对话。
+3. 🤖 支持接入 Dify、阿里云百炼、Coze 等智能体平台。
+4. 🌐 多平台，支持 QQ、企业微信、飞书、钉钉、微信公众号、Telegram、Slack 以及[更多](#支持的消息平台)。
+5. 📦 插件扩展，已有 1000+ 个插件可一键安装。
+6. 🛡️ [Agent Sandbox](https://docs.astrbot.app/use/astrbot-agent-sandbox.html) 隔离化环境，安全地执行任何代码、调用 Shell、会话级资源复用。
+7. 💻 WebUI 支持。
+8. 🌈 Web ChatUI 支持，ChatUI 内置代理沙盒、网页搜索等。
+9. 🌐 国际化（i18n）支持。
+
+<br>
+
+<table align="center">
+  <tr align="center">
+    <th>💙 角色扮演 & 情感陪伴</th>
+    <th>✨ 主动式 Agent</th>
+    <th>🚀 通用 Agentic 能力</th>
+    <th>🧩 1000+ 社区插件</th>
+  </tr>
+  <tr>
+    <td align="center"><p align="center"><img width="984" height="1746" alt="99b587c5d35eea09d84f33e6cf6cfd4f" src="https://github.com/user-attachments/assets/89196061-3290-458d-b51f-afa178049f84" /></p></td>
+    <td align="center"><p align="center"><img width="976" height="1612" alt="c449acd838c41d0915cc08a3824025b1" src="https://github.com/user-attachments/assets/f75368b4-e022-41dc-a9e0-131c3e73e32e" /></p></td>
+    <td align="center"><p align="center"><img width="974" height="1732" alt="image" src="https://github.com/user-attachments/assets/e22a3968-87d7-4708-a7cd-e7f198c7c32e" /></p></td>
+    <td align="center"><p align="center"><img width="976" height="1734" alt="image" src="https://github.com/user-attachments/assets/0952b395-6b4a-432a-8a50-c294b7f89750" /></p></td>
+  </tr>
+</table>
+
+## 快速开始
+
+### 一键部署
+
+对于想快速体验 AstrBot、且熟悉命令行并能够自行安装 `uv` 环境的用户，我们推荐使用 `uv` 一键部署方式 ⚡️。
+
+```bash
+uv tool install astrbot
+astrbot init # 仅首次执行此命令以初始化环境
+astrbot
+```
+
+> 需要安装 [uv](https://docs.astral.sh/uv/)。
+
+> [!NOTE]
+> 对于 macOS 用户：由于 macOS 安全检查，首次运行 `astrbot` 命令可能需要较长时间（约 10-20 秒）。
+
+更新 `astrbot`：
+
+```bash
+uv tool upgrade astrbot
+```
+
+### Docker 部署
+
+对于熟悉容器、希望获得更稳定且更适合生产环境部署方式的用户，我们推荐使用 Docker / Docker Compose 部署 AstrBot。
+
+请参考官方文档 [使用 Docker 部署 AstrBot](https://astrbot.app/deploy/astrbot/docker.html#%E4%BD%BF%E7%94%A8-docker-%E9%83%A8%E7%BD%B2-astrbot)。
+
+### 在 雨云 上部署
+
+对于希望一键部署 AstrBot 且不想自行管理服务器的用户，我们推荐使用雨云的一键云部署服务 ☁️：
+
+[![Deploy on RainYun](https://rainyun-apps.cn-nb1.rains3.com/materials/deploy-on-rainyun-en.svg)](https://app.rainyun.com/apps/rca/store/5994?ref=NjU1ODg0)
+
+### 桌面客户端部署
+
+对于希望在桌面端使用 AstrBot、并以 ChatUI 为主要入口的用户，我们推荐使用 AstrBot App。
+
+前往 [AstrBot-desktop](https://github.com/AstrBotDevs/AstrBot-desktop) 下载并安装；该方式面向桌面使用，不推荐服务器场景。
+
+### 启动器部署
+
+同样在桌面端，希望快速部署并实现环境隔离多开的用户，我们推荐使用 AstrBot Launcher。
+
+前往 [AstrBot Launcher](https://github.com/Raven95676/astrbot-launcher) 下载并安装。
+
+### 在 Replit 上部署
+
+Replit 部署由社区维护，适合在线演示和轻量试用场景。
+
+[![Run on Repl.it](https://repl.it/badge/github/AstrBotDevs/AstrBot)](https://repl.it/github/AstrBotDevs/AstrBot)
+
+### AUR
+
+AUR 方式面向 Arch Linux 用户，适合希望通过系统包管理器安装 AstrBot 的场景。
+
+在终端执行下方命令安装 `astrbot-git` 包，安装完成后即可启动使用。
+
+```bash
+yay -S astrbot-git
+```
+
+**更多部署方式**
+
+若你需要面板化或更高自定义部署，可参考 [宝塔面板](https://astrbot.app/deploy/astrbot/btpanel.html)（BT Panel 应用商店安装）、[1Panel](https://astrbot.app/deploy/astrbot/1panel.html)（1Panel 应用商店安装）、[CasaOS](https://astrbot.app/deploy/astrbot/casaos.html)（NAS / 家庭服务器可视化部署）和 [手动部署](https://astrbot.app/deploy/astrbot/cli.html)（基于源码与 `uv` 的完整自定义安装）。
+
+## 支持的消息平台
+
+将 AstrBot 连接到你常用的聊天平台。
+
+| 平台 | 维护方 |
+|---------|---------------|
+| **QQ** | 官方维护 |
+| **OneBot v11** | 官方维护 |
+| **Telegram** | 官方维护 |
+| **企微应用 & 企微智能机器人** | 官方维护 |
+| **微信客服 & 微信公众号** | 官方维护 |
+| **飞书** | 官方维护 |
+| **钉钉** | 官方维护 |
+| **Slack** | 官方维护 |
+| **Discord** | 官方维护 |
+| **LINE** | 官方维护 |
+| **Satori** | 官方维护 |
+| **Misskey** | 官方维护 |
+| **Whatsapp (将支持)** | 官方维护 |
+| [**Matrix**](https://github.com/stevessr/astrbot_plugin_matrix_adapter) | 社区维护 |
+| [**KOOK**](https://github.com/wuyan1003/astrbot_plugin_kook_adapter) | 社区维护 |
+| [**VoceChat**](https://github.com/HikariFroya/astrbot_plugin_vocechat) | 社区维护 |
+
+## 支持的模型提供商
+
+| 提供商 | 类型 |
+|---------|---------------|
+| 自定义 | 任何 OpenAI API 兼容的服务 |
+| OpenAI | LLM |
+| Anthropic | LLM |
+| Google Gemini | LLM |
+| Moonshot AI | LLM |
+| 智谱 AI | LLM |
+| DeepSeek | LLM |
+| Ollama (本地部署) | LLM |
+| LM Studio (本地部署) | LLM |
+| [AIHubMix](https://aihubmix.com/?aff=4bfH) | LLM (API 网关, 支持所有模型) |
+| [优云智算](https://www.compshare.cn/?ytag=GPU_YY-gh_astrbot&referral_code=FV7DcGowN4hB5UuXKgpE74) | LLM (API 网关, 支持所有模型) |
+| [硅基流动](https://docs.siliconflow.cn/cn/usercases/use-siliconcloud-in-astrbot) | LLM (API 网关, 支持所有模型)  |
+| [PPIO 派欧云](https://ppio.com/user/register?invited_by=AIOONE) | LLM (API 网关, 支持所有模型) |
+| [302.AI](https://share.302.ai/rr1M3l) | LLM (API 网关, 支持所有模型)|
+| [小马算力](https://www.tokenpony.cn/3YPyf) | LLM (API 网关, 支持所有模型)|
+| ModelScope | LLM |
+| OneAPI | LLM |
+| Dify | LLMOps 平台 |
+| 阿里云百炼应用 | LLMOps 平台 |
+| Coze | LLMOps 平台 |
+| OpenAI Whisper | 语音转文本 |
+| SenseVoice | 语音转文本 |
+| OpenAI TTS | 文本转语音 |
+| Gemini TTS | 文本转语音 |
+| GPT-Sovits-Inference | 文本转语音 |
+| GPT-Sovits | 文本转语音 |
+| FishAudio | 文本转语音 |
+| Edge TTS | 文本转语音 |
+| 阿里云百炼 TTS | 文本转语音 |
+| Azure TTS | 文本转语音 |
+| Minimax TTS | 文本转语音 |
+| 火山引擎 TTS | 文本转语音 |
+
+## ❤️ 贡献
+
+欢迎任何 Issues/Pull Requests！只需要将你的更改提交到此项目 ：)
+
+### 如何贡献
+
+你可以通过查看问题或帮助审核 PR（拉取请求）来贡献。任何问题或 PR 都欢迎参与，以促进社区贡献。当然，这些只是建议，你可以以任何方式进行贡献。对于新功能的添加，请先通过 Issue 讨论。
+
+### 开发环境
+
+AstrBot 使用 `ruff` 进行代码格式化和检查。
+
+```bash
+git clone https://github.com/AstrBotDevs/AstrBot
+pip install pre-commit
+pre-commit install
+```
+
+## 🌍 社区
+
+### QQ 群组
+
+- 9 群: 1076659624 (新)
+- 10 群: 1078079676 (新)
+- 1 群：322154837
+- 3 群：630166526
+- 5 群：822130018
+- 6 群：753075035
+- 7 群：743746109
+- 8 群：1030353265
+- 开发者群（偏闲聊吹水）：975206796
+- 开发者群（正式）：1039761811
+
+### Discord 频道
+
+- [Discord](https://discord.gg/hAVk6tgV36)
+
+## ❤️ Special Thanks
+
+特别感谢所有 Contributors 和插件开发者对 AstrBot 的贡献 ❤️
+
+<a href="https://github.com/AstrBotDevs/AstrBot/graphs/contributors">
+  <img src="https://contrib.rocks/image?repo=AstrBotDevs/AstrBot&max=200&columns=14" />
+</a>
+
+此外，本项目的诞生离不开以下开源项目的帮助：
+
+- [NapNeko/NapCatQQ](https://github.com/NapNeko/NapCatQQ) - 伟大的猫猫框架
+
+开源项目友情链接：
+
+- [NoneBot2](https://github.com/nonebot/nonebot2) - 优秀的 Python 异步 ChatBot 框架
+- [Koishi](https://github.com/koishijs/koishi) - 优秀的 Node.js ChatBot 框架
+- [MaiBot](https://github.com/Mai-with-u/MaiBot) - 优秀的拟人化 AI ChatBot
+- [nekro-agent](https://github.com/KroMiose/nekro-agent) - 优秀的 Agent ChatBot
+- [LangBot](https://github.com/langbot-app/LangBot) - 优秀的多平台 AI ChatBot
+- [ChatLuna](https://github.com/ChatLunaLab/chatluna) - 优秀的多平台 AI ChatBot Koishi 插件
+- [Operit AI](https://github.com/AAswordman/Operit) - 优秀的 AI 智能助手 Android APP
+
+## ⭐ Star History
+
+> [!TIP]
+> 如果本项目对您的生活 / 工作产生了帮助，或者您关注本项目的未来发展，请给项目 Star，这是我们维护这个开源项目的动力 <3
+
+<div align="center">
+
+[![Star History Chart](https://api.star-history.com/svg?repos=astrbotdevs/astrbot&type=Date)](https://star-history.com/#astrbotdevs/astrbot&Date)
+
+</div>
+
+<div align="center">
+
+_陪伴与能力从来不应该是对立面。我们希望创造的是一个既能理解情绪、给予陪伴，也能可靠完成工作的机器人。_
+
+_私は、高性能ですから!_
+
+<img src="https://files.astrbot.app/watashiwa-koseino-desukara.gif" width="100"/>
+
+</div>
@@ -20,7 +20,17 @@ from astrbot.core.star.register import (
 )
 from astrbot.core.star.register import register_on_llm_request as on_llm_request
 from astrbot.core.star.register import register_on_llm_response as on_llm_response
+from astrbot.core.star.register import (
+    register_on_llm_tool_respond as on_llm_tool_respond,
+)
 from astrbot.core.star.register import register_on_platform_loaded as on_platform_loaded
+from astrbot.core.star.register import register_on_plugin_error as on_plugin_error
+from astrbot.core.star.register import register_on_plugin_loaded as on_plugin_loaded
+from astrbot.core.star.register import register_on_plugin_unloaded as on_plugin_unloaded
+from astrbot.core.star.register import register_on_using_llm_tool as on_using_llm_tool
+from astrbot.core.star.register import (
+    register_on_waiting_llm_request as on_waiting_llm_request,
+)
 from astrbot.core.star.register import register_permission_type as permission_type
 from astrbot.core.star.register import (
    register_platform_adapter_type as platform_adapter_type,
@@ -45,8 +55,14 @@ __all__ = [
    "on_decorating_result",
    "on_llm_request",
    "on_llm_response",
+    "on_plugin_error",
+    "on_plugin_loaded",
+    "on_plugin_unloaded",
    "on_platform_loaded",
+    "on_waiting_llm_request",
    "permission_type",
    "platform_adapter_type",
    "regex",
+    "on_using_llm_tool",
+    "on_llm_tool_respond",
 ]
@@ -6,9 +6,9 @@ from collections import defaultdict
 from astrbot import logger
 from astrbot.api import star
 from astrbot.api.event import AstrMessageEvent
-from astrbot.api.message_components import Image, Plain
+from astrbot.api.message_components import At, Image, Plain
 from astrbot.api.platform import MessageType
-from astrbot.api.provider import Provider, ProviderRequest
+from astrbot.api.provider import LLMResponse, Provider, ProviderRequest
 from astrbot.core.astrbot_config_mgr import AstrBotConfigManager

 """
@@ -17,7 +17,7 @@ from astrbot.core.astrbot_config_mgr import AstrBotConfigManager


 class LongTermMemory:
-    def __init__(self, acm: AstrBotConfigManager, context: star.Context):
+    def __init__(self, acm: AstrBotConfigManager, context: star.Context) -> None:
        self.acm = acm
        self.context = context
        self.session_chats = defaultdict(list)
@@ -30,16 +30,13 @@ class LongTermMemory:
        except BaseException as e:
            logger.error(e)
            max_cnt = 300
-        image_caption = (
-            True
-            if cfg["provider_settings"]["default_image_caption_provider_id"]
-            and cfg["provider_ltm_settings"]["image_caption"]
-            else False
-        )
        image_caption_prompt = cfg["provider_settings"]["image_caption_prompt"]
-        image_caption_provider_id = cfg["provider_settings"][
-            "default_image_caption_provider_id"
-        ]
+        image_caption_provider_id = cfg["provider_ltm_settings"].get(
+            "image_caption_provider_id"
+        )
+        image_caption = cfg["provider_ltm_settings"]["image_caption"] and bool(
+            image_caption_provider_id
+        )
        active_reply = cfg["provider_ltm_settings"]["active_reply"]
        enable_active_reply = active_reply.get("enable", False)
        ar_method = active_reply["method"]
@@ -114,7 +111,7 @@ class LongTermMemory:

        return False

-    async def handle_message(self, event: AstrMessageEvent):
+    async def handle_message(self, event: AstrMessageEvent) -> None:
        """仅支持群聊"""
        if event.get_message_type() == MessageType.GROUP_MESSAGE:
            datetime_str = datetime.datetime.now().strftime("%H:%M:%S")
@@ -142,6 +139,8 @@ class LongTermMemory:
                            logger.error(f"获取图片描述失败: {e}")
                    else:
                        parts.append(" [Image]")
+                elif isinstance(comp, At):
+                    parts.append(f" [At: {comp.name}]")

            final_message = "".join(parts)
            logger.debug(f"ltm | {event.unified_msg_origin} | {final_message}")
@@ -149,7 +148,7 @@ class LongTermMemory:
            if len(self.session_chats[event.unified_msg_origin]) > cfg["max_cnt"]:
                self.session_chats[event.unified_msg_origin].pop(0)

-    async def on_req_llm(self, event: AstrMessageEvent, req: ProviderRequest):
+    async def on_req_llm(self, event: AstrMessageEvent, req: ProviderRequest) -> None:
        """当触发 LLM 请求前，调用此方法修改 req"""
        if event.unified_msg_origin not in self.session_chats:
            return
@@ -159,8 +158,12 @@ class LongTermMemory:
        cfg = self.cfg(event)
        if cfg["enable_active_reply"]:
            prompt = req.prompt
-            req.prompt = f"You are now in a chatroom. The chat history is as follows:\n{chats_str}"
-            req.prompt += f"\nNow, a new message is coming: `{prompt}`. Please react to it. Only output your response and do not output any other information."
+            req.prompt = (
+                f"You are now in a chatroom. The chat history is as follows:\n{chats_str}"
+                f"\nNow, a new message is coming: `{prompt}`. "
+                "Please react to it. Only output your response and do not output any other information. "
+                "You MUST use the SAME language as the chatroom is using."
+            )
            req.contexts = []  # 清空上下文，当使用了主动回复，所有聊天记录都在一个prompt中。
        else:
            req.system_prompt += (
@@ -168,13 +171,17 @@ class LongTermMemory:
            )
            req.system_prompt += chats_str

-    async def after_req_llm(self, event: AstrMessageEvent):
+    async def after_req_llm(
+        self, event: AstrMessageEvent, llm_resp: LLMResponse
+    ) -> None:
        if event.unified_msg_origin not in self.session_chats:
            return

-        if event.get_result() and event.get_result().is_llm_result():
-            final_message = f"[You/{datetime.datetime.now().strftime('%H:%M:%S')}]: {event.get_result().get_plain_text()}"
-            logger.debug(f"ltm | {event.unified_msg_origin} | {final_message}")
+        if llm_resp.completion_text:
+            final_message = f"[You/{datetime.datetime.now().strftime('%H:%M:%S')}]: {llm_resp.completion_text}"
+            logger.debug(
+                f"Recorded AI response: {event.unified_msg_origin} | {final_message}"
+            )
            self.session_chats[event.unified_msg_origin].append(final_message)
            cfg = self.cfg(event)
            if len(self.session_chats[event.unified_msg_origin]) > cfg["max_cnt"]:
@@ -0,0 +1,118 @@
+import traceback
+
+from astrbot.api import star
+from astrbot.api.event import AstrMessageEvent, filter
+from astrbot.api.message_components import Image, Plain
+from astrbot.api.provider import LLMResponse, ProviderRequest
+from astrbot.core import logger
+
+from .long_term_memory import LongTermMemory
+
+
+class Main(star.Star):
+    def __init__(self, context: star.Context) -> None:
+        self.context = context
+        self.ltm = None
+        try:
+            self.ltm = LongTermMemory(self.context.astrbot_config_mgr, self.context)
+        except BaseException as e:
+            logger.error(f"聊天增强 err: {e}")
+
+    def ltm_enabled(self, event: AstrMessageEvent):
+        ltmse = self.context.get_config(umo=event.unified_msg_origin)[
+            "provider_ltm_settings"
+        ]
+        return ltmse["group_icl_enable"] or ltmse["active_reply"]["enable"]
+
+    @filter.platform_adapter_type(filter.PlatformAdapterType.ALL)
+    async def on_message(self, event: AstrMessageEvent):
+        """群聊记忆增强"""
+        has_image_or_plain = False
+        for comp in event.message_obj.message:
+            if isinstance(comp, Plain) or isinstance(comp, Image):
+                has_image_or_plain = True
+                break
+
+        if self.ltm_enabled(event) and self.ltm and has_image_or_plain:
+            need_active = await self.ltm.need_active_reply(event)
+
+            group_icl_enable = self.context.get_config()["provider_ltm_settings"][
+                "group_icl_enable"
+            ]
+            if group_icl_enable:
+                """记录对话"""
+                try:
+                    await self.ltm.handle_message(event)
+                except BaseException as e:
+                    logger.error(e)
+
+            if need_active:
+                """主动回复"""
+                provider = self.context.get_using_provider(event.unified_msg_origin)
+                if not provider:
+                    logger.error("未找到任何 LLM 提供商。请先配置。无法主动回复")
+                    return
+                try:
+                    conv = None
+                    session_curr_cid = await self.context.conversation_manager.get_curr_conversation_id(
+                        event.unified_msg_origin,
+                    )
+
+                    if not session_curr_cid:
+                        logger.error(
+                            "当前未处于对话状态，无法主动回复，请确保 平台设置->会话隔离(unique_session) 未开启，并使用 /switch 序号 切换或者 /new 创建一个会话。",
+                        )
+                        return
+
+                    conv = await self.context.conversation_manager.get_conversation(
+                        event.unified_msg_origin,
+                        session_curr_cid,
+                    )
+
+                    prompt = event.message_str
+
+                    if not conv:
+                        logger.error("未找到对话，无法主动回复")
+                        return
+
+                    yield event.request_llm(
+                        prompt=prompt,
+                        session_id=event.session_id,
+                        conversation=conv,
+                    )
+                except BaseException as e:
+                    logger.error(traceback.format_exc())
+                    logger.error(f"主动回复失败: {e}")
+
+    @filter.on_llm_request()
+    async def decorate_llm_req(
+        self, event: AstrMessageEvent, req: ProviderRequest
+    ) -> None:
+        """在请求 LLM 前注入人格信息、Identifier、时间、回复内容等 System Prompt"""
+        if self.ltm and self.ltm_enabled(event):
+            try:
+                await self.ltm.on_req_llm(event, req)
+            except BaseException as e:
+                logger.error(f"ltm: {e}")
+
+    @filter.on_llm_response()
+    async def record_llm_resp_to_ltm(
+        self, event: AstrMessageEvent, resp: LLMResponse
+    ) -> None:
+        """在 LLM 响应后记录对话"""
+        if self.ltm and self.ltm_enabled(event):
+            try:
+                await self.ltm.after_req_llm(event, resp)
+            except Exception as e:
+                logger.error(f"ltm: {e}")
+
+    @filter.after_message_sent()
+    async def after_message_sent(self, event: AstrMessageEvent) -> None:
+        """消息发送后处理"""
+        if self.ltm and self.ltm_enabled(event):
+            try:
+                clean_session = event.get_extra("_clean_ltm_session", False)
+                if clean_session:
+                    await self.ltm.remove_session(event)
+            except Exception as e:
+                logger.error(f"ltm: {e}")
@@ -0,0 +1,4 @@
+name: astrbot
+desc: AstrBot 自带插件，包含人格注入、思考内容注入、群聊上下文感知等功能的实现，禁用后将无法使用这些功能。
+author: Soulter
+version: 4.1.0
@@ -11,7 +11,6 @@ from .provider import ProviderCommands
 from .setunset import SetUnsetCommands
 from .sid import SIDCommand
 from .t2i import T2ICommand
-from .tool import ToolCommands
 from .tts import TTSCommand

 __all__ = [
@@ -27,5 +26,4 @@ __all__ = [
    "SetUnsetCommands",
    "T2ICommand",
    "TTSCommand",
-    "ToolCommands",
 ]
@@ -5,10 +5,10 @@ from astrbot.core.utils.io import download_dashboard


 class AdminCommands:
-    def __init__(self, context: star.Context):
+    def __init__(self, context: star.Context) -> None:
        self.context = context

-    async def op(self, event: AstrMessageEvent, admin_id: str = ""):
+    async def op(self, event: AstrMessageEvent, admin_id: str = "") -> None:
        """授权管理员。op <admin_id>"""
        if not admin_id:
            event.set_result(
@@ -21,7 +21,7 @@ class AdminCommands:
        self.context.get_config().save_config()
        event.set_result(MessageEventResult().message("授权成功。"))

-    async def deop(self, event: AstrMessageEvent, admin_id: str = ""):
+    async def deop(self, event: AstrMessageEvent, admin_id: str = "") -> None:
        """取消授权管理员。deop <admin_id>"""
        if not admin_id:
            event.set_result(
@@ -39,7 +39,7 @@ class AdminCommands:
                MessageEventResult().message("此用户 ID 不在管理员名单内。"),
            )

-    async def wl(self, event: AstrMessageEvent, sid: str = ""):
+    async def wl(self, event: AstrMessageEvent, sid: str = "") -> None:
        """添加白名单。wl <sid>"""
        if not sid:
            event.set_result(
@@ -53,7 +53,7 @@ class AdminCommands:
        cfg.save_config()
        event.set_result(MessageEventResult().message("添加白名单成功。"))

-    async def dwl(self, event: AstrMessageEvent, sid: str = ""):
+    async def dwl(self, event: AstrMessageEvent, sid: str = "") -> None:
        """删除白名单。dwl <sid>"""
        if not sid:
            event.set_result(
@@ -70,7 +70,8 @@ class AdminCommands:
        except ValueError:
            event.set_result(MessageEventResult().message("此 SID 不在白名单内。"))

-    async def update_dashboard(self, event: AstrMessageEvent):
+    async def update_dashboard(self, event: AstrMessageEvent) -> None:
+        """更新管理面板"""
        await event.send(MessageChain().message("正在尝试更新管理面板..."))
        await download_dashboard(version=f"v{VERSION}", latest=False)
        await event.send(MessageChain().message("管理面板更新完成。"))
@@ -11,10 +11,10 @@ from .utils.rst_scene import RstScene


 class AlterCmdCommands(CommandParserMixin):
-    def __init__(self, context: star.Context):
+    def __init__(self, context: star.Context) -> None:
        self.context = context

-    async def update_reset_permission(self, scene_key: str, perm_type: str):
+    async def update_reset_permission(self, scene_key: str, perm_type: str) -> None:
        """更新reset命令在特定场景下的权限设置"""
        from astrbot.api import sp

@@ -26,7 +26,7 @@ class AlterCmdCommands(CommandParserMixin):
        alter_cmd_cfg["astrbot"] = plugin_cfg
        await sp.global_put("alter_cmd", alter_cmd_cfg)

-    async def alter_cmd(self, event: AstrMessageEvent):
+    async def alter_cmd(self, event: AstrMessageEvent) -> None:
        token = self.parse_commands(event.message_str)
        if token.len < 3:
            await event.send(
@@ -1,20 +1,29 @@
 import datetime

-from astrbot.api import logger, sp, star
+from astrbot.api import sp, star
 from astrbot.api.event import AstrMessageEvent, MessageEventResult
-from astrbot.core.platform.astr_message_event import MessageSesion
+from astrbot.core.agent.runners.deerflow.constants import (
+    DEERFLOW_PROVIDER_TYPE,
+    DEERFLOW_THREAD_ID_KEY,
+)
+from astrbot.core.platform.astr_message_event import MessageSession
 from astrbot.core.platform.message_type import MessageType
-from astrbot.core.provider.sources.coze_source import ProviderCoze
-from astrbot.core.provider.sources.dify_source import ProviderDify
+from astrbot.core.utils.active_event_registry import active_event_registry

-from ..long_term_memory import LongTermMemory
 from .utils.rst_scene import RstScene

+THIRD_PARTY_AGENT_RUNNER_KEY = {
+    "dify": "dify_conversation_id",
+    "coze": "coze_conversation_id",
+    "dashscope": "dashscope_conversation_id",
+    DEERFLOW_PROVIDER_TYPE: DEERFLOW_THREAD_ID_KEY,
+}
+THIRD_PARTY_AGENT_RUNNER_STR = ", ".join(THIRD_PARTY_AGENT_RUNNER_KEY.keys())
+

 class ConversationCommands:
-    def __init__(self, context: star.Context, ltm: LongTermMemory | None = None):
+    def __init__(self, context: star.Context) -> None:
        self.context = context
-        self.ltm = ltm

    async def _get_current_persona_id(self, session_id):
        curr = await self.context.conversation_manager.get_curr_conversation_id(
@@ -26,21 +35,15 @@ class ConversationCommands:
            session_id,
            curr,
        )
+        if not conv:
+            return None
        return conv.persona_id

-    def ltm_enabled(self, event: AstrMessageEvent):
-        if not self.ltm:
-            return False
-        ltmse = self.context.get_config(umo=event.unified_msg_origin)[
-            "provider_ltm_settings"
-        ]
-        return ltmse["group_icl_enable"] or ltmse["active_reply"]["enable"]
-
-    async def reset(self, message: AstrMessageEvent):
+    async def reset(self, message: AstrMessageEvent) -> None:
        """重置 LLM 会话"""
-        is_unique_session = self.context.get_config()["platform_settings"][
-            "unique_session"
-        ]
+        umo = message.unified_msg_origin
+        cfg = self.context.get_config(umo=message.unified_msg_origin)
+        is_unique_session = cfg["platform_settings"]["unique_session"]
        is_group = bool(message.get_group_id())

        scene = RstScene.get_scene(is_group, is_unique_session)
@@ -63,28 +66,24 @@ class ConversationCommands:
            )
            return

-        if not self.context.get_using_provider(message.unified_msg_origin):
+        agent_runner_type = cfg["provider_settings"]["agent_runner_type"]
+        if agent_runner_type in THIRD_PARTY_AGENT_RUNNER_KEY:
+            active_event_registry.stop_all(umo, exclude=message)
+            await sp.remove_async(
+                scope="umo",
+                scope_id=umo,
+                key=THIRD_PARTY_AGENT_RUNNER_KEY[agent_runner_type],
+            )
+            message.set_result(MessageEventResult().message("重置对话成功。"))
+            return
+
+        if not self.context.get_using_provider(umo):
            message.set_result(
                MessageEventResult().message("未找到任何 LLM 提供商。请先配置。"),
            )
            return

-        provider = self.context.get_using_provider(message.unified_msg_origin)
-        if provider and provider.meta().type in ["dify", "coze"]:
-            assert isinstance(provider, (ProviderDify, ProviderCoze)), (
-                "provider type is not dify or coze"
-            )
-            await provider.forget(message.unified_msg_origin)
-            message.set_result(
-                MessageEventResult().message(
-                    "已重置当前 Dify / Coze 会话，新聊天将更换到新的会话。",
-                ),
-            )
-            return
-
-        cid = await self.context.conversation_manager.get_curr_conversation_id(
-            message.unified_msg_origin,
-        )
+        cid = await self.context.conversation_manager.get_curr_conversation_id(umo)

        if not cid:
            message.set_result(
@@ -94,20 +93,45 @@ class ConversationCommands:
            )
            return

+        active_event_registry.stop_all(umo, exclude=message)
+
        await self.context.conversation_manager.update_conversation(
-            message.unified_msg_origin,
+            umo,
            cid,
            [],
        )

-        ret = "清除会话 LLM 聊天历史成功。"
-        if self.ltm and self.ltm_enabled(message):
-            cnt = await self.ltm.remove_session(event=message)
-            ret += f"\n聊天增强: 已清除 {cnt} 条聊天记录。"
+        ret = "清除聊天历史成功！"
+
+        message.set_extra("_clean_ltm_session", True)

        message.set_result(MessageEventResult().message(ret))

-    async def his(self, message: AstrMessageEvent, page: int = 1):
+    async def stop(self, message: AstrMessageEvent) -> None:
+        """停止当前会话正在运行的 Agent"""
+        cfg = self.context.get_config(umo=message.unified_msg_origin)
+        agent_runner_type = cfg["provider_settings"]["agent_runner_type"]
+        umo = message.unified_msg_origin
+
+        if agent_runner_type in THIRD_PARTY_AGENT_RUNNER_KEY:
+            stopped_count = active_event_registry.stop_all(umo, exclude=message)
+        else:
+            stopped_count = active_event_registry.request_agent_stop_all(
+                umo,
+                exclude=message,
+            )
+
+        if stopped_count > 0:
+            message.set_result(
+                MessageEventResult().message(
+                    f"已请求停止 {stopped_count} 个运行中的任务。"
+                )
+            )
+            return
+
+        message.set_result(MessageEventResult().message("当前会话没有运行中的任务。"))
+
+    async def his(self, message: AstrMessageEvent, page: int = 1) -> None:
        """查看对话记录"""
        if not self.context.get_using_provider(message.unified_msg_origin):
            message.set_result(
@@ -150,31 +174,16 @@ class ConversationCommands:

        message.set_result(MessageEventResult().message(ret).use_t2i(False))

-    async def convs(self, message: AstrMessageEvent, page: int = 1):
+    async def convs(self, message: AstrMessageEvent, page: int = 1) -> None:
        """查看对话列表"""
-        provider = self.context.get_using_provider(message.unified_msg_origin)
-        if provider and provider.meta().type == "dify":
-            """原有的Dify处理逻辑保持不变"""
-            parts = ["Dify 对话列表:\n"]
-            assert isinstance(provider, ProviderDify)
-            data = await provider.api_client.get_chat_convs(message.unified_msg_origin)
-            idx = 1
-            for conv in data["data"]:
-                ts_h = datetime.datetime.fromtimestamp(conv["updated_at"]).strftime(
-                    "%m-%d %H:%M",
-                )
-                parts.append(
-                    f"{idx}. {conv['name']}({conv['id'][:4]})\n  上次更新:{ts_h}\n"
-                )
-                idx += 1
-            if idx == 1:
-                parts.append("没有找到任何对话。")
-            dify_cid = provider.conversation_ids.get(message.unified_msg_origin, None)
-            parts.append(
-                f"\n\n用户: {message.unified_msg_origin}\n当前对话: {dify_cid}\n使用 /switch <序号> 切换对话。"
+        cfg = self.context.get_config(umo=message.unified_msg_origin)
+        agent_runner_type = cfg["provider_settings"]["agent_runner_type"]
+        if agent_runner_type in THIRD_PARTY_AGENT_RUNNER_KEY:
+            message.set_result(
+                MessageEventResult().message(
+                    f"{THIRD_PARTY_AGENT_RUNNER_STR} 对话列表功能暂不支持。",
+                ),
            )
-            ret = "".join(parts)
-            message.set_result(MessageEventResult().message(ret))
            return

        size_per_page = 6
@@ -202,16 +211,33 @@ class ConversationCommands:
            _titles[conv.cid] = title

        """遍历分页后的对话生成列表显示"""
+        provider_settings = cfg.get("provider_settings", {})
+        platform_name = message.get_platform_name()
        for conv in conversations_paged:
-            persona_id = conv.persona_id
-            if not persona_id or persona_id == "[%None]":
-                persona = await self.context.persona_manager.get_default_persona_v3(
-                    umo=message.unified_msg_origin,
-                )
-                persona_id = persona["name"]
+            (
+                persona_id,
+                _,
+                force_applied_persona_id,
+                _,
+            ) = await self.context.persona_manager.resolve_selected_persona(
+                umo=message.unified_msg_origin,
+                conversation_persona_id=conv.persona_id,
+                platform_name=platform_name,
+                provider_settings=provider_settings,
+            )
+            if persona_id == "[%None]":
+                persona_name = "无"
+            elif persona_id:
+                persona_name = persona_id
+            else:
+                persona_name = "无"
+
+            if force_applied_persona_id:
+                persona_name = f"{persona_name} (自定义规则)"
+
            title = _titles.get(conv.cid, "新对话")
            parts.append(
-                f"{global_index}. {title}({conv.cid[:4]})\n  人格情景: {persona_id}\n  上次更新: {datetime.datetime.fromtimestamp(conv.updated_at).strftime('%m-%d %H:%M')}\n"
+                f"{global_index}. {title}({conv.cid[:4]})\n  人格情景: {persona_name}\n  上次更新: {datetime.datetime.fromtimestamp(conv.updated_at).strftime('%m-%d %H:%M')}\n"
            )
            global_index += 1

@@ -227,9 +253,8 @@ class ConversationCommands:
        else:
            ret += "\n当前对话: 无"

-        unique_session = self.context.get_config()["platform_settings"][
-            "unique_session"
-        ]
+        cfg = self.context.get_config(umo=message.unified_msg_origin)
+        unique_session = cfg["platform_settings"]["unique_session"]
        if unique_session:
            ret += "\n会话隔离粒度: 个人"
        else:
@@ -241,19 +266,21 @@ class ConversationCommands:
        message.set_result(MessageEventResult().message(ret).use_t2i(False))
        return

-    async def new_conv(self, message: AstrMessageEvent):
+    async def new_conv(self, message: AstrMessageEvent) -> None:
        """创建新对话"""
-        provider = self.context.get_using_provider(message.unified_msg_origin)
-        if provider and provider.meta().type in ["dify", "coze"]:
-            assert isinstance(provider, (ProviderDify, ProviderCoze)), (
-                "provider type is not dify or coze"
-            )
-            await provider.forget(message.unified_msg_origin)
-            message.set_result(
-                MessageEventResult().message("成功，下次聊天将是新对话。"),
+        cfg = self.context.get_config(umo=message.unified_msg_origin)
+        agent_runner_type = cfg["provider_settings"]["agent_runner_type"]
+        if agent_runner_type in THIRD_PARTY_AGENT_RUNNER_KEY:
+            active_event_registry.stop_all(message.unified_msg_origin, exclude=message)
+            await sp.remove_async(
+                scope="umo",
+                scope_id=message.unified_msg_origin,
+                key=THIRD_PARTY_AGENT_RUNNER_KEY[agent_runner_type],
            )
+            message.set_result(MessageEventResult().message("已创建新对话。"))
            return

+        active_event_registry.stop_all(message.unified_msg_origin, exclude=message)
        cpersona = await self._get_current_persona_id(message.unified_msg_origin)
        cid = await self.context.conversation_manager.new_conversation(
            message.unified_msg_origin,
@@ -261,32 +288,17 @@ class ConversationCommands:
            persona_id=cpersona,
        )

-        # 长期记忆
-        if self.ltm and self.ltm_enabled(message):
-            try:
-                await self.ltm.remove_session(event=message)
-            except Exception as e:
-                logger.error(f"清理聊天增强记录失败: {e}")
+        message.set_extra("_clean_ltm_session", True)

        message.set_result(
            MessageEventResult().message(f"切换到新对话: 新对话({cid[:4]})。"),
        )

-    async def groupnew_conv(self, message: AstrMessageEvent, sid: str = ""):
+    async def groupnew_conv(self, message: AstrMessageEvent, sid: str = "") -> None:
        """创建新群聊对话"""
-        provider = self.context.get_using_provider(message.unified_msg_origin)
-        if provider and provider.meta().type in ["dify", "coze"]:
-            assert isinstance(provider, (ProviderDify, ProviderCoze)), (
-                "provider type is not dify or coze"
-            )
-            await provider.forget(message.unified_msg_origin)
-            message.set_result(
-                MessageEventResult().message("成功，下次聊天将是新对话。"),
-            )
-            return
        if sid:
            session = str(
-                MessageSesion(
+                MessageSession(
                    platform_name=message.platform_meta.id,
                    message_type=MessageType("GroupMessage"),
                    session_id=sid,
@@ -313,7 +325,7 @@ class ConversationCommands:
        self,
        message: AstrMessageEvent,
        index: int | None = None,
-    ):
+    ) -> None:
        """通过 /ls 前面的序号切换对话"""
        if not isinstance(index, int):
            message.set_result(
@@ -321,31 +333,6 @@ class ConversationCommands:
            )
            return

-        provider = self.context.get_using_provider(message.unified_msg_origin)
-        if provider and provider.meta().type == "dify":
-            assert isinstance(provider, ProviderDify), "provider type is not dify"
-            data = await provider.api_client.get_chat_convs(message.unified_msg_origin)
-            if not data["data"]:
-                message.set_result(MessageEventResult().message("未找到任何对话。"))
-                return
-            selected_conv = None
-            if index is not None:
-                try:
-                    selected_conv = data["data"][index - 1]
-                except IndexError:
-                    message.set_result(
-                        MessageEventResult().message("对话序号错误，请使用 /ls 查看"),
-                    )
-                    return
-            else:
-                selected_conv = data["data"][0]
-            ret = (
-                f"Dify 切换到对话: {selected_conv['name']}({selected_conv['id'][:4]})。"
-            )
-            provider.conversation_ids[message.unified_msg_origin] = selected_conv["id"]
-            message.set_result(MessageEventResult().message(ret))
-            return
-
        if index is None:
            message.set_result(
                MessageEventResult().message(
@@ -373,35 +360,22 @@ class ConversationCommands:
                ),
            )

-    async def rename_conv(self, message: AstrMessageEvent, new_name: str = ""):
+    async def rename_conv(self, message: AstrMessageEvent, new_name: str = "") -> None:
        """重命名对话"""
        if not new_name:
            message.set_result(MessageEventResult().message("请输入新的对话名称。"))
            return
-
-        provider = self.context.get_using_provider(message.unified_msg_origin)
-
-        if provider and provider.meta().type == "dify":
-            assert isinstance(provider, ProviderDify)
-            cid = provider.conversation_ids.get(message.unified_msg_origin, None)
-            if not cid:
-                message.set_result(MessageEventResult().message("未找到当前对话。"))
-                return
-            await provider.api_client.rename(cid, new_name, message.unified_msg_origin)
-            message.set_result(MessageEventResult().message("重命名对话成功。"))
-            return
-
        await self.context.conversation_manager.update_conversation_title(
            message.unified_msg_origin,
            new_name,
        )
        message.set_result(MessageEventResult().message("重命名对话成功。"))

-    async def del_conv(self, message: AstrMessageEvent):
+    async def del_conv(self, message: AstrMessageEvent) -> None:
        """删除当前对话"""
-        is_unique_session = self.context.get_config()["platform_settings"][
-            "unique_session"
-        ]
+        umo = message.unified_msg_origin
+        cfg = self.context.get_config(umo=umo)
+        is_unique_session = cfg["platform_settings"]["unique_session"]
        if message.get_group_id() and not is_unique_session and message.role != "admin":
            # 群聊，没开独立会话，发送人不是管理员
            message.set_result(
@@ -411,26 +385,19 @@ class ConversationCommands:
            )
            return

-        provider = self.context.get_using_provider(message.unified_msg_origin)
-        if provider and provider.meta().type == "dify":
-            assert isinstance(provider, ProviderDify)
-            dify_cid = provider.conversation_ids.pop(message.unified_msg_origin, None)
-            if dify_cid:
-                await provider.api_client.delete_chat_conv(
-                    message.unified_msg_origin,
-                    dify_cid,
-                )
-            message.set_result(
-                MessageEventResult().message(
-                    "删除当前对话成功。不再处于对话状态，使用 /switch 序号 切换到其他对话或 /new 创建。",
-                ),
+        agent_runner_type = cfg["provider_settings"]["agent_runner_type"]
+        if agent_runner_type in THIRD_PARTY_AGENT_RUNNER_KEY:
+            active_event_registry.stop_all(umo, exclude=message)
+            await sp.remove_async(
+                scope="umo",
+                scope_id=umo,
+                key=THIRD_PARTY_AGENT_RUNNER_KEY[agent_runner_type],
            )
+            message.set_result(MessageEventResult().message("重置对话成功。"))
            return

        session_curr_cid = (
-            await self.context.conversation_manager.get_curr_conversation_id(
-                message.unified_msg_origin,
-            )
+            await self.context.conversation_manager.get_curr_conversation_id(umo)
        )

        if not session_curr_cid:
@@ -441,13 +408,13 @@ class ConversationCommands:
            )
            return

+        active_event_registry.stop_all(umo, exclude=message)
+
        await self.context.conversation_manager.delete_conversation(
-            message.unified_msg_origin,
+            umo,
            session_curr_cid,
        )

        ret = "删除当前对话成功。不再处于对话状态，使用 /switch 序号 切换到其他对话或 /new 创建。"
-        if self.ltm and self.ltm_enabled(message):
-            cnt = await self.ltm.remove_session(event=message)
-            ret += f"\n聊天增强: 已清除 {cnt} 条聊天记录。"
+        message.set_extra("_clean_ltm_session", True)
        message.set_result(MessageEventResult().message(ret))
@@ -0,0 +1,88 @@
+import aiohttp
+
+from astrbot.api import star
+from astrbot.api.event import AstrMessageEvent, MessageEventResult
+from astrbot.core.config.default import VERSION
+from astrbot.core.star import command_management
+from astrbot.core.utils.io import get_dashboard_version
+
+
+class HelpCommand:
+    def __init__(self, context: star.Context) -> None:
+        self.context = context
+
+    async def _query_astrbot_notice(self):
+        try:
+            async with aiohttp.ClientSession(trust_env=True) as session:
+                async with session.get(
+                    "https://astrbot.app/notice.json",
+                    timeout=2,
+                ) as resp:
+                    return (await resp.json())["notice"]
+        except BaseException:
+            return ""
+
+    async def _build_reserved_command_lines(self) -> list[str]:
+        """
+        使用实时指令配置生成内置指令清单，确保重命名/禁用后与实际生效状态保持一致。
+        """
+        try:
+            commands = await command_management.list_commands()
+        except BaseException:
+            return []
+
+        lines: list[str] = []
+        hidden_commands = {"set", "unset", "websearch"}
+
+        def walk(items: list[dict], indent: int = 0) -> None:
+            for item in items:
+                if not item.get("reserved") or not item.get("enabled"):
+                    continue
+                # 仅展示顶级指令或指令组
+                if item.get("type") == "sub_command":
+                    continue
+                if item.get("parent_signature"):
+                    continue
+
+                effective = (
+                    item.get("effective_command")
+                    or item.get("original_command")
+                    or item.get("handler_name")
+                )
+                if not effective:
+                    continue
+                if effective in hidden_commands:
+                    continue
+
+                description = item.get("description") or ""
+                desc_text = f" - {description}" if description else ""
+                indent_prefix = "  " * indent
+                lines.append(f"{indent_prefix}/{effective}{desc_text}")
+
+        walk(commands)
+        return lines
+
+    async def help(self, event: AstrMessageEvent) -> None:
+        """查看帮助"""
+        notice = ""
+        try:
+            notice = await self._query_astrbot_notice()
+        except BaseException:
+            pass
+
+        dashboard_version = await get_dashboard_version()
+        command_lines = await self._build_reserved_command_lines()
+        commands_section = (
+            "\n".join(command_lines) if command_lines else "暂无启用的内置指令"
+        )
+
+        msg_parts = [
+            f"AstrBot v{VERSION}(WebUI: {dashboard_version})",
+            "内置指令:",
+            commands_section,
+        ]
+        if notice:
+            msg_parts.append(notice)
+        msg = "\n".join(msg_parts)
+
+        event.set_result(MessageEventResult().message(msg).use_t2i(False))
@@ -3,10 +3,10 @@ from astrbot.api.event import AstrMessageEvent, MessageChain


 class LLMCommands:
-    def __init__(self, context: star.Context):
+    def __init__(self, context: star.Context) -> None:
        self.context = context

-    async def llm(self, event: AstrMessageEvent):
+    async def llm(self, event: AstrMessageEvent) -> None:
        """开启/关闭 LLM"""
        cfg = self.context.get_config(umo=event.unified_msg_origin)
        enable = cfg["provider_settings"].get("enable", True)
@@ -1,14 +1,56 @@
 import builtins
+from typing import TYPE_CHECKING

 from astrbot.api import star
 from astrbot.api.event import AstrMessageEvent, MessageEventResult

+if TYPE_CHECKING:
+    from astrbot.core.db.po import Persona
+

 class PersonaCommands:
-    def __init__(self, context: star.Context):
+    def __init__(self, context: star.Context) -> None:
        self.context = context

-    async def persona(self, message: AstrMessageEvent):
+    def _build_tree_output(
+        self,
+        folder_tree: list[dict],
+        all_personas: list["Persona"],
+        depth: int = 0,
+    ) -> list[str]:
+        """递归构建树状输出，使用短线条表示层级"""
+        lines: list[str] = []
+        # 使用短线条作为缩进前缀，每层只用 "│" 加一个空格
+        prefix = "│ " * depth
+
+        for folder in folder_tree:
+            # 输出文件夹
+            lines.append(f"{prefix}├ 📁 {folder['name']}/")
+
+            # 获取该文件夹下的人格
+            folder_personas = [
+                p for p in all_personas if p.folder_id == folder["folder_id"]
+            ]
+            child_prefix = "│ " * (depth + 1)
+
+            # 输出该文件夹下的人格
+            for persona in folder_personas:
+                lines.append(f"{child_prefix}├ 👤 {persona.persona_id}")
+
+            # 递归处理子文件夹
+            children = folder.get("children", [])
+            if children:
+                lines.extend(
+                    self._build_tree_output(
+                        children,
+                        all_personas,
+                        depth + 1,
+                    )
+                )
+
+        return lines
+
+    async def persona(self, message: AstrMessageEvent) -> None:
        l = message.message_str.split(" ")  # noqa: E741
        umo = message.unified_msg_origin

@@ -17,6 +59,8 @@ class PersonaCommands:
        default_persona = await self.context.persona_manager.get_default_persona_v3(
            umo=umo,
        )
+        force_applied_persona_id = None
+
        curr_cid_title = "无"
        if cid:
            conv = await self.context.conversation_manager.get_conversation(
@@ -31,10 +75,30 @@ class PersonaCommands:
                    ),
                )
                return
-            if not conv.persona_id and conv.persona_id != "[%None]":
-                curr_persona_name = default_persona["name"]
-            else:
-                curr_persona_name = conv.persona_id
+
+            provider_settings = self.context.get_config(umo=umo).get(
+                "provider_settings",
+                {},
+            )
+            (
+                persona_id,
+                _,
+                force_applied_persona_id,
+                _,
+            ) = await self.context.persona_manager.resolve_selected_persona(
+                umo=umo,
+                conversation_persona_id=conv.persona_id,
+                platform_name=message.get_platform_name(),
+                provider_settings=provider_settings,
+            )
+
+            if persona_id == "[%None]":
+                curr_persona_name = "无"
+            elif persona_id:
+                curr_persona_name = persona_id
+
+            if force_applied_persona_id:
+                curr_persona_name = f"{curr_persona_name} (自定义规则)"

            curr_cid_title = conv.title if conv.title else "新对话"
            curr_cid_title += f"({cid[:4]})"
@@ -59,12 +123,32 @@ class PersonaCommands:
                .use_t2i(False),
            )
        elif l[1] == "list":
-            parts = ["人格列表：\n"]
-            for persona in self.context.provider_manager.personas:
-                parts.append(f"- {persona['name']}\n")
-            parts.append("\n\n*输入 `/persona view 人格名` 查看人格详细信息")
-            msg = "".join(parts)
-            message.set_result(MessageEventResult().message(msg))
+            # 获取文件夹树和所有人格
+            folder_tree = await self.context.persona_manager.get_folder_tree()
+            all_personas = self.context.persona_manager.personas
+
+            lines = ["📂 人格列表：\n"]
+
+            # 构建树状输出
+            tree_lines = self._build_tree_output(folder_tree, all_personas)
+            lines.extend(tree_lines)
+
+            # 输出根目录下的人格（没有文件夹的）
+            root_personas = [p for p in all_personas if p.folder_id is None]
+            if root_personas:
+                if tree_lines:  # 如果有文件夹内容，加个空行
+                    lines.append("")
+                for persona in root_personas:
+                    lines.append(f"👤 {persona.persona_id}")
+
+            # 统计信息
+            total_count = len(all_personas)
+            lines.append(f"\n共 {total_count} 个人格")
+            lines.append("\n*使用 `/persona <人格名>` 设置人格")
+            lines.append("*使用 `/persona view <人格名>` 查看详细信息")
+
+            msg = "\n".join(lines)
+            message.set_result(MessageEventResult().message(msg).use_t2i(False))
        elif l[1] == "view":
            if len(l) == 2:
                message.set_result(MessageEventResult().message("请输入人格情景名"))
@@ -113,9 +197,15 @@ class PersonaCommands:
                    message.unified_msg_origin,
                    ps,
                )
+                force_warn_msg = ""
+                if force_applied_persona_id:
+                    force_warn_msg = (
+                        "提醒：由于自定义规则，您现在切换的人格将不会生效。"
+                    )
+
                message.set_result(
                    MessageEventResult().message(
-                        "设置成功。如果您正在切换到不同的人格，请注意使用 /reset 来清空上下文，防止原人格对话影响现人格。",
+                        f"设置成功。如果您正在切换到不同的人格，请注意使用 /reset 来清空上下文，防止原人格对话影响现人格。{force_warn_msg}",
                    ),
                )
            else:
@@ -8,10 +8,10 @@ from astrbot.core.star.star_manager import PluginManager


 class PluginCommands:
-    def __init__(self, context: star.Context):
+    def __init__(self, context: star.Context) -> None:
        self.context = context

-    async def plugin_ls(self, event: AstrMessageEvent):
+    async def plugin_ls(self, event: AstrMessageEvent) -> None:
        """获取已经安装的插件列表。"""
        parts = ["已加载的插件：\n"]
        for plugin in self.context.get_all_stars():
@@ -30,7 +30,7 @@ class PluginCommands:
            MessageEventResult().message(f"{plugin_list_info}").use_t2i(False),
        )

-    async def plugin_off(self, event: AstrMessageEvent, plugin_name: str = ""):
+    async def plugin_off(self, event: AstrMessageEvent, plugin_name: str = "") -> None:
        """禁用插件"""
        if DEMO_MODE:
            event.set_result(MessageEventResult().message("演示模式下无法禁用插件。"))
@@ -43,7 +43,7 @@ class PluginCommands:
        await self.context._star_manager.turn_off_plugin(plugin_name)  # type: ignore
        event.set_result(MessageEventResult().message(f"插件 {plugin_name} 已禁用。"))

-    async def plugin_on(self, event: AstrMessageEvent, plugin_name: str = ""):
+    async def plugin_on(self, event: AstrMessageEvent, plugin_name: str = "") -> None:
        """启用插件"""
        if DEMO_MODE:
            event.set_result(MessageEventResult().message("演示模式下无法启用插件。"))
@@ -56,7 +56,7 @@ class PluginCommands:
        await self.context._star_manager.turn_on_plugin(plugin_name)  # type: ignore
        event.set_result(MessageEventResult().message(f"插件 {plugin_name} 已启用。"))

-    async def plugin_get(self, event: AstrMessageEvent, plugin_repo: str = ""):
+    async def plugin_get(self, event: AstrMessageEvent, plugin_repo: str = "") -> None:
        """安装插件"""
        if DEMO_MODE:
            event.set_result(MessageEventResult().message("演示模式下无法安装插件。"))
@@ -77,7 +77,7 @@ class PluginCommands:
                event.set_result(MessageEventResult().message(f"安装插件失败: {e}"))
                return

-    async def plugin_help(self, event: AstrMessageEvent, plugin_name: str = ""):
+    async def plugin_help(self, event: AstrMessageEvent, plugin_name: str = "") -> None:
        """获取插件帮助"""
        if not plugin_name:
            event.set_result(
@@ -0,0 +1,736 @@
+from __future__ import annotations
+
+import asyncio
+import time
+from collections.abc import Sequence
+from dataclasses import dataclass
+from typing import TYPE_CHECKING
+
+from astrbot import logger
+from astrbot.api import star
+from astrbot.api.event import AstrMessageEvent, MessageEventResult
+from astrbot.core.provider.entities import ProviderType
+from astrbot.core.utils.error_redaction import safe_error
+
+if TYPE_CHECKING:
+    from astrbot.core.provider.provider import Provider
+
+
+MODEL_LIST_CACHE_TTL_SECONDS_DEFAULT = 30.0
+MODEL_LOOKUP_MAX_CONCURRENCY_DEFAULT = 4
+MODEL_LOOKUP_MAX_CONCURRENCY_UPPER_BOUND = 16
+MODEL_LIST_CACHE_TTL_KEY = "model_list_cache_ttl_seconds"
+MODEL_LOOKUP_MAX_CONCURRENCY_KEY = "model_lookup_max_concurrency"
+MODEL_CACHE_MAX_ENTRIES = 512
+
+
+@dataclass(frozen=True)
+class _ModelLookupConfig:
+    umo: str | None
+    cache_ttl_seconds: float
+    max_concurrency: int
+
+
+class _ModelCache:
+    def __init__(self) -> None:
+        self._store: dict[tuple[str, str | None], tuple[float, list[str]]] = {}
+
+    def get(self, provider_id: str, umo: str | None, ttl: float) -> list[str] | None:
+        if ttl <= 0:
+            return None
+        entry = self._store.get((provider_id, umo))
+        if not entry:
+            return None
+        timestamp, models = entry
+        if time.monotonic() - timestamp > ttl:
+            self._store.pop((provider_id, umo), None)
+            return None
+        return models
+
+    def set(
+        self, provider_id: str, umo: str | None, models: list[str], ttl: float
+    ) -> None:
+        if ttl <= 0:
+            return
+        self._store[(provider_id, umo)] = (time.monotonic(), list(models))
+        self._evict_if_needed()
+
+    def _evict_if_needed(self) -> None:
+        if len(self._store) <= MODEL_CACHE_MAX_ENTRIES:
+            return
+        # Drop oldest entries first when cache grows too large.
+        overflow = len(self._store) - MODEL_CACHE_MAX_ENTRIES
+        for key, _ in sorted(
+            self._store.items(),
+            key=lambda item: item[1][0],
+        )[:overflow]:
+            self._store.pop(key, None)
+
+    def invalidate(
+        self, provider_id: str | None = None, *, umo: str | None = None
+    ) -> None:
+        if provider_id is None:
+            self._store.clear()
+            return
+        if umo is not None:
+            self._store.pop((provider_id, umo), None)
+            return
+        stale_keys = [
+            cache_key for cache_key in self._store if cache_key[0] == provider_id
+        ]
+        for cache_key in stale_keys:
+            self._store.pop(cache_key, None)
+
+
+class ProviderCommands:
+    def __init__(self, context: star.Context) -> None:
+        self.context = context
+        self._model_cache = _ModelCache()
+        self._register_provider_change_hook()
+
+    def _register_provider_change_hook(self) -> None:
+        set_change_callback = getattr(
+            self.context.provider_manager,
+            "set_provider_change_callback",
+            None,
+        )
+        if callable(set_change_callback):
+            set_change_callback(self._on_provider_manager_changed)
+            return
+        register_change_hook = getattr(
+            self.context.provider_manager,
+            "register_provider_change_hook",
+            None,
+        )
+        if callable(register_change_hook):
+            register_change_hook(self._on_provider_manager_changed)
+
+    def invalidate_provider_models_cache(
+        self, provider_id: str | None = None, *, umo: str | None = None
+    ) -> None:
+        """Public hook for cache invalidation on external provider config changes."""
+        self._model_cache.invalidate(provider_id, umo=umo)
+
+    def _on_provider_manager_changed(
+        self,
+        provider_id: str,
+        provider_type: ProviderType,
+        umo: str | None,
+    ) -> None:
+        if provider_type == ProviderType.CHAT_COMPLETION:
+            self.invalidate_provider_models_cache(provider_id, umo=umo)
+
+    def _get_provider_settings(self, umo: str | None) -> dict:
+        if not umo:
+            return {}
+        try:
+            return self.context.get_config(umo).get("provider_settings", {}) or {}
+        except Exception as e:
+            logger.debug(
+                "读取 provider_settings 失败，使用默认值: %s",
+                safe_error("", e),
+            )
+            return {}
+
+    def _get_model_cache_ttl(self, umo: str | None) -> float:
+        settings = self._get_provider_settings(umo)
+        raw = settings.get(
+            MODEL_LIST_CACHE_TTL_KEY,
+            MODEL_LIST_CACHE_TTL_SECONDS_DEFAULT,
+        )
+        try:
+            return max(float(raw), 0.0)
+        except Exception as e:
+            logger.debug(
+                "读取 %s 失败，回退默认值 %r: %s",
+                MODEL_LIST_CACHE_TTL_KEY,
+                MODEL_LIST_CACHE_TTL_SECONDS_DEFAULT,
+                safe_error("", e),
+            )
+            return MODEL_LIST_CACHE_TTL_SECONDS_DEFAULT
+
+    def _get_model_lookup_concurrency(self, umo: str | None) -> int:
+        settings = self._get_provider_settings(umo)
+        raw = settings.get(
+            MODEL_LOOKUP_MAX_CONCURRENCY_KEY,
+            MODEL_LOOKUP_MAX_CONCURRENCY_DEFAULT,
+        )
+        try:
+            value = int(raw)
+        except Exception as e:
+            logger.debug(
+                "读取 %s 失败，回退默认值 %r: %s",
+                MODEL_LOOKUP_MAX_CONCURRENCY_KEY,
+                MODEL_LOOKUP_MAX_CONCURRENCY_DEFAULT,
+                safe_error("", e),
+            )
+            value = MODEL_LOOKUP_MAX_CONCURRENCY_DEFAULT
+        return min(max(value, 1), MODEL_LOOKUP_MAX_CONCURRENCY_UPPER_BOUND)
+
+    def _get_model_lookup_config(self, umo: str | None) -> _ModelLookupConfig:
+        return _ModelLookupConfig(
+            umo=umo,
+            cache_ttl_seconds=self._get_model_cache_ttl(umo),
+            max_concurrency=self._get_model_lookup_concurrency(umo),
+        )
+
+    def _resolve_model_name(
+        self,
+        model_name: str,
+        models: Sequence[str],
+    ) -> str | None:
+        """Resolve model name with precedence:
+        exact > case-insensitive > provider-qualified suffix.
+        """
+        requested = model_name.strip()
+        if not requested:
+            return None
+
+        requested_norm = requested.casefold()
+
+        # exact / case-insensitive match
+        for candidate in models:
+            if candidate == requested or candidate.casefold() == requested_norm:
+                return candidate
+
+        # provider-qualified suffix match:
+        # e.g. candidate `openai/gpt-4o` should match requested `gpt-4o`.
+        for candidate in models:
+            cand_norm = candidate.casefold()
+            if cand_norm.endswith(f"/{requested_norm}") or cand_norm.endswith(
+                f":{requested_norm}"
+            ):
+                return candidate
+
+        return None
+
+    def _apply_model(
+        self, prov: Provider, model_name: str, *, umo: str | None = None
+    ) -> str:
+        prov.set_model(model_name)
+        self.invalidate_provider_models_cache(prov.meta().id, umo=umo)
+        return f"切换模型成功。当前提供商: [{prov.meta().id}] 当前模型: [{prov.get_model()}]"
+
+    async def _get_provider_models(
+        self,
+        provider: Provider,
+        *,
+        config: _ModelLookupConfig,
+        use_cache: bool = True,
+    ) -> list[str]:
+        provider_id = provider.meta().id
+        ttl_seconds = config.cache_ttl_seconds
+        umo = config.umo
+        if use_cache:
+            cached = self._model_cache.get(provider_id, umo, ttl_seconds)
+            if cached is not None:
+                return cached
+
+        models = list(await provider.get_models())
+        if use_cache:
+            self._model_cache.set(provider_id, umo, models, ttl_seconds)
+        return models
+
+    async def _get_models_or_reply_error(
+        self,
+        message: AstrMessageEvent,
+        prov: Provider,
+        config: _ModelLookupConfig,
+        *,
+        error_prefix: str,
+        disable_t2i: bool = False,
+        warning_log: str | None = None,
+    ) -> list[str] | None:
+        try:
+            return await self._get_provider_models(prov, config=config)
+        except asyncio.CancelledError:
+            raise
+        except Exception as e:
+            if warning_log is not None:
+                logger.warning(
+                    warning_log,
+                    prov.meta().id,
+                    safe_error("", e),
+                )
+            result = MessageEventResult().message(safe_error(error_prefix, e))
+            if disable_t2i:
+                result = result.use_t2i(False)
+            message.set_result(result)
+            return None
+
+    def _log_reachability_failure(
+        self,
+        provider,
+        provider_capability_type: ProviderType | None,
+        err_code: str,
+        err_reason: str,
+    ) -> None:
+        """记录不可达原因到日志。"""
+        meta = provider.meta()
+        logger.warning(
+            "Provider reachability check failed: id=%s type=%s code=%s reason=%s",
+            meta.id,
+            provider_capability_type.name if provider_capability_type else "unknown",
+            err_code,
+            err_reason,
+        )
+
+    async def _test_provider_capability(self, provider):
+        """测试单个 provider 的可用性"""
+        meta = provider.meta()
+        provider_capability_type = meta.provider_type
+
+        try:
+            await provider.test()
+            return True, None, None
+        except Exception as e:
+            err_code = "TEST_FAILED"
+            err_reason = safe_error("", e)
+            self._log_reachability_failure(
+                provider, provider_capability_type, err_code, err_reason
+            )
+            return False, err_code, err_reason
+
+    async def _find_provider_for_model(
+        self,
+        model_name: str,
+        *,
+        exclude_provider_id: str | None = None,
+        config: _ModelLookupConfig,
+        use_cache: bool = True,
+    ) -> tuple[Provider | None, str | None]:
+        all_providers = []
+        for provider in self.context.get_all_providers():
+            provider_meta = provider.meta()
+            if provider_meta.provider_type != ProviderType.CHAT_COMPLETION:
+                continue
+            if (
+                exclude_provider_id is not None
+                and provider_meta.id == exclude_provider_id
+            ):
+                continue
+            all_providers.append(provider)
+        if not all_providers:
+            return None, None
+
+        semaphore = asyncio.Semaphore(config.max_concurrency)
+
+        async def fetch_models(
+            provider: Provider,
+        ) -> tuple[Provider, list[str] | None, str | None]:
+            async with semaphore:
+                try:
+                    models = await self._get_provider_models(
+                        provider,
+                        config=config,
+                        use_cache=use_cache,
+                    )
+                    return provider, models, None
+                except asyncio.CancelledError:
+                    raise
+                except Exception as e:
+                    err = safe_error("", e)
+                    logger.debug(
+                        "跨提供商查找模型 %s 获取 %s 模型列表失败: %s",
+                        model_name,
+                        provider.meta().id,
+                        err,
+                    )
+                    return provider, None, err
+
+        results = await asyncio.gather(
+            *(fetch_models(provider) for provider in all_providers)
+        )
+        failed_provider_errors: list[tuple[str, str]] = []
+        for provider, models, err in results:
+            if err is not None:
+                failed_provider_errors.append((provider.meta().id, err))
+                continue
+            if models is None:
+                continue
+
+            matched_model_name = self._resolve_model_name(model_name, models)
+            if matched_model_name is not None:
+                return provider, matched_model_name
+
+        if failed_provider_errors and len(failed_provider_errors) == len(all_providers):
+            failed_ids = ",".join(
+                provider_id for provider_id, _ in failed_provider_errors
+            )
+            logger.error(
+                "跨提供商查找模型 %s 时，所有 %d 个提供商的 get_models() 均失败: %s。请检查配置或网络",
+                model_name,
+                len(all_providers),
+                failed_ids,
+            )
+        elif failed_provider_errors:
+            logger.debug(
+                "跨提供商查找模型 %s 时有 %d 个提供商获取模型失败: %s",
+                model_name,
+                len(failed_provider_errors),
+                ",".join(
+                    f"{provider_id}({error})"
+                    for provider_id, error in failed_provider_errors
+                ),
+            )
+        return None, None
+
+    async def provider(
+        self,
+        event: AstrMessageEvent,
+        idx: str | int | None = None,
+        idx2: int | None = None,
+    ) -> None:
+        """查看或者切换 LLM Provider"""
+        umo = event.unified_msg_origin
+        cfg = self.context.get_config(umo).get("provider_settings", {})
+        reachability_check_enabled = cfg.get("reachability_check", True)
+
+        if idx is None:
+            parts = ["## 载入的 LLM 提供商\n"]
+
+            # 获取所有类型的提供商
+            llms = list(self.context.get_all_providers())
+            ttss = self.context.get_all_tts_providers()
+            stts = self.context.get_all_stt_providers()
+
+            # 构造待检测列表: [(provider, type_label), ...]
+            all_providers = []
+            all_providers.extend([(p, "llm") for p in llms])
+            all_providers.extend([(p, "tts") for p in ttss])
+            all_providers.extend([(p, "stt") for p in stts])
+
+            # 并发测试连通性
+            if reachability_check_enabled:
+                if all_providers:
+                    await event.send(
+                        MessageEventResult().message(
+                            "正在进行提供商可达性测试，请稍候..."
+                        )
+                    )
+                check_results = await asyncio.gather(
+                    *[self._test_provider_capability(p) for p, _ in all_providers],
+                    return_exceptions=True,
+                )
+            else:
+                # 用 None 表示未检测
+                check_results = [None for _ in all_providers]
+
+            # 整合结果
+            display_data = []
+            for (p, p_type), reachable in zip(all_providers, check_results):
+                meta = p.meta()
+                id_ = meta.id
+                error_code = None
+
+                if isinstance(reachable, asyncio.CancelledError):
+                    raise reachable
+                if isinstance(reachable, Exception):
+                    # 异常情况下兜底处理，避免单个 provider 导致列表失败
+                    self._log_reachability_failure(
+                        p,
+                        None,
+                        reachable.__class__.__name__,
+                        safe_error("", reachable),
+                    )
+                    reachable_flag = False
+                    error_code = reachable.__class__.__name__
+                elif isinstance(reachable, tuple):
+                    reachable_flag, error_code, _ = reachable
+                else:
+                    reachable_flag = reachable
+
+                # 根据类型构建显示名称
+                if p_type == "llm":
+                    info = f"{id_} ({meta.model})"
+                else:
+                    info = f"{id_}"
+
+                # 确定状态标记
+                if reachable_flag is True:
+                    mark = " ✅"
+                elif reachable_flag is False:
+                    if error_code:
+                        mark = f" ❌(错误码: {error_code})"
+                    else:
+                        mark = " ❌"
+                else:
+                    mark = ""  # 不支持检测时不显示标记
+
+                display_data.append(
+                    {
+                        "type": p_type,
+                        "info": info,
+                        "mark": mark,
+                        "provider": p,
+                    }
+                )
+
+            # 分组输出
+            # 1. LLM
+            llm_data = [d for d in display_data if d["type"] == "llm"]
+            for i, d in enumerate(llm_data):
+                line = f"{i + 1}. {d['info']}{d['mark']}"
+                provider_using = self.context.get_using_provider(umo=umo)
+                if (
+                    provider_using
+                    and provider_using.meta().id == d["provider"].meta().id
+                ):
+                    line += " (当前使用)"
+                parts.append(line + "\n")
+
+            # 2. TTS
+            tts_data = [d for d in display_data if d["type"] == "tts"]
+            if tts_data:
+                parts.append("\n## 载入的 TTS 提供商\n")
+                for i, d in enumerate(tts_data):
+                    line = f"{i + 1}. {d['info']}{d['mark']}"
+                    tts_using = self.context.get_using_tts_provider(umo=umo)
+                    if tts_using and tts_using.meta().id == d["provider"].meta().id:
+                        line += " (当前使用)"
+                    parts.append(line + "\n")
+
+            # 3. STT
+            stt_data = [d for d in display_data if d["type"] == "stt"]
+            if stt_data:
+                parts.append("\n## 载入的 STT 提供商\n")
+                for i, d in enumerate(stt_data):
+                    line = f"{i + 1}. {d['info']}{d['mark']}"
+                    stt_using = self.context.get_using_stt_provider(umo=umo)
+                    if stt_using and stt_using.meta().id == d["provider"].meta().id:
+                        line += " (当前使用)"
+                    parts.append(line + "\n")
+
+            parts.append("\n使用 /provider <序号> 切换 LLM 提供商。")
+            ret = "".join(parts)
+
+            if ttss:
+                ret += "\n使用 /provider tts <序号> 切换 TTS 提供商。"
+            if stts:
+                ret += "\n使用 /provider stt <序号> 切换 STT 提供商。"
+            if not reachability_check_enabled:
+                ret += "\n已跳过提供商可达性检测，如需检测请在配置文件中开启。"
+
+            event.set_result(MessageEventResult().message(ret))
+        elif idx == "tts":
+            if idx2 is None:
+                event.set_result(MessageEventResult().message("请输入序号。"))
+                return
+            if idx2 > len(self.context.get_all_tts_providers()) or idx2 < 1:
+                event.set_result(MessageEventResult().message("无效的提供商序号。"))
+                return
+            provider = self.context.get_all_tts_providers()[idx2 - 1]
+            id_ = provider.meta().id
+            await self.context.provider_manager.set_provider(
+                provider_id=id_,
+                provider_type=ProviderType.TEXT_TO_SPEECH,
+                umo=umo,
+            )
+            event.set_result(MessageEventResult().message(f"成功切换到 {id_}。"))
+        elif idx == "stt":
+            if idx2 is None:
+                event.set_result(MessageEventResult().message("请输入序号。"))
+                return
+            if idx2 > len(self.context.get_all_stt_providers()) or idx2 < 1:
+                event.set_result(MessageEventResult().message("无效的提供商序号。"))
+                return
+            provider = self.context.get_all_stt_providers()[idx2 - 1]
+            id_ = provider.meta().id
+            await self.context.provider_manager.set_provider(
+                provider_id=id_,
+                provider_type=ProviderType.SPEECH_TO_TEXT,
+                umo=umo,
+            )
+            event.set_result(MessageEventResult().message(f"成功切换到 {id_}。"))
+        elif isinstance(idx, int):
+            if idx > len(self.context.get_all_providers()) or idx < 1:
+                event.set_result(MessageEventResult().message("无效的提供商序号。"))
+                return
+            provider = self.context.get_all_providers()[idx - 1]
+            id_ = provider.meta().id
+            await self.context.provider_manager.set_provider(
+                provider_id=id_,
+                provider_type=ProviderType.CHAT_COMPLETION,
+                umo=umo,
+            )
+            event.set_result(MessageEventResult().message(f"成功切换到 {id_}。"))
+        else:
+            event.set_result(MessageEventResult().message("无效的参数。"))
+
+    async def _switch_model_by_name(
+        self, message: AstrMessageEvent, model_name: str, prov: Provider
+    ) -> None:
+        model_name = model_name.strip()
+        if not model_name:
+            message.set_result(MessageEventResult().message("模型名不能为空。"))
+            return
+
+        umo = message.unified_msg_origin
+        config = self._get_model_lookup_config(umo)
+        curr_provider_id = prov.meta().id
+
+        models = await self._get_models_or_reply_error(
+            message,
+            prov,
+            config,
+            error_prefix="获取当前提供商模型列表失败: ",
+            warning_log="获取当前提供商 %s 模型列表失败，停止跨提供商查找: %s",
+        )
+        if models is None:
+            return
+
+        matched_model_name = self._resolve_model_name(model_name, models)
+        if matched_model_name is not None:
+            message.set_result(
+                MessageEventResult().message(
+                    self._apply_model(prov, matched_model_name, umo=umo)
+                ),
+            )
+            return
+
+        target_prov, matched_target_model_name = await self._find_provider_for_model(
+            model_name,
+            exclude_provider_id=curr_provider_id,
+            config=config,
+        )
+
+        if target_prov is None or matched_target_model_name is None:
+            message.set_result(
+                MessageEventResult().message(
+                    f"模型 [{model_name}] 未在任何已配置的提供商中找到，或所有提供商模型列表获取失败，请检查配置或网络后重试。",
+                ),
+            )
+            return
+
+        target_id = target_prov.meta().id
+        try:
+            await self.context.provider_manager.set_provider(
+                provider_id=target_id,
+                provider_type=ProviderType.CHAT_COMPLETION,
+                umo=umo,
+            )
+            self._apply_model(target_prov, matched_target_model_name, umo=umo)
+            message.set_result(
+                MessageEventResult().message(
+                    f"检测到模型 [{matched_target_model_name}] 属于提供商 [{target_id}]，已自动切换提供商并设置模型。",
+                ),
+            )
+        except asyncio.CancelledError:
+            raise
+        except Exception as e:
+            message.set_result(
+                MessageEventResult().message(
+                    safe_error("跨提供商切换并设置模型失败: ", e)
+                ),
+            )
+
+    async def model_ls(
+        self,
+        message: AstrMessageEvent,
+        idx_or_name: int | str | None = None,
+    ) -> None:
+        """查看或者切换模型"""
+        prov = self.context.get_using_provider(message.unified_msg_origin)
+        if not prov:
+            message.set_result(
+                MessageEventResult().message("未找到任何 LLM 提供商。请先配置。"),
+            )
+            return
+        config = self._get_model_lookup_config(message.unified_msg_origin)
+
+        if idx_or_name is None:
+            models = await self._get_models_or_reply_error(
+                message,
+                prov,
+                config,
+                error_prefix="获取模型列表失败: ",
+                disable_t2i=True,
+            )
+            if models is None:
+                return
+            parts = ["下面列出了此模型提供商可用模型:"]
+            for i, model in enumerate(models, 1):
+                parts.append(f"\n{i}. {model}")
+
+            curr_model = prov.get_model() or "无"
+            parts.append(f"\n当前模型: [{curr_model}]")
+            parts.append(
+                "\nTips: 使用 /model <模型名/编号> 切换模型。输入模型名时可自动跨提供商查找并切换；跨提供商也可使用 /provider 切换。"
+            )
+
+            ret = "".join(parts)
+            message.set_result(MessageEventResult().message(ret).use_t2i(False))
+        elif isinstance(idx_or_name, int):
+            models = await self._get_models_or_reply_error(
+                message,
+                prov,
+                config,
+                error_prefix="获取模型列表失败: ",
+            )
+            if models is None:
+                return
+            if idx_or_name > len(models) or idx_or_name < 1:
+                message.set_result(MessageEventResult().message("模型序号错误。"))
+            else:
+                try:
+                    new_model = models[idx_or_name - 1]
+                    message.set_result(
+                        MessageEventResult().message(
+                            self._apply_model(
+                                prov,
+                                new_model,
+                                umo=message.unified_msg_origin,
+                            )
+                        ),
+                    )
+                except Exception as e:
+                    message.set_result(
+                        MessageEventResult().message(
+                            safe_error("切换模型未知错误: ", e)
+                        ),
+                    )
+                    return
+        else:
+            await self._switch_model_by_name(message, idx_or_name, prov)
+
+    async def key(self, message: AstrMessageEvent, index: int | None = None) -> None:
+        prov = self.context.get_using_provider(message.unified_msg_origin)
+        if not prov:
+            message.set_result(
+                MessageEventResult().message("未找到任何 LLM 提供商。请先配置。"),
+            )
+            return
+
+        if index is None:
+            keys_data = prov.get_keys()
+            curr_key = prov.get_current_key()
+            parts = ["Key:"]
+            for i, k in enumerate(keys_data, 1):
+                parts.append(f"\n{i}. {k[:8]}")
+
+            parts.append(f"\n当前 Key: {curr_key[:8]}")
+            parts.append("\n当前模型: " + prov.get_model())
+            parts.append("\n使用 /key <idx> 切换 Key。")
+
+            ret = "".join(parts)
+            message.set_result(MessageEventResult().message(ret).use_t2i(False))
+        else:
+            keys_data = prov.get_keys()
+            if index > len(keys_data) or index < 1:
+                message.set_result(MessageEventResult().message("Key 序号错误。"))
+            else:
+                try:
+                    new_key = keys_data[index - 1]
+                    prov.set_key(new_key)
+                    self.invalidate_provider_models_cache(
+                        prov.meta().id,
+                        umo=message.unified_msg_origin,
+                    )
+                    message.set_result(MessageEventResult().message("切换 Key 成功。"))
+                except Exception as e:
+                    message.set_result(
+                        MessageEventResult().message(
+                            safe_error("切换 Key 未知错误: ", e)
+                        ),
+                    )
+                    return
@@ -3,10 +3,10 @@ from astrbot.api.event import AstrMessageEvent, MessageEventResult


 class SetUnsetCommands:
-    def __init__(self, context: star.Context):
+    def __init__(self, context: star.Context) -> None:
        self.context = context

-    async def set_variable(self, event: AstrMessageEvent, key: str, value: str):
+    async def set_variable(self, event: AstrMessageEvent, key: str, value: str) -> None:
        """设置会话变量"""
        uid = event.unified_msg_origin
        session_var = await sp.session_get(uid, "session_variables", {})
@@ -19,7 +19,7 @@ class SetUnsetCommands:
            ),
        )

-    async def unset_variable(self, event: AstrMessageEvent, key: str):
+    async def unset_variable(self, event: AstrMessageEvent, key: str) -> None:
        """移除会话变量"""
        uid = event.unified_msg_origin
        session_var = await sp.session_get(uid, "session_variables", {})
@@ -7,10 +7,10 @@ from astrbot.api.event import AstrMessageEvent, MessageEventResult
 class SIDCommand:
    """会话ID命令类"""

-    def __init__(self, context: star.Context):
+    def __init__(self, context: star.Context) -> None:
        self.context = context

-    async def sid(self, event: AstrMessageEvent):
+    async def sid(self, event: AstrMessageEvent) -> None:
        """获取消息来源信息"""
        sid = event.unified_msg_origin
        user_id = str(event.get_sender_id())
@@ -7,10 +7,10 @@ from astrbot.api.event import AstrMessageEvent, MessageEventResult
 class T2ICommand:
    """文本转图片命令类"""

-    def __init__(self, context: star.Context):
+    def __init__(self, context: star.Context) -> None:
        self.context = context

-    async def t2i(self, event: AstrMessageEvent):
+    async def t2i(self, event: AstrMessageEvent) -> None:
        """开关文本转图片"""
        config = self.context.get_config(umo=event.unified_msg_origin)
        if config["t2i"]:
@@ -8,19 +8,19 @@ from astrbot.core.star.session_llm_manager import SessionServiceManager
 class TTSCommand:
    """文本转语音命令类"""

-    def __init__(self, context: star.Context):
+    def __init__(self, context: star.Context) -> None:
        self.context = context

-    async def tts(self, event: AstrMessageEvent):
+    async def tts(self, event: AstrMessageEvent) -> None:
        """开关文本转语音（会话级别）"""
        umo = event.unified_msg_origin
-        ses_tts = SessionServiceManager.is_tts_enabled_for_session(umo)
+        ses_tts = await SessionServiceManager.is_tts_enabled_for_session(umo)
        cfg = self.context.get_config(umo=umo)
        tts_enable = cfg["provider_tts_settings"]["enable"]

        # 切换状态
        new_status = not ses_tts
-        SessionServiceManager.set_tts_status_for_session(umo, new_status)
+        await SessionServiceManager.set_tts_status_for_session(umo, new_status)

        status_text = "已开启" if new_status else "已关闭"

@@ -0,0 +1,218 @@
+from astrbot.api import star
+from astrbot.api.event import AstrMessageEvent, filter
+
+from .commands import (
+    AdminCommands,
+    AlterCmdCommands,
+    ConversationCommands,
+    HelpCommand,
+    LLMCommands,
+    PersonaCommands,
+    PluginCommands,
+    ProviderCommands,
+    SetUnsetCommands,
+    SIDCommand,
+    T2ICommand,
+    TTSCommand,
+)
+
+
+class Main(star.Star):
+    def __init__(self, context: star.Context) -> None:
+        self.context = context
+
+        self.help_c = HelpCommand(self.context)
+        self.llm_c = LLMCommands(self.context)
+        self.plugin_c = PluginCommands(self.context)
+        self.admin_c = AdminCommands(self.context)
+        self.conversation_c = ConversationCommands(self.context)
+        self.provider_c = ProviderCommands(self.context)
+        self.persona_c = PersonaCommands(self.context)
+        self.alter_cmd_c = AlterCmdCommands(self.context)
+        self.setunset_c = SetUnsetCommands(self.context)
+        self.t2i_c = T2ICommand(self.context)
+        self.tts_c = TTSCommand(self.context)
+        self.sid_c = SIDCommand(self.context)
+
+    @filter.command("help")
+    async def help(self, event: AstrMessageEvent) -> None:
+        """查看帮助"""
+        await self.help_c.help(event)
+
+    @filter.permission_type(filter.PermissionType.ADMIN)
+    @filter.command("llm")
+    async def llm(self, event: AstrMessageEvent) -> None:
+        """开启/关闭 LLM"""
+        await self.llm_c.llm(event)
+
+    @filter.command_group("plugin")
+    def plugin(self) -> None:
+        """插件管理"""
+
+    @plugin.command("ls")
+    async def plugin_ls(self, event: AstrMessageEvent) -> None:
+        """获取已经安装的插件列表。"""
+        await self.plugin_c.plugin_ls(event)
+
+    @filter.permission_type(filter.PermissionType.ADMIN)
+    @plugin.command("off")
+    async def plugin_off(self, event: AstrMessageEvent, plugin_name: str = "") -> None:
+        """禁用插件"""
+        await self.plugin_c.plugin_off(event, plugin_name)
+
+    @filter.permission_type(filter.PermissionType.ADMIN)
+    @plugin.command("on")
+    async def plugin_on(self, event: AstrMessageEvent, plugin_name: str = "") -> None:
+        """启用插件"""
+        await self.plugin_c.plugin_on(event, plugin_name)
+
+    @filter.permission_type(filter.PermissionType.ADMIN)
+    @plugin.command("get")
+    async def plugin_get(self, event: AstrMessageEvent, plugin_repo: str = "") -> None:
+        """安装插件"""
+        await self.plugin_c.plugin_get(event, plugin_repo)
+
+    @plugin.command("help")
+    async def plugin_help(self, event: AstrMessageEvent, plugin_name: str = "") -> None:
+        """获取插件帮助"""
+        await self.plugin_c.plugin_help(event, plugin_name)
+
+    @filter.command("t2i")
+    async def t2i(self, event: AstrMessageEvent) -> None:
+        """开关文本转图片"""
+        await self.t2i_c.t2i(event)
+
+    @filter.command("tts")
+    async def tts(self, event: AstrMessageEvent) -> None:
+        """开关文本转语音（会话级别）"""
+        await self.tts_c.tts(event)
+
+    @filter.command("sid")
+    async def sid(self, event: AstrMessageEvent) -> None:
+        """获取会话 ID 和 管理员 ID"""
+        await self.sid_c.sid(event)
+
+    @filter.permission_type(filter.PermissionType.ADMIN)
+    @filter.command("op")
+    async def op(self, event: AstrMessageEvent, admin_id: str = "") -> None:
+        """授权管理员。op <admin_id>"""
+        await self.admin_c.op(event, admin_id)
+
+    @filter.permission_type(filter.PermissionType.ADMIN)
+    @filter.command("deop")
+    async def deop(self, event: AstrMessageEvent, admin_id: str) -> None:
+        """取消授权管理员。deop <admin_id>"""
+        await self.admin_c.deop(event, admin_id)
+
+    @filter.permission_type(filter.PermissionType.ADMIN)
+    @filter.command("wl")
+    async def wl(self, event: AstrMessageEvent, sid: str = "") -> None:
+        """添加白名单。wl <sid>"""
+        await self.admin_c.wl(event, sid)
+
+    @filter.permission_type(filter.PermissionType.ADMIN)
+    @filter.command("dwl")
+    async def dwl(self, event: AstrMessageEvent, sid: str) -> None:
+        """删除白名单。dwl <sid>"""
+        await self.admin_c.dwl(event, sid)
+
+    @filter.permission_type(filter.PermissionType.ADMIN)
+    @filter.command("provider")
+    async def provider(
+        self,
+        event: AstrMessageEvent,
+        idx: str | int | None = None,
+        idx2: int | None = None,
+    ) -> None:
+        """查看或者切换 LLM Provider"""
+        await self.provider_c.provider(event, idx, idx2)
+
+    @filter.command("reset")
+    async def reset(self, message: AstrMessageEvent) -> None:
+        """重置 LLM 会话"""
+        await self.conversation_c.reset(message)
+
+    @filter.command("stop")
+    async def stop(self, message: AstrMessageEvent) -> None:
+        """停止当前会话中正在运行的 Agent"""
+        await self.conversation_c.stop(message)
+
+    @filter.permission_type(filter.PermissionType.ADMIN)
+    @filter.command("model")
+    async def model_ls(
+        self,
+        message: AstrMessageEvent,
+        idx_or_name: int | str | None = None,
+    ) -> None:
+        """查看或者切换模型"""
+        await self.provider_c.model_ls(message, idx_or_name)
+
+    @filter.command("history")
+    async def his(self, message: AstrMessageEvent, page: int = 1) -> None:
+        """查看对话记录"""
+        await self.conversation_c.his(message, page)
+
+    @filter.command("ls")
+    async def convs(self, message: AstrMessageEvent, page: int = 1) -> None:
+        """查看对话列表"""
+        await self.conversation_c.convs(message, page)
+
+    @filter.command("new")
+    async def new_conv(self, message: AstrMessageEvent) -> None:
+        """创建新对话"""
+        await self.conversation_c.new_conv(message)
+
+    @filter.permission_type(filter.PermissionType.ADMIN)
+    @filter.command("groupnew")
+    async def groupnew_conv(self, message: AstrMessageEvent, sid: str) -> None:
+        """创建新群聊对话"""
+        await self.conversation_c.groupnew_conv(message, sid)
+
+    @filter.command("switch")
+    async def switch_conv(
+        self, message: AstrMessageEvent, index: int | None = None
+    ) -> None:
+        """通过 /ls 前面的序号切换对话"""
+        await self.conversation_c.switch_conv(message, index)
+
+    @filter.command("rename")
+    async def rename_conv(self, message: AstrMessageEvent, new_name: str) -> None:
+        """重命名对话"""
+        await self.conversation_c.rename_conv(message, new_name)
+
+    @filter.command("del")
+    async def del_conv(self, message: AstrMessageEvent) -> None:
+        """删除当前对话"""
+        await self.conversation_c.del_conv(message)
+
+    @filter.permission_type(filter.PermissionType.ADMIN)
+    @filter.command("key")
+    async def key(self, message: AstrMessageEvent, index: int | None = None) -> None:
+        """查看或者切换 Key"""
+        await self.provider_c.key(message, index)
+
+    @filter.permission_type(filter.PermissionType.ADMIN)
+    @filter.command("persona")
+    async def persona(self, message: AstrMessageEvent) -> None:
+        """查看或者切换 Persona"""
+        await self.persona_c.persona(message)
+
+    @filter.permission_type(filter.PermissionType.ADMIN)
+    @filter.command("dashboard_update")
+    async def update_dashboard(self, event: AstrMessageEvent) -> None:
+        """更新管理面板"""
+        await self.admin_c.update_dashboard(event)
+
+    @filter.command("set")
+    async def set_variable(self, event: AstrMessageEvent, key: str, value: str) -> None:
+        await self.setunset_c.set_variable(event, key, value)
+
+    @filter.command("unset")
+    async def unset_variable(self, event: AstrMessageEvent, key: str) -> None:
+        await self.setunset_c.unset_variable(event, key)
+
+    @filter.permission_type(filter.PermissionType.ADMIN)
+    @filter.command("alter_cmd", alias={"alter"})
+    async def alter_cmd(self, event: AstrMessageEvent) -> None:
+        """修改命令权限"""
+        await self.alter_cmd_c.alter_cmd(event)
@@ -0,0 +1,4 @@
+name: builtin_commands
+desc: AstrBot 自带指令，提供常用的对话管理、工具使用、插件管理等功能。
+author: Soulter
+version: 0.0.1
@@ -14,14 +14,14 @@ from astrbot.core.utils.session_waiter import (
 )


-class Waiter(Star):
+class Main(Star):
    """会话控制"""

-    def __init__(self, context: Context):
+    def __init__(self, context: Context) -> None:
        super().__init__(context)

    @filter.event_message_type(filter.EventMessageType.ALL, priority=maxsize)
-    async def handle_session_control_agent(self, event: AstrMessageEvent):
+    async def handle_session_control_agent(self, event: AstrMessageEvent) -> None:
        """会话控制代理"""
        for session_filter in FILTERS:
            session_id = session_filter.filter(event)
@@ -49,7 +49,7 @@ class Waiter(Star):
                    if p_settings.get("empty_mention_waiting_need_reply", True):
                        try:
                            # 尝试使用 LLM 生成更生动的回复
-                            func_tools_mgr = self.context.get_llm_tool_manager()
+                            # func_tools_mgr = self.context.get_llm_tool_manager()

                            # 获取用户当前的对话信息
                            curr_cid = await self.context.conversation_manager.get_curr_conversation_id(
@@ -76,7 +76,6 @@ class Waiter(Star):
                                    "你友好地询问用户想要聊些什么或者需要什么帮助，回复要符合人设，不要太过机械化。"
                                    "请注意，你仅需要输出要回复用户的内容，不要输出其他任何东西"
                                ),
-                                func_tool_manager=func_tools_mgr,
                                session_id=curr_cid,
                                contexts=[],
                                system_prompt="",
@@ -91,7 +90,7 @@ class Waiter(Star):
                    async def empty_mention_waiter(
                        controller: SessionController,
                        event: AstrMessageEvent,
-                    ):
+                    ) -> None:
                        event.message_obj.message.insert(
                            0,
                            Comp.At(qq=event.get_self_id(), name=event.get_self_id()),
@@ -3,7 +3,7 @@ import urllib.parse
 from dataclasses import dataclass

 from aiohttp import ClientSession
-from bs4 import BeautifulSoup
+from bs4 import BeautifulSoup, Tag

 HEADERS = {
    "User-Agent": "Mozilla/5.0 (Windows NT 6.1; rv:84.0) Gecko/20100101 Firefox/84.0",
@@ -32,6 +32,7 @@ class SearchResult:
    title: str
    url: str
    snippet: str
+    favicon: str | None = None

    def __str__(self) -> str:
        return f"{self.title} - {self.url}\n{self.snippet}"
@@ -45,13 +46,13 @@ class SearchEngine:
        self.page = 1
        self.headers = HEADERS

-    def _set_selector(self, selector: str) -> None:
+    def _set_selector(self, selector: str) -> str:
        raise NotImplementedError

-    def _get_next_page(self):
+    async def _get_next_page(self, query: str) -> str:
        raise NotImplementedError

-    async def _get_html(self, url: str, data: dict = None) -> str:
+    async def _get_html(self, url: str, data: dict | None = None) -> str:
        headers = self.headers
        headers["Referer"] = url
        headers["User-Agent"] = random.choice(USER_AGENTS)
@@ -83,6 +84,9 @@ class SearchEngine:
        """清理文本，去除空格、换行符等"""
        return text.strip().replace("\n", " ").replace("\r", " ").replace("  ", " ")

+    def _get_url(self, tag: Tag) -> str:
+        return self.tidy_text(tag.get_text())
+
    async def search(self, query: str, num_results: int) -> list[SearchResult]:
        query = urllib.parse.quote(query)

@@ -92,12 +96,16 @@ class SearchEngine:
            links = soup.select(self._set_selector("links"))
            results = []
            for link in links:
-                title = self.tidy_text(
-                    link.select_one(self._set_selector("title")).text,
-                )
-                url = link.select_one(self._set_selector("url"))
+                # Safely get the title text (select_one may return None)
+                title_elem = link.select_one(self._set_selector("title"))
+                title = ""
+                if title_elem is not None:
+                    title = self.tidy_text(title_elem.get_text())
+
+                url_tag = link.select_one(self._set_selector("url"))
                snippet = ""
-                if title and url:
+                if title and url_tag:
+                    url = self._get_url(url_tag)
                    results.append(SearchResult(title=title, url=url, snippet=snippet))
            return results[:num_results] if len(results) > num_results else results
        except Exception as e:
@@ -1,4 +1,4 @@
-from . import USER_AGENT_BING, SearchEngine, SearchResult
+from . import USER_AGENT_BING, SearchEngine


 class Bing(SearchEngine):
@@ -28,11 +28,3 @@ class Bing(SearchEngine):
                self.base_url = base_url
                continue
        raise Exception("Bing search failed")
-
-    async def search(self, query: str, num_results: int) -> list[SearchResult]:
-        results = await super().search(query, num_results)
-        for result in results:
-            if not isinstance(result.url, str):
-                result.url = result.url.text
-
-        return results
@@ -1,7 +1,8 @@
 import random
 import re
+from typing import cast

-from bs4 import BeautifulSoup
+from bs4 import BeautifulSoup, Tag

 from . import USER_AGENTS, SearchEngine, SearchResult

@@ -26,10 +27,12 @@ class Sogo(SearchEngine):
        url = f"{self.base_url}/web?query={query}"
        return await self._get_html(url, None)

+    def _get_url(self, tag: Tag) -> str:
+        return cast(str, tag.get("href"))
+
    async def search(self, query: str, num_results: int) -> list[SearchResult]:
        results = await super().search(query, num_results)
        for result in results:
-            result.url = result.url.get("href")
            if result.url.startswith("/link?"):
                result.url = self.base_url + result.url
                result.url = await self._parse_url(result.url)
@@ -40,7 +43,10 @@ class Sogo(SearchEngine):
        soup = BeautifulSoup(html, "html.parser")
        script = soup.find("script")
        if script:
-            url = re.search(r'window.location.replace\("(.+?)"\)', script.string).group(
-                1,
+            script_text = (
+                script.string if script.string is not None else script.get_text()
            )
+            match = re.search(r'window.location.replace\("(.+?)"\)', script_text)
+            if match:
+                url = match.group(1)
        return url
@@ -1,12 +1,14 @@
 import asyncio
+import json
 import random
+import uuid

 import aiohttp
 from bs4 import BeautifulSoup
 from readability import Document

-from astrbot.api import AstrBotConfig, llm_tool, logger, star
-from astrbot.api.event import AstrMessageEvent, MessageEventResult, filter
+from astrbot.api import AstrBotConfig, llm_tool, logger, sp, star
+from astrbot.api.event import AstrMessageEvent, filter
 from astrbot.api.provider import ProviderRequest
 from astrbot.core.provider.func_tool_manager import FunctionToolManager

@@ -21,6 +23,7 @@ class Main(star.Star):
        "fetch_url",
        "web_search_tavily",
        "tavily_extract_web_page",
+        "web_search_bocha",
    ]

    def __init__(self, context: star.Context) -> None:
@@ -28,6 +31,9 @@ class Main(star.Star):
        self.tavily_key_index = 0
        self.tavily_key_lock = asyncio.Lock()

+        self.bocha_key_index = 0
+        self.bocha_key_lock = asyncio.Lock()
+
        # 将 str 类型的 key 迁移至 list[str]，并保存
        cfg = self.context.get_config()
        provider_settings = cfg.get("provider_settings")
@@ -43,6 +49,14 @@ class Main(star.Star):
                    provider_settings["websearch_tavily_key"] = []
                cfg.save_config()

+            bocha_key = provider_settings.get("websearch_bocha_key")
+            if isinstance(bocha_key, str):
+                if bocha_key:
+                    provider_settings["websearch_bocha_key"] = [bocha_key]
+                else:
+                    provider_settings["websearch_bocha_key"] = []
+                cfg.save_config()
+
        self.bing_search = Bing()
        self.sogo_search = Sogo()
        self.baidu_initialized = False
@@ -56,7 +70,7 @@ class Main(star.Star):
        header = HEADERS
        header.update({"User-Agent": random.choice(USER_AGENTS)})
        async with aiohttp.ClientSession(trust_env=True) as session:
-            async with session.get(url, headers=header, timeout=6) as response:
+            async with session.get(url, headers=header) as response:
                html = await response.text(encoding="utf-8")
                doc = Document(html)
                ret = doc.summary(html_partial=True)
@@ -137,7 +151,6 @@ class Main(star.Star):
                url,
                json=payload,
                headers=header,
-                timeout=6,
            ) as response:
                if response.status != 200:
                    reason = await response.text()
@@ -151,6 +164,7 @@ class Main(star.Star):
                        title=item.get("title"),
                        url=item.get("url"),
                        snippet=item.get("content"),
+                        favicon=item.get("favicon"),
                    )
                    results.append(result)
                return results
@@ -168,7 +182,6 @@ class Main(star.Star):
                url,
                json=payload,
                headers=header,
-                timeout=6,
            ) as response:
                if response.status != 200:
                    reason = await response.text()
@@ -183,14 +196,6 @@ class Main(star.Star):
                    )
                return results

-    @filter.command("websearch")
-    async def websearch(self, event: AstrMessageEvent, oper: str | None = None):
-        event.set_result(
-            MessageEventResult().message(
-                "此指令已经被废弃，请在 WebUI 中开启或关闭网页搜索功能。",
-            ),
-        )
-
    @llm_tool(name="web_search")
    async def search_from_search_engine(
        self,
@@ -230,7 +235,7 @@ class Main(star.Star):

        return ret

-    async def ensure_baidu_ai_search_mcp(self, umo: str | None = None):
+    async def ensure_baidu_ai_search_mcp(self, umo: str | None = None) -> None:
        if self.baidu_initialized:
            return
        cfg = self.context.get_config(umo=umo)
@@ -249,7 +254,7 @@ class Main(star.Star):
                "transport": "sse",
                "url": f"http://appbuilder.baidu.com/v2/ai_search/mcp/sse?api_key={key}",
                "headers": {},
-                "timeout": 30,
+                "timeout": 600,
            },
        )
        self.baidu_initialized = True
@@ -271,7 +276,7 @@ class Main(star.Star):
        self,
        event: AstrMessageEvent,
        query: str,
-        max_results: int = 5,
+        max_results: int = 7,
        search_depth: str = "basic",
        topic: str = "general",
        days: int = 3,
@@ -284,7 +289,7 @@ class Main(star.Star):

        Args:
            query(string): Required. Search query.
-            max_results(number): Optional. The maximum number of results to return. Default is 5. Range is 5-20.
+            max_results(number): Optional. The maximum number of results to return. Default is 7. Range is 5-20.
            search_depth(string): Optional. The depth of the search, must be one of 'basic', 'advanced'. Default is "basic".
            topic(string): Optional. The topic of the search, must be one of 'general', 'news'. Default is "general".
            days(number): Optional. The number of days back from the current date to include in the search results. Please note that this feature is only available when using the 'news' search topic.
@@ -295,15 +300,12 @@ class Main(star.Star):
        """
        logger.info(f"web_searcher - search_from_tavily: {query}")
        cfg = self.context.get_config(umo=event.unified_msg_origin)
-        websearch_link = cfg["provider_settings"].get("web_search_link", False)
+        # websearch_link = cfg["provider_settings"].get("web_search_link", False)
        if not cfg.get("provider_settings", {}).get("websearch_tavily_key", []):
            raise ValueError("Error: Tavily API key is not configured in AstrBot.")

        # build payload
-        payload = {
-            "query": query,
-            "max_results": max_results,
-        }
+        payload = {"query": query, "max_results": max_results, "include_favicon": True}
        if search_depth not in ["basic", "advanced"]:
            search_depth = "basic"
        payload["search_depth"] = search_depth
@@ -327,14 +329,22 @@ class Main(star.Star):
            return "Error: Tavily web searcher does not return any results."

        ret_ls = []
-        for result in results:
-            ret_ls.append(f"\nTitle: {result.title}")
-            ret_ls.append(f"URL: {result.url}")
-            ret_ls.append(f"Content: {result.snippet}")
-        ret = "\n".join(ret_ls)
-
-        if websearch_link:
-            ret += "\n\n针对问题，请根据上面的结果分点总结，并且在结尾处附上对应内容的参考链接（如有）。"
+        ref_uuid = str(uuid.uuid4())[:4]
+        for idx, result in enumerate(results, 1):
+            index = f"{ref_uuid}.{idx}"
+            ret_ls.append(
+                {
+                    "title": f"{result.title}",
+                    "url": f"{result.url}",
+                    "snippet": f"{result.snippet}",
+                    # TODO: do not need ref for non-webchat platform adapter
+                    "index": index,
+                }
+            )
+            if result.favicon:
+                sp.temporary_cache["_ws_favicon"][result.url] = result.favicon
+        # ret = "\n".join(ret_ls)
+        ret = json.dumps({"results": ret_ls}, ensure_ascii=False)
        return ret

    @llm_tool("tavily_extract_web_page")
@@ -373,12 +383,166 @@ class Main(star.Star):
            return "Error: Tavily web searcher does not return any results."
        return ret

+    async def _get_bocha_key(self, cfg: AstrBotConfig) -> str:
+        """并发安全的从列表中获取并轮换BoCha API密钥。"""
+        bocha_keys = cfg.get("provider_settings", {}).get("websearch_bocha_key", [])
+        if not bocha_keys:
+            raise ValueError("错误：BoCha API密钥未在AstrBot中配置。")
+
+        async with self.bocha_key_lock:
+            key = bocha_keys[self.bocha_key_index]
+            self.bocha_key_index = (self.bocha_key_index + 1) % len(bocha_keys)
+            return key
+
+    async def _web_search_bocha(
+        self,
+        cfg: AstrBotConfig,
+        payload: dict,
+    ) -> list[SearchResult]:
+        """使用 BoCha 搜索引擎进行搜索"""
+        bocha_key = await self._get_bocha_key(cfg)
+        url = "https://api.bochaai.com/v1/web-search"
+        header = {
+            "Authorization": f"Bearer {bocha_key}",
+            "Content-Type": "application/json",
+        }
+        async with aiohttp.ClientSession(trust_env=True) as session:
+            async with session.post(
+                url,
+                json=payload,
+                headers=header,
+            ) as response:
+                if response.status != 200:
+                    reason = await response.text()
+                    raise Exception(
+                        f"BoCha web search failed: {reason}, status: {response.status}",
+                    )
+                data = await response.json()
+                data = data["data"]["webPages"]["value"]
+                results = []
+                for item in data:
+                    result = SearchResult(
+                        title=item.get("name"),
+                        url=item.get("url"),
+                        snippet=item.get("snippet"),
+                        favicon=item.get("siteIcon"),
+                    )
+                    results.append(result)
+                return results
+
+    @llm_tool("web_search_bocha")
+    async def search_from_bocha(
+        self,
+        event: AstrMessageEvent,
+        query: str,
+        freshness: str = "noLimit",
+        summary: bool = False,
+        include: str = "",
+        exclude: str = "",
+        count: int = 10,
+    ) -> str:
+        """
+        A web search tool based on Bocha Search API, used to retrieve web pages
+        related to the user's query.
+
+        Args:
+            query (string): Required. User's search query.
+
+            freshness (string): Optional. Specifies the time range of the search.
+                Supported values:
+                - "noLimit": No time limit (default, recommended).
+                - "oneDay": Within one day.
+                - "oneWeek": Within one week.
+                - "oneMonth": Within one month.
+                - "oneYear": Within one year.
+                - "YYYY-MM-DD..YYYY-MM-DD": Search within a specific date range.
+                  Example: "2025-01-01..2025-04-06".
+                - "YYYY-MM-DD": Search on a specific date.
+                  Example: "2025-04-06".
+                It is recommended to use "noLimit", as the search algorithm will
+                automatically optimize time relevance. Manually restricting the
+                time range may result in no search results.
+
+            summary (boolean): Optional. Whether to include a text summary
+                for each search result.
+                - True: Include summary.
+                - False: Do not include summary (default).
+
+            include (string): Optional. Specifies the domains to include in
+                the search. Multiple domains can be separated by "|" or ",".
+                A maximum of 100 domains is allowed.
+                Examples:
+                - "qq.com"
+                - "qq.com|m.163.com"
+
+            exclude (string): Optional. Specifies the domains to exclude from
+                the search. Multiple domains can be separated by "|" or ",".
+                A maximum of 100 domains is allowed.
+                Examples:
+                - "qq.com"
+                - "qq.com|m.163.com"
+
+            count (number): Optional. Number of search results to return.
+                - Range: 1–50
+                - Default: 10
+                The actual number of returned results may be less than the
+                specified count.
+        """
+        logger.info(f"web_searcher - search_from_bocha: {query}")
+        cfg = self.context.get_config(umo=event.unified_msg_origin)
+        # websearch_link = cfg["provider_settings"].get("web_search_link", False)
+        if not cfg.get("provider_settings", {}).get("websearch_bocha_key", []):
+            raise ValueError("Error: BoCha API key is not configured in AstrBot.")
+
+        # build payload
+        payload = {
+            "query": query,
+            "count": count,
+        }
+
+        # freshness：时间范围
+        if freshness:
+            payload["freshness"] = freshness
+
+        # 是否返回摘要
+        payload["summary"] = summary
+
+        # include：限制搜索域
+        if include:
+            payload["include"] = include
+
+        # exclude：排除搜索域
+        if exclude:
+            payload["exclude"] = exclude
+
+        results = await self._web_search_bocha(cfg, payload)
+        if not results:
+            return "Error: BoCha web searcher does not return any results."
+
+        ret_ls = []
+        ref_uuid = str(uuid.uuid4())[:4]
+        for idx, result in enumerate(results, 1):
+            index = f"{ref_uuid}.{idx}"
+            ret_ls.append(
+                {
+                    "title": f"{result.title}",
+                    "url": f"{result.url}",
+                    "snippet": f"{result.snippet}",
+                    "index": index,
+                }
+            )
+            if result.favicon:
+                sp.temporary_cache["_ws_favicon"][result.url] = result.favicon
+        # ret = "\n".join(ret_ls)
+        ret = json.dumps({"results": ret_ls}, ensure_ascii=False)
+        return ret
+
    @filter.on_llm_request(priority=-10000)
    async def edit_web_search_tools(
        self,
        event: AstrMessageEvent,
        req: ProviderRequest,
-    ):
+    ) -> None:
        """Get the session conversation for the given event."""
        cfg = self.context.get_config(umo=event.unified_msg_origin)
        prov_settings = cfg.get("provider_settings", {})
@@ -410,6 +574,7 @@ class Main(star.Star):
            tool_set.remove_tool("web_search_tavily")
            tool_set.remove_tool("tavily_extract_web_page")
            tool_set.remove_tool("AIsearch")
+            tool_set.remove_tool("web_search_bocha")
        elif provider == "tavily":
            web_search_tavily = func_tool_mgr.get_func("web_search_tavily")
            tavily_extract_web_page = func_tool_mgr.get_func("tavily_extract_web_page")
@@ -420,6 +585,7 @@ class Main(star.Star):
            tool_set.remove_tool("web_search")
            tool_set.remove_tool("fetch_url")
            tool_set.remove_tool("AIsearch")
+            tool_set.remove_tool("web_search_bocha")
        elif provider == "baidu_ai_search":
            try:
                await self.ensure_baidu_ai_search_mcp(event.unified_msg_origin)
@@ -431,5 +597,15 @@ class Main(star.Star):
                tool_set.remove_tool("fetch_url")
                tool_set.remove_tool("web_search_tavily")
                tool_set.remove_tool("tavily_extract_web_page")
+                tool_set.remove_tool("web_search_bocha")
            except Exception as e:
                logger.error(f"Cannot Initialize Baidu AI Search MCP Server: {e}")
+        elif provider == "bocha":
+            web_search_bocha = func_tool_mgr.get_func("web_search_bocha")
+            if web_search_bocha:
+                tool_set.add_tool(web_search_bocha)
+            tool_set.remove_tool("web_search")
+            tool_set.remove_tool("fetch_url")
+            tool_set.remove_tool("AIsearch")
+            tool_set.remove_tool("web_search_tavily")
+            tool_set.remove_tool("tavily_extract_web_page")
@@ -1 +1 @@
-__version__ = "3.5.23"
+__version__ = "4.19.5"
@@ -1,4 +1,4 @@
-"""AstrBot CLI入口"""
+"""AstrBot CLI entry point"""

 import sys

@@ -29,23 +29,23 @@ def cli() -> None:
@click.command()
@click.argument("command_name", required=False, type=str)
 def help(command_name: str | None) -> None:
-    """显示命令的帮助信息
+    """Display help information for commands

-    如果提供了 COMMAND_NAME，则显示该命令的详细帮助信息。
-    否则，显示通用帮助信息。
+    If COMMAND_NAME is provided, display detailed help for that command.
+    Otherwise, display general help information.
    """
    ctx = click.get_current_context()
    if command_name:
-        # 查找指定命令
+        # Find the specified command
        command = cli.get_command(ctx, command_name)
        if command:
-            # 显示特定命令的帮助信息
+            # Display help for the specific command
            click.echo(command.get_help(ctx))
        else:
            click.echo(f"Unknown command: {command_name}")
            sys.exit(1)
    else:
-        # 显示通用帮助信息
+        # Display general help information
        click.echo(cli.get_help(ctx))


@@ -10,57 +10,61 @@ from ..utils import check_astrbot_root, get_astrbot_root


 def _validate_log_level(value: str) -> str:
-    """验证日志级别"""
+    """Validate log level"""
    value = value.upper()
    if value not in ["DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL"]:
        raise click.ClickException(
-            "日志级别必须是 DEBUG/INFO/WARNING/ERROR/CRITICAL 之一",
+            "Log level must be one of DEBUG/INFO/WARNING/ERROR/CRITICAL",
        )
    return value


 def _validate_dashboard_port(value: str) -> int:
-    """验证 Dashboard 端口"""
+    """Validate Dashboard port"""
    try:
        port = int(value)
        if port < 1 or port > 65535:
-            raise click.ClickException("端口必须在 1-65535 范围内")
+            raise click.ClickException("Port must be in range 1-65535")
        return port
    except ValueError:
-        raise click.ClickException("端口必须是数字")
+        raise click.ClickException("Port must be a number")


 def _validate_dashboard_username(value: str) -> str:
-    """验证 Dashboard 用户名"""
+    """Validate Dashboard username"""
    if not value:
-        raise click.ClickException("用户名不能为空")
+        raise click.ClickException("Username cannot be empty")
    return value


 def _validate_dashboard_password(value: str) -> str:
-    """验证 Dashboard 密码"""
+    """Validate Dashboard password"""
    if not value:
-        raise click.ClickException("密码不能为空")
+        raise click.ClickException("Password cannot be empty")
    return hashlib.md5(value.encode()).hexdigest()


 def _validate_timezone(value: str) -> str:
-    """验证时区"""
+    """Validate timezone"""
    try:
        zoneinfo.ZoneInfo(value)
    except Exception:
-        raise click.ClickException(f"无效的时区: {value}，请使用有效的IANA时区名称")
+        raise click.ClickException(
+            f"Invalid timezone: {value}. Please use a valid IANA timezone name"
+        )
    return value


 def _validate_callback_api_base(value: str) -> str:
-    """验证回调接口基址"""
+    """Validate callback API base URL"""
    if not value.startswith("http://") and not value.startswith("https://"):
-        raise click.ClickException("回调接口基址必须以 http:// 或 https:// 开头")
+        raise click.ClickException(
+            "Callback API base must start with http:// or https://"
+        )
    return value


-# 可通过CLI设置的配置项，配置键到验证器函数的映射
+# Configuration items settable via CLI, mapping config keys to validator functions
 CONFIG_VALIDATORS: dict[str, Callable[[str], Any]] = {
    "timezone": _validate_timezone,
    "log_level": _validate_log_level,
@@ -72,11 +76,11 @@ CONFIG_VALIDATORS: dict[str, Callable[[str], Any]] = {


 def _load_config() -> dict[str, Any]:
-    """加载或初始化配置文件"""
+    """Load or initialize config file"""
    root = get_astrbot_root()
    if not check_astrbot_root(root):
        raise click.ClickException(
-            f"{root}不是有效的 AstrBot 根目录，如需初始化请使用 astrbot init",
+            f"{root} is not a valid AstrBot root directory. Use 'astrbot init' to initialize",
        )

    config_path = root / "data" / "cmd_config.json"
@@ -91,11 +95,11 @@ def _load_config() -> dict[str, Any]:
    try:
        return json.loads(config_path.read_text(encoding="utf-8-sig"))
    except json.JSONDecodeError as e:
-        raise click.ClickException(f"配置文件解析失败: {e!s}")
+        raise click.ClickException(f"Failed to parse config file: {e!s}")


 def _save_config(config: dict[str, Any]) -> None:
-    """保存配置文件"""
+    """Save config file"""
    config_path = get_astrbot_root() / "data" / "cmd_config.json"

    config_path.write_text(
@@ -105,21 +109,21 @@ def _save_config(config: dict[str, Any]) -> None:


 def _set_nested_item(obj: dict[str, Any], path: str, value: Any) -> None:
-    """设置嵌套字典中的值"""
+    """Set a value in a nested dictionary"""
    parts = path.split(".")
    for part in parts[:-1]:
        if part not in obj:
            obj[part] = {}
        elif not isinstance(obj[part], dict):
            raise click.ClickException(
-                f"配置路径冲突: {'.'.join(parts[: parts.index(part) + 1])} 不是字典",
+                f"Config path conflict: {'.'.join(parts[: parts.index(part) + 1])} is not a dict",
            )
        obj = obj[part]
    obj[parts[-1]] = value


 def _get_nested_item(obj: dict[str, Any], path: str) -> Any:
-    """获取嵌套字典中的值"""
+    """Get a value from a nested dictionary"""
    parts = path.split(".")
    for part in parts:
        obj = obj[part]
@@ -127,32 +131,32 @@ def _get_nested_item(obj: dict[str, Any], path: str) -> Any:


@click.group(name="conf")
-def conf():
-    """配置管理命令
+def conf() -> None:
+    """Configuration management commands

-    支持的配置项:
+    Supported config keys:

-    - timezone: 时区设置 (例如: Asia/Shanghai)
+    - timezone: Timezone setting (e.g. Asia/Shanghai)

-    - log_level: 日志级别 (DEBUG/INFO/WARNING/ERROR/CRITICAL)
+    - log_level: Log level (DEBUG/INFO/WARNING/ERROR/CRITICAL)

-    - dashboard.port: Dashboard 端口
+    - dashboard.port: Dashboard port

-    - dashboard.username: Dashboard 用户名
+    - dashboard.username: Dashboard username

-    - dashboard.password: Dashboard 密码
+    - dashboard.password: Dashboard password

-    - callback_api_base: 回调接口基址
+    - callback_api_base: Callback API base URL
    """


@conf.command(name="set")
@click.argument("key")
@click.argument("value")
-def set_config(key: str, value: str):
-    """设置配置项的值"""
+def set_config(key: str, value: str) -> None:
+    """Set the value of a config item"""
    if key not in CONFIG_VALIDATORS:
-        raise click.ClickException(f"不支持的配置项: {key}")
+        raise click.ClickException(f"Unsupported config key: {key}")

    config = _load_config()

@@ -162,29 +166,29 @@ def set_config(key: str, value: str):
        _set_nested_item(config, key, validated_value)
        _save_config(config)

-        click.echo(f"配置已更新: {key}")
+        click.echo(f"Config updated: {key}")
        if key == "dashboard.password":
-            click.echo("  原值: ********")
-            click.echo("  新值: ********")
+            click.echo("  Old value: ********")
+            click.echo("  New value: ********")
        else:
-            click.echo(f"  原值: {old_value}")
-            click.echo(f"  新值: {validated_value}")
+            click.echo(f"  Old value: {old_value}")
+            click.echo(f"  New value: {validated_value}")

    except KeyError:
-        raise click.ClickException(f"未知的配置项: {key}")
+        raise click.ClickException(f"Unknown config key: {key}")
    except Exception as e:
-        raise click.UsageError(f"设置配置失败: {e!s}")
+        raise click.UsageError(f"Failed to set config: {e!s}")


@conf.command(name="get")
@click.argument("key", required=False)
-def get_config(key: str | None = None):
-    """获取配置项的值，不提供key则显示所有可配置项"""
+def get_config(key: str | None = None) -> None:
+    """Get the value of a config item. If no key is provided, show all configurable items"""
    config = _load_config()

    if key:
        if key not in CONFIG_VALIDATORS:
-            raise click.ClickException(f"不支持的配置项: {key}")
+            raise click.ClickException(f"Unsupported config key: {key}")

        try:
            value = _get_nested_item(config, key)
@@ -192,11 +196,11 @@ def get_config(key: str | None = None):
                value = "********"
            click.echo(f"{key}: {value}")
        except KeyError:
-            raise click.ClickException(f"未知的配置项: {key}")
+            raise click.ClickException(f"Unknown config key: {key}")
        except Exception as e:
-            raise click.UsageError(f"获取配置失败: {e!s}")
+            raise click.UsageError(f"Failed to get config: {e!s}")
    else:
-        click.echo("当前配置:")
+        click.echo("Current config:")
        for key in CONFIG_VALIDATORS:
            try:
                value = (
@@ -8,16 +8,12 @@ from ..utils import check_dashboard, get_astrbot_root


 async def initialize_astrbot(astrbot_root: Path) -> None:
-    """执行 AstrBot 初始化逻辑"""
+    """Execute AstrBot initialization logic"""
    dot_astrbot = astrbot_root / ".astrbot"

    if not dot_astrbot.exists():
-        click.echo(f"Current Directory: {astrbot_root}")
-        click.echo(
-            "如果你确认这是 Astrbot root directory, 你需要在当前目录下创建一个 .astrbot 文件标记该目录为 AstrBot 的数据目录。",
-        )
        if click.confirm(
-            f"请检查当前目录是否正确，确认正确请回车: {astrbot_root}",
+            f"Install AstrBot to this directory? {astrbot_root}",
            default=True,
            abort=True,
        ):
@@ -40,7 +36,7 @@ async def initialize_astrbot(astrbot_root: Path) -> None:

@click.command()
 def init() -> None:
-    """初始化 AstrBot"""
+    """Initialize AstrBot"""
    click.echo("Initializing AstrBot...")
    astrbot_root = get_astrbot_root()
    lock_file = astrbot_root / "astrbot.lock"
@@ -49,8 +45,11 @@ def init() -> None:
    try:
        with lock.acquire():
            asyncio.run(initialize_astrbot(astrbot_root))
+            click.echo("Done! You can now run 'astrbot run' to start AstrBot")
    except Timeout:
-        raise click.ClickException("无法获取锁文件，请检查是否有其他实例正在运行")
+        raise click.ClickException(
+            "Cannot acquire lock file. Please check if another instance is running"
+        )

    except Exception as e:
-        raise click.ClickException(f"初始化失败: {e!s}")
+        raise click.ClickException(f"Initialization failed: {e!s}")
@@ -15,24 +15,26 @@ from ..utils import (


@click.group()
-def plug():
-    """插件管理"""
+def plug() -> None:
+    """Plugin management"""


 def _get_data_path() -> Path:
    base = get_astrbot_root()
    if not check_astrbot_root(base):
        raise click.ClickException(
-            f"{base}不是有效的 AstrBot 根目录，如需初始化请使用 astrbot init",
+            f"{base} is not a valid AstrBot root directory. Use 'astrbot init' to initialize",
        )
    return (base / "data").resolve()


-def display_plugins(plugins, title=None, color=None):
+def display_plugins(plugins, title=None, color=None) -> None:
    if title:
        click.echo(click.style(title, fg=color, bold=True))

-    click.echo(f"{'名称':<20} {'版本':<10} {'状态':<10} {'作者':<15} {'描述':<30}")
+    click.echo(
+        f"{'Name':<20} {'Version':<10} {'Status':<10} {'Author':<15} {'Description':<30}"
+    )
    click.echo("-" * 85)

    for p in plugins:
@@ -45,31 +47,31 @@ def display_plugins(plugins, title=None, color=None):

@plug.command()
@click.argument("name")
-def new(name: str):
-    """创建新插件"""
+def new(name: str) -> None:
+    """Create a new plugin"""
    base_path = _get_data_path()
    plug_path = base_path / "plugins" / name

    if plug_path.exists():
-        raise click.ClickException(f"插件 {name} 已存在")
+        raise click.ClickException(f"Plugin {name} already exists")

-    author = click.prompt("请输入插件作者", type=str)
-    desc = click.prompt("请输入插件描述", type=str)
-    version = click.prompt("请输入插件版本", type=str)
+    author = click.prompt("Enter plugin author", type=str)
+    desc = click.prompt("Enter plugin description", type=str)
+    version = click.prompt("Enter plugin version", type=str)
    if not re.match(r"^\d+\.\d+(\.\d+)?$", version.lower().lstrip("v")):
-        raise click.ClickException("版本号必须为 x.y 或 x.y.z 格式")
-    repo = click.prompt("请输入插件仓库：", type=str)
+        raise click.ClickException("Version must be in x.y or x.y.z format")
+    repo = click.prompt("Enter plugin repository URL:", type=str)
    if not repo.startswith("http"):
-        raise click.ClickException("仓库地址必须以 http 开头")
+        raise click.ClickException("Repository URL must start with http")

-    click.echo("下载插件模板...")
+    click.echo("Downloading plugin template...")
    get_git_repo(
        "https://github.com/Soulter/helloworld",
        plug_path,
    )

-    click.echo("重写插件信息...")
-    # 重写 metadata.yaml
+    click.echo("Rewriting plugin metadata...")
+    # Rewrite metadata.yaml
    with open(plug_path / "metadata.yaml", "w", encoding="utf-8") as f:
        f.write(
            f"name: {name}\n"
@@ -79,11 +81,13 @@ def new(name: str):
            f"repo: {repo}\n",
        )

-    # 重写 README.md
+    # Rewrite README.md
    with open(plug_path / "README.md", "w", encoding="utf-8") as f:
-        f.write(f"# {name}\n\n{desc}\n\n# 支持\n\n[帮助文档](https://astrbot.app)\n")
+        f.write(
+            f"# {name}\n\n{desc}\n\n# Support\n\n[Documentation](https://astrbot.app)\n"
+        )

-    # 重写 main.py
+    # Rewrite main.py
    with open(plug_path / "main.py", encoding="utf-8") as f:
        content = f.read()

@@ -95,54 +99,54 @@ def new(name: str):
    with open(plug_path / "main.py", "w", encoding="utf-8") as f:
        f.write(new_content)

-    click.echo(f"插件 {name} 创建成功")
+    click.echo(f"Plugin {name} created successfully")


@plug.command()
-@click.option("--all", "-a", is_flag=True, help="列出未安装的插件")
-def list(all: bool):
-    """列出插件"""
+@click.option("--all", "-a", is_flag=True, help="List uninstalled plugins")
+def list(all: bool) -> None:
+    """List plugins"""
    base_path = _get_data_path()
    plugins = build_plug_list(base_path / "plugins")

-    # 未发布的插件
+    # Unpublished plugins
    not_published_plugins = [
        p for p in plugins if p["status"] == PluginStatus.NOT_PUBLISHED
    ]
    if not_published_plugins:
-        display_plugins(not_published_plugins, "未发布的插件", "red")
+        display_plugins(not_published_plugins, "Unpublished Plugins", "red")

-    # 需要更新的插件
+    # Plugins needing update
    need_update_plugins = [
        p for p in plugins if p["status"] == PluginStatus.NEED_UPDATE
    ]
    if need_update_plugins:
-        display_plugins(need_update_plugins, "需要更新的插件", "yellow")
+        display_plugins(need_update_plugins, "Plugins Needing Update", "yellow")

-    # 已安装的插件
+    # Installed plugins
    installed_plugins = [p for p in plugins if p["status"] == PluginStatus.INSTALLED]
    if installed_plugins:
-        display_plugins(installed_plugins, "已安装的插件", "green")
+        display_plugins(installed_plugins, "Installed Plugins", "green")

-    # 未安装的插件
+    # Uninstalled plugins
    not_installed_plugins = [
        p for p in plugins if p["status"] == PluginStatus.NOT_INSTALLED
    ]
    if not_installed_plugins and all:
-        display_plugins(not_installed_plugins, "未安装的插件", "blue")
+        display_plugins(not_installed_plugins, "Uninstalled Plugins", "blue")

    if (
        not any([not_published_plugins, need_update_plugins, installed_plugins])
        and not all
    ):
-        click.echo("未安装任何插件")
+        click.echo("No plugins installed")


@plug.command()
@click.argument("name")
-@click.option("--proxy", help="代理服务器地址")
-def install(name: str, proxy: str | None):
-    """安装插件"""
+@click.option("--proxy", help="Proxy server address")
+def install(name: str, proxy: str | None) -> None:
+    """Install a plugin"""
    base_path = _get_data_path()
    plug_path = base_path / "plugins"
    plugins = build_plug_list(base_path / "plugins")
@@ -157,38 +161,40 @@ def install(name: str, proxy: str | None):
    )

    if not plugin:
-        raise click.ClickException(f"未找到可安装的插件 {name}，可能是不存在或已安装")
+        raise click.ClickException(f"Plugin {name} not found or already installed")

    manage_plugin(plugin, plug_path, is_update=False, proxy=proxy)


@plug.command()
@click.argument("name")
-def remove(name: str):
-    """卸载插件"""
+def remove(name: str) -> None:
+    """Uninstall a plugin"""
    base_path = _get_data_path()
    plugins = build_plug_list(base_path / "plugins")
    plugin = next((p for p in plugins if p["name"] == name), None)

    if not plugin or not plugin.get("local_path"):
-        raise click.ClickException(f"插件 {name} 不存在或未安装")
+        raise click.ClickException(f"Plugin {name} does not exist or is not installed")

    plugin_path = plugin["local_path"]

-    click.confirm(f"确定要卸载插件 {name} 吗?", default=False, abort=True)
+    click.confirm(
+        f"Are you sure you want to uninstall plugin {name}?", default=False, abort=True
+    )

    try:
        shutil.rmtree(plugin_path)
-        click.echo(f"插件 {name} 已卸载")
+        click.echo(f"Plugin {name} has been uninstalled")
    except Exception as e:
-        raise click.ClickException(f"卸载插件 {name} 失败: {e}")
+        raise click.ClickException(f"Failed to uninstall plugin {name}: {e}")


@plug.command()
@click.argument("name", required=False)
-@click.option("--proxy", help="Github代理地址")
-def update(name: str, proxy: str | None):
-    """更新插件"""
+@click.option("--proxy", help="GitHub proxy address")
+def update(name: str, proxy: str | None) -> None:
+    """Update plugins"""
    base_path = _get_data_path()
    plug_path = base_path / "plugins"
    plugins = build_plug_list(base_path / "plugins")
@@ -204,7 +210,9 @@ def update(name: str, proxy: str | None):
        )

        if not plugin:
-            raise click.ClickException(f"插件 {name} 不需要更新或无法更新")
+            raise click.ClickException(
+                f"Plugin {name} does not need updating or cannot be updated"
+            )

        manage_plugin(plugin, plug_path, is_update=True, proxy=proxy)
    else:
@@ -213,20 +221,20 @@ def update(name: str, proxy: str | None):
        ]

        if not need_update_plugins:
-            click.echo("没有需要更新的插件")
+            click.echo("No plugins need updating")
            return

-        click.echo(f"发现 {len(need_update_plugins)} 个插件需要更新")
+        click.echo(f"Found {len(need_update_plugins)} plugin(s) needing update")
        for plugin in need_update_plugins:
            plugin_name = plugin["name"]
-            click.echo(f"正在更新插件 {plugin_name}...")
+            click.echo(f"Updating plugin {plugin_name}...")
            manage_plugin(plugin, plug_path, is_update=True, proxy=proxy)


@plug.command()
@click.argument("query")
-def search(query: str):
-    """搜索插件"""
+def search(query: str) -> None:
+    """Search for plugins"""
    base_path = _get_data_path()
    plugins = build_plug_list(base_path / "plugins")

@@ -239,7 +247,7 @@ def search(query: str):
    ]

    if not matched_plugins:
-        click.echo(f"未找到匹配 '{query}' 的插件")
+        click.echo(f"No plugins matching '{query}' found")
        return

-    display_plugins(matched_plugins, f"搜索结果: '{query}'", "cyan")
+    display_plugins(matched_plugins, f"Search results: '{query}'", "cyan")
@@ -10,8 +10,8 @@ from filelock import FileLock, Timeout
 from ..utils import check_astrbot_root, check_dashboard, get_astrbot_root


-async def run_astrbot(astrbot_root: Path):
-    """运行 AstrBot"""
+async def run_astrbot(astrbot_root: Path) -> None:
+    """Run AstrBot"""
    from astrbot.core import LogBroker, LogManager, db_helper, logger
    from astrbot.core.initial_loader import InitialLoader

@@ -26,18 +26,18 @@ async def run_astrbot(astrbot_root: Path):
    await core_lifecycle.start()


-@click.option("--reload", "-r", is_flag=True, help="插件自动重载")
-@click.option("--port", "-p", help="Astrbot Dashboard端口", required=False, type=str)
+@click.option("--reload", "-r", is_flag=True, help="Auto-reload plugins")
+@click.option("--port", "-p", help="AstrBot Dashboard port", required=False, type=str)
@click.command()
 def run(reload: bool, port: str) -> None:
-    """运行 AstrBot"""
+    """Run AstrBot"""
    try:
        os.environ["ASTRBOT_CLI"] = "1"
        astrbot_root = get_astrbot_root()

        if not check_astrbot_root(astrbot_root):
            raise click.ClickException(
-                f"{astrbot_root}不是有效的 AstrBot 根目录，如需初始化请使用 astrbot init",
+                f"{astrbot_root} is not a valid AstrBot root directory. Use 'astrbot init' to initialize",
            )

        os.environ["ASTRBOT_ROOT"] = str(astrbot_root)
@@ -47,7 +47,7 @@ def run(reload: bool, port: str) -> None:
            os.environ["DASHBOARD_PORT"] = port

        if reload:
-            click.echo("启用插件自动重载")
+            click.echo("Plugin auto-reload enabled")
            os.environ["ASTRBOT_RELOAD"] = "1"

        lock_file = astrbot_root / "astrbot.lock"
@@ -55,8 +55,10 @@ def run(reload: bool, port: str) -> None:
        with lock.acquire():
            asyncio.run(run_astrbot(astrbot_root))
    except KeyboardInterrupt:
-        click.echo("AstrBot 已关闭...")
+        click.echo("AstrBot has been shut down.")
    except Timeout:
-        raise click.ClickException("无法获取锁文件，请检查是否有其他实例正在运行")
+        raise click.ClickException(
+            "Cannot acquire lock file. Please check if another instance is running"
+        )
    except Exception as e:
-        raise click.ClickException(f"运行时出现错误: {e}\n{traceback.format_exc()}")
+        raise click.ClickException(f"Runtime error: {e}\n{traceback.format_exc()}")
@@ -2,9 +2,12 @@ from pathlib import Path

 import click

+# Static assets bundled inside the installed wheel (built by hatch_build.py).
+_BUNDLED_DIST = Path(__file__).parent.parent.parent / "dashboard" / "dist"
+

 def check_astrbot_root(path: str | Path) -> bool:
-    """检查路径是否为 AstrBot 根目录"""
+    """Check if the path is an AstrBot root directory"""
    if not isinstance(path, Path):
        path = Path(path)
    if not path.exists() or not path.is_dir():
@@ -15,43 +18,48 @@ def check_astrbot_root(path: str | Path) -> bool:


 def get_astrbot_root() -> Path:
-    """获取Astrbot根目录路径"""
+    """Get the AstrBot root directory path"""
    return Path.cwd()


 async def check_dashboard(astrbot_root: Path) -> None:
-    """检查是否安装了dashboard"""
+    """Check if the dashboard is installed"""
    from astrbot.core.config.default import VERSION
    from astrbot.core.utils.io import download_dashboard, get_dashboard_version

    from .version_comparator import VersionComparator

+    # If the wheel ships bundled dashboard assets, no network download is needed.
+    if _BUNDLED_DIST.exists():
+        click.echo("Dashboard is bundled with the package – skipping download.")
+        return
+
    try:
        dashboard_version = await get_dashboard_version()
        match dashboard_version:
            case None:
-                click.echo("未安装管理面板")
+                click.echo("Dashboard is not installed")
                if click.confirm(
-                    "是否安装管理面板？",
+                    "Install dashboard?",
                    default=True,
                    abort=True,
                ):
-                    click.echo("正在安装管理面板...")
+                    click.echo("Installing dashboard...")
                    await download_dashboard(
                        path="data/dashboard.zip",
                        extract_path=str(astrbot_root),
                        version=f"v{VERSION}",
                        latest=False,
                    )
-                    click.echo("管理面板安装完成")
+                    click.echo("Dashboard installed successfully")

            case str():
                if VersionComparator.compare_version(VERSION, dashboard_version) <= 0:
-                    click.echo("管理面板已是最新版本")
+                    click.echo("Dashboard is already up to date")
                    return
                try:
                    version = dashboard_version.split("v")[1]
-                    click.echo(f"管理面板版本: {version}")
+                    click.echo(f"Dashboard version: {version}")
                    await download_dashboard(
                        path="data/dashboard.zip",
                        extract_path=str(astrbot_root),
@@ -59,10 +67,10 @@ async def check_dashboard(astrbot_root: Path) -> None:
                        latest=False,
                    )
                except Exception as e:
-                    click.echo(f"下载管理面板失败: {e}")
+                    click.echo(f"Failed to download dashboard: {e}")
                    return
    except FileNotFoundError:
-        click.echo("初始化管理面板目录...")
+        click.echo("Initializing dashboard directory...")
        try:
            await download_dashboard(
                path=str(astrbot_root / "dashboard.zip"),
@@ -70,7 +78,7 @@ async def check_dashboard(astrbot_root: Path) -> None:
                version=f"v{VERSION}",
                latest=False,
            )
-            click.echo("管理面板初始化完成")
+            click.echo("Dashboard initialized successfully")
        except Exception as e:
-            click.echo(f"下载管理面板失败: {e}")
+            click.echo(f"Failed to download dashboard: {e}")
            return
@@ -13,22 +13,22 @@ from .version_comparator import VersionComparator


 class PluginStatus(str, Enum):
-    INSTALLED = "已安装"
-    NEED_UPDATE = "需更新"
-    NOT_INSTALLED = "未安装"
-    NOT_PUBLISHED = "未发布"
+    INSTALLED = "installed"
+    NEED_UPDATE = "needs-update"
+    NOT_INSTALLED = "not-installed"
+    NOT_PUBLISHED = "unpublished"


-def get_git_repo(url: str, target_path: Path, proxy: str | None = None):
-    """从 Git 仓库下载代码并解压到指定路径"""
+def get_git_repo(url: str, target_path: Path, proxy: str | None = None) -> None:
+    """Download code from a Git repository and extract to the specified path"""
    temp_dir = Path(tempfile.mkdtemp())
    try:
-        # 解析仓库信息
+        # Parse repository info
        repo_namespace = url.split("/")[-2:]
        author = repo_namespace[0]
        repo = repo_namespace[1]

-        # 尝试获取最新的 release
+        # Try to get the latest release
        release_url = f"https://api.github.com/repos/{author}/{repo}/releases"
        try:
            with httpx.Client(
@@ -40,21 +40,21 @@ def get_git_repo(url: str, target_path: Path, proxy: str | None = None):
                releases = resp.json()

                if releases:
-                    # 使用最新的 release
+                    # Use the latest release
                    download_url = releases[0]["zipball_url"]
                else:
-                    # 没有 release，使用默认分支
-                    click.echo(f"正在从默认分支下载 {author}/{repo}")
+                    # No release found, use default branch
+                    click.echo(f"Downloading {author}/{repo} from default branch")
                    download_url = f"https://github.com/{author}/{repo}/archive/refs/heads/master.zip"
        except Exception as e:
-            click.echo(f"获取 release 信息失败: {e}，将直接使用提供的 URL")
+            click.echo(f"Failed to get release info: {e}. Using provided URL directly")
            download_url = url

-        # 应用代理
+        # Apply proxy
        if proxy:
            download_url = f"{proxy}/{download_url}"

-        # 下载并解压
+        # Download and extract
        with httpx.Client(
            proxy=proxy if proxy else None,
            follow_redirects=True,
@@ -65,7 +65,7 @@ def get_git_repo(url: str, target_path: Path, proxy: str | None = None):
                and "archive/refs/heads/master.zip" in download_url
            ):
                alt_url = download_url.replace("master.zip", "main.zip")
-                click.echo("master 分支不存在，尝试下载 main 分支")
+                click.echo("Branch 'master' not found, trying 'main' branch")
                resp = client.get(alt_url)
                resp.raise_for_status()
            else:
@@ -84,13 +84,13 @@ def get_git_repo(url: str, target_path: Path, proxy: str | None = None):


 def load_yaml_metadata(plugin_dir: Path) -> dict:
-    """从 metadata.yaml 文件加载插件元数据
+    """Load plugin metadata from metadata.yaml file

    Args:
-        plugin_dir: 插件目录路径
+        plugin_dir: Plugin directory path

    Returns:
-        dict: 包含元数据的字典，如果读取失败则返回空字典
+        dict: Dictionary containing metadata, or empty dict if loading fails

    """
    yaml_path = plugin_dir / "metadata.yaml"
@@ -98,33 +98,33 @@ def load_yaml_metadata(plugin_dir: Path) -> dict:
        try:
            return yaml.safe_load(yaml_path.read_text(encoding="utf-8")) or {}
        except Exception as e:
-            click.echo(f"读取 {yaml_path} 失败: {e}", err=True)
+            click.echo(f"Failed to read {yaml_path}: {e}", err=True)
    return {}


 def build_plug_list(plugins_dir: Path) -> list:
-    """构建插件列表，包含本地和在线插件信息
+    """Build plugin list containing local and online plugin information

    Args:
-        plugins_dir (Path): 插件目录路径
+        plugins_dir (Path): Plugin directory path

    Returns:
-        list: 包含插件信息的字典列表
+        list: List of dicts containing plugin information

    """
-    # 获取本地插件信息
+    # Get local plugin info
    result = []
    if plugins_dir.exists():
        for plugin_name in [d.name for d in plugins_dir.glob("*") if d.is_dir()]:
            plugin_dir = plugins_dir / plugin_name

-            # 从 metadata.yaml 加载元数据
+            # Load metadata from metadata.yaml
            metadata = load_yaml_metadata(plugin_dir)

            if "desc" not in metadata and "description" in metadata:
                metadata["desc"] = metadata["description"]

-            # 如果成功加载元数据，添加到结果列表
+            # If metadata loaded successfully, add to result list
            if metadata and all(
                k in metadata for k in ["name", "desc", "version", "author", "repo"]
            ):
@@ -140,7 +140,7 @@ def build_plug_list(plugins_dir: Path) -> list:
                    },
                )

-    # 获取在线插件列表
+    # Get online plugin list
    online_plugins = []
    try:
        with httpx.Client() as client:
@@ -160,13 +160,13 @@ def build_plug_list(plugins_dir: Path) -> list:
                    },
                )
    except Exception as e:
-        click.echo(f"获取在线插件列表失败: {e}", err=True)
+        click.echo(f"Failed to get online plugin list: {e}", err=True)

-    # 与在线插件比对，更新状态
+    # Compare with online plugins and update status
    online_plugin_names = {plugin["name"] for plugin in online_plugins}
    for local_plugin in result:
        if local_plugin["name"] in online_plugin_names:
-            # 查找对应的在线插件
+            # Find the corresponding online plugin
            online_plugin = next(
                p for p in online_plugins if p["name"] == local_plugin["name"]
            )
@@ -179,10 +179,10 @@ def build_plug_list(plugins_dir: Path) -> list:
            ):
                local_plugin["status"] = PluginStatus.NEED_UPDATE
        else:
-            # 本地插件未在线上发布
+            # Local plugin is not published online
            local_plugin["status"] = PluginStatus.NOT_PUBLISHED

-    # 添加未安装的在线插件
+    # Add uninstalled online plugins
    for online_plugin in online_plugins:
        if not any(plugin["name"] == online_plugin["name"] for plugin in result):
            result.append(online_plugin)
@@ -196,19 +196,19 @@ def manage_plugin(
    is_update: bool = False,
    proxy: str | None = None,
 ) -> None:
-    """安装或更新插件
+    """Install or update a plugin

    Args:
-        plugin (dict): 插件信息字典
-        plugins_dir (Path): 插件目录
-        is_update (bool, optional): 是否为更新操作. 默认为 False
-        proxy (str, optional): 代理服务器地址
+        plugin (dict): Plugin info dict
+        plugins_dir (Path): Plugins directory
+        is_update (bool, optional): Whether this is an update operation. Defaults to False
+        proxy (str, optional): Proxy server address

    """
    plugin_name = plugin["name"]
    repo_url = plugin["repo"]

-    # 如果是更新且有本地路径，直接使用本地路径
+    # If updating and local path exists, use it directly
    if is_update and plugin.get("local_path"):
        target_path = Path(plugin["local_path"])
    else:
@@ -216,11 +216,13 @@ def manage_plugin(

    backup_path = Path(f"{target_path}_backup") if is_update else None

-    # 检查插件是否存在
+    # Check if plugin exists
    if is_update and not target_path.exists():
-        raise click.ClickException(f"插件 {plugin_name} 未安装，无法更新")
+        raise click.ClickException(
+            f"Plugin {plugin_name} is not installed and cannot be updated"
+        )

-    # 备份现有插件
+    # Backup existing plugin
    if is_update and backup_path is not None and backup_path.exists():
        shutil.rmtree(backup_path)
    if is_update and backup_path is not None:
@@ -228,19 +230,21 @@ def manage_plugin(

    try:
        click.echo(
-            f"正在从 {repo_url} {'更新' if is_update else '下载'}插件 {plugin_name}...",
+            f"{'Updating' if is_update else 'Downloading'} plugin {plugin_name} from {repo_url}...",
        )
        get_git_repo(repo_url, target_path, proxy)

-        # 更新成功，删除备份
+        # Update succeeded, delete backup
        if is_update and backup_path is not None and backup_path.exists():
            shutil.rmtree(backup_path)
-        click.echo(f"插件 {plugin_name} {'更新' if is_update else '安装'}成功")
+        click.echo(
+            f"Plugin {plugin_name} {'updated' if is_update else 'installed'} successfully"
+        )
    except Exception as e:
        if target_path.exists():
            shutil.rmtree(target_path, ignore_errors=True)
        if is_update and backup_path is not None and backup_path.exists():
            shutil.move(backup_path, target_path)
        raise click.ClickException(
-            f"{'更新' if is_update else '安装'}插件 {plugin_name} 时出错: {e}",
+            f"Error {'updating' if is_update else 'installing'} plugin {plugin_name}: {e}",
        )
@@ -1,4 +1,4 @@
-"""拷贝自 astrbot.core.utils.version_comparator"""
+"""Copied from astrbot.core.utils.version_comparator"""

 import re

@@ -6,11 +6,11 @@ import re
 class VersionComparator:
    @staticmethod
    def compare_version(v1: str, v2: str) -> int:
-        """根据 Semver 语义版本规范来比较版本号的大小。支持不仅局限于 3 个数字的版本号，并处理预发布标签。
+        """Compare version numbers according to Semver semantics. Supports version numbers with more than 3 digits and handles pre-release tags.

-        参考: https://semver.org/lang/zh-CN/
+        Reference: https://semver.org/

-        返回 1 表示 v1 > v2，返回 -1 表示 v1 < v2，返回 0 表示 v1 = v2。
+        Returns 1 if v1 > v2, -1 if v1 < v2, 0 if v1 == v2.
        """
        v1 = v1.lower().replace("v", "")
        v2 = v2.lower().replace("v", "")
@@ -24,7 +24,7 @@ class VersionComparator:
                return [], None
            major_minor_patch = match.group(1).split(".")
            prerelease = match.group(2)
-            # buildmetadata = match.group(3) # 构建元数据在比较时忽略
+            # buildmetadata = match.group(3)  # Build metadata is ignored in comparison
            parts = [int(x) for x in major_minor_patch]
            prerelease = VersionComparator._split_prerelease(prerelease)
            return parts, prerelease
@@ -32,7 +32,7 @@ class VersionComparator:
        v1_parts, v1_prerelease = split_version(v1)
        v2_parts, v2_prerelease = split_version(v2)

-        # 比较数字部分
+        # Compare numeric parts
        length = max(len(v1_parts), len(v2_parts))
        v1_parts.extend([0] * (length - len(v1_parts)))
        v2_parts.extend([0] * (length - len(v2_parts)))
@@ -43,11 +43,11 @@ class VersionComparator:
            if v1_parts[i] < v2_parts[i]:
                return -1

-        # 比较预发布标签
+        # Compare pre-release tags
        if v1_prerelease is None and v2_prerelease is not None:
-            return 1  # 没有预发布标签的版本高于有预发布标签的版本
+            return 1  # Version without pre-release tag is higher than one with it
        if v1_prerelease is not None and v2_prerelease is None:
-            return -1  # 有预发布标签的版本低于没有预发布标签的版本
+            return -1  # Version with pre-release tag is lower than one without it
        if v1_prerelease is not None and v2_prerelease is not None:
            len_pre = max(len(v1_prerelease), len(v2_prerelease))
            for i in range(len_pre):
@@ -72,9 +72,9 @@ class VersionComparator:
                        return 1
                    if p1 < p2:
                        return -1
-            return 0  # 预发布标签完全相同
+            return 0  # Pre-release tags are identical

-        return 0  # 数字部分和预发布标签都相同
+        return 0  # Both numeric parts and pre-release tags are equal

    @staticmethod
    def _split_prerelease(prerelease):
@@ -4,7 +4,21 @@ from astrbot.core.config import AstrBotConfig
 from astrbot.core.config.default import DB_PATH
 from astrbot.core.db.sqlite import SQLiteDatabase
 from astrbot.core.file_token_service import FileTokenService
-from astrbot.core.utils.pip_installer import PipInstaller
+from astrbot.core.utils.pip_installer import (
+    DependencyConflictError as DependencyConflictError,
+)
+from astrbot.core.utils.pip_installer import (
+    PipInstaller,
+)
+from astrbot.core.utils.requirements_utils import (
+    RequirementsPrecheckFailed as RequirementsPrecheckFailed,
+)
+from astrbot.core.utils.requirements_utils import (
+    find_missing_requirements as find_missing_requirements,
+)
+from astrbot.core.utils.requirements_utils import (
+    find_missing_requirements_or_raise as find_missing_requirements_or_raise,
+)
 from astrbot.core.utils.shared_preferences import SharedPreferences
 from astrbot.core.utils.t2i.renderer import HtmlRenderer

@@ -14,12 +28,14 @@ from .utils.astrbot_path import get_astrbot_data_path
 # 初始化数据存储文件夹
 os.makedirs(get_astrbot_data_path(), exist_ok=True)

-DEMO_MODE = os.getenv("DEMO_MODE", False)
+DEMO_MODE = os.getenv("DEMO_MODE", "False").strip().lower() in ("true", "1", "t")

 astrbot_config = AstrBotConfig()
 t2i_base_url = astrbot_config.get("t2i_endpoint", "https://t2i.soulter.top/text2img")
 html_renderer = HtmlRenderer(t2i_base_url)
 logger = LogManager.GetLogger(log_name="astrbot")
+LogManager.configure_logger(logger, astrbot_config)
+LogManager.configure_trace_logger(astrbot_config)
 db_helper = SQLiteDatabase(DB_PATH)
 # 简单的偏好设置存储, 这里后续应该存储到数据库中, 一些部分可以存储到配置中
 sp = SharedPreferences(db_helper=db_helper)
@@ -1,5 +1,5 @@
 from dataclasses import dataclass
-from typing import Generic
+from typing import Any, Generic

 from .hooks import BaseAgentRunHooks
 from .run_context import TContext
@@ -12,3 +12,4 @@ class Agent(Generic[TContext]):
    instructions: str | None = None
    tools: list[str | FunctionTool] | None = None
    run_hooks: BaseAgentRunHooks[TContext] | None = None
+    begin_dialogs: list[Any] | None = None
@@ -0,0 +1,245 @@
+from typing import TYPE_CHECKING, Protocol, runtime_checkable
+
+from ..message import Message
+
+if TYPE_CHECKING:
+    from astrbot import logger
+else:
+    try:
+        from astrbot import logger
+    except ImportError:
+        import logging
+
+        logger = logging.getLogger("astrbot")
+
+if TYPE_CHECKING:
+    from astrbot.core.provider.provider import Provider
+
+from ..context.truncator import ContextTruncator
+
+
+@runtime_checkable
+class ContextCompressor(Protocol):
+    """
+    Protocol for context compressors.
+    Provides an interface for compressing message lists.
+    """
+
+    def should_compress(
+        self, messages: list[Message], current_tokens: int, max_tokens: int
+    ) -> bool:
+        """Check if compression is needed.
+
+        Args:
+            messages: The message list to evaluate.
+            current_tokens: The current token count.
+            max_tokens: The maximum allowed tokens for the model.
+
+        Returns:
+            True if compression is needed, False otherwise.
+        """
+        ...
+
+    async def __call__(self, messages: list[Message]) -> list[Message]:
+        """Compress the message list.
+
+        Args:
+            messages: The original message list.
+
+        Returns:
+            The compressed message list.
+        """
+        ...
+
+
+class TruncateByTurnsCompressor:
+    """Truncate by turns compressor implementation.
+    Truncates the message list by removing older turns.
+    """
+
+    def __init__(
+        self, truncate_turns: int = 1, compression_threshold: float = 0.82
+    ) -> None:
+        """Initialize the truncate by turns compressor.
+
+        Args:
+            truncate_turns: The number of turns to remove when truncating (default: 1).
+            compression_threshold: The compression trigger threshold (default: 0.82).
+        """
+        self.truncate_turns = truncate_turns
+        self.compression_threshold = compression_threshold
+
+    def should_compress(
+        self, messages: list[Message], current_tokens: int, max_tokens: int
+    ) -> bool:
+        """Check if compression is needed.
+
+        Args:
+            messages: The message list to evaluate.
+            current_tokens: The current token count.
+            max_tokens: The maximum allowed tokens.
+
+        Returns:
+            True if compression is needed, False otherwise.
+        """
+        if max_tokens <= 0 or current_tokens <= 0:
+            return False
+        usage_rate = current_tokens / max_tokens
+        return usage_rate > self.compression_threshold
+
+    async def __call__(self, messages: list[Message]) -> list[Message]:
+        truncator = ContextTruncator()
+        truncated_messages = truncator.truncate_by_dropping_oldest_turns(
+            messages,
+            drop_turns=self.truncate_turns,
+        )
+        return truncated_messages
+
+
+def split_history(
+    messages: list[Message], keep_recent: int
+) -> tuple[list[Message], list[Message], list[Message]]:
+    """Split the message list into system messages, messages to summarize, and recent messages.
+
+    Ensures that the split point is between complete user-assistant pairs to maintain conversation flow.
+
+    Args:
+        messages: The original message list.
+        keep_recent: The number of latest messages to keep.
+
+    Returns:
+        tuple: (system_messages, messages_to_summarize, recent_messages)
+    """
+    # keep the system messages
+    first_non_system = 0
+    for i, msg in enumerate(messages):
+        if msg.role != "system":
+            first_non_system = i
+            break
+
+    system_messages = messages[:first_non_system]
+    non_system_messages = messages[first_non_system:]
+
+    if len(non_system_messages) <= keep_recent:
+        return system_messages, [], non_system_messages
+
+    # Find the split point, ensuring recent_messages starts with a user message
+    # This maintains complete conversation turns
+    split_index = len(non_system_messages) - keep_recent
+
+    # Search backward from split_index to find the first user message
+    # This ensures recent_messages starts with a user message (complete turn)
+    while split_index > 0 and non_system_messages[split_index].role != "user":
+        # TODO: +=1 or -=1 ? calculate by tokens
+        split_index -= 1
+
+    # If we couldn't find a user message, keep all messages as recent
+    if split_index == 0:
+        return system_messages, [], non_system_messages
+
+    messages_to_summarize = non_system_messages[:split_index]
+    recent_messages = non_system_messages[split_index:]
+
+    return system_messages, messages_to_summarize, recent_messages
+
+
+class LLMSummaryCompressor:
+    """LLM-based summary compressor.
+    Uses LLM to summarize the old conversation history, keeping the latest messages.
+    """
+
+    def __init__(
+        self,
+        provider: "Provider",
+        keep_recent: int = 4,
+        instruction_text: str | None = None,
+        compression_threshold: float = 0.82,
+    ) -> None:
+        """Initialize the LLM summary compressor.
+
+        Args:
+            provider: The LLM provider instance.
+            keep_recent: The number of latest messages to keep (default: 4).
+            instruction_text: Custom instruction for summary generation.
+            compression_threshold: The compression trigger threshold (default: 0.82).
+        """
+        self.provider = provider
+        self.keep_recent = keep_recent
+        self.compression_threshold = compression_threshold
+
+        self.instruction_text = instruction_text or (
+            "Based on our full conversation history, produce a concise summary of key takeaways and/or project progress.\n"
+            "1. Systematically cover all core topics discussed and the final conclusion/outcome for each; clearly highlight the latest primary focus.\n"
+            "2. If any tools were used, summarize tool usage (total call count) and extract the most valuable insights from tool outputs.\n"
+            "3. If there was an initial user goal, state it first and describe the current progress/status.\n"
+            "4. Write the summary in the user's language.\n"
+        )
+
+    def should_compress(
+        self, messages: list[Message], current_tokens: int, max_tokens: int
+    ) -> bool:
+        """Check if compression is needed.
+
+        Args:
+            messages: The message list to evaluate.
+            current_tokens: The current token count.
+            max_tokens: The maximum allowed tokens.
+
+        Returns:
+            True if compression is needed, False otherwise.
+        """
+        if max_tokens <= 0 or current_tokens <= 0:
+            return False
+        usage_rate = current_tokens / max_tokens
+        return usage_rate > self.compression_threshold
+
+    async def __call__(self, messages: list[Message]) -> list[Message]:
+        """Use LLM to generate a summary of the conversation history.
+
+        Process:
+        1. Divide messages: keep the system message and the latest N messages.
+        2. Send the old messages + the instruction message to the LLM.
+        3. Reconstruct the message list: [system message, summary message, latest messages].
+        """
+        if len(messages) <= self.keep_recent + 1:
+            return messages
+
+        system_messages, messages_to_summarize, recent_messages = split_history(
+            messages, self.keep_recent
+        )
+
+        if not messages_to_summarize:
+            return messages
+
+        # build payload
+        instruction_message = Message(role="user", content=self.instruction_text)
+        llm_payload = messages_to_summarize + [instruction_message]
+
+        # generate summary
+        try:
+            response = await self.provider.text_chat(contexts=llm_payload)
+            summary_content = response.completion_text
+        except Exception as e:
+            logger.error(f"Failed to generate summary: {e}")
+            return messages
+
+        # build result
+        result = []
+        result.extend(system_messages)
+
+        result.append(
+            Message(
+                role="user",
+                content=f"Our previous history conversation summary: {summary_content}",
+            )
+        )
+        result.append(
+            Message(
+                role="assistant",
+                content="Acknowledged the summary of our previous conversation history.",
+            )
+        )
+
+        result.extend(recent_messages)
+
+        return result
@@ -0,0 +1,35 @@
+from dataclasses import dataclass
+from typing import TYPE_CHECKING
+
+from .compressor import ContextCompressor
+from .token_counter import TokenCounter
+
+if TYPE_CHECKING:
+    from astrbot.core.provider.provider import Provider
+
+
+@dataclass
+class ContextConfig:
+    """Context configuration class."""
+
+    max_context_tokens: int = 0
+    """Maximum number of context tokens. <= 0 means no limit."""
+    enforce_max_turns: int = -1  # -1 means no limit
+    """Maximum number of conversation turns to keep. -1 means no limit. Executed before compression."""
+    truncate_turns: int = 1
+    """Number of conversation turns to discard at once when truncation is triggered.
+    Two processes will use this value:
+
+    1. Enforce max turns truncation.
+    2. Truncation by turns compression strategy.
+    """
+    llm_compress_instruction: str | None = None
+    """Instruction prompt for LLM-based compression."""
+    llm_compress_keep_recent: int = 0
+    """Number of recent messages to keep during LLM-based compression."""
+    llm_compress_provider: "Provider | None" = None
+    """LLM provider used for compression tasks. If None, truncation strategy is used."""
+    custom_token_counter: TokenCounter | None = None
+    """Custom token counting method. If None, the default method is used."""
+    custom_compressor: ContextCompressor | None = None
+    """Custom context compression method. If None, the default method is used."""
@@ -0,0 +1,120 @@
+from astrbot import logger
+
+from ..message import Message
+from .compressor import LLMSummaryCompressor, TruncateByTurnsCompressor
+from .config import ContextConfig
+from .token_counter import EstimateTokenCounter
+from .truncator import ContextTruncator
+
+
+class ContextManager:
+    """Context compression manager."""
+
+    def __init__(
+        self,
+        config: ContextConfig,
+    ) -> None:
+        """Initialize the context manager.
+
+        There are two strategies to handle context limit reached:
+        1. Truncate by turns: remove older messages by turns.
+        2. LLM-based compression: use LLM to summarize old messages.
+
+        Args:
+            config: The context configuration.
+        """
+        self.config = config
+
+        self.token_counter = config.custom_token_counter or EstimateTokenCounter()
+        self.truncator = ContextTruncator()
+
+        if config.custom_compressor:
+            self.compressor = config.custom_compressor
+        elif config.llm_compress_provider:
+            self.compressor = LLMSummaryCompressor(
+                provider=config.llm_compress_provider,
+                keep_recent=config.llm_compress_keep_recent,
+                instruction_text=config.llm_compress_instruction,
+            )
+        else:
+            self.compressor = TruncateByTurnsCompressor(
+                truncate_turns=config.truncate_turns
+            )
+
+    async def process(
+        self, messages: list[Message], trusted_token_usage: int = 0
+    ) -> list[Message]:
+        """Process the messages.
+
+        Args:
+            messages: The original message list.
+
+        Returns:
+            The processed message list.
+        """
+        try:
+            result = messages
+
+            # 1. 基于轮次的截断 (Enforce max turns)
+            if self.config.enforce_max_turns != -1:
+                result = self.truncator.truncate_by_turns(
+                    result,
+                    keep_most_recent_turns=self.config.enforce_max_turns,
+                    drop_turns=self.config.truncate_turns,
+                )
+
+            # 2. 基于 token 的压缩
+            if self.config.max_context_tokens > 0:
+                total_tokens = self.token_counter.count_tokens(
+                    result, trusted_token_usage
+                )
+
+                if self.compressor.should_compress(
+                    result, total_tokens, self.config.max_context_tokens
+                ):
+                    result = await self._run_compression(result, total_tokens)
+
+            return result
+        except Exception as e:
+            logger.error(f"Error during context processing: {e}", exc_info=True)
+            return messages
+
+    async def _run_compression(
+        self, messages: list[Message], prev_tokens: int
+    ) -> list[Message]:
+        """
+        Compress/truncate the messages.
+
+        Args:
+            messages: The original message list.
+            prev_tokens: The token count before compression.
+
+        Returns:
+            The compressed/truncated message list.
+        """
+        logger.debug("Compress triggered, starting compression...")
+
+        messages = await self.compressor(messages)
+
+        # double check
+        tokens_after_summary = self.token_counter.count_tokens(messages)
+
+        # calculate compress rate
+        compress_rate = (tokens_after_summary / self.config.max_context_tokens) * 100
+        logger.info(
+            f"Compress completed."
+            f" {prev_tokens} -> {tokens_after_summary} tokens,"
+            f" compression rate: {compress_rate:.2f}%.",
+        )
+
+        # last check
+        if self.compressor.should_compress(
+            messages, tokens_after_summary, self.config.max_context_tokens
+        ):
+            logger.info(
+                "Context still exceeds max tokens after compression, applying halving truncation..."
+            )
+            # still need compress, truncate by half
+            messages = self.truncator.truncate_by_halving(messages)
+
+        return messages
@@ -0,0 +1,64 @@
+import json
+from typing import Protocol, runtime_checkable
+
+from ..message import Message, TextPart
+
+
+@runtime_checkable
+class TokenCounter(Protocol):
+    """
+    Protocol for token counters.
+    Provides an interface for counting tokens in message lists.
+    """
+
+    def count_tokens(
+        self, messages: list[Message], trusted_token_usage: int = 0
+    ) -> int:
+        """Count the total tokens in the message list.
+
+        Args:
+            messages: The message list.
+            trusted_token_usage: The total token usage that LLM API returned.
+                For some cases, this value is more accurate.
+                But some API does not return it, so the value defaults to 0.
+
+        Returns:
+            The total token count.
+        """
+        ...
+
+
+class EstimateTokenCounter:
+    """Estimate token counter implementation.
+    Provides a simple estimation of token count based on character types.
+    """
+
+    def count_tokens(
+        self, messages: list[Message], trusted_token_usage: int = 0
+    ) -> int:
+        if trusted_token_usage > 0:
+            return trusted_token_usage
+
+        total = 0
+        for msg in messages:
+            content = msg.content
+            if isinstance(content, str):
+                total += self._estimate_tokens(content)
+            elif isinstance(content, list):
+                # 处理多模态内容
+                for part in content:
+                    if isinstance(part, TextPart):
+                        total += self._estimate_tokens(part.text)
+
+            # 处理 Tool Calls
+            if msg.tool_calls:
+                for tc in msg.tool_calls:
+                    tc_str = json.dumps(tc if isinstance(tc, dict) else tc.model_dump())
+                    total += self._estimate_tokens(tc_str)
+
+        return total
+
+    def _estimate_tokens(self, text: str) -> int:
+        chinese_count = len([c for c in text if "\u4e00" <= c <= "\u9fff"])
+        other_count = len(text) - chinese_count
+        return int(chinese_count * 0.6 + other_count * 0.3)
@@ -0,0 +1,182 @@
+from ..message import Message
+
+
+class ContextTruncator:
+    """Context truncator."""
+
+    def _has_tool_calls(self, message: Message) -> bool:
+        """Check if a message contains tool calls."""
+        return (
+            message.role == "assistant"
+            and message.tool_calls is not None
+            and len(message.tool_calls) > 0
+        )
+
+    def fix_messages(self, messages: list[Message]) -> list[Message]:
+        """修复消息列表，确保 tool call 和 tool response 的配对关系有效。
+
+        此方法确保：
+        1. 每个 `tool` 消息前面都有一个包含 tool_calls 的 `assistant` 消息
+        2. 每个包含 tool_calls 的 `assistant` 消息后面都有对应的 `tool` 响应
+
+        这是 OpenAI Chat Completions API 规范的要求（Gemini 对此执行严格检查）。
+        """
+        if not messages:
+            return messages
+
+        fixed_messages: list[Message] = []
+        pending_assistant: Message | None = None
+        pending_tools: list[Message] = []
+
+        def flush_pending_if_valid() -> None:
+            nonlocal pending_assistant, pending_tools
+            if pending_assistant is not None and pending_tools:
+                fixed_messages.append(pending_assistant)
+                fixed_messages.extend(pending_tools)
+            pending_assistant = None
+            pending_tools = []
+
+        for msg in messages:
+            if msg.role == "tool":
+                # 只有在有挂起的 assistant(tool_calls) 时才记录 tool 响应
+                if pending_assistant is not None:
+                    pending_tools.append(msg)
+                # else: 孤立的 tool 消息，直接忽略
+                continue
+
+            if self._has_tool_calls(msg):
+                # 遇到新的 assistant(tool_calls) 前，先处理旧的 pending 链
+                flush_pending_if_valid()
+                pending_assistant = msg
+                continue
+
+            # 非 tool，且不含 tool_calls 的消息
+            # 先结束任何 pending 链，再正常追加
+            flush_pending_if_valid()
+            fixed_messages.append(msg)
+
+        # 结束时处理最后一个 pending 链
+        flush_pending_if_valid()
+
+        return fixed_messages
+
+    def truncate_by_turns(
+        self,
+        messages: list[Message],
+        keep_most_recent_turns: int,
+        drop_turns: int = 1,
+    ) -> list[Message]:
+        """截断上下文列表，确保不超过最大长度。
+        一个 turn 包含一个 user 消息和一个 assistant 消息。
+        这个方法会保证截断后的上下文列表符合 OpenAI 的上下文格式。
+
+        Args:
+            messages: 上下文列表
+            keep_most_recent_turns: 保留最近的对话轮数
+            drop_turns: 一次性丢弃的对话轮数
+
+        Returns:
+            截断后的上下文列表
+        """
+        if keep_most_recent_turns == -1:
+            return messages
+
+        first_non_system = 0
+        for i, msg in enumerate(messages):
+            if msg.role != "system":
+                first_non_system = i
+                break
+
+        system_messages = messages[:first_non_system]
+        non_system_messages = messages[first_non_system:]
+
+        if len(non_system_messages) // 2 <= keep_most_recent_turns:
+            return messages
+
+        num_to_keep = keep_most_recent_turns - drop_turns + 1
+        if num_to_keep <= 0:
+            truncated_contexts = []
+        else:
+            truncated_contexts = non_system_messages[-num_to_keep * 2 :]
+
+        # 找到第一个 role 为 user 的索引，确保上下文格式正确
+        index = next(
+            (i for i, item in enumerate(truncated_contexts) if item.role == "user"),
+            None,
+        )
+        if index is not None and index > 0:
+            truncated_contexts = truncated_contexts[index:]
+
+        result = system_messages + truncated_contexts
+
+        return self.fix_messages(result)
+
+    def truncate_by_dropping_oldest_turns(
+        self,
+        messages: list[Message],
+        drop_turns: int = 1,
+    ) -> list[Message]:
+        """丢弃最旧的 N 个对话轮次。"""
+        if drop_turns <= 0:
+            return messages
+
+        first_non_system = 0
+        for i, msg in enumerate(messages):
+            if msg.role != "system":
+                first_non_system = i
+                break
+
+        system_messages = messages[:first_non_system]
+        non_system_messages = messages[first_non_system:]
+
+        if len(non_system_messages) // 2 <= drop_turns:
+            truncated_non_system = []
+        else:
+            truncated_non_system = non_system_messages[drop_turns * 2 :]
+
+        index = next(
+            (i for i, item in enumerate(truncated_non_system) if item.role == "user"),
+            None,
+        )
+        if index is not None:
+            truncated_non_system = truncated_non_system[index:]
+        elif truncated_non_system:
+            truncated_non_system = []
+
+        result = system_messages + truncated_non_system
+
+        return self.fix_messages(result)
+
+    def truncate_by_halving(
+        self,
+        messages: list[Message],
+    ) -> list[Message]:
+        """对半砍策略，删除 50% 的消息"""
+        if len(messages) <= 2:
+            return messages
+
+        first_non_system = 0
+        for i, msg in enumerate(messages):
+            if msg.role != "system":
+                first_non_system = i
+                break
+
+        system_messages = messages[:first_non_system]
+        non_system_messages = messages[first_non_system:]
+
+        messages_to_delete = len(non_system_messages) // 2
+        if messages_to_delete == 0:
+            return messages
+
+        truncated_non_system = non_system_messages[messages_to_delete:]
+
+        index = next(
+            (i for i, item in enumerate(truncated_non_system) if item.role == "user"),
+            None,
+        )
+        if index is not None:
+            truncated_non_system = truncated_non_system[index:]
+
+        result = system_messages + truncated_non_system
+
+        return self.fix_messages(result)
@@ -12,16 +12,30 @@ class HandoffTool(FunctionTool, Generic[TContext]):
        self,
        agent: Agent[TContext],
        parameters: dict | None = None,
+        tool_description: str | None = None,
        **kwargs,
-    ):
-        self.agent = agent
+    ) -> None:
+
+        # Avoid passing duplicate `description` to the FunctionTool dataclass.
+        # Some call sites (e.g. SubAgentOrchestrator) pass `description` via kwargs
+        # to override what the main agent sees, while we also compute a default
+        # description here.
+        # `tool_description` is the public description shown to the main LLM.
+        # Keep a separate kwarg to avoid conflicting with FunctionTool's `description`.
+        description = tool_description or self.default_description(agent.name)
        super().__init__(
            name=f"transfer_to_{agent.name}",
            parameters=parameters or self.default_parameters(),
-            description=agent.instructions or self.default_description(agent.name),
+            description=description,
            **kwargs,
        )

+        # Optional provider override for this subagent. When set, the handoff
+        # execution will use this chat provider id instead of the global/default.
+        self.provider_id: str | None = None
+        # Note: Must assign after super().__init__() to prevent parent class from overriding this attribute
+        self.agent = agent
+
    def default_parameters(self) -> dict:
        return {
            "type": "object",
@@ -30,6 +44,19 @@ class HandoffTool(FunctionTool, Generic[TContext]):
                    "type": "string",
                    "description": "The input to be handed off to another agent. This should be a clear and concise request or task.",
                },
+                "image_urls": {
+                    "type": "array",
+                    "items": {"type": "string"},
+                    "description": "Optional: An array of image sources (public HTTP URLs or local file paths) used as references in multimodal tasks such as video generation.",
+                },
+                "background_task": {
+                    "type": "boolean",
+                    "description": (
+                        "Defaults to false. "
+                        "Set to true if the task may take noticeable time, involves external tools, or the user does not need to wait. "
+                        "Use false only for quick, immediate tasks."
+                    ),
+                },
            },
        }

@@ -9,22 +9,22 @@ from .run_context import ContextWrapper, TContext


 class BaseAgentRunHooks(Generic[TContext]):
-    async def on_agent_begin(self, run_context: ContextWrapper[TContext]): ...
+    async def on_agent_begin(self, run_context: ContextWrapper[TContext]) -> None: ...
    async def on_tool_start(
        self,
        run_context: ContextWrapper[TContext],
        tool: FunctionTool,
        tool_args: dict | None,
-    ): ...
+    ) -> None: ...
    async def on_tool_end(
        self,
        run_context: ContextWrapper[TContext],
        tool: FunctionTool,
        tool_args: dict | None,
        tool_result: mcp.types.CallToolResult | None,
-    ): ...
+    ) -> None: ...
    async def on_agent_done(
        self,
        run_context: ContextWrapper[TContext],
        llm_response: LLMResponse,
-    ): ...
+    ) -> None: ...
@@ -4,6 +4,14 @@ from contextlib import AsyncExitStack
 from datetime import timedelta
 from typing import Generic

+from tenacity import (
+    before_sleep_log,
+    retry,
+    retry_if_exception_type,
+    stop_after_attempt,
+    wait_exponential,
+)
+
 from astrbot import logger
 from astrbot.core.agent.run_context import ContextWrapper
 from astrbot.core.utils.log_pipe import LogPipe
@@ -12,21 +20,24 @@ from .run_context import TContext
 from .tool import FunctionTool

 try:
+    import anyio
    import mcp
    from mcp.client.sse import sse_client
 except (ModuleNotFoundError, ImportError):
-    logger.warning("警告: 缺少依赖库 'mcp'，将无法使用 MCP 服务。")
+    logger.warning(
+        "Warning: Missing 'mcp' dependency, MCP services will be unavailable."
+    )

 try:
    from mcp.client.streamable_http import streamablehttp_client
 except (ModuleNotFoundError, ImportError):
    logger.warning(
-        "警告: 缺少依赖库 'mcp' 或者 mcp 库版本过低，无法使用 Streamable HTTP 连接方式。",
+        "Warning: Missing 'mcp' dependency or MCP library version too old, Streamable HTTP connection unavailable.",
    )


 def _prepare_config(config: dict) -> dict:
-    """准备配置，处理嵌套格式"""
+    """Prepare configuration, handle nested format"""
    if config.get("mcpServers"):
        first_key = next(iter(config["mcpServers"]))
        config = config["mcpServers"][first_key]
@@ -35,7 +46,7 @@ def _prepare_config(config: dict) -> dict:


 async def _quick_test_mcp_connection(config: dict) -> tuple[bool, str]:
-    """快速测试 MCP 服务器可达性"""
+    """Quick test MCP server connectivity"""
    import aiohttp

    cfg = _prepare_config(config.copy())
@@ -50,7 +61,7 @@ async def _quick_test_mcp_connection(config: dict) -> tuple[bool, str]:
        elif "type" in cfg:
            transport_type = cfg["type"]
        else:
-            raise Exception("MCP 连接配置缺少 transport 或 type 字段")
+            raise Exception("MCP connection config missing transport or type field")

        async with aiohttp.ClientSession() as session:
            if transport_type == "streamable_http":
@@ -91,16 +102,17 @@ async def _quick_test_mcp_connection(config: dict) -> tuple[bool, str]:
                    return False, f"HTTP {response.status}: {response.reason}"

    except asyncio.TimeoutError:
-        return False, f"连接超时: {timeout}秒"
+        return False, f"Connection timeout: {timeout} seconds"
    except Exception as e:
        return False, f"{e!s}"


 class MCPClient:
-    def __init__(self):
+    def __init__(self) -> None:
        # Initialize session and client objects
        self.session: mcp.ClientSession | None = None
        self.exit_stack = AsyncExitStack()
+        self._old_exit_stacks: list[AsyncExitStack] = []  # Track old stacks for cleanup

        self.name: str | None = None
        self.active: bool = True
@@ -108,24 +120,38 @@ class MCPClient:
        self.server_errlogs: list[str] = []
        self.running_event = asyncio.Event()

-    async def connect_to_server(self, mcp_server_config: dict, name: str):
-        """连接到 MCP 服务器
+        # Store connection config for reconnection
+        self._mcp_server_config: dict | None = None
+        self._server_name: str | None = None
+        self._reconnect_lock = asyncio.Lock()  # Lock for thread-safe reconnection
+        self._reconnecting: bool = False  # For logging and debugging

-        如果 `url` 参数存在：
-            1. 当 transport 指定为 `streamable_http` 时，使用 Streamable HTTP 连接方式。
-            1. 当 transport 指定为 `sse` 时，使用 SSE 连接方式。
-            2. 如果没有指定，默认使用 SSE 的方式连接到 MCP 服务。
+    async def connect_to_server(self, mcp_server_config: dict, name: str) -> None:
+        """Connect to MCP server
+
+        If `url` parameter exists:
+            1. When transport is specified as `streamable_http`, use Streamable HTTP connection.
+            2. When transport is specified as `sse`, use SSE connection.
+            3. If not specified, default to SSE connection to MCP service.

        Args:
            mcp_server_config (dict): Configuration for the MCP server. See https://modelcontextprotocol.io/quickstart/server

        """
+        # Store config for reconnection
+        self._mcp_server_config = mcp_server_config
+        self._server_name = name
+
        cfg = _prepare_config(mcp_server_config.copy())

-        def logging_callback(msg: str):
-            # 处理 MCP 服务的错误日志
-            print(f"MCP Server {name} Error: {msg}")
-            self.server_errlogs.append(msg)
+        def logging_callback(
+            msg: str | mcp.types.LoggingMessageNotificationParams,
+        ) -> None:
+            # Handle MCP service error logs
+            if isinstance(msg, mcp.types.LoggingMessageNotificationParams):
+                if msg.level in ("warning", "error", "critical", "alert", "emergency"):
+                    log_msg = f"[{msg.level.upper()}] {str(msg.data)}"
+                    self.server_errlogs.append(log_msg)

        if "url" in cfg:
            success, error_msg = await _quick_test_mcp_connection(cfg)
@@ -137,7 +163,7 @@ class MCPClient:
            elif "type" in cfg:
                transport_type = cfg["type"]
            else:
-                raise Exception("MCP 连接配置缺少 transport 或 type 字段")
+                raise Exception("MCP connection config missing transport or type field")

            if transport_type != "streamable_http":
                # SSE transport method
@@ -192,15 +218,24 @@ class MCPClient:
                **cfg,
            )

-            def callback(msg: str):
-                # 处理 MCP 服务的错误日志
-                self.server_errlogs.append(msg)
+            def callback(msg: str | mcp.types.LoggingMessageNotificationParams) -> None:
+                # Handle MCP service error logs
+                if isinstance(msg, mcp.types.LoggingMessageNotificationParams):
+                    if msg.level in (
+                        "warning",
+                        "error",
+                        "critical",
+                        "alert",
+                        "emergency",
+                    ):
+                        log_msg = f"[{msg.level.upper()}] {str(msg.data)}"
+                        self.server_errlogs.append(log_msg)

            stdio_transport = await self.exit_stack.enter_async_context(
                mcp.stdio_client(
                    server_params,
                    errlog=LogPipe(
-                        level=logging.ERROR,
+                        level=logging.INFO,
                        logger=logger,
                        identifier=f"MCPServer-{name}",
                        callback=callback,
@@ -222,10 +257,120 @@ class MCPClient:
        self.tools = response.tools
        return response

-    async def cleanup(self):
-        """Clean up resources"""
-        await self.exit_stack.aclose()
-        self.running_event.set()  # Set the running event to indicate cleanup is done
+    async def _reconnect(self) -> None:
+        """Reconnect to the MCP server using the stored configuration.
+
+        Uses asyncio.Lock to ensure thread-safe reconnection in concurrent environments.
+
+        Raises:
+            Exception: raised when reconnection fails
+        """
+        async with self._reconnect_lock:
+            # Check if already reconnecting (useful for logging)
+            if self._reconnecting:
+                logger.debug(
+                    f"MCP Client {self._server_name} is already reconnecting, skipping"
+                )
+                return
+
+            if not self._mcp_server_config or not self._server_name:
+                raise Exception("Cannot reconnect: missing connection configuration")
+
+            self._reconnecting = True
+            try:
+                logger.info(
+                    f"Attempting to reconnect to MCP server {self._server_name}..."
+                )
+
+                # Save old exit_stack for later cleanup (don't close it now to avoid cancel scope issues)
+                if self.exit_stack:
+                    self._old_exit_stacks.append(self.exit_stack)
+
+                # Mark old session as invalid
+                self.session = None
+
+                # Create new exit stack for new connection
+                self.exit_stack = AsyncExitStack()
+
+                # Reconnect using stored config
+                await self.connect_to_server(self._mcp_server_config, self._server_name)
+                await self.list_tools_and_save()
+
+                logger.info(
+                    f"Successfully reconnected to MCP server {self._server_name}"
+                )
+            except Exception as e:
+                logger.error(
+                    f"Failed to reconnect to MCP server {self._server_name}: {e}"
+                )
+                raise
+            finally:
+                self._reconnecting = False
+
+    async def call_tool_with_reconnect(
+        self,
+        tool_name: str,
+        arguments: dict,
+        read_timeout_seconds: timedelta,
+    ) -> mcp.types.CallToolResult:
+        """Call MCP tool with automatic reconnection on failure, max 2 retries.
+
+        Args:
+            tool_name: tool name
+            arguments: tool arguments
+            read_timeout_seconds: read timeout
+
+        Returns:
+            MCP tool call result
+
+        Raises:
+            ValueError: MCP session is not available
+            anyio.ClosedResourceError: raised after reconnection failure
+        """
+
+        @retry(
+            retry=retry_if_exception_type(anyio.ClosedResourceError),
+            stop=stop_after_attempt(2),
+            wait=wait_exponential(multiplier=1, min=1, max=3),
+            before_sleep=before_sleep_log(logger, logging.WARNING),
+            reraise=True,
+        )
+        async def _call_with_retry():
+            if not self.session:
+                raise ValueError("MCP session is not available for MCP function tools.")
+
+            try:
+                return await self.session.call_tool(
+                    name=tool_name,
+                    arguments=arguments,
+                    read_timeout_seconds=read_timeout_seconds,
+                )
+            except anyio.ClosedResourceError:
+                logger.warning(
+                    f"MCP tool {tool_name} call failed (ClosedResourceError), attempting to reconnect..."
+                )
+                # Attempt to reconnect
+                await self._reconnect()
+                # Reraise the exception to trigger tenacity retry
+                raise
+
+        return await _call_with_retry()
+
+    async def cleanup(self) -> None:
+        """Clean up resources including old exit stacks from reconnections"""
+        # Close current exit stack
+        try:
+            await self.exit_stack.aclose()
+        except Exception as e:
+            logger.debug(f"Error closing current exit stack: {e}")
+
+        # Don't close old exit stacks as they may be in different task contexts
+        # They will be garbage collected naturally
+        # Just clear the list to release references
+        self._old_exit_stacks.clear()
+
+        # Set running_event first to unblock any waiting tasks
+        self.running_event.set()


 class MCPTool(FunctionTool, Generic[TContext]):
@@ -233,7 +378,7 @@ class MCPTool(FunctionTool, Generic[TContext]):

    def __init__(
        self, mcp_tool: mcp.Tool, mcp_client: MCPClient, mcp_server_name: str, **kwargs
-    ):
+    ) -> None:
        super().__init__(
            name=mcp_tool.name,
            description=mcp_tool.description or "",
@@ -246,14 +391,8 @@ class MCPTool(FunctionTool, Generic[TContext]):
    async def call(
        self, context: ContextWrapper[TContext], **kwargs
    ) -> mcp.types.CallToolResult:
-        session = self.mcp_client.session
-        if not session:
-            raise ValueError("MCP session is not available for MCP function tools.")
-        res = await session.call_tool(
-            name=self.mcp_tool.name,
+        return await self.mcp_client.call_tool_with_reconnect(
+            tool_name=self.mcp_tool.name,
            arguments=kwargs,
-            read_timeout_seconds=timedelta(
-                seconds=context.tool_call_timeout,
-            ),
+            read_timeout_seconds=timedelta(seconds=context.tool_call_timeout),
        )
-        return res
@@ -3,7 +3,13 @@

 from typing import Any, ClassVar, Literal, cast

-from pydantic import BaseModel, GetCoreSchemaHandler
+from pydantic import (
+    BaseModel,
+    GetCoreSchemaHandler,
+    PrivateAttr,
+    model_serializer,
+    model_validator,
+)
 from pydantic_core import core_schema


@@ -12,7 +18,7 @@ class ContentPart(BaseModel):

    __content_part_registry: ClassVar[dict[str, type["ContentPart"]]] = {}

-    type: str
+    type: Literal["text", "think", "image_url", "audio_url"]

    def __init_subclass__(cls, **kwargs: Any) -> None:
        super().__init_subclass__(**kwargs)
@@ -63,6 +69,28 @@ class TextPart(ContentPart):
    text: str


+class ThinkPart(ContentPart):
+    """
+    >>> ThinkPart(think="I think I need to think about this.").model_dump()
+    {'type': 'think', 'think': 'I think I need to think about this.', 'encrypted': None}
+    """
+
+    type: str = "think"
+    think: str
+    encrypted: str | None = None
+    """Encrypted thinking content, or signature."""
+
+    def merge_in_place(self, other: Any) -> bool:
+        if not isinstance(other, ThinkPart):
+            return False
+        if self.encrypted:
+            return False
+        self.think += other.think
+        if other.encrypted:
+            self.encrypted = other.encrypted
+        return True
+
+
 class ImageURLPart(ContentPart):
    """
    >>> ImageURLPart(image_url="http://example.com/image.jpg").model_dump()
@@ -119,6 +147,15 @@ class ToolCall(BaseModel):
    """The ID of the tool call."""
    function: FunctionBody
    """The function body of the tool call."""
+    extra_content: dict[str, Any] | None = None
+    """Extra metadata for the tool call."""
+
+    @model_serializer(mode="wrap")
+    def serialize(self, handler):
+        data = handler(self)
+        if self.extra_content is None:
+            data.pop("extra_content", None)
+        return data


 class ToolCallPart(BaseModel):
@@ -138,22 +175,50 @@ class Message(BaseModel):
        "tool",
    ]

-    content: str | list[ContentPart]
+    content: str | list[ContentPart] | None = None
    """The content of the message."""

+    tool_calls: list[ToolCall] | list[dict] | None = None
+    """The tool calls of the message."""
+
+    tool_call_id: str | None = None
+    """The ID of the tool call."""
+
+    _no_save: bool = PrivateAttr(default=False)
+
+    @model_validator(mode="after")
+    def check_content_required(self):
+        # assistant + tool_calls is not None: allow content to be None
+        if self.role == "assistant" and self.tool_calls is not None:
+            return self
+
+        # other all cases: content is required
+        if self.content is None:
+            raise ValueError(
+                "content is required unless role='assistant' and tool_calls is not None"
+            )
+        return self
+
+    @model_serializer(mode="wrap")
+    def serialize(self, handler):
+        data = handler(self)
+        if self.tool_calls is None:
+            data.pop("tool_calls", None)
+        if self.tool_call_id is None:
+            data.pop("tool_call_id", None)
+        return data
+

 class AssistantMessageSegment(Message):
    """A message segment from the assistant."""

    role: Literal["assistant"] = "assistant"
-    tool_calls: list[ToolCall] | list[dict] | None = None


 class ToolCallMessageSegment(Message):
    """A message segment representing a tool call."""

    role: Literal["tool"] = "tool"
-    tool_call_id: str


 class UserMessageSegment(Message):
@@ -1,7 +1,8 @@
 import typing as T
-from dataclasses import dataclass
+from dataclasses import dataclass, field

 from astrbot.core.message.message_event_result import MessageChain
+from astrbot.core.provider.entities import TokenUsage


 class AgentResponseData(T.TypedDict):
@@ -12,3 +13,23 @@ class AgentResponseData(T.TypedDict):
 class AgentResponse:
    type: str
    data: AgentResponseData
+
+
+@dataclass
+class AgentStats:
+    token_usage: TokenUsage = field(default_factory=TokenUsage)
+    start_time: float = 0.0
+    end_time: float = 0.0
+    time_to_first_token: float = 0.0
+
+    @property
+    def duration(self) -> float:
+        return self.end_time - self.start_time
+
+    def to_dict(self) -> dict:
+        return {
+            "token_usage": self.token_usage.__dict__,
+            "start_time": self.start_time,
+            "end_time": self.end_time,
+            "time_to_first_token": self.time_to_first_token,
+        }
@@ -9,7 +9,7 @@ from .message import Message
 TContext = TypeVar("TContext", default=Any)


-@dataclass(config={"arbitrary_types_allowed": True})
+@dataclass
 class ContextWrapper(Generic[TContext]):
    """A context for running an agent, which can be used to pass additional data or state."""

@@ -2,13 +2,12 @@ import abc
 import typing as T
 from enum import Enum, auto

-from astrbot.core.provider import Provider
+from astrbot import logger
 from astrbot.core.provider.entities import LLMResponse

 from ..hooks import BaseAgentRunHooks
 from ..response import AgentResponse
 from ..run_context import ContextWrapper, TContext
-from ..tool_executor import BaseFunctionToolExecutor


 class AgentState(Enum):
@@ -24,9 +23,7 @@ class BaseAgentRunner(T.Generic[TContext]):
    @abc.abstractmethod
    async def reset(
        self,
-        provider: Provider,
        run_context: ContextWrapper[TContext],
-        tool_executor: BaseFunctionToolExecutor[TContext],
        agent_hooks: BaseAgentRunHooks[TContext],
        **kwargs: T.Any,
    ) -> None:
@@ -60,3 +57,9 @@ class BaseAgentRunner(T.Generic[TContext]):
        This method should be called after the agent is done.
        """
        ...
+
+    def _transition_state(self, new_state: AgentState) -> None:
+        """Transition the agent state."""
+        if self._state != new_state:
+            logger.debug(f"Agent state transition: {self._state} -> {new_state}")
+            self._state = new_state
@@ -0,0 +1,367 @@
+import base64
+import json
+import sys
+import typing as T
+
+import astrbot.core.message.components as Comp
+from astrbot import logger
+from astrbot.core import sp
+from astrbot.core.message.message_event_result import MessageChain
+from astrbot.core.provider.entities import (
+    LLMResponse,
+    ProviderRequest,
+)
+
+from ...hooks import BaseAgentRunHooks
+from ...response import AgentResponseData
+from ...run_context import ContextWrapper, TContext
+from ..base import AgentResponse, AgentState, BaseAgentRunner
+from .coze_api_client import CozeAPIClient
+
+if sys.version_info >= (3, 12):
+    from typing import override
+else:
+    from typing_extensions import override
+
+
+class CozeAgentRunner(BaseAgentRunner[TContext]):
+    """Coze Agent Runner"""
+
+    @override
+    async def reset(
+        self,
+        request: ProviderRequest,
+        run_context: ContextWrapper[TContext],
+        agent_hooks: BaseAgentRunHooks[TContext],
+        provider_config: dict,
+        **kwargs: T.Any,
+    ) -> None:
+        self.req = request
+        self.streaming = kwargs.get("streaming", False)
+        self.final_llm_resp = None
+        self._state = AgentState.IDLE
+        self.agent_hooks = agent_hooks
+        self.run_context = run_context
+
+        self.api_key = provider_config.get("coze_api_key", "")
+        if not self.api_key:
+            raise Exception("Coze API Key 不能为空。")
+        self.bot_id = provider_config.get("bot_id", "")
+        if not self.bot_id:
+            raise Exception("Coze Bot ID 不能为空。")
+        self.api_base: str = provider_config.get("coze_api_base", "https://api.coze.cn")
+
+        if not isinstance(self.api_base, str) or not self.api_base.startswith(
+            ("http://", "https://"),
+        ):
+            raise Exception(
+                "Coze API Base URL 格式不正确，必须以 http:// 或 https:// 开头。",
+            )
+
+        self.timeout = provider_config.get("timeout", 120)
+        if isinstance(self.timeout, str):
+            self.timeout = int(self.timeout)
+        self.auto_save_history = provider_config.get("auto_save_history", True)
+
+        # 创建 API 客户端
+        self.api_client = CozeAPIClient(api_key=self.api_key, api_base=self.api_base)
+
+        # 会话相关缓存
+        self.file_id_cache: dict[str, dict[str, str]] = {}
+
+    @override
+    async def step(self):
+        """
+        执行 Coze Agent 的一个步骤
+        """
+        if not self.req:
+            raise ValueError("Request is not set. Please call reset() first.")
+
+        if self._state == AgentState.IDLE:
+            try:
+                await self.agent_hooks.on_agent_begin(self.run_context)
+            except Exception as e:
+                logger.error(f"Error in on_agent_begin hook: {e}", exc_info=True)
+
+        # 开始处理，转换到运行状态
+        self._transition_state(AgentState.RUNNING)
+
+        try:
+            # 执行 Coze 请求并处理结果
+            async for response in self._execute_coze_request():
+                yield response
+        except Exception as e:
+            logger.error(f"Coze 请求失败：{str(e)}")
+            self._transition_state(AgentState.ERROR)
+            self.final_llm_resp = LLMResponse(
+                role="err", completion_text=f"Coze 请求失败：{str(e)}"
+            )
+            yield AgentResponse(
+                type="err",
+                data=AgentResponseData(
+                    chain=MessageChain().message(f"Coze 请求失败：{str(e)}")
+                ),
+            )
+        finally:
+            await self.api_client.close()
+
+    @override
+    async def step_until_done(
+        self, max_step: int = 30
+    ) -> T.AsyncGenerator[AgentResponse, None]:
+        while not self.done():
+            async for resp in self.step():
+                yield resp
+
+    async def _execute_coze_request(self):
+        """执行 Coze 请求的核心逻辑"""
+        prompt = self.req.prompt or ""
+        session_id = self.req.session_id or "unknown"
+        image_urls = self.req.image_urls or []
+        contexts = self.req.contexts or []
+        system_prompt = self.req.system_prompt
+
+        # 用户ID参数
+        user_id = session_id
+
+        # 获取或创建会话ID
+        conversation_id = await sp.get_async(
+            scope="umo",
+            scope_id=user_id,
+            key="coze_conversation_id",
+            default="",
+        )
+
+        # 构建消息
+        additional_messages = []
+
+        if system_prompt:
+            if not self.auto_save_history or not conversation_id:
+                additional_messages.append(
+                    {
+                        "role": "system",
+                        "content": system_prompt,
+                        "content_type": "text",
+                    },
+                )
+
+        # 处理历史上下文
+        if not self.auto_save_history and contexts:
+            for ctx in contexts:
+                if isinstance(ctx, dict) and "role" in ctx and "content" in ctx:
+                    # 处理上下文中的图片
+                    content = ctx["content"]
+                    if isinstance(content, list):
+                        # 多模态内容，需要处理图片
+                        processed_content = []
+                        for item in content:
+                            if isinstance(item, dict):
+                                if item.get("type") == "text":
+                                    processed_content.append(item)
+                                elif item.get("type") == "image_url":
+                                    # 处理图片上传
+                                    try:
+                                        image_data = item.get("image_url", {})
+                                        url = image_data.get("url", "")
+                                        if url:
+                                            file_id = (
+                                                await self._download_and_upload_image(
+                                                    url, session_id
+                                                )
+                                            )
+                                            processed_content.append(
+                                                {
+                                                    "type": "file",
+                                                    "file_id": file_id,
+                                                    "file_url": url,
+                                                }
+                                            )
+                                    except Exception as e:
+                                        logger.warning(f"处理上下文图片失败: {e}")
+                                        continue
+
+                        if processed_content:
+                            additional_messages.append(
+                                {
+                                    "role": ctx["role"],
+                                    "content": processed_content,
+                                    "content_type": "object_string",
+                                }
+                            )
+                    else:
+                        # 纯文本内容
+                        additional_messages.append(
+                            {
+                                "role": ctx["role"],
+                                "content": content,
+                                "content_type": "text",
+                            }
+                        )
+
+        # 构建当前消息
+        if prompt or image_urls:
+            if image_urls:
+                # 多模态
+                object_string_content = []
+                if prompt:
+                    object_string_content.append({"type": "text", "text": prompt})
+
+                for url in image_urls:
+                    # the url is a base64 string
+                    try:
+                        image_data = base64.b64decode(url)
+                        file_id = await self.api_client.upload_file(image_data)
+                        object_string_content.append(
+                            {
+                                "type": "image",
+                                "file_id": file_id,
+                            }
+                        )
+                    except Exception as e:
+                        logger.warning(f"处理图片失败 {url}: {e}")
+                        continue
+
+                if object_string_content:
+                    content = json.dumps(object_string_content, ensure_ascii=False)
+                    additional_messages.append(
+                        {
+                            "role": "user",
+                            "content": content,
+                            "content_type": "object_string",
+                        }
+                    )
+            elif prompt:
+                # 纯文本
+                additional_messages.append(
+                    {
+                        "role": "user",
+                        "content": prompt,
+                        "content_type": "text",
+                    },
+                )
+
+        # 执行 Coze API 请求
+        accumulated_content = ""
+        message_started = False
+
+        async for chunk in self.api_client.chat_messages(
+            bot_id=self.bot_id,
+            user_id=user_id,
+            additional_messages=additional_messages,
+            conversation_id=conversation_id,
+            auto_save_history=self.auto_save_history,
+            stream=True,
+            timeout=self.timeout,
+        ):
+            event_type = chunk.get("event")
+            data = chunk.get("data", {})
+
+            if event_type == "conversation.chat.created":
+                if isinstance(data, dict) and "conversation_id" in data:
+                    await sp.put_async(
+                        scope="umo",
+                        scope_id=user_id,
+                        key="coze_conversation_id",
+                        value=data["conversation_id"],
+                    )
+
+            if event_type == "conversation.message.delta":
+                # 增量消息
+                content = data.get("content", "")
+                if not content and "delta" in data:
+                    content = data["delta"].get("content", "")
+                if not content and "text" in data:
+                    content = data.get("text", "")
+
+                if content:
+                    accumulated_content += content
+                    message_started = True
+
+                    # 如果是流式响应，发送增量数据
+                    if self.streaming:
+                        yield AgentResponse(
+                            type="streaming_delta",
+                            data=AgentResponseData(
+                                chain=MessageChain().message(content)
+                            ),
+                        )
+
+            elif event_type == "conversation.message.completed":
+                # 消息完成
+                logger.debug("Coze message completed")
+                message_started = True
+
+            elif event_type == "conversation.chat.completed":
+                # 对话完成
+                logger.debug("Coze chat completed")
+                break
+
+            elif event_type == "error":
+                # 错误处理
+                error_msg = data.get("msg", "未知错误")
+                error_code = data.get("code", "UNKNOWN")
+                logger.error(f"Coze 出现错误: {error_code} - {error_msg}")
+                raise Exception(f"Coze 出现错误: {error_code} - {error_msg}")
+
+        if not message_started and not accumulated_content:
+            logger.warning("Coze 未返回任何内容")
+            accumulated_content = ""
+
+        # 创建最终响应
+        chain = MessageChain(chain=[Comp.Plain(accumulated_content)])
+        self.final_llm_resp = LLMResponse(role="assistant", result_chain=chain)
+        self._transition_state(AgentState.DONE)
+
+        try:
+            await self.agent_hooks.on_agent_done(self.run_context, self.final_llm_resp)
+        except Exception as e:
+            logger.error(f"Error in on_agent_done hook: {e}", exc_info=True)
+
+        # 返回最终结果
+        yield AgentResponse(
+            type="llm_result",
+            data=AgentResponseData(chain=chain),
+        )
+
+    async def _download_and_upload_image(
+        self,
+        image_url: str,
+        session_id: str | None = None,
+    ) -> str:
+        """下载图片并上传到 Coze，返回 file_id"""
+        import hashlib
+
+        # 计算哈希实现缓存
+        cache_key = hashlib.md5(image_url.encode("utf-8")).hexdigest()
+
+        if session_id:
+            if session_id not in self.file_id_cache:
+                self.file_id_cache[session_id] = {}
+
+            if cache_key in self.file_id_cache[session_id]:
+                file_id = self.file_id_cache[session_id][cache_key]
+                logger.debug(f"[Coze] 使用缓存的 file_id: {file_id}")
+                return file_id
+
+        try:
+            image_data = await self.api_client.download_image(image_url)
+            file_id = await self.api_client.upload_file(image_data)
+
+            if session_id:
+                self.file_id_cache[session_id][cache_key] = file_id
+                logger.debug(f"[Coze] 图片上传成功并缓存，file_id: {file_id}")
+
+            return file_id
+
+        except Exception as e:
+            logger.error(f"处理图片失败 {image_url}: {e!s}")
+            raise Exception(f"处理图片失败: {e!s}")
+
+    @override
+    def done(self) -> bool:
+        """检查 Agent 是否已完成工作"""
+        return self._state in (AgentState.DONE, AgentState.ERROR)
+
+    @override
+    def get_final_llm_resp(self) -> LLMResponse | None:
+        return self.final_llm_resp
@@ -10,7 +10,7 @@ from astrbot.core import logger


 class CozeAPIClient:
-    def __init__(self, api_key: str, api_base: str = "https://api.coze.cn"):
+    def __init__(self, api_key: str, api_base: str = "https://api.coze.cn") -> None:
        self.api_key = api_key
        self.api_base = api_base
        self.session = None
@@ -277,7 +277,7 @@ class CozeAPIClient:
            logger.error(f"获取Coze消息列表失败: {e!s}")
            raise Exception(f"获取Coze消息列表失败: {e!s}")

-    async def close(self):
+    async def close(self) -> None:
        """关闭会话"""
        if self.session:
            await self.session.close()
@@ -288,7 +288,7 @@ if __name__ == "__main__":
    import asyncio
    import os

-    async def test_coze_api_client():
+    async def test_coze_api_client() -> None:
        api_key = os.getenv("COZE_API_KEY", "")
        bot_id = os.getenv("COZE_BOT_ID", "")
        client = CozeAPIClient(api_key=api_key)
@@ -0,0 +1,403 @@
+import asyncio
+import functools
+import queue
+import re
+import sys
+import threading
+import typing as T
+
+from dashscope import Application
+from dashscope.app.application_response import ApplicationResponse
+
+import astrbot.core.message.components as Comp
+from astrbot.core import logger, sp
+from astrbot.core.message.message_event_result import MessageChain
+from astrbot.core.provider.entities import (
+    LLMResponse,
+    ProviderRequest,
+)
+
+from ...hooks import BaseAgentRunHooks
+from ...response import AgentResponseData
+from ...run_context import ContextWrapper, TContext
+from ..base import AgentResponse, AgentState, BaseAgentRunner
+
+if sys.version_info >= (3, 12):
+    from typing import override
+else:
+    from typing_extensions import override
+
+
+class DashscopeAgentRunner(BaseAgentRunner[TContext]):
+    """Dashscope Agent Runner"""
+
+    @override
+    async def reset(
+        self,
+        request: ProviderRequest,
+        run_context: ContextWrapper[TContext],
+        agent_hooks: BaseAgentRunHooks[TContext],
+        provider_config: dict,
+        **kwargs: T.Any,
+    ) -> None:
+        self.req = request
+        self.streaming = kwargs.get("streaming", False)
+        self.final_llm_resp = None
+        self._state = AgentState.IDLE
+        self.agent_hooks = agent_hooks
+        self.run_context = run_context
+
+        self.api_key = provider_config.get("dashscope_api_key", "")
+        if not self.api_key:
+            raise Exception("阿里云百炼 API Key 不能为空。")
+        self.app_id = provider_config.get("dashscope_app_id", "")
+        if not self.app_id:
+            raise Exception("阿里云百炼 APP ID 不能为空。")
+        self.dashscope_app_type = provider_config.get("dashscope_app_type", "")
+        if not self.dashscope_app_type:
+            raise Exception("阿里云百炼 APP 类型不能为空。")
+
+        self.variables: dict = provider_config.get("variables", {}) or {}
+        self.rag_options: dict = provider_config.get("rag_options", {})
+        self.output_reference = self.rag_options.get("output_reference", False)
+        self.rag_options = self.rag_options.copy()
+        self.rag_options.pop("output_reference", None)
+
+        self.timeout = provider_config.get("timeout", 120)
+        if isinstance(self.timeout, str):
+            self.timeout = int(self.timeout)
+
+    def has_rag_options(self) -> bool:
+        """判断是否有 RAG 选项
+
+        Returns:
+            bool: 是否有 RAG 选项
+
+        """
+        if self.rag_options and (
+            len(self.rag_options.get("pipeline_ids", [])) > 0
+            or len(self.rag_options.get("file_ids", [])) > 0
+        ):
+            return True
+        return False
+
+    @override
+    async def step(self):
+        """
+        执行 Dashscope Agent 的一个步骤
+        """
+        if not self.req:
+            raise ValueError("Request is not set. Please call reset() first.")
+
+        if self._state == AgentState.IDLE:
+            try:
+                await self.agent_hooks.on_agent_begin(self.run_context)
+            except Exception as e:
+                logger.error(f"Error in on_agent_begin hook: {e}", exc_info=True)
+
+        # 开始处理，转换到运行状态
+        self._transition_state(AgentState.RUNNING)
+
+        try:
+            # 执行 Dashscope 请求并处理结果
+            async for response in self._execute_dashscope_request():
+                yield response
+        except Exception as e:
+            logger.error(f"阿里云百炼请求失败：{str(e)}")
+            self._transition_state(AgentState.ERROR)
+            self.final_llm_resp = LLMResponse(
+                role="err", completion_text=f"阿里云百炼请求失败：{str(e)}"
+            )
+            yield AgentResponse(
+                type="err",
+                data=AgentResponseData(
+                    chain=MessageChain().message(f"阿里云百炼请求失败：{str(e)}")
+                ),
+            )
+
+    @override
+    async def step_until_done(
+        self, max_step: int = 30
+    ) -> T.AsyncGenerator[AgentResponse, None]:
+        while not self.done():
+            async for resp in self.step():
+                yield resp
+
+    def _consume_sync_generator(
+        self, response: T.Any, response_queue: queue.Queue
+    ) -> None:
+        """在线程中消费同步generator,将结果放入队列
+
+        Args:
+            response: 同步generator对象
+            response_queue: 用于传递数据的队列
+
+        """
+        try:
+            if self.streaming:
+                for chunk in response:
+                    response_queue.put(("data", chunk))
+            else:
+                response_queue.put(("data", response))
+        except Exception as e:
+            response_queue.put(("error", e))
+        finally:
+            response_queue.put(("done", None))
+
+    async def _process_stream_chunk(
+        self, chunk: ApplicationResponse, output_text: str
+    ) -> tuple[str, list | None, AgentResponse | None]:
+        """处理流式响应的单个chunk
+
+        Args:
+            chunk: Dashscope响应chunk
+            output_text: 当前累积的输出文本
+
+        Returns:
+            (更新后的output_text, doc_references, AgentResponse或None)
+
+        """
+        logger.debug(f"dashscope stream chunk: {chunk}")
+
+        if chunk.status_code != 200:
+            logger.error(
+                f"阿里云百炼请求失败: request_id={chunk.request_id}, code={chunk.status_code}, message={chunk.message}, 请参考文档：https://help.aliyun.com/zh/model-studio/developer-reference/error-code",
+            )
+            self._transition_state(AgentState.ERROR)
+            error_msg = (
+                f"阿里云百炼请求失败: message={chunk.message} code={chunk.status_code}"
+            )
+            self.final_llm_resp = LLMResponse(
+                role="err",
+                result_chain=MessageChain().message(error_msg),
+            )
+            return (
+                output_text,
+                None,
+                AgentResponse(
+                    type="err",
+                    data=AgentResponseData(chain=MessageChain().message(error_msg)),
+                ),
+            )
+
+        chunk_text = chunk.output.get("text", "") or ""
+        # RAG 引用脚标格式化
+        chunk_text = re.sub(r"<ref>\[(\d+)\]</ref>", r"[\1]", chunk_text)
+
+        response = None
+        if chunk_text:
+            output_text += chunk_text
+            response = AgentResponse(
+                type="streaming_delta",
+                data=AgentResponseData(chain=MessageChain().message(chunk_text)),
+            )
+
+        # 获取文档引用
+        doc_references = chunk.output.get("doc_references", None)
+
+        return output_text, doc_references, response
+
+    def _format_doc_references(self, doc_references: list) -> str:
+        """格式化文档引用为文本
+
+        Args:
+            doc_references: 文档引用列表
+
+        Returns:
+            格式化后的引用文本
+
+        """
+        ref_parts = []
+        for ref in doc_references:
+            ref_title = (
+                ref.get("title", "") if ref.get("title") else ref.get("doc_name", "")
+            )
+            ref_parts.append(f"{ref['index_id']}. {ref_title}\n")
+        ref_str = "".join(ref_parts)
+        return f"\n\n回答来源:\n{ref_str}"
+
+    async def _build_request_payload(
+        self, prompt: str, session_id: str, contexts: list, system_prompt: str
+    ) -> dict:
+        """构建请求payload
+
+        Args:
+            prompt: 用户输入
+            session_id: 会话ID
+            contexts: 上下文列表
+            system_prompt: 系统提示词
+
+        Returns:
+            请求payload字典
+
+        """
+        conversation_id = await sp.get_async(
+            scope="umo",
+            scope_id=session_id,
+            key="dashscope_conversation_id",
+            default="",
+        )
+        # 获得会话变量
+        payload_vars = self.variables.copy()
+        session_var = await sp.get_async(
+            scope="umo",
+            scope_id=session_id,
+            key="session_variables",
+            default={},
+        )
+        payload_vars.update(session_var)
+
+        if (
+            self.dashscope_app_type in ["agent", "dialog-workflow"]
+            and not self.has_rag_options()
+        ):
+            # 支持多轮对话的
+            p = {
+                "app_id": self.app_id,
+                "api_key": self.api_key,
+                "prompt": prompt,
+                "biz_params": payload_vars or None,
+                "stream": self.streaming,
+                "incremental_output": True,
+            }
+            if conversation_id:
+                p["session_id"] = conversation_id
+            return p
+        else:
+            # 不支持多轮对话的
+            payload = {
+                "app_id": self.app_id,
+                "prompt": prompt,
+                "api_key": self.api_key,
+                "biz_params": payload_vars or None,
+                "stream": self.streaming,
+                "incremental_output": True,
+            }
+            if self.rag_options:
+                payload["rag_options"] = self.rag_options
+            return payload
+
+    async def _handle_streaming_response(
+        self, response: T.Any, session_id: str
+    ) -> T.AsyncGenerator[AgentResponse, None]:
+        """处理流式响应
+
+        Args:
+            response: Dashscope 流式响应 generator
+
+        Yields:
+            AgentResponse 对象
+
+        """
+        response_queue = queue.Queue()
+        consumer_thread = threading.Thread(
+            target=self._consume_sync_generator,
+            args=(response, response_queue),
+            daemon=True,
+        )
+        consumer_thread.start()
+
+        output_text = ""
+        doc_references = None
+
+        while True:
+            try:
+                item_type, item_data = await asyncio.get_running_loop().run_in_executor(
+                    None, response_queue.get, True, 1
+                )
+            except queue.Empty:
+                continue
+
+            if item_type == "done":
+                break
+            elif item_type == "error":
+                raise item_data
+            elif item_type == "data":
+                chunk = item_data
+                assert isinstance(chunk, ApplicationResponse)
+
+                (
+                    output_text,
+                    chunk_doc_refs,
+                    response,
+                ) = await self._process_stream_chunk(chunk, output_text)
+
+                if response:
+                    if response.type == "err":
+                        yield response
+                        return
+                    yield response
+
+                if chunk_doc_refs:
+                    doc_references = chunk_doc_refs
+
+                if chunk.output.session_id:
+                    await sp.put_async(
+                        scope="umo",
+                        scope_id=session_id,
+                        key="dashscope_conversation_id",
+                        value=chunk.output.session_id,
+                    )
+
+        # 添加 RAG 引用
+        if self.output_reference and doc_references:
+            ref_text = self._format_doc_references(doc_references)
+            output_text += ref_text
+
+            if self.streaming:
+                yield AgentResponse(
+                    type="streaming_delta",
+                    data=AgentResponseData(chain=MessageChain().message(ref_text)),
+                )
+
+        # 创建最终响应
+        chain = MessageChain(chain=[Comp.Plain(output_text)])
+        self.final_llm_resp = LLMResponse(role="assistant", result_chain=chain)
+        self._transition_state(AgentState.DONE)
+
+        try:
+            await self.agent_hooks.on_agent_done(self.run_context, self.final_llm_resp)
+        except Exception as e:
+            logger.error(f"Error in on_agent_done hook: {e}", exc_info=True)
+
+        # 返回最终结果
+        yield AgentResponse(
+            type="llm_result",
+            data=AgentResponseData(chain=chain),
+        )
+
+    async def _execute_dashscope_request(self):
+        """执行 Dashscope 请求的核心逻辑"""
+        prompt = self.req.prompt or ""
+        session_id = self.req.session_id or "unknown"
+        image_urls = self.req.image_urls or []
+        contexts = self.req.contexts or []
+        system_prompt = self.req.system_prompt
+
+        # 检查图片输入
+        if image_urls:
+            logger.warning("阿里云百炼暂不支持图片输入，将自动忽略图片内容。")
+
+        # 构建请求payload
+        payload = await self._build_request_payload(
+            prompt, session_id, contexts, system_prompt
+        )
+
+        if not self.streaming:
+            payload["incremental_output"] = False
+
+        # 发起请求
+        partial = functools.partial(Application.call, **payload)
+        response = await asyncio.get_running_loop().run_in_executor(None, partial)
+
+        async for resp in self._handle_streaming_response(response, session_id):
+            yield resp
+
+    @override
+    def done(self) -> bool:
+        """检查 Agent 是否已完成工作"""
+        return self._state in (AgentState.DONE, AgentState.ERROR)
+
+    @override
+    def get_final_llm_resp(self) -> LLMResponse | None:
+        return self.final_llm_resp
@@ -0,0 +1,4 @@
+DEERFLOW_PROVIDER_TYPE = "deerflow"
+DEERFLOW_THREAD_ID_KEY = "deerflow_thread_id"
+DEERFLOW_SESSION_PREFIX = "deerflow-ephemeral"
+DEERFLOW_AGENT_RUNNER_PROVIDER_ID_KEY = "deerflow_agent_runner_provider_id"
@@ -0,0 +1,693 @@
+import asyncio
+import hashlib
+import json
+import sys
+import typing as T
+from collections import deque
+from dataclasses import dataclass, field
+from uuid import uuid4
+
+import astrbot.core.message.components as Comp
+from astrbot import logger
+from astrbot.core import sp
+from astrbot.core.message.message_event_result import MessageChain
+from astrbot.core.provider.entities import (
+    LLMResponse,
+    ProviderRequest,
+)
+from astrbot.core.utils.config_number import coerce_int_config
+
+from ...hooks import BaseAgentRunHooks
+from ...response import AgentResponseData
+from ...run_context import ContextWrapper, TContext
+from ..base import AgentResponse, AgentState, BaseAgentRunner
+from .constants import DEERFLOW_SESSION_PREFIX, DEERFLOW_THREAD_ID_KEY
+from .deerflow_api_client import DeerFlowAPIClient
+from .deerflow_content_mapper import (
+    build_chain_from_ai_content,
+    build_user_content,
+    image_component_from_url,
+)
+from .deerflow_stream_utils import (
+    build_task_failure_summary,
+    extract_ai_delta_from_event_data,
+    extract_clarification_from_event_data,
+    extract_latest_ai_message,
+    extract_latest_ai_text,
+    extract_latest_clarification_text,
+    extract_messages_from_values_data,
+    extract_task_failures_from_custom_event,
+    get_message_id,
+)
+
+if sys.version_info >= (3, 12):
+    from typing import override
+else:
+    from typing_extensions import override
+
+
+class DeerFlowAgentRunner(BaseAgentRunner[TContext]):
+    """DeerFlow Agent Runner via LangGraph HTTP API."""
+
+    _MAX_VALUES_HISTORY = 200
+
+    @dataclass(frozen=True)
+    class _RunnerConfig:
+        api_base: str
+        api_key: str
+        auth_header: str
+        proxy: str
+        assistant_id: str
+        model_name: str
+        thinking_enabled: bool
+        plan_mode: bool
+        subagent_enabled: bool
+        max_concurrent_subagents: int
+        timeout: int
+        recursion_limit: int
+
+    @dataclass
+    class _StreamState:
+        latest_text: str = ""
+        prev_text_for_streaming: str = ""
+        clarification_text: str = ""
+        task_failures: list[str] = field(default_factory=list)
+        seen_message_ids: set[str] = field(default_factory=set)
+        seen_message_order: deque[str] = field(default_factory=deque)
+        # Fallback tracking for backends that omit message ids in values events.
+        no_id_message_fingerprints: dict[int, str] = field(default_factory=dict)
+        baseline_initialized: bool = False
+        has_values_text: bool = False
+        run_values_messages: list[dict[str, T.Any]] = field(default_factory=list)
+        timed_out: bool = False
+
+    @dataclass(frozen=True)
+    class _FinalResult:
+        chain: MessageChain
+        role: str
+
+    def _format_exception(self, err: Exception) -> str:
+        err_type = type(err).__name__
+        detail = str(err).strip()
+
+        if isinstance(err, (asyncio.TimeoutError, TimeoutError)):
+            timeout_text = (
+                f"{self.timeout}s"
+                if isinstance(getattr(self, "timeout", None), (int, float))
+                else "configured timeout"
+            )
+            return (
+                f"{err_type}: request timed out after {timeout_text}. "
+                "Please check DeerFlow service health and backend logs."
+            )
+
+        if detail:
+            if detail.startswith(f"{err_type}:"):
+                return detail
+            return f"{err_type}: {detail}"
+
+        return f"{err_type}: no detailed error message provided."
+
+    async def close(self) -> None:
+        """Explicit cleanup hook for long-lived workers."""
+        api_client = getattr(self, "api_client", None)
+        if isinstance(api_client, DeerFlowAPIClient) and not api_client.is_closed:
+            try:
+                await api_client.close()
+            except Exception as e:
+                logger.warning(
+                    "Failed to close DeerFlowAPIClient during runner shutdown: %s",
+                    e,
+                    exc_info=True,
+                )
+
+    async def _notify_agent_done_hook(self) -> None:
+        if not self.final_llm_resp:
+            return
+        try:
+            await self.agent_hooks.on_agent_done(self.run_context, self.final_llm_resp)
+        except Exception as e:
+            logger.error(f"Error in on_agent_done hook: {e}", exc_info=True)
+
+    async def _finish_with_result(
+        self, chain: MessageChain, role: str
+    ) -> AgentResponse:
+        self.final_llm_resp = LLMResponse(
+            role=role,
+            result_chain=chain,
+        )
+        self._transition_state(AgentState.DONE)
+        await self._notify_agent_done_hook()
+        return AgentResponse(
+            type="llm_result",
+            data=AgentResponseData(chain=chain),
+        )
+
+    async def _finish_with_error(self, err_msg: str) -> AgentResponse:
+        err_text = f"DeerFlow request failed: {err_msg}"
+        err_chain = MessageChain().message(err_text)
+        self.final_llm_resp = LLMResponse(
+            role="err",
+            completion_text=err_text,
+            result_chain=err_chain,
+        )
+        self._transition_state(AgentState.ERROR)
+        await self._notify_agent_done_hook()
+        return AgentResponse(
+            type="err",
+            data=AgentResponseData(
+                chain=err_chain,
+            ),
+        )
+
+    def _parse_runner_config(self, provider_config: dict) -> _RunnerConfig:
+        api_base = provider_config.get("deerflow_api_base", "http://127.0.0.1:2026")
+        if not isinstance(api_base, str) or not api_base.startswith(
+            ("http://", "https://"),
+        ):
+            raise ValueError(
+                "DeerFlow API Base URL format is invalid. It must start with http:// or https://.",
+            )
+
+        proxy = provider_config.get("proxy", "")
+        normalized_proxy = proxy.strip() if isinstance(proxy, str) else ""
+
+        return self._RunnerConfig(
+            api_base=api_base,
+            api_key=provider_config.get("deerflow_api_key", ""),
+            auth_header=provider_config.get("deerflow_auth_header", ""),
+            proxy=normalized_proxy,
+            assistant_id=provider_config.get("deerflow_assistant_id", "lead_agent"),
+            model_name=provider_config.get("deerflow_model_name", ""),
+            thinking_enabled=bool(
+                provider_config.get("deerflow_thinking_enabled", False),
+            ),
+            plan_mode=bool(provider_config.get("deerflow_plan_mode", False)),
+            subagent_enabled=bool(
+                provider_config.get("deerflow_subagent_enabled", False),
+            ),
+            max_concurrent_subagents=coerce_int_config(
+                provider_config.get("deerflow_max_concurrent_subagents", 3),
+                default=3,
+                min_value=1,
+                field_name="deerflow_max_concurrent_subagents",
+                source="DeerFlow config",
+            ),
+            timeout=coerce_int_config(
+                provider_config.get("timeout", 300),
+                default=300,
+                min_value=1,
+                field_name="timeout",
+                source="DeerFlow config",
+            ),
+            recursion_limit=coerce_int_config(
+                provider_config.get("deerflow_recursion_limit", 1000),
+                default=1000,
+                min_value=1,
+                field_name="deerflow_recursion_limit",
+                source="DeerFlow config",
+            ),
+        )
+
+    async def _load_config_and_client(self, provider_config: dict) -> None:
+        config = self._parse_runner_config(provider_config)
+
+        self.api_base = config.api_base
+        self.api_key = config.api_key
+        self.auth_header = config.auth_header
+        self.proxy = config.proxy
+        self.assistant_id = config.assistant_id
+        self.model_name = config.model_name
+        self.thinking_enabled = config.thinking_enabled
+        self.plan_mode = config.plan_mode
+        self.subagent_enabled = config.subagent_enabled
+        self.max_concurrent_subagents = config.max_concurrent_subagents
+        self.timeout = config.timeout
+        self.recursion_limit = config.recursion_limit
+
+        new_client_signature = (
+            config.api_base,
+            config.api_key,
+            config.auth_header,
+            config.proxy,
+        )
+        old_client = getattr(self, "api_client", None)
+        old_signature = getattr(self, "_api_client_signature", None)
+
+        if (
+            isinstance(old_client, DeerFlowAPIClient)
+            and old_signature == new_client_signature
+            and not old_client.is_closed
+        ):
+            self.api_client = old_client
+            return
+
+        if isinstance(old_client, DeerFlowAPIClient):
+            try:
+                await old_client.close()
+            except Exception as e:
+                logger.warning(
+                    f"Failed to close previous DeerFlow API client cleanly: {e}"
+                )
+
+        self.api_client = DeerFlowAPIClient(
+            api_base=config.api_base,
+            api_key=config.api_key,
+            auth_header=config.auth_header,
+            proxy=config.proxy,
+        )
+        self._api_client_signature = new_client_signature
+
+    @override
+    async def reset(
+        self,
+        request: ProviderRequest,
+        run_context: ContextWrapper[TContext],
+        agent_hooks: BaseAgentRunHooks[TContext],
+        provider_config: dict,
+        **kwargs: T.Any,
+    ) -> None:
+        self.req = request
+        self.streaming = kwargs.get("streaming", False)
+        self.final_llm_resp = None
+        self._state = AgentState.IDLE
+        self.agent_hooks = agent_hooks
+        self.run_context = run_context
+
+        await self._load_config_and_client(provider_config)
+
+    @override
+    async def step(self):
+        if not self.req:
+            raise ValueError("Request is not set. Please call reset() first.")
+        if self.done():
+            return
+
+        if self._state == AgentState.IDLE:
+            try:
+                await self.agent_hooks.on_agent_begin(self.run_context)
+            except Exception as e:
+                logger.error(f"Error in on_agent_begin hook: {e}", exc_info=True)
+
+        self._transition_state(AgentState.RUNNING)
+
+        try:
+            async for response in self._execute_deerflow_request():
+                yield response
+        except asyncio.CancelledError:
+            # Let caller manage cancellation semantics.
+            raise
+        except Exception as e:
+            err_msg = self._format_exception(e)
+            logger.error(f"DeerFlow request failed: {err_msg}", exc_info=True)
+            yield await self._finish_with_error(err_msg)
+
+    @override
+    async def step_until_done(
+        self, max_step: int = 30
+    ) -> T.AsyncGenerator[AgentResponse, None]:
+        if max_step <= 0:
+            raise ValueError("max_step must be greater than 0")
+
+        step_count = 0
+        while not self.done() and step_count < max_step:
+            step_count += 1
+            async for resp in self.step():
+                yield resp
+
+        if not self.done():
+            raise RuntimeError(
+                f"DeerFlow agent reached max_step ({max_step}) without completion."
+            )
+
+    def _extract_new_messages_from_values(
+        self,
+        values_messages: list[T.Any],
+        state: _StreamState,
+    ) -> list[dict[str, T.Any]]:
+        new_messages: list[dict[str, T.Any]] = []
+        no_id_indexes_seen: set[int] = set()
+        for idx, msg in enumerate(values_messages):
+            if not isinstance(msg, dict):
+                continue
+            msg_id = get_message_id(msg)
+            if msg_id:
+                if msg_id in state.seen_message_ids:
+                    continue
+                self._remember_seen_message_id(state, msg_id)
+                new_messages.append(msg)
+                continue
+
+            no_id_indexes_seen.add(idx)
+            msg_fingerprint = self._fingerprint_message(msg)
+            if state.no_id_message_fingerprints.get(idx) == msg_fingerprint:
+                continue
+            state.no_id_message_fingerprints[idx] = msg_fingerprint
+            new_messages.append(msg)
+
+        # Keep no-id index state aligned with latest values payload shape.
+        for idx in list(state.no_id_message_fingerprints.keys()):
+            if idx not in no_id_indexes_seen:
+                state.no_id_message_fingerprints.pop(idx, None)
+        return new_messages
+
+    def _fingerprint_message(self, message: dict[str, T.Any]) -> str:
+        try:
+            raw = json.dumps(message, sort_keys=True, ensure_ascii=False, default=str)
+        except (TypeError, ValueError):
+            raw = repr(message)
+        return hashlib.sha1(raw.encode("utf-8", errors="ignore")).hexdigest()
+
+    def _remember_seen_message_id(self, state: _StreamState, msg_id: str) -> None:
+        if not msg_id or msg_id in state.seen_message_ids:
+            return
+
+        state.seen_message_ids.add(msg_id)
+        state.seen_message_order.append(msg_id)
+        while len(state.seen_message_order) > self._MAX_VALUES_HISTORY:
+            dropped = state.seen_message_order.popleft()
+            state.seen_message_ids.discard(dropped)
+
+    async def _ensure_thread_id(self, session_id: str) -> str:
+        thread_id = await sp.get_async(
+            scope="umo",
+            scope_id=session_id,
+            key=DEERFLOW_THREAD_ID_KEY,
+            default="",
+        )
+        if thread_id:
+            return thread_id
+
+        thread = await self.api_client.create_thread(timeout=min(30, self.timeout))
+        thread_id = thread.get("thread_id", "")
+        if not thread_id:
+            raise Exception(
+                f"DeerFlow create thread returned invalid payload: {thread}"
+            )
+
+        await sp.put_async(
+            scope="umo",
+            scope_id=session_id,
+            key=DEERFLOW_THREAD_ID_KEY,
+            value=thread_id,
+        )
+        return thread_id
+
+    def _build_messages(
+        self,
+        prompt: str,
+        image_urls: list[str],
+        system_prompt: str | None,
+    ) -> list[dict[str, T.Any]]:
+        messages: list[dict[str, T.Any]] = []
+        if system_prompt:
+            messages.append({"role": "system", "content": system_prompt})
+        messages.append(
+            {
+                "role": "user",
+                "content": build_user_content(prompt, image_urls),
+            },
+        )
+        return messages
+
+    def _build_runtime_context(self, thread_id: str) -> dict[str, T.Any]:
+        runtime_context: dict[str, T.Any] = {
+            "thread_id": thread_id,
+            "thinking_enabled": self.thinking_enabled,
+            "is_plan_mode": self.plan_mode,
+            "subagent_enabled": self.subagent_enabled,
+        }
+        if self.subagent_enabled:
+            runtime_context["max_concurrent_subagents"] = self.max_concurrent_subagents
+        if self.model_name:
+            runtime_context["model_name"] = self.model_name
+        return runtime_context
+
+    def _build_payload(
+        self,
+        thread_id: str,
+        prompt: str,
+        image_urls: list[str],
+        system_prompt: str | None,
+    ) -> dict[str, T.Any]:
+        return {
+            "assistant_id": self.assistant_id,
+            "input": {
+                "messages": self._build_messages(prompt, image_urls, system_prompt),
+            },
+            "stream_mode": ["values", "messages-tuple", "custom"],
+            # LangGraph 0.6+ prefers context instead of configurable.
+            "context": self._build_runtime_context(thread_id),
+            "config": {
+                "recursion_limit": self.recursion_limit,
+            },
+        }
+
+    def _update_text_and_maybe_stream(
+        self,
+        *,
+        state: _StreamState,
+        new_full_text: str | None = None,
+        delta_text: str | None = None,
+    ) -> list[AgentResponse]:
+        if new_full_text:
+            state.latest_text = new_full_text
+            if not self.streaming:
+                return []
+
+            if new_full_text.startswith(state.prev_text_for_streaming):
+                delta = new_full_text[len(state.prev_text_for_streaming) :]
+            else:
+                delta = new_full_text
+
+            if not delta:
+                return []
+
+            state.prev_text_for_streaming = new_full_text
+            return [
+                AgentResponse(
+                    type="streaming_delta",
+                    data=AgentResponseData(chain=MessageChain().message(delta)),
+                )
+            ]
+
+        if delta_text:
+            state.latest_text += delta_text
+            if self.streaming:
+                return [
+                    AgentResponse(
+                        type="streaming_delta",
+                        data=AgentResponseData(
+                            chain=MessageChain().message(delta_text)
+                        ),
+                    )
+                ]
+
+        return []
+
+    def _handle_values_event(
+        self,
+        data: T.Any,
+        state: _StreamState,
+    ) -> list[AgentResponse]:
+        responses: list[AgentResponse] = []
+        values_messages = extract_messages_from_values_data(data)
+        if not values_messages:
+            return responses
+
+        new_messages: list[dict[str, T.Any]] = []
+        if not state.baseline_initialized:
+            state.baseline_initialized = True
+            for idx, msg in enumerate(values_messages):
+                if not isinstance(msg, dict):
+                    continue
+                new_messages.append(msg)
+                msg_id = get_message_id(msg)
+                if msg_id:
+                    self._remember_seen_message_id(state, msg_id)
+                    continue
+                state.no_id_message_fingerprints[idx] = self._fingerprint_message(msg)
+        else:
+            new_messages = self._extract_new_messages_from_values(
+                values_messages,
+                state,
+            )
+        latest_text = ""
+        if new_messages:
+            state.run_values_messages.extend(new_messages)
+            if len(state.run_values_messages) > self._MAX_VALUES_HISTORY:
+                state.run_values_messages = state.run_values_messages[
+                    -self._MAX_VALUES_HISTORY :
+                ]
+            latest_text = extract_latest_ai_text(state.run_values_messages)
+            if latest_text:
+                state.has_values_text = True
+            latest_clarification = extract_latest_clarification_text(
+                state.run_values_messages,
+            )
+            if latest_clarification:
+                state.clarification_text = latest_clarification
+
+        responses.extend(
+            self._update_text_and_maybe_stream(
+                state=state,
+                new_full_text=latest_text or None,
+            )
+        )
+        return responses
+
+    def _handle_message_event(
+        self,
+        data: T.Any,
+        state: _StreamState,
+    ) -> AgentResponse | None:
+        delta = extract_ai_delta_from_event_data(data)
+
+        responses: list[AgentResponse] = []
+        if delta and not state.has_values_text:
+            responses.extend(
+                self._update_text_and_maybe_stream(
+                    state=state,
+                    delta_text=delta,
+                )
+            )
+
+        maybe_clarification = extract_clarification_from_event_data(data)
+        if maybe_clarification:
+            state.clarification_text = maybe_clarification
+        return responses[0] if responses else None
+
+    def _build_final_result(self, state: _StreamState) -> _FinalResult:
+        failures_only = False
+
+        if state.clarification_text:
+            final_chain = MessageChain(chain=[Comp.Plain(state.clarification_text)])
+        else:
+            final_chain = MessageChain()
+            latest_ai_message = extract_latest_ai_message(state.run_values_messages)
+            if latest_ai_message:
+                final_chain = build_chain_from_ai_content(
+                    latest_ai_message.get("content"),
+                    image_component_from_url,
+                )
+
+            if not final_chain.chain and state.latest_text:
+                final_chain = MessageChain(chain=[Comp.Plain(state.latest_text)])
+
+            if not final_chain.chain:
+                failure_text = build_task_failure_summary(state.task_failures)
+                if failure_text:
+                    final_chain = MessageChain(chain=[Comp.Plain(failure_text)])
+                    failures_only = True
+
+        if not final_chain.chain:
+            logger.warning("DeerFlow returned no text content in stream events.")
+            final_chain = MessageChain(
+                chain=[Comp.Plain("DeerFlow returned an empty response.")],
+            )
+
+        if state.timed_out:
+            timeout_note = (
+                f"DeerFlow stream timed out after {self.timeout}s. "
+                "Returning partial result."
+            )
+            if final_chain.chain and isinstance(final_chain.chain[-1], Comp.Plain):
+                last_text = final_chain.chain[-1].text
+                final_chain.chain[-1].text = (
+                    f"{last_text}\n\n{timeout_note}" if last_text else timeout_note
+                )
+            else:
+                final_chain.chain.append(Comp.Plain(timeout_note))
+
+        role = "err" if (state.timed_out or failures_only) else "assistant"
+        return self._FinalResult(chain=final_chain, role=role)
+
+    def _emit_non_plain_components_at_end(
+        self,
+        final_chain: MessageChain,
+    ) -> AgentResponse | None:
+        non_plain_components = [
+            component
+            for component in final_chain.chain
+            if not isinstance(component, Comp.Plain)
+        ]
+        if not non_plain_components:
+            return None
+        return AgentResponse(
+            type="streaming_delta",
+            data=AgentResponseData(
+                chain=MessageChain(chain=non_plain_components),
+            ),
+        )
+
+    async def _execute_deerflow_request(self):
+        prompt = self.req.prompt or ""
+        session_id = self.req.session_id or f"{DEERFLOW_SESSION_PREFIX}-{uuid4()}"
+        image_urls = self.req.image_urls or []
+        system_prompt = self.req.system_prompt
+
+        thread_id = await self._ensure_thread_id(session_id)
+        payload = self._build_payload(
+            thread_id=thread_id,
+            prompt=prompt,
+            image_urls=image_urls,
+            system_prompt=system_prompt,
+        )
+        state = self._StreamState()
+
+        try:
+            async for event in self.api_client.stream_run(
+                thread_id=thread_id,
+                payload=payload,
+                timeout=self.timeout,
+            ):
+                event_type = event.get("event")
+                data = event.get("data")
+
+                if event_type == "values":
+                    for response in self._handle_values_event(data, state):
+                        yield response
+                    continue
+
+                if event_type in {"messages-tuple", "messages", "message"}:
+                    response = self._handle_message_event(data, state)
+                    if response:
+                        yield response
+                    continue
+
+                if event_type == "custom":
+                    state.task_failures.extend(
+                        extract_task_failures_from_custom_event(data),
+                    )
+                    continue
+
+                if event_type == "error":
+                    raise Exception(f"DeerFlow stream returned error event: {data}")
+
+                if event_type == "end":
+                    break
+        except (asyncio.TimeoutError, TimeoutError):
+            logger.warning(
+                "DeerFlow stream timed out after %ss for thread_id=%s; returning partial result.",
+                self.timeout,
+                thread_id,
+            )
+            state.timed_out = True
+
+        final_result = self._build_final_result(state)
+
+        if self.streaming:
+            extra_response = self._emit_non_plain_components_at_end(final_result.chain)
+            if extra_response:
+                yield extra_response
+
+        yield await self._finish_with_result(final_result.chain, final_result.role)
+
+    @override
+    def done(self) -> bool:
+        """Check whether the agent has finished or failed."""
+        return self._state in (AgentState.DONE, AgentState.ERROR)
+
+    @override
+    def get_final_llm_resp(self) -> LLMResponse | None:
+        return self.final_llm_resp
@@ -0,0 +1,245 @@
+import codecs
+import json
+from collections.abc import AsyncGenerator
+from typing import Any
+
+from aiohttp import ClientResponse, ClientSession, ClientTimeout
+
+from astrbot.core import logger
+
+SSE_MAX_BUFFER_CHARS = 1_048_576
+
+
+def _normalize_sse_newlines(text: str) -> str:
+    """Normalize CRLF/CR to LF so SSE block splitting works reliably."""
+    return text.replace("\r\n", "\n").replace("\r", "\n")
+
+
+def _parse_sse_data_lines(data_lines: list[str]) -> Any:
+    raw_data = "\n".join(data_lines)
+    try:
+        return json.loads(raw_data)
+    except json.JSONDecodeError:
+        # Some LangGraph-compatible servers emit multiple JSON fragments
+        # in one SSE event using repeated data lines (e.g. tuple payloads).
+        parsed_lines: list[Any] = []
+        can_parse_all = True
+        for line in data_lines:
+            line = line.strip()
+            if not line:
+                continue
+            try:
+                parsed_lines.append(json.loads(line))
+            except json.JSONDecodeError:
+                can_parse_all = False
+                break
+        if can_parse_all and parsed_lines:
+            return parsed_lines[0] if len(parsed_lines) == 1 else parsed_lines
+        return raw_data
+
+
+def _parse_sse_block(block: str) -> dict[str, Any] | None:
+    if not block.strip():
+        return None
+
+    event_name = "message"
+    data_lines: list[str] = []
+    for line in block.splitlines():
+        if line.startswith("event:"):
+            event_name = line[6:].strip()
+        elif line.startswith("data:"):
+            data_lines.append(line[5:].lstrip())
+
+    if not data_lines:
+        return None
+    return {"event": event_name, "data": _parse_sse_data_lines(data_lines)}
+
+
+async def _stream_sse(resp: ClientResponse) -> AsyncGenerator[dict[str, Any], None]:
+    """Parse SSE response blocks into event/data dictionaries."""
+    # Use a forgiving decoder at network boundaries so malformed bytes do not abort stream parsing.
+    decoder = codecs.getincrementaldecoder("utf-8")("replace")
+    buffer = ""
+
+    async for chunk in resp.content.iter_chunked(8192):
+        buffer += _normalize_sse_newlines(decoder.decode(chunk))
+
+        while "\n\n" in buffer:
+            block, buffer = buffer.split("\n\n", 1)
+            parsed = _parse_sse_block(block)
+            if parsed is not None:
+                yield parsed
+
+        if len(buffer) > SSE_MAX_BUFFER_CHARS:
+            logger.warning(
+                "DeerFlow SSE parser buffer exceeded %d chars without delimiter; "
+                "flushing oversized block to prevent unbounded memory growth.",
+                SSE_MAX_BUFFER_CHARS,
+            )
+            parsed = _parse_sse_block(buffer)
+            if parsed is not None:
+                yield parsed
+            buffer = ""
+
+    # flush any remaining buffered text
+    buffer += _normalize_sse_newlines(decoder.decode(b"", final=True))
+    while "\n\n" in buffer:
+        block, buffer = buffer.split("\n\n", 1)
+        parsed = _parse_sse_block(block)
+        if parsed is not None:
+            yield parsed
+
+    if buffer.strip():
+        parsed = _parse_sse_block(buffer)
+        if parsed is not None:
+            yield parsed
+
+
+class DeerFlowAPIClient:
+    """HTTP client for DeerFlow LangGraph API.
+
+    Lifecycle is explicitly managed by callers (runner/stage). `__del__` is only a
+    fallback diagnostic and must not be relied on for cleanup.
+    """
+
+    def __init__(
+        self,
+        api_base: str = "http://127.0.0.1:2026",
+        api_key: str = "",
+        auth_header: str = "",
+        proxy: str | None = None,
+    ) -> None:
+        self.api_base = api_base.rstrip("/")
+        self._session: ClientSession | None = None
+        self._closed = False
+        self.proxy = proxy.strip() if isinstance(proxy, str) else None
+        if self.proxy == "":
+            self.proxy = None
+        self.headers: dict[str, str] = {}
+        if auth_header:
+            self.headers["Authorization"] = auth_header
+        elif api_key:
+            self.headers["Authorization"] = f"Bearer {api_key}"
+
+    def _get_session(self) -> ClientSession:
+        if self._closed:
+            raise RuntimeError("DeerFlowAPIClient is already closed.")
+        if self._session is None or self._session.closed:
+            self._session = ClientSession(trust_env=True)
+        return self._session
+
+    async def __aenter__(self) -> "DeerFlowAPIClient":
+        return self
+
+    async def __aexit__(
+        self,
+        exc_type: type[BaseException] | None,
+        exc: BaseException | None,
+        tb: object | None,
+    ) -> None:
+        await self.close()
+
+    async def create_thread(self, timeout: float = 20) -> dict[str, Any]:
+        session = self._get_session()
+        url = f"{self.api_base}/api/langgraph/threads"
+        payload = {"metadata": {}}
+        async with session.post(
+            url,
+            json=payload,
+            headers=self.headers,
+            timeout=timeout,
+            proxy=self.proxy,
+        ) as resp:
+            if resp.status not in (200, 201):
+                text = await resp.text()
+                raise Exception(
+                    f"DeerFlow create thread failed: {resp.status}. {text}",
+                )
+            return await resp.json()
+
+    async def stream_run(
+        self,
+        thread_id: str,
+        payload: dict[str, Any],
+        timeout: float = 120,
+    ) -> AsyncGenerator[dict[str, Any], None]:
+        session = self._get_session()
+        url = f"{self.api_base}/api/langgraph/threads/{thread_id}/runs/stream"
+        input_payload = payload.get("input")
+        message_count = 0
+        if isinstance(input_payload, dict) and isinstance(
+            input_payload.get("messages"), list
+        ):
+            message_count = len(input_payload["messages"])
+        # Log only a minimal summary to avoid exposing sensitive user content.
+        logger.debug(
+            "deerflow stream_run payload summary: thread_id=%s, keys=%s, message_count=%d, stream_mode=%s",
+            thread_id,
+            list(payload.keys()),
+            message_count,
+            payload.get("stream_mode"),
+        )
+        # For long-running SSE streams, avoid aiohttp total timeout.
+        # Use socket read timeout so active heartbeats/chunks can keep the stream alive.
+        stream_timeout = ClientTimeout(
+            total=None,
+            connect=min(timeout, 30),
+            sock_connect=min(timeout, 30),
+            sock_read=timeout,
+        )
+        async with session.post(
+            url,
+            json=payload,
+            headers={
+                **self.headers,
+                "Accept": "text/event-stream",
+                "Content-Type": "application/json",
+            },
+            timeout=stream_timeout,
+            proxy=self.proxy,
+        ) as resp:
+            if resp.status != 200:
+                text = await resp.text()
+                raise Exception(
+                    f"DeerFlow runs/stream request failed: {resp.status}. {text}",
+                )
+            async for event in _stream_sse(resp):
+                yield event
+
+    async def close(self) -> None:
+        session = self._session
+        if session is None:
+            self._closed = True
+            return
+
+        if session.closed:
+            self._session = None
+            self._closed = True
+            return
+
+        try:
+            await session.close()
+        except Exception as e:
+            logger.warning(
+                "Failed to close DeerFlowAPIClient session cleanly: %s",
+                e,
+                exc_info=True,
+            )
+        finally:
+            # Cleanup is best-effort and should not make teardown paths fail loudly.
+            self._session = None
+            self._closed = True
+
+    def __del__(self) -> None:
+        session = getattr(self, "_session", None)
+        closed = bool(getattr(self, "_closed", False))
+        if closed or session is None or session.closed:
+            return
+        logger.warning(
+            "DeerFlowAPIClient garbage collected with unclosed session; "
+            "explicit close() should be called by runner lifecycle (or `async with`)."
+        )
+
+    @property
+    def is_closed(self) -> bool:
+        return self._closed
@@ -0,0 +1,190 @@
+import base64
+from collections.abc import Callable
+from typing import Any
+
+import astrbot.core.message.components as Comp
+from astrbot import logger
+from astrbot.core.message.message_event_result import MessageChain
+
+from .deerflow_stream_utils import extract_text
+
+
+def is_likely_base64_image(value: str) -> bool:
+    if " " in value:
+        return False
+
+    compact = value.replace("\n", "").replace("\r", "")
+    if not compact or len(compact) < 32 or len(compact) % 4 != 0:
+        return False
+
+    base64_chars = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/="
+    if any(ch not in base64_chars for ch in compact):
+        return False
+    try:
+        base64.b64decode(compact, validate=True)
+    except Exception:
+        return False
+    return True
+
+
+def build_user_content(prompt: str, image_urls: list[str]) -> Any:
+    if not image_urls:
+        return prompt
+
+    content: list[dict[str, Any]] = []
+    skipped_invalid_images = 0
+    any_valid_image = False
+    if prompt:
+        content.append({"type": "text", "text": prompt})
+
+    for image_url in image_urls:
+        url = image_url
+        if not isinstance(url, str):
+            skipped_invalid_images += 1
+            logger.debug(
+                "Skipped DeerFlow image input because value is not a string: %r",
+                type(image_url).__name__,
+            )
+            continue
+        url = url.strip()
+        if not url:
+            skipped_invalid_images += 1
+            logger.debug("Skipped DeerFlow image input because value is empty.")
+            continue
+        if url.startswith(("http://", "https://", "data:")):
+            content.append({"type": "image_url", "image_url": {"url": url}})
+            any_valid_image = True
+            continue
+        if not is_likely_base64_image(url):
+            skipped_invalid_images += 1
+            logger.debug(
+                "Skipped DeerFlow image input because it is neither URL/data URI nor valid base64."
+            )
+            continue
+        compact_base64 = url.replace("\n", "").replace("\r", "")
+        content.append(
+            {
+                "type": "image_url",
+                "image_url": {"url": f"data:image/png;base64,{compact_base64}"},
+            },
+        )
+        any_valid_image = True
+
+    if skipped_invalid_images:
+        note_text = (
+            "Note: some images could not be processed and were ignored."
+            if any_valid_image
+            else "Note: none of the provided images could be processed."
+        )
+        content.insert(0, {"type": "text", "text": note_text})
+        if not any_valid_image:
+            logger.warning(
+                "All %d provided DeerFlow image inputs were rejected as invalid or unsupported.",
+                skipped_invalid_images,
+            )
+        else:
+            logger.info(
+                "%d DeerFlow image input(s) were rejected as invalid or unsupported.",
+                skipped_invalid_images,
+            )
+        logger.debug(
+            "Skipped %d DeerFlow image inputs that were neither URL/data URI nor valid base64.",
+            skipped_invalid_images,
+        )
+    return content
+
+
+def image_component_from_url(url: Any) -> Comp.Image | None:
+    if not isinstance(url, str):
+        return None
+
+    normalized = url.strip()
+    if not normalized:
+        return None
+
+    if normalized.startswith(("http://", "https://")):
+        try:
+            return Comp.Image.fromURL(normalized)
+        except Exception:
+            return None
+
+    if not normalized.startswith("data:"):
+        return None
+
+    header, sep, payload = normalized.partition(",")
+    if not sep:
+        return None
+    if ";base64" not in header.lower():
+        return None
+
+    compact_payload = payload.replace("\n", "").replace("\r", "").strip()
+    if not compact_payload:
+        return None
+    try:
+        base64.b64decode(compact_payload, validate=True)
+    except Exception:
+        return None
+    return Comp.Image.fromBase64(compact_payload)
+
+
+def append_components_from_content(
+    content: Any,
+    components: list[Comp.BaseMessageComponent],
+    image_resolver: Callable[[Any], Comp.Image | None],
+) -> None:
+    if isinstance(content, str):
+        if content:
+            components.append(Comp.Plain(content))
+        return
+
+    if isinstance(content, list):
+        for item in content:
+            append_components_from_content(item, components, image_resolver)
+        return
+
+    if not isinstance(content, dict):
+        return
+
+    item_type = str(content.get("type", "")).lower()
+    if item_type == "text" and isinstance(content.get("text"), str):
+        text = content["text"]
+        if text:
+            components.append(Comp.Plain(text))
+        return
+
+    if item_type == "image_url":
+        image_payload = content.get("image_url")
+        image_url: Any = image_payload
+        if isinstance(image_payload, dict):
+            image_url = image_payload.get("url")
+        image_comp = image_resolver(image_url)
+        if image_comp is not None:
+            components.append(image_comp)
+        return
+
+    if "content" in content:
+        append_components_from_content(
+            content.get("content"), components, image_resolver
+        )
+        return
+
+    kwargs = content.get("kwargs")
+    if isinstance(kwargs, dict) and "content" in kwargs:
+        append_components_from_content(
+            kwargs.get("content"), components, image_resolver
+        )
+
+
+def build_chain_from_ai_content(
+    content: Any,
+    image_resolver: Callable[[Any], Comp.Image | None],
+) -> MessageChain:
+    components: list[Comp.BaseMessageComponent] = []
+    append_components_from_content(content, components, image_resolver)
+    if components:
+        return MessageChain(chain=components)
+
+    fallback_text = extract_text(content)
+    if fallback_text:
+        return MessageChain(chain=[Comp.Plain(fallback_text)])
+    return MessageChain()
@@ -0,0 +1,201 @@
+import typing as T
+from collections.abc import Iterable
+
+
+def extract_text(content: T.Any) -> str:
+    if isinstance(content, str):
+        return content
+    if isinstance(content, dict):
+        if isinstance(content.get("text"), str):
+            return content["text"]
+        if "content" in content:
+            return extract_text(content.get("content"))
+        if "kwargs" in content and isinstance(content["kwargs"], dict):
+            return extract_text(content["kwargs"].get("content"))
+    if isinstance(content, list):
+        parts: list[str] = []
+        for item in content:
+            if isinstance(item, str):
+                parts.append(item)
+            elif isinstance(item, dict):
+                item_type = item.get("type")
+                if item_type == "text" and isinstance(item.get("text"), str):
+                    parts.append(item["text"])
+                elif "content" in item:
+                    parts.append(extract_text(item["content"]))
+        return "\n".join([p for p in parts if p]).strip()
+    return str(content) if content is not None else ""
+
+
+def extract_messages_from_values_data(data: T.Any) -> list[T.Any]:
+    """Extract messages list from possible values event payload shapes."""
+    candidates: list[T.Any] = []
+    if isinstance(data, dict):
+        candidates.append(data)
+        if isinstance(data.get("values"), dict):
+            candidates.append(data["values"])
+    elif isinstance(data, list):
+        candidates.extend([x for x in data if isinstance(x, dict)])
+
+    for item in candidates:
+        messages = item.get("messages")
+        if isinstance(messages, list):
+            return messages
+    return []
+
+
+def is_ai_message(message: dict[str, T.Any]) -> bool:
+    role = str(message.get("role", "")).lower()
+    if role in {"assistant", "ai"}:
+        return True
+
+    msg_type = str(message.get("type", "")).lower()
+    if msg_type in {"ai", "assistant", "aimessage", "aimessagechunk"}:
+        return True
+    if "ai" in msg_type and all(
+        token not in msg_type for token in ("human", "tool", "system")
+    ):
+        return True
+    return False
+
+
+def extract_latest_ai_text(messages: Iterable[T.Any]) -> str:
+    # Scan backwards to get the latest assistant/ai message text.
+    if isinstance(messages, (list, tuple)):
+        iterable = reversed(messages)
+    else:
+        # Fallback for generic iterables (e.g. generators).
+        iterable = reversed(list(messages))
+
+    for msg in iterable:
+        if not isinstance(msg, dict):
+            continue
+        if is_ai_message(msg):
+            text = extract_text(msg.get("content"))
+            if text:
+                return text
+    return ""
+
+
+def extract_latest_ai_message(messages: Iterable[T.Any]) -> dict[str, T.Any] | None:
+    if isinstance(messages, (list, tuple)):
+        iterable = reversed(messages)
+    else:
+        iterable = reversed(list(messages))
+
+    for msg in iterable:
+        if not isinstance(msg, dict):
+            continue
+        if is_ai_message(msg):
+            return msg
+    return None
+
+
+def is_clarification_tool_message(message: dict[str, T.Any]) -> bool:
+    msg_type = str(message.get("type", "")).lower()
+    tool_name = str(message.get("name", "")).lower()
+    return msg_type == "tool" and tool_name == "ask_clarification"
+
+
+def extract_latest_clarification_text(messages: Iterable[T.Any]) -> str:
+    if isinstance(messages, (list, tuple)):
+        iterable = reversed(messages)
+    else:
+        iterable = reversed(list(messages))
+
+    for msg in iterable:
+        if not isinstance(msg, dict):
+            continue
+        if is_clarification_tool_message(msg):
+            text = extract_text(msg.get("content"))
+            if text:
+                return text
+    return ""
+
+
+def get_message_id(message: T.Any) -> str:
+    if not isinstance(message, dict):
+        return ""
+    msg_id = message.get("id")
+    return msg_id if isinstance(msg_id, str) else ""
+
+
+def extract_event_message_obj(data: T.Any) -> dict[str, T.Any] | None:
+    msg_obj = data
+    if isinstance(data, (list, tuple)) and data:
+        msg_obj = data[0]
+    if isinstance(msg_obj, dict) and isinstance(msg_obj.get("data"), dict):
+        # Some servers wrap message body in {"data": {...}}
+        msg_obj = msg_obj["data"]
+    return msg_obj if isinstance(msg_obj, dict) else None
+
+
+def extract_ai_delta_from_event_data(data: T.Any) -> str:
+    # LangGraph messages-tuple events usually carry either:
+    # - {"type": "ai", "content": "..."}
+    # - [message_obj, metadata]
+    msg_obj = extract_event_message_obj(data)
+    if not msg_obj:
+        return ""
+    if is_ai_message(msg_obj):
+        return extract_text(msg_obj.get("content"))
+    return ""
+
+
+def extract_clarification_from_event_data(data: T.Any) -> str:
+    msg_obj = extract_event_message_obj(data)
+    if not msg_obj:
+        return ""
+    if is_clarification_tool_message(msg_obj):
+        return extract_text(msg_obj.get("content"))
+    return ""
+
+
+def _iter_custom_event_items(data: T.Any) -> list[dict[str, T.Any]]:
+    items: list[dict[str, T.Any]] = []
+    if isinstance(data, dict):
+        return [data]
+    if isinstance(data, list):
+        for item in data:
+            if isinstance(item, dict):
+                items.append(item)
+            elif isinstance(item, (list, tuple)):
+                for nested in item:
+                    if isinstance(nested, dict):
+                        items.append(nested)
+    return items
+
+
+def extract_task_failures_from_custom_event(data: T.Any) -> list[str]:
+    failures: list[str] = []
+    for item in _iter_custom_event_items(data):
+        event_type = str(item.get("type", "")).lower()
+        if event_type not in {"task_failed", "task_timed_out"}:
+            continue
+
+        task_id = str(item.get("task_id", "")).strip()
+        error_text = extract_text(item.get("error")).strip()
+        if task_id and error_text:
+            failures.append(f"{task_id}: {error_text}")
+        elif error_text:
+            failures.append(error_text)
+        elif task_id:
+            failures.append(f"{task_id}: unknown error")
+        else:
+            failures.append("unknown task failure")
+    return failures
+
+
+def build_task_failure_summary(failures: list[str]) -> str:
+    if not failures:
+        return ""
+    deduped: list[str] = []
+    seen: set[str] = set()
+    for failure in failures:
+        if failure not in seen:
+            seen.add(failure)
+            deduped.append(failure)
+    if len(deduped) == 1:
+        return f"DeerFlow subtask failed: {deduped[0]}"
+    joined = "\n".join([f"- {item}" for item in deduped[:5]])
+    return f"DeerFlow subtasks failed:\n{joined}"
@@ -0,0 +1,336 @@
+import base64
+import os
+import sys
+import typing as T
+
+import astrbot.core.message.components as Comp
+from astrbot.core import logger, sp
+from astrbot.core.message.message_event_result import MessageChain
+from astrbot.core.provider.entities import (
+    LLMResponse,
+    ProviderRequest,
+)
+from astrbot.core.utils.astrbot_path import get_astrbot_temp_path
+from astrbot.core.utils.io import download_file
+
+from ...hooks import BaseAgentRunHooks
+from ...response import AgentResponseData
+from ...run_context import ContextWrapper, TContext
+from ..base import AgentResponse, AgentState, BaseAgentRunner
+from .dify_api_client import DifyAPIClient
+
+if sys.version_info >= (3, 12):
+    from typing import override
+else:
+    from typing_extensions import override
+
+
+class DifyAgentRunner(BaseAgentRunner[TContext]):
+    """Dify Agent Runner"""
+
+    @override
+    async def reset(
+        self,
+        request: ProviderRequest,
+        run_context: ContextWrapper[TContext],
+        agent_hooks: BaseAgentRunHooks[TContext],
+        provider_config: dict,
+        **kwargs: T.Any,
+    ) -> None:
+        self.req = request
+        self.streaming = kwargs.get("streaming", False)
+        self.final_llm_resp = None
+        self._state = AgentState.IDLE
+        self.agent_hooks = agent_hooks
+        self.run_context = run_context
+
+        self.api_key = provider_config.get("dify_api_key", "")
+        self.api_base = provider_config.get("dify_api_base", "https://api.dify.ai/v1")
+        self.api_type = provider_config.get("dify_api_type", "chat")
+        self.workflow_output_key = provider_config.get(
+            "dify_workflow_output_key",
+            "astrbot_wf_output",
+        )
+        self.dify_query_input_key = provider_config.get(
+            "dify_query_input_key",
+            "astrbot_text_query",
+        )
+        self.variables: dict = provider_config.get("variables", {}) or {}
+        self.timeout = provider_config.get("timeout", 60)
+        if isinstance(self.timeout, str):
+            self.timeout = int(self.timeout)
+
+        self.api_client = DifyAPIClient(self.api_key, self.api_base)
+
+    @override
+    async def step(self):
+        """
+        执行 Dify Agent 的一个步骤
+        """
+        if not self.req:
+            raise ValueError("Request is not set. Please call reset() first.")
+
+        if self._state == AgentState.IDLE:
+            try:
+                await self.agent_hooks.on_agent_begin(self.run_context)
+            except Exception as e:
+                logger.error(f"Error in on_agent_begin hook: {e}", exc_info=True)
+
+        # 开始处理，转换到运行状态
+        self._transition_state(AgentState.RUNNING)
+
+        try:
+            # 执行 Dify 请求并处理结果
+            async for response in self._execute_dify_request():
+                yield response
+        except Exception as e:
+            logger.error(f"Dify 请求失败：{str(e)}")
+            self._transition_state(AgentState.ERROR)
+            self.final_llm_resp = LLMResponse(
+                role="err", completion_text=f"Dify 请求失败：{str(e)}"
+            )
+            yield AgentResponse(
+                type="err",
+                data=AgentResponseData(
+                    chain=MessageChain().message(f"Dify 请求失败：{str(e)}")
+                ),
+            )
+        finally:
+            await self.api_client.close()
+
+    @override
+    async def step_until_done(
+        self, max_step: int = 30
+    ) -> T.AsyncGenerator[AgentResponse, None]:
+        while not self.done():
+            async for resp in self.step():
+                yield resp
+
+    async def _execute_dify_request(self):
+        """执行 Dify 请求的核心逻辑"""
+        prompt = self.req.prompt or ""
+        session_id = self.req.session_id or "unknown"
+        image_urls = self.req.image_urls or []
+        system_prompt = self.req.system_prompt
+
+        conversation_id = await sp.get_async(
+            scope="umo",
+            scope_id=session_id,
+            key="dify_conversation_id",
+            default="",
+        )
+        result = ""
+
+        # 处理图片上传
+        files_payload = []
+        for image_url in image_urls:
+            # image_url is a base64 string
+            try:
+                image_data = base64.b64decode(image_url)
+                file_response = await self.api_client.file_upload(
+                    file_data=image_data,
+                    user=session_id,
+                    mime_type="image/png",
+                    file_name="image.png",
+                )
+                logger.debug(f"Dify 上传图片响应：{file_response}")
+                if "id" not in file_response:
+                    logger.warning(
+                        f"上传图片后得到未知的 Dify 响应：{file_response}，图片将忽略。"
+                    )
+                    continue
+                files_payload.append(
+                    {
+                        "type": "image",
+                        "transfer_method": "local_file",
+                        "upload_file_id": file_response["id"],
+                    }
+                )
+            except Exception as e:
+                logger.warning(f"上传图片失败：{e}")
+                continue
+
+        # 获得会话变量
+        payload_vars = self.variables.copy()
+        # 动态变量
+        session_var = await sp.get_async(
+            scope="umo",
+            scope_id=session_id,
+            key="session_variables",
+            default={},
+        )
+        payload_vars.update(session_var)
+        payload_vars["system_prompt"] = system_prompt
+
+        # 处理不同的 API 类型
+        match self.api_type:
+            case "chat" | "agent" | "chatflow":
+                if not prompt:
+                    prompt = "请描述这张图片。"
+
+                async for chunk in self.api_client.chat_messages(
+                    inputs={
+                        **payload_vars,
+                    },
+                    query=prompt,
+                    user=session_id,
+                    conversation_id=conversation_id,
+                    files=files_payload,
+                    timeout=self.timeout,
+                ):
+                    logger.debug(f"dify resp chunk: {chunk}")
+                    if chunk["event"] == "message" or chunk["event"] == "agent_message":
+                        result += chunk["answer"]
+                        if not conversation_id:
+                            await sp.put_async(
+                                scope="umo",
+                                scope_id=session_id,
+                                key="dify_conversation_id",
+                                value=chunk["conversation_id"],
+                            )
+                            conversation_id = chunk["conversation_id"]
+
+                        # 如果是流式响应，发送增量数据
+                        if self.streaming and chunk["answer"]:
+                            yield AgentResponse(
+                                type="streaming_delta",
+                                data=AgentResponseData(
+                                    chain=MessageChain().message(chunk["answer"])
+                                ),
+                            )
+                    elif chunk["event"] == "message_end":
+                        logger.debug("Dify message end")
+                        break
+                    elif chunk["event"] == "error":
+                        logger.error(f"Dify 出现错误：{chunk}")
+                        raise Exception(
+                            f"Dify 出现错误 status: {chunk['status']} message: {chunk['message']}"
+                        )
+
+            case "workflow":
+                async for chunk in self.api_client.workflow_run(
+                    inputs={
+                        self.dify_query_input_key: prompt,
+                        "astrbot_session_id": session_id,
+                        **payload_vars,
+                    },
+                    user=session_id,
+                    files=files_payload,
+                    timeout=self.timeout,
+                ):
+                    logger.debug(f"dify workflow resp chunk: {chunk}")
+                    match chunk["event"]:
+                        case "workflow_started":
+                            logger.info(
+                                f"Dify 工作流(ID: {chunk['workflow_run_id']})开始运行。"
+                            )
+                        case "node_finished":
+                            logger.debug(
+                                f"Dify 工作流节点(ID: {chunk['data']['node_id']} Title: {chunk['data'].get('title', '')})运行结束。"
+                            )
+                        case "text_chunk":
+                            if self.streaming and chunk["data"]["text"]:
+                                yield AgentResponse(
+                                    type="streaming_delta",
+                                    data=AgentResponseData(
+                                        chain=MessageChain().message(
+                                            chunk["data"]["text"]
+                                        )
+                                    ),
+                                )
+                        case "workflow_finished":
+                            logger.info(
+                                f"Dify 工作流(ID: {chunk['workflow_run_id']})运行结束"
+                            )
+                            logger.debug(f"Dify 工作流结果：{chunk}")
+                            if chunk["data"]["error"]:
+                                logger.error(
+                                    f"Dify 工作流出现错误：{chunk['data']['error']}"
+                                )
+                                raise Exception(
+                                    f"Dify 工作流出现错误：{chunk['data']['error']}"
+                                )
+                            if self.workflow_output_key not in chunk["data"]["outputs"]:
+                                raise Exception(
+                                    f"Dify 工作流的输出不包含指定的键名：{self.workflow_output_key}"
+                                )
+                            result = chunk
+            case _:
+                raise Exception(f"未知的 Dify API 类型：{self.api_type}")
+
+        if not result:
+            logger.warning("Dify 请求结果为空，请查看 Debug 日志。")
+
+        # 解析结果
+        chain = await self.parse_dify_result(result)
+
+        # 创建最终响应
+        self.final_llm_resp = LLMResponse(role="assistant", result_chain=chain)
+        self._transition_state(AgentState.DONE)
+
+        try:
+            await self.agent_hooks.on_agent_done(self.run_context, self.final_llm_resp)
+        except Exception as e:
+            logger.error(f"Error in on_agent_done hook: {e}", exc_info=True)
+
+        # 返回最终结果
+        yield AgentResponse(
+            type="llm_result",
+            data=AgentResponseData(chain=chain),
+        )
+
+    async def parse_dify_result(self, chunk: dict | str) -> MessageChain:
+        """解析 Dify 的响应结果"""
+        if isinstance(chunk, str):
+            # Chat
+            return MessageChain(chain=[Comp.Plain(chunk)])
+
+        async def parse_file(item: dict):
+            match item["type"]:
+                case "image":
+                    return Comp.Image(file=item["url"], url=item["url"])
+                case "audio":
+                    # 仅支持 wav
+                    temp_dir = get_astrbot_temp_path()
+                    path = os.path.join(temp_dir, f"dify_{item['filename']}.wav")
+                    await download_file(item["url"], path)
+                    return Comp.Image(file=item["url"], url=item["url"])
+                case "video":
+                    return Comp.Video(file=item["url"])
+                case _:
+                    return Comp.File(name=item["filename"], file=item["url"])
+
+        output = chunk["data"]["outputs"][self.workflow_output_key]
+        chains = []
+        if isinstance(output, str):
+            # 纯文本输出
+            chains.append(Comp.Plain(output))
+        elif isinstance(output, list):
+            # 主要适配 Dify 的 HTTP 请求结点的多模态输出
+            for item in output:
+                # handle Array[File]
+                if (
+                    not isinstance(item, dict)
+                    or item.get("dify_model_identity", "") != "__dify__file__"
+                ):
+                    chains.append(Comp.Plain(str(output)))
+                    break
+        else:
+            chains.append(Comp.Plain(str(output)))
+
+        # scan file
+        files = chunk["data"].get("files", [])
+        for item in files:
+            comp = await parse_file(item)
+            chains.append(comp)
+
+        return MessageChain(chain=chains)
+
+    @override
+    def done(self) -> bool:
+        """检查 Agent 是否已完成工作"""
+        return self._state in (AgentState.DONE, AgentState.ERROR)
+
+    @override
+    def get_final_llm_resp(self) -> LLMResponse | None:
+        return self.final_llm_resp
@@ -3,7 +3,7 @@ import json
 from collections.abc import AsyncGenerator
 from typing import Any

-from aiohttp import ClientResponse, ClientSession
+from aiohttp import ClientResponse, ClientSession, FormData

 from astrbot.core import logger

@@ -31,7 +31,7 @@ async def _stream_sse(resp: ClientResponse) -> AsyncGenerator[dict, None]:


 class DifyAPIClient:
-    def __init__(self, api_key: str, api_base: str = "https://api.dify.ai/v1"):
+    def __init__(self, api_key: str, api_base: str = "https://api.dify.ai/v1") -> None:
        self.api_key = api_key
        self.api_base = api_base
        self.session = ClientSession(trust_env=True)
@@ -101,23 +101,61 @@ class DifyAPIClient:

    async def file_upload(
        self,
-        file_path: str,
        user: str,
+        file_path: str | None = None,
+        file_data: bytes | None = None,
+        file_name: str | None = None,
+        mime_type: str | None = None,
    ) -> dict[str, Any]:
-        url = f"{self.api_base}/files/upload"
-        with open(file_path, "rb") as f:
-            payload = {
-                "user": user,
-                "file": f,
-            }
-            async with self.session.post(
-                url,
-                data=payload,
-                headers=self.headers,
-            ) as resp:
-                return await resp.json()  # {"id": "xxx", ...}
+        """Upload a file to Dify. Must provide either file_path or file_data.

-    async def close(self):
+        Args:
+            user: The user ID.
+            file_path: The path to the file to upload.
+            file_data: The file data in bytes.
+            file_name: Optional file name when using file_data.
+        Returns:
+            A dictionary containing the uploaded file information.
+        """
+        url = f"{self.api_base}/files/upload"
+
+        form = FormData()
+        form.add_field("user", user)
+
+        if file_data is not None:
+            # 使用 bytes 数据
+            form.add_field(
+                "file",
+                file_data,
+                filename=file_name or "uploaded_file",
+                content_type=mime_type or "application/octet-stream",
+            )
+        elif file_path is not None:
+            # 使用文件路径
+            import os
+
+            with open(file_path, "rb") as f:
+                file_content = f.read()
+                form.add_field(
+                    "file",
+                    file_content,
+                    filename=os.path.basename(file_path),
+                    content_type=mime_type or "application/octet-stream",
+                )
+        else:
+            raise ValueError("file_path 和 file_data 不能同时为 None")
+
+        async with self.session.post(
+            url,
+            data=form,
+            headers=self.headers,  # 不包含 Content-Type，让 aiohttp 自动设置
+        ) as resp:
+            if resp.status != 200 and resp.status != 201:
+                text = await resp.text()
+                raise Exception(f"Dify 文件上传失败：{resp.status}. {text}")
+            return await resp.json()  # {"id": "xxx", ...}
+
+    async def close(self) -> None:
        await self.session.close()

    async def get_chat_convs(self, user: str, limit: int = 20):
@@ -1,6 +1,10 @@
+import asyncio
+import copy
 import sys
+import time
 import traceback
 import typing as T
+from dataclasses import dataclass, field

 from mcp.types import (
    BlobResourceContents,
@@ -12,9 +16,16 @@ from mcp.types import (
 )

 from astrbot import logger
+from astrbot.core.agent.message import ImageURLPart, TextPart, ThinkPart
+from astrbot.core.agent.tool import ToolSet
+from astrbot.core.agent.tool_image_cache import tool_image_cache
+from astrbot.core.message.components import Json
 from astrbot.core.message.message_event_result import (
    MessageChain,
 )
+from astrbot.core.persona_error_reply import (
+    extract_persona_custom_error_message_from_event,
+)
 from astrbot.core.provider.entities import (
    LLMResponse,
    ProviderRequest,
@@ -22,9 +33,13 @@ from astrbot.core.provider.entities import (
 )
 from astrbot.core.provider.provider import Provider

+from ..context.compressor import ContextCompressor
+from ..context.config import ContextConfig
+from ..context.manager import ContextManager
+from ..context.token_counter import TokenCounter
 from ..hooks import BaseAgentRunHooks
 from ..message import AssistantMessageSegment, Message, ToolCallMessageSegment
-from ..response import AgentResponseData
+from ..response import AgentResponseData, AgentStats
 from ..run_context import ContextWrapper, TContext
 from ..tool_executor import BaseFunctionToolExecutor
 from .base import AgentResponse, AgentState, BaseAgentRunner
@@ -35,7 +50,42 @@ else:
    from typing_extensions import override


+@dataclass(slots=True)
+class _HandleFunctionToolsResult:
+    kind: T.Literal["message_chain", "tool_call_result_blocks", "cached_image"]
+    message_chain: MessageChain | None = None
+    tool_call_result_blocks: list[ToolCallMessageSegment] | None = None
+    cached_image: T.Any = None
+
+    @classmethod
+    def from_message_chain(cls, chain: MessageChain) -> "_HandleFunctionToolsResult":
+        return cls(kind="message_chain", message_chain=chain)
+
+    @classmethod
+    def from_tool_call_result_blocks(
+        cls, blocks: list[ToolCallMessageSegment]
+    ) -> "_HandleFunctionToolsResult":
+        return cls(kind="tool_call_result_blocks", tool_call_result_blocks=blocks)
+
+    @classmethod
+    def from_cached_image(cls, image: T.Any) -> "_HandleFunctionToolsResult":
+        return cls(kind="cached_image", cached_image=image)
+
+
+@dataclass(slots=True)
+class FollowUpTicket:
+    seq: int
+    text: str
+    consumed: bool = False
+    resolved: asyncio.Event = field(default_factory=asyncio.Event)
+
+
 class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
+    def _get_persona_custom_error_message(self) -> str | None:
+        """Read persona-level custom error message from event extras when available."""
+        event = getattr(self.run_context.context, "event", None)
+        return extract_persona_custom_error_message_from_event(event)
+
    @override
    async def reset(
        self,
@@ -44,21 +94,98 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
        run_context: ContextWrapper[TContext],
        tool_executor: BaseFunctionToolExecutor[TContext],
        agent_hooks: BaseAgentRunHooks[TContext],
+        streaming: bool = False,
+        # enforce max turns, will discard older turns when exceeded BEFORE compression
+        # -1 means no limit
+        enforce_max_turns: int = -1,
+        # llm compressor
+        llm_compress_instruction: str | None = None,
+        llm_compress_keep_recent: int = 0,
+        llm_compress_provider: Provider | None = None,
+        # truncate by turns compressor
+        truncate_turns: int = 1,
+        # customize
+        custom_token_counter: TokenCounter | None = None,
+        custom_compressor: ContextCompressor | None = None,
+        tool_schema_mode: str | None = "full",
+        fallback_providers: list[Provider] | None = None,
        **kwargs: T.Any,
    ) -> None:
        self.req = request
-        self.streaming = kwargs.get("streaming", False)
+        self.streaming = streaming
+        self.enforce_max_turns = enforce_max_turns
+        self.llm_compress_instruction = llm_compress_instruction
+        self.llm_compress_keep_recent = llm_compress_keep_recent
+        self.llm_compress_provider = llm_compress_provider
+        self.truncate_turns = truncate_turns
+        self.custom_token_counter = custom_token_counter
+        self.custom_compressor = custom_compressor
+        # we will do compress when:
+        # 1. before requesting LLM
+        # TODO: 2. after LLM output a tool call
+        self.context_config = ContextConfig(
+            # <=0 will never do compress
+            max_context_tokens=provider.provider_config.get("max_context_tokens", 0),
+            # enforce max turns before compression
+            enforce_max_turns=self.enforce_max_turns,
+            truncate_turns=self.truncate_turns,
+            llm_compress_instruction=self.llm_compress_instruction,
+            llm_compress_keep_recent=self.llm_compress_keep_recent,
+            llm_compress_provider=self.llm_compress_provider,
+            custom_token_counter=self.custom_token_counter,
+            custom_compressor=self.custom_compressor,
+        )
+        self.context_manager = ContextManager(self.context_config)
+
        self.provider = provider
+        self.fallback_providers: list[Provider] = []
+        seen_provider_ids: set[str] = {str(provider.provider_config.get("id", ""))}
+        for fallback_provider in fallback_providers or []:
+            fallback_id = str(fallback_provider.provider_config.get("id", ""))
+            if fallback_provider is provider:
+                continue
+            if fallback_id and fallback_id in seen_provider_ids:
+                continue
+            self.fallback_providers.append(fallback_provider)
+            if fallback_id:
+                seen_provider_ids.add(fallback_id)
        self.final_llm_resp = None
        self._state = AgentState.IDLE
        self.tool_executor = tool_executor
        self.agent_hooks = agent_hooks
        self.run_context = run_context
+        self._stop_requested = False
+        self._aborted = False
+        self._pending_follow_ups: list[FollowUpTicket] = []
+        self._follow_up_seq = 0
+
+        # These two are used for tool schema mode handling
+        # We now have two modes:
+        # - "full": use full tool schema for LLM calls, default.
+        # - "skills_like": use light tool schema for LLM calls, and re-query with param-only schema when needed.
+        #   Light tool schema does not include tool parameters.
+        #   This can reduce token usage when tools have large descriptions.
+        # See #4681
+        self.tool_schema_mode = tool_schema_mode
+        self._tool_schema_param_set = None
+        self._skill_like_raw_tool_set = None
+        if tool_schema_mode == "skills_like":
+            tool_set = self.req.func_tool
+            if not tool_set:
+                return
+            self._skill_like_raw_tool_set = tool_set
+            light_set = tool_set.get_light_tool_set()
+            self._tool_schema_param_set = tool_set.get_param_only_tool_set()
+            # MODIFIE the req.func_tool to use light tool schemas
+            self.req.func_tool = light_set

        messages = []
        # append existing messages in the run context
        for msg in request.contexts:
-            messages.append(Message.model_validate(msg))
+            m = Message.model_validate(msg)
+            if isinstance(msg, dict) and msg.get("_no_save"):
+                m._no_save = True
+            messages.append(m)
        if request.prompt is not None:
            m = await request.assemble_context()
            messages.append(Message.model_validate(m))
@@ -69,20 +196,154 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
            )
        self.run_context.messages = messages

-    def _transition_state(self, new_state: AgentState) -> None:
-        """转换 Agent 状态"""
-        if self._state != new_state:
-            logger.debug(f"Agent state transition: {self._state} -> {new_state}")
-            self._state = new_state
+        self.stats = AgentStats()
+        self.stats.start_time = time.time()

-    async def _iter_llm_responses(self) -> T.AsyncGenerator[LLMResponse, None]:
+    async def _iter_llm_responses(
+        self, *, include_model: bool = True
+    ) -> T.AsyncGenerator[LLMResponse, None]:
        """Yields chunks *and* a final LLMResponse."""
+        payload = {
+            "contexts": self.run_context.messages,  # list[Message]
+            "func_tool": self.req.func_tool,
+            "session_id": self.req.session_id,
+            "extra_user_content_parts": self.req.extra_user_content_parts,  # list[ContentPart]
+        }
+        if include_model:
+            # For primary provider we keep explicit model selection if provided.
+            payload["model"] = self.req.model
        if self.streaming:
-            stream = self.provider.text_chat_stream(**self.req.__dict__)
+            stream = self.provider.text_chat_stream(**payload)
            async for resp in stream:  # type: ignore
                yield resp
        else:
-            yield await self.provider.text_chat(**self.req.__dict__)
+            yield await self.provider.text_chat(**payload)
+
+    async def _iter_llm_responses_with_fallback(
+        self,
+    ) -> T.AsyncGenerator[LLMResponse, None]:
+        """Wrap _iter_llm_responses with provider fallback handling."""
+        candidates = [self.provider, *self.fallback_providers]
+        total_candidates = len(candidates)
+        last_exception: Exception | None = None
+        last_err_response: LLMResponse | None = None
+
+        for idx, candidate in enumerate(candidates):
+            candidate_id = candidate.provider_config.get("id", "<unknown>")
+            is_last_candidate = idx == total_candidates - 1
+            if idx > 0:
+                logger.warning(
+                    "Switched from %s to fallback chat provider: %s",
+                    self.provider.provider_config.get("id", "<unknown>"),
+                    candidate_id,
+                )
+            self.provider = candidate
+            has_stream_output = False
+            try:
+                async for resp in self._iter_llm_responses(include_model=idx == 0):
+                    if resp.is_chunk:
+                        has_stream_output = True
+                        yield resp
+                        continue
+
+                    if (
+                        resp.role == "err"
+                        and not has_stream_output
+                        and (not is_last_candidate)
+                    ):
+                        last_err_response = resp
+                        logger.warning(
+                            "Chat Model %s returns error response, trying fallback to next provider.",
+                            candidate_id,
+                        )
+                        break
+
+                    yield resp
+                    return
+
+                if has_stream_output:
+                    return
+            except Exception as exc:  # noqa: BLE001
+                last_exception = exc
+                logger.warning(
+                    "Chat Model %s request error: %s",
+                    candidate_id,
+                    exc,
+                    exc_info=True,
+                )
+                continue
+
+        if last_err_response:
+            yield last_err_response
+            return
+        if last_exception:
+            yield LLMResponse(
+                role="err",
+                completion_text=(
+                    "All chat models failed: "
+                    f"{type(last_exception).__name__}: {last_exception}"
+                ),
+            )
+            return
+        yield LLMResponse(
+            role="err",
+            completion_text="All available chat models are unavailable.",
+        )
+
+    def _simple_print_message_role(self, tag: str = ""):
+        roles = []
+        for message in self.run_context.messages:
+            roles.append(message.role)
+        logger.debug(f"{tag} RunCtx.messages -> [{len(roles)}] {','.join(roles)}")
+
+    def follow_up(
+        self,
+        *,
+        message_text: str,
+    ) -> FollowUpTicket | None:
+        """Queue a follow-up message for the next tool result."""
+        if self.done():
+            return None
+        text = (message_text or "").strip()
+        if not text:
+            return None
+        ticket = FollowUpTicket(seq=self._follow_up_seq, text=text)
+        self._follow_up_seq += 1
+        self._pending_follow_ups.append(ticket)
+        return ticket
+
+    def _resolve_unconsumed_follow_ups(self) -> None:
+        if not self._pending_follow_ups:
+            return
+        follow_ups = self._pending_follow_ups
+        self._pending_follow_ups = []
+        for ticket in follow_ups:
+            ticket.resolved.set()
+
+    def _consume_follow_up_notice(self) -> str:
+        if not self._pending_follow_ups:
+            return ""
+        follow_ups = self._pending_follow_ups
+        self._pending_follow_ups = []
+        for ticket in follow_ups:
+            ticket.consumed = True
+            ticket.resolved.set()
+        follow_up_lines = "\n".join(
+            f"{idx}. {ticket.text}" for idx, ticket in enumerate(follow_ups, start=1)
+        )
+        return (
+            "\n\n[SYSTEM NOTICE] User sent follow-up messages while tool execution "
+            "was in progress. Prioritize these follow-up instructions in your next "
+            "actions. In your very next action, briefly acknowledge to the user "
+            "that their follow-up message(s) were received before continuing.\n"
+            f"{follow_up_lines}"
+        )
+
+    def _merge_follow_up_notice(self, content: str) -> str:
+        notice = self._consume_follow_up_notice()
+        if not notice:
+            return content
+        return f"{content}{notice}"

    @override
    async def step(self):
@@ -102,9 +363,20 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
        self._transition_state(AgentState.RUNNING)
        llm_resp_result = None

-        async for llm_response in self._iter_llm_responses():
-            assert isinstance(llm_response, LLMResponse)
+        # do truncate and compress
+        token_usage = self.req.conversation.token_usage if self.req.conversation else 0
+        self._simple_print_message_role("[BefCompact]")
+        self.run_context.messages = await self.context_manager.process(
+            self.run_context.messages, trusted_token_usage=token_usage
+        )
+        self._simple_print_message_role("[AftCompact]")
+
+        async for llm_response in self._iter_llm_responses_with_fallback():
            if llm_response.is_chunk:
+                # update ttft
+                if self.stats.time_to_first_token == 0:
+                    self.stats.time_to_first_token = time.time() - self.stats.start_time
+
                if llm_response.result_chain:
                    yield AgentResponse(
                        type="streaming_delta",
@@ -126,11 +398,68 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
                            ),
                        ),
                    )
+                if self._stop_requested:
+                    llm_resp_result = LLMResponse(
+                        role="assistant",
+                        completion_text="[SYSTEM: User actively interrupted the response generation. Partial output before interruption is preserved.]",
+                        reasoning_content=llm_response.reasoning_content,
+                        reasoning_signature=llm_response.reasoning_signature,
+                    )
+                    break
                continue
            llm_resp_result = llm_response
+
+            if not llm_response.is_chunk and llm_response.usage:
+                # only count the token usage of the final response for computation purpose
+                self.stats.token_usage += llm_response.usage
+                if self.req.conversation:
+                    self.req.conversation.token_usage = llm_response.usage.total
            break  # got final response

        if not llm_resp_result:
+            if self._stop_requested:
+                llm_resp_result = LLMResponse(role="assistant", completion_text="")
+            else:
+                return
+
+        if self._stop_requested:
+            logger.info("Agent execution was requested to stop by user.")
+            llm_resp = llm_resp_result
+            if llm_resp.role != "assistant":
+                llm_resp = LLMResponse(
+                    role="assistant",
+                    completion_text="[SYSTEM: User actively interrupted the response generation. Partial output before interruption is preserved.]",
+                )
+            self.final_llm_resp = llm_resp
+            self._aborted = True
+            self._transition_state(AgentState.DONE)
+            self.stats.end_time = time.time()
+
+            parts = []
+            if llm_resp.reasoning_content or llm_resp.reasoning_signature:
+                parts.append(
+                    ThinkPart(
+                        think=llm_resp.reasoning_content,
+                        encrypted=llm_resp.reasoning_signature,
+                    )
+                )
+            if llm_resp.completion_text:
+                parts.append(TextPart(text=llm_resp.completion_text))
+            if parts:
+                self.run_context.messages.append(
+                    Message(role="assistant", content=parts)
+                )
+
+            try:
+                await self.agent_hooks.on_agent_done(self.run_context, llm_resp)
+            except Exception as e:
+                logger.error(f"Error in on_agent_done hook: {e}", exc_info=True)
+
+            yield AgentResponse(
+                type="aborted",
+                data=AgentResponseData(chain=MessageChain(type="aborted")),
+            )
+            self._resolve_unconsumed_follow_ups()
            return

        # 处理 LLM 响应
@@ -139,31 +468,50 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
        if llm_resp.role == "err":
            # 如果 LLM 响应错误，转换到错误状态
            self.final_llm_resp = llm_resp
+            self.stats.end_time = time.time()
            self._transition_state(AgentState.ERROR)
+            self._resolve_unconsumed_follow_ups()
+            custom_error_message = self._get_persona_custom_error_message()
+            error_text = custom_error_message or (
+                f"LLM 响应错误: {llm_resp.completion_text or '未知错误'}"
+            )
            yield AgentResponse(
                type="err",
                data=AgentResponseData(
-                    chain=MessageChain().message(
-                        f"LLM 响应错误: {llm_resp.completion_text or '未知错误'}",
-                    ),
+                    chain=MessageChain().message(error_text),
                ),
            )
+            return

        if not llm_resp.tools_call_name:
            # 如果没有工具调用，转换到完成状态
            self.final_llm_resp = llm_resp
            self._transition_state(AgentState.DONE)
+            self.stats.end_time = time.time()
+
            # record the final assistant message
-            self.run_context.messages.append(
-                Message(
-                    role="assistant",
-                    content=llm_resp.completion_text or "",
-                ),
-            )
+            parts = []
+            if llm_resp.reasoning_content or llm_resp.reasoning_signature:
+                parts.append(
+                    ThinkPart(
+                        think=llm_resp.reasoning_content,
+                        encrypted=llm_resp.reasoning_signature,
+                    )
+                )
+            if llm_resp.completion_text:
+                parts.append(TextPart(text=llm_resp.completion_text))
+            if len(parts) == 0:
+                logger.warning(
+                    "LLM returned empty assistant message with no tool calls."
+                )
+            self.run_context.messages.append(Message(role="assistant", content=parts))
+
+            # call the on_agent_done hook
            try:
                await self.agent_hooks.on_agent_done(self.run_context, llm_resp)
            except Exception as e:
                logger.error(f"Error in on_agent_done hook: {e}", exc_info=True)
+            self._resolve_unconsumed_follow_ups()

        # 返回 LLM 结果
        if llm_resp.result_chain:
@@ -181,30 +529,50 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):

        # 如果有工具调用，还需处理工具调用
        if llm_resp.tools_call_name:
+            if self.tool_schema_mode == "skills_like":
+                llm_resp, _ = await self._resolve_tool_exec(llm_resp)
+
            tool_call_result_blocks = []
-            for tool_call_name in llm_resp.tools_call_name:
-                yield AgentResponse(
-                    type="tool_call",
-                    data=AgentResponseData(
-                        chain=MessageChain(type="tool_call").message(
-                            f"🔨 调用工具: {tool_call_name}"
-                        ),
-                    ),
-                )
+            cached_images = []  # Collect cached images for LLM visibility
            async for result in self._handle_function_tools(self.req, llm_resp):
-                if isinstance(result, list):
-                    tool_call_result_blocks = result
-                elif isinstance(result, MessageChain):
-                    result.type = "tool_call_result"
+                if result.kind == "tool_call_result_blocks":
+                    if result.tool_call_result_blocks is not None:
+                        tool_call_result_blocks = result.tool_call_result_blocks
+                elif result.kind == "cached_image":
+                    if result.cached_image is not None:
+                        # Collect cached image info
+                        cached_images.append(result.cached_image)
+                elif result.kind == "message_chain":
+                    chain = result.message_chain
+                    if chain is None or chain.type is None:
+                        # should not happen
+                        continue
+                    if chain.type == "tool_direct_result":
+                        ar_type = "tool_call_result"
+                    else:
+                        ar_type = chain.type
                    yield AgentResponse(
-                        type="tool_call_result",
-                        data=AgentResponseData(chain=result),
+                        type=ar_type,
+                        data=AgentResponseData(chain=chain),
                    )
+
            # 将结果添加到上下文中
+            parts = []
+            if llm_resp.reasoning_content or llm_resp.reasoning_signature:
+                parts.append(
+                    ThinkPart(
+                        think=llm_resp.reasoning_content,
+                        encrypted=llm_resp.reasoning_signature,
+                    )
+                )
+            if llm_resp.completion_text:
+                parts.append(TextPart(text=llm_resp.completion_text))
+            if len(parts) == 0:
+                parts = None
            tool_calls_result = ToolCallsResult(
                tool_calls_info=AssistantMessageSegment(
                    tool_calls=llm_resp.to_openai_to_calls_model(),
-                    content=llm_resp.completion_text,
+                    content=parts,
                ),
                tool_calls_result=tool_call_result_blocks,
            )
@@ -213,6 +581,41 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
                tool_calls_result.to_openai_messages_model()
            )

+            # If there are cached images and the model supports image input,
+            # append a user message with images so LLM can see them
+            if cached_images:
+                modalities = self.provider.provider_config.get("modalities", [])
+                supports_image = "image" in modalities
+                if supports_image:
+                    # Build user message with images for LLM to review
+                    image_parts = []
+                    for cached_img in cached_images:
+                        img_data = tool_image_cache.get_image_base64_by_path(
+                            cached_img.file_path, cached_img.mime_type
+                        )
+                        if img_data:
+                            base64_data, mime_type = img_data
+                            image_parts.append(
+                                TextPart(
+                                    text=f"[Image from tool '{cached_img.tool_name}', path='{cached_img.file_path}']"
+                                )
+                            )
+                            image_parts.append(
+                                ImageURLPart(
+                                    image_url=ImageURLPart.ImageURL(
+                                        url=f"data:{mime_type};base64,{base64_data}",
+                                        id=cached_img.file_path,
+                                    )
+                                )
+                            )
+                    if image_parts:
+                        self.run_context.messages.append(
+                            Message(role="user", content=image_parts)
+                        )
+                        logger.debug(
+                            f"Appended {len(cached_images)} cached image(s) to context for LLM review"
+                        )
+
            self.req.append_tool_calls_result(tool_calls_result)

    async def step_until_done(
@@ -225,35 +628,85 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
            async for resp in self.step():
                yield resp

+        #  如果循环结束了但是 agent 还没有完成，说明是达到了 max_step
+        if not self.done():
+            logger.warning(
+                f"Agent reached max steps ({max_step}), forcing a final response."
+            )
+            # 拔掉所有工具
+            if self.req:
+                self.req.func_tool = None
+            # 注入提示词
+            self.run_context.messages.append(
+                Message(
+                    role="user",
+                    content="工具调用次数已达到上限，请停止使用工具，并根据已经收集到的信息，对你的任务和发现进行总结，然后直接回复用户。",
+                )
+            )
+            # 再执行最后一步
+            async for resp in self.step():
+                yield resp
+
    async def _handle_function_tools(
        self,
        req: ProviderRequest,
        llm_response: LLMResponse,
-    ) -> T.AsyncGenerator[MessageChain | list[ToolCallMessageSegment], None]:
+    ) -> T.AsyncGenerator[_HandleFunctionToolsResult, None]:
        """处理函数工具调用。"""
        tool_call_result_blocks: list[ToolCallMessageSegment] = []
        logger.info(f"Agent 使用工具: {llm_response.tools_call_name}")

+        def _append_tool_call_result(tool_call_id: str, content: str) -> None:
+            tool_call_result_blocks.append(
+                ToolCallMessageSegment(
+                    role="tool",
+                    tool_call_id=tool_call_id,
+                    content=self._merge_follow_up_notice(content),
+                ),
+            )
+
        # 执行函数调用
        for func_tool_name, func_tool_args, func_tool_id in zip(
            llm_response.tools_call_name,
            llm_response.tools_call_args,
            llm_response.tools_call_ids,
        ):
+            yield _HandleFunctionToolsResult.from_message_chain(
+                MessageChain(
+                    type="tool_call",
+                    chain=[
+                        Json(
+                            data={
+                                "id": func_tool_id,
+                                "name": func_tool_name,
+                                "args": func_tool_args,
+                                "ts": time.time(),
+                            }
+                        )
+                    ],
+                )
+            )
            try:
                if not req.func_tool:
                    return
-                func_tool = req.func_tool.get_func(func_tool_name)
+
+                if (
+                    self.tool_schema_mode == "skills_like"
+                    and self._skill_like_raw_tool_set
+                ):
+                    # in 'skills_like' mode, raw.func_tool is light schema, does not have handler
+                    # so we need to get the tool from the raw tool set
+                    func_tool = self._skill_like_raw_tool_set.get_tool(func_tool_name)
+                else:
+                    func_tool = req.func_tool.get_tool(func_tool_name)
+
                logger.info(f"使用工具：{func_tool_name}，参数：{func_tool_args}")

                if not func_tool:
                    logger.warning(f"未找到指定的工具: {func_tool_name}，将跳过。")
-                    tool_call_result_blocks.append(
-                        ToolCallMessageSegment(
-                            role="tool",
-                            tool_call_id=func_tool_id,
-                            content=f"error: 未找到工具 {func_tool_name}",
-                        ),
+                    _append_tool_call_result(
+                        func_tool_id,
+                        f"error: Tool {func_tool_name} not found.",
                    )
                    continue

@@ -306,73 +759,90 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
                        res = resp
                        _final_resp = resp
                        if isinstance(res.content[0], TextContent):
-                            tool_call_result_blocks.append(
-                                ToolCallMessageSegment(
-                                    role="tool",
-                                    tool_call_id=func_tool_id,
-                                    content=res.content[0].text,
-                                ),
+                            _append_tool_call_result(
+                                func_tool_id,
+                                res.content[0].text,
                            )
-                            yield MessageChain().message(res.content[0].text)
                        elif isinstance(res.content[0], ImageContent):
-                            tool_call_result_blocks.append(
-                                ToolCallMessageSegment(
-                                    role="tool",
-                                    tool_call_id=func_tool_id,
-                                    content="返回了图片(已直接发送给用户)",
+                            # Cache the image instead of sending directly
+                            cached_img = tool_image_cache.save_image(
+                                base64_data=res.content[0].data,
+                                tool_call_id=func_tool_id,
+                                tool_name=func_tool_name,
+                                index=0,
+                                mime_type=res.content[0].mimeType or "image/png",
+                            )
+                            _append_tool_call_result(
+                                func_tool_id,
+                                (
+                                    f"Image returned and cached at path='{cached_img.file_path}'. "
+                                    f"Review the image below. Use send_message_to_user to send it to the user if satisfied, "
+                                    f"with type='image' and path='{cached_img.file_path}'."
                                ),
                            )
-                            yield MessageChain(type="tool_direct_result").base64_image(
-                                res.content[0].data,
+                            # Yield image info for LLM visibility (will be handled in step())
+                            yield _HandleFunctionToolsResult.from_cached_image(
+                                cached_img
                            )
                        elif isinstance(res.content[0], EmbeddedResource):
                            resource = res.content[0].resource
                            if isinstance(resource, TextResourceContents):
-                                tool_call_result_blocks.append(
-                                    ToolCallMessageSegment(
-                                        role="tool",
-                                        tool_call_id=func_tool_id,
-                                        content=resource.text,
-                                    ),
+                                _append_tool_call_result(
+                                    func_tool_id,
+                                    resource.text,
                                )
-                                yield MessageChain().message(resource.text)
                            elif (
                                isinstance(resource, BlobResourceContents)
                                and resource.mimeType
                                and resource.mimeType.startswith("image/")
                            ):
-                                tool_call_result_blocks.append(
-                                    ToolCallMessageSegment(
-                                        role="tool",
-                                        tool_call_id=func_tool_id,
-                                        content="返回了图片(已直接发送给用户)",
+                                # Cache the image instead of sending directly
+                                cached_img = tool_image_cache.save_image(
+                                    base64_data=resource.blob,
+                                    tool_call_id=func_tool_id,
+                                    tool_name=func_tool_name,
+                                    index=0,
+                                    mime_type=resource.mimeType,
+                                )
+                                _append_tool_call_result(
+                                    func_tool_id,
+                                    (
+                                        f"Image returned and cached at path='{cached_img.file_path}'. "
+                                        f"Review the image below. Use send_message_to_user to send it to the user if satisfied, "
+                                        f"with type='image' and path='{cached_img.file_path}'."
                                    ),
                                )
-                                yield MessageChain(
-                                    type="tool_direct_result",
-                                ).base64_image(resource.blob)
+                                # Yield image info for LLM visibility
+                                yield _HandleFunctionToolsResult.from_cached_image(
+                                    cached_img
+                                )
                            else:
-                                tool_call_result_blocks.append(
-                                    ToolCallMessageSegment(
-                                        role="tool",
-                                        tool_call_id=func_tool_id,
-                                        content="返回的数据类型不受支持",
-                                    ),
+                                _append_tool_call_result(
+                                    func_tool_id,
+                                    "The tool has returned a data type that is not supported.",
                                )
-                                yield MessageChain().message("返回的数据类型不受支持。")

                    elif resp is None:
                        # Tool 直接请求发送消息给用户
-                        # 这里我们将直接结束 Agent Loop。
-                        # 发送消息逻辑在 ToolExecutor 中处理了。
+                        # 这里我们将直接结束 Agent Loop
+                        # 发送消息逻辑在 ToolExecutor 中处理了
                        logger.warning(
-                            f"{func_tool_name} 没有没有返回值或者将结果直接发送给用户，此工具调用不会被记录到历史中。"
+                            f"{func_tool_name} 没有返回值，或者已将结果直接发送给用户。"
                        )
                        self._transition_state(AgentState.DONE)
+                        self.stats.end_time = time.time()
+                        _append_tool_call_result(
+                            func_tool_id,
+                            "The tool has no return value, or has sent the result directly to the user.",
+                        )
                    else:
                        # 不应该出现其他类型
                        logger.warning(
-                            f"Tool 返回了不支持的类型: {type(resp)}，将忽略。",
+                            f"Tool 返回了不支持的类型: {type(resp)}。",
+                        )
+                        _append_tool_call_result(
+                            func_tool_id,
+                            "*The tool has returned an unsupported type. Please tell the user to check the definition and implementation of this tool.*",
                        )

                try:
@@ -386,21 +856,110 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
                    logger.error(f"Error in on_tool_end hook: {e}", exc_info=True)
            except Exception as e:
                logger.warning(traceback.format_exc())
-                tool_call_result_blocks.append(
-                    ToolCallMessageSegment(
-                        role="tool",
-                        tool_call_id=func_tool_id,
-                        content=f"error: {e!s}",
-                    ),
+                _append_tool_call_result(
+                    func_tool_id,
+                    f"error: {e!s}",
                )

+        # yield the last tool call result
+        if tool_call_result_blocks:
+            last_tcr_content = str(tool_call_result_blocks[-1].content)
+            yield _HandleFunctionToolsResult.from_message_chain(
+                MessageChain(
+                    type="tool_call_result",
+                    chain=[
+                        Json(
+                            data={
+                                "id": func_tool_id,
+                                "ts": time.time(),
+                                "result": last_tcr_content,
+                            }
+                        )
+                    ],
+                )
+            )
+            logger.info(f"Tool `{func_tool_name}` Result: {last_tcr_content}")
+
        # 处理函数调用响应
        if tool_call_result_blocks:
-            yield tool_call_result_blocks
+            yield _HandleFunctionToolsResult.from_tool_call_result_blocks(
+                tool_call_result_blocks
+            )
+
+    def _build_tool_requery_context(
+        self, tool_names: list[str]
+    ) -> list[dict[str, T.Any]]:
+        """Build contexts for re-querying LLM with param-only tool schemas."""
+        contexts: list[dict[str, T.Any]] = []
+        for msg in self.run_context.messages:
+            if hasattr(msg, "model_dump"):
+                contexts.append(msg.model_dump())  # type: ignore[call-arg]
+            elif isinstance(msg, dict):
+                contexts.append(copy.deepcopy(msg))
+        instruction = (
+            "You have decided to call tool(s): "
+            + ", ".join(tool_names)
+            + ". Now call the tool(s) with required arguments using the tool schema, "
+            "and follow the existing tool-use rules."
+        )
+        if contexts and contexts[0].get("role") == "system":
+            content = contexts[0].get("content") or ""
+            contexts[0]["content"] = f"{content}\n{instruction}"
+        else:
+            contexts.insert(0, {"role": "system", "content": instruction})
+        return contexts
+
+    def _build_tool_subset(self, tool_set: ToolSet, tool_names: list[str]) -> ToolSet:
+        """Build a subset of tools from the given tool set based on tool names."""
+        subset = ToolSet()
+        for name in tool_names:
+            tool = tool_set.get_tool(name)
+            if tool:
+                subset.add_tool(tool)
+        return subset
+
+    async def _resolve_tool_exec(
+        self,
+        llm_resp: LLMResponse,
+    ) -> tuple[LLMResponse, ToolSet | None]:
+        """Used in 'skills_like' tool schema mode to re-query LLM with param-only tool schemas."""
+        tool_names = llm_resp.tools_call_name
+        if not tool_names:
+            return llm_resp, self.req.func_tool
+        full_tool_set = self.req.func_tool
+        if not isinstance(full_tool_set, ToolSet):
+            return llm_resp, self.req.func_tool
+
+        subset = self._build_tool_subset(full_tool_set, tool_names)
+        if not subset.tools:
+            return llm_resp, full_tool_set
+
+        if isinstance(self._tool_schema_param_set, ToolSet):
+            param_subset = self._build_tool_subset(
+                self._tool_schema_param_set, tool_names
+            )
+            if param_subset.tools and tool_names:
+                contexts = self._build_tool_requery_context(tool_names)
+                requery_resp = await self.provider.text_chat(
+                    contexts=contexts,
+                    func_tool=param_subset,
+                    model=self.req.model,
+                    session_id=self.req.session_id,
+                )
+                if requery_resp:
+                    llm_resp = requery_resp
+
+        return llm_resp, subset

    def done(self) -> bool:
        """检查 Agent 是否已完成工作"""
        return self._state in (AgentState.DONE, AgentState.ERROR)

+    def request_stop(self) -> None:
+        self._stop_requested = True
+
+    def was_aborted(self) -> bool:
+        return self._aborted
+
    def get_final_llm_resp(self) -> LLMResponse | None:
        return self.final_llm_resp
@@ -1,4 +1,5 @@
-from collections.abc import Awaitable, Callable
+import copy
+from collections.abc import AsyncGenerator, Awaitable, Callable
 from typing import Any, Generic

 import jsonschema
@@ -7,6 +8,8 @@ from deprecated import deprecated
 from pydantic import Field, model_validator
 from pydantic.dataclasses import dataclass

+from astrbot.core.message.message_event_result import MessageEventResult
+
 from .run_context import ContextWrapper, TContext

 ParametersType = dict[str, Any]
@@ -38,7 +41,10 @@ class ToolSchema:
 class FunctionTool(ToolSchema, Generic[TContext]):
    """A callable tool, for function calling."""

-    handler: Callable[..., Awaitable[Any]] | None = None
+    handler: (
+        Callable[..., Awaitable[str | None] | AsyncGenerator[MessageEventResult, None]]
+        | None
+    ) = None
    """a callable that implements the tool's functionality. It should be an async function."""

    handler_module_path: str | None = None
@@ -52,8 +58,13 @@ class FunctionTool(ToolSchema, Generic[TContext]):
    Whether the tool is active. This field is a special field for AstrBot.
    You can ignore it when integrating with other frameworks.
    """
+    is_background_task: bool = False
+    """
+    Declare this tool as a background task. Background tasks return immediately
+    with a task identifier while the real work continues asynchronously.
+    """

-    def __repr__(self):
+    def __repr__(self) -> str:
        return f"FuncTool(name={self.name}, parameters={self.parameters}, description={self.description})"

    async def call(self, context: ContextWrapper[TContext], **kwargs) -> ToolExecResult:
@@ -77,7 +88,7 @@ class ToolSet:
        """Check if the tool set is empty."""
        return len(self.tools) == 0

-    def add_tool(self, tool: FunctionTool):
+    def add_tool(self, tool: FunctionTool) -> None:
        """Add a tool to the set."""
        # 检查是否已存在同名工具
        for i, existing_tool in enumerate(self.tools):
@@ -86,7 +97,7 @@ class ToolSet:
                return
        self.tools.append(tool)

-    def remove_tool(self, name: str):
+    def remove_tool(self, name: str) -> None:
        """Remove a tool by its name."""
        self.tools = [tool for tool in self.tools if tool.name != name]

@@ -97,6 +108,47 @@ class ToolSet:
                return tool
        return None

+    def get_light_tool_set(self) -> "ToolSet":
+        """Return a light tool set with only name/description."""
+        light_tools = []
+        for tool in self.tools:
+            if hasattr(tool, "active") and not tool.active:
+                continue
+            light_params = {
+                "type": "object",
+                "properties": {},
+            }
+            light_tools.append(
+                FunctionTool(
+                    name=tool.name,
+                    parameters=light_params,
+                    description=tool.description,
+                    handler=None,
+                )
+            )
+        return ToolSet(light_tools)
+
+    def get_param_only_tool_set(self) -> "ToolSet":
+        """Return a tool set with name/parameters only (no description)."""
+        param_tools = []
+        for tool in self.tools:
+            if hasattr(tool, "active") and not tool.active:
+                continue
+            params = (
+                copy.deepcopy(tool.parameters)
+                if tool.parameters
+                else {"type": "object", "properties": {}}
+            )
+            param_tools.append(
+                FunctionTool(
+                    name=tool.name,
+                    parameters=params,
+                    description="",
+                    handler=None,
+                )
+            )
+        return ToolSet(param_tools)
+
    @deprecated(reason="Use add_tool() instead", version="4.0.0")
    def add_func(
        self,
@@ -104,7 +156,7 @@ class ToolSet:
        func_args: list,
        desc: str,
        handler: Callable[..., Awaitable[Any]],
-    ):
+    ) -> None:
        """Add a function tool to the set."""
        params = {
            "type": "object",  # hard-coded here
@@ -124,7 +176,7 @@ class ToolSet:
        self.add_tool(_func)

    @deprecated(reason="Use remove_tool() instead", version="4.0.0")
-    def remove_func(self, name: str):
+    def remove_func(self, name: str) -> None:
        """Remove a function tool by its name."""
        self.remove_tool(name)

@@ -142,18 +194,15 @@ class ToolSet:
        """Convert tools to OpenAI API function calling schema format."""
        result = []
        for tool in self.tools:
-            func_def = {
-                "type": "function",
-                "function": {
-                    "name": tool.name,
-                    "description": tool.description,
-                },
-            }
+            func_def = {"type": "function", "function": {"name": tool.name}}
+            if tool.description:
+                func_def["function"]["description"] = tool.description

-            if (
-                tool.parameters and tool.parameters.get("properties")
-            ) or not omit_empty_parameter_field:
-                func_def["function"]["parameters"] = tool.parameters
+            if tool.parameters is not None:
+                if (
+                    tool.parameters and tool.parameters.get("properties")
+                ) or not omit_empty_parameter_field:
+                    func_def["function"]["parameters"] = tool.parameters

            result.append(func_def)
        return result
@@ -166,11 +215,9 @@ class ToolSet:
            if tool.parameters:
                input_schema["properties"] = tool.parameters.get("properties", {})
                input_schema["required"] = tool.parameters.get("required", [])
-            tool_def = {
-                "name": tool.name,
-                "description": tool.description,
-                "input_schema": input_schema,
-            }
+            tool_def = {"name": tool.name, "input_schema": input_schema}
+            if tool.description:
+                tool_def["description"] = tool.description
            result.append(tool_def)
        return result

@@ -199,8 +246,18 @@ class ToolSet:

            result = {}

-            if "type" in schema and schema["type"] in supported_types:
-                result["type"] = schema["type"]
+            # Avoid side effects by not modifying the original schema
+            origin_type = schema.get("type")
+            target_type = origin_type
+
+            # Compatibility fix: Gemini API expects 'type' to be a string (enum),
+            # but standard JSON Schema (MCP) allows lists (e.g. ["string", "null"]).
+            # We fallback to the first non-null type.
+            if isinstance(origin_type, list):
+                target_type = next((t for t in origin_type if t != "null"), "string")
+
+            if target_type in supported_types:
+                result["type"] = target_type
                if "format" in schema and schema["format"] in supported_formats.get(
                    result["type"],
                    set(),
@@ -228,6 +285,9 @@ class ToolSet:
                    prop_value = convert_schema(value)
                    if "default" in prop_value:
                        del prop_value["default"]
+                    # see #5217
+                    if "additionalProperties" in prop_value:
+                        del prop_value["additionalProperties"]
                    properties[key] = prop_value

                if properties:
@@ -240,10 +300,9 @@ class ToolSet:

        tools = []
        for tool in self.tools:
-            d: dict[str, Any] = {
-                "name": tool.name,
-                "description": tool.description,
-            }
+            d: dict[str, Any] = {"name": tool.name}
+            if tool.description:
+                d["description"] = tool.description
            if tool.parameters:
                d["parameters"] = convert_schema(tool.parameters)
            tools.append(d)
@@ -269,17 +328,22 @@ class ToolSet:
        """获取所有工具的名称列表"""
        return [tool.name for tool in self.tools]

-    def __len__(self):
+    def merge(self, other: "ToolSet") -> None:
+        """Merge another ToolSet into this one."""
+        for tool in other.tools:
+            self.add_tool(tool)
+
+    def __len__(self) -> int:
        return len(self.tools)

-    def __bool__(self):
+    def __bool__(self) -> bool:
        return len(self.tools) > 0

    def __iter__(self):
        return iter(self.tools)

-    def __repr__(self):
+    def __repr__(self) -> str:
        return f"ToolSet(tools={self.tools})"

-    def __str__(self):
+    def __str__(self) -> str:
        return f"ToolSet(tools={self.tools})"
@@ -0,0 +1,162 @@
+"""Tool image cache module for storing and retrieving images returned by tools.
+
+This module allows LLM to review images before deciding whether to send them to users.
+"""
+
+import base64
+import os
+import time
+from dataclasses import dataclass, field
+from typing import ClassVar
+
+from astrbot import logger
+from astrbot.core.utils.astrbot_path import get_astrbot_temp_path
+
+
+@dataclass
+class CachedImage:
+    """Represents a cached image from a tool call."""
+
+    tool_call_id: str
+    """The tool call ID that produced this image."""
+    tool_name: str
+    """The name of the tool that produced this image."""
+    file_path: str
+    """The file path where the image is stored."""
+    mime_type: str
+    """The MIME type of the image."""
+    created_at: float = field(default_factory=time.time)
+    """Timestamp when the image was cached."""
+
+
+class ToolImageCache:
+    """Manages cached images from tool calls.
+
+    Images are stored in data/temp/tool_images/ and can be retrieved by file path.
+    """
+
+    _instance: ClassVar["ToolImageCache | None"] = None
+    CACHE_DIR_NAME: ClassVar[str] = "tool_images"
+    # Cache expiry time in seconds (1 hour)
+    CACHE_EXPIRY: ClassVar[int] = 3600
+
+    def __new__(cls) -> "ToolImageCache":
+        if cls._instance is None:
+            cls._instance = super().__new__(cls)
+            cls._instance._initialized = False
+        return cls._instance
+
+    def __init__(self) -> None:
+        if self._initialized:
+            return
+        self._initialized = True
+        self._cache_dir = os.path.join(get_astrbot_temp_path(), self.CACHE_DIR_NAME)
+        os.makedirs(self._cache_dir, exist_ok=True)
+        logger.debug(f"ToolImageCache initialized, cache dir: {self._cache_dir}")
+
+    def _get_file_extension(self, mime_type: str) -> str:
+        """Get file extension from MIME type."""
+        mime_to_ext = {
+            "image/png": ".png",
+            "image/jpeg": ".jpg",
+            "image/jpg": ".jpg",
+            "image/gif": ".gif",
+            "image/webp": ".webp",
+            "image/bmp": ".bmp",
+            "image/svg+xml": ".svg",
+        }
+        return mime_to_ext.get(mime_type.lower(), ".png")
+
+    def save_image(
+        self,
+        base64_data: str,
+        tool_call_id: str,
+        tool_name: str,
+        index: int = 0,
+        mime_type: str = "image/png",
+    ) -> CachedImage:
+        """Save an image to cache and return the cached image info.
+
+        Args:
+            base64_data: Base64 encoded image data.
+            tool_call_id: The tool call ID that produced this image.
+            tool_name: The name of the tool that produced this image.
+            index: The index of the image (for multiple images from same tool call).
+            mime_type: The MIME type of the image.
+
+        Returns:
+            CachedImage object with file path.
+        """
+        ext = self._get_file_extension(mime_type)
+        file_name = f"{tool_call_id}_{index}{ext}"
+        file_path = os.path.join(self._cache_dir, file_name)
+
+        # Decode and save the image
+        try:
+            image_bytes = base64.b64decode(base64_data)
+            with open(file_path, "wb") as f:
+                f.write(image_bytes)
+            logger.debug(f"Saved tool image to: {file_path}")
+        except Exception as e:
+            logger.error(f"Failed to save tool image: {e}")
+            raise
+
+        return CachedImage(
+            tool_call_id=tool_call_id,
+            tool_name=tool_name,
+            file_path=file_path,
+            mime_type=mime_type,
+        )
+
+    def get_image_base64_by_path(
+        self, file_path: str, mime_type: str = "image/png"
+    ) -> tuple[str, str] | None:
+        """Read an image file and return its base64 encoded data.
+
+        Args:
+            file_path: The file path of the cached image.
+            mime_type: The MIME type of the image.
+
+        Returns:
+            Tuple of (base64_data, mime_type) if found, None otherwise.
+        """
+        if not os.path.exists(file_path):
+            return None
+
+        try:
+            with open(file_path, "rb") as f:
+                image_bytes = f.read()
+            base64_data = base64.b64encode(image_bytes).decode("utf-8")
+            return base64_data, mime_type
+        except Exception as e:
+            logger.error(f"Failed to read cached image {file_path}: {e}")
+            return None
+
+    def cleanup_expired(self) -> int:
+        """Clean up expired cached images.
+
+        Returns:
+            Number of images cleaned up.
+        """
+        now = time.time()
+        cleaned = 0
+
+        try:
+            for file_name in os.listdir(self._cache_dir):
+                file_path = os.path.join(self._cache_dir, file_name)
+                if os.path.isfile(file_path):
+                    file_age = now - os.path.getmtime(file_path)
+                    if file_age > self.CACHE_EXPIRY:
+                        os.remove(file_path)
+                        cleaned += 1
+        except Exception as e:
+            logger.warning(f"Error during cache cleanup: {e}")
+
+        if cleaned:
+            logger.info(f"Cleaned up {cleaned} expired cached images")
+
+        return cleaned
+
+
+# Global singleton instance
+tool_image_cache = ToolImageCache()
@@ -6,8 +6,10 @@ from astrbot.core.platform.astr_message_event import AstrMessageEvent
 from astrbot.core.star.context import Context


-@dataclass(config={"arbitrary_types_allowed": True})
+@dataclass
 class AstrAgentContext:
+    __pydantic_config__ = {"arbitrary_types_allowed": True}
+
    context: Context
    """The star context instance"""
    event: AstrMessageEvent
@@ -3,6 +3,7 @@ from typing import Any
 from mcp.types import CallToolResult

 from astrbot.core.agent.hooks import BaseAgentRunHooks
+from astrbot.core.agent.message import Message
 from astrbot.core.agent.run_context import ContextWrapper
 from astrbot.core.agent.tool import FunctionTool
 from astrbot.core.astr_agent_context import AstrAgentContext
@@ -11,22 +12,73 @@ from astrbot.core.star.star_handler import EventType


 class MainAgentHooks(BaseAgentRunHooks[AstrAgentContext]):
-    async def on_agent_done(self, run_context, llm_response):
+    async def on_agent_done(self, run_context, llm_response) -> None:
        # 执行事件钩子
+        if llm_response and llm_response.reasoning_content:
+            # we will use this in result_decorate stage to inject reasoning content to chain
+            run_context.context.event.set_extra(
+                "_llm_reasoning_content", llm_response.reasoning_content
+            )
+
        await call_event_hook(
            run_context.context.event,
            EventType.OnLLMResponseEvent,
            llm_response,
        )

+    async def on_tool_start(
+        self,
+        run_context: ContextWrapper[AstrAgentContext],
+        tool: FunctionTool[Any],
+        tool_args: dict | None,
+    ) -> None:
+        await call_event_hook(
+            run_context.context.event,
+            EventType.OnUsingLLMToolEvent,
+            tool,
+            tool_args,
+        )
+
    async def on_tool_end(
        self,
        run_context: ContextWrapper[AstrAgentContext],
        tool: FunctionTool[Any],
        tool_args: dict | None,
        tool_result: CallToolResult | None,
-    ):
+    ) -> None:
        run_context.context.event.clear_result()
+        await call_event_hook(
+            run_context.context.event,
+            EventType.OnLLMToolRespondEvent,
+            tool,
+            tool_args,
+            tool_result,
+        )
+
+        # special handle web_search_tavily
+        platform_name = run_context.context.event.get_platform_name()
+        if (
+            platform_name == "webchat"
+            and tool.name in ["web_search_tavily", "web_search_bocha"]
+            and len(run_context.messages) > 0
+            and tool_result
+            and len(tool_result.content)
+        ):
+            # inject system prompt
+            first_part = run_context.messages[0]
+            if (
+                isinstance(first_part, Message)
+                and first_part.role == "system"
+                and first_part.content
+                and isinstance(first_part.content, str)
+            ):
+                # we assume system part is str
+                first_part.content += (
+                    "Always cite web search results you rely on. "
+                    "Index is a unique identifier for each search result. "
+                    "Use the exact citation format <ref>index</ref> (e.g. <ref>abcd.3</ref>) "
+                    "after the sentence that uses the information. Do not invent citations."
+                )


 class EmptyAgentHooks(BaseAgentRunHooks[AstrAgentContext]):
@@ -1,47 +1,191 @@
+import asyncio
+import re
+import time
 import traceback
 from collections.abc import AsyncGenerator

 from astrbot.core import logger
+from astrbot.core.agent.message import Message
 from astrbot.core.agent.runners.tool_loop_agent_runner import ToolLoopAgentRunner
 from astrbot.core.astr_agent_context import AstrAgentContext
+from astrbot.core.message.components import BaseMessageComponent, Json, Plain
 from astrbot.core.message.message_event_result import (
    MessageChain,
    MessageEventResult,
    ResultContentType,
 )
+from astrbot.core.persona_error_reply import (
+    extract_persona_custom_error_message_from_event,
+)
+from astrbot.core.provider.entities import LLMResponse
+from astrbot.core.provider.provider import TTSProvider

 AgentRunner = ToolLoopAgentRunner[AstrAgentContext]


+def _should_stop_agent(astr_event) -> bool:
+    return astr_event.is_stopped() or bool(astr_event.get_extra("agent_stop_requested"))
+
+
+def _truncate_tool_result(text: str, limit: int = 70) -> str:
+    if limit <= 0:
+        return ""
+    if len(text) <= limit:
+        return text
+    if limit <= 3:
+        return text[:limit]
+    return f"{text[: limit - 3]}..."
+
+
+def _extract_chain_json_data(msg_chain: MessageChain) -> dict | None:
+    if not msg_chain.chain:
+        return None
+    first_comp = msg_chain.chain[0]
+    if isinstance(first_comp, Json) and isinstance(first_comp.data, dict):
+        return first_comp.data
+    return None
+
+
+def _record_tool_call_name(
+    tool_info: dict | None, tool_name_by_call_id: dict[str, str]
+) -> None:
+    if not isinstance(tool_info, dict):
+        return
+    tool_call_id = tool_info.get("id")
+    tool_name = tool_info.get("name")
+    if tool_call_id is None or tool_name is None:
+        return
+    tool_name_by_call_id[str(tool_call_id)] = str(tool_name)
+
+
+def _build_tool_call_status_message(tool_info: dict | None) -> str:
+    if tool_info:
+        return f"🔨 调用工具: {tool_info.get('name', 'unknown')}"
+    return "🔨 调用工具..."
+
+
+def _build_tool_result_status_message(
+    msg_chain: MessageChain, tool_name_by_call_id: dict[str, str]
+) -> str:
+    tool_name = "unknown"
+    tool_result = ""
+
+    result_data = _extract_chain_json_data(msg_chain)
+    if result_data:
+        tool_call_id = result_data.get("id")
+        if tool_call_id is not None:
+            tool_name = tool_name_by_call_id.pop(str(tool_call_id), "unknown")
+        tool_result = str(result_data.get("result", ""))
+
+    if not tool_result:
+        tool_result = msg_chain.get_plain_text(with_other_comps_mark=True)
+    tool_result = _truncate_tool_result(tool_result, 70)
+
+    status_msg = f"🔨 调用工具: {tool_name}"
+    if tool_result:
+        status_msg = f"{status_msg}\n📎 返回结果: {tool_result}"
+    return status_msg
+
+
 async def run_agent(
    agent_runner: AgentRunner,
    max_step: int = 30,
    show_tool_use: bool = True,
+    show_tool_call_result: bool = False,
    stream_to_general: bool = False,
    show_reasoning: bool = False,
 ) -> AsyncGenerator[MessageChain | None, None]:
    step_idx = 0
    astr_event = agent_runner.run_context.context.event
-    while step_idx < max_step:
+    tool_name_by_call_id: dict[str, str] = {}
+    while step_idx < max_step + 1:
        step_idx += 1
+
+        if step_idx == max_step + 1:
+            logger.warning(
+                f"Agent reached max steps ({max_step}), forcing a final response."
+            )
+            if not agent_runner.done():
+                # 拔掉所有工具
+                if agent_runner.req:
+                    agent_runner.req.func_tool = None
+                # 注入提示词
+                agent_runner.run_context.messages.append(
+                    Message(
+                        role="user",
+                        content="工具调用次数已达到上限，请停止使用工具，并根据已经收集到的信息，对你的任务和发现进行总结，然后直接回复用户。",
+                    )
+                )
+
+        stop_watcher = asyncio.create_task(
+            _watch_agent_stop_signal(agent_runner, astr_event),
+        )
        try:
            async for resp in agent_runner.step():
-                if astr_event.is_stopped():
+                if _should_stop_agent(astr_event):
+                    agent_runner.request_stop()
+
+                if resp.type == "aborted":
+                    if not stop_watcher.done():
+                        stop_watcher.cancel()
+                        try:
+                            await stop_watcher
+                        except asyncio.CancelledError:
+                            pass
+                    astr_event.set_extra("agent_user_aborted", True)
+                    astr_event.set_extra("agent_stop_requested", False)
                    return
+
+                if _should_stop_agent(astr_event):
+                    continue
+
                if resp.type == "tool_call_result":
                    msg_chain = resp.data["chain"]
+
+                    astr_event.trace.record(
+                        "agent_tool_result",
+                        tool_result=msg_chain.get_plain_text(
+                            with_other_comps_mark=True
+                        ),
+                    )
+
                    if msg_chain.type == "tool_direct_result":
                        # tool_direct_result 用于标记 llm tool 需要直接发送给用户的内容
-                        await astr_event.send(resp.data["chain"])
+                        await astr_event.send(msg_chain)
                        continue
+                    if astr_event.get_platform_id() == "webchat":
+                        await astr_event.send(msg_chain)
+                    elif show_tool_use and show_tool_call_result:
+                        status_msg = _build_tool_result_status_message(
+                            msg_chain, tool_name_by_call_id
+                        )
+                        await astr_event.send(
+                            MessageChain(type="tool_call").message(status_msg)
+                        )
                    # 对于其他情况，暂时先不处理
                    continue
                elif resp.type == "tool_call":
                    if agent_runner.streaming:
                        # 用来标记流式响应需要分节
                        yield MessageChain(chain=[], type="break")
-                    if show_tool_use:
+
+                    tool_info = _extract_chain_json_data(resp.data["chain"])
+                    astr_event.trace.record(
+                        "agent_tool_call",
+                        tool_name=tool_info if tool_info else "unknown",
+                    )
+                    _record_tool_call_name(tool_info, tool_name_by_call_id)
+
+                    if astr_event.get_platform_name() == "webchat":
                        await astr_event.send(resp.data["chain"])
+                    elif show_tool_use:
+                        if show_tool_call_result and isinstance(tool_info, dict):
+                            # Delay tool status notification until tool_call_result.
+                            continue
+                        chain = MessageChain(type="tool_call").message(
+                            _build_tool_call_status_message(tool_info)
+                        )
+                        await astr_event.send(chain)
                    continue

                if stream_to_general and resp.type == "streaming_delta":
@@ -67,14 +211,314 @@ async def run_agent(
                        # display the reasoning content only when configured
                        continue
                    yield resp.data["chain"]  # MessageChain
+            if not stop_watcher.done():
+                stop_watcher.cancel()
+                try:
+                    await stop_watcher
+                except asyncio.CancelledError:
+                    pass
            if agent_runner.done():
+                # send agent stats to webchat
+                if astr_event.get_platform_name() == "webchat":
+                    await astr_event.send(
+                        MessageChain(
+                            type="agent_stats",
+                            chain=[Json(data=agent_runner.stats.to_dict())],
+                        )
+                    )
+
                break

        except Exception as e:
+            if "stop_watcher" in locals() and not stop_watcher.done():
+                stop_watcher.cancel()
+                try:
+                    await stop_watcher
+                except asyncio.CancelledError:
+                    pass
            logger.error(traceback.format_exc())
-            err_msg = f"\n\nAstrBot 请求失败。\n错误类型: {type(e).__name__}\n错误信息: {e!s}\n\n请在控制台查看和分享错误详情。\n"
+
+            custom_error_message = extract_persona_custom_error_message_from_event(
+                astr_event
+            )
+            if custom_error_message:
+                err_msg = custom_error_message
+            else:
+                err_msg = (
+                    f"Error occurred during AI execution.\n"
+                    f"Error Type: {type(e).__name__}\n"
+                    f"Error Message: {str(e)}"
+                )
+
+            error_llm_response = LLMResponse(
+                role="err",
+                completion_text=err_msg,
+            )
+            try:
+                await agent_runner.agent_hooks.on_agent_done(
+                    agent_runner.run_context, error_llm_response
+                )
+            except Exception:
+                logger.exception("Error in on_agent_done hook")
+
            if agent_runner.streaming:
                yield MessageChain().message(err_msg)
            else:
                astr_event.set_result(MessageEventResult().message(err_msg))
            return
+
+
+async def _watch_agent_stop_signal(agent_runner: AgentRunner, astr_event) -> None:
+    while not agent_runner.done():
+        if _should_stop_agent(astr_event):
+            agent_runner.request_stop()
+            return
+        await asyncio.sleep(0.5)
+
+
+async def run_live_agent(
+    agent_runner: AgentRunner,
+    tts_provider: TTSProvider | None = None,
+    max_step: int = 30,
+    show_tool_use: bool = True,
+    show_tool_call_result: bool = False,
+    show_reasoning: bool = False,
+) -> AsyncGenerator[MessageChain | None, None]:
+    """Live Mode 的 Agent 运行器，支持流式 TTS
+
+    Args:
+        agent_runner: Agent 运行器
+        tts_provider: TTS Provider 实例
+        max_step: 最大步数
+        show_tool_use: 是否显示工具使用
+        show_tool_call_result: 是否显示工具返回结果
+        show_reasoning: 是否显示推理过程
+
+    Yields:
+        MessageChain: 包含文本或音频数据的消息链
+    """
+    # 如果没有 TTS Provider，直接发送文本
+    if not tts_provider:
+        async for chain in run_agent(
+            agent_runner,
+            max_step=max_step,
+            show_tool_use=show_tool_use,
+            show_tool_call_result=show_tool_call_result,
+            stream_to_general=False,
+            show_reasoning=show_reasoning,
+        ):
+            yield chain
+        return
+
+    support_stream = tts_provider.support_stream()
+    if support_stream:
+        logger.info("[Live Agent] 使用流式 TTS（原生支持 get_audio_stream）")
+    else:
+        logger.info(
+            f"[Live Agent] 使用 TTS（{tts_provider.meta().type} "
+            "使用 get_audio，将按句子分块生成音频）"
+        )
+
+    # 统计数据初始化
+    tts_start_time = time.time()
+    tts_first_frame_time = 0.0
+    first_chunk_received = False
+
+    # 创建队列
+    text_queue: asyncio.Queue[str | None] = asyncio.Queue()
+    # audio_queue stored bytes or (text, bytes)
+    audio_queue: asyncio.Queue[bytes | tuple[str, bytes] | None] = asyncio.Queue()
+
+    # 1. 启动 Agent Feeder 任务：负责运行 Agent 并将文本分句喂给 text_queue
+    feeder_task = asyncio.create_task(
+        _run_agent_feeder(
+            agent_runner,
+            text_queue,
+            max_step,
+            show_tool_use,
+            show_tool_call_result,
+            show_reasoning,
+        )
+    )
+
+    # 2. 启动 TTS 任务：负责从 text_queue 读取文本并生成音频到 audio_queue
+    if support_stream:
+        tts_task = asyncio.create_task(
+            _safe_tts_stream_wrapper(tts_provider, text_queue, audio_queue)
+        )
+    else:
+        tts_task = asyncio.create_task(
+            _simulated_stream_tts(tts_provider, text_queue, audio_queue)
+        )
+
+    # 3. 主循环：从 audio_queue 读取音频并 yield
+    try:
+        while True:
+            queue_item = await audio_queue.get()
+
+            if queue_item is None:
+                break
+
+            text = None
+            if isinstance(queue_item, tuple):
+                text, audio_data = queue_item
+            else:
+                audio_data = queue_item
+
+            if not first_chunk_received:
+                # 记录首帧延迟（从开始处理到收到第一个音频块）
+                tts_first_frame_time = time.time() - tts_start_time
+                first_chunk_received = True
+
+            # 将音频数据封装为 MessageChain
+            import base64
+
+            audio_b64 = base64.b64encode(audio_data).decode("utf-8")
+            comps: list[BaseMessageComponent] = [Plain(audio_b64)]
+            if text:
+                comps.append(Json(data={"text": text}))
+            chain = MessageChain(chain=comps, type="audio_chunk")
+            yield chain
+
+    except Exception as e:
+        logger.error(f"[Live Agent] 运行时发生错误: {e}", exc_info=True)
+    finally:
+        # 清理任务
+        if not feeder_task.done():
+            feeder_task.cancel()
+        if not tts_task.done():
+            tts_task.cancel()
+
+        # 确保队列被消费
+        pass
+
+    tts_end_time = time.time()
+
+    # 发送 TTS 统计信息
+    try:
+        astr_event = agent_runner.run_context.context.event
+        if astr_event.get_platform_name() == "webchat":
+            tts_duration = tts_end_time - tts_start_time
+            await astr_event.send(
+                MessageChain(
+                    type="tts_stats",
+                    chain=[
+                        Json(
+                            data={
+                                "tts_total_time": tts_duration,
+                                "tts_first_frame_time": tts_first_frame_time,
+                                "tts": tts_provider.meta().type,
+                                "chat_model": agent_runner.provider.get_model(),
+                            }
+                        )
+                    ],
+                )
+            )
+    except Exception as e:
+        logger.error(f"发送 TTS 统计信息失败: {e}")
+
+
+async def _run_agent_feeder(
+    agent_runner: AgentRunner,
+    text_queue: asyncio.Queue,
+    max_step: int,
+    show_tool_use: bool,
+    show_tool_call_result: bool,
+    show_reasoning: bool,
+) -> None:
+    """运行 Agent 并将文本输出分句放入队列"""
+    buffer = ""
+    try:
+        async for chain in run_agent(
+            agent_runner,
+            max_step=max_step,
+            show_tool_use=show_tool_use,
+            show_tool_call_result=show_tool_call_result,
+            stream_to_general=False,
+            show_reasoning=show_reasoning,
+        ):
+            if chain is None:
+                continue
+
+            # 提取文本
+            text = chain.get_plain_text()
+            if text:
+                buffer += text
+
+                # 分句逻辑：匹配标点符号
+                # r"([.。!！?？\n]+)" 会保留分隔符
+                parts = re.split(r"([.。!！?？\n]+)", buffer)
+
+                if len(parts) > 1:
+                    # 处理完整的句子
+                    # range step 2 因为 split 后是 [text, delim, text, delim, ...]
+                    temp_buffer = ""
+                    for i in range(0, len(parts) - 1, 2):
+                        sentence = parts[i]
+                        delim = parts[i + 1]
+                        full_sentence = sentence + delim
+                        temp_buffer += full_sentence
+
+                        if len(temp_buffer) >= 10:
+                            if temp_buffer.strip():
+                                logger.info(f"[Live Agent Feeder] 分句: {temp_buffer}")
+                                await text_queue.put(temp_buffer)
+                            temp_buffer = ""
+
+                    # 更新 buffer 为剩余部分
+                    buffer = temp_buffer + parts[-1]
+
+        # 处理剩余 buffer
+        if buffer.strip():
+            await text_queue.put(buffer)
+
+    except Exception as e:
+        logger.error(f"[Live Agent Feeder] Error: {e}", exc_info=True)
+    finally:
+        # 发送结束信号
+        await text_queue.put(None)
+
+
+async def _safe_tts_stream_wrapper(
+    tts_provider: TTSProvider,
+    text_queue: asyncio.Queue[str | None],
+    audio_queue: "asyncio.Queue[bytes | tuple[str, bytes] | None]",
+) -> None:
+    """包装原生流式 TTS 确保异常处理和队列关闭"""
+    try:
+        await tts_provider.get_audio_stream(text_queue, audio_queue)
+    except Exception as e:
+        logger.error(f"[Live TTS Stream] Error: {e}", exc_info=True)
+    finally:
+        await audio_queue.put(None)
+
+
+async def _simulated_stream_tts(
+    tts_provider: TTSProvider,
+    text_queue: asyncio.Queue[str | None],
+    audio_queue: "asyncio.Queue[bytes | tuple[str, bytes] | None]",
+) -> None:
+    """模拟流式 TTS 分句生成音频"""
+    try:
+        while True:
+            text = await text_queue.get()
+            if text is None:
+                break
+
+            try:
+                audio_path = await tts_provider.get_audio(text)
+
+                if audio_path:
+                    with open(audio_path, "rb") as f:
+                        audio_data = f.read()
+                    await audio_queue.put((text, audio_data))
+            except Exception as e:
+                logger.error(
+                    f"[Live TTS Simulated] Error processing text '{text[:20]}...': {e}"
+                )
+                # 继续处理下一句
+
+    except Exception as e:
+        logger.error(f"[Live TTS Simulated] Critical Error: {e}", exc_info=True)
+    finally:
+        await audio_queue.put(None)
@@ -1,26 +1,122 @@
 import asyncio
 import inspect
+import json
 import traceback
 import typing as T
+import uuid
+from collections.abc import Sequence
+from collections.abc import Set as AbstractSet

 import mcp

 from astrbot import logger
 from astrbot.core.agent.handoff import HandoffTool
 from astrbot.core.agent.mcp_client import MCPTool
+from astrbot.core.agent.message import Message
 from astrbot.core.agent.run_context import ContextWrapper
 from astrbot.core.agent.tool import FunctionTool, ToolSet
 from astrbot.core.agent.tool_executor import BaseFunctionToolExecutor
 from astrbot.core.astr_agent_context import AstrAgentContext
+from astrbot.core.astr_main_agent_resources import (
+    BACKGROUND_TASK_RESULT_WOKE_SYSTEM_PROMPT,
+    EXECUTE_SHELL_TOOL,
+    FILE_DOWNLOAD_TOOL,
+    FILE_UPLOAD_TOOL,
+    LOCAL_EXECUTE_SHELL_TOOL,
+    LOCAL_PYTHON_TOOL,
+    PYTHON_TOOL,
+    SEND_MESSAGE_TO_USER_TOOL,
+)
+from astrbot.core.cron.events import CronMessageEvent
+from astrbot.core.message.components import Image
 from astrbot.core.message.message_event_result import (
    CommandResult,
    MessageChain,
    MessageEventResult,
 )
+from astrbot.core.platform.message_session import MessageSession
+from astrbot.core.provider.entites import ProviderRequest
 from astrbot.core.provider.register import llm_tools
+from astrbot.core.utils.astrbot_path import get_astrbot_temp_path
+from astrbot.core.utils.history_saver import persist_agent_history
+from astrbot.core.utils.image_ref_utils import is_supported_image_ref
+from astrbot.core.utils.string_utils import normalize_and_dedupe_strings


 class FunctionToolExecutor(BaseFunctionToolExecutor[AstrAgentContext]):
+    @classmethod
+    def _collect_image_urls_from_args(cls, image_urls_raw: T.Any) -> list[str]:
+        if image_urls_raw is None:
+            return []
+
+        if isinstance(image_urls_raw, str):
+            return [image_urls_raw]
+
+        if isinstance(image_urls_raw, (Sequence, AbstractSet)) and not isinstance(
+            image_urls_raw, (str, bytes, bytearray)
+        ):
+            return [item for item in image_urls_raw if isinstance(item, str)]
+
+        logger.debug(
+            "Unsupported image_urls type in handoff tool args: %s",
+            type(image_urls_raw).__name__,
+        )
+        return []
+
+    @classmethod
+    async def _collect_image_urls_from_message(
+        cls, run_context: ContextWrapper[AstrAgentContext]
+    ) -> list[str]:
+        urls: list[str] = []
+        event = getattr(run_context.context, "event", None)
+        message_obj = getattr(event, "message_obj", None)
+        message = getattr(message_obj, "message", None)
+        if message:
+            for idx, component in enumerate(message):
+                if not isinstance(component, Image):
+                    continue
+                try:
+                    path = await component.convert_to_file_path()
+                    if path:
+                        urls.append(path)
+                except Exception as e:
+                    logger.error(
+                        "Failed to convert handoff image component at index %d: %s",
+                        idx,
+                        e,
+                        exc_info=True,
+                    )
+        return urls
+
+    @classmethod
+    async def _collect_handoff_image_urls(
+        cls,
+        run_context: ContextWrapper[AstrAgentContext],
+        image_urls_raw: T.Any,
+    ) -> list[str]:
+        candidates: list[str] = []
+        candidates.extend(cls._collect_image_urls_from_args(image_urls_raw))
+        candidates.extend(await cls._collect_image_urls_from_message(run_context))
+
+        normalized = normalize_and_dedupe_strings(candidates)
+        extensionless_local_roots = (get_astrbot_temp_path(),)
+        sanitized = [
+            item
+            for item in normalized
+            if is_supported_image_ref(
+                item,
+                allow_extensionless_existing_local_file=True,
+                extensionless_local_roots=extensionless_local_roots,
+            )
+        ]
+        dropped_count = len(normalized) - len(sanitized)
+        if dropped_count > 0:
+            logger.debug(
+                "Dropped %d invalid image_urls entries in handoff image inputs.",
+                dropped_count,
+            )
+        return sanitized
+
    @classmethod
    async def execute(cls, tool, run_context, **tool_args):
        """执行函数调用。
@@ -34,6 +130,13 @@ class FunctionToolExecutor(BaseFunctionToolExecutor[AstrAgentContext]):

        """
        if isinstance(tool, HandoffTool):
+            is_bg = tool_args.pop("background_task", False)
+            if is_bg:
+                async for r in cls._execute_handoff_background(
+                    tool, run_context, **tool_args
+                ):
+                    yield r
+                return
            async for r in cls._execute_handoff(tool, run_context, **tool_args):
                yield r
            return
@@ -43,56 +146,415 @@ class FunctionToolExecutor(BaseFunctionToolExecutor[AstrAgentContext]):
                yield r
            return

+        elif tool.is_background_task:
+            task_id = uuid.uuid4().hex
+
+            async def _run_in_background() -> None:
+                try:
+                    await cls._execute_background(
+                        tool=tool,
+                        run_context=run_context,
+                        task_id=task_id,
+                        **tool_args,
+                    )
+                except Exception as e:  # noqa: BLE001
+                    logger.error(
+                        f"Background task {task_id} failed: {e!s}",
+                        exc_info=True,
+                    )
+
+            asyncio.create_task(_run_in_background())
+            text_content = mcp.types.TextContent(
+                type="text",
+                text=f"Background task submitted. task_id={task_id}",
+            )
+            yield mcp.types.CallToolResult(content=[text_content])
+
+            return
        else:
            async for r in cls._execute_local(tool, run_context, **tool_args):
                yield r
            return

+    @classmethod
+    def _get_runtime_computer_tools(cls, runtime: str) -> dict[str, FunctionTool]:
+        if runtime == "sandbox":
+            return {
+                EXECUTE_SHELL_TOOL.name: EXECUTE_SHELL_TOOL,
+                PYTHON_TOOL.name: PYTHON_TOOL,
+                FILE_UPLOAD_TOOL.name: FILE_UPLOAD_TOOL,
+                FILE_DOWNLOAD_TOOL.name: FILE_DOWNLOAD_TOOL,
+            }
+        if runtime == "local":
+            return {
+                LOCAL_EXECUTE_SHELL_TOOL.name: LOCAL_EXECUTE_SHELL_TOOL,
+                LOCAL_PYTHON_TOOL.name: LOCAL_PYTHON_TOOL,
+            }
+        return {}
+
+    @classmethod
+    def _build_handoff_toolset(
+        cls,
+        run_context: ContextWrapper[AstrAgentContext],
+        tools: list[str | FunctionTool] | None,
+    ) -> ToolSet | None:
+        ctx = run_context.context.context
+        event = run_context.context.event
+        cfg = ctx.get_config(umo=event.unified_msg_origin)
+        provider_settings = cfg.get("provider_settings", {})
+        runtime = str(provider_settings.get("computer_use_runtime", "local"))
+        runtime_computer_tools = cls._get_runtime_computer_tools(runtime)
+
+        # Keep persona semantics aligned with the main agent: tools=None means
+        # "all tools", including runtime computer-use tools.
+        if tools is None:
+            toolset = ToolSet()
+            for registered_tool in llm_tools.func_list:
+                if isinstance(registered_tool, HandoffTool):
+                    continue
+                if registered_tool.active:
+                    toolset.add_tool(registered_tool)
+            for runtime_tool in runtime_computer_tools.values():
+                toolset.add_tool(runtime_tool)
+            return None if toolset.empty() else toolset
+
+        if not tools:
+            return None
+
+        toolset = ToolSet()
+        for tool_name_or_obj in tools:
+            if isinstance(tool_name_or_obj, str):
+                registered_tool = llm_tools.get_func(tool_name_or_obj)
+                if registered_tool and registered_tool.active:
+                    toolset.add_tool(registered_tool)
+                    continue
+                runtime_tool = runtime_computer_tools.get(tool_name_or_obj)
+                if runtime_tool:
+                    toolset.add_tool(runtime_tool)
+            elif isinstance(tool_name_or_obj, FunctionTool):
+                toolset.add_tool(tool_name_or_obj)
+        return None if toolset.empty() else toolset
+
    @classmethod
    async def _execute_handoff(
        cls,
        tool: HandoffTool,
        run_context: ContextWrapper[AstrAgentContext],
-        **tool_args,
+        *,
+        image_urls_prepared: bool = False,
+        **tool_args: T.Any,
    ):
+        tool_args = dict(tool_args)
        input_ = tool_args.get("input")
-
-        # make toolset for the agent
-        tools = tool.agent.tools
-        if tools:
-            toolset = ToolSet()
-            for t in tools:
-                if isinstance(t, str):
-                    _t = llm_tools.get_func(t)
-                    if _t:
-                        toolset.add_tool(_t)
-                elif isinstance(t, FunctionTool):
-                    toolset.add_tool(t)
+        if image_urls_prepared:
+            prepared_image_urls = tool_args.get("image_urls")
+            if isinstance(prepared_image_urls, list):
+                image_urls = prepared_image_urls
+            else:
+                logger.debug(
+                    "Expected prepared handoff image_urls as list[str], got %s.",
+                    type(prepared_image_urls).__name__,
+                )
+                image_urls = []
        else:
-            toolset = None
+            image_urls = await cls._collect_handoff_image_urls(
+                run_context,
+                tool_args.get("image_urls"),
+            )
+        tool_args["image_urls"] = image_urls
+
+        # Build handoff toolset from registered tools plus runtime computer tools.
+        toolset = cls._build_handoff_toolset(run_context, tool.agent.tools)

        ctx = run_context.context.context
        event = run_context.context.event
        umo = event.unified_msg_origin
-        prov_id = await ctx.get_current_chat_provider_id(umo)
+
+        # Use per-subagent provider override if configured; otherwise fall back
+        # to the current/default provider resolution.
+        prov_id = getattr(
+            tool, "provider_id", None
+        ) or await ctx.get_current_chat_provider_id(umo)
+
+        # prepare begin dialogs
+        contexts = None
+        dialogs = tool.agent.begin_dialogs
+        if dialogs:
+            contexts = []
+            for dialog in dialogs:
+                try:
+                    contexts.append(
+                        dialog
+                        if isinstance(dialog, Message)
+                        else Message.model_validate(dialog)
+                    )
+                except Exception:
+                    continue
+
+        prov_settings: dict = ctx.get_config(umo=umo).get("provider_settings", {})
+        agent_max_step = int(prov_settings.get("max_agent_step", 30))
+        stream = prov_settings.get("streaming_response", False)
        llm_resp = await ctx.tool_loop_agent(
            event=event,
            chat_provider_id=prov_id,
            prompt=input_,
+            image_urls=image_urls,
            system_prompt=tool.agent.instructions,
            tools=toolset,
-            max_steps=30,
-            run_hooks=tool.agent.run_hooks,
+            contexts=contexts,
+            max_steps=agent_max_step,
+            stream=stream,
        )
        yield mcp.types.CallToolResult(
            content=[mcp.types.TextContent(type="text", text=llm_resp.completion_text)]
        )

+    @classmethod
+    async def _execute_handoff_background(
+        cls,
+        tool: HandoffTool,
+        run_context: ContextWrapper[AstrAgentContext],
+        **tool_args,
+    ):
+        """Execute a handoff as a background task.
+
+        Immediately yields a success response with a task_id, then runs
+        the subagent asynchronously.  When the subagent finishes, a
+        ``CronMessageEvent`` is created so the main LLM can inform the
+        user of the result – the same pattern used by
+        ``_execute_background`` for regular background tasks.
+        """
+        task_id = uuid.uuid4().hex
+
+        async def _run_handoff_in_background() -> None:
+            try:
+                await cls._do_handoff_background(
+                    tool=tool,
+                    run_context=run_context,
+                    task_id=task_id,
+                    **tool_args,
+                )
+            except Exception as e:  # noqa: BLE001
+                logger.error(
+                    f"Background handoff {task_id} ({tool.name}) failed: {e!s}",
+                    exc_info=True,
+                )
+
+        asyncio.create_task(_run_handoff_in_background())
+
+        text_content = mcp.types.TextContent(
+            type="text",
+            text=(
+                f"Background task dedicated to subagent '{tool.agent.name}' submitted. task_id={task_id}. "
+                f"The subagent '{tool.agent.name}' is working on the task on hehalf you. "
+                f"You will be notified when it finishes."
+            ),
+        )
+        yield mcp.types.CallToolResult(content=[text_content])
+
+    @classmethod
+    async def _do_handoff_background(
+        cls,
+        tool: HandoffTool,
+        run_context: ContextWrapper[AstrAgentContext],
+        task_id: str,
+        **tool_args,
+    ) -> None:
+        """Run the subagent handoff and, on completion, wake the main agent."""
+        result_text = ""
+        tool_args = dict(tool_args)
+        tool_args["image_urls"] = await cls._collect_handoff_image_urls(
+            run_context,
+            tool_args.get("image_urls"),
+        )
+        try:
+            async for r in cls._execute_handoff(
+                tool,
+                run_context,
+                image_urls_prepared=True,
+                **tool_args,
+            ):
+                if isinstance(r, mcp.types.CallToolResult):
+                    for content in r.content:
+                        if isinstance(content, mcp.types.TextContent):
+                            result_text += content.text + "\n"
+        except Exception as e:
+            result_text = (
+                f"error: Background task execution failed, internal error: {e!s}"
+            )
+
+        event = run_context.context.event
+
+        await cls._wake_main_agent_for_background_result(
+            run_context=run_context,
+            task_id=task_id,
+            tool_name=tool.name,
+            result_text=result_text,
+            tool_args=tool_args,
+            note=(
+                event.get_extra("background_note")
+                or f"Background task for subagent '{tool.agent.name}' finished."
+            ),
+            summary_name=f"Dedicated to subagent `{tool.agent.name}`",
+            extra_result_fields={"subagent_name": tool.agent.name},
+        )
+
+    @classmethod
+    async def _execute_background(
+        cls,
+        tool: FunctionTool,
+        run_context: ContextWrapper[AstrAgentContext],
+        task_id: str,
+        **tool_args,
+    ) -> None:
+        # run the tool
+        result_text = ""
+        try:
+            async for r in cls._execute_local(
+                tool, run_context, tool_call_timeout=3600, **tool_args
+            ):
+                # collect results, currently we just collect the text results
+                if isinstance(r, mcp.types.CallToolResult):
+                    result_text = ""
+                    for content in r.content:
+                        if isinstance(content, mcp.types.TextContent):
+                            result_text += content.text + "\n"
+        except Exception as e:
+            result_text = (
+                f"error: Background task execution failed, internal error: {e!s}"
+            )
+
+        event = run_context.context.event
+
+        await cls._wake_main_agent_for_background_result(
+            run_context=run_context,
+            task_id=task_id,
+            tool_name=tool.name,
+            result_text=result_text,
+            tool_args=tool_args,
+            note=(
+                event.get_extra("background_note")
+                or f"Background task {tool.name} finished."
+            ),
+            summary_name=tool.name,
+        )
+
+    @classmethod
+    async def _wake_main_agent_for_background_result(
+        cls,
+        run_context: ContextWrapper[AstrAgentContext],
+        *,
+        task_id: str,
+        tool_name: str,
+        result_text: str,
+        tool_args: dict[str, T.Any],
+        note: str,
+        summary_name: str,
+        extra_result_fields: dict[str, T.Any] | None = None,
+    ) -> None:
+        from astrbot.core.astr_main_agent import (
+            MainAgentBuildConfig,
+            _get_session_conv,
+            build_main_agent,
+        )
+
+        event = run_context.context.event
+        ctx = run_context.context.context
+
+        task_result = {
+            "task_id": task_id,
+            "tool_name": tool_name,
+            "result": result_text or "",
+            "tool_args": tool_args,
+        }
+        if extra_result_fields:
+            task_result.update(extra_result_fields)
+        extras = {"background_task_result": task_result}
+
+        session = MessageSession.from_str(event.unified_msg_origin)
+        cron_event = CronMessageEvent(
+            context=ctx,
+            session=session,
+            message=note,
+            extras=extras,
+            message_type=session.message_type,
+        )
+        cron_event.role = event.role
+        config = MainAgentBuildConfig(
+            tool_call_timeout=3600,
+            streaming_response=ctx.get_config()
+            .get("provider_settings", {})
+            .get("stream", False),
+        )
+
+        req = ProviderRequest()
+        conv = await _get_session_conv(event=cron_event, plugin_context=ctx)
+        req.conversation = conv
+        context = json.loads(conv.history)
+        if context:
+            req.contexts = context
+            context_dump = req._print_friendly_context()
+            req.contexts = []
+            req.system_prompt += (
+                "\n\nBellow is you and user previous conversation history:\n"
+                f"{context_dump}"
+            )
+
+        bg = json.dumps(extras["background_task_result"], ensure_ascii=False)
+        req.system_prompt += BACKGROUND_TASK_RESULT_WOKE_SYSTEM_PROMPT.format(
+            background_task_result=bg
+        )
+        req.prompt = (
+            "Proceed according to your system instructions. "
+            "Output using same language as previous conversation. "
+            "If you need to deliver the result to the user immediately, "
+            "you MUST use `send_message_to_user` tool to send the message directly to the user, "
+            "otherwise the user will not see the result. "
+            "After completing your task, summarize and output your actions and results. "
+        )
+        if not req.func_tool:
+            req.func_tool = ToolSet()
+        req.func_tool.add_tool(SEND_MESSAGE_TO_USER_TOOL)
+
+        result = await build_main_agent(
+            event=cron_event, plugin_context=ctx, config=config, req=req
+        )
+        if not result:
+            logger.error(f"Failed to build main agent for background task {tool_name}.")
+            return
+
+        runner = result.agent_runner
+        async for _ in runner.step_until_done(30):
+            # agent will send message to user via using tools
+            pass
+        llm_resp = runner.get_final_llm_resp()
+        task_meta = extras.get("background_task_result", {})
+        summary_note = (
+            f"[BackgroundTask] {summary_name} "
+            f"(task_id={task_meta.get('task_id', task_id)}) finished. "
+            f"Result: {task_meta.get('result') or result_text or 'no content'}"
+        )
+        if llm_resp and llm_resp.completion_text:
+            summary_note += (
+                f"I finished the task, here is the result: {llm_resp.completion_text}"
+            )
+        await persist_agent_history(
+            ctx.conversation_manager,
+            event=cron_event,
+            req=req,
+            summary_note=summary_note,
+        )
+        if not llm_resp:
+            logger.warning("background task agent got no response")
+            return
+
    @classmethod
    async def _execute_local(
        cls,
        tool: FunctionTool,
        run_context: ContextWrapper[AstrAgentContext],
+        *,
+        tool_call_timeout: int | None = None,
        **tool_args,
    ):
        event = run_context.context.event
@@ -133,7 +595,7 @@ class FunctionToolExecutor(BaseFunctionToolExecutor[AstrAgentContext]):
            try:
                resp = await asyncio.wait_for(
                    anext(wrapper),
-                    timeout=run_context.tool_call_timeout,
+                    timeout=tool_call_timeout or run_context.tool_call_timeout,
                )
                if resp is not None:
                    if isinstance(resp, mcp.types.CallToolResult):
@@ -165,7 +627,7 @@ class FunctionToolExecutor(BaseFunctionToolExecutor[AstrAgentContext]):
                    yield None
            except asyncio.TimeoutError:
                raise Exception(
-                    f"tool {tool.name} execution timeout after {run_context.tool_call_timeout} seconds.",
+                    f"tool {tool.name} execution timeout after {tool_call_timeout or run_context.tool_call_timeout} seconds.",
                )
            except StopAsyncIteration:
                break
@@ -185,7 +647,11 @@ class FunctionToolExecutor(BaseFunctionToolExecutor[AstrAgentContext]):

 async def call_local_llm_tool(
    context: ContextWrapper[AstrAgentContext],
-    handler: T.Callable[..., T.Awaitable[T.Any]],
+    handler: T.Callable[
+        ...,
+        T.Awaitable[MessageEventResult | mcp.types.CallToolResult | str | None]
+        | T.AsyncGenerator[MessageEventResult | CommandResult | str | None, None],
+    ],
    method_name: str,
    *args,
    **kwargs,
@@ -205,12 +671,42 @@ async def call_local_llm_tool(
        else:
            raise ValueError(f"未知的方法名: {method_name}")
    except ValueError as e:
-        logger.error(f"调用本地 LLM 工具时出错: {e}", exc_info=True)
-    except TypeError:
-        logger.error("处理函数参数不匹配，请检查 handler 的定义。", exc_info=True)
+        raise Exception(f"Tool execution ValueError: {e}") from e
+    except TypeError as e:
+        # 获取函数的签名（包括类型），除了第一个 event/context 参数。
+        try:
+            sig = inspect.signature(handler)
+            params = list(sig.parameters.values())
+            # 跳过第一个参数（event 或 context）
+            if params:
+                params = params[1:]
+
+            param_strs = []
+            for param in params:
+                param_str = param.name
+                if param.annotation != inspect.Parameter.empty:
+                    # 获取类型注解的字符串表示
+                    if isinstance(param.annotation, type):
+                        type_str = param.annotation.__name__
+                    else:
+                        type_str = str(param.annotation)
+                    param_str += f": {type_str}"
+                if param.default != inspect.Parameter.empty:
+                    param_str += f" = {param.default!r}"
+                param_strs.append(param_str)
+
+            handler_param_str = (
+                ", ".join(param_strs) if param_strs else "(no additional parameters)"
+            )
+        except Exception:
+            handler_param_str = "(unable to inspect signature)"
+
+        raise Exception(
+            f"Tool handler parameter mismatch, please check the handler definition. Handler parameters: {handler_param_str}"
+        ) from e
    except Exception as e:
        trace_ = traceback.format_exc()
-        logger.error(f"调用本地 LLM 工具时出错: {e}\n{trace_}")
+        raise Exception(f"Tool execution error: {e}. Traceback: {trace_}") from e

    if not ready_to_call:
        return
@@ -222,7 +718,7 @@ async def call_local_llm_tool(
                # 这里逐步执行异步生成器, 对于每个 yield 返回的 ret, 执行下面的代码
                # 返回值只能是 MessageEventResult 或者 None（无返回值）
                _has_yielded = True
-                if isinstance(ret, (MessageEventResult, CommandResult)):
+                if isinstance(ret, MessageEventResult | CommandResult):
                    # 如果返回值是 MessageEventResult, 设置结果并继续
                    event.set_result(ret)
                    yield
@@ -239,7 +735,7 @@ async def call_local_llm_tool(
    elif inspect.iscoroutine(ready_to_call):
        # 如果只是一个协程, 直接执行
        ret = await ready_to_call
-        if isinstance(ret, (MessageEventResult, CommandResult)):
+        if isinstance(ret, MessageEventResult | CommandResult):
            event.set_result(ret)
            yield
        else:
--- a/Show More
+++ b/Show More
@@ -1 +1 @@
 .10
 .12