stage

* feat: chatui-project

* fix: remove console log from getProjects function

.github/ISSUE_TEMPLATE/bug-report.yml

@@ -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！"

.github/PULL_REQUEST_TEMPLATE.md

@@ -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**.

.github/copilot-instructions.md

@@ -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
 

.github/workflows/auto_release.yml

@@ -13,7 +13,7 @@ jobs:
       contents: write
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v5
+        uses: actions/checkout@v6
 
       - name: Dashboard Build
         run: |
@@ -70,7 +70,7 @@ jobs:
     needs: build-and-publish-to-github-release
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v5
+        uses: actions/checkout@v6
 
       - name: Set up Python
         uses: actions/setup-python@v6

.github/workflows/code-format.yml

@@ -12,7 +12,7 @@ jobs:
     
     steps:
     - name: Checkout code
-      uses: actions/checkout@v5
+      uses: actions/checkout@v6
       
     - name: Set up Python
       uses: actions/setup-python@v6

.github/workflows/codeql.yml

@@ -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

.github/workflows/coverage_test.yml

@@ -17,7 +17,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Checkout
-        uses: actions/checkout@v5
+        uses: actions/checkout@v6
         with:
           fetch-depth: 0
 

.github/workflows/dashboard_ci.yml

@@ -11,7 +11,7 @@ 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
@@ -36,7 +36,7 @@ jobs:
           zip -r dist.zip dist
 
       - name: Archive production artifacts
-        uses: actions/upload-artifact@v5
+        uses: actions/upload-artifact@v6
         with:
           name: dist-without-markdown
           path: |

.github/workflows/docker-image.yml

@@ -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: soulter
+      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@v3
+
+      - name: Set Docker Buildx
+        uses: docker/setup-buildx-action@v3
+
+      - name: Log in to DockerHub
+        uses: docker/login-action@v3
+        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@v3
+        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@v6
+        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: soulter
+      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: |
@@ -67,23 +175,24 @@ jobs:
           password: ${{ secrets.DOCKER_HUB_PASSWORD }}
 
       - name: Login to GitHub Container Registry
+        if: env.HAS_GHCR_TOKEN == 'true'
         uses: docker/login-action@v3
         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
+      - name: Build and Push Release Image
         uses: docker/build-push-action@v6
         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"

.github/workflows/smoke_test.yml

@@ -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

.github/workflows/stale.yml

@@ -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 }}

.gitignore

@@ -24,9 +24,9 @@ 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
@@ -34,6 +34,7 @@ dashboard/node_modules/
 dashboard/dist/
 package-lock.json
 package.json
+yarn.lock
 
 # Operating System
 **/.DS_Store
@@ -47,3 +48,5 @@ astrbot.lock
 chroma
 venv/*
 pytest.ini
+AGENTS.md
+IFLOW.md

CONTRIBUTING.md

@@ -0,0 +1,90 @@
+# 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。
+
+
+## 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 .
+```

EULA.md

@@ -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.

README.md

@@ -1,10 +1,13 @@
 ![AstrBot-Logo-Simplified](https://github.com/user-attachments/assets/ffd99b6b-3272-4682-beaa-6fe74250f7d9)
 
-</p>
-
 <div align="center">
 
-<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://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>
 
 <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>
@@ -14,35 +17,38 @@
 <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=%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://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://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>
 </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 是一个开源的一站式 Agent 聊天机器人平台，可接入主流即时通讯软件，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生产可用的 AI 应用。
+
+![521771166-00782c4c-4437-4d97-aabc-605e3738da5c (1)](https://github.com/user-attachments/assets/61e7b505-f7db-41aa-a75f-4ef8f079b8ba)
 
 ## 主要功能
 
-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。
+1. 💯 免费 & 开源。
+1. ✨ AI 大模型对话，多模态，Agent，MCP，知识库，人格设定。
+2. 🤖 支持接入 Dify、阿里云百炼、Coze 等智能体平台。
+2. 🌐 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)。
+3. 📦 插件扩展，已有近 800 个插件可一键安装。
+5. 💻 WebUI 支持。
+6. 🌐 国际化（i18n）支持。
 
-## 部署方式
+## 快速开始
 
 #### Docker 部署(推荐 🥳)
 
@@ -50,6 +56,12 @@ AstrBot 是一个开源的一站式 Agent 聊天机器人平台及开发框架
 
 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) 。
 
+#### uv 部署
+
+```bash
+uvx astrbot
+```
+
 #### 宝塔面板部署
 
 AstrBot 与宝塔面板合作，已上架至宝塔面板。
@@ -101,24 +113,6 @@ uv run main.py
 
 或者请参阅官方文档 [通过源码部署 AstrBot](https://astrbot.app/deploy/astrbot/cli.html) 。
 
-## 🌍 社区
-
-### QQ 群组
-
-- 1 群：322154837
-- 3 群：630166526
-- 5 群：822130018
-- 6 群：753075035
-- 开发者群：975206796
-
-### Telegram 群组
-
-<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>
-
-### Discord 群组
-
-<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
 
 **官方维护**
@@ -138,10 +132,9 @@ uv run main.py
 
 **社区维护**
 
+- [Matrix](https://github.com/stevessr/astrbot_plugin_matrix_adapter)
 - [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)
 
 ## 支持的模型服务
 
@@ -205,6 +198,26 @@ pip install pre-commit
 pre-commit install
 ```
 
+## 🌍 社区
+
+### QQ 群组
+
+- 1 群：322154837
+- 3 群：630166526
+- 5 群：822130018
+- 6 群：753075035
+- 7 群：743746109
+- 8 群：1030353265
+- 开发者群：975206796
+
+### Telegram 群组
+
+<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>
+
+### Discord 群组
+
+<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 ❤️
@@ -230,4 +243,10 @@ pre-commit install
 
 </details>
 
+<div align="center">
+
 _私は、高性能ですから!_
+
+<img src="https://files.astrbot.app/watashiwa-koseino-desukara.gif" width="100"/>
+</div
+

README_en.md

@@ -1,182 +1,246 @@
-<p align="center">
-    
-![6e1279651f16d7fdf4727558b72bbaf1](https://github.com/user-attachments/assets/ead4c551-fc3c-48f7-a6f7-afbfdb820512)
+![AstrBot-Logo-Simplified](https://github.com/user-attachments/assets/ffd99b6b-3272-4682-beaa-6fe74250f7d9)
 
 </p>
 
 <div align="center">
 
-_✨ Easy-to-use Multi-platform LLM Chatbot & Development Framework ✨_
+<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"/></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>
+<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 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.
+<br>
 
-## ✨ Key Features
+<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=%20plugins&style=for-the-badge&label=Marketplace&cacheSeconds=3600">
+</div>
 
-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.
+<br>
 
-> [!TIP]
-> Dashboard Demo: [https://demo.astrbot.app/](https://demo.astrbot.app/)  
-> Username: `astrbot`, Password: `astrbot` (LLM not configured for chat page)
+<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README.md">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_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>
 
-## ✨ Deployment
+<a href="https://astrbot.app/">Documentation</a> ｜
+<a href="https://blog.astrbot.app/">Blog</a> ｜
+<a href="https://astrbot.featurebase.app/roadmap">Roadmap</a> ｜
+<a href="https://github.com/AstrBotDevs/AstrBot/issues">Issue Tracker</a>
+</div>
 
-#### Docker Deployment
+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.
 
-See docs: [Deploy with Docker](https://astrbot.app/deploy/astrbot/docker.html#docker-deployment)
+<img width="1776" height="1080" alt="image" src="https://github.com/user-attachments/assets/00782c4c-4437-4d97-aabc-605e3738da5c" />
 
-#### Windows Installer
+## Key Features
 
-Requires Python (>3.10). See docs: [Windows Installer Guide](https://astrbot.app/deploy/astrbot/windows.html)
+1. 💯 Free & Open Source.
+2. ✨ AI LLM Conversations, Multimodal, Agent, MCP, Knowledge Base, Persona Settings.
+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 nearly 800 plugins available for one-click installation.
+6. 💻 WebUI Support.
+7. 🌐 Internationalization (i18n) Support.
 
-#### Replit Deployment
+## Quick Start
+
+#### Docker Deployment (Recommended 🥳)
+
+We recommend deploying AstrBot using Docker or 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).
+
+#### uv Deployment
+
+```bash
+uvx astrbot
+```
+
+#### BT-Panel Deployment
+
+AstrBot has partnered with BT-Panel and is now available in their marketplace.
+
+Please refer to the official documentation: [BT-Panel Deployment](https://astrbot.app/deploy/astrbot/btpanel.html).
+
+#### 1Panel Deployment
+
+AstrBot has been officially listed on the 1Panel marketplace.
+
+Please refer to the official documentation: [1Panel Deployment](https://astrbot.app/deploy/astrbot/1panel.html).
+
+#### Deploy on RainYun
+
+AstrBot has been officially listed on RainYun's cloud application platform with one-click deployment.
+
+[![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)
+
+#### Deploy on Replit
+
+Community-contributed deployment method.
 
 [![Run on Repl.it](https://repl.it/badge/github/AstrBotDevs/AstrBot)](https://repl.it/github/AstrBotDevs/AstrBot)
 
+#### Windows One-Click Installer
+
+Please refer to the official documentation: [Deploy AstrBot with Windows One-Click Installer](https://astrbot.app/deploy/astrbot/windows.html).
+
 #### CasaOS Deployment
 
-Community-contributed method.  
-See docs: [CasaOS Deployment](https://astrbot.app/deploy/astrbot/casaos.html)
+Community-contributed deployment method.
+
+Please refer to the official documentation: [CasaOS Deployment](https://astrbot.app/deploy/astrbot/casaos.html).
 
 #### Manual Deployment
 
-See docs: [Source Code Deployment](https://astrbot.app/deploy/astrbot/cli.html)
+First, install uv:
 
-## ⚡ Platform Support
+```bash
+pip install uv
+```
 
-| 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             | -                   |
+Install AstrBot via Git Clone:
 
-## Provider Support Status
+```bash
+git clone https://github.com/AstrBotDevs/AstrBot && cd AstrBot
+uv run main.py
+```
 
-| 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                                  |
+Or refer to the official documentation: [Deploy AstrBot from Source](https://astrbot.app/deploy/astrbot/cli.html).
 
-# 🦌 Roadmap
+## Supported Messaging Platforms
 
-> [!TIP]
-> Suggestions welcome via Issues <3
+**Officially Maintained**
 
-- [ ] 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
+- QQ (Official Platform & OneBot)
+- Telegram
+- WeChat Work Application & WeChat Work Intelligent Bot
+- WeChat Customer Service & WeChat Official Accounts
+- Feishu (Lark)
+- DingTalk
+- Slack
+- Discord
+- Satori
+- Misskey
+- WhatsApp (Coming Soon)
+- LINE (Coming Soon)
 
-## ❤️ Contributions
+**Community Maintained**
 
-All Issues/PRs welcome! Simply submit your changes to this project :)
+- [Matrix](https://github.com/stevessr/astrbot_plugin_matrix_adapter)
+- [KOOK](https://github.com/wuyan1003/astrbot_plugin_kook_adapter)
+- [VoceChat](https://github.com/HikariFroya/astrbot_plugin_vocechat)
 
-For major features, please discuss via Issues first.
+## Supported Model Services
 
-## 🌟 Support
+**LLM Services**
 
-- Star this project!
-- Support via [Afdian](https://afdian.com/a/soulter)
-- WeChat support: [QR Code](https://drive.soulter.top/f/pYfA/d903f4fa49a496fda3f16d2be9e023b5.png)
+- OpenAI and Compatible Services
+- Anthropic
+- Google Gemini
+- Moonshot AI
+- Zhipu AI
+- DeepSeek
+- Ollama (Self-hosted)
+- LM Studio (Self-hosted)
+- [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_astrbot&referral_code=FV7DcGowN4hB5UuXKgpE74)
+- [302.AI](https://share.302.ai/rr1M3l)
+- [TokenPony](https://www.tokenpony.cn/3YPyf)
+- [SiliconFlow](https://docs.siliconflow.cn/cn/usecases/use-siliconcloud-in-astrbot)
+- [PPIO Cloud](https://ppio.com/user/register?invited_by=AIOONE)
+- ModelScope
+- OneAPI
 
-## ✨ Demos
+**LLMOps Platforms**
 
-> [!NOTE]
-> Code executor file I/O currently tested with Napcat(QQ)/Lagrange(QQ)
+- Dify
+- Alibaba Cloud Bailian Applications
+- Coze
 
-<div align='center'>
+**Speech-to-Text Services**
 
-<img src="https://github.com/user-attachments/assets/4ee688d9-467d-45c8-99d6-368f9a8a92d8" width="600">
+- OpenAI Whisper
+- SenseVoice
 
-_✨ Docker-based Sandboxed Code Executor (Beta) ✨_
+**Text-to-Speech Services**
 
-<img src="https://github.com/user-attachments/assets/0378f407-6079-4f64-ae4c-e97ab20611d2" height=500>
+- OpenAI TTS
+- Gemini TTS
+- GPT-Sovits-Inference
+- GPT-Sovits
+- FishAudio
+- Edge TTS
+- Alibaba Cloud Bailian TTS
+- Azure TTS
+- Minimax TTS
+- Volcano Engine TTS
 
-_✨ Multimodal Input, Web Search, Text-to-Image ✨_
+## ❤️ Contributing
 
-<img src="https://github.com/user-attachments/assets/8ec12797-e70f-460a-959e-48eca39ca2bb" height=100>
+Issues and Pull Requests are always welcome! Feel free to submit your changes to this project :)
 
-_✨ Natural Language TODO Lists ✨_
+### How to Contribute
 
-<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>
+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.
 
-_✨ Plugin System Showcase ✨_
+### Development Environment
 
-<img src="https://github.com/user-attachments/assets/592a8630-14c7-4e06-b496-9c0386e4f36c" width=600>
+AstrBot uses `ruff` for code formatting and linting.
 
-_✨ Web Dashboard ✨_
+```bash
+git clone https://github.com/AstrBotDevs/AstrBot
+pip install pre-commit
+pre-commit install
+```
 
-![webchat](https://drive.soulter.top/f/vlsA/ezgif-5-fb044b2542.gif)
+## 🌍 Community
 
-_✨ Built-in Web Chat Interface ✨_
+### QQ Groups
 
-</div>
+- Group 1: 322154837
+- Group 3: 630166526
+- Group 5: 822130018
+- Group 6: 753075035
+- Developer Group: 975206796
+
+### Telegram Group
+
+<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>
+
+### 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
+
+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" />
+</a>
+
+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) - The amazing cat framework
 
 ## ⭐ Star History
 
-> [!TIP] 
-> If this project helps you, please give it a star <3
+> [!TIP]
+> 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">
-    
-[![Star History Chart](https://api.star-history.com/svg?repos=AstrBotDevs/AstrBot&type=Date)](https://star-history.com/#AstrBotDevs/AstrBot&Date)
+
+[![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
-    -->
-
+</details>
 
 _私は、高性能ですから!_
-

README_fr.md

@@ -0,0 +1,247 @@
+![AstrBot-Logo-Simplified](https://github.com/user-attachments/assets/ffd99b6b-3272-4682-beaa-6fe74250f7d9)
+
+</p>
+
+<div align="center">
+
+<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?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=%20plugins&style=for-the-badge&label=Marketplace&cacheSeconds=3600">
+</div>
+
+<br>
+
+<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README.md">中文</a> ｜
+<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://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_ru.md">Русский</a>
+
+<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>
+</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.
+
+<img width="1776" height="1080" alt="image" src="https://github.com/user-attachments/assets/00782c4c-4437-4d97-aabc-605e3738da5c" />
+
+## Fonctionnalités principales
+
+1. 💯 Gratuit & Open Source.
+2. ✨ Conversations avec LLM IA, Multimodal, Agent, MCP, Base de connaissances, Paramètres de personnalité.
+3. 🤖 Prise en charge de l'intégration avec Dify, Alibaba Cloud Bailian, Coze et autres plateformes d'agents.
+4. 🌐 Multi-plateforme : QQ, WeChat Work, Feishu, DingTalk, Comptes officiels WeChat, Telegram, Slack, et [plus encore](#plateformes-de-messagerie-prises-en-charge).
+5. 📦 Extensions de plugins avec près de 800 plugins disponibles pour une installation en un clic.
+6. 💻 Support WebUI.
+7. 🌐 Support de l'internationalisation (i18n).
+
+## Démarrage rapide
+
+#### Déploiement Docker (Recommandé 🥳)
+
+Nous recommandons de déployer AstrBot en utilisant Docker ou 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).
+
+#### Déploiement uv
+
+```bash
+uvx astrbot
+```
+
+#### Déploiement BT-Panel
+
+AstrBot s'est associé à BT-Panel et est maintenant disponible sur leur marketplace.
+
+Veuillez consulter la documentation officielle : [Déploiement BT-Panel](https://astrbot.app/deploy/astrbot/btpanel.html).
+
+#### Déploiement 1Panel
+
+AstrBot a été officiellement listé sur le marketplace 1Panel.
+
+Veuillez consulter la documentation officielle : [Déploiement 1Panel](https://astrbot.app/deploy/astrbot/1panel.html).
+
+#### Déployer sur RainYun
+
+AstrBot a été officiellement listé sur la plateforme d'applications cloud de RainYun avec un déploiement en un clic.
+
+[![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)
+
+#### Déployer sur Replit
+
+Méthode de déploiement contribuée par la communauté.
+
+[![Run on Repl.it](https://repl.it/badge/github/AstrBotDevs/AstrBot)](https://repl.it/github/AstrBotDevs/AstrBot)
+
+#### Installateur Windows en un clic
+
+Veuillez consulter la documentation officielle : [Déployer AstrBot avec l'installateur Windows en un clic](https://astrbot.app/deploy/astrbot/windows.html).
+
+#### Déploiement CasaOS
+
+Méthode de déploiement contribuée par la communauté.
+
+Veuillez consulter la documentation officielle : [Déploiement CasaOS](https://astrbot.app/deploy/astrbot/casaos.html).
+
+#### Déploiement manuel
+
+Tout d'abord, installez uv :
+
+```bash
+pip install uv
+```
+
+Installez AstrBot via Git Clone :
+
+```bash
+git clone https://github.com/AstrBotDevs/AstrBot && cd AstrBot
+uv run main.py
+```
+
+Ou consultez la documentation officielle : [Déployer AstrBot depuis les sources](https://astrbot.app/deploy/astrbot/cli.html).
+
+## Plateformes de messagerie prises en charge
+
+**Maintenues officiellement**
+
+- QQ (Plateforme officielle & OneBot)
+- Telegram
+- Application WeChat Work & Bot intelligent WeChat Work
+- Service client WeChat & Comptes officiels WeChat
+- Feishu (Lark)
+- DingTalk
+- Slack
+- Discord
+- Satori
+- Misskey
+- WhatsApp (Bientôt disponible)
+- LINE (Bientôt disponible)
+
+**Maintenues par la communauté**
+
+- [Matrix](https://github.com/stevessr/astrbot_plugin_matrix_adapter)
+- [KOOK](https://github.com/wuyan1003/astrbot_plugin_kook_adapter)
+- [VoceChat](https://github.com/HikariFroya/astrbot_plugin_vocechat)
+
+## Services de modèles pris en charge
+
+**Services LLM**
+
+- OpenAI et services compatibles
+- Anthropic
+- Google Gemini
+- Moonshot AI
+- Zhipu AI
+- DeepSeek
+- Ollama (Auto-hébergé)
+- LM Studio (Auto-hébergé)
+- [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_astrbot&referral_code=FV7DcGowN4hB5UuXKgpE74)
+- [302.AI](https://share.302.ai/rr1M3l)
+- [TokenPony](https://www.tokenpony.cn/3YPyf)
+- [SiliconFlow](https://docs.siliconflow.cn/cn/usecases/use-siliconcloud-in-astrbot)
+- [PPIO Cloud](https://ppio.com/user/register?invited_by=AIOONE)
+- ModelScope
+- OneAPI
+
+**Plateformes LLMOps**
+
+- Dify
+- Applications Alibaba Cloud Bailian
+- Coze
+
+**Services de reconnaissance vocale**
+
+- OpenAI Whisper
+- SenseVoice
+
+**Services de synthèse vocale**
+
+- OpenAI TTS
+- Gemini TTS
+- GPT-Sovits-Inference
+- GPT-Sovits
+- FishAudio
+- Edge TTS
+- Alibaba Cloud Bailian TTS
+- Azure TTS
+- Minimax TTS
+- Volcano Engine TTS
+
+## ❤️ 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 Telegram
+
+<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>
+
+### 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" />
+</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>
+
+</details>
+
+_私は、高性能ですから!_
+

README_ja.md

@@ -1,167 +1,247 @@
-<p align="center">
-
-![6e1279651f16d7fdf4727558b72bbaf1](https://github.com/user-attachments/assets/ead4c551-fc3c-48f7-a6f7-afbfdb820512)
+![AstrBot-Logo-Simplified](https://github.com/user-attachments/assets/ffd99b6b-3272-4682-beaa-6fe74250f7d9)
 
 </p>
 
 <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 ✨_
+<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?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=%E5%80%8B&style=for-the-badge&label=%E3%83%97%E3%83%A9%E3%82%B0%E3%82%A4%E3%83%B3&cacheSeconds=3600">
+</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://github.com/AstrBotDevs/AstrBot/blob/master/README.md">中文</a> ｜
+<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README_en.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>
 
-## ✨ 使用方法
+<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>
+</div>
 
-#### Docker デプロイ
+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。
 
-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。
+<img width="1776" height="1080" alt="image" src="https://github.com/user-attachments/assets/00782c4c-4437-4d97-aabc-605e3738da5c" />
 
-#### Windows ワンクリックインストーラーのデプロイ
+## 主な機能
 
-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。
+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、ナレッジベース、ペルソナ設定。
+3. 🤖 Dify、Alibaba Cloud 百炼、Coze などの Agent プラットフォームとの統合をサポート。
+4. 🌐 マルチプラットフォーム：QQ、WeChat Work、Feishu、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)。
+5. 📦 約800個のプラグインをワンクリックでインストール可能なプラグイン拡張機能。
+6. 💻 WebUI サポート。
+7. 🌐 国際化（i18n）サポート。
 
-#### Replit デプロイ
+## クイックスタート
+
+#### Docker デプロイ（推奨 🥳）
+
+Docker / Docker Compose を使用した AstrBot のデプロイを推奨します。
+
+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。
+
+#### uv デプロイ
+
+```bash
+uvx astrbot
+```
+
+#### 宝塔パネルデプロイ
+
+AstrBot は宝塔パネルと提携し、宝塔パネルに公開されています。
+
+公式ドキュメント [宝塔パネルデプロイ](https://astrbot.app/deploy/astrbot/btpanel.html) をご参照ください。
+
+#### 1Panel デプロイ
+
+AstrBot は 1Panel 公式により 1Panel パネルに公開されています。
+
+公式ドキュメント [1Panel デプロイ](https://astrbot.app/deploy/astrbot/1panel.html) をご参照ください。
+
+#### 雨云でのデプロイ
+
+AstrBot は雨云公式によりクラウドアプリケーションプラットフォームに公開され、ワンクリックでデプロイ可能です。
+
+[![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)
+
+#### Replit でのデプロイ
+
+コミュニティ貢献によるデプロイ方法。
 
 [![Run on Repl.it](https://repl.it/badge/github/AstrBotDevs/AstrBot)](https://repl.it/github/AstrBotDevs/AstrBot)
 
+#### Windows ワンクリックインストーラーデプロイ
+
+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た AstrBot のデプロイ](https://astrbot.app/deploy/astrbot/windows.html) をご参照ください。
+
 #### CasaOS デプロイ
 
-コミュニティが提供するデプロイ方法です。
+コミュニティ貢献によるデプロイ方法。
 
-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。
+公式ドキュメント [CasaOS デプロイ](https://astrbot.app/deploy/astrbot/casaos.html) をご参照ください。
 
 #### 手動デプロイ
 
-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。
+まず uv をインストールします:
 
-## ⚡ メッセージプラットフォームのサポート状況
+```bash
+pip install uv
+```
 
-| 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 | - |
+Git Clone で AstrBot をインストール:
 
-# 🦌 今後のロードマップ
+```bash
+git clone https://github.com/AstrBotDevs/AstrBot && cd AstrBot
+uv run main.py
+```
 
-> [!TIP]
-> Issue でさらに多くの提案を歓迎します <3
+または、公式ドキュメント [ソースコードから AstrBot をデプロイ](https://astrbot.app/deploy/astrbot/cli.html) をご参照ください。
 
-- [ ] 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
+## サポートされているメッセージプラットフォーム
 
-## ❤️ 貢献
+**公式メンテナンス**
 
-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 :)
+- QQ (公式プラットフォーム & OneBot)
+- Telegram
+- WeChat Work アプリケーション & WeChat Work インテリジェントボット
+- WeChat カスタマーサービス & WeChat 公式アカウント
+- Feishu (Lark)
+- DingTalk
+- Slack
+- Discord
+- Satori
+- Misskey
+- WhatsApp (近日対応予定)
+- LINE (近日対応予定)
 
-新機能の追加については、まず Issue で議論してください。
+**コミュニティメンテナンス**
 
-## 🌟 サポート
+- [Matrix](https://github.com/stevessr/astrbot_plugin_matrix_adapter)
+- [KOOK](https://github.com/wuyan1003/astrbot_plugin_kook_adapter)
+- [VoceChat](https://github.com/HikariFroya/astrbot_plugin_vocechat)
 
-- 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~
 
-## ✨ デモ
+## サポートされているモデルサービス
 
-> [!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
+**大規模言語モデルサービス**
 
-<div align='center'>
+- OpenAI および互換サービス
+- Anthropic
+- Google Gemini
+- Moonshot AI
+- 智谱 AI
+- DeepSeek
+- Ollama (セルフホスト)
+- LM Studio (セルフホスト)
+- [優云智算](https://www.compshare.cn/?ytag=GPU_YY-gh_astrbot&referral_code=FV7DcGowN4hB5UuXKgpE74)
+- [302.AI](https://share.302.ai/rr1M3l)
+- [小馬算力](https://www.tokenpony.cn/3YPyf)
+- [硅基流動](https://docs.siliconflow.cn/cn/usercases/use-siliconcloud-in-astrbot)
+- [PPIO 派欧云](https://ppio.com/user/register?invited_by=AIOONE)
+- ModelScope
+- OneAPI
 
-<img src="https://github.com/user-attachments/assets/4ee688d9-467d-45c8-99d6-368f9a8a92d8" width="600">
+**LLMOps プラットフォーム**
 
-_✨ 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）✨_
+- Dify
+- Alibaba Cloud 百炼アプリケーション
+- Coze
 
-<img src="https://github.com/user-attachments/assets/0378f407-6079-4f64-ae4c-e97ab20611d2" height=500>
+**音声認識サービス**
 
-_✨ 多モーダル、ウェブ検索、長文の画像変換（設定可能）✨_
+- OpenAI Whisper
+- SenseVoice
 
-<img src="https://github.com/user-attachments/assets/8ec12797-e70f-460a-959e-48eca39ca2bb" height=100>
+**音声合成サービス**
 
-_✨ 自然言語タスク ✨_
+- OpenAI TTS
+- Gemini TTS
+- GPT-Sovits-Inference
+- GPT-Sovits
+- FishAudio
+- Edge TTS
+- Alibaba Cloud 百炼 TTS
+- Azure TTS
+- Minimax TTS
+- Volcano Engine TTS
 
-<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>
+## ❤️ コントリビューション
 
-_✨ プラグインシステム - 一部のプラグインの展示 ✨_
+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 :)
 
-<img src="https://github.com/user-attachments/assets/592a8630-14c7-4e06-b496-9c0386e4f36c" width="600">
+### コントリビュート方法
 
-_✨ 管理パネル ✨_
+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。
 
-![webchat](https://drive.soulter.top/f/vlsA/ezgif-5-fb044b2542.gif)
+### 開発環境
 
-_✨ 内蔵 Web Chat、オンラインでボットと対話 ✨_
+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。
 
-</div>
+```bash
+git clone https://github.com/AstrBotDevs/AstrBot
+pip install pre-commit
+pre-commit install
+```
+
+## 🌍 コミュニティ
+
+### QQ グループ
+
+- 1群: 322154837
+- 3群: 630166526
+- 5群: 822130018
+- 6群: 753075035
+- 開発者群: 975206796
+
+### Telegram グループ
+
+<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>
+
+### Discord サーバー
+
+<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
+
+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 ❤️
+
+<a href="https://github.com/AstrBotDevs/AstrBot/graphs/contributors">
+  <img src="https://contrib.rocks/image?repo=AstrBotDevs/AstrBot" />
+</a>
+
+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:
+
+- [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
-
-[<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
-    -->
+</details>
 
 _私は、高性能ですから!_

README_ru.md

@@ -0,0 +1,247 @@
+![AstrBot-Logo-Simplified](https://github.com/user-attachments/assets/ffd99b6b-3272-4682-beaa-6fe74250f7d9)
+
+</p>
+
+<div align="center">
+
+<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?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=%20%D0%BF%D0%BB%D0%B0%D0%B3%D0%B8%D0%BD%D0%BE%D0%B2&style=for-the-badge&label=%D0%9C%D0%B0%D0%B3%D0%B0%D0%B7%D0%B8%D0%BD&cacheSeconds=3600">
+</div>
+
+<br>
+
+<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README.md">中文</a> ｜
+<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://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://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>
+</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.
+
+<img width="1776" height="1080" alt="image" src="https://github.com/user-attachments/assets/00782c4c-4437-4d97-aabc-605e3738da5c" />
+
+## Основные возможности
+
+1. 💯 Бесплатно и с открытым исходным кодом.
+2. ✨ ИИ-диалоги с LLM, мультимодальность, Agent, MCP, база знаний, настройки личности.
+3. 🤖 Поддержка интеграции с Dify, Alibaba Cloud Bailian, Coze и другими платформами агентов.
+4. 🌐 Мультиплатформенность: QQ, WeChat Work, Feishu, DingTalk, официальные аккаунты WeChat, Telegram, Slack и [другие](#поддерживаемые-платформы-обмена-сообщениями).
+5. 📦 Расширения плагинов с почти 800 плагинами, доступными для установки в один клик.
+6. 💻 Поддержка WebUI.
+7. 🌐 Поддержка интернационализации (i18n).
+
+## Быстрый старт
+
+#### Развёртывание Docker (Рекомендуется 🥳)
+
+Мы рекомендуем развёртывать AstrBot с помощью Docker или 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 uv
+
+```bash
+uvx astrbot
+```
+
+#### Развёртывание BT-Panel
+
+AstrBot в партнёрстве с BT-Panel теперь доступен на их маркетплейсе.
+
+См. официальную документацию: [Развёртывание BT-Panel](https://astrbot.app/deploy/astrbot/btpanel.html).
+
+#### Развёртывание 1Panel
+
+AstrBot официально размещён на маркетплейсе 1Panel.
+
+См. официальную документацию: [Развёртывание 1Panel](https://astrbot.app/deploy/astrbot/1panel.html).
+
+#### Развёртывание на RainYun
+
+AstrBot официально размещён на облачной платформе приложений RainYun с развёртыванием в один клик.
+
+[![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 на Replit
+
+Метод развёртывания от сообщества.
+
+[![Run on Repl.it](https://repl.it/badge/github/AstrBotDevs/AstrBot)](https://repl.it/github/AstrBotDevs/AstrBot)
+
+#### Установщик Windows в один клик
+
+См. официальную документацию: [Развёртывание AstrBot с установщиком Windows в один клик](https://astrbot.app/deploy/astrbot/windows.html).
+
+#### Развёртывание CasaOS
+
+Метод развёртывания от сообщества.
+
+См. официальную документацию: [Развёртывание CasaOS](https://astrbot.app/deploy/astrbot/casaos.html).
+
+#### Ручное развёртывание
+
+Сначала установите uv:
+
+```bash
+pip install uv
+```
+
+Установите AstrBot через Git Clone:
+
+```bash
+git clone https://github.com/AstrBotDevs/AstrBot && cd AstrBot
+uv run main.py
+```
+
+Или см. официальную документацию: [Развёртывание AstrBot из исходного кода](https://astrbot.app/deploy/astrbot/cli.html).
+
+## Поддерживаемые платформы обмена сообщениями
+
+**Официально поддерживаемые**
+
+- QQ (Официальная платформа и OneBot)
+- Telegram
+- Приложение WeChat Work и интеллектуальный бот WeChat Work
+- Служба поддержки WeChat и официальные аккаунты WeChat
+- Feishu (Lark)
+- DingTalk
+- Slack
+- Discord
+- Satori
+- Misskey
+- WhatsApp (Скоро)
+- LINE (Скоро)
+
+**Поддерживаемые сообществом**
+
+- [Matrix](https://github.com/stevessr/astrbot_plugin_matrix_adapter)
+- [KOOK](https://github.com/wuyan1003/astrbot_plugin_kook_adapter)
+- [VoceChat](https://github.com/HikariFroya/astrbot_plugin_vocechat)
+
+## Поддерживаемые сервисы моделей
+
+**Сервисы LLM**
+
+- OpenAI и совместимые сервисы
+- Anthropic
+- Google Gemini
+- Moonshot AI
+- Zhipu AI
+- DeepSeek
+- Ollama (Самостоятельное размещение)
+- LM Studio (Самостоятельное размещение)
+- [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_astrbot&referral_code=FV7DcGowN4hB5UuXKgpE74)
+- [302.AI](https://share.302.ai/rr1M3l)
+- [TokenPony](https://www.tokenpony.cn/3YPyf)
+- [SiliconFlow](https://docs.siliconflow.cn/cn/usecases/use-siliconcloud-in-astrbot)
+- [PPIO Cloud](https://ppio.com/user/register?invited_by=AIOONE)
+- ModelScope
+- OneAPI
+
+**Платформы LLMOps**
+
+- Dify
+- Приложения Alibaba Cloud Bailian
+- Coze
+
+**Сервисы распознавания речи**
+
+- OpenAI Whisper
+- SenseVoice
+
+**Сервисы синтеза речи**
+
+- OpenAI TTS
+- Gemini TTS
+- GPT-Sovits-Inference
+- GPT-Sovits
+- FishAudio
+- Edge TTS
+- Alibaba Cloud Bailian TTS
+- Azure TTS
+- Minimax TTS
+- Volcano Engine TTS
+
+## ❤️ 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 Telegram
+
+<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>
+
+### 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" />
+</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>
+
+</details>
+
+_私は、高性能ですから!_
+

README_zh-TW.md

@@ -0,0 +1,247 @@
+![AstrBot-Logo-Simplified](https://github.com/user-attachments/assets/ffd99b6b-3272-4682-beaa-6fe74250f7d9)
+
+</p>
+
+<div align="center">
+
+<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?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=%E5%80%8B&style=for-the-badge&label=%E6%8F%92%E4%BB%B6%E5%B8%82%E5%A0%B4&cacheSeconds=3600">
+</div>
+
+<br>
+
+<a href="https://github.com/AstrBotDevs/AstrBot/blob/master/README.md">简体中文</a> ｜
+<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://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>
+
+<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>
+</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。
+
+<img width="1776" height="1080" alt="image" src="https://github.com/user-attachments/assets/00782c4c-4437-4d97-aabc-605e3738da5c" />
+
+## 主要功能
+
+1. 💯 免費 & 開源。
+2. ✨ AI 大型模型對話，多模態，Agent，MCP，知識庫，人格設定。
+3. 🤖 支援接入 Dify、阿里雲百煉、Coze 等智慧體平台。
+4. 🌐 多平台：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. 📦 外掛擴充，已有近 800 個外掛可一鍵安裝。
+6. 💻 WebUI 支援。
+7. 🌐 國際化（i18n）支援。
+
+## 快速開始
+
+#### Docker 部署（推薦 🥳）
+
+推薦使用 Docker / Docker Compose 方式部署 AstrBot。
+
+請參閱官方文件 [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)。
+
+#### uv 部署
+
+```bash
+uvx astrbot
+```
+
+#### 寶塔面板部署
+
+AstrBot 與寶塔面板合作，已上架至寶塔面板。
+
+請參閱官方文件 [寶塔面板部署](https://astrbot.app/deploy/astrbot/btpanel.html)。
+
+#### 1Panel 部署
+
+AstrBot 已由 1Panel 官方上架至 1Panel 面板。
+
+請參閱官方文件 [1Panel 部署](https://astrbot.app/deploy/astrbot/1panel.html)。
+
+#### 在雨雲上部署
+
+AstrBot 已由雨雲官方上架至雲端應用程式平台，可一鍵部署。
+
+[![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
+
+社群貢獻的部署方式。
+
+[![Run on Repl.it](https://repl.it/badge/github/AstrBotDevs/AstrBot)](https://repl.it/github/AstrBotDevs/AstrBot)
+
+#### Windows 一鍵安裝器部署
+
+請參閱官方文件 [使用 Windows 一鍵安裝器部署 AstrBot](https://astrbot.app/deploy/astrbot/windows.html)。
+
+#### CasaOS 部署
+
+社群貢獻的部署方式。
+
+請參閱官方文件 [CasaOS 部署](https://astrbot.app/deploy/astrbot/casaos.html)。
+
+#### 手動部署
+
+首先安裝 uv：
+
+```bash
+pip install uv
+```
+
+透過 Git Clone 安裝 AstrBot：
+
+```bash
+git clone https://github.com/AstrBotDevs/AstrBot && cd AstrBot
+uv run main.py
+```
+
+或者請參閱官方文件 [透過原始碼部署 AstrBot](https://astrbot.app/deploy/astrbot/cli.html)。
+
+## 支援的訊息平台
+
+**官方維護**
+
+- QQ（官方平台 & OneBot）
+- Telegram
+- 企微應用 & 企微智慧機器人
+- 微信客服 & 微信公眾號
+- 飛書
+- 釘釘
+- Slack
+- Discord
+- Satori
+- Misskey
+- Whatsapp（即將支援）
+- LINE（即將支援）
+
+**社群維護**
+
+- [Matrix](https://github.com/stevessr/astrbot_plugin_matrix_adapter)
+- [KOOK](https://github.com/wuyan1003/astrbot_plugin_kook_adapter)
+- [VoceChat](https://github.com/HikariFroya/astrbot_plugin_vocechat)
+
+## 支援的模型服務
+
+**大型模型服務**
+
+- OpenAI 及相容服務
+- Anthropic
+- Google Gemini
+- Moonshot AI
+- 智譜 AI
+- DeepSeek
+- Ollama（本機部署）
+- LM Studio（本機部署）
+- [優雲智算](https://www.compshare.cn/?ytag=GPU_YY-gh_astrbot&referral_code=FV7DcGowN4hB5UuXKgpE74)
+- [302.AI](https://share.302.ai/rr1M3l)
+- [小馬算力](https://www.tokenpony.cn/3YPyf)
+- [矽基流動](https://docs.siliconflow.cn/cn/usercases/use-siliconcloud-in-astrbot)
+- [PPIO 派歐雲](https://ppio.com/user/register?invited_by=AIOONE)
+- ModelScope
+- OneAPI
+
+**LLMOps 平台**
+
+- Dify
+- 阿里雲百煉應用
+- Coze
+
+**語音轉文字服務**
+
+- OpenAI Whisper
+- SenseVoice
+
+**文字轉語音服務**
+
+- OpenAI TTS
+- Gemini TTS
+- GPT-Sovits-Inference
+- GPT-Sovits
+- FishAudio
+- Edge TTS
+- 阿里雲百煉 TTS
+- Azure TTS
+- Minimax TTS
+- 火山引擎 TTS
+
+## ❤️ 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
+
+- 1 群：322154837
+- 3 群：630166526
+- 5 群：822130018
+- 6 群：753075035
+- 開發者群：975206796
+
+### Telegram 群組
+
+<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>
+
+### 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" />
+</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>
+
+</details>
+
+_私は、高性能ですから!_
+

astrbot/api/event/filter/__init__.py

@@ -21,6 +21,9 @@ 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_platform_loaded as on_platform_loaded
+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,
@@ -46,6 +49,7 @@ __all__ = [
     "on_llm_request",
     "on_llm_response",
     "on_platform_loaded",
+    "on_waiting_llm_request",
     "permission_type",
     "platform_adapter_type",
     "regex",

astrbot/builtin_stars/astrbot/long_term_memory.py

@@ -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
 
 """
@@ -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"]
@@ -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}")
@@ -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 +171,15 @@ 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):
         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"]:

astrbot/builtin_stars/astrbot/main.py

@@ -0,0 +1,120 @@
+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
+from .process_llm_request import ProcessLLMRequest
+
+
+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}")
+
+        self.proc_llm_req = ProcessLLMRequest(self.context)
+
+    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,
+                        func_tool_manager=self.context.get_llm_tool_manager(),
+                        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):
+        """在请求 LLM 前注入人格信息、Identifier、时间、回复内容等 System Prompt"""
+        await self.proc_llm_req.process_llm_request(event, req)
+
+        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):
+        """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):
+        """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}")

astrbot/builtin_stars/astrbot/metadata.yaml

@@ -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

astrbot/builtin_stars/astrbot/process_llm_request.py

@@ -3,10 +3,11 @@ import copy
 import datetime
 import zoneinfo
 
-from astrbot.api import logger, star
+from astrbot.api import logger, sp, star
 from astrbot.api.event import AstrMessageEvent
 from astrbot.api.message_components import Image, Reply
 from astrbot.api.provider import Provider, ProviderRequest
+from astrbot.core.agent.message import TextPart
 from astrbot.core.provider.func_tool_manager import ToolSet
 
 
@@ -21,16 +22,26 @@ class ProcessLLMRequest:
         else:
             logger.info(f"Timezone set to: {self.timezone}")
 
-    def _ensure_persona(self, req: ProviderRequest, cfg: dict):
+    async def _ensure_persona(self, req: ProviderRequest, cfg: dict, umo: str):
         """确保用户人格已加载"""
         if not req.conversation:
             return
         # persona inject
-        persona_id = req.conversation.persona_id or cfg.get("default_personality")
-        if not persona_id and persona_id != "[%None]":  # [%None] 为用户取消人格
-            default_persona = self.ctx.persona_manager.selected_default_persona_v3
-            if default_persona:
-                persona_id = default_persona["name"]
+
+        # custom rule is preferred
+        persona_id = (
+            await sp.get_async(
+                scope="umo", scope_id=umo, key="session_service_config", default={}
+            )
+        ).get("persona_id")
+
+        if not persona_id:
+            persona_id = req.conversation.persona_id or cfg.get("default_personality")
+            if not persona_id and persona_id != "[%None]":  # [%None] 为用户取消人格
+                default_persona = self.ctx.persona_manager.selected_default_persona_v3
+                if default_persona:
+                    persona_id = default_persona["name"]
+
         persona = next(
             builtins.filter(
                 lambda persona: persona["name"] == persona_id,
@@ -75,7 +86,9 @@ class ProcessLLMRequest:
                 req.image_urls,
             )
             if caption:
-                req.prompt = f"(Image Caption: {caption})\n\n{req.prompt}"
+                req.extra_user_content_parts.append(
+                    TextPart(text=f"<image_caption>{caption}</image_caption>")
+                )
                 req.image_urls = []
         except Exception as e:
             logger.error(f"处理图片描述失败: {e}")
@@ -119,19 +132,25 @@ class ProcessLLMRequest:
             else:
                 req.prompt = prefix + req.prompt
 
+        # 收集系统提醒信息
+        system_parts = []
+
         # user identifier
         if cfg.get("identifier"):
             user_id = event.message_obj.sender.user_id
             user_nickname = event.message_obj.sender.nickname
-            req.prompt = (
-                f"\n[User ID: {user_id}, Nickname: {user_nickname}]\n{req.prompt}"
-            )
+            system_parts.append(f"User ID: {user_id}, Nickname: {user_nickname}")
 
         # group name identifier
         if cfg.get("group_name_display") and event.message_obj.group_id:
+            if not event.message_obj.group:
+                logger.error(
+                    f"Group name display enabled but group object is None. Group ID: {event.message_obj.group_id}"
+                )
+                return
             group_name = event.message_obj.group.group_name
             if group_name:
-                req.system_prompt += f"\nGroup name: {group_name}\n"
+                system_parts.append(f"Group name: {group_name}")
 
         # time info
         if cfg.get("datetime_system_prompt"):
@@ -147,12 +166,12 @@ class ProcessLLMRequest:
                 current_time = (
                     datetime.datetime.now().astimezone().strftime("%Y-%m-%d %H:%M (%Z)")
                 )
-            req.system_prompt += f"\nCurrent datetime: {current_time}\n"
+            system_parts.append(f"Current datetime: {current_time}")
 
         img_cap_prov_id: str = cfg.get("default_image_caption_provider_id") or ""
         if req.conversation:
             # inject persona for this request
-            self._ensure_persona(req, cfg)
+            await self._ensure_persona(req, cfg, event.unified_msg_origin)
 
             # image caption
             if img_cap_prov_id and req.image_urls:
@@ -166,37 +185,61 @@ class ProcessLLMRequest:
                 quote = comp
                 break
         if quote:
-            sender_info = ""
-            if quote.sender_nickname:
-                sender_info = f"(Sent by {quote.sender_nickname})"
-            message_str = quote.message_str or "[Empty Text]"
-            req.system_prompt += (
-                f"\nUser is quoting a message{sender_info}.\n"
-                f"Here are the information of the quoted message: Text Content: {message_str}.\n"
+            content_parts = []
+
+            # 1. 处理引用的文本
+            sender_info = (
+                f"({quote.sender_nickname}): " if quote.sender_nickname else ""
             )
+            message_str = quote.message_str or "[Empty Text]"
+            content_parts.append(f"{sender_info}{message_str}")
+
+            # 2. 处理引用的图片 (保留原有逻辑，但改变输出目标)
             image_seg = None
             if quote.chain:
                 for comp in quote.chain:
                     if isinstance(comp, Image):
                         image_seg = comp
                         break
+
             if image_seg:
                 try:
+                    # 找到可以生成图片描述的 provider
                     prov = None
                     if img_cap_prov_id:
                         prov = self.ctx.get_provider_by_id(img_cap_prov_id)
                     if prov is None:
                         prov = self.ctx.get_using_provider(event.unified_msg_origin)
+
+                    # 调用 provider 生成图片描述
                     if prov and isinstance(prov, Provider):
                         llm_resp = await prov.text_chat(
                             prompt="Please describe the image content.",
                             image_urls=[await image_seg.convert_to_file_path()],
                         )
                         if llm_resp.completion_text:
-                            req.system_prompt += (
-                                f"Image Caption: {llm_resp.completion_text}\n"
+                            # 将图片描述作为文本添加到 content_parts
+                            content_parts.append(
+                                f"[Image Caption in quoted message]: {llm_resp.completion_text}"
                             )
                     else:
-                        logger.warning("No provider found for image captioning.")
+                        logger.warning(
+                            "No provider found for image captioning in quote."
+                        )
                 except BaseException as e:
                     logger.error(f"处理引用图片失败: {e}")
+
+            # 3. 将所有部分组合成文本并添加到 extra_user_content_parts 中
+            # 确保引用内容被正确的标签包裹
+            quoted_content = "\n".join(content_parts)
+            # 确保所有内容都在<Quoted Message>标签内
+            quoted_text = f"<Quoted Message>\n{quoted_content}\n</Quoted Message>"
+
+            req.extra_user_content_parts.append(TextPart(text=quoted_text))
+
+        # 统一包裹所有系统提醒
+        if system_parts:
+            system_content = (
+                "<system_reminder>" + "\n".join(system_parts) + "</system_reminder>"
+            )
+            req.extra_user_content_parts.append(TextPart(text=system_content))

astrbot/builtin_stars/builtin_commands/commands/admin.py

@@ -71,6 +71,7 @@ class AdminCommands:
             event.set_result(MessageEventResult().message("此 SID 不在白名单内。"))
 
     async def update_dashboard(self, event: AstrMessageEvent):
+        """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。"))

astrbot/builtin_stars/builtin_commands/commands/conversation.py

@@ -1,20 +1,23 @@
 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.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 ..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",
+}
+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):
         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 +29,15 @@ 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):
         """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 +60,23 @@ 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:
+            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(
@@ -95,15 +87,14 @@ class ConversationCommands:
             return
 
         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))
 
@@ -152,29 +143,14 @@ class ConversationCommands:
 
     async def convs(self, message: AstrMessageEvent, page: int = 1):
         """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
@@ -227,9 +203,8 @@ 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:
@@ -243,15 +218,15 @@ class ConversationCommands:
 
     async def new_conv(self, message: AstrMessageEvent):
         """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:
+            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
 
         cpersona = await self._get_current_persona_id(message.unified_msg_origin)
@@ -261,12 +236,7 @@ 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]})。"),
@@ -274,19 +244,9 @@ class ConversationCommands:
 
     async def groupnew_conv(self, message: AstrMessageEvent, sid: str = ""):
         """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,
@@ -321,31 +281,6 @@ 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(
@@ -378,19 +313,6 @@ class ConversationCommands:
         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,
@@ -399,9 +321,8 @@ class ConversationCommands:
 
     async def del_conv(self, message: AstrMessageEvent):
         """删除当前对话"""
-        is_unique_session = self.context.get_config()["platform_settings"][
-            "unique_session"
-        ]
+        cfg = self.context.get_config(umo=message.unified_msg_origin)
+        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(
@@ -411,20 +332,14 @@ 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:
+            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("重置对话成功。"))
             return
 
         session_curr_cid = (
@@ -447,7 +362,5 @@ class ConversationCommands:
         )
 
         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))

astrbot/builtin_stars/builtin_commands/commands/help.py

@@ -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):
+        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):
+            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):
+        """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))

astrbot/builtin_stars/builtin_commands/commands/persona.py

@@ -1,6 +1,6 @@
 import builtins
 
-from astrbot.api import star
+from astrbot.api import sp, star
 from astrbot.api.event import AstrMessageEvent, MessageEventResult
 
 
@@ -17,6 +17,13 @@ class PersonaCommands:
         default_persona = await self.context.persona_manager.get_default_persona_v3(
             umo=umo,
         )
+
+        force_applied_persona_id = (
+            await sp.get_async(
+                scope="umo", scope_id=umo, key="session_service_config", default={}
+            )
+        ).get("persona_id")
+
         curr_cid_title = "无"
         if cid:
             conv = await self.context.conversation_manager.get_conversation(
@@ -36,6 +43,9 @@ class PersonaCommands:
             else:
                 curr_persona_name = conv.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]})"
 
@@ -113,9 +123,15 @@ 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:

astrbot/builtin_stars/builtin_commands/commands/provider.py

@@ -1,5 +1,7 @@
+import asyncio
 import re
 
+from astrbot import logger
 from astrbot.api import star
 from astrbot.api.event import AstrMessageEvent, MessageEventResult
 from astrbot.core.provider.entities import ProviderType
@@ -9,6 +11,39 @@ class ProviderCommands:
     def __init__(self, context: star.Context):
         self.context = context
 
+    def _log_reachability_failure(
+        self,
+        provider,
+        provider_capability_type: ProviderType | None,
+        err_code: str,
+        err_reason: str,
+    ):
+        """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 = str(e)
+            self._log_reachability_failure(
+                provider, provider_capability_type, err_code, err_reason
+            )
+            return False, err_code, err_reason
+
     async def provider(
         self,
         event: AstrMessageEvent,
@@ -17,46 +52,131 @@ class ProviderCommands:
     ):
         """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"]
-            for idx, llm in enumerate(self.context.get_all_providers()):
-                id_ = llm.meta().id
-                line = f"{idx + 1}. {id_} ({llm.meta().model})"
+
+            # 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, 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__,
+                        str(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 == id_:
+                if (
+                    provider_using
+                    and provider_using.meta().id == d["provider"].meta().id
+                ):
                     line += " (当前使用)"
                 parts.append(line + "\n")
 
-            tts_providers = self.context.get_all_tts_providers()
-            if tts_providers:
+            # 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 idx, tts in enumerate(tts_providers):
-                    id_ = tts.meta().id
-                    line = f"{idx + 1}. {id_}"
+                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 == id_:
+                    if tts_using and tts_using.meta().id == d["provider"].meta().id:
                         line += " (当前使用)"
                     parts.append(line + "\n")
 
-            stt_providers = self.context.get_all_stt_providers()
-            if stt_providers:
+            # 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 idx, stt in enumerate(stt_providers):
-                    id_ = stt.meta().id
-                    line = f"{idx + 1}. {id_}"
+                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 == id_:
+                    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 tts_providers:
+            if ttss:
                 ret += "\n使用 /provider tts <序号> 切换 TTS 提供商。"
-            if stt_providers:
-                ret += "\n使用 /provider stt <切换> STT 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":
@@ -64,7 +184,8 @@ class ProviderCommands:
                 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("无效的序号。"))
+                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(
@@ -78,7 +199,8 @@ class ProviderCommands:
                 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("无效的序号。"))
+                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(
@@ -89,8 +211,8 @@ class ProviderCommands:
             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("无效的序号。"))
-
+                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(

astrbot/builtin_stars/builtin_commands/commands/tts.py

@@ -14,13 +14,13 @@ class TTSCommand:
     async def tts(self, event: AstrMessageEvent):
         """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"
 

astrbot/builtin_stars/builtin_commands/main.py

@@ -1,11 +1,5 @@
-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 astrbot.core.provider.sources.dify_source import ProviderDify
 
 from .commands import (
     AdminCommands,
@@ -22,25 +16,18 @@ from .commands import (
     ToolCommands,
     TTSCommand,
 )
-from .long_term_memory import LongTermMemory
-from .process_llm_request import ProcessLLMRequest
 
 
 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}")
 
         self.help_c = HelpCommand(self.context)
         self.llm_c = LLMCommands(self.context)
         self.tool_c = ToolCommands(self.context)
         self.plugin_c = PluginCommands(self.context)
         self.admin_c = AdminCommands(self.context)
-        self.conversation_c = ConversationCommands(self.context, self.ltm)
+        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)
@@ -48,13 +35,6 @@ class Main(star.Star):
         self.t2i_c = T2ICommand(self.context)
         self.tts_c = TTSCommand(self.context)
         self.sid_c = SIDCommand(self.context)
-        self.proc_llm_req = ProcessLLMRequest(self.context)
-
-    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.command("help")
     async def help(self, event: AstrMessageEvent):
@@ -69,7 +49,7 @@ class Main(star.Star):
 
     @filter.command_group("tool")
     def tool(self):
-        pass
+        """函数工具管理"""
 
     @tool.command("ls")
     async def tool_ls(self, event: AstrMessageEvent):
@@ -93,7 +73,7 @@ class Main(star.Star):
 
     @filter.command_group("plugin")
     def plugin(self):
-        pass
+        """插件管理"""
 
     @plugin.command("ls")
     async def plugin_ls(self, event: AstrMessageEvent):
@@ -239,6 +219,7 @@ class Main(star.Star):
     @filter.permission_type(filter.PermissionType.ADMIN)
     @filter.command("dashboard_update")
     async def update_dashboard(self, event: AstrMessageEvent):
+        """更新管理面板"""
         await self.admin_c.update_dashboard(event)
 
     @filter.command("set")
@@ -249,111 +230,6 @@ class Main(star.Star):
     async def unset_variable(self, event: AstrMessageEvent, key: str):
         await self.setunset_c.unset_variable(event, key)
 
-    @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
-                    if provider.meta().type != "dify":
-                        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,
-                        )
-                    else:
-                        # Dify 自己有维护对话，不需要 bot 端维护。
-                        assert isinstance(provider, ProviderDify)
-                        cid = provider.conversation_ids.get(
-                            event.unified_msg_origin,
-                            None,
-                        )
-                        if cid is None:
-                            logger.error(
-                                "[Dify] 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
-
-                    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,
-                        func_tool_manager=self.context.get_llm_tool_manager(),
-                        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):
-        """在请求 LLM 前注入人格信息、Identifier、时间、回复内容等 System Prompt"""
-        await self.proc_llm_req.process_llm_request(event, req)
-
-        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 inject_reasoning(self, event: AstrMessageEvent, resp: LLMResponse):
-        """在 LLM 响应后基于配置注入思考过程文本"""
-        umo = event.unified_msg_origin
-        cfg = self.context.get_config(umo).get("provider_settings", {})
-        show_reasoning = cfg.get("display_reasoning_text", False)
-        if show_reasoning and resp.reasoning_content:
-            resp.completion_text = (
-                f"🤔 思考: {resp.reasoning_content}\n\n{resp.completion_text}"
-            )
-
-    @filter.after_message_sent()
-    async def after_llm_req(self, event: AstrMessageEvent):
-        """在 LLM 请求后记录对话"""
-        if self.ltm and self.ltm_enabled(event):
-            try:
-                await self.ltm.after_req_llm(event)
-            except Exception as e:
-                logger.error(f"ltm: {e}")
-
     @filter.permission_type(filter.PermissionType.ADMIN)
     @filter.command("alter_cmd", alias={"alter"})
     async def alter_cmd(self, event: AstrMessageEvent):

astrbot/builtin_stars/builtin_commands/metadata.yaml

@@ -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

astrbot/builtin_stars/python_interpreter/main.py

@@ -14,6 +14,7 @@ from astrbot.api import llm_tool, logger, star
 from astrbot.api.event import AstrMessageEvent, MessageEventResult, filter
 from astrbot.api.message_components import File, Image
 from astrbot.api.provider import ProviderRequest
+from astrbot.core.message.components import BaseMessageComponent
 from astrbot.core.utils.astrbot_path import get_astrbot_data_path
 from astrbot.core.utils.io import download_file, download_image_by_url
 
@@ -156,9 +157,8 @@ class Main(star.Star):
     async def is_docker_available(self) -> bool:
         """Check if docker is available"""
         try:
-            docker = aiodocker.Docker()
-            await docker.version()
-            await docker.close()
+            async with aiodocker.Docker() as docker:
+                await docker.version()
             return True
         except BaseException as e:
             logger.info(f"检查 Docker 可用性: {e}")
@@ -224,6 +224,8 @@ class Main(star.Star):
                     del self.user_waiting[uid]
             elif isinstance(comp, Image):
                 image_url = comp.url if comp.url else comp.file
+                if image_url is None:
+                    raise ValueError("Image URL is None")
                 if image_url.startswith("http"):
                     image_path = await download_image_by_url(image_url)
                 elif image_url.startswith("file:///"):
@@ -240,11 +242,13 @@ class Main(star.Star):
     async def on_llm_req(self, event: AstrMessageEvent, request: ProviderRequest):
         if event.get_session_id() in self.user_file_msg_buffer:
             files = self.user_file_msg_buffer[event.get_session_id()]
+            if not request.prompt:
+                request.prompt = ""
             request.prompt += f"\nUser provided files: {files}"
 
     @filter.command_group("pi")
     def pi(self):
-        pass
+        """代码执行器配置"""
 
     @pi.command("absdir")
     async def pi_absdir(self, event: AstrMessageEvent, path: str = ""):
@@ -274,14 +278,14 @@ class Main(star.Star):
     @pi.command("repull")
     async def pi_repull(self, event: AstrMessageEvent):
         """重新拉取沙箱镜像"""
-        docker = aiodocker.Docker()
-        image_name = await self.get_image_name()
-        try:
-            await docker.images.get(image_name)
-            await docker.images.delete(image_name, force=True)
-        except aiodocker.exceptions.DockerError:
-            pass
-        await docker.images.pull(image_name)
+        async with aiodocker.Docker() as docker:
+            image_name = await self.get_image_name()
+            try:
+                await docker.images.get(image_name)
+                await docker.images.delete(image_name, force=True)
+            except aiodocker.exceptions.DockerError:
+                pass
+            await docker.images.pull(image_name)
         yield event.plain_result("重新拉取沙箱镜像成功。")
 
     @pi.command("file")
@@ -366,135 +370,137 @@ class Main(star.Star):
         obs = ""
         n = 5
 
-        for i in range(n):
-            if i > 0:
-                logger.info(f"Try {i + 1}/{n}")
+        async with aiodocker.Docker() as docker:
+            for i in range(n):
+                if i > 0:
+                    logger.info(f"Try {i + 1}/{n}")
 
-            PROMPT_ = PROMPT.format(
-                prompt=plain_text,
-                extra_input=extra_inputs,
-                extra_prompt=obs,
-            )
-            provider = self.context.get_using_provider()
-            llm_response = await provider.text_chat(
-                prompt=PROMPT_,
-                session_id=f"{event.session_id}_{magic_code}_{i!s}",
-            )
-
-            logger.debug(
-                "code interpreter llm gened code:" + llm_response.completion_text,
-            )
-
-            # 整理代码并保存
-            code_clean = await self.tidy_code(llm_response.completion_text)
-            with open(os.path.join(workplace_path, "exec.py"), "w") as f:
-                f.write(code_clean)
-
-            # 启动容器
-            docker = aiodocker.Docker()
-
-            # 检查有没有image
-            image_name = await self.get_image_name()
-            try:
-                await docker.images.get(image_name)
-            except aiodocker.exceptions.DockerError:
-                # 拉取镜像
-                logger.info(f"未找到沙箱镜像，正在尝试拉取 {image_name}...")
-                await docker.images.pull(image_name)
-
-            yield event.plain_result(
-                f"使用沙箱执行代码中，请稍等...(尝试次数: {i + 1}/{n})",
-            )
-
-            self.docker_host_astrbot_abs_path = self.config.get(
-                "docker_host_astrbot_abs_path",
-                "",
-            )
-            if self.docker_host_astrbot_abs_path:
-                host_shared = os.path.join(
-                    self.docker_host_astrbot_abs_path,
-                    self.shared_path,
+                PROMPT_ = PROMPT.format(
+                    prompt=plain_text,
+                    extra_input=extra_inputs,
+                    extra_prompt=obs,
                 )
-                host_output = os.path.join(
-                    self.docker_host_astrbot_abs_path,
-                    output_path,
-                )
-                host_workplace = os.path.join(
-                    self.docker_host_astrbot_abs_path,
-                    workplace_path,
+                provider = self.context.get_using_provider()
+                llm_response = await provider.text_chat(
+                    prompt=PROMPT_,
+                    session_id=f"{event.session_id}_{magic_code}_{i!s}",
                 )
 
-            else:
-                host_shared = os.path.abspath(self.shared_path)
-                host_output = os.path.abspath(output_path)
-                host_workplace = os.path.abspath(workplace_path)
+                logger.debug(
+                    "code interpreter llm gened code:" + llm_response.completion_text,
+                )
 
-            logger.debug(
-                f"host_shared: {host_shared}, host_output: {host_output}, host_workplace: {host_workplace}",
-            )
+                # 整理代码并保存
+                code_clean = await self.tidy_code(llm_response.completion_text)
+                with open(os.path.join(workplace_path, "exec.py"), "w") as f:
+                    f.write(code_clean)
 
-            container = await docker.containers.run(
-                {
-                    "Image": image_name,
-                    "Cmd": ["python", "exec.py"],
-                    "Memory": 512 * 1024 * 1024,
-                    "NanoCPUs": 1000000000,
-                    "HostConfig": {
-                        "Binds": [
-                            f"{host_shared}:/astrbot_sandbox/shared:ro",
-                            f"{host_output}:/astrbot_sandbox/output:rw",
-                            f"{host_workplace}:/astrbot_sandbox:rw",
-                        ],
-                    },
-                    "Env": [f"MAGIC_CODE={magic_code}"],
-                    "AutoRemove": True,
-                },
-            )
+                # 检查有没有image
+                image_name = await self.get_image_name()
+                try:
+                    await docker.images.get(image_name)
+                except aiodocker.exceptions.DockerError:
+                    # 拉取镜像
+                    logger.info(f"未找到沙箱镜像，正在尝试拉取 {image_name}...")
+                    await docker.images.pull(image_name)
 
-            logger.debug(f"Container {container.id} created.")
-            logs = await self.run_container(container)
+                yield event.plain_result(
+                    f"使用沙箱执行代码中，请稍等...(尝试次数: {i + 1}/{n})",
+                )
 
-            logger.debug(f"Container {container.id} finished.")
-            logger.debug(f"Container {container.id} logs: {logs}")
-
-            # 发送结果
-            pattern = r"\[ASTRBOT_(TEXT|IMAGE|FILE)_OUTPUT#\w+\]: (.*)"
-            ok = False
-            traceback = ""
-            for idx, log in enumerate(logs):
-                match = re.match(pattern, log)
-                if match:
-                    ok = True
-                    if match.group(1) == "TEXT":
-                        yield event.plain_result(match.group(2))
-                    elif match.group(1) == "IMAGE":
-                        image_path = os.path.join(workplace_path, match.group(2))
-                        logger.debug(f"Sending image: {image_path}")
-                        yield event.image_result(image_path)
-                    elif match.group(1) == "FILE":
-                        file_path = os.path.join(workplace_path, match.group(2))
-                        # logger.debug(f"Sending file: {file_path}")
-                        # file_s3_url = await self.file_upload(file_path)
-                        # logger.info(f"文件上传到 AstrBot 云节点: {file_s3_url}")
-                        file_name = os.path.basename(file_path)
-                        chain = [File(name=file_name, file=file_path)]
-                        yield event.set_result(MessageEventResult(chain=chain))
-
-                elif "Traceback (most recent call last)" in log or "[Error]: " in log:
-                    traceback = "\n".join(logs[idx:])
-
-            if not ok:
-                if traceback:
-                    obs = f"## Observation \n When execute the code: ```python\n{code_clean}\n```\n\n Error occurred:\n\n{traceback}\n Need to improve/fix the code."
-                else:
-                    logger.warning(
-                        f"未从沙箱输出中捕获到合法的输出。沙箱输出日志: {logs}",
+                self.docker_host_astrbot_abs_path = self.config.get(
+                    "docker_host_astrbot_abs_path",
+                    "",
+                )
+                if self.docker_host_astrbot_abs_path:
+                    host_shared = os.path.join(
+                        self.docker_host_astrbot_abs_path,
+                        self.shared_path,
                     )
-                    break
-            else:
-                # 成功了
-                self.user_file_msg_buffer.pop(event.get_session_id())
-                return
+                    host_output = os.path.join(
+                        self.docker_host_astrbot_abs_path,
+                        output_path,
+                    )
+                    host_workplace = os.path.join(
+                        self.docker_host_astrbot_abs_path,
+                        workplace_path,
+                    )
+
+                else:
+                    host_shared = os.path.abspath(self.shared_path)
+                    host_output = os.path.abspath(output_path)
+                    host_workplace = os.path.abspath(workplace_path)
+
+                logger.debug(
+                    f"host_shared: {host_shared}, host_output: {host_output}, host_workplace: {host_workplace}",
+                )
+
+                container = await docker.containers.run(
+                    {
+                        "Image": image_name,
+                        "Cmd": ["python", "exec.py"],
+                        "Memory": 512 * 1024 * 1024,
+                        "NanoCPUs": 1000000000,
+                        "HostConfig": {
+                            "Binds": [
+                                f"{host_shared}:/astrbot_sandbox/shared:ro",
+                                f"{host_output}:/astrbot_sandbox/output:rw",
+                                f"{host_workplace}:/astrbot_sandbox:rw",
+                            ],
+                        },
+                        "Env": [f"MAGIC_CODE={magic_code}"],
+                        "AutoRemove": True,
+                    },
+                )
+
+                logger.debug(f"Container {container.id} created.")
+                logs = await self.run_container(container)
+
+                logger.debug(f"Container {container.id} finished.")
+                logger.debug(f"Container {container.id} logs: {logs}")
+
+                # 发送结果
+                pattern = r"\[ASTRBOT_(TEXT|IMAGE|FILE)_OUTPUT#\w+\]: (.*)"
+                ok = False
+                traceback = ""
+                for idx, log in enumerate(logs):
+                    match = re.match(pattern, log)
+                    if match:
+                        ok = True
+                        if match.group(1) == "TEXT":
+                            yield event.plain_result(match.group(2))
+                        elif match.group(1) == "IMAGE":
+                            image_path = os.path.join(workplace_path, match.group(2))
+                            logger.debug(f"Sending image: {image_path}")
+                            yield event.image_result(image_path)
+                        elif match.group(1) == "FILE":
+                            file_path = os.path.join(workplace_path, match.group(2))
+                            # logger.debug(f"Sending file: {file_path}")
+                            # file_s3_url = await self.file_upload(file_path)
+                            # logger.info(f"文件上传到 AstrBot 云节点: {file_s3_url}")
+                            file_name = os.path.basename(file_path)
+                            chain: list[BaseMessageComponent] = [
+                                File(name=file_name, file=file_path)
+                            ]
+                            yield event.set_result(MessageEventResult(chain=chain))
+
+                    elif (
+                        "Traceback (most recent call last)" in log or "[Error]: " in log
+                    ):
+                        traceback = "\n".join(logs[idx:])
+
+                if not ok:
+                    if traceback:
+                        obs = f"## Observation \n When execute the code: ```python\n{code_clean}\n```\n\n Error occurred:\n\n{traceback}\n Need to improve/fix the code."
+                    else:
+                        logger.warning(
+                            f"未从沙箱输出中捕获到合法的输出。沙箱输出日志: {logs}",
+                        )
+                        break
+                else:
+                    # 成功了
+                    self.user_file_msg_buffer.pop(event.get_session_id())
+                    return
 
         yield event.plain_result(
             "经过多次尝试后，未从沙箱输出中捕获到合法的输出，请更换问法或者查看日志。",

astrbot/builtin_stars/reminder/main.py

@@ -5,6 +5,7 @@ import uuid
 import zoneinfo
 
 from apscheduler.schedulers.asyncio import AsyncIOScheduler
+from apscheduler.triggers.cron import CronTrigger
 
 from astrbot.api import llm_tool, logger, star
 from astrbot.api.event import AstrMessageEvent, MessageEventResult, filter
@@ -62,13 +63,13 @@ class Main(star.Star):
                         misfire_grace_time=60,
                     )
                 elif "cron" in reminder:
+                    trigger = CronTrigger(**self._parse_cron_expr(reminder["cron"]))
                     self.scheduler.add_job(
                         self._reminder_callback,
-                        trigger="cron",
+                        trigger=trigger,
                         id=id_,
                         args=[group, reminder],
                         misfire_grace_time=60,
-                        **self._parse_cron_expr(reminder["cron"]),
                     )
 
     def check_is_outdated(self, reminder: dict):
@@ -101,10 +102,10 @@ class Main(star.Star):
     async def reminder_tool(
         self,
         event: AstrMessageEvent,
-        text: str = None,
-        datetime_str: str = None,
-        cron_expression: str = None,
-        human_readable_cron: str = None,
+        text: str | None = None,
+        datetime_str: str | None = None,
+        cron_expression: str | None = None,
+        human_readable_cron: str | None = None,
     ):
         """Call this function when user is asking for setting a reminder.
 
@@ -139,17 +140,19 @@ class Main(star.Star):
                 "id": str(uuid.uuid4()),
             }
             self.reminder_data[event.unified_msg_origin].append(d)
+            trigger = CronTrigger(**self._parse_cron_expr(cron_expression))
             self.scheduler.add_job(
                 self._reminder_callback,
-                "cron",
+                trigger,
                 id=d["id"],
                 misfire_grace_time=60,
-                **self._parse_cron_expr(cron_expression),
                 args=[event.unified_msg_origin, d],
             )
             if human_readable_cron:
                 reminder_time = f"{human_readable_cron}(Cron: {cron_expression})"
         else:
+            if datetime_str is None:
+                raise ValueError("datetime_str cannot be None.")
             d = {"text": text, "datetime": datetime_str, "id": str(uuid.uuid4())}
             self.reminder_data[event.unified_msg_origin].append(d)
             datetime_scheduled = datetime.datetime.strptime(
@@ -176,7 +179,7 @@ class Main(star.Star):
 
     @filter.command_group("reminder")
     def reminder(self):
-        """The command group of the reminder."""
+        """待办提醒"""
 
     async def get_upcoming_reminders(self, unified_msg_origin: str):
         """Get upcoming reminders."""

astrbot/builtin_stars/session_controller/main.py

@@ -14,7 +14,7 @@ from astrbot.core.utils.session_waiter import (
 )
 
 
-class Waiter(Star):
+class Main(Star):
     """会话控制"""
 
     def __init__(self, context: Context):

astrbot/builtin_stars/web_searcher/engines/__init__.py

@@ -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",
@@ -45,13 +45,13 @@ 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):
+    def _get_next_page(self, query: 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 +83,9 @@ 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 +95,16 @@ 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:

astrbot/builtin_stars/web_searcher/engines/bing.py

@@ -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

astrbot/builtin_stars/web_searcher/engines/sogo.py

@@ -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

astrbot/builtin_stars/web_searcher/main.py

@@ -185,6 +185,7 @@ class Main(star.Star):
 
     @filter.command("websearch")
     async def websearch(self, event: AstrMessageEvent, oper: str | None = None):
+        """网页搜索指令（已废弃）"""
         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。",

astrbot/cli/__init__.py

@@ -1 +1 @@
-__version__ = "3.5.23"
+__version__ = "4.11.4"

astrbot/core/agent/context/compressor.py

@@ -0,0 +1,243 @@
+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):
+        """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,
+    ):
+        """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

astrbot/core/agent/context/config.py

@@ -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."""

astrbot/core/agent/context/manager.py

@@ -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,
+    ):
+        """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

astrbot/core/agent/context/token_counter.py

@@ -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)

astrbot/core/agent/context/truncator.py

@@ -0,0 +1,141 @@
+from ..message import Message
+
+
+class ContextTruncator:
+    """Context truncator."""
+
+    def fix_messages(self, messages: list[Message]) -> list[Message]:
+        fixed_messages = []
+        for message in messages:
+            if message.role == "tool":
+                # tool block 前面必须要有 user 和 assistant block
+                if len(fixed_messages) < 2:
+                    # 这种情况可能是上下文被截断导致的
+                    # 我们直接将之前的上下文都清空
+                    fixed_messages = []
+                else:
+                    fixed_messages.append(message)
+            else:
+                fixed_messages.append(message)
+        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)

astrbot/core/agent/mcp_client.py

@@ -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":
@@ -91,7 +102,7 @@ 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}"
 
@@ -101,6 +112,7 @@ class MCPClient:
         # 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
@@ -108,22 +120,32 @@ 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):
+        """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
+            # Handle MCP service error logs
             print(f"MCP Server {name} Error: {msg}")
             self.server_errlogs.append(msg)
 
@@ -137,7 +159,7 @@ 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
@@ -193,7 +215,7 @@ class MCPClient:
             )
 
             def callback(msg: str):
-                # 处理 MCP 服务的错误日志
+                # Handle MCP service error logs
                 self.server_errlogs.append(msg)
 
             stdio_transport = await self.exit_stack.enter_async_context(
@@ -222,10 +244,120 @@ class MCPClient:
         self.tools = response.tools
         return response
 
+    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):
-        """Clean up resources"""
-        await self.exit_stack.aclose()
-        self.running_event.set()  # Set the running event to indicate cleanup is done
+        """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]):
@@ -246,14 +378,8 @@ 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

astrbot/core/agent/message.py

@@ -3,7 +3,7 @@
 
 from typing import Any, ClassVar, Literal, cast
 
-from pydantic import BaseModel, GetCoreSchemaHandler
+from pydantic import BaseModel, GetCoreSchemaHandler, model_serializer, model_validator
 from pydantic_core import core_schema
 
 
@@ -12,7 +12,7 @@ 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 +63,28 @@ 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()
@@ -76,7 +98,7 @@ class ImageURLPart(ContentPart):
         """The ID of the image, to allow LLMs to distinguish different images."""
 
     type: str = "image_url"
-    image_url: str
+    image_url: ImageURL
 
 
 class AudioURLPart(ContentPart):
@@ -119,6 +141,15 @@ 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 +169,48 @@ 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."""
+
+    @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):

astrbot/core/agent/response.py

@@ -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,
+        }

astrbot/core/agent/run_context.py

@@ -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."""
 

astrbot/core/agent/runners/base.py

@@ -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

astrbot/core/agent/runners/coze/coze_agent_runner.py

@@ -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

astrbot/core/agent/runners/dashscope/dashscope_agent_runner.py

@@ -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):
+        """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_event_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_event_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

astrbot/core/agent/runners/dify/dify_agent_runner.py

@@ -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_data_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 = os.path.join(get_astrbot_data_path(), "temp")
+                    path = os.path.join(temp_dir, f"{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

astrbot/core/agent/runners/dify/dify_api_client.py

@@ -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
 
@@ -101,21 +101,59 @@ 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]:
+        """Upload a file to Dify. Must provide either file_path or file_data.
+
+        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"
-        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", ...}
+
+        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):
         await self.session.close()

astrbot/core/agent/runners/tool_loop_agent_runner.py

@@ -1,4 +1,5 @@
 import sys
+import time
 import traceback
 import typing as T
 
@@ -12,6 +13,8 @@ from mcp.types import (
 )
 
 from astrbot import logger
+from astrbot.core.agent.message import TextPart, ThinkPart
+from astrbot.core.message.components import Json
 from astrbot.core.message.message_event_result import (
     MessageChain,
 )
@@ -22,9 +25,13 @@ 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
@@ -44,10 +51,47 @@ 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,
         **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.final_llm_resp = None
         self._state = AgentState.IDLE
@@ -69,20 +113,25 @@ 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]:
         """Yields chunks *and* a final LLMResponse."""
+        payload = {
+            "contexts": self.run_context.messages,  # list[Message]
+            "func_tool": self.req.func_tool,
+            "model": self.req.model,  # NOTE: in fact, this arg is None in most cases
+            "session_id": self.req.session_id,
+            "extra_user_content_parts": self.req.extra_user_content_parts,  # list[ContentPart]
+        }
+
         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)
 
     @override
     async def step(self):
@@ -102,9 +151,18 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
         self._transition_state(AgentState.RUNNING)
         llm_resp_result = None
 
+        # do truncate and compress
+        token_usage = self.req.conversation.token_usage if self.req.conversation else 0
+        self.run_context.messages = await self.context_manager.process(
+            self.run_context.messages, trusted_token_usage=token_usage
+        )
+
         async for llm_response in self._iter_llm_responses():
-            assert isinstance(llm_response, LLMResponse)
             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",
@@ -128,6 +186,10 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
                     )
                 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
             break  # got final response
 
         if not llm_resp_result:
@@ -139,6 +201,7 @@ 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)
             yield AgentResponse(
                 type="err",
@@ -153,13 +216,21 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
             # 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,
+                    )
+                )
+            parts.append(TextPart(text=llm_resp.completion_text or "*No response*"))
+            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:
@@ -182,29 +253,35 @@ 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:
             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}"
-                        ),
-                    ),
-                )
             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.type is None:
+                        # should not happen
+                        continue
+                    if result.type == "tool_direct_result":
+                        ar_type = "tool_call_result"
+                    else:
+                        ar_type = result.type
                     yield AgentResponse(
-                        type="tool_call_result",
+                        type=ar_type,
                         data=AgentResponseData(chain=result),
                     )
             # 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,
+                    )
+                )
+            parts.append(TextPart(text=llm_resp.completion_text or "*No response*"))
             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,
             )
@@ -225,6 +302,25 @@ 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,
@@ -240,6 +336,19 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
             llm_response.tools_call_args,
             llm_response.tools_call_ids,
         ):
+            yield 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
@@ -313,7 +422,6 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
                                     content=res.content[0].text,
                                 ),
                             )
-                            yield MessageChain().message(res.content[0].text)
                         elif isinstance(res.content[0], ImageContent):
                             tool_call_result_blocks.append(
                                 ToolCallMessageSegment(
@@ -335,7 +443,6 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
                                         content=resource.text,
                                     ),
                                 )
-                                yield MessageChain().message(resource.text)
                             elif (
                                 isinstance(resource, BlobResourceContents)
                                 and resource.mimeType
@@ -359,20 +466,34 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
                                         content="返回的数据类型不受支持",
                                     ),
                                 )
-                                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()
+                        tool_call_result_blocks.append(
+                            ToolCallMessageSegment(
+                                role="tool",
+                                tool_call_id=func_tool_id,
+                                content="*工具没有返回值或者将结果直接发送给了用户*",
+                            ),
+                        )
                     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)}。",
+                        )
+                        tool_call_result_blocks.append(
+                            ToolCallMessageSegment(
+                                role="tool",
+                                tool_call_id=func_tool_id,
+                                content="*工具返回了不支持的类型，请告诉用户检查这个工具的定义和实现。*",
+                            ),
                         )
 
                 try:
@@ -394,6 +515,22 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
                     ),
                 )
 
+        # yield the last tool call result
+        if tool_call_result_blocks:
+            last_tcr_content = str(tool_call_result_blocks[-1].content)
+            yield MessageChain(
+                type="tool_call_result",
+                chain=[
+                    Json(
+                        data={
+                            "id": func_tool_id,
+                            "ts": time.time(),
+                            "result": last_tcr_content,
+                        }
+                    )
+                ],
+            )
+
         # 处理函数调用响应
         if tool_call_result_blocks:
             yield tool_call_result_blocks

astrbot/core/agent/tool.py

@@ -1,4 +1,4 @@
-from collections.abc import Awaitable, Callable
+from collections.abc import AsyncGenerator, Awaitable, Callable
 from typing import Any, Generic
 
 import jsonschema
@@ -7,6 +7,8 @@ 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 +40,10 @@ 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

astrbot/core/astr_agent_context.py

@@ -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

astrbot/core/astr_agent_hooks.py

@@ -13,6 +13,12 @@ from astrbot.core.star.star_handler import EventType
 class MainAgentHooks(BaseAgentRunHooks[AstrAgentContext]):
     async def on_agent_done(self, run_context, llm_response):
         # 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,

astrbot/core/astr_agent_run_util.py

@@ -2,13 +2,16 @@ 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 Json
 from astrbot.core.message.message_event_result import (
     MessageChain,
     MessageEventResult,
     ResultContentType,
 )
+from astrbot.core.provider.entities import LLMResponse
 
 AgentRunner = ToolLoopAgentRunner[AstrAgentContext]
 
@@ -22,8 +25,25 @@ async def run_agent(
 ) -> AsyncGenerator[MessageChain | None, None]:
     step_idx = 0
     astr_event = agent_runner.run_context.context.event
-    while step_idx < max_step:
+    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。",
+                    )
+                )
+
         try:
             async for resp in agent_runner.step():
                 if astr_event.is_stopped():
@@ -32,16 +52,27 @@ async def run_agent(
                     msg_chain = resp.data["chain"]
                     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)
                     # 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:
+
+                    if astr_event.get_platform_name() == "webchat":
                         await astr_event.send(resp.data["chain"])
+                    elif show_tool_use:
+                        json_comp = resp.data["chain"].chain[0]
+                        if isinstance(json_comp, Json):
+                            m = f"🔨 调用工具: {json_comp.data.get('name')}"
+                        else:
+                            m = "🔨 调用工具..."
+                        chain = MessageChain(type="tool_call").message(m)
+                        await astr_event.send(chain)
                     continue
 
                 if stream_to_general and resp.type == "streaming_delta":
@@ -68,11 +99,33 @@ async def run_agent(
                         continue
                     yield resp.data["chain"]  # MessageChain
             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:
             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"
+
+            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请在平台日志查看和分享错误详情。\n"
+
+            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:

astrbot/core/astr_agent_tool_exec.py

@@ -185,7 +185,11 @@ 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 +209,42 @@ 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

astrbot/core/backup/__init__.py

@@ -0,0 +1,26 @@
+"""AstrBot 备份与恢复模块
+
+提供数据导出和导入功能，支持用户在服务器迁移时一键备份和恢复所有数据。
+"""
+
+# 从 constants 模块导入共享常量
+from .constants import (
+    BACKUP_MANIFEST_VERSION,
+    KB_METADATA_MODELS,
+    MAIN_DB_MODELS,
+    get_backup_directories,
+)
+
+# 导入导出器和导入器
+from .exporter import AstrBotExporter
+from .importer import AstrBotImporter, ImportPreCheckResult
+
+__all__ = [
+    "AstrBotExporter",
+    "AstrBotImporter",
+    "ImportPreCheckResult",
+    "MAIN_DB_MODELS",
+    "KB_METADATA_MODELS",
+    "get_backup_directories",
+    "BACKUP_MANIFEST_VERSION",
+]

astrbot/core/backup/constants.py

@@ -0,0 +1,77 @@
+"""AstrBot 备份模块共享常量
+
+此文件定义了导出器和导入器共享的常量，确保两端配置一致。
+"""
+
+from sqlmodel import SQLModel
+
+from astrbot.core.db.po import (
+    Attachment,
+    CommandConfig,
+    CommandConflict,
+    ConversationV2,
+    Persona,
+    PlatformMessageHistory,
+    PlatformSession,
+    PlatformStat,
+    Preference,
+)
+from astrbot.core.knowledge_base.models import (
+    KBDocument,
+    KBMedia,
+    KnowledgeBase,
+)
+from astrbot.core.utils.astrbot_path import (
+    get_astrbot_config_path,
+    get_astrbot_plugin_data_path,
+    get_astrbot_plugin_path,
+    get_astrbot_t2i_templates_path,
+    get_astrbot_temp_path,
+    get_astrbot_webchat_path,
+)
+
+# ============================================================
+# 共享常量 - 确保导出和导入端配置一致
+# ============================================================
+
+# 主数据库模型类映射
+MAIN_DB_MODELS: dict[str, type[SQLModel]] = {
+    "platform_stats": PlatformStat,
+    "conversations": ConversationV2,
+    "personas": Persona,
+    "preferences": Preference,
+    "platform_message_history": PlatformMessageHistory,
+    "platform_sessions": PlatformSession,
+    "attachments": Attachment,
+    "command_configs": CommandConfig,
+    "command_conflicts": CommandConflict,
+}
+
+# 知识库元数据模型类映射
+KB_METADATA_MODELS: dict[str, type[SQLModel]] = {
+    "knowledge_bases": KnowledgeBase,
+    "kb_documents": KBDocument,
+    "kb_media": KBMedia,
+}
+
+
+def get_backup_directories() -> dict[str, str]:
+    """获取需要备份的目录列表
+
+    使用 astrbot_path 模块动态获取路径，支持通过环境变量 ASTRBOT_ROOT 自定义根目录。
+
+    Returns:
+        dict: 键为备份文件中的目录名称，值为目录的绝对路径
+    """
+    return {
+        "plugins": get_astrbot_plugin_path(),  # 插件本体
+        "plugin_data": get_astrbot_plugin_data_path(),  # 插件数据
+        "config": get_astrbot_config_path(),  # 配置目录
+        "t2i_templates": get_astrbot_t2i_templates_path(),  # T2I 模板
+        "webchat": get_astrbot_webchat_path(),  # WebChat 数据
+        "temp": get_astrbot_temp_path(),  # 临时文件
+    }
+
+
+# 备份清单版本号
+BACKUP_MANIFEST_VERSION = "1.1"

astrbot/core/backup/exporter.py

@@ -0,0 +1,477 @@
+"""AstrBot 数据导出器
+
+负责将所有数据导出为 ZIP 备份文件。
+导出格式为 JSON，这是数据库无关的方案，支持未来向 MySQL/PostgreSQL 迁移。
+"""
+
+import hashlib
+import json
+import os
+import zipfile
+from datetime import datetime, timezone
+from pathlib import Path
+from typing import TYPE_CHECKING, Any
+
+from sqlalchemy import select
+
+from astrbot.core import logger
+from astrbot.core.config.default import VERSION
+from astrbot.core.db import BaseDatabase
+from astrbot.core.utils.astrbot_path import (
+    get_astrbot_backups_path,
+    get_astrbot_data_path,
+)
+
+# 从共享常量模块导入
+from .constants import (
+    BACKUP_MANIFEST_VERSION,
+    KB_METADATA_MODELS,
+    MAIN_DB_MODELS,
+    get_backup_directories,
+)
+
+if TYPE_CHECKING:
+    from astrbot.core.knowledge_base.kb_mgr import KnowledgeBaseManager
+
+CMD_CONFIG_FILE_PATH = os.path.join(get_astrbot_data_path(), "cmd_config.json")
+
+
+class AstrBotExporter:
+    """AstrBot 数据导出器
+
+    导出内容：
+    - 主数据库所有表（data/data_v4.db）
+    - 知识库元数据（data/knowledge_base/kb.db）
+    - 每个知识库的向量文档数据
+    - 配置文件（data/cmd_config.json）
+    - 附件文件
+    - 知识库多媒体文件
+    - 插件目录（data/plugins）
+    - 插件数据目录（data/plugin_data）
+    - 配置目录（data/config）
+    - T2I 模板目录（data/t2i_templates）
+    - WebChat 数据目录（data/webchat）
+    - 临时文件目录（data/temp）
+    """
+
+    def __init__(
+        self,
+        main_db: BaseDatabase,
+        kb_manager: "KnowledgeBaseManager | None" = None,
+        config_path: str = CMD_CONFIG_FILE_PATH,
+    ):
+        self.main_db = main_db
+        self.kb_manager = kb_manager
+        self.config_path = config_path
+        self._checksums: dict[str, str] = {}
+
+    async def export_all(
+        self,
+        output_dir: str | None = None,
+        progress_callback: Any | None = None,
+    ) -> str:
+        """导出所有数据到 ZIP 文件
+
+        Args:
+            output_dir: 输出目录
+            progress_callback: 进度回调函数，接收参数 (stage, current, total, message)
+
+        Returns:
+            str: 生成的 ZIP 文件路径
+        """
+        if output_dir is None:
+            output_dir = get_astrbot_backups_path()
+
+        # 确保输出目录存在
+        Path(output_dir).mkdir(parents=True, exist_ok=True)
+
+        timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
+        zip_filename = f"astrbot_backup_{timestamp}.zip"
+        zip_path = os.path.join(output_dir, zip_filename)
+
+        logger.info(f"开始导出备份到 {zip_path}")
+
+        try:
+            with zipfile.ZipFile(zip_path, "w", zipfile.ZIP_DEFLATED) as zf:
+                # 1. 导出主数据库
+                if progress_callback:
+                    await progress_callback("main_db", 0, 100, "正在导出主数据库...")
+                main_data = await self._export_main_database()
+                main_db_json = json.dumps(
+                    main_data, ensure_ascii=False, indent=2, default=str
+                )
+                zf.writestr("databases/main_db.json", main_db_json)
+                self._add_checksum("databases/main_db.json", main_db_json)
+                if progress_callback:
+                    await progress_callback("main_db", 100, 100, "主数据库导出完成")
+
+                # 2. 导出知识库数据
+                kb_meta_data: dict[str, Any] = {
+                    "knowledge_bases": [],
+                    "kb_documents": [],
+                    "kb_media": [],
+                }
+                if self.kb_manager:
+                    if progress_callback:
+                        await progress_callback(
+                            "kb_metadata", 0, 100, "正在导出知识库元数据..."
+                        )
+                    kb_meta_data = await self._export_kb_metadata()
+                    kb_meta_json = json.dumps(
+                        kb_meta_data, ensure_ascii=False, indent=2, default=str
+                    )
+                    zf.writestr("databases/kb_metadata.json", kb_meta_json)
+                    self._add_checksum("databases/kb_metadata.json", kb_meta_json)
+                    if progress_callback:
+                        await progress_callback(
+                            "kb_metadata", 100, 100, "知识库元数据导出完成"
+                        )
+
+                    # 导出每个知识库的文档数据
+                    kb_insts = self.kb_manager.kb_insts
+                    total_kbs = len(kb_insts)
+                    for idx, (kb_id, kb_helper) in enumerate(kb_insts.items()):
+                        if progress_callback:
+                            await progress_callback(
+                                "kb_documents",
+                                idx,
+                                total_kbs,
+                                f"正在导出知识库 {kb_helper.kb.kb_name} 的文档数据...",
+                            )
+                        doc_data = await self._export_kb_documents(kb_helper)
+                        doc_json = json.dumps(
+                            doc_data, ensure_ascii=False, indent=2, default=str
+                        )
+                        doc_path = f"databases/kb_{kb_id}/documents.json"
+                        zf.writestr(doc_path, doc_json)
+                        self._add_checksum(doc_path, doc_json)
+
+                        # 导出 FAISS 索引文件
+                        await self._export_faiss_index(zf, kb_helper, kb_id)
+
+                        # 导出知识库多媒体文件
+                        await self._export_kb_media_files(zf, kb_helper, kb_id)
+
+                    if progress_callback:
+                        await progress_callback(
+                            "kb_documents", total_kbs, total_kbs, "知识库文档导出完成"
+                        )
+
+                # 3. 导出配置文件
+                if progress_callback:
+                    await progress_callback("config", 0, 100, "正在导出配置文件...")
+                if os.path.exists(self.config_path):
+                    with open(self.config_path, encoding="utf-8") as f:
+                        config_content = f.read()
+                    zf.writestr("config/cmd_config.json", config_content)
+                    self._add_checksum("config/cmd_config.json", config_content)
+                if progress_callback:
+                    await progress_callback("config", 100, 100, "配置文件导出完成")
+
+                # 4. 导出附件文件
+                if progress_callback:
+                    await progress_callback("attachments", 0, 100, "正在导出附件...")
+                await self._export_attachments(zf, main_data.get("attachments", []))
+                if progress_callback:
+                    await progress_callback("attachments", 100, 100, "附件导出完成")
+
+                # 5. 导出插件和其他目录
+                if progress_callback:
+                    await progress_callback(
+                        "directories", 0, 100, "正在导出插件和数据目录..."
+                    )
+                dir_stats = await self._export_directories(zf)
+                if progress_callback:
+                    await progress_callback("directories", 100, 100, "目录导出完成")
+
+                # 6. 生成 manifest
+                if progress_callback:
+                    await progress_callback("manifest", 0, 100, "正在生成清单...")
+                manifest = self._generate_manifest(main_data, kb_meta_data, dir_stats)
+                manifest_json = json.dumps(manifest, ensure_ascii=False, indent=2)
+                zf.writestr("manifest.json", manifest_json)
+                if progress_callback:
+                    await progress_callback("manifest", 100, 100, "清单生成完成")
+
+            logger.info(f"备份导出完成: {zip_path}")
+            return zip_path
+
+        except Exception as e:
+            logger.error(f"备份导出失败: {e}")
+            # 清理失败的文件
+            if os.path.exists(zip_path):
+                os.remove(zip_path)
+            raise
+
+    async def _export_main_database(self) -> dict[str, list[dict]]:
+        """导出主数据库所有表"""
+        export_data: dict[str, list[dict]] = {}
+
+        async with self.main_db.get_db() as session:
+            for table_name, model_class in MAIN_DB_MODELS.items():
+                try:
+                    result = await session.execute(select(model_class))
+                    records = result.scalars().all()
+                    export_data[table_name] = [
+                        self._model_to_dict(record) for record in records
+                    ]
+                    logger.debug(
+                        f"导出表 {table_name}: {len(export_data[table_name])} 条记录"
+                    )
+                except Exception as e:
+                    logger.warning(f"导出表 {table_name} 失败: {e}")
+                    export_data[table_name] = []
+
+        return export_data
+
+    async def _export_kb_metadata(self) -> dict[str, list[dict]]:
+        """导出知识库元数据库"""
+        if not self.kb_manager:
+            return {"knowledge_bases": [], "kb_documents": [], "kb_media": []}
+
+        export_data: dict[str, list[dict]] = {}
+
+        async with self.kb_manager.kb_db.get_db() as session:
+            for table_name, model_class in KB_METADATA_MODELS.items():
+                try:
+                    result = await session.execute(select(model_class))
+                    records = result.scalars().all()
+                    export_data[table_name] = [
+                        self._model_to_dict(record) for record in records
+                    ]
+                    logger.debug(
+                        f"导出知识库表 {table_name}: {len(export_data[table_name])} 条记录"
+                    )
+                except Exception as e:
+                    logger.warning(f"导出知识库表 {table_name} 失败: {e}")
+                    export_data[table_name] = []
+
+        return export_data
+
+    async def _export_kb_documents(self, kb_helper: Any) -> dict[str, Any]:
+        """导出知识库的文档块数据"""
+        try:
+            from astrbot.core.db.vec_db.faiss_impl.vec_db import FaissVecDB
+
+            vec_db: FaissVecDB = kb_helper.vec_db
+            if not vec_db or not vec_db.document_storage:
+                return {"documents": []}
+
+            # 获取所有文档
+            docs = await vec_db.document_storage.get_documents(
+                metadata_filters={},
+                offset=0,
+                limit=None,  # 获取全部
+            )
+
+            return {"documents": docs}
+        except Exception as e:
+            logger.warning(f"导出知识库文档失败: {e}")
+            return {"documents": []}
+
+    async def _export_faiss_index(
+        self,
+        zf: zipfile.ZipFile,
+        kb_helper: Any,
+        kb_id: str,
+    ) -> None:
+        """导出 FAISS 索引文件"""
+        try:
+            index_path = kb_helper.kb_dir / "index.faiss"
+            if index_path.exists():
+                archive_path = f"databases/kb_{kb_id}/index.faiss"
+                zf.write(str(index_path), archive_path)
+                logger.debug(f"导出 FAISS 索引: {archive_path}")
+        except Exception as e:
+            logger.warning(f"导出 FAISS 索引失败: {e}")
+
+    async def _export_kb_media_files(
+        self, zf: zipfile.ZipFile, kb_helper: Any, kb_id: str
+    ) -> None:
+        """导出知识库的多媒体文件"""
+        try:
+            media_dir = kb_helper.kb_medias_dir
+            if not media_dir.exists():
+                return
+
+            for root, _, files in os.walk(media_dir):
+                for file in files:
+                    file_path = Path(root) / file
+                    # 计算相对路径
+                    rel_path = file_path.relative_to(kb_helper.kb_dir)
+                    archive_path = f"files/kb_media/{kb_id}/{rel_path}"
+                    zf.write(str(file_path), archive_path)
+        except Exception as e:
+            logger.warning(f"导出知识库媒体文件失败: {e}")
+
+    async def _export_directories(
+        self, zf: zipfile.ZipFile
+    ) -> dict[str, dict[str, int]]:
+        """导出插件和其他数据目录
+
+        Returns:
+            dict: 每个目录的统计信息 {dir_name: {"files": count, "size": bytes}}
+        """
+        stats: dict[str, dict[str, int]] = {}
+        backup_directories = get_backup_directories()
+
+        for dir_name, dir_path in backup_directories.items():
+            full_path = Path(dir_path)
+            if not full_path.exists():
+                logger.debug(f"目录不存在，跳过: {full_path}")
+                continue
+
+            file_count = 0
+            total_size = 0
+
+            try:
+                for root, dirs, files in os.walk(full_path):
+                    # 跳过 __pycache__ 目录
+                    dirs[:] = [d for d in dirs if d != "__pycache__"]
+
+                    for file in files:
+                        # 跳过 .pyc 文件
+                        if file.endswith(".pyc"):
+                            continue
+
+                        file_path = Path(root) / file
+                        try:
+                            # 计算相对路径
+                            rel_path = file_path.relative_to(full_path)
+                            archive_path = f"directories/{dir_name}/{rel_path}"
+                            zf.write(str(file_path), archive_path)
+                            file_count += 1
+                            total_size += file_path.stat().st_size
+                        except Exception as e:
+                            logger.warning(f"导出文件 {file_path} 失败: {e}")
+
+                stats[dir_name] = {"files": file_count, "size": total_size}
+                logger.debug(
+                    f"导出目录 {dir_name}: {file_count} 个文件, {total_size} 字节"
+                )
+            except Exception as e:
+                logger.warning(f"导出目录 {dir_path} 失败: {e}")
+                stats[dir_name] = {"files": 0, "size": 0}
+
+        return stats
+
+    async def _export_attachments(
+        self, zf: zipfile.ZipFile, attachments: list[dict]
+    ) -> None:
+        """导出附件文件"""
+        for attachment in attachments:
+            try:
+                file_path = attachment.get("path", "")
+                if file_path and os.path.exists(file_path):
+                    # 使用 attachment_id 作为文件名
+                    attachment_id = attachment.get("attachment_id", "")
+                    ext = os.path.splitext(file_path)[1]
+                    archive_path = f"files/attachments/{attachment_id}{ext}"
+                    zf.write(file_path, archive_path)
+            except Exception as e:
+                logger.warning(f"导出附件失败: {e}")
+
+    def _model_to_dict(self, record: Any) -> dict:
+        """将 SQLModel 实例转换为字典
+
+        这是数据库无关的序列化方式，支持未来迁移到其他数据库。
+        """
+        # 使用 SQLModel 内置的 model_dump 方法（如果可用）
+        if hasattr(record, "model_dump"):
+            data = record.model_dump(mode="python")
+            # 处理 datetime 类型
+            for key, value in data.items():
+                if isinstance(value, datetime):
+                    data[key] = value.isoformat()
+            return data
+
+        # 回退到手动提取
+        data = {}
+        # 使用 inspect 获取表信息
+        from sqlalchemy import inspect as sa_inspect
+
+        mapper = sa_inspect(record.__class__)
+        for column in mapper.columns:
+            value = getattr(record, column.name)
+            # 处理 datetime 类型 - 统一转为 ISO 格式字符串
+            if isinstance(value, datetime):
+                value = value.isoformat()
+            data[column.name] = value
+        return data
+
+    def _add_checksum(self, path: str, content: str | bytes) -> None:
+        """计算并添加文件校验和"""
+        if isinstance(content, str):
+            content = content.encode("utf-8")
+        checksum = hashlib.sha256(content).hexdigest()
+        self._checksums[path] = f"sha256:{checksum}"
+
+    def _generate_manifest(
+        self,
+        main_data: dict[str, list[dict]],
+        kb_meta_data: dict[str, list[dict]],
+        dir_stats: dict[str, dict[str, int]] | None = None,
+    ) -> dict:
+        """生成备份清单"""
+        if dir_stats is None:
+            dir_stats = {}
+        # 收集知识库 ID
+        kb_document_tables = {}
+        if self.kb_manager:
+            for kb_id in self.kb_manager.kb_insts.keys():
+                kb_document_tables[kb_id] = "documents"
+
+        # 收集附件文件列表
+        attachment_files = []
+        for attachment in main_data.get("attachments", []):
+            attachment_id = attachment.get("attachment_id", "")
+            path = attachment.get("path", "")
+            if attachment_id and path:
+                ext = os.path.splitext(path)[1]
+                attachment_files.append(f"{attachment_id}{ext}")
+
+        # 收集知识库媒体文件
+        kb_media_files: dict[str, list[str]] = {}
+        if self.kb_manager:
+            for kb_id, kb_helper in self.kb_manager.kb_insts.items():
+                media_files: list[str] = []
+                media_dir = kb_helper.kb_medias_dir
+                if media_dir.exists():
+                    for root, _, files in os.walk(media_dir):
+                        for file in files:
+                            media_files.append(file)
+                if media_files:
+                    kb_media_files[kb_id] = media_files
+
+        manifest = {
+            "version": BACKUP_MANIFEST_VERSION,
+            "astrbot_version": VERSION,
+            "exported_at": datetime.now(timezone.utc).isoformat(),
+            "origin": "exported",  # 标记备份来源：exported=本实例导出, uploaded=用户上传
+            "schema_version": {
+                "main_db": "v4",
+                "kb_db": "v1",
+            },
+            "tables": {
+                "main_db": list(main_data.keys()),
+                "kb_metadata": list(kb_meta_data.keys()),
+                "kb_documents": kb_document_tables,
+            },
+            "files": {
+                "attachments": attachment_files,
+                "kb_media": kb_media_files,
+            },
+            "directories": list(dir_stats.keys()),
+            "checksums": self._checksums,
+            "statistics": {
+                "main_db": {
+                    table: len(records) for table, records in main_data.items()
+                },
+                "kb_metadata": {
+                    table: len(records) for table, records in kb_meta_data.items()
+                },
+                "directories": dir_stats,
+            },
+        }
+
+        return manifest

astrbot/core/backup/importer.py

@@ -0,0 +1,761 @@
+"""AstrBot 数据导入器
+
+负责从 ZIP 备份文件恢复所有数据。
+导入时进行版本校验：
+- 主版本（前两位）不同时直接拒绝导入
+- 小版本（第三位）不同时提示警告，用户可选择强制导入
+- 版本匹配时也需要用户确认
+"""
+
+import json
+import os
+import shutil
+import zipfile
+from dataclasses import dataclass, field
+from datetime import datetime
+from pathlib import Path
+from typing import TYPE_CHECKING, Any
+
+from sqlalchemy import delete
+
+from astrbot.core import logger
+from astrbot.core.config.default import VERSION
+from astrbot.core.db import BaseDatabase
+from astrbot.core.utils.astrbot_path import (
+    get_astrbot_data_path,
+    get_astrbot_knowledge_base_path,
+)
+from astrbot.core.utils.version_comparator import VersionComparator
+
+# 从共享常量模块导入
+from .constants import (
+    KB_METADATA_MODELS,
+    MAIN_DB_MODELS,
+    get_backup_directories,
+)
+
+if TYPE_CHECKING:
+    from astrbot.core.knowledge_base.kb_mgr import KnowledgeBaseManager
+
+
+def _get_major_version(version_str: str) -> str:
+    """提取版本的主版本部分（前两位）
+
+    Args:
+        version_str: 版本字符串，如 "4.9.1", "4.10.0-beta"
+
+    Returns:
+        主版本字符串，如 "4.9", "4.10"
+    """
+    if not version_str:
+        return "0.0"
+    # 移除 v 前缀和预发布标签
+    version = version_str.lower().replace("v", "").split("-")[0].split("+")[0]
+    parts = [p for p in version.split(".") if p]  # 过滤空字符串
+    if len(parts) >= 2:
+        return f"{parts[0]}.{parts[1]}"
+    elif len(parts) == 1 and parts[0]:
+        return f"{parts[0]}.0"
+    return "0.0"
+
+
+CMD_CONFIG_FILE_PATH = os.path.join(get_astrbot_data_path(), "cmd_config.json")
+KB_PATH = get_astrbot_knowledge_base_path()
+
+
+@dataclass
+class ImportPreCheckResult:
+    """导入预检查结果
+
+    用于在实际导入前检查备份文件的版本兼容性，
+    并返回确认信息让用户决定是否继续导入。
+    """
+
+    # 检查是否通过（文件有效且版本可导入）
+    valid: bool = False
+    # 是否可以导入（版本兼容）
+    can_import: bool = False
+    # 版本状态: match（完全匹配）, minor_diff（小版本差异）, major_diff（主版本不同，拒绝）
+    version_status: str = ""
+    # 备份文件中的 AstrBot 版本
+    backup_version: str = ""
+    # 当前运行的 AstrBot 版本
+    current_version: str = VERSION
+    # 备份创建时间
+    backup_time: str = ""
+    # 确认消息（显示给用户）
+    confirm_message: str = ""
+    # 警告消息列表
+    warnings: list[str] = field(default_factory=list)
+    # 错误消息（如果检查失败）
+    error: str = ""
+    # 备份包含的内容摘要
+    backup_summary: dict = field(default_factory=dict)
+
+    def to_dict(self) -> dict:
+        return {
+            "valid": self.valid,
+            "can_import": self.can_import,
+            "version_status": self.version_status,
+            "backup_version": self.backup_version,
+            "current_version": self.current_version,
+            "backup_time": self.backup_time,
+            "confirm_message": self.confirm_message,
+            "warnings": self.warnings,
+            "error": self.error,
+            "backup_summary": self.backup_summary,
+        }
+
+
+class ImportResult:
+    """导入结果"""
+
+    def __init__(self):
+        self.success = True
+        self.imported_tables: dict[str, int] = {}
+        self.imported_files: dict[str, int] = {}
+        self.imported_directories: dict[str, int] = {}
+        self.warnings: list[str] = []
+        self.errors: list[str] = []
+
+    def add_warning(self, msg: str) -> None:
+        self.warnings.append(msg)
+        logger.warning(msg)
+
+    def add_error(self, msg: str) -> None:
+        self.errors.append(msg)
+        self.success = False
+        logger.error(msg)
+
+    def to_dict(self) -> dict:
+        return {
+            "success": self.success,
+            "imported_tables": self.imported_tables,
+            "imported_files": self.imported_files,
+            "imported_directories": self.imported_directories,
+            "warnings": self.warnings,
+            "errors": self.errors,
+        }
+
+
+class AstrBotImporter:
+    """AstrBot 数据导入器
+
+    导入备份文件中的所有数据，包括：
+    - 主数据库所有表
+    - 知识库元数据和文档
+    - 配置文件
+    - 附件文件
+    - 知识库多媒体文件
+    - 插件目录（data/plugins）
+    - 插件数据目录（data/plugin_data）
+    - 配置目录（data/config）
+    - T2I 模板目录（data/t2i_templates）
+    - WebChat 数据目录（data/webchat）
+    - 临时文件目录（data/temp）
+    """
+
+    def __init__(
+        self,
+        main_db: BaseDatabase,
+        kb_manager: "KnowledgeBaseManager | None" = None,
+        config_path: str = CMD_CONFIG_FILE_PATH,
+        kb_root_dir: str = KB_PATH,
+    ):
+        self.main_db = main_db
+        self.kb_manager = kb_manager
+        self.config_path = config_path
+        self.kb_root_dir = kb_root_dir
+
+    def pre_check(self, zip_path: str) -> ImportPreCheckResult:
+        """预检查备份文件
+
+        在实际导入前检查备份文件的有效性和版本兼容性。
+        返回检查结果供前端显示确认对话框。
+
+        Args:
+            zip_path: ZIP 备份文件路径
+
+        Returns:
+            ImportPreCheckResult: 预检查结果
+        """
+        result = ImportPreCheckResult()
+        result.current_version = VERSION
+
+        if not os.path.exists(zip_path):
+            result.error = f"备份文件不存在: {zip_path}"
+            return result
+
+        try:
+            with zipfile.ZipFile(zip_path, "r") as zf:
+                # 读取 manifest
+                try:
+                    manifest_data = zf.read("manifest.json")
+                    manifest = json.loads(manifest_data)
+                except KeyError:
+                    result.error = "备份文件缺少 manifest.json，不是有效的 AstrBot 备份"
+                    return result
+                except json.JSONDecodeError as e:
+                    result.error = f"manifest.json 格式错误: {e}"
+                    return result
+
+                # 提取基本信息
+                result.backup_version = manifest.get("astrbot_version", "未知")
+                result.backup_time = manifest.get("exported_at", "未知")
+                result.valid = True
+
+                # 构建备份摘要
+                result.backup_summary = {
+                    "tables": list(manifest.get("tables", {}).keys()),
+                    "has_knowledge_bases": manifest.get("has_knowledge_bases", False),
+                    "has_config": manifest.get("has_config", False),
+                    "directories": manifest.get("directories", []),
+                }
+
+                # 检查版本兼容性
+                version_check = self._check_version_compatibility(result.backup_version)
+                result.version_status = version_check["status"]
+                result.can_import = version_check["can_import"]
+
+                # 版本信息由前端根据 version_status 和 i18n 生成显示
+                # 不再将版本消息添加到 warnings 列表中，避免中文硬编码
+                # warnings 列表保留用于其他非版本相关的警告
+
+                return result
+
+        except zipfile.BadZipFile:
+            result.error = "无效的 ZIP 文件"
+            return result
+        except Exception as e:
+            result.error = f"检查备份文件失败: {e}"
+            return result
+
+    def _check_version_compatibility(self, backup_version: str) -> dict:
+        """检查版本兼容性
+
+        规则：
+        - 主版本（前两位，如 4.9）必须一致，否则拒绝
+        - 小版本（第三位，如 4.9.1 vs 4.9.2）不同时，警告但允许导入
+
+        Returns:
+            dict: {status, can_import, message}
+        """
+        if not backup_version:
+            return {
+                "status": "major_diff",
+                "can_import": False,
+                "message": "备份文件缺少版本信息",
+            }
+
+        # 提取主版本（前两位）进行比较
+        backup_major = _get_major_version(backup_version)
+        current_major = _get_major_version(VERSION)
+
+        # 比较主版本
+        if VersionComparator.compare_version(backup_major, current_major) != 0:
+            return {
+                "status": "major_diff",
+                "can_import": False,
+                "message": (
+                    f"主版本不兼容: 备份版本 {backup_version}, 当前版本 {VERSION}。"
+                    f"跨主版本导入可能导致数据损坏，请使用相同主版本的 AstrBot。"
+                ),
+            }
+
+        # 比较完整版本
+        version_cmp = VersionComparator.compare_version(backup_version, VERSION)
+        if version_cmp != 0:
+            return {
+                "status": "minor_diff",
+                "can_import": True,
+                "message": (
+                    f"小版本差异: 备份版本 {backup_version}, 当前版本 {VERSION}。"
+                ),
+            }
+
+        return {
+            "status": "match",
+            "can_import": True,
+            "message": "版本匹配",
+        }
+
+    async def import_all(
+        self,
+        zip_path: str,
+        mode: str = "replace",  # "replace" 清空后导入
+        progress_callback: Any | None = None,
+    ) -> ImportResult:
+        """从 ZIP 文件导入所有数据
+
+        Args:
+            zip_path: ZIP 备份文件路径
+            mode: 导入模式，目前仅支持 "replace"（清空后导入）
+            progress_callback: 进度回调函数，接收参数 (stage, current, total, message)
+
+        Returns:
+            ImportResult: 导入结果
+        """
+        result = ImportResult()
+
+        if not os.path.exists(zip_path):
+            result.add_error(f"备份文件不存在: {zip_path}")
+            return result
+
+        logger.info(f"开始从 {zip_path} 导入备份")
+
+        try:
+            with zipfile.ZipFile(zip_path, "r") as zf:
+                # 1. 读取并验证 manifest
+                if progress_callback:
+                    await progress_callback("validate", 0, 100, "正在验证备份文件...")
+
+                try:
+                    manifest_data = zf.read("manifest.json")
+                    manifest = json.loads(manifest_data)
+                except KeyError:
+                    result.add_error("备份文件缺少 manifest.json")
+                    return result
+                except json.JSONDecodeError as e:
+                    result.add_error(f"manifest.json 格式错误: {e}")
+                    return result
+
+                # 版本校验
+                try:
+                    self._validate_version(manifest)
+                except ValueError as e:
+                    result.add_error(str(e))
+                    return result
+
+                if progress_callback:
+                    await progress_callback("validate", 100, 100, "验证完成")
+
+                # 2. 导入主数据库
+                if progress_callback:
+                    await progress_callback("main_db", 0, 100, "正在导入主数据库...")
+
+                try:
+                    main_data_content = zf.read("databases/main_db.json")
+                    main_data = json.loads(main_data_content)
+
+                    if mode == "replace":
+                        await self._clear_main_db()
+
+                    imported = await self._import_main_database(main_data)
+                    result.imported_tables.update(imported)
+                except Exception as e:
+                    result.add_error(f"导入主数据库失败: {e}")
+                    return result
+
+                if progress_callback:
+                    await progress_callback("main_db", 100, 100, "主数据库导入完成")
+
+                # 3. 导入知识库
+                if self.kb_manager and "databases/kb_metadata.json" in zf.namelist():
+                    if progress_callback:
+                        await progress_callback("kb", 0, 100, "正在导入知识库...")
+
+                    try:
+                        kb_meta_content = zf.read("databases/kb_metadata.json")
+                        kb_meta_data = json.loads(kb_meta_content)
+
+                        if mode == "replace":
+                            await self._clear_kb_data()
+
+                        await self._import_knowledge_bases(zf, kb_meta_data, result)
+                    except Exception as e:
+                        result.add_warning(f"导入知识库失败: {e}")
+
+                    if progress_callback:
+                        await progress_callback("kb", 100, 100, "知识库导入完成")
+
+                # 4. 导入配置文件
+                if progress_callback:
+                    await progress_callback("config", 0, 100, "正在导入配置文件...")
+
+                if "config/cmd_config.json" in zf.namelist():
+                    try:
+                        config_content = zf.read("config/cmd_config.json")
+                        # 备份现有配置
+                        if os.path.exists(self.config_path):
+                            backup_path = f"{self.config_path}.bak"
+                            shutil.copy2(self.config_path, backup_path)
+
+                        with open(self.config_path, "wb") as f:
+                            f.write(config_content)
+                        result.imported_files["config"] = 1
+                    except Exception as e:
+                        result.add_warning(f"导入配置文件失败: {e}")
+
+                if progress_callback:
+                    await progress_callback("config", 100, 100, "配置文件导入完成")
+
+                # 5. 导入附件文件
+                if progress_callback:
+                    await progress_callback("attachments", 0, 100, "正在导入附件...")
+
+                attachment_count = await self._import_attachments(
+                    zf, main_data.get("attachments", [])
+                )
+                result.imported_files["attachments"] = attachment_count
+
+                if progress_callback:
+                    await progress_callback("attachments", 100, 100, "附件导入完成")
+
+                # 6. 导入插件和其他目录
+                if progress_callback:
+                    await progress_callback(
+                        "directories", 0, 100, "正在导入插件和数据目录..."
+                    )
+
+                dir_stats = await self._import_directories(zf, manifest, result)
+                result.imported_directories = dir_stats
+
+                if progress_callback:
+                    await progress_callback("directories", 100, 100, "目录导入完成")
+
+            logger.info(f"备份导入完成: {result.to_dict()}")
+            return result
+
+        except zipfile.BadZipFile:
+            result.add_error("无效的 ZIP 文件")
+            return result
+        except Exception as e:
+            result.add_error(f"导入失败: {e}")
+            return result
+
+    def _validate_version(self, manifest: dict) -> None:
+        """验证版本兼容性 - 仅允许相同主版本导入
+
+        注意：此方法仅在 import_all 中调用，用于双重校验。
+        前端应先调用 pre_check 获取详细的版本信息并让用户确认。
+        """
+        backup_version = manifest.get("astrbot_version")
+        if not backup_version:
+            raise ValueError("备份文件缺少版本信息")
+
+        # 使用新的版本兼容性检查
+        version_check = self._check_version_compatibility(backup_version)
+
+        if version_check["status"] == "major_diff":
+            raise ValueError(version_check["message"])
+
+        # minor_diff 和 match 都允许导入
+        if version_check["status"] == "minor_diff":
+            logger.warning(f"版本差异警告: {version_check['message']}")
+
+    async def _clear_main_db(self) -> None:
+        """清空主数据库所有表"""
+        async with self.main_db.get_db() as session:
+            async with session.begin():
+                for table_name, model_class in MAIN_DB_MODELS.items():
+                    try:
+                        await session.execute(delete(model_class))
+                        logger.debug(f"已清空表 {table_name}")
+                    except Exception as e:
+                        logger.warning(f"清空表 {table_name} 失败: {e}")
+
+    async def _clear_kb_data(self) -> None:
+        """清空知识库数据"""
+        if not self.kb_manager:
+            return
+
+        # 清空知识库元数据表
+        async with self.kb_manager.kb_db.get_db() as session:
+            async with session.begin():
+                for table_name, model_class in KB_METADATA_MODELS.items():
+                    try:
+                        await session.execute(delete(model_class))
+                        logger.debug(f"已清空知识库表 {table_name}")
+                    except Exception as e:
+                        logger.warning(f"清空知识库表 {table_name} 失败: {e}")
+
+        # 删除知识库文件目录
+        for kb_id in list(self.kb_manager.kb_insts.keys()):
+            try:
+                kb_helper = self.kb_manager.kb_insts[kb_id]
+                await kb_helper.terminate()
+                if kb_helper.kb_dir.exists():
+                    shutil.rmtree(kb_helper.kb_dir)
+            except Exception as e:
+                logger.warning(f"清理知识库 {kb_id} 失败: {e}")
+
+        self.kb_manager.kb_insts.clear()
+
+    async def _import_main_database(
+        self, data: dict[str, list[dict]]
+    ) -> dict[str, int]:
+        """导入主数据库数据"""
+        imported: dict[str, int] = {}
+
+        async with self.main_db.get_db() as session:
+            async with session.begin():
+                for table_name, rows in data.items():
+                    model_class = MAIN_DB_MODELS.get(table_name)
+                    if not model_class:
+                        logger.warning(f"未知的表: {table_name}")
+                        continue
+
+                    count = 0
+                    for row in rows:
+                        try:
+                            # 转换 datetime 字符串为 datetime 对象
+                            row = self._convert_datetime_fields(row, model_class)
+                            obj = model_class(**row)
+                            session.add(obj)
+                            count += 1
+                        except Exception as e:
+                            logger.warning(f"导入记录到 {table_name} 失败: {e}")
+
+                    imported[table_name] = count
+                    logger.debug(f"导入表 {table_name}: {count} 条记录")
+
+        return imported
+
+    async def _import_knowledge_bases(
+        self,
+        zf: zipfile.ZipFile,
+        kb_meta_data: dict[str, list[dict]],
+        result: ImportResult,
+    ) -> None:
+        """导入知识库数据"""
+        if not self.kb_manager:
+            return
+
+        # 1. 导入知识库元数据
+        async with self.kb_manager.kb_db.get_db() as session:
+            async with session.begin():
+                for table_name, rows in kb_meta_data.items():
+                    model_class = KB_METADATA_MODELS.get(table_name)
+                    if not model_class:
+                        continue
+
+                    count = 0
+                    for row in rows:
+                        try:
+                            row = self._convert_datetime_fields(row, model_class)
+                            obj = model_class(**row)
+                            session.add(obj)
+                            count += 1
+                        except Exception as e:
+                            logger.warning(f"导入知识库记录到 {table_name} 失败: {e}")
+
+                    result.imported_tables[f"kb_{table_name}"] = count
+
+        # 2. 导入每个知识库的文档和文件
+        for kb_data in kb_meta_data.get("knowledge_bases", []):
+            kb_id = kb_data.get("kb_id")
+            if not kb_id:
+                continue
+
+            # 创建知识库目录
+            kb_dir = Path(self.kb_root_dir) / kb_id
+            kb_dir.mkdir(parents=True, exist_ok=True)
+
+            # 导入文档数据
+            doc_path = f"databases/kb_{kb_id}/documents.json"
+            if doc_path in zf.namelist():
+                try:
+                    doc_content = zf.read(doc_path)
+                    doc_data = json.loads(doc_content)
+
+                    # 导入到文档存储数据库
+                    await self._import_kb_documents(kb_id, doc_data)
+                except Exception as e:
+                    result.add_warning(f"导入知识库 {kb_id} 的文档失败: {e}")
+
+            # 导入 FAISS 索引
+            faiss_path = f"databases/kb_{kb_id}/index.faiss"
+            if faiss_path in zf.namelist():
+                try:
+                    target_path = kb_dir / "index.faiss"
+                    with zf.open(faiss_path) as src, open(target_path, "wb") as dst:
+                        dst.write(src.read())
+                except Exception as e:
+                    result.add_warning(f"导入知识库 {kb_id} 的 FAISS 索引失败: {e}")
+
+            # 导入媒体文件
+            media_prefix = f"files/kb_media/{kb_id}/"
+            for name in zf.namelist():
+                if name.startswith(media_prefix):
+                    try:
+                        rel_path = name[len(media_prefix) :]
+                        target_path = kb_dir / rel_path
+                        target_path.parent.mkdir(parents=True, exist_ok=True)
+                        with zf.open(name) as src, open(target_path, "wb") as dst:
+                            dst.write(src.read())
+                    except Exception as e:
+                        result.add_warning(f"导入媒体文件 {name} 失败: {e}")
+
+        # 3. 重新加载知识库实例
+        await self.kb_manager.load_kbs()
+
+    async def _import_kb_documents(self, kb_id: str, doc_data: dict) -> None:
+        """导入知识库文档到向量数据库"""
+        from astrbot.core.db.vec_db.faiss_impl.document_storage import DocumentStorage
+
+        kb_dir = Path(self.kb_root_dir) / kb_id
+        doc_db_path = kb_dir / "doc.db"
+
+        # 初始化文档存储
+        doc_storage = DocumentStorage(str(doc_db_path))
+        await doc_storage.initialize()
+
+        try:
+            documents = doc_data.get("documents", [])
+            for doc in documents:
+                try:
+                    await doc_storage.insert_document(
+                        doc_id=doc.get("doc_id", ""),
+                        text=doc.get("text", ""),
+                        metadata=json.loads(doc.get("metadata", "{}")),
+                    )
+                except Exception as e:
+                    logger.warning(f"导入文档块失败: {e}")
+        finally:
+            await doc_storage.close()
+
+    async def _import_attachments(
+        self,
+        zf: zipfile.ZipFile,
+        attachments: list[dict],
+    ) -> int:
+        """导入附件文件"""
+        count = 0
+
+        attachments_dir = Path(self.config_path).parent / "attachments"
+        attachments_dir.mkdir(parents=True, exist_ok=True)
+
+        attachment_prefix = "files/attachments/"
+        for name in zf.namelist():
+            if name.startswith(attachment_prefix) and name != attachment_prefix:
+                try:
+                    # 从附件记录中找到原始路径
+                    attachment_id = os.path.splitext(os.path.basename(name))[0]
+                    original_path = None
+                    for att in attachments:
+                        if att.get("attachment_id") == attachment_id:
+                            original_path = att.get("path")
+                            break
+
+                    if original_path:
+                        target_path = Path(original_path)
+                    else:
+                        target_path = attachments_dir / os.path.basename(name)
+
+                    target_path.parent.mkdir(parents=True, exist_ok=True)
+                    with zf.open(name) as src, open(target_path, "wb") as dst:
+                        dst.write(src.read())
+                    count += 1
+                except Exception as e:
+                    logger.warning(f"导入附件 {name} 失败: {e}")
+
+        return count
+
+    async def _import_directories(
+        self,
+        zf: zipfile.ZipFile,
+        manifest: dict,
+        result: ImportResult,
+    ) -> dict[str, int]:
+        """导入插件和其他数据目录
+
+        Args:
+            zf: ZIP 文件对象
+            manifest: 备份清单
+            result: 导入结果对象
+
+        Returns:
+            dict: 每个目录导入的文件数量
+        """
+        dir_stats: dict[str, int] = {}
+
+        # 检查备份版本是否支持目录备份（需要版本 >= 1.1）
+        backup_version = manifest.get("version", "1.0")
+        if VersionComparator.compare_version(backup_version, "1.1") < 0:
+            logger.info("备份版本不支持目录备份，跳过目录导入")
+            return dir_stats
+
+        backed_up_dirs = manifest.get("directories", [])
+        backup_directories = get_backup_directories()
+
+        for dir_name in backed_up_dirs:
+            if dir_name not in backup_directories:
+                result.add_warning(f"未知的目录类型: {dir_name}")
+                continue
+
+            target_dir = Path(backup_directories[dir_name])
+            archive_prefix = f"directories/{dir_name}/"
+
+            file_count = 0
+
+            try:
+                # 获取该目录下的所有文件
+                dir_files = [
+                    name
+                    for name in zf.namelist()
+                    if name.startswith(archive_prefix) and name != archive_prefix
+                ]
+
+                if not dir_files:
+                    continue
+
+                # 备份现有目录（如果存在）
+                if target_dir.exists():
+                    backup_path = Path(f"{target_dir}.bak")
+                    if backup_path.exists():
+                        shutil.rmtree(backup_path)
+                    shutil.move(str(target_dir), str(backup_path))
+                    logger.debug(f"已备份现有目录 {target_dir} 到 {backup_path}")
+
+                # 创建目标目录
+                target_dir.mkdir(parents=True, exist_ok=True)
+
+                # 解压文件
+                for name in dir_files:
+                    try:
+                        # 计算相对路径
+                        rel_path = name[len(archive_prefix) :]
+                        if not rel_path:  # 跳过目录条目
+                            continue
+
+                        target_path = target_dir / rel_path
+                        target_path.parent.mkdir(parents=True, exist_ok=True)
+
+                        with zf.open(name) as src, open(target_path, "wb") as dst:
+                            dst.write(src.read())
+                        file_count += 1
+                    except Exception as e:
+                        result.add_warning(f"导入文件 {name} 失败: {e}")
+
+                dir_stats[dir_name] = file_count
+                logger.debug(f"导入目录 {dir_name}: {file_count} 个文件")
+
+            except Exception as e:
+                result.add_warning(f"导入目录 {dir_name} 失败: {e}")
+                dir_stats[dir_name] = 0
+
+        return dir_stats
+
+    def _convert_datetime_fields(self, row: dict, model_class: type) -> dict:
+        """转换 datetime 字符串字段为 datetime 对象"""
+        result = row.copy()
+
+        # 获取模型的 datetime 字段
+        from sqlalchemy import inspect as sa_inspect
+
+        try:
+            mapper = sa_inspect(model_class)
+            for column in mapper.columns:
+                if column.name in result and result[column.name] is not None:
+                    # 检查是否是 datetime 类型的列
+                    from sqlalchemy import DateTime
+
+                    if isinstance(column.type, DateTime):
+                        value = result[column.name]
+                        if isinstance(value, str):
+                            # 解析 ISO 格式的日期时间字符串
+                            result[column.name] = datetime.fromisoformat(value)
+        except Exception:
+            pass
+
+        return result

astrbot/core/config/astrbot_config.py

@@ -24,6 +24,10 @@ class AstrBotConfig(dict):
     - 如果传入了 schema，将会通过 schema 解析出 default_config，此时传入的 default_config 会被忽略。
     """
 
+    config_path: str
+    default_config: dict
+    schema: dict | None
+
     def __init__(
         self,
         config_path: str = ASTRBOT_CONFIG_PATH,
@@ -76,6 +80,8 @@ class AstrBotConfig(dict):
                 if v["type"] == "object":
                     conf[k] = {}
                     _parse_schema(v["items"], conf[k])
+                elif v["type"] == "template_list":
+                    conf[k] = default
                 else:
                     conf[k] = default
 

astrbot/core/config/i18n_utils.py

@@ -0,0 +1,111 @@
+"""
+配置元数据国际化工具
+
+提供配置元数据的国际化键转换功能
+"""
+
+from typing import Any
+
+
+class ConfigMetadataI18n:
+    """配置元数据国际化转换器"""
+
+    @staticmethod
+    def _get_i18n_key(group: str, section: str, field: str, attr: str) -> str:
+        """
+        生成国际化键
+
+        Args:
+            group: 配置组，如 'ai_group', 'platform_group'
+            section: 配置节，如 'agent_runner', 'general'
+            field: 字段名，如 'enable', 'default_provider'
+            attr: 属性类型，如 'description', 'hint', 'labels'
+
+        Returns:
+            国际化键，格式如: 'ai_group.agent_runner.enable.description'
+        """
+        if field:
+            return f"{group}.{section}.{field}.{attr}"
+        else:
+            return f"{group}.{section}.{attr}"
+
+    @staticmethod
+    def convert_to_i18n_keys(metadata: dict[str, Any]) -> dict[str, Any]:
+        """
+        将配置元数据转换为使用国际化键
+
+        Args:
+            metadata: 原始配置元数据字典
+
+        Returns:
+            使用国际化键的配置元数据字典
+        """
+        result = {}
+
+        for group_key, group_data in metadata.items():
+            group_result = {
+                "name": f"{group_key}.name",
+                "metadata": {},
+            }
+
+            for section_key, section_data in group_data.get("metadata", {}).items():
+                section_result = {
+                    "description": f"{group_key}.{section_key}.description",
+                    "type": section_data.get("type"),
+                }
+
+                # 复制其他属性
+                for key in ["items", "condition", "_special", "invisible"]:
+                    if key in section_data:
+                        section_result[key] = section_data[key]
+
+                # 处理 hint
+                if "hint" in section_data:
+                    section_result["hint"] = f"{group_key}.{section_key}.hint"
+
+                # 处理 items 中的字段
+                if "items" in section_data and isinstance(section_data["items"], dict):
+                    items_result = {}
+                    for field_key, field_data in section_data["items"].items():
+                        # 处理嵌套的点号字段名（如 provider_settings.enable）
+                        field_name = field_key
+
+                        field_result = {}
+
+                        # 复制基本属性
+                        for attr in [
+                            "type",
+                            "condition",
+                            "_special",
+                            "invisible",
+                            "options",
+                            "slider",
+                        ]:
+                            if attr in field_data:
+                                field_result[attr] = field_data[attr]
+
+                        # 转换文本属性为国际化键
+                        if "description" in field_data:
+                            field_result["description"] = (
+                                f"{group_key}.{section_key}.{field_name}.description"
+                            )
+
+                        if "hint" in field_data:
+                            field_result["hint"] = (
+                                f"{group_key}.{section_key}.{field_name}.hint"
+                            )
+
+                        if "labels" in field_data:
+                            field_result["labels"] = (
+                                f"{group_key}.{section_key}.{field_name}.labels"
+                            )
+
+                        items_result[field_key] = field_result
+
+                    section_result["items"] = items_result
+
+                group_result["metadata"][section_key] = section_result
+
+            result[group_key] = group_result
+
+        return result

astrbot/core/conversation_mgr.py

@@ -69,6 +69,7 @@ class ConversationManager:
             persona_id=conv_v2.persona_id,
             created_at=created_at,
             updated_at=updated_at,
+            token_usage=conv_v2.token_usage,
         )
 
     async def new_conversation(
@@ -256,6 +257,7 @@ class ConversationManager:
         history: list[dict] | None = None,
         title: str | None = None,
         persona_id: str | None = None,
+        token_usage: int | None = None,
     ) -> None:
         """更新会话的对话.
 
@@ -263,6 +265,7 @@ class ConversationManager:
             unified_msg_origin (str): 统一的消息来源字符串。格式为 platform_name:message_type:session_id
             conversation_id (str): 对话 ID, 是 uuid 格式的字符串
             history (List[Dict]): 对话历史记录, 是一个字典列表, 每个字典包含 role 和 content 字段
+            token_usage (int | None): token 使用量。None 表示不更新
 
         """
         if not conversation_id:
@@ -274,6 +277,7 @@ class ConversationManager:
                 title=title,
                 persona_id=persona_id,
                 content=history,
+                token_usage=token_usage,
             )
 
     async def update_conversation_title(

astrbot/core/core_lifecycle.py

@@ -16,12 +16,12 @@ import time
 import traceback
 from asyncio import Queue
 
-from astrbot.core import LogBroker, logger, sp
+from astrbot.api import logger, sp
+from astrbot.core import LogBroker
 from astrbot.core.astrbot_config_mgr import AstrBotConfigManager
 from astrbot.core.config.default import VERSION
 from astrbot.core.conversation_mgr import ConversationManager
 from astrbot.core.db import BaseDatabase
-from astrbot.core.db.migration.migra_45_to_46 import migrate_45_to_46
 from astrbot.core.knowledge_base.kb_mgr import KnowledgeBaseManager
 from astrbot.core.persona_mgr import PersonaManager
 from astrbot.core.pipeline.scheduler import PipelineContext, PipelineScheduler
@@ -33,6 +33,8 @@ from astrbot.core.star.context import Context
 from astrbot.core.star.star_handler import EventType, star_handlers_registry, star_map
 from astrbot.core.umop_config_router import UmopConfigRouter
 from astrbot.core.updator import AstrBotUpdator
+from astrbot.core.utils.llm_metadata import update_llm_metadata
+from astrbot.core.utils.migra_helper import migra
 
 from . import astrbot_config, html_renderer
 from .event_bus import EventBus
@@ -88,6 +90,7 @@ class AstrBotCoreLifecycle:
 
         # 初始化 UMOP 配置路由器
         self.umop_config_router = UmopConfigRouter(sp=sp)
+        await self.umop_config_router.initialize()
 
         # 初始化 AstrBot 配置管理器
         self.astrbot_config_mgr = AstrBotConfigManager(
@@ -96,11 +99,16 @@ class AstrBotCoreLifecycle:
             sp=sp,
         )
 
-        # 4.5 to 4.6 migration for umop_config_router
+        # apply migration
         try:
-            await migrate_45_to_46(self.astrbot_config_mgr, self.umop_config_router)
+            await migra(
+                self.db,
+                self.astrbot_config_mgr,
+                self.umop_config_router,
+                self.astrbot_config_mgr,
+            )
         except Exception as e:
-            logger.error(f"Migration from version 4.5 to 4.6 failed: {e!s}")
+            logger.error(f"AstrBot migration failed: {e!s}")
             logger.error(traceback.format_exc())
 
         # 初始化事件队列
@@ -179,6 +187,8 @@ class AstrBotCoreLifecycle:
         # 初始化关闭控制面板的事件
         self.dashboard_shutdown_event = asyncio.Event()
 
+        asyncio.create_task(update_llm_metadata())
+
     def _load(self) -> None:
         """加载事件总线和任务并初始化."""
         # 创建一个异步任务来执行事件总线的 dispatch() 方法
@@ -191,7 +201,7 @@ class AstrBotCoreLifecycle:
         # 把插件中注册的所有协程函数注册到事件总线中并执行
         extra_tasks = []
         for task in self.star_context._register_tasks:
-            extra_tasks.append(asyncio.create_task(task, name=task.__name__))
+            extra_tasks.append(asyncio.create_task(task, name=task.__name__))  # type: ignore
 
         tasks_ = [event_bus_task, *extra_tasks]
         for task in tasks_:

astrbot/core/db/__init__.py

@@ -5,16 +5,20 @@ from contextlib import asynccontextmanager
 from dataclasses import dataclass
 
 from deprecated import deprecated
-from sqlalchemy.ext.asyncio import AsyncSession, create_async_engine
-from sqlalchemy.orm import sessionmaker
+from sqlalchemy.ext.asyncio import AsyncSession, async_sessionmaker, create_async_engine
 
 from astrbot.core.db.po import (
     Attachment,
+    ChatUIProject,
+    CommandConfig,
+    CommandConflict,
     ConversationV2,
     Persona,
     PlatformMessageHistory,
+    PlatformSession,
     PlatformStat,
     Preference,
+    SessionProjectRelation,
     Stats,
 )
 
@@ -31,7 +35,7 @@ class BaseDatabase(abc.ABC):
             echo=False,
             future=True,
         )
-        self.AsyncSessionLocal = sessionmaker(
+        self.AsyncSessionLocal = async_sessionmaker(
             self.engine,
             class_=AsyncSession,
             expire_on_commit=False,
@@ -150,6 +154,7 @@ class BaseDatabase(abc.ABC):
         title: str | None = None,
         persona_id: str | None = None,
         content: list[dict] | None = None,
+        token_usage: int | None = None,
     ) -> None:
         """Update a conversation's history."""
         ...
@@ -172,7 +177,7 @@ class BaseDatabase(abc.ABC):
         content: dict,
         sender_id: str | None = None,
         sender_name: str | None = None,
-    ) -> None:
+    ) -> PlatformMessageHistory:
         """Insert a new platform message history record."""
         ...
 
@@ -183,7 +188,7 @@ class BaseDatabase(abc.ABC):
         user_id: str,
         offset_sec: int = 86400,
     ) -> None:
-        """Delete platform message history records older than the specified offset."""
+        """Delete platform message history records newer than the specified offset."""
         ...
 
     @abc.abstractmethod
@@ -197,6 +202,14 @@ class BaseDatabase(abc.ABC):
         """Get platform message history for a specific user."""
         ...
 
+    @abc.abstractmethod
+    async def get_platform_message_history_by_id(
+        self,
+        message_id: int,
+    ) -> PlatformMessageHistory | None:
+        """Get a platform message history record by its ID."""
+        ...
+
     @abc.abstractmethod
     async def insert_attachment(
         self,
@@ -212,6 +225,27 @@ class BaseDatabase(abc.ABC):
         """Get an attachment by its ID."""
         ...
 
+    @abc.abstractmethod
+    async def get_attachments(self, attachment_ids: list[str]) -> list[Attachment]:
+        """Get multiple attachments by their IDs."""
+        ...
+
+    @abc.abstractmethod
+    async def delete_attachment(self, attachment_id: str) -> bool:
+        """Delete an attachment by its ID.
+
+        Returns True if the attachment was deleted, False if it was not found.
+        """
+        ...
+
+    @abc.abstractmethod
+    async def delete_attachments(self, attachment_ids: list[str]) -> int:
+        """Delete multiple attachments by their IDs.
+
+        Returns the number of attachments deleted.
+        """
+        ...
+
     @abc.abstractmethod
     async def insert_persona(
         self,
@@ -285,6 +319,76 @@ class BaseDatabase(abc.ABC):
         """Clear all preferences for a specific scope ID."""
         ...
 
+    @abc.abstractmethod
+    async def get_command_configs(self) -> list[CommandConfig]:
+        """Get all stored command configurations."""
+        ...
+
+    @abc.abstractmethod
+    async def get_command_config(self, handler_full_name: str) -> CommandConfig | None:
+        """Fetch a single command configuration by handler."""
+        ...
+
+    @abc.abstractmethod
+    async def upsert_command_config(
+        self,
+        handler_full_name: str,
+        plugin_name: str,
+        module_path: str,
+        original_command: str,
+        *,
+        resolved_command: str | None = None,
+        enabled: bool | None = None,
+        keep_original_alias: bool | None = None,
+        conflict_key: str | None = None,
+        resolution_strategy: str | None = None,
+        note: str | None = None,
+        extra_data: dict | None = None,
+        auto_managed: bool | None = None,
+    ) -> CommandConfig:
+        """Create or update a command configuration."""
+        ...
+
+    @abc.abstractmethod
+    async def delete_command_config(self, handler_full_name: str) -> None:
+        """Delete a single command configuration."""
+        ...
+
+    @abc.abstractmethod
+    async def delete_command_configs(self, handler_full_names: list[str]) -> None:
+        """Bulk delete command configurations."""
+        ...
+
+    @abc.abstractmethod
+    async def list_command_conflicts(
+        self,
+        status: str | None = None,
+    ) -> list[CommandConflict]:
+        """List recorded command conflict entries."""
+        ...
+
+    @abc.abstractmethod
+    async def upsert_command_conflict(
+        self,
+        conflict_key: str,
+        handler_full_name: str,
+        plugin_name: str,
+        *,
+        status: str | None = None,
+        resolution: str | None = None,
+        resolved_command: str | None = None,
+        note: str | None = None,
+        extra_data: dict | None = None,
+        auto_generated: bool | None = None,
+    ) -> CommandConflict:
+        """Create or update a conflict record."""
+        ...
+
+    @abc.abstractmethod
+    async def delete_command_conflicts(self, ids: list[int]) -> None:
+        """Delete conflict records."""
+        ...
+
     # @abc.abstractmethod
     # async def insert_llm_message(
     #     self,
@@ -313,3 +417,131 @@ class BaseDatabase(abc.ABC):
     ) -> tuple[list[dict], int]:
         """Get paginated session conversations with joined conversation and persona details, support search and platform filter."""
         ...
+
+    # ====
+    # Platform Session Management
+    # ====
+
+    @abc.abstractmethod
+    async def create_platform_session(
+        self,
+        creator: str,
+        platform_id: str = "webchat",
+        session_id: str | None = None,
+        display_name: str | None = None,
+        is_group: int = 0,
+    ) -> PlatformSession:
+        """Create a new Platform session."""
+        ...
+
+    @abc.abstractmethod
+    async def get_platform_session_by_id(
+        self, session_id: str
+    ) -> PlatformSession | None:
+        """Get a Platform session by its ID."""
+        ...
+
+    @abc.abstractmethod
+    async def get_platform_sessions_by_creator(
+        self,
+        creator: str,
+        platform_id: str | None = None,
+        page: int = 1,
+        page_size: int = 20,
+    ) -> list[dict]:
+        """Get all Platform sessions for a specific creator (username) and optionally platform.
+
+        Returns a list of dicts containing session info and project info (if session belongs to a project).
+        """
+        ...
+
+    @abc.abstractmethod
+    async def update_platform_session(
+        self,
+        session_id: str,
+        display_name: str | None = None,
+    ) -> None:
+        """Update a Platform session's updated_at timestamp and optionally display_name."""
+        ...
+
+    @abc.abstractmethod
+    async def delete_platform_session(self, session_id: str) -> None:
+        """Delete a Platform session by its ID."""
+        ...
+
+    # ====
+    # ChatUI Project Management
+    # ====
+
+    @abc.abstractmethod
+    async def create_chatui_project(
+        self,
+        creator: str,
+        title: str,
+        emoji: str | None = "📁",
+        description: str | None = None,
+    ) -> ChatUIProject:
+        """Create a new ChatUI project."""
+        ...
+
+    @abc.abstractmethod
+    async def get_chatui_project_by_id(self, project_id: str) -> ChatUIProject | None:
+        """Get a ChatUI project by its ID."""
+        ...
+
+    @abc.abstractmethod
+    async def get_chatui_projects_by_creator(
+        self,
+        creator: str,
+        page: int = 1,
+        page_size: int = 100,
+    ) -> list[ChatUIProject]:
+        """Get all ChatUI projects for a specific creator."""
+        ...
+
+    @abc.abstractmethod
+    async def update_chatui_project(
+        self,
+        project_id: str,
+        title: str | None = None,
+        emoji: str | None = None,
+        description: str | None = None,
+    ) -> None:
+        """Update a ChatUI project."""
+        ...
+
+    @abc.abstractmethod
+    async def delete_chatui_project(self, project_id: str) -> None:
+        """Delete a ChatUI project by its ID."""
+        ...
+
+    @abc.abstractmethod
+    async def add_session_to_project(
+        self,
+        session_id: str,
+        project_id: str,
+    ) -> SessionProjectRelation:
+        """Add a session to a project."""
+        ...
+
+    @abc.abstractmethod
+    async def remove_session_from_project(self, session_id: str) -> None:
+        """Remove a session from its project."""
+        ...
+
+    @abc.abstractmethod
+    async def get_project_sessions(
+        self,
+        project_id: str,
+        page: int = 1,
+        page_size: int = 100,
+    ) -> list[PlatformSession]:
+        """Get all sessions in a project."""
+        ...
+
+    @abc.abstractmethod
+    async def get_project_by_session(
+        self, session_id: str, creator: str
+    ) -> ChatUIProject | None:
+        """Get the project that a session belongs to."""
+        ...

astrbot/core/db/migration/migra_3_to_4.py

@@ -70,6 +70,7 @@ async def migration_conversation_table(
                         logger.info(
                             f"未找到该条旧会话对应的具体数据: {conversation}, 跳过。",
                         )
+                        continue
                     if ":" not in conv.user_id:
                         continue
                     session = MessageSesion.from_str(session_str=conv.user_id)
@@ -207,6 +208,7 @@ async def migration_webchat_data(
                         logger.info(
                             f"未找到该条旧会话对应的具体数据: {conversation}, 跳过。",
                         )
+                        continue
                     if ":" in conv.user_id:
                         continue
                     platform_id = "webchat"

astrbot/core/db/migration/migra_token_usage.py

@@ -0,0 +1,61 @@
+"""Migration script to add token_usage column to conversations table.
+
+This migration adds the token_usage field to track token consumption for each conversation.
+
+Changes:
+- Adds token_usage column to conversations table (default: 0)
+"""
+
+from sqlalchemy import text
+
+from astrbot.api import logger, sp
+from astrbot.core.db import BaseDatabase
+
+
+async def migrate_token_usage(db_helper: BaseDatabase):
+    """Add token_usage column to conversations table.
+
+    This migration adds a new column to track token consumption in conversations.
+    """
+    # 检查是否已经完成迁移
+    migration_done = await db_helper.get_preference(
+        "global", "global", "migration_done_token_usage_1"
+    )
+    if migration_done:
+        return
+
+    logger.info("开始执行数据库迁移（添加 conversations.token_usage 列）...")
+
+    # 这里只适配了 SQLite。因为截止至这一版本，AstrBot 仅支持 SQLite。
+
+    try:
+        async with db_helper.get_db() as session:
+            # 检查列是否已存在
+            result = await session.execute(text("PRAGMA table_info(conversations)"))
+            columns = result.fetchall()
+            column_names = [col[1] for col in columns]
+
+            if "token_usage" in column_names:
+                logger.info("token_usage 列已存在，跳过迁移")
+                await sp.put_async(
+                    "global", "global", "migration_done_token_usage_1", True
+                )
+                return
+
+            # 添加 token_usage 列
+            await session.execute(
+                text(
+                    "ALTER TABLE conversations ADD COLUMN token_usage INTEGER NOT NULL DEFAULT 0"
+                )
+            )
+            await session.commit()
+
+            logger.info("token_usage 列添加成功")
+
+        # 标记迁移完成
+        await sp.put_async("global", "global", "migration_done_token_usage_1", True)
+        logger.info("token_usage 迁移完成")
+
+    except Exception as e:
+        logger.error(f"迁移过程中发生错误: {e}", exc_info=True)
+        raise

astrbot/core/db/migration/migra_webchat_session.py

@@ -0,0 +1,131 @@
+"""Migration script for WebChat sessions.
+
+This migration creates PlatformSession from existing platform_message_history records.
+
+Changes:
+- Creates platform_sessions table
+- Adds platform_id field (default: 'webchat')
+- Adds display_name field
+- Session_id format: {platform_id}_{uuid}
+"""
+
+from sqlalchemy import func, select
+from sqlmodel import col
+
+from astrbot.api import logger, sp
+from astrbot.core.db import BaseDatabase
+from astrbot.core.db.po import ConversationV2, PlatformMessageHistory, PlatformSession
+
+
+async def migrate_webchat_session(db_helper: BaseDatabase):
+    """Create PlatformSession records from platform_message_history.
+
+    This migration extracts all unique user_ids from platform_message_history
+    where platform_id='webchat' and creates corresponding PlatformSession records.
+    """
+    # 检查是否已经完成迁移
+    migration_done = await db_helper.get_preference(
+        "global", "global", "migration_done_webchat_session_1"
+    )
+    if migration_done:
+        return
+
+    logger.info("开始执行数据库迁移（WebChat 会话迁移）...")
+
+    try:
+        async with db_helper.get_db() as session:
+            # 从 platform_message_history 创建 PlatformSession
+            query = (
+                select(
+                    col(PlatformMessageHistory.user_id),
+                    col(PlatformMessageHistory.sender_name),
+                    func.min(PlatformMessageHistory.created_at).label("earliest"),
+                    func.max(PlatformMessageHistory.updated_at).label("latest"),
+                )
+                .where(col(PlatformMessageHistory.platform_id) == "webchat")
+                .where(col(PlatformMessageHistory.sender_id) != "bot")
+                .group_by(col(PlatformMessageHistory.user_id))
+            )
+
+            result = await session.execute(query)
+            webchat_users = result.all()
+
+            if not webchat_users:
+                logger.info("没有找到需要迁移的 WebChat 数据")
+                await sp.put_async(
+                    "global", "global", "migration_done_webchat_session_1", True
+                )
+                return
+
+            logger.info(f"找到 {len(webchat_users)} 个 WebChat 会话需要迁移")
+
+            # 检查已存在的会话
+            existing_query = select(col(PlatformSession.session_id))
+            existing_result = await session.execute(existing_query)
+            existing_session_ids = {row[0] for row in existing_result.fetchall()}
+
+            # 查询 Conversations 表中的 title，用于设置 display_name
+            # 对于每个 user_id，对应的 conversation user_id 格式为: webchat:FriendMessage:webchat!astrbot!{user_id}
+            user_ids_to_query = [
+                f"webchat:FriendMessage:webchat!astrbot!{user_id}"
+                for user_id, _, _, _ in webchat_users
+            ]
+            conv_query = select(
+                col(ConversationV2.user_id), col(ConversationV2.title)
+            ).where(col(ConversationV2.user_id).in_(user_ids_to_query))
+            conv_result = await session.execute(conv_query)
+            # 创建 user_id -> title 的映射字典
+            title_map = {
+                user_id.replace("webchat:FriendMessage:webchat!astrbot!", ""): title
+                for user_id, title in conv_result.fetchall()
+            }
+
+            # 批量创建 PlatformSession 记录
+            sessions_to_add = []
+            skipped_count = 0
+
+            for user_id, sender_name, created_at, updated_at in webchat_users:
+                # user_id 就是 webchat_conv_id (session_id)
+                session_id = user_id
+
+                # sender_name 通常是 username，但可能为 None
+                creator = sender_name if sender_name else "guest"
+
+                # 检查是否已经存在该会话
+                if session_id in existing_session_ids:
+                    logger.debug(f"会话 {session_id} 已存在，跳过")
+                    skipped_count += 1
+                    continue
+
+                # 从 Conversations 表中获取 display_name
+                display_name = title_map.get(user_id)
+
+                # 创建新的 PlatformSession（保留原有的时间戳）
+                new_session = PlatformSession(
+                    session_id=session_id,
+                    platform_id="webchat",
+                    creator=creator,
+                    is_group=0,
+                    created_at=created_at,
+                    updated_at=updated_at,
+                    display_name=display_name,
+                )
+                sessions_to_add.append(new_session)
+
+            # 批量插入
+            if sessions_to_add:
+                session.add_all(sessions_to_add)
+                await session.commit()
+
+                logger.info(
+                    f"WebChat 会话迁移完成！成功迁移: {len(sessions_to_add)}, 跳过: {skipped_count}",
+                )
+            else:
+                logger.info("没有新会话需要迁移")
+
+        # 标记迁移完成
+        await sp.put_async("global", "global", "migration_done_webchat_session_1", True)
+
+    except Exception as e:
+        logger.error(f"迁移过程中发生错误: {e}", exc_info=True)
+        raise

astrbot/core/db/migration/sqlite_v3.py

@@ -127,7 +127,7 @@ class SQLiteDatabase:
         conn.text_factory = str
         return conn
 
-    def _exec_sql(self, sql: str, params: tuple = None):
+    def _exec_sql(self, sql: str, params: tuple | None = None):
         conn = self.conn
         try:
             c = self.conn.cursor()
@@ -224,9 +224,11 @@ class SQLiteDatabase:
 
         c.close()
 
-        return Stats(platform, [], [])
+        return Stats(platform)
 
-    def get_conversation_by_user_id(self, user_id: str, cid: str) -> Conversation:
+    def get_conversation_by_user_id(
+        self, user_id: str, cid: str
+    ) -> Conversation | None:
         try:
             c = self.conn.cursor()
         except sqlite3.ProgrammingError:
@@ -258,7 +260,7 @@ class SQLiteDatabase:
             (user_id, cid, history, updated_at, created_at),
         )
 
-    def get_conversations(self, user_id: str) -> tuple:
+    def get_conversations(self, user_id: str) -> list[Conversation]:
         try:
             c = self.conn.cursor()
         except sqlite3.ProgrammingError:

astrbot/core/db/po.py

@@ -3,13 +3,7 @@ from dataclasses import dataclass, field
 from datetime import datetime, timezone
 from typing import TypedDict
 
-from sqlmodel import (
-    JSON,
-    Field,
-    SQLModel,
-    Text,
-    UniqueConstraint,
-)
+from sqlmodel import JSON, Field, SQLModel, Text, UniqueConstraint
 
 
 class PlatformStat(SQLModel, table=True):
@@ -18,7 +12,7 @@ class PlatformStat(SQLModel, table=True):
     Note: In astrbot v4, we moved `platform` table to here.
     """
 
-    __tablename__ = "platform_stats"
+    __tablename__: str = "platform_stats"
 
     id: int = Field(primary_key=True, sa_column_kwargs={"autoincrement": True})
     timestamp: datetime = Field(nullable=False)
@@ -37,9 +31,10 @@ class PlatformStat(SQLModel, table=True):
 
 
 class ConversationV2(SQLModel, table=True):
-    __tablename__ = "conversations"
+    __tablename__: str = "conversations"
 
-    inner_conversation_id: int = Field(
+    inner_conversation_id: int | None = Field(
+        default=None,
         primary_key=True,
         sa_column_kwargs={"autoincrement": True},
     )
@@ -59,6 +54,11 @@ class ConversationV2(SQLModel, table=True):
     )
     title: str | None = Field(default=None, max_length=255)
     persona_id: str | None = Field(default=None)
+    token_usage: int = Field(default=0, nullable=False)
+    """content is a list of OpenAI-formated messages in list[dict] format.
+    token_usage is the total token value of the messages.
+    when 0, will use estimated token counter.
+    """
 
     __table_args__ = (
         UniqueConstraint(
@@ -74,7 +74,7 @@ class Persona(SQLModel, table=True):
     It can be used to customize the behavior of LLMs.
     """
 
-    __tablename__ = "personas"
+    __tablename__: str = "personas"
 
     id: int | None = Field(
         primary_key=True,
@@ -104,7 +104,7 @@ class Persona(SQLModel, table=True):
 class Preference(SQLModel, table=True):
     """This class represents preferences for bots."""
 
-    __tablename__ = "preferences"
+    __tablename__: str = "preferences"
 
     id: int | None = Field(
         default=None,
@@ -140,7 +140,7 @@ class PlatformMessageHistory(SQLModel, table=True):
     or platform-specific messages.
     """
 
-    __tablename__ = "platform_message_history"
+    __tablename__: str = "platform_message_history"
 
     id: int | None = Field(
         primary_key=True,
@@ -161,13 +161,55 @@ class PlatformMessageHistory(SQLModel, table=True):
     )
 
 
+class PlatformSession(SQLModel, table=True):
+    """Platform session table for managing user sessions across different platforms.
+
+    A session represents a chat window for a specific user on a specific platform.
+    Each session can have multiple conversations (对话) associated with it.
+    """
+
+    __tablename__: str = "platform_sessions"
+
+    inner_id: int | None = Field(
+        primary_key=True,
+        sa_column_kwargs={"autoincrement": True},
+        default=None,
+    )
+    session_id: str = Field(
+        max_length=100,
+        nullable=False,
+        unique=True,
+        default_factory=lambda: str(uuid.uuid4()),
+    )
+    platform_id: str = Field(default="webchat", nullable=False)
+    """Platform identifier (e.g., 'webchat', 'qq', 'discord')"""
+    creator: str = Field(nullable=False)
+    """Username of the session creator"""
+    display_name: str | None = Field(default=None, max_length=255)
+    """Display name for the session"""
+    is_group: int = Field(default=0, nullable=False)
+    """0 for private chat, 1 for group chat (not implemented yet)"""
+    created_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
+    updated_at: datetime = Field(
+        default_factory=lambda: datetime.now(timezone.utc),
+        sa_column_kwargs={"onupdate": datetime.now(timezone.utc)},
+    )
+
+    __table_args__ = (
+        UniqueConstraint(
+            "session_id",
+            name="uix_platform_session_id",
+        ),
+    )
+
+
 class Attachment(SQLModel, table=True):
     """This class represents attachments for messages in AstrBot.
 
     Attachments can be images, files, or other media types.
     """
 
-    __tablename__ = "attachments"
+    __tablename__: str = "attachments"
 
     inner_attachment_id: int | None = Field(
         primary_key=True,
@@ -197,6 +239,130 @@ class Attachment(SQLModel, table=True):
     )
 
 
+class ChatUIProject(SQLModel, table=True):
+    """This class represents projects for organizing ChatUI conversations.
+
+    Projects allow users to group related conversations together.
+    """
+
+    __tablename__: str = "chatui_projects"
+
+    inner_id: int | None = Field(
+        primary_key=True,
+        sa_column_kwargs={"autoincrement": True},
+        default=None,
+    )
+    project_id: str = Field(
+        max_length=36,
+        nullable=False,
+        unique=True,
+        default_factory=lambda: str(uuid.uuid4()),
+    )
+    creator: str = Field(nullable=False)
+    """Username of the project creator"""
+    emoji: str | None = Field(default="📁", max_length=10)
+    """Emoji icon for the project"""
+    title: str = Field(nullable=False, max_length=255)
+    """Title of the project"""
+    description: str | None = Field(default=None, max_length=1000)
+    """Description of the project"""
+    created_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
+    updated_at: datetime = Field(
+        default_factory=lambda: datetime.now(timezone.utc),
+        sa_column_kwargs={"onupdate": datetime.now(timezone.utc)},
+    )
+
+    __table_args__ = (
+        UniqueConstraint(
+            "project_id",
+            name="uix_chatui_project_id",
+        ),
+    )
+
+
+class SessionProjectRelation(SQLModel, table=True):
+    """This class represents the relationship between platform sessions and ChatUI projects."""
+
+    __tablename__: str = "session_project_relations"
+
+    id: int | None = Field(
+        primary_key=True,
+        sa_column_kwargs={"autoincrement": True},
+        default=None,
+    )
+    session_id: str = Field(nullable=False, max_length=100)
+    """Session ID from PlatformSession"""
+    project_id: str = Field(nullable=False, max_length=36)
+    """Project ID from ChatUIProject"""
+    created_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
+
+    __table_args__ = (
+        UniqueConstraint(
+            "session_id",
+            name="uix_session_project_relation",
+        ),
+    )
+
+
+class CommandConfig(SQLModel, table=True):
+    """Per-command configuration overrides for dashboard management."""
+
+    __tablename__ = "command_configs"  # type: ignore
+
+    handler_full_name: str = Field(
+        primary_key=True,
+        max_length=512,
+    )
+    plugin_name: str = Field(nullable=False, max_length=255)
+    module_path: str = Field(nullable=False, max_length=255)
+    original_command: str = Field(nullable=False, max_length=255)
+    resolved_command: str | None = Field(default=None, max_length=255)
+    enabled: bool = Field(default=True, nullable=False)
+    keep_original_alias: bool = Field(default=False, nullable=False)
+    conflict_key: str | None = Field(default=None, max_length=255)
+    resolution_strategy: str | None = Field(default=None, max_length=64)
+    note: str | None = Field(default=None, sa_type=Text)
+    extra_data: dict | None = Field(default=None, sa_type=JSON)
+    auto_managed: bool = Field(default=False, nullable=False)
+    created_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
+    updated_at: datetime = Field(
+        default_factory=lambda: datetime.now(timezone.utc),
+        sa_column_kwargs={"onupdate": datetime.now(timezone.utc)},
+    )
+
+
+class CommandConflict(SQLModel, table=True):
+    """Conflict tracking for duplicated command names."""
+
+    __tablename__ = "command_conflicts"  # type: ignore
+
+    id: int | None = Field(
+        default=None, primary_key=True, sa_column_kwargs={"autoincrement": True}
+    )
+    conflict_key: str = Field(nullable=False, max_length=255)
+    handler_full_name: str = Field(nullable=False, max_length=512)
+    plugin_name: str = Field(nullable=False, max_length=255)
+    status: str = Field(default="pending", max_length=32)
+    resolution: str | None = Field(default=None, max_length=64)
+    resolved_command: str | None = Field(default=None, max_length=255)
+    note: str | None = Field(default=None, sa_type=Text)
+    extra_data: dict | None = Field(default=None, sa_type=JSON)
+    auto_generated: bool = Field(default=False, nullable=False)
+    created_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
+    updated_at: datetime = Field(
+        default_factory=lambda: datetime.now(timezone.utc),
+        sa_column_kwargs={"onupdate": datetime.now(timezone.utc)},
+    )
+
+    __table_args__ = (
+        UniqueConstraint(
+            "conflict_key",
+            "handler_full_name",
+            name="uix_conflict_handler",
+        ),
+    )
+
+
 @dataclass
 class Conversation:
     """LLM 对话类
@@ -217,6 +383,8 @@ class Conversation:
     persona_id: str | None = ""
     created_at: int = 0
     updated_at: int = 0
+    token_usage: int = 0
+    """对话的总 token 数量。AstrBot 会保留最近一次 LLM 请求返回的总 token 数，方便统计。token_usage 可能为 0，表示未知。"""
 
 
 class Personality(TypedDict):
@@ -225,17 +393,17 @@ class Personality(TypedDict):
     在 v4.0.0 版本及之后，推荐使用上面的 Persona 类。并且， mood_imitation_dialogs 字段已被废弃。
     """
 
-    prompt: str = ""
-    name: str = ""
-    begin_dialogs: list[str] = []
-    mood_imitation_dialogs: list[str] = []
+    prompt: str
+    name: str
+    begin_dialogs: list[str]
+    mood_imitation_dialogs: list[str]
     """情感模拟对话预设。在 v4.0.0 版本及之后，已被废弃。"""
-    tools: list[str] | None = None
+    tools: list[str] | None
     """工具列表。None 表示使用所有工具，空列表表示不使用任何工具"""
 
     # cache
-    _begin_dialogs_processed: list[dict] = []
-    _mood_imitation_dialogs_processed: str = ""
+    _begin_dialogs_processed: list[dict]
+    _mood_imitation_dialogs_processed: str
 
 
 # ====

astrbot/core/db/sqlite.py

@@ -1,19 +1,26 @@
 import asyncio
 import threading
 import typing as T
-from datetime import datetime, timedelta
+from collections.abc import Awaitable, Callable
+from datetime import datetime, timedelta, timezone
 
+from sqlalchemy import CursorResult
 from sqlalchemy.ext.asyncio import AsyncSession
 from sqlmodel import col, delete, desc, func, or_, select, text, update
 
 from astrbot.core.db import BaseDatabase
 from astrbot.core.db.po import (
     Attachment,
+    ChatUIProject,
+    CommandConfig,
+    CommandConflict,
     ConversationV2,
     Persona,
     PlatformMessageHistory,
+    PlatformSession,
     PlatformStat,
     Preference,
+    SessionProjectRelation,
     SQLModel,
 )
 from astrbot.core.db.po import (
@@ -24,6 +31,7 @@ from astrbot.core.db.po import (
 )
 
 NOT_GIVEN = T.TypeVar("NOT_GIVEN")
+TxResult = T.TypeVar("TxResult")
 
 
 class SQLiteDatabase(BaseDatabase):
@@ -104,8 +112,8 @@ class SQLiteDatabase(BaseDatabase):
                 text("""
                 SELECT * FROM platform_stats
                 WHERE timestamp >= :start_time
-                ORDER BY timestamp DESC
                 GROUP BY platform_id
+                ORDER BY timestamp DESC
                 """),
                 {"start_time": start_time},
             )
@@ -235,7 +243,9 @@ class SQLiteDatabase(BaseDatabase):
                 session.add(new_conversation)
                 return new_conversation
 
-    async def update_conversation(self, cid, title=None, persona_id=None, content=None):
+    async def update_conversation(
+        self, cid, title=None, persona_id=None, content=None, token_usage=None
+    ):
         async with self.get_db() as session:
             session: AsyncSession
             async with session.begin():
@@ -249,6 +259,8 @@ class SQLiteDatabase(BaseDatabase):
                     values["persona_id"] = persona_id
                 if content is not None:
                     values["content"] = content
+                if token_usage is not None:
+                    values["token_usage"] = token_usage
                 if not values:
                     return None
                 query = query.values(**values)
@@ -412,7 +424,7 @@ class SQLiteDatabase(BaseDatabase):
         user_id,
         offset_sec=86400,
     ):
-        """Delete platform message history records older than the specified offset."""
+        """Delete platform message history records newer than the specified offset."""
         async with self.get_db() as session:
             session: AsyncSession
             async with session.begin():
@@ -422,7 +434,7 @@ class SQLiteDatabase(BaseDatabase):
                     delete(PlatformMessageHistory).where(
                         col(PlatformMessageHistory.platform_id) == platform_id,
                         col(PlatformMessageHistory.user_id) == user_id,
-                        col(PlatformMessageHistory.created_at) < cutoff_time,
+                        col(PlatformMessageHistory.created_at) >= cutoff_time,
                     ),
                 )
 
@@ -448,6 +460,18 @@ class SQLiteDatabase(BaseDatabase):
             result = await session.execute(query.offset(offset).limit(page_size))
             return result.scalars().all()
 
+    async def get_platform_message_history_by_id(
+        self, message_id: int
+    ) -> PlatformMessageHistory | None:
+        """Get a platform message history record by its ID."""
+        async with self.get_db() as session:
+            session: AsyncSession
+            query = select(PlatformMessageHistory).where(
+                PlatformMessageHistory.id == message_id
+            )
+            result = await session.execute(query)
+            return result.scalar_one_or_none()
+
     async def insert_attachment(self, path, type, mime_type):
         """Insert a new attachment record."""
         async with self.get_db() as session:
@@ -469,6 +493,48 @@ class SQLiteDatabase(BaseDatabase):
             result = await session.execute(query)
             return result.scalar_one_or_none()
 
+    async def get_attachments(self, attachment_ids: list[str]) -> list:
+        """Get multiple attachments by their IDs."""
+        if not attachment_ids:
+            return []
+        async with self.get_db() as session:
+            session: AsyncSession
+            query = select(Attachment).where(
+                col(Attachment.attachment_id).in_(attachment_ids)
+            )
+            result = await session.execute(query)
+            return list(result.scalars().all())
+
+    async def delete_attachment(self, attachment_id: str) -> bool:
+        """Delete an attachment by its ID.
+
+        Returns True if the attachment was deleted, False if it was not found.
+        """
+        async with self.get_db() as session:
+            session: AsyncSession
+            async with session.begin():
+                query = delete(Attachment).where(
+                    col(Attachment.attachment_id) == attachment_id
+                )
+                result = T.cast(CursorResult, await session.execute(query))
+                return result.rowcount > 0
+
+    async def delete_attachments(self, attachment_ids: list[str]) -> int:
+        """Delete multiple attachments by their IDs.
+
+        Returns the number of attachments deleted.
+        """
+        if not attachment_ids:
+            return 0
+        async with self.get_db() as session:
+            session: AsyncSession
+            async with session.begin():
+                query = delete(Attachment).where(
+                    col(Attachment.attachment_id).in_(attachment_ids)
+                )
+                result = T.cast(CursorResult, await session.execute(query))
+                return result.rowcount
+
     async def insert_persona(
         self,
         persona_id,
@@ -614,6 +680,242 @@ class SQLiteDatabase(BaseDatabase):
                 )
             await session.commit()
 
+    # ====
+    # Command Configuration & Conflict Tracking
+    # ====
+
+    async def _run_in_tx(
+        self,
+        fn: Callable[[AsyncSession], Awaitable[TxResult]],
+    ) -> TxResult:
+        async with self.get_db() as session:
+            session: AsyncSession
+            async with session.begin():
+                return await fn(session)
+
+    @staticmethod
+    def _apply_updates(model, **updates) -> None:
+        for field, value in updates.items():
+            if value is not None:
+                setattr(model, field, value)
+
+    @staticmethod
+    def _new_command_config(
+        handler_full_name: str,
+        plugin_name: str,
+        module_path: str,
+        original_command: str,
+        *,
+        resolved_command: str | None = None,
+        enabled: bool | None = None,
+        keep_original_alias: bool | None = None,
+        conflict_key: str | None = None,
+        resolution_strategy: str | None = None,
+        note: str | None = None,
+        extra_data: dict | None = None,
+        auto_managed: bool | None = None,
+    ) -> CommandConfig:
+        return CommandConfig(
+            handler_full_name=handler_full_name,
+            plugin_name=plugin_name,
+            module_path=module_path,
+            original_command=original_command,
+            resolved_command=resolved_command,
+            enabled=True if enabled is None else enabled,
+            keep_original_alias=False
+            if keep_original_alias is None
+            else keep_original_alias,
+            conflict_key=conflict_key or original_command,
+            resolution_strategy=resolution_strategy,
+            note=note,
+            extra_data=extra_data,
+            auto_managed=bool(auto_managed),
+        )
+
+    @staticmethod
+    def _new_command_conflict(
+        conflict_key: str,
+        handler_full_name: str,
+        plugin_name: str,
+        *,
+        status: str | None = None,
+        resolution: str | None = None,
+        resolved_command: str | None = None,
+        note: str | None = None,
+        extra_data: dict | None = None,
+        auto_generated: bool | None = None,
+    ) -> CommandConflict:
+        return CommandConflict(
+            conflict_key=conflict_key,
+            handler_full_name=handler_full_name,
+            plugin_name=plugin_name,
+            status=status or "pending",
+            resolution=resolution,
+            resolved_command=resolved_command,
+            note=note,
+            extra_data=extra_data,
+            auto_generated=bool(auto_generated),
+        )
+
+    async def get_command_configs(self) -> list[CommandConfig]:
+        async with self.get_db() as session:
+            session: AsyncSession
+            result = await session.execute(select(CommandConfig))
+            return list(result.scalars().all())
+
+    async def get_command_config(
+        self,
+        handler_full_name: str,
+    ) -> CommandConfig | None:
+        async with self.get_db() as session:
+            session: AsyncSession
+            return await session.get(CommandConfig, handler_full_name)
+
+    async def upsert_command_config(
+        self,
+        handler_full_name: str,
+        plugin_name: str,
+        module_path: str,
+        original_command: str,
+        *,
+        resolved_command: str | None = None,
+        enabled: bool | None = None,
+        keep_original_alias: bool | None = None,
+        conflict_key: str | None = None,
+        resolution_strategy: str | None = None,
+        note: str | None = None,
+        extra_data: dict | None = None,
+        auto_managed: bool | None = None,
+    ) -> CommandConfig:
+        async def _op(session: AsyncSession) -> CommandConfig:
+            config = await session.get(CommandConfig, handler_full_name)
+            if not config:
+                config = self._new_command_config(
+                    handler_full_name,
+                    plugin_name,
+                    module_path,
+                    original_command,
+                    resolved_command=resolved_command,
+                    enabled=enabled,
+                    keep_original_alias=keep_original_alias,
+                    conflict_key=conflict_key,
+                    resolution_strategy=resolution_strategy,
+                    note=note,
+                    extra_data=extra_data,
+                    auto_managed=auto_managed,
+                )
+                session.add(config)
+            else:
+                self._apply_updates(
+                    config,
+                    plugin_name=plugin_name,
+                    module_path=module_path,
+                    original_command=original_command,
+                    resolved_command=resolved_command,
+                    enabled=enabled,
+                    keep_original_alias=keep_original_alias,
+                    conflict_key=conflict_key,
+                    resolution_strategy=resolution_strategy,
+                    note=note,
+                    extra_data=extra_data,
+                    auto_managed=auto_managed,
+                )
+            await session.flush()
+            await session.refresh(config)
+            return config
+
+        return await self._run_in_tx(_op)
+
+    async def delete_command_config(self, handler_full_name: str) -> None:
+        await self.delete_command_configs([handler_full_name])
+
+    async def delete_command_configs(self, handler_full_names: list[str]) -> None:
+        if not handler_full_names:
+            return
+
+        async def _op(session: AsyncSession) -> None:
+            await session.execute(
+                delete(CommandConfig).where(
+                    col(CommandConfig.handler_full_name).in_(handler_full_names),
+                ),
+            )
+
+        await self._run_in_tx(_op)
+
+    async def list_command_conflicts(
+        self,
+        status: str | None = None,
+    ) -> list[CommandConflict]:
+        async with self.get_db() as session:
+            session: AsyncSession
+            query = select(CommandConflict)
+            if status:
+                query = query.where(CommandConflict.status == status)
+            result = await session.execute(query)
+            return list(result.scalars().all())
+
+    async def upsert_command_conflict(
+        self,
+        conflict_key: str,
+        handler_full_name: str,
+        plugin_name: str,
+        *,
+        status: str | None = None,
+        resolution: str | None = None,
+        resolved_command: str | None = None,
+        note: str | None = None,
+        extra_data: dict | None = None,
+        auto_generated: bool | None = None,
+    ) -> CommandConflict:
+        async def _op(session: AsyncSession) -> CommandConflict:
+            result = await session.execute(
+                select(CommandConflict).where(
+                    CommandConflict.conflict_key == conflict_key,
+                    CommandConflict.handler_full_name == handler_full_name,
+                ),
+            )
+            record = result.scalar_one_or_none()
+            if not record:
+                record = self._new_command_conflict(
+                    conflict_key,
+                    handler_full_name,
+                    plugin_name,
+                    status=status,
+                    resolution=resolution,
+                    resolved_command=resolved_command,
+                    note=note,
+                    extra_data=extra_data,
+                    auto_generated=auto_generated,
+                )
+                session.add(record)
+            else:
+                self._apply_updates(
+                    record,
+                    plugin_name=plugin_name,
+                    status=status,
+                    resolution=resolution,
+                    resolved_command=resolved_command,
+                    note=note,
+                    extra_data=extra_data,
+                    auto_generated=auto_generated,
+                )
+            await session.flush()
+            await session.refresh(record)
+            return record
+
+        return await self._run_in_tx(_op)
+
+    async def delete_command_conflicts(self, ids: list[int]) -> None:
+        if not ids:
+            return
+
+        async def _op(session: AsyncSession) -> None:
+            await session.execute(
+                delete(CommandConflict).where(col(CommandConflict.id).in_(ids)),
+            )
+
+        await self._run_in_tx(_op)
+
     # ====
     # Deprecated Methods
     # ====
@@ -709,3 +1011,320 @@ class SQLiteDatabase(BaseDatabase):
         t.start()
         t.join()
         return result
+
+    # ====
+    # Platform Session Management
+    # ====
+
+    async def create_platform_session(
+        self,
+        creator: str,
+        platform_id: str = "webchat",
+        session_id: str | None = None,
+        display_name: str | None = None,
+        is_group: int = 0,
+    ) -> PlatformSession:
+        """Create a new Platform session."""
+        kwargs = {}
+        if session_id:
+            kwargs["session_id"] = session_id
+
+        async with self.get_db() as session:
+            session: AsyncSession
+            async with session.begin():
+                new_session = PlatformSession(
+                    creator=creator,
+                    platform_id=platform_id,
+                    display_name=display_name,
+                    is_group=is_group,
+                    **kwargs,
+                )
+                session.add(new_session)
+                await session.flush()
+                await session.refresh(new_session)
+                return new_session
+
+    async def get_platform_session_by_id(
+        self, session_id: str
+    ) -> PlatformSession | None:
+        """Get a Platform session by its ID."""
+        async with self.get_db() as session:
+            session: AsyncSession
+            query = select(PlatformSession).where(
+                PlatformSession.session_id == session_id,
+            )
+            result = await session.execute(query)
+            return result.scalar_one_or_none()
+
+    async def get_platform_sessions_by_creator(
+        self,
+        creator: str,
+        platform_id: str | None = None,
+        page: int = 1,
+        page_size: int = 20,
+    ) -> list[dict]:
+        """Get all Platform sessions for a specific creator (username) and optionally platform.
+
+        Returns a list of dicts containing session info and project info (if session belongs to a project).
+        """
+        async with self.get_db() as session:
+            session: AsyncSession
+            offset = (page - 1) * page_size
+
+            # LEFT JOIN with SessionProjectRelation and ChatUIProject to get project info
+            query = (
+                select(
+                    PlatformSession,
+                    col(ChatUIProject.project_id),
+                    col(ChatUIProject.title).label("project_title"),
+                    col(ChatUIProject.emoji).label("project_emoji"),
+                )
+                .outerjoin(
+                    SessionProjectRelation,
+                    col(PlatformSession.session_id)
+                    == col(SessionProjectRelation.session_id),
+                )
+                .outerjoin(
+                    ChatUIProject,
+                    col(SessionProjectRelation.project_id)
+                    == col(ChatUIProject.project_id),
+                )
+                .where(col(PlatformSession.creator) == creator)
+            )
+
+            if platform_id:
+                query = query.where(PlatformSession.platform_id == platform_id)
+
+            query = (
+                query.order_by(desc(PlatformSession.updated_at))
+                .offset(offset)
+                .limit(page_size)
+            )
+            result = await session.execute(query)
+
+            # Convert to list of dicts with session and project info
+            sessions_with_projects = []
+            for row in result.all():
+                platform_session = row[0]
+                project_id = row[1]
+                project_title = row[2]
+                project_emoji = row[3]
+
+                session_dict = {
+                    "session": platform_session,
+                    "project_id": project_id,
+                    "project_title": project_title,
+                    "project_emoji": project_emoji,
+                }
+                sessions_with_projects.append(session_dict)
+
+            return sessions_with_projects
+
+    async def update_platform_session(
+        self,
+        session_id: str,
+        display_name: str | None = None,
+    ) -> None:
+        """Update a Platform session's updated_at timestamp and optionally display_name."""
+        async with self.get_db() as session:
+            session: AsyncSession
+            async with session.begin():
+                values: dict[str, T.Any] = {"updated_at": datetime.now(timezone.utc)}
+                if display_name is not None:
+                    values["display_name"] = display_name
+
+                await session.execute(
+                    update(PlatformSession)
+                    .where(col(PlatformSession.session_id) == session_id)
+                    .values(**values),
+                )
+
+    async def delete_platform_session(self, session_id: str) -> None:
+        """Delete a Platform session by its ID."""
+        async with self.get_db() as session:
+            session: AsyncSession
+            async with session.begin():
+                await session.execute(
+                    delete(PlatformSession).where(
+                        col(PlatformSession.session_id) == session_id,
+                    ),
+                )
+
+    # ====
+    # ChatUI Project Management
+    # ====
+
+    async def create_chatui_project(
+        self,
+        creator: str,
+        title: str,
+        emoji: str | None = "📁",
+        description: str | None = None,
+    ) -> ChatUIProject:
+        """Create a new ChatUI project."""
+        async with self.get_db() as session:
+            session: AsyncSession
+            async with session.begin():
+                project = ChatUIProject(
+                    creator=creator,
+                    title=title,
+                    emoji=emoji,
+                    description=description,
+                )
+                session.add(project)
+                await session.flush()
+                await session.refresh(project)
+                return project
+
+    async def get_chatui_project_by_id(self, project_id: str) -> ChatUIProject | None:
+        """Get a ChatUI project by its ID."""
+        async with self.get_db() as session:
+            session: AsyncSession
+            result = await session.execute(
+                select(ChatUIProject).where(
+                    col(ChatUIProject.project_id) == project_id,
+                ),
+            )
+            return result.scalar_one_or_none()
+
+    async def get_chatui_projects_by_creator(
+        self,
+        creator: str,
+        page: int = 1,
+        page_size: int = 100,
+    ) -> list[ChatUIProject]:
+        """Get all ChatUI projects for a specific creator."""
+        async with self.get_db() as session:
+            session: AsyncSession
+            offset = (page - 1) * page_size
+            result = await session.execute(
+                select(ChatUIProject)
+                .where(col(ChatUIProject.creator) == creator)
+                .order_by(desc(ChatUIProject.updated_at))
+                .limit(page_size)
+                .offset(offset),
+            )
+            return list(result.scalars().all())
+
+    async def update_chatui_project(
+        self,
+        project_id: str,
+        title: str | None = None,
+        emoji: str | None = None,
+        description: str | None = None,
+    ) -> None:
+        """Update a ChatUI project."""
+        async with self.get_db() as session:
+            session: AsyncSession
+            async with session.begin():
+                values: dict[str, T.Any] = {"updated_at": datetime.now(timezone.utc)}
+                if title is not None:
+                    values["title"] = title
+                if emoji is not None:
+                    values["emoji"] = emoji
+                if description is not None:
+                    values["description"] = description
+
+                await session.execute(
+                    update(ChatUIProject)
+                    .where(col(ChatUIProject.project_id) == project_id)
+                    .values(**values),
+                )
+
+    async def delete_chatui_project(self, project_id: str) -> None:
+        """Delete a ChatUI project by its ID."""
+        async with self.get_db() as session:
+            session: AsyncSession
+            async with session.begin():
+                # First remove all session relations
+                await session.execute(
+                    delete(SessionProjectRelation).where(
+                        col(SessionProjectRelation.project_id) == project_id,
+                    ),
+                )
+                # Then delete the project
+                await session.execute(
+                    delete(ChatUIProject).where(
+                        col(ChatUIProject.project_id) == project_id,
+                    ),
+                )
+
+    async def add_session_to_project(
+        self,
+        session_id: str,
+        project_id: str,
+    ) -> SessionProjectRelation:
+        """Add a session to a project."""
+        async with self.get_db() as session:
+            session: AsyncSession
+            async with session.begin():
+                # First remove existing relation if any
+                await session.execute(
+                    delete(SessionProjectRelation).where(
+                        col(SessionProjectRelation.session_id) == session_id,
+                    ),
+                )
+                # Then create new relation
+                relation = SessionProjectRelation(
+                    session_id=session_id,
+                    project_id=project_id,
+                )
+                session.add(relation)
+                await session.flush()
+                await session.refresh(relation)
+                return relation
+
+    async def remove_session_from_project(self, session_id: str) -> None:
+        """Remove a session from its project."""
+        async with self.get_db() as session:
+            session: AsyncSession
+            async with session.begin():
+                await session.execute(
+                    delete(SessionProjectRelation).where(
+                        col(SessionProjectRelation.session_id) == session_id,
+                    ),
+                )
+
+    async def get_project_sessions(
+        self,
+        project_id: str,
+        page: int = 1,
+        page_size: int = 100,
+    ) -> list[PlatformSession]:
+        """Get all sessions in a project."""
+        async with self.get_db() as session:
+            session: AsyncSession
+            offset = (page - 1) * page_size
+            result = await session.execute(
+                select(PlatformSession)
+                .join(
+                    SessionProjectRelation,
+                    col(PlatformSession.session_id)
+                    == col(SessionProjectRelation.session_id),
+                )
+                .where(col(SessionProjectRelation.project_id) == project_id)
+                .order_by(desc(PlatformSession.updated_at))
+                .limit(page_size)
+                .offset(offset),
+            )
+            return list(result.scalars().all())
+
+    async def get_project_by_session(
+        self, session_id: str, creator: str
+    ) -> ChatUIProject | None:
+        """Get the project that a session belongs to."""
+        async with self.get_db() as session:
+            session: AsyncSession
+            result = await session.execute(
+                select(ChatUIProject)
+                .join(
+                    SessionProjectRelation,
+                    col(ChatUIProject.project_id)
+                    == col(SessionProjectRelation.project_id),
+                )
+                .where(
+                    col(SessionProjectRelation.session_id) == session_id,
+                    col(ChatUIProject.creator) == creator,
+                ),
+            )
+            return result.scalar_one_or_none()

astrbot/core/db/vec_db/faiss_impl/embedding_storage.py

@@ -90,4 +90,6 @@ class EmbeddingStorage:
             path (str): 保存索引的路径
 
         """
+        if self.index is None:
+            return
         faiss.write_index(self.index, self.path)

astrbot/core/event_bus.py

@@ -27,7 +27,7 @@ class EventBus:
         self,
         event_queue: Queue,
         pipeline_scheduler_mapping: dict[str, PipelineScheduler],
-        astrbot_config_mgr: AstrBotConfigManager = None,
+        astrbot_config_mgr: AstrBotConfigManager,
     ):
         self.event_queue = event_queue  # 事件队列
         # abconf uuid -> scheduler
@@ -40,6 +40,11 @@ class EventBus:
             conf_info = self.astrbot_config_mgr.get_conf_info(event.unified_msg_origin)
             self._print_event(event, conf_info["name"])
             scheduler = self.pipeline_scheduler_mapping.get(conf_info["id"])
+            if not scheduler:
+                logger.error(
+                    f"PipelineScheduler not found for id: {conf_info['id']}, event ignored."
+                )
+                continue
             asyncio.create_task(scheduler.execute(event))
 
     def _print_event(self, event: AstrMessageEvent, conf_name: str):

astrbot/core/knowledge_base/chunking/recursive.py

@@ -149,8 +149,16 @@ class RecursiveCharacterChunker(BaseChunker):
             分割后的文本块列表
 
         """
-        chunk_size = chunk_size or self.chunk_size
-        overlap = overlap or self.chunk_overlap
+        if chunk_size is None:
+            chunk_size = self.chunk_size
+        if overlap is None:
+            overlap = self.chunk_overlap
+        if chunk_size <= 0:
+            raise ValueError("chunk_size must be greater than 0")
+        if overlap < 0:
+            raise ValueError("chunk_overlap must be non-negative")
+        if overlap >= chunk_size:
+            raise ValueError("chunk_overlap must be less than chunk_size")
         result = []
         for i in range(0, len(text), chunk_size - overlap):
             end = min(i + chunk_size, len(text))

astrbot/core/knowledge_base/kb_helper.py

@@ -1,4 +1,7 @@
+import asyncio
 import json
+import re
+import time
 import uuid
 from pathlib import Path
 
@@ -8,12 +11,98 @@ from astrbot.core import logger
 from astrbot.core.db.vec_db.base import BaseVecDB
 from astrbot.core.db.vec_db.faiss_impl.vec_db import FaissVecDB
 from astrbot.core.provider.manager import ProviderManager
-from astrbot.core.provider.provider import EmbeddingProvider, RerankProvider
+from astrbot.core.provider.provider import (
+    EmbeddingProvider,
+    RerankProvider,
+)
+from astrbot.core.provider.provider import (
+    Provider as LLMProvider,
+)
 
 from .chunking.base import BaseChunker
+from .chunking.recursive import RecursiveCharacterChunker
 from .kb_db_sqlite import KBSQLiteDatabase
 from .models import KBDocument, KBMedia, KnowledgeBase
+from .parsers.url_parser import extract_text_from_url
 from .parsers.util import select_parser
+from .prompts import TEXT_REPAIR_SYSTEM_PROMPT
+
+
+class RateLimiter:
+    """一个简单的速率限制器"""
+
+    def __init__(self, max_rpm: int):
+        self.max_per_minute = max_rpm
+        self.interval = 60.0 / max_rpm if max_rpm > 0 else 0
+        self.last_call_time = 0
+
+    async def __aenter__(self):
+        if self.interval == 0:
+            return
+
+        now = time.monotonic()
+        elapsed = now - self.last_call_time
+
+        if elapsed < self.interval:
+            await asyncio.sleep(self.interval - elapsed)
+
+        self.last_call_time = time.monotonic()
+
+    async def __aexit__(self, exc_type, exc_val, exc_tb):
+        pass
+
+
+async def _repair_and_translate_chunk_with_retry(
+    chunk: str,
+    repair_llm_service: LLMProvider,
+    rate_limiter: RateLimiter,
+    max_retries: int = 2,
+) -> list[str]:
+    """
+    Repairs, translates, and optionally re-chunks a single text chunk using the small LLM, with rate limiting.
+    """
+    # 为了防止 LLM 上下文污染，在 user_prompt 中也加入明确的指令
+    user_prompt = f"""IGNORE ALL PREVIOUS INSTRUCTIONS. Your ONLY task is to process the following text chunk according to the system prompt provided.
+
+Text chunk to process:
+---
+{chunk}
+---
+"""
+    for attempt in range(max_retries + 1):
+        try:
+            async with rate_limiter:
+                response = await repair_llm_service.text_chat(
+                    prompt=user_prompt, system_prompt=TEXT_REPAIR_SYSTEM_PROMPT
+                )
+
+            llm_output = response.completion_text
+
+            if "<discard_chunk />" in llm_output:
+                return []  # Signal to discard this chunk
+
+            # More robust regex to handle potential LLM formatting errors (spaces, newlines in tags)
+            matches = re.findall(
+                r"<\s*repaired_text\s*>\s*(.*?)\s*<\s*/\s*repaired_text\s*>",
+                llm_output,
+                re.DOTALL,
+            )
+
+            if matches:
+                # Further cleaning to ensure no empty strings are returned
+                return [m.strip() for m in matches if m.strip()]
+            else:
+                # If no valid tags and not explicitly discarded, discard it to be safe.
+                return []
+        except Exception as e:
+            logger.warning(
+                f"  - LLM call failed on attempt {attempt + 1}/{max_retries + 1}. Error: {str(e)}"
+            )
+
+    logger.error(
+        f"  - Failed to process chunk after {max_retries + 1} attempts. Using original text."
+    )
+    return [chunk]
 
 
 class KBHelper:
@@ -100,7 +189,7 @@ class KBHelper:
     async def upload_document(
         self,
         file_name: str,
-        file_content: bytes,
+        file_content: bytes | None,
         file_type: str,
         chunk_size: int = 512,
         chunk_overlap: int = 50,
@@ -108,6 +197,7 @@ class KBHelper:
         tasks_limit: int = 3,
         max_retries: int = 3,
         progress_callback=None,
+        pre_chunked_text: list[str] | None = None,
     ) -> KBDocument:
         """上传并处理文档（带原子性保证和失败清理）
 
@@ -130,46 +220,63 @@ class KBHelper:
         await self._ensure_vec_db()
         doc_id = str(uuid.uuid4())
         media_paths: list[Path] = []
+        file_size = 0
 
         # file_path = self.kb_files_dir / f"{doc_id}.{file_type}"
         # async with aiofiles.open(file_path, "wb") as f:
         #     await f.write(file_content)
 
         try:
-            # 阶段1: 解析文档
-            if progress_callback:
-                await progress_callback("parsing", 0, 100)
-
-            parser = await select_parser(f".{file_type}")
-            parse_result = await parser.parse(file_content, file_name)
-            text_content = parse_result.text
-            media_items = parse_result.media
-
-            if progress_callback:
-                await progress_callback("parsing", 100, 100)
-
-            # 保存媒体文件
+            chunks_text = []
             saved_media = []
-            for media_item in media_items:
-                media = await self._save_media(
-                    doc_id=doc_id,
-                    media_type=media_item.media_type,
-                    file_name=media_item.file_name,
-                    content=media_item.content,
-                    mime_type=media_item.mime_type,
+
+            if pre_chunked_text is not None:
+                # 如果提供了预分块文本，直接使用
+                chunks_text = pre_chunked_text
+                file_size = sum(len(chunk) for chunk in chunks_text)
+                logger.info(f"使用预分块文本进行上传，共 {len(chunks_text)} 个块。")
+            else:
+                # 否则，执行标准的文件解析和分块流程
+                if file_content is None:
+                    raise ValueError(
+                        "当未提供 pre_chunked_text 时，file_content 不能为空。"
+                    )
+
+                file_size = len(file_content)
+
+                # 阶段1: 解析文档
+                if progress_callback:
+                    await progress_callback("parsing", 0, 100)
+
+                parser = await select_parser(f".{file_type}")
+                parse_result = await parser.parse(file_content, file_name)
+                text_content = parse_result.text
+                media_items = parse_result.media
+
+                if progress_callback:
+                    await progress_callback("parsing", 100, 100)
+
+                # 保存媒体文件
+                for media_item in media_items:
+                    media = await self._save_media(
+                        doc_id=doc_id,
+                        media_type=media_item.media_type,
+                        file_name=media_item.file_name,
+                        content=media_item.content,
+                        mime_type=media_item.mime_type,
+                    )
+                    saved_media.append(media)
+                    media_paths.append(Path(media.file_path))
+
+                # 阶段2: 分块
+                if progress_callback:
+                    await progress_callback("chunking", 0, 100)
+
+                chunks_text = await self.chunker.chunk(
+                    text_content,
+                    chunk_size=chunk_size,
+                    chunk_overlap=chunk_overlap,
                 )
-                saved_media.append(media)
-                media_paths.append(Path(media.file_path))
-
-            # 阶段2: 分块
-            if progress_callback:
-                await progress_callback("chunking", 0, 100)
-
-            chunks_text = await self.chunker.chunk(
-                text_content,
-                chunk_size=chunk_size,
-                chunk_overlap=chunk_overlap,
-            )
             contents = []
             metadatas = []
             for idx, chunk_text in enumerate(chunks_text):
@@ -205,7 +312,7 @@ class KBHelper:
                 kb_id=self.kb.kb_id,
                 doc_name=file_name,
                 file_type=file_type,
-                file_size=len(file_content),
+                file_size=file_size,
                 # file_path=str(file_path),
                 file_path="",
                 chunk_count=len(chunks_text),
@@ -359,3 +466,177 @@ class KBHelper:
         )
 
         return media
+
+    async def upload_from_url(
+        self,
+        url: str,
+        chunk_size: int = 512,
+        chunk_overlap: int = 50,
+        batch_size: int = 32,
+        tasks_limit: int = 3,
+        max_retries: int = 3,
+        progress_callback=None,
+        enable_cleaning: bool = False,
+        cleaning_provider_id: str | None = None,
+    ) -> KBDocument:
+        """从 URL 上传并处理文档（带原子性保证和失败清理）
+        Args:
+            url: 要提取内容的网页 URL
+            chunk_size: 文本块大小
+            chunk_overlap: 文本块重叠大小
+            batch_size: 批处理大小
+            tasks_limit: 并发任务限制
+            max_retries: 最大重试次数
+            progress_callback: 进度回调函数，接收参数 (stage, current, total)
+                - stage: 当前阶段 ('extracting', 'cleaning', 'parsing', 'chunking', 'embedding')
+                - current: 当前进度
+                - total: 总数
+        Returns:
+            KBDocument: 上传的文档对象
+        Raises:
+            ValueError: 如果 URL 为空或无法提取内容
+            IOError: 如果网络请求失败
+        """
+        # 获取 Tavily API 密钥
+        config = self.prov_mgr.acm.default_conf
+        tavily_keys = config.get("provider_settings", {}).get(
+            "websearch_tavily_key", []
+        )
+        if not tavily_keys:
+            raise ValueError(
+                "Error: Tavily API key is not configured in provider_settings."
+            )
+
+        # 阶段1: 从 URL 提取内容
+        if progress_callback:
+            await progress_callback("extracting", 0, 100)
+
+        try:
+            text_content = await extract_text_from_url(url, tavily_keys)
+        except Exception as e:
+            logger.error(f"Failed to extract content from URL {url}: {e}")
+            raise OSError(f"Failed to extract content from URL {url}: {e}") from e
+
+        if not text_content:
+            raise ValueError(f"No content extracted from URL: {url}")
+
+        if progress_callback:
+            await progress_callback("extracting", 100, 100)
+
+        # 阶段2: (可选)清洗内容并分块
+        final_chunks = await self._clean_and_rechunk_content(
+            content=text_content,
+            url=url,
+            progress_callback=progress_callback,
+            enable_cleaning=enable_cleaning,
+            cleaning_provider_id=cleaning_provider_id,
+            chunk_size=chunk_size,
+            chunk_overlap=chunk_overlap,
+        )
+
+        if enable_cleaning and not final_chunks:
+            raise ValueError(
+                "内容清洗后未提取到有效文本。请尝试关闭内容清洗功能，或更换更高性能的LLM模型后重试。"
+            )
+
+        # 创建一个虚拟文件名
+        file_name = url.split("/")[-1] or f"document_from_{url}"
+        if not Path(file_name).suffix:
+            file_name += ".url"
+
+        # 复用现有的 upload_document 方法，但传入预分块文本
+        return await self.upload_document(
+            file_name=file_name,
+            file_content=None,
+            file_type="url",  # 使用 'url' 作为特殊文件类型
+            chunk_size=chunk_size,
+            chunk_overlap=chunk_overlap,
+            batch_size=batch_size,
+            tasks_limit=tasks_limit,
+            max_retries=max_retries,
+            progress_callback=progress_callback,
+            pre_chunked_text=final_chunks,
+        )
+
+    async def _clean_and_rechunk_content(
+        self,
+        content: str,
+        url: str,
+        progress_callback=None,
+        enable_cleaning: bool = False,
+        cleaning_provider_id: str | None = None,
+        repair_max_rpm: int = 60,
+        chunk_size: int = 512,
+        chunk_overlap: int = 50,
+    ) -> list[str]:
+        """
+        对从 URL 获取的内容进行清洗、修复、翻译和重新分块。
+        """
+        if not enable_cleaning:
+            # 如果不启用清洗，则使用从前端传递的参数进行分块
+            logger.info(
+                f"内容清洗未启用，使用指定参数进行分块: chunk_size={chunk_size}, chunk_overlap={chunk_overlap}"
+            )
+            return await self.chunker.chunk(
+                content, chunk_size=chunk_size, chunk_overlap=chunk_overlap
+            )
+
+        if not cleaning_provider_id:
+            logger.warning(
+                "启用了内容清洗，但未提供 cleaning_provider_id，跳过清洗并使用默认分块。"
+            )
+            return await self.chunker.chunk(content)
+
+        if progress_callback:
+            await progress_callback("cleaning", 0, 100)
+
+        try:
+            # 获取指定的 LLM Provider
+            llm_provider = await self.prov_mgr.get_provider_by_id(cleaning_provider_id)
+            if not llm_provider or not isinstance(llm_provider, LLMProvider):
+                raise ValueError(
+                    f"无法找到 ID 为 {cleaning_provider_id} 的 LLM Provider 或类型不正确"
+                )
+
+            # 初步分块
+            # 优化分隔符，优先按段落分割，以获得更高质量的文本块
+            text_splitter = RecursiveCharacterChunker(
+                chunk_size=chunk_size,
+                chunk_overlap=chunk_overlap,
+                separators=["\n\n", "\n", " "],  # 优先使用段落分隔符
+            )
+            initial_chunks = await text_splitter.chunk(content)
+            logger.info(f"初步分块完成，生成 {len(initial_chunks)} 个块用于修复。")
+
+            # 并发处理所有块
+            rate_limiter = RateLimiter(repair_max_rpm)
+            tasks = [
+                _repair_and_translate_chunk_with_retry(
+                    chunk, llm_provider, rate_limiter
+                )
+                for chunk in initial_chunks
+            ]
+
+            repaired_results = await asyncio.gather(*tasks, return_exceptions=True)
+
+            final_chunks = []
+            for i, result in enumerate(repaired_results):
+                if isinstance(result, Exception):
+                    logger.warning(f"块 {i} 处理异常: {str(result)}. 回退到原始块。")
+                    final_chunks.append(initial_chunks[i])
+                elif isinstance(result, list):
+                    final_chunks.extend(result)
+
+            logger.info(
+                f"文本修复完成: {len(initial_chunks)} 个原始块 -> {len(final_chunks)} 个最终块。"
+            )
+
+            if progress_callback:
+                await progress_callback("cleaning", 100, 100)
+
+            return final_chunks
+
+        except Exception as e:
+            logger.error(f"使用 Provider '{cleaning_provider_id}' 清洗内容失败: {e}")
+            # 清洗失败，返回默认分块结果，保证流程不中断
+            return await self.chunker.chunk(content)

astrbot/core/knowledge_base/kb_mgr.py

@@ -8,7 +8,7 @@ from astrbot.core.provider.manager import ProviderManager
 from .chunking.recursive import RecursiveCharacterChunker
 from .kb_db_sqlite import KBSQLiteDatabase
 from .kb_helper import KBHelper
-from .models import KnowledgeBase
+from .models import KBDocument, KnowledgeBase
 from .retrieval.manager import RetrievalManager, RetrievalResult
 from .retrieval.rank_fusion import RankFusion
 from .retrieval.sparse_retriever import SparseRetriever
@@ -92,6 +92,8 @@ class KnowledgeBaseManager:
         top_m_final: int | None = None,
     ) -> KBHelper:
         """创建新的知识库实例"""
+        if embedding_provider_id is None:
+            raise ValueError("创建知识库时必须提供embedding_provider_id")
         kb = KnowledgeBase(
             kb_name=kb_name,
             description=description,
@@ -104,21 +106,26 @@ class KnowledgeBaseManager:
             top_k_sparse=top_k_sparse if top_k_sparse is not None else 50,
             top_m_final=top_m_final if top_m_final is not None else 5,
         )
-        async with self.kb_db.get_db() as session:
-            session.add(kb)
-            await session.commit()
-            await session.refresh(kb)
+        try:
+            async with self.kb_db.get_db() as session:
+                session.add(kb)
+                await session.flush()
 
-            kb_helper = KBHelper(
-                kb_db=self.kb_db,
-                kb=kb,
-                provider_manager=self.provider_manager,
-                kb_root_dir=FILES_PATH,
-                chunker=CHUNKER,
-            )
-            await kb_helper.initialize()
-        self.kb_insts[kb.kb_id] = kb_helper
-        return kb_helper
+                kb_helper = KBHelper(
+                    kb_db=self.kb_db,
+                    kb=kb,
+                    provider_manager=self.provider_manager,
+                    kb_root_dir=FILES_PATH,
+                    chunker=CHUNKER,
+                )
+                await kb_helper.initialize()
+                await session.commit()
+                self.kb_insts[kb.kb_id] = kb_helper
+                return kb_helper
+        except Exception as e:
+            if "kb_name" in str(e):
+                raise ValueError(f"知识库名称 '{kb_name}' 已存在")
+            raise
 
     async def get_kb(self, kb_id: str) -> KBHelper | None:
         """获取知识库实例"""
@@ -284,3 +291,47 @@ class KnowledgeBaseManager:
                 await self.kb_db.close()
             except Exception as e:
                 logger.error(f"关闭知识库元数据数据库失败: {e}")
+
+    async def upload_from_url(
+        self,
+        kb_id: str,
+        url: str,
+        chunk_size: int = 512,
+        chunk_overlap: int = 50,
+        batch_size: int = 32,
+        tasks_limit: int = 3,
+        max_retries: int = 3,
+        progress_callback=None,
+    ) -> KBDocument:
+        """从 URL 上传文档到指定的知识库
+
+        Args:
+            kb_id: 知识库 ID
+            url: 要提取内容的网页 URL
+            chunk_size: 文本块大小
+            chunk_overlap: 文本块重叠大小
+            batch_size: 批处理大小
+            tasks_limit: 并发任务限制
+            max_retries: 最大重试次数
+            progress_callback: 进度回调函数
+
+        Returns:
+            KBDocument: 上传的文档对象
+
+        Raises:
+            ValueError: 如果知识库不存在或 URL 为空
+            IOError: 如果网络请求失败
+        """
+        kb_helper = await self.get_kb(kb_id)
+        if not kb_helper:
+            raise ValueError(f"Knowledge base with id {kb_id} not found.")
+
+        return await kb_helper.upload_from_url(
+            url=url,
+            chunk_size=chunk_size,
+            chunk_overlap=chunk_overlap,
+            batch_size=batch_size,
+            tasks_limit=tasks_limit,
+            max_retries=max_retries,
+            progress_callback=progress_callback,
+        )

astrbot/core/knowledge_base/parsers/url_parser.py

@@ -0,0 +1,103 @@
+import asyncio
+
+import aiohttp
+
+
+class URLExtractor:
+    """URL 内容提取器，封装了 Tavily API 调用和密钥管理"""
+
+    def __init__(self, tavily_keys: list[str]):
+        """
+        初始化 URL 提取器
+
+        Args:
+            tavily_keys: Tavily API 密钥列表
+        """
+        if not tavily_keys:
+            raise ValueError("Error: Tavily API keys are not configured.")
+
+        self.tavily_keys = tavily_keys
+        self.tavily_key_index = 0
+        self.tavily_key_lock = asyncio.Lock()
+
+    async def _get_tavily_key(self) -> str:
+        """并发安全的从列表中获取并轮换Tavily API密钥。"""
+        async with self.tavily_key_lock:
+            key = self.tavily_keys[self.tavily_key_index]
+            self.tavily_key_index = (self.tavily_key_index + 1) % len(self.tavily_keys)
+            return key
+
+    async def extract_text_from_url(self, url: str) -> str:
+        """
+        使用 Tavily API 从 URL 提取主要文本内容。
+        这是 web_searcher 插件中 tavily_extract_web_page 方法的简化版本，
+        专门为知识库模块设计，不依赖 AstrMessageEvent。
+
+        Args:
+            url: 要提取内容的网页 URL
+
+        Returns:
+            提取的文本内容
+
+        Raises:
+            ValueError: 如果 URL 为空或 API 密钥未配置
+            IOError: 如果请求失败或返回错误
+        """
+        if not url:
+            raise ValueError("Error: url must be a non-empty string.")
+
+        tavily_key = await self._get_tavily_key()
+        api_url = "https://api.tavily.com/extract"
+        headers = {
+            "Authorization": f"Bearer {tavily_key}",
+            "Content-Type": "application/json",
+        }
+
+        payload = {
+            "urls": [url],
+            "extract_depth": "basic",  # 使用基础提取深度
+        }
+
+        try:
+            async with aiohttp.ClientSession(trust_env=True) as session:
+                async with session.post(
+                    api_url,
+                    json=payload,
+                    headers=headers,
+                    timeout=30.0,  # 增加超时时间，因为内容提取可能需要更长时间
+                ) as response:
+                    if response.status != 200:
+                        reason = await response.text()
+                        raise OSError(
+                            f"Tavily web extraction failed: {reason}, status: {response.status}"
+                        )
+
+                    data = await response.json()
+                    results = data.get("results", [])
+
+                    if not results:
+                        raise ValueError(f"No content extracted from URL: {url}")
+
+                    # 返回第一个结果的内容
+                    return results[0].get("raw_content", "")
+
+        except aiohttp.ClientError as e:
+            raise OSError(f"Failed to fetch URL {url}: {e}") from e
+        except Exception as e:
+            raise OSError(f"Failed to extract content from URL {url}: {e}") from e
+
+
+# 为了向后兼容，提供一个简单的函数接口
+async def extract_text_from_url(url: str, tavily_keys: list[str]) -> str:
+    """
+    简单的函数接口，用于从 URL 提取文本内容
+
+    Args:
+        url: 要提取内容的网页 URL
+        tavily_keys: Tavily API 密钥列表
+
+    Returns:
+        提取的文本内容
+    """
+    extractor = URLExtractor(tavily_keys)
+    return await extractor.extract_text_from_url(url)

astrbot/core/knowledge_base/prompts.py

@@ -0,0 +1,65 @@
+TEXT_REPAIR_SYSTEM_PROMPT = """You are a meticulous digital archivist. Your mission is to reconstruct a clean, readable article from raw, noisy text chunks.
+
+**Core Task:**
+1.  **Analyze:** Examine the text chunk to separate "signal" (substantive information) from "noise" (UI elements, ads, navigation, footers).
+2.  **Process:** Clean and repair the signal. **Do not translate it.** Keep the original language.
+
+**Crucial Rules:**
+- **NEVER discard a chunk if it contains ANY valuable information.** Your primary duty is to salvage content.
+- **If a chunk contains multiple distinct topics, split them.** Enclose each topic in its own `<repaired_text>` tag.
+- Your output MUST be ONLY `<repaired_text>...</repaired_text>` tags or a single `<discard_chunk />` tag.
+
+---
+**Example 1: Chunk with Noise and Signal**
+
+*Input Chunk:*
+"Home | About | Products | **The Llama is a domesticated South American camelid.** | © 2025 ACME Corp."
+
+*Your Thought Process:*
+1.  "Home | About | Products..." and "© 2025 ACME Corp." are noise.
+2.  "The Llama is a domesticated..." is the signal.
+3.  I must extract the signal and wrap it.
+
+*Your Output:*
+<repaired_text>
+The Llama is a domesticated South American camelid.
+</repaired_text>
+
+---
+**Example 2: Chunk with ONLY Noise**
+
+*Input Chunk:*
+"Next Page > | Subscribe to our newsletter | Follow us on X"
+
+*Your Thought Process:*
+1.  This entire chunk is noise. There is no signal.
+2.  I must discard this.
+
+*Your Output:*
+<discard_chunk />
+
+---
+**Example 3: Chunk with Multiple Topics (Requires Splitting)**
+
+*Input Chunk:*
+"## Chapter 1: The Sun
+The Sun is the star at the center of the Solar System.
+
+## Chapter 2: The Moon
+The Moon is Earth's only natural satellite."
+
+*Your Thought Process:*
+1.  This chunk contains two distinct topics.
+2.  I must process them separately to maintain semantic integrity.
+3.  I will create two `<repaired_text>` blocks.
+
+*Your Output:*
+<repaired_text>
+## Chapter 1: The Sun
+The Sun is the star at the center of the Solar System.
+</repaired_text>
+<repaired_text>
+## Chapter 2: The Moon
+The Moon is Earth's only natural satellite.
+</repaired_text>
+"""