merge: merge master into feat/unified_webhook

Resolved conflicts by keeping current branch changes for webhook feature files:
- src/langbot/libs/wecom_ai_bot_api/api.py
- src/langbot/libs/wecom_ai_bot_api/wecombotevent.py
- src/langbot/pkg/api/http/controller/groups/webhooks.py
- src/langbot/pkg/platform/sources/officialaccount.py
- src/langbot/pkg/platform/sources/qqofficial.py
- src/langbot/pkg/platform/sources/wecom.py
- src/langbot/pkg/platform/sources/wecombot.py

Merged master branch changes including:
- Project restructure: moved files from pkg/ and libs/ to src/langbot/
- New features: API key auth, MCP resources, pipeline extensions
- Documentation updates: AGENTS.md, CLAUDE.md, API docs

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

.github/pull_request_template.md

@@ -2,6 +2,17 @@
 
 > 请在此部分填写你实现/解决/优化的内容:  
 > Summary of what you implemented/solved/optimized:
+> 
+
+### 更改前后对比截图 / Screenshots
+
+> 请在此部分粘贴更改前后对比截图（可以是界面截图、控制台输出、对话截图等）:  
+> Please paste the screenshots of changes before and after here (can be interface screenshots, console output, conversation screenshots, etc.):
+> 
+> 修改前 / Before:
+> 
+> 修改后 / After:
+> 
 
 ## 检查清单 / Checklist
 
@@ -9,7 +20,7 @@
 
 *请在方括号间写`x`以打勾 / Please tick the box with `x`*
 
-- [ ] 阅读仓库[贡献指引](https://github.com/RockChinQ/LangBot/blob/master/CONTRIBUTING.md)了吗？ / Have you read the [contribution guide](https://github.com/RockChinQ/LangBot/blob/master/CONTRIBUTING.md)?
+- [ ] 阅读仓库[贡献指引](https://github.com/langbot-app/LangBot/blob/master/CONTRIBUTING.md)了吗？ / Have you read the [contribution guide](https://github.com/langbot-app/LangBot/blob/master/CONTRIBUTING.md)?
 - [ ] 与项目所有者沟通过了吗？ / Have you communicated with the project maintainer?
 - [ ] 我确定已自行测试所作的更改，确保功能符合预期。 / I have tested the changes and ensured they work as expected.
 

.github/workflows/build-docker-image.yml

@@ -1,10 +1,9 @@
 name: Build Docker Image
 on:
-  #防止fork乱用action设置只能手动触发构建
-  workflow_dispatch:
   ## 发布release的时候会自动构建
   release:
     types: [published]
+  workflow_dispatch:
 jobs:
   publish-docker-image:
     runs-on: ubuntu-latest
@@ -41,5 +40,9 @@ jobs:
         run: docker login --username=${{ secrets.DOCKER_USERNAME }} --password ${{ secrets.DOCKER_PASSWORD }}
       - name: Create Buildx
         run: docker buildx create --name mybuilder --use
-      - name: Build  # image name: rockchin/langbot:<VERSION>
-        run: docker buildx build --platform linux/arm64,linux/amd64 -t rockchin/langbot:${{ steps.check_version.outputs.version }} -t rockchin/langbot:latest . --push
+      - name: Build for Release # only relase, exlude pre-release
+        if: ${{ github.event.release.prerelease == false }}
+        run: docker buildx build --platform linux/amd64 -t rockchin/langbot:${{ steps.check_version.outputs.version }} -t rockchin/langbot:latest . --push
+      - name: Build for Pre-release # no update for latest tag
+        if: ${{ github.event.release.prerelease == true }}
+        run: docker buildx build --platform linux/amd64 -t rockchin/langbot:${{ steps.check_version.outputs.version }} . --push

.github/workflows/publish-to-pypi.yml

@@ -0,0 +1,46 @@
+name: Build and Publish to PyPI
+
+on:
+  workflow_dispatch:
+  release:
+    types: [published]
+
+jobs:
+  build-and-publish:
+    runs-on: ubuntu-latest
+    permissions:
+      contents: read
+      id-token: write  # Required for trusted publishing to PyPI
+    
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+        with:
+          persist-credentials: false
+
+      - name: Set up Node.js
+        uses: actions/setup-node@v4
+        with:
+          node-version: '22'
+
+      - name: Build frontend
+        run: |
+          cd web
+          npm install -g pnpm
+          pnpm install
+          pnpm build
+          mkdir -p ../src/langbot/web/out
+          cp -r out ../src/langbot/web/
+
+      - name: Install the latest version of uv
+        uses: astral-sh/setup-uv@v6
+        with:
+          version: "latest"
+
+      - name: Build package
+        run: |
+          uv build
+
+      - name: Publish to PyPI
+        run: |
+          uv publish --token ${{ secrets.PYPI_TOKEN }}

.github/workflows/run-tests.yml

@@ -0,0 +1,71 @@
+name: Unit Tests
+
+on:
+  pull_request:
+    types: [opened, ready_for_review, synchronize]
+    paths:
+      - 'pkg/**'
+      - 'tests/**'
+      - '.github/workflows/run-tests.yml'
+      - 'pyproject.toml'
+      - 'run_tests.sh'
+  push:
+    branches:
+      - master
+      - develop
+    paths:
+      - 'pkg/**'
+      - 'tests/**'
+      - '.github/workflows/run-tests.yml'
+      - 'pyproject.toml'
+      - 'run_tests.sh'
+
+jobs:
+  test:
+    name: Run Unit Tests
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        python-version: ['3.10', '3.11', '3.12']
+      fail-fast: false
+
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v5
+        with:
+          python-version: ${{ matrix.python-version }}
+
+      - name: Install uv
+        run: |
+          curl -LsSf https://astral.sh/uv/install.sh | sh
+          echo "$HOME/.cargo/bin" >> $GITHUB_PATH
+
+      - name: Install dependencies
+        run: |
+          uv sync --dev
+
+      - name: Run unit tests
+        run: |
+          bash run_tests.sh
+
+      - name: Upload coverage to Codecov
+        if: matrix.python-version == '3.12'
+        uses: codecov/codecov-action@v5
+        with:
+          files: ./coverage.xml
+          flags: unit-tests
+          name: unit-tests-coverage
+          fail_ci_if_error: false
+        env:
+          CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }}
+
+      - name: Test Summary
+        if: always()
+        run: |
+          echo "## Unit Tests Results" >> $GITHUB_STEP_SUMMARY
+          echo "" >> $GITHUB_STEP_SUMMARY
+          echo "Python Version: ${{ matrix.python-version }}" >> $GITHUB_STEP_SUMMARY
+          echo "Test Status: ${{ job.status }}" >> $GITHUB_STEP_SUMMARY

.github/workflows/test-dev-image.yaml

@@ -0,0 +1,108 @@
+name: Test Dev Image
+
+on:
+  workflow_run:
+    workflows: ["Build Dev Image"]
+    types:
+      - completed
+    branches:
+      - master
+
+jobs:
+  test-dev-image:
+    runs-on: ubuntu-latest
+    # Only run if the build workflow succeeded
+    if: ${{ github.event.workflow_run.conclusion == 'success' }}
+    
+    permissions:
+      contents: read
+    
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+
+      - name: Update Docker Compose to use master tag
+        working-directory: ./docker
+        run: |
+          # Replace 'latest' with 'master' tag for testing the dev image
+          sed -i 's/rockchin\/langbot:latest/rockchin\/langbot:master/g' docker-compose.yaml
+          echo "Updated docker-compose.yaml to use master tag:"
+          cat docker-compose.yaml
+
+      - name: Start Docker Compose
+        working-directory: ./docker
+        run: docker compose up -d
+
+      - name: Wait and Test API
+        run: |
+          # Function to test API endpoint
+          test_api() {
+            echo "Testing API endpoint..."
+            response=$(curl -s --connect-timeout 10 --max-time 30 -w "\n%{http_code}" http://localhost:5300/api/v1/system/info 2>&1)
+            curl_exit_code=$?
+            
+            if [ $curl_exit_code -ne 0 ]; then
+              echo "Curl failed with exit code: $curl_exit_code"
+              echo "Error: $response"
+              return 1
+            fi
+            
+            http_code=$(echo "$response" | tail -n 1)
+            response_body=$(echo "$response" | head -n -1)
+            
+            if [ "$http_code" = "200" ]; then
+              echo "API is healthy! Response code: $http_code"
+              echo "Response: $response_body"
+              return 0
+            else
+              echo "API returned non-200 response: $http_code"
+              echo "Response body: $response_body"
+              return 1
+            fi
+          }
+
+          # Wait 30 seconds before first attempt
+          echo "Waiting 30 seconds for services to start..."
+          sleep 30
+
+          # Try up to 3 times with 30-second intervals
+          max_attempts=3
+          attempt=1
+
+          while [ $attempt -le $max_attempts ]; do
+            echo "Attempt $attempt of $max_attempts"
+            
+            if test_api; then
+              echo "Success! API is responding correctly."
+              exit 0
+            fi
+            
+            if [ $attempt -lt $max_attempts ]; then
+              echo "Retrying in 30 seconds..."
+              sleep 30
+            fi
+            
+            attempt=$((attempt + 1))
+          done
+
+          # All attempts failed
+          echo "Failed to get healthy response after $max_attempts attempts"
+          exit 1
+
+      - name: Show Container Logs on Failure
+        if: failure()
+        working-directory: ./docker
+        run: |
+          echo "=== Docker Compose Status ==="
+          docker compose ps
+          echo ""
+          echo "=== LangBot Logs ==="
+          docker compose logs langbot
+          echo ""
+          echo "=== Plugin Runtime Logs ==="
+          docker compose logs langbot_plugin_runtime
+
+      - name: Cleanup
+        if: always()
+        working-directory: ./docker
+        run: docker compose down

.gitignore

@@ -22,7 +22,7 @@ tips.py
 venv*
 bin/
 .vscode
-test_*
+/test_*
 venv/
 hugchat.json
 qcapi
@@ -42,4 +42,14 @@ botpy.log*
 test.py
 /web_ui
 .venv/
-uv.lock
+uv.lock
+/test
+plugins.bak
+coverage.xml
+.coverage
+src/langbot/web/
+
+# Build artifacts
+/dist
+/build
+*.egg-info

AGENTS.md

@@ -0,0 +1,86 @@
+# AGENTS.md
+
+This file is for guiding code agents (like Claude Code, GitHub Copilot, OpenAI Codex, etc.) to work in LangBot project.
+
+## Project Overview
+
+LangBot is a open-source LLM native instant messaging bot development platform, aiming to provide an out-of-the-box IM robot development experience, with Agent, RAG, MCP and other LLM application functions, supporting global instant messaging platforms, and providing rich API interfaces, supporting custom development.
+
+LangBot has a comprehensive frontend, all operations can be performed through the frontend. The project splited into these major parts:
+
+- `./pkg`: The core python package of the project backend.
+    - `./pkg/platform`: The platform module of the project, containing the logic of message platform adapters, bot managers, message session managers, etc.
+    - `./pkg/provider`: The provider module of the project, containing the logic of LLM providers, tool providers, etc.
+    - `./pkg/pipeline`: The pipeline module of the project, containing the logic of pipelines, stages, query pool, etc.
+    - `./pkg/api`: The api module of the project, containing the http api controllers and services.
+    - `./pkg/plugin`: LangBot bridge for connecting with plugin system.
+- `./libs`: Some SDKs we previously developed for the project, such as `qq_official_api`, `wecom_api`, etc.
+- `./templates`: Templates of config files, components, etc.
+- `./web`: Frontend codebase, built with Next.js + **shadcn** + **Tailwind CSS**.
+- `./docker`: docker-compose deployment files.
+
+## Backend Development
+
+We use `uv` to manage dependencies.
+
+```bash
+pip install uv
+uv sync --dev
+```
+
+Start the backend and run the project in development mode.
+
+```bash
+uv run main.py
+```
+
+Then you can access the project at `http://127.0.0.1:5300`.
+
+## Frontend Development
+
+We use `pnpm` to manage dependencies.
+
+```bash
+cd web
+cp .env.example .env
+pnpm install
+pnpm dev
+```
+
+Then you can access the project at `http://127.0.0.1:3000`.
+
+## Plugin System Architecture
+
+LangBot is composed of various internal components such as Large Language Model tools, commands, messaging platform adapters, LLM requesters, and more. To meet extensibility and flexibility requirements, we have implemented a production-grade plugin system.
+
+Each plugin runs in an independent process, managed uniformly by the Plugin Runtime. It has two operating modes: `stdio` and `websocket`. When LangBot is started directly by users (not running in a container), it uses `stdio` mode, which is common for personal users or lightweight environments. When LangBot runs in a container, it uses `websocket` mode, designed specifically for production environments.
+
+Plugin Runtime automatically starts each installed plugin and interacts through stdio. In plugin development scenarios, developers can use the lbp command-line tool to start plugins and connect to the running Runtime via WebSocket for debugging.
+
+> Plugin SDK, CLI, Runtime, and entities definitions shared between LangBot and plugins are contained in the [`langbot-plugin-sdk`](https://github.com/langbot-app/langbot-plugin-sdk) repository.
+
+## Some Development Tips and Standards
+
+- LangBot is a global project, any comments in code should be in English, and user experience should be considered in all aspects.
+- Thus you should consider the i18n support in all aspects.
+- LangBot is widely adopted in both toC and toB scenarios, so you should consider the compatibility and security in all aspects.
+- If you were asked to make a commit, please follow the commit message format: 
+    - format: <type>(<scope>): <subject>
+    - type: must be a specific type, such as feat (new feature), fix (bug fix), docs (documentation), style (code style), refactor (refactoring), perf (performance optimization), etc.
+    - scope: the scope of the commit, such as the package name, the file name, the function name, the class name, the module name, etc.
+    - subject: the subject of the commit, such as the description of the commit, the reason for the commit, the impact of the commit, etc.
+
+## Some Principles
+
+- Keep it simple, stupid.
+- Entities should not be multiplied unnecessarily
+- 八荣八耻
+
+    以瞎猜接口为耻，以认真查询为荣。
+    以模糊执行为耻，以寻求确认为荣。
+    以臆想业务为耻，以人类确认为荣。
+    以创造接口为耻，以复用现有为荣。
+    以跳过验证为耻，以主动测试为荣。
+    以破坏架构为耻，以遵循规范为荣。
+    以假装理解为耻，以诚实无知为荣。
+    以盲目修改为耻，以谨慎重构为荣。

CLAUDE.md

@@ -0,0 +1 @@
+AGENTS.md

LICENSE

@@ -1,661 +1,201 @@
-                    GNU AFFERO GENERAL PUBLIC LICENSE
-                       Version 3, 19 November 2007
-
- Copyright (C) 2007 Free Software Foundation, Inc. <https://fsf.org/>
- Everyone is permitted to copy and distribute verbatim copies
- of this license document, but changing it is not allowed.
-
-                            Preamble
-
-  The GNU Affero General Public License is a free, copyleft license for
-software and other kinds of works, specifically designed to ensure
-cooperation with the community in the case of network server software.
-
-  The licenses for most software and other practical works are designed
-to take away your freedom to share and change the works.  By contrast,
-our General Public Licenses are intended to guarantee your freedom to
-share and change all versions of a program--to make sure it remains free
-software for all its users.
-
-  When we speak of free software, we are referring to freedom, not
-price.  Our General Public Licenses are designed to make sure that you
-have the freedom to distribute copies of free software (and charge for
-them if you wish), that you receive source code or can get it if you
-want it, that you can change the software or use pieces of it in new
-free programs, and that you know you can do these things.
-
-  Developers that use our General Public Licenses protect your rights
-with two steps: (1) assert copyright on the software, and (2) offer
-you this License which gives you legal permission to copy, distribute
-and/or modify the software.
-
-  A secondary benefit of defending all users' freedom is that
-improvements made in alternate versions of the program, if they
-receive widespread use, become available for other developers to
-incorporate.  Many developers of free software are heartened and
-encouraged by the resulting cooperation.  However, in the case of
-software used on network servers, this result may fail to come about.
-The GNU General Public License permits making a modified version and
-letting the public access it on a server without ever releasing its
-source code to the public.
-
-  The GNU Affero General Public License is designed specifically to
-ensure that, in such cases, the modified source code becomes available
-to the community.  It requires the operator of a network server to
-provide the source code of the modified version running there to the
-users of that server.  Therefore, public use of a modified version, on
-a publicly accessible server, gives the public access to the source
-code of the modified version.
-
-  An older license, called the Affero General Public License and
-published by Affero, was designed to accomplish similar goals.  This is
-a different license, not a version of the Affero GPL, but Affero has
-released a new version of the Affero GPL which permits relicensing under
-this license.
-
-  The precise terms and conditions for copying, distribution and
-modification follow.
-
-                       TERMS AND CONDITIONS
-
-  0. Definitions.
-
-  "This License" refers to version 3 of the GNU Affero General Public License.
-
-  "Copyright" also means copyright-like laws that apply to other kinds of
-works, such as semiconductor masks.
-
-  "The Program" refers to any copyrightable work licensed under this
-License.  Each licensee is addressed as "you".  "Licensees" and
-"recipients" may be individuals or organizations.
-
-  To "modify" a work means to copy from or adapt all or part of the work
-in a fashion requiring copyright permission, other than the making of an
-exact copy.  The resulting work is called a "modified version" of the
-earlier work or a work "based on" the earlier work.
-
-  A "covered work" means either the unmodified Program or a work based
-on the Program.
-
-  To "propagate" a work means to do anything with it that, without
-permission, would make you directly or secondarily liable for
-infringement under applicable copyright law, except executing it on a
-computer or modifying a private copy.  Propagation includes copying,
-distribution (with or without modification), making available to the
-public, and in some countries other activities as well.
-
-  To "convey" a work means any kind of propagation that enables other
-parties to make or receive copies.  Mere interaction with a user through
-a computer network, with no transfer of a copy, is not conveying.
-
-  An interactive user interface displays "Appropriate Legal Notices"
-to the extent that it includes a convenient and prominently visible
-feature that (1) displays an appropriate copyright notice, and (2)
-tells the user that there is no warranty for the work (except to the
-extent that warranties are provided), that licensees may convey the
-work under this License, and how to view a copy of this License.  If
-the interface presents a list of user commands or options, such as a
-menu, a prominent item in the list meets this criterion.
-
-  1. Source Code.
-
-  The "source code" for a work means the preferred form of the work
-for making modifications to it.  "Object code" means any non-source
-form of a work.
-
-  A "Standard Interface" means an interface that either is an official
-standard defined by a recognized standards body, or, in the case of
-interfaces specified for a particular programming language, one that
-is widely used among developers working in that language.
-
-  The "System Libraries" of an executable work include anything, other
-than the work as a whole, that (a) is included in the normal form of
-packaging a Major Component, but which is not part of that Major
-Component, and (b) serves only to enable use of the work with that
-Major Component, or to implement a Standard Interface for which an
-implementation is available to the public in source code form.  A
-"Major Component", in this context, means a major essential component
-(kernel, window system, and so on) of the specific operating system
-(if any) on which the executable work runs, or a compiler used to
-produce the work, or an object code interpreter used to run it.
-
-  The "Corresponding Source" for a work in object code form means all
-the source code needed to generate, install, and (for an executable
-work) run the object code and to modify the work, including scripts to
-control those activities.  However, it does not include the work's
-System Libraries, or general-purpose tools or generally available free
-programs which are used unmodified in performing those activities but
-which are not part of the work.  For example, Corresponding Source
-includes interface definition files associated with source files for
-the work, and the source code for shared libraries and dynamically
-linked subprograms that the work is specifically designed to require,
-such as by intimate data communication or control flow between those
-subprograms and other parts of the work.
-
-  The Corresponding Source need not include anything that users
-can regenerate automatically from other parts of the Corresponding
-Source.
-
-  The Corresponding Source for a work in source code form is that
-same work.
-
-  2. Basic Permissions.
-
-  All rights granted under this License are granted for the term of
-copyright on the Program, and are irrevocable provided the stated
-conditions are met.  This License explicitly affirms your unlimited
-permission to run the unmodified Program.  The output from running a
-covered work is covered by this License only if the output, given its
-content, constitutes a covered work.  This License acknowledges your
-rights of fair use or other equivalent, as provided by copyright law.
-
-  You may make, run and propagate covered works that you do not
-convey, without conditions so long as your license otherwise remains
-in force.  You may convey covered works to others for the sole purpose
-of having them make modifications exclusively for you, or provide you
-with facilities for running those works, provided that you comply with
-the terms of this License in conveying all material for which you do
-not control copyright.  Those thus making or running the covered works
-for you must do so exclusively on your behalf, under your direction
-and control, on terms that prohibit them from making any copies of
-your copyrighted material outside their relationship with you.
-
-  Conveying under any other circumstances is permitted solely under
-the conditions stated below.  Sublicensing is not allowed; section 10
-makes it unnecessary.
-
-  3. Protecting Users' Legal Rights From Anti-Circumvention Law.
-
-  No covered work shall be deemed part of an effective technological
-measure under any applicable law fulfilling obligations under article
-11 of the WIPO copyright treaty adopted on 20 December 1996, or
-similar laws prohibiting or restricting circumvention of such
-measures.
-
-  When you convey a covered work, you waive any legal power to forbid
-circumvention of technological measures to the extent such circumvention
-is effected by exercising rights under this License with respect to
-the covered work, and you disclaim any intention to limit operation or
-modification of the work as a means of enforcing, against the work's
-users, your or third parties' legal rights to forbid circumvention of
-technological measures.
-
-  4. Conveying Verbatim Copies.
-
-  You may convey verbatim copies of the Program's source code as you
-receive it, in any medium, provided that you conspicuously and
-appropriately publish on each copy an appropriate copyright notice;
-keep intact all notices stating that this License and any
-non-permissive terms added in accord with section 7 apply to the code;
-keep intact all notices of the absence of any warranty; and give all
-recipients a copy of this License along with the Program.
-
-  You may charge any price or no price for each copy that you convey,
-and you may offer support or warranty protection for a fee.
-
-  5. Conveying Modified Source Versions.
-
-  You may convey a work based on the Program, or the modifications to
-produce it from the Program, in the form of source code under the
-terms of section 4, provided that you also meet all of these conditions:
-
-    a) The work must carry prominent notices stating that you modified
-    it, and giving a relevant date.
-
-    b) The work must carry prominent notices stating that it is
-    released under this License and any conditions added under section
-    7.  This requirement modifies the requirement in section 4 to
-    "keep intact all notices".
-
-    c) You must license the entire work, as a whole, under this
-    License to anyone who comes into possession of a copy.  This
-    License will therefore apply, along with any applicable section 7
-    additional terms, to the whole of the work, and all its parts,
-    regardless of how they are packaged.  This License gives no
-    permission to license the work in any other way, but it does not
-    invalidate such permission if you have separately received it.
-
-    d) If the work has interactive user interfaces, each must display
-    Appropriate Legal Notices; however, if the Program has interactive
-    interfaces that do not display Appropriate Legal Notices, your
-    work need not make them do so.
-
-  A compilation of a covered work with other separate and independent
-works, which are not by their nature extensions of the covered work,
-and which are not combined with it such as to form a larger program,
-in or on a volume of a storage or distribution medium, is called an
-"aggregate" if the compilation and its resulting copyright are not
-used to limit the access or legal rights of the compilation's users
-beyond what the individual works permit.  Inclusion of a covered work
-in an aggregate does not cause this License to apply to the other
-parts of the aggregate.
-
-  6. Conveying Non-Source Forms.
-
-  You may convey a covered work in object code form under the terms
-of sections 4 and 5, provided that you also convey the
-machine-readable Corresponding Source under the terms of this License,
-in one of these ways:
-
-    a) Convey the object code in, or embodied in, a physical product
-    (including a physical distribution medium), accompanied by the
-    Corresponding Source fixed on a durable physical medium
-    customarily used for software interchange.
-
-    b) Convey the object code in, or embodied in, a physical product
-    (including a physical distribution medium), accompanied by a
-    written offer, valid for at least three years and valid for as
-    long as you offer spare parts or customer support for that product
-    model, to give anyone who possesses the object code either (1) a
-    copy of the Corresponding Source for all the software in the
-    product that is covered by this License, on a durable physical
-    medium customarily used for software interchange, for a price no
-    more than your reasonable cost of physically performing this
-    conveying of source, or (2) access to copy the
-    Corresponding Source from a network server at no charge.
-
-    c) Convey individual copies of the object code with a copy of the
-    written offer to provide the Corresponding Source.  This
-    alternative is allowed only occasionally and noncommercially, and
-    only if you received the object code with such an offer, in accord
-    with subsection 6b.
-
-    d) Convey the object code by offering access from a designated
-    place (gratis or for a charge), and offer equivalent access to the
-    Corresponding Source in the same way through the same place at no
-    further charge.  You need not require recipients to copy the
-    Corresponding Source along with the object code.  If the place to
-    copy the object code is a network server, the Corresponding Source
-    may be on a different server (operated by you or a third party)
-    that supports equivalent copying facilities, provided you maintain
-    clear directions next to the object code saying where to find the
-    Corresponding Source.  Regardless of what server hosts the
-    Corresponding Source, you remain obligated to ensure that it is
-    available for as long as needed to satisfy these requirements.
-
-    e) Convey the object code using peer-to-peer transmission, provided
-    you inform other peers where the object code and Corresponding
-    Source of the work are being offered to the general public at no
-    charge under subsection 6d.
-
-  A separable portion of the object code, whose source code is excluded
-from the Corresponding Source as a System Library, need not be
-included in conveying the object code work.
-
-  A "User Product" is either (1) a "consumer product", which means any
-tangible personal property which is normally used for personal, family,
-or household purposes, or (2) anything designed or sold for incorporation
-into a dwelling.  In determining whether a product is a consumer product,
-doubtful cases shall be resolved in favor of coverage.  For a particular
-product received by a particular user, "normally used" refers to a
-typical or common use of that class of product, regardless of the status
-of the particular user or of the way in which the particular user
-actually uses, or expects or is expected to use, the product.  A product
-is a consumer product regardless of whether the product has substantial
-commercial, industrial or non-consumer uses, unless such uses represent
-the only significant mode of use of the product.
-
-  "Installation Information" for a User Product means any methods,
-procedures, authorization keys, or other information required to install
-and execute modified versions of a covered work in that User Product from
-a modified version of its Corresponding Source.  The information must
-suffice to ensure that the continued functioning of the modified object
-code is in no case prevented or interfered with solely because
-modification has been made.
-
-  If you convey an object code work under this section in, or with, or
-specifically for use in, a User Product, and the conveying occurs as
-part of a transaction in which the right of possession and use of the
-User Product is transferred to the recipient in perpetuity or for a
-fixed term (regardless of how the transaction is characterized), the
-Corresponding Source conveyed under this section must be accompanied
-by the Installation Information.  But this requirement does not apply
-if neither you nor any third party retains the ability to install
-modified object code on the User Product (for example, the work has
-been installed in ROM).
-
-  The requirement to provide Installation Information does not include a
-requirement to continue to provide support service, warranty, or updates
-for a work that has been modified or installed by the recipient, or for
-the User Product in which it has been modified or installed.  Access to a
-network may be denied when the modification itself materially and
-adversely affects the operation of the network or violates the rules and
-protocols for communication across the network.
-
-  Corresponding Source conveyed, and Installation Information provided,
-in accord with this section must be in a format that is publicly
-documented (and with an implementation available to the public in
-source code form), and must require no special password or key for
-unpacking, reading or copying.
-
-  7. Additional Terms.
-
-  "Additional permissions" are terms that supplement the terms of this
-License by making exceptions from one or more of its conditions.
-Additional permissions that are applicable to the entire Program shall
-be treated as though they were included in this License, to the extent
-that they are valid under applicable law.  If additional permissions
-apply only to part of the Program, that part may be used separately
-under those permissions, but the entire Program remains governed by
-this License without regard to the additional permissions.
-
-  When you convey a copy of a covered work, you may at your option
-remove any additional permissions from that copy, or from any part of
-it.  (Additional permissions may be written to require their own
-removal in certain cases when you modify the work.)  You may place
-additional permissions on material, added by you to a covered work,
-for which you have or can give appropriate copyright permission.
-
-  Notwithstanding any other provision of this License, for material you
-add to a covered work, you may (if authorized by the copyright holders of
-that material) supplement the terms of this License with terms:
-
-    a) Disclaiming warranty or limiting liability differently from the
-    terms of sections 15 and 16 of this License; or
-
-    b) Requiring preservation of specified reasonable legal notices or
-    author attributions in that material or in the Appropriate Legal
-    Notices displayed by works containing it; or
-
-    c) Prohibiting misrepresentation of the origin of that material, or
-    requiring that modified versions of such material be marked in
-    reasonable ways as different from the original version; or
-
-    d) Limiting the use for publicity purposes of names of licensors or
-    authors of the material; or
-
-    e) Declining to grant rights under trademark law for use of some
-    trade names, trademarks, or service marks; or
-
-    f) Requiring indemnification of licensors and authors of that
-    material by anyone who conveys the material (or modified versions of
-    it) with contractual assumptions of liability to the recipient, for
-    any liability that these contractual assumptions directly impose on
-    those licensors and authors.
-
-  All other non-permissive additional terms are considered "further
-restrictions" within the meaning of section 10.  If the Program as you
-received it, or any part of it, contains a notice stating that it is
-governed by this License along with a term that is a further
-restriction, you may remove that term.  If a license document contains
-a further restriction but permits relicensing or conveying under this
-License, you may add to a covered work material governed by the terms
-of that license document, provided that the further restriction does
-not survive such relicensing or conveying.
-
-  If you add terms to a covered work in accord with this section, you
-must place, in the relevant source files, a statement of the
-additional terms that apply to those files, or a notice indicating
-where to find the applicable terms.
-
-  Additional terms, permissive or non-permissive, may be stated in the
-form of a separately written license, or stated as exceptions;
-the above requirements apply either way.
-
-  8. Termination.
-
-  You may not propagate or modify a covered work except as expressly
-provided under this License.  Any attempt otherwise to propagate or
-modify it is void, and will automatically terminate your rights under
-this License (including any patent licenses granted under the third
-paragraph of section 11).
-
-  However, if you cease all violation of this License, then your
-license from a particular copyright holder is reinstated (a)
-provisionally, unless and until the copyright holder explicitly and
-finally terminates your license, and (b) permanently, if the copyright
-holder fails to notify you of the violation by some reasonable means
-prior to 60 days after the cessation.
-
-  Moreover, your license from a particular copyright holder is
-reinstated permanently if the copyright holder notifies you of the
-violation by some reasonable means, this is the first time you have
-received notice of violation of this License (for any work) from that
-copyright holder, and you cure the violation prior to 30 days after
-your receipt of the notice.
-
-  Termination of your rights under this section does not terminate the
-licenses of parties who have received copies or rights from you under
-this License.  If your rights have been terminated and not permanently
-reinstated, you do not qualify to receive new licenses for the same
-material under section 10.
-
-  9. Acceptance Not Required for Having Copies.
-
-  You are not required to accept this License in order to receive or
-run a copy of the Program.  Ancillary propagation of a covered work
-occurring solely as a consequence of using peer-to-peer transmission
-to receive a copy likewise does not require acceptance.  However,
-nothing other than this License grants you permission to propagate or
-modify any covered work.  These actions infringe copyright if you do
-not accept this License.  Therefore, by modifying or propagating a
-covered work, you indicate your acceptance of this License to do so.
-
-  10. Automatic Licensing of Downstream Recipients.
-
-  Each time you convey a covered work, the recipient automatically
-receives a license from the original licensors, to run, modify and
-propagate that work, subject to this License.  You are not responsible
-for enforcing compliance by third parties with this License.
-
-  An "entity transaction" is a transaction transferring control of an
-organization, or substantially all assets of one, or subdividing an
-organization, or merging organizations.  If propagation of a covered
-work results from an entity transaction, each party to that
-transaction who receives a copy of the work also receives whatever
-licenses to the work the party's predecessor in interest had or could
-give under the previous paragraph, plus a right to possession of the
-Corresponding Source of the work from the predecessor in interest, if
-the predecessor has it or can get it with reasonable efforts.
-
-  You may not impose any further restrictions on the exercise of the
-rights granted or affirmed under this License.  For example, you may
-not impose a license fee, royalty, or other charge for exercise of
-rights granted under this License, and you may not initiate litigation
-(including a cross-claim or counterclaim in a lawsuit) alleging that
-any patent claim is infringed by making, using, selling, offering for
-sale, or importing the Program or any portion of it.
-
-  11. Patents.
-
-  A "contributor" is a copyright holder who authorizes use under this
-License of the Program or a work on which the Program is based.  The
-work thus licensed is called the contributor's "contributor version".
-
-  A contributor's "essential patent claims" are all patent claims
-owned or controlled by the contributor, whether already acquired or
-hereafter acquired, that would be infringed by some manner, permitted
-by this License, of making, using, or selling its contributor version,
-but do not include claims that would be infringed only as a
-consequence of further modification of the contributor version.  For
-purposes of this definition, "control" includes the right to grant
-patent sublicenses in a manner consistent with the requirements of
-this License.
-
-  Each contributor grants you a non-exclusive, worldwide, royalty-free
-patent license under the contributor's essential patent claims, to
-make, use, sell, offer for sale, import and otherwise run, modify and
-propagate the contents of its contributor version.
-
-  In the following three paragraphs, a "patent license" is any express
-agreement or commitment, however denominated, not to enforce a patent
-(such as an express permission to practice a patent or covenant not to
-sue for patent infringement).  To "grant" such a patent license to a
-party means to make such an agreement or commitment not to enforce a
-patent against the party.
-
-  If you convey a covered work, knowingly relying on a patent license,
-and the Corresponding Source of the work is not available for anyone
-to copy, free of charge and under the terms of this License, through a
-publicly available network server or other readily accessible means,
-then you must either (1) cause the Corresponding Source to be so
-available, or (2) arrange to deprive yourself of the benefit of the
-patent license for this particular work, or (3) arrange, in a manner
-consistent with the requirements of this License, to extend the patent
-license to downstream recipients.  "Knowingly relying" means you have
-actual knowledge that, but for the patent license, your conveying the
-covered work in a country, or your recipient's use of the covered work
-in a country, would infringe one or more identifiable patents in that
-country that you have reason to believe are valid.
-
-  If, pursuant to or in connection with a single transaction or
-arrangement, you convey, or propagate by procuring conveyance of, a
-covered work, and grant a patent license to some of the parties
-receiving the covered work authorizing them to use, propagate, modify
-or convey a specific copy of the covered work, then the patent license
-you grant is automatically extended to all recipients of the covered
-work and works based on it.
-
-  A patent license is "discriminatory" if it does not include within
-the scope of its coverage, prohibits the exercise of, or is
-conditioned on the non-exercise of one or more of the rights that are
-specifically granted under this License.  You may not convey a covered
-work if you are a party to an arrangement with a third party that is
-in the business of distributing software, under which you make payment
-to the third party based on the extent of your activity of conveying
-the work, and under which the third party grants, to any of the
-parties who would receive the covered work from you, a discriminatory
-patent license (a) in connection with copies of the covered work
-conveyed by you (or copies made from those copies), or (b) primarily
-for and in connection with specific products or compilations that
-contain the covered work, unless you entered into that arrangement,
-or that patent license was granted, prior to 28 March 2007.
-
-  Nothing in this License shall be construed as excluding or limiting
-any implied license or other defenses to infringement that may
-otherwise be available to you under applicable patent law.
-
-  12. No Surrender of Others' Freedom.
-
-  If conditions are imposed on you (whether by court order, agreement or
-otherwise) that contradict the conditions of this License, they do not
-excuse you from the conditions of this License.  If you cannot convey a
-covered work so as to satisfy simultaneously your obligations under this
-License and any other pertinent obligations, then as a consequence you may
-not convey it at all.  For example, if you agree to terms that obligate you
-to collect a royalty for further conveying from those to whom you convey
-the Program, the only way you could satisfy both those terms and this
-License would be to refrain entirely from conveying the Program.
-
-  13. Remote Network Interaction; Use with the GNU General Public License.
-
-  Notwithstanding any other provision of this License, if you modify the
-Program, your modified version must prominently offer all users
-interacting with it remotely through a computer network (if your version
-supports such interaction) an opportunity to receive the Corresponding
-Source of your version by providing access to the Corresponding Source
-from a network server at no charge, through some standard or customary
-means of facilitating copying of software.  This Corresponding Source
-shall include the Corresponding Source for any work covered by version 3
-of the GNU General Public License that is incorporated pursuant to the
-following paragraph.
-
-  Notwithstanding any other provision of this License, you have
-permission to link or combine any covered work with a work licensed
-under version 3 of the GNU General Public License into a single
-combined work, and to convey the resulting work.  The terms of this
-License will continue to apply to the part which is the covered work,
-but the work with which it is combined will remain governed by version
-3 of the GNU General Public License.
-
-  14. Revised Versions of this License.
-
-  The Free Software Foundation may publish revised and/or new versions of
-the GNU Affero General Public License from time to time.  Such new versions
-will be similar in spirit to the present version, but may differ in detail to
-address new problems or concerns.
-
-  Each version is given a distinguishing version number.  If the
-Program specifies that a certain numbered version of the GNU Affero General
-Public License "or any later version" applies to it, you have the
-option of following the terms and conditions either of that numbered
-version or of any later version published by the Free Software
-Foundation.  If the Program does not specify a version number of the
-GNU Affero General Public License, you may choose any version ever published
-by the Free Software Foundation.
-
-  If the Program specifies that a proxy can decide which future
-versions of the GNU Affero General Public License can be used, that proxy's
-public statement of acceptance of a version permanently authorizes you
-to choose that version for the Program.
-
-  Later license versions may give you additional or different
-permissions.  However, no additional obligations are imposed on any
-author or copyright holder as a result of your choosing to follow a
-later version.
-
-  15. Disclaimer of Warranty.
-
-  THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
-APPLICABLE LAW.  EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
-HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY
-OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO,
-THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
-PURPOSE.  THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM
-IS WITH YOU.  SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF
-ALL NECESSARY SERVICING, REPAIR OR CORRECTION.
-
-  16. Limitation of Liability.
-
-  IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING
-WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS
-THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY
-GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE
-USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF
-DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD
-PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS),
-EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF
-SUCH DAMAGES.
-
-  17. Interpretation of Sections 15 and 16.
-
-  If the disclaimer of warranty and limitation of liability provided
-above cannot be given local legal effect according to their terms,
-reviewing courts shall apply local law that most closely approximates
-an absolute waiver of all civil liability in connection with the
-Program, unless a warranty or assumption of liability accompanies a
-copy of the Program in return for a fee.
-
-                     END OF TERMS AND CONDITIONS
-
-            How to Apply These Terms to Your New Programs
-
-  If you develop a new program, and you want it to be of the greatest
-possible use to the public, the best way to achieve this is to make it
-free software which everyone can redistribute and change under these terms.
-
-  To do so, attach the following notices to the program.  It is safest
-to attach them to the start of each source file to most effectively
-state the exclusion of warranty; and each file should have at least
-the "copyright" line and a pointer to where the full notice is found.
-
-    <one line to give the program's name and a brief idea of what it does.>
-    Copyright (C) <year>  <name of author>
-
-    This program is free software: you can redistribute it and/or modify
-    it under the terms of the GNU Affero General Public License as published
-    by the Free Software Foundation, either version 3 of the License, or
-    (at your option) any later version.
-
-    This program is distributed in the hope that it will be useful,
-    but WITHOUT ANY WARRANTY; without even the implied warranty of
-    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
-    GNU Affero General Public License for more details.
-
-    You should have received a copy of the GNU Affero General Public License
-    along with this program.  If not, see <https://www.gnu.org/licenses/>.
-
-Also add information on how to contact you by electronic and paper mail.
-
-  If your software can interact with users remotely through a computer
-network, you should also make sure that it provides a way for users to
-get its source.  For example, if your program is a web application, its
-interface could display a "Source" link that leads users to an archive
-of the code.  There are many ways you could offer source, and different
-solutions will be better for different programs; see section 13 for the
-specific requirements.
-
-  You should also get your employer (if you work as a programmer) or school,
-if any, to sign a "copyright disclaimer" for the program, if necessary.
-For more information on this, and how to apply and follow the GNU AGPL, see
-<https://www.gnu.org/licenses/>.
+                                 Apache License
+                           Version 2.0, January 2004
+                        http://www.apache.org/licenses/
+
+   TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
+
+   1. Definitions.
+
+      "License" shall mean the terms and conditions for use, reproduction,
+      and distribution as defined by Sections 1 through 9 of this document.
+
+      "Licensor" shall mean the copyright owner or entity authorized by
+      the copyright owner that is granting the License.
+
+      "Legal Entity" shall mean the union of the acting entity and all
+      other entities that control, are controlled by, or are under common
+      control with that entity. For the purposes of this definition,
+      "control" means (i) the power, direct or indirect, to cause the
+      direction or management of such entity, whether by contract or
+      otherwise, or (ii) ownership of fifty percent (50%) or more of the
+      outstanding shares, or (iii) beneficial ownership of such entity.
+
+      "You" (or "Your") shall mean an individual or Legal Entity
+      exercising permissions granted by this License.
+
+      "Source" form shall mean the preferred form for making modifications,
+      including but not limited to software source code, documentation
+      source, and configuration files.
+
+      "Object" form shall mean any form resulting from mechanical
+      transformation or translation of a Source form, including but
+      not limited to compiled object code, generated documentation,
+      and conversions to other media types.
+
+      "Work" shall mean the work of authorship, whether in Source or
+      Object form, made available under the License, as indicated by a
+      copyright notice that is included in or attached to the work
+      (an example is provided in the Appendix below).
+
+      "Derivative Works" shall mean any work, whether in Source or Object
+      form, that is based on (or derived from) the Work and for which the
+      editorial revisions, annotations, elaborations, or other modifications
+      represent, as a whole, an original work of authorship. For the purposes
+      of this License, Derivative Works shall not include works that remain
+      separable from, or merely link (or bind by name) to the interfaces of,
+      the Work and Derivative Works thereof.
+
+      "Contribution" shall mean any work of authorship, including
+      the original version of the Work and any modifications or additions
+      to that Work or Derivative Works thereof, that is intentionally
+      submitted to Licensor for inclusion in the Work by the copyright owner
+      or by an individual or Legal Entity authorized to submit on behalf of
+      the copyright owner. For the purposes of this definition, "submitted"
+      means any form of electronic, verbal, or written communication sent
+      to the Licensor or its representatives, including but not limited to
+      communication on electronic mailing lists, source code control systems,
+      and issue tracking systems that are managed by, or on behalf of, the
+      Licensor for the purpose of discussing and improving the Work, but
+      excluding communication that is conspicuously marked or otherwise
+      designated in writing by the copyright owner as "Not a Contribution."
+
+      "Contributor" shall mean Licensor and any individual or Legal Entity
+      on behalf of whom a Contribution has been received by Licensor and
+      subsequently incorporated within the Work.
+
+   2. Grant of Copyright License. Subject to the terms and conditions of
+      this License, each Contributor hereby grants to You a perpetual,
+      worldwide, non-exclusive, no-charge, royalty-free, irrevocable
+      copyright license to reproduce, prepare Derivative Works of,
+      publicly display, publicly perform, sublicense, and distribute the
+      Work and such Derivative Works in Source or Object form.
+
+   3. Grant of Patent License. Subject to the terms and conditions of
+      this License, each Contributor hereby grants to You a perpetual,
+      worldwide, non-exclusive, no-charge, royalty-free, irrevocable
+      (except as stated in this section) patent license to make, have made,
+      use, offer to sell, sell, import, and otherwise transfer the Work,
+      where such license applies only to those patent claims licensable
+      by such Contributor that are necessarily infringed by their
+      Contribution(s) alone or by combination of their Contribution(s)
+      with the Work to which such Contribution(s) was submitted. If You
+      institute patent litigation against any entity (including a
+      cross-claim or counterclaim in a lawsuit) alleging that the Work
+      or a Contribution incorporated within the Work constitutes direct
+      or contributory patent infringement, then any patent licenses
+      granted to You under this License for that Work shall terminate
+      as of the date such litigation is filed.
+
+   4. Redistribution. You may reproduce and distribute copies of the
+      Work or Derivative Works thereof in any medium, with or without
+      modifications, and in Source or Object form, provided that You
+      meet the following conditions:
+
+      (a) You must give any other recipients of the Work or
+          Derivative Works a copy of this License; and
+
+      (b) You must cause any modified files to carry prominent notices
+          stating that You changed the files; and
+
+      (c) You must retain, in the Source form of any Derivative Works
+          that You distribute, all copyright, patent, trademark, and
+          attribution notices from the Source form of the Work,
+          excluding those notices that do not pertain to any part of
+          the Derivative Works; and
+
+      (d) If the Work includes a "NOTICE" text file as part of its
+          distribution, then any Derivative Works that You distribute must
+          include a readable copy of the attribution notices contained
+          within such NOTICE file, excluding those notices that do not
+          pertain to any part of the Derivative Works, in at least one
+          of the following places: within a NOTICE text file distributed
+          as part of the Derivative Works; within the Source form or
+          documentation, if provided along with the Derivative Works; or,
+          within a display generated by the Derivative Works, if and
+          wherever such third-party notices normally appear. The contents
+          of the NOTICE file are for informational purposes only and
+          do not modify the License. You may add Your own attribution
+          notices within Derivative Works that You distribute, alongside
+          or as an addendum to the NOTICE text from the Work, provided
+          that such additional attribution notices cannot be construed
+          as modifying the License.
+
+      You may add Your own copyright statement to Your modifications and
+      may provide additional or different license terms and conditions
+      for use, reproduction, or distribution of Your modifications, or
+      for any such Derivative Works as a whole, provided Your use,
+      reproduction, and distribution of the Work otherwise complies with
+      the conditions stated in this License.
+
+   5. Submission of Contributions. Unless You explicitly state otherwise,
+      any Contribution intentionally submitted for inclusion in the Work
+      by You to the Licensor shall be under the terms and conditions of
+      this License, without any additional terms or conditions.
+      Notwithstanding the above, nothing herein shall supersede or modify
+      the terms of any separate license agreement you may have executed
+      with Licensor regarding such Contributions.
+
+   6. Trademarks. This License does not grant permission to use the trade
+      names, trademarks, service marks, or product names of the Licensor,
+      except as required for reasonable and customary use in describing the
+      origin of the Work and reproducing the content of the NOTICE file.
+
+   7. Disclaimer of Warranty. Unless required by applicable law or
+      agreed to in writing, Licensor provides the Work (and each
+      Contributor provides its Contributions) on an "AS IS" BASIS,
+      WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
+      implied, including, without limitation, any warranties or conditions
+      of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A
+      PARTICULAR PURPOSE. You are solely responsible for determining the
+      appropriateness of using or redistributing the Work and assume any
+      risks associated with Your exercise of permissions under this License.
+
+   8. Limitation of Liability. In no event and under no legal theory,
+      whether in tort (including negligence), contract, or otherwise,
+      unless required by applicable law (such as deliberate and grossly
+      negligent acts) or agreed to in writing, shall any Contributor be
+      liable to You for damages, including any direct, indirect, special,
+      incidental, or consequential damages of any character arising as a
+      result of this License or out of the use or inability to use the
+      Work (including but not limited to damages for loss of goodwill,
+      work stoppage, computer failure or malfunction, or any and all
+      other commercial damages or losses), even if such Contributor
+      has been advised of the possibility of such damages.
+
+   9. Accepting Warranty or Additional Liability. While redistributing
+      the Work or Derivative Works thereof, You may choose to offer,
+      and charge a fee for, acceptance of support, warranty, indemnity,
+      or other liability obligations and/or rights consistent with this
+      License. However, in accepting such obligations, You may act only
+      on Your own behalf and on Your sole responsibility, not on behalf
+      of any other Contributor, and only if You agree to indemnify,
+      defend, and hold each Contributor harmless for any liability
+      incurred by, or claims asserted against, such Contributor by reason
+      of your accepting any such warranty or additional liability.
+
+   END OF TERMS AND CONDITIONS
+
+   APPENDIX: How to apply the Apache License to your work.
+
+      To apply the Apache License to your work, attach the following
+      boilerplate notice, with the fields enclosed by brackets "[]"
+      replaced with your own identifying information. (Don't include
+      the brackets!)  The text should be enclosed in the appropriate
+      comment syntax for the file format. We also recommend that a
+      file or class name and description of purpose be included on the
+      same "printed page" as the copyright notice for easier
+      identification within third-party archives.
+
+   Copyright [yyyy] [name of copyright owner]
+
+   Licensed under the Apache License, Version 2.0 (the "License");
+   you may not use this file except in compliance with the License.
+   You may obtain a copy of the License at
+
+       http://www.apache.org/licenses/LICENSE-2.0
+
+   Unless required by applicable law or agreed to in writing, software
+   distributed under the License is distributed on an "AS IS" BASIS,
+   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+   See the License for the specific language governing permissions and
+   limitations under the License.

README.md

@@ -1,51 +1,51 @@
 
 <p align="center">
 <a href="https://langbot.app">
-<img src="https://docs.langbot.app/social.png" alt="LangBot"/>
+<img src="https://docs.langbot.app/social_zh.png" alt="LangBot"/>
 </a>
 
 <div align="center">
 
-<a href="https://trendshift.io/repositories/12901" target="_blank"><img src="https://trendshift.io/api/badge/repositories/12901" alt="RockChinQ%2FLangBot | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
+<a href="https://hellogithub.com/repository/langbot-app/LangBot" target="_blank"><img src="https://abroad.hellogithub.com/v1/widgets/recommend.svg?rid=5ce8ae2aa4f74316bf393b57b952433c&claim_uid=gtmc6YWjMZkT21R" alt="Featured｜HelloGitHub" style="width: 250px; height: 54px;" width="250" height="54" /></a>
+
+[English](README_EN.md) / 简体中文 / [繁體中文](README_TW.md) / [日本語](README_JP.md) / (PR for your language)
+
+[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
+[![QQ Group](https://img.shields.io/badge/%E7%A4%BE%E5%8C%BAQQ%E7%BE%A4-966235608-blue)](https://qm.qq.com/q/JLi38whHum)
+[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/langbot-app/LangBot)
+[![GitHub release (latest by date)](https://img.shields.io/github/v/release/langbot-app/LangBot)](https://github.com/langbot-app/LangBot/releases/latest)
+<img src="https://img.shields.io/badge/python-3.10 ~ 3.13 -blue.svg" alt="python">
+[![star](https://gitcode.com/RockChinQ/LangBot/star/badge.svg)](https://gitcode.com/RockChinQ/LangBot)
 
 <a href="https://langbot.app">项目主页</a> ｜
 <a href="https://docs.langbot.app/zh/insight/guide.html">部署文档</a> ｜
 <a href="https://docs.langbot.app/zh/plugin/plugin-intro.html">插件介绍</a> ｜
-<a href="https://github.com/RockChinQ/LangBot/issues/new?assignees=&labels=%E7%8B%AC%E7%AB%8B%E6%8F%92%E4%BB%B6&projects=&template=submit-plugin.yml&title=%5BPlugin%5D%3A+%E8%AF%B7%E6%B1%82%E7%99%BB%E8%AE%B0%E6%96%B0%E6%8F%92%E4%BB%B6">提交插件</a>
+<a href="https://github.com/langbot-app/LangBot/issues/new?assignees=&labels=%E7%8B%AC%E7%AB%8B%E6%8F%92%E4%BB%B6&projects=&template=submit-plugin.yml&title=%5BPlugin%5D%3A+%E8%AF%B7%E6%B1%82%E7%99%BB%E8%AE%B0%E6%96%B0%E6%8F%92%E4%BB%B6">提交插件</a>
 
-<div align="center">
-😎高稳定、🧩支持扩展、🦄多模态 - 大模型原生即时通信机器人平台🤖  
-</div>
-
-<br/>
-
-[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
-[![QQ Group](https://img.shields.io/badge/%E7%A4%BE%E5%8C%BAQQ%E7%BE%A4-966235608-blue)](https://qm.qq.com/q/JLi38whHum)
-[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/RockChinQ/LangBot)
-[![GitHub release (latest by date)](https://img.shields.io/github/v/release/RockChinQ/LangBot)](https://github.com/RockChinQ/LangBot/releases/latest)
-<img src="https://img.shields.io/badge/python-3.10 ~ 3.13 -blue.svg" alt="python">
-[![star](https://gitcode.com/RockChinQ/LangBot/star/badge.svg)](https://gitcode.com/RockChinQ/LangBot)
-
-简体中文 / [English](README_EN.md) / [日本語](README_JP.md) / (PR for your language)
 
 </div>
 
 </p>
 
-## ✨ 特性
-
-- 💬 大模型对话、Agent：支持多种大模型，适配群聊和私聊；具有多轮对话、工具调用、多模态能力，并深度适配 [Dify](https://dify.ai)。目前支持 QQ、QQ频道、企业微信、个人微信、飞书、Discord、Telegram 等平台。
-- 🛠️ 高稳定性、功能完备：原生支持访问控制、限速、敏感词过滤等机制；配置简单，支持多种部署方式。支持多流水线配置，不同机器人用于不同应用场景。
-- 🧩 插件扩展、活跃社区：支持事件驱动、组件扩展等插件机制；适配 Anthropic [MCP 协议](https://modelcontextprotocol.io/)；目前已有数百个插件。
-- 😻 Web 管理面板：支持通过浏览器管理 LangBot 实例，不再需要手动编写配置文件。
+LangBot 是一个开源的大语言模型原生即时通信机器人开发平台，旨在提供开箱即用的 IM 机器人开发体验，具有 Agent、RAG、MCP 等多种 LLM 应用功能，适配全球主流即时通信平台，并提供丰富的 API 接口，支持自定义开发。
 
 ## 📦 开始使用
 
+#### 快速部署
+
+使用 `uvx` 一键启动（需要先安装 [uv](https://docs.astral.sh/uv/getting-started/installation/)）：
+
+```bash
+uvx langbot
+```
+
+访问 http://localhost:5300 即可开始使用。
+
 #### Docker Compose 部署
 
 ```bash
-git clone https://github.com/RockChinQ/LangBot
-cd LangBot
+git clone https://github.com/langbot-app/LangBot
+cd LangBot/docker
 docker compose up -d
 ```
 
@@ -71,23 +71,29 @@ docker compose up -d
 
 直接使用发行版运行，查看文档[手动部署](https://docs.langbot.app/zh/deploy/langbot/manual.html)。
 
-## 📸 效果展示
+#### Kubernetes 部署
 
-<img alt="bots" src="https://docs.langbot.app/webui/bot-page.png" width="450px"/>
+参考 [Kubernetes 部署](./docker/README_K8S.md) 文档。
 
-<img alt="bots" src="https://docs.langbot.app/webui/create-model.png" width="450px"/>
+## 😎 保持更新
 
-<img alt="bots" src="https://docs.langbot.app/webui/edit-pipeline.png" width="450px"/>
+点击仓库右上角 Star 和 Watch 按钮，获取最新动态。
 
-<img alt="bots" src="https://docs.langbot.app/webui/plugin-market.png" width="450px"/>
+![star gif](https://docs.langbot.app/star.gif)
 
-<img alt="回复效果（带有联网插件）" src="https://docs.langbot.app/QChatGPT-0516.png" width="500px"/>
+## ✨ 特性
 
-- WebUI Demo: https://demo.langbot.dev/
-    - 登录信息：邮箱：`demo@langbot.app` 密码：`langbot123456`
-    - 注意：仅展示webui效果，公开环境，请不要在其中填入您的任何敏感信息。
+- 💬 大模型对话、Agent：支持多种大模型，适配群聊和私聊；具有多轮对话、工具调用、多模态、流式输出能力，自带 RAG（知识库）实现，并深度适配 [Dify](https://dify.ai)。
+- 🤖 多平台支持：目前支持 QQ、QQ频道、企业微信、个人微信、飞书、Discord、Telegram 等平台。
+- 🛠️ 高稳定性、功能完备：原生支持访问控制、限速、敏感词过滤等机制；配置简单，支持多种部署方式。支持多流水线配置，不同机器人用于不同应用场景。
+- 🧩 插件扩展、活跃社区：支持事件驱动、组件扩展等插件机制；适配 Anthropic [MCP 协议](https://modelcontextprotocol.io/)；目前已有数百个插件。
+- 😻 Web 管理面板：支持通过浏览器管理 LangBot 实例，不再需要手动编写配置文件。
 
-## 🔌 组件兼容性
+详细规格特性请访问[文档](https://docs.langbot.app/zh/insight/features.html)。
+
+或访问 demo 环境：https://demo.langbot.dev/  
+  - 登录信息：邮箱：`demo@langbot.app` 密码：`langbot123456`
+  - 注意：仅展示 WebUI 效果，公开环境，请不要在其中填入您的任何敏感信息。
 
 ### 消息平台
 
@@ -97,6 +103,7 @@ docker compose up -d
 | QQ 官方机器人 | ✅ | QQ 官方机器人，支持频道、私聊、群聊 |
 | 企业微信 | ✅ |  |
 | 企微对外客服 | ✅ |  |
+| 企微智能机器人 | ✅ |  |
 | 个人微信 | ✅ |  |
 | 微信公众号 | ✅ |  |
 | 飞书 | ✅ |  |
@@ -104,10 +111,7 @@ docker compose up -d
 | Discord | ✅ |  |
 | Telegram | ✅ |  |
 | Slack | ✅ |  |
-| LINE | 🚧 |  |
-| WhatsApp | 🚧 |  |
-
-🚧: 正在开发中
+| LINE | ✅ |  |
 
 ### 大模型能力
 
@@ -119,18 +123,23 @@ docker compose up -d
 | [Anthropic](https://www.anthropic.com/) | ✅ |  |
 | [xAI](https://x.ai/) | ✅ |  |
 | [智谱AI](https://open.bigmodel.cn/) | ✅ |  |
+| [胜算云](https://www.shengsuanyun.com/?from=CH_KYIPP758) | ✅ | 全球大模型都可调用（友情推荐） |
+| [优云智算](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | ✅ | 大模型和 GPU 资源平台 |
 | [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | ✅ | 大模型和 GPU 资源平台 |
-| [302 AI](https://share.302.ai/SuTG99) | ✅ | 大模型聚合平台 |
+| [接口 AI](https://jiekou.ai/) | ✅ | 大模型聚合平台，专注全球大模型接入 |
+| [302.AI](https://share.302.ai/SuTG99) | ✅ | 大模型聚合平台 |
 | [Google Gemini](https://aistudio.google.com/prompts/new_chat) | ✅ | |
 | [Dify](https://dify.ai) | ✅ | LLMOps 平台 |
 | [Ollama](https://ollama.com/) | ✅ | 本地大模型运行平台 |
 | [LMStudio](https://lmstudio.ai/) | ✅ | 本地大模型运行平台 |
 | [GiteeAI](https://ai.gitee.com/) | ✅ | 大模型接口聚合平台 |
 | [SiliconFlow](https://siliconflow.cn/) | ✅ | 大模型聚合平台 |
+| [小马算力](https://www.tokenpony.cn/453z1) | ✅ | 大模型聚合平台 |
 | [阿里云百炼](https://bailian.console.aliyun.com/) | ✅ | 大模型聚合平台, LLMOps 平台 |
 | [火山方舟](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | ✅ | 大模型聚合平台, LLMOps 平台 |
 | [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | ✅ | 大模型聚合平台 |
 | [MCP](https://modelcontextprotocol.io/) | ✅ | 支持通过 MCP 协议获取工具 |
+| [百宝箱Tbox](https://www.tbox.cn/open) | ✅ | 蚂蚁百宝箱智能体平台，每月免费10亿大模型Token |
 
 ### TTS
 
@@ -148,14 +157,14 @@ docker compose up -d
 
 ## 😘 社区贡献
 
-感谢以下[代码贡献者](https://github.com/RockChinQ/LangBot/graphs/contributors)和社区里其他成员对 LangBot 的贡献：
+感谢以下[代码贡献者](https://github.com/langbot-app/LangBot/graphs/contributors)和社区里其他成员对 LangBot 的贡献：
 
-<a href="https://github.com/RockChinQ/LangBot/graphs/contributors">
-  <img src="https://contrib.rocks/image?repo=RockChinQ/LangBot" />
+<a href="https://github.com/langbot-app/LangBot/graphs/contributors">
+  <img src="https://contrib.rocks/image?repo=langbot-app/LangBot" />
 </a>
 
-## 😎 保持更新
+<!--
+## For Code Agents
 
-点击仓库右上角 Star 和 Watch 按钮，获取最新动态。
-
-![star gif](https://docs.langbot.app/star.gif)
+If you're a code agent based on LLM, you should read [AGENTS.md](AGENTS.md) to understand the project structure and development process before you start any development.
+-->

README_EN.md

@@ -1,49 +1,45 @@
 <p align="center">
 <a href="https://langbot.app">
-<img src="https://docs.langbot.app/social.png" alt="LangBot"/>
+<img src="https://docs.langbot.app/social_en.png" alt="LangBot"/>
 </a>
 
 <div align="center">
 
-<a href="https://trendshift.io/repositories/12901" target="_blank"><img src="https://trendshift.io/api/badge/repositories/12901" alt="RockChinQ%2FLangBot | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
+English / [简体中文](README.md) / [繁體中文](README_TW.md) / [日本語](README_JP.md) / (PR for your language)
+
+[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
+[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/langbot-app/LangBot)
+[![GitHub release (latest by date)](https://img.shields.io/github/v/release/langbot-app/LangBot)](https://github.com/langbot-app/LangBot/releases/latest)
+<img src="https://img.shields.io/badge/python-3.10 ~ 3.13 -blue.svg" alt="python">
 
 <a href="https://langbot.app">Home</a> ｜
 <a href="https://docs.langbot.app/en/insight/guide.html">Deployment</a> ｜
 <a href="https://docs.langbot.app/en/plugin/plugin-intro.html">Plugin</a> ｜
-<a href="https://github.com/RockChinQ/LangBot/issues/new?assignees=&labels=%E7%8B%AC%E7%AB%8B%E6%8F%92%E4%BB%B6&projects=&template=submit-plugin.yml&title=%5BPlugin%5D%3A+%E8%AF%B7%E6%B1%82%E7%99%BB%E8%AE%B0%E6%96%B0%E6%8F%92%E4%BB%B6">Submit Plugin</a>
-
-<div align="center">
-😎High Stability, 🧩Extension Supported, 🦄Multi-modal - LLM Native Instant Messaging Bot Platform🤖  
-</div>
-
-<br/>
-
-
-[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
-[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/RockChinQ/LangBot)
-[![GitHub release (latest by date)](https://img.shields.io/github/v/release/RockChinQ/LangBot)](https://github.com/RockChinQ/LangBot/releases/latest)
-<img src="https://img.shields.io/badge/python-3.10 ~ 3.13 -blue.svg" alt="python">
-
-[简体中文](README.md) / English / [日本語](README_JP.md) / (PR for your language)
+<a href="https://github.com/langbot-app/LangBot/issues/new?assignees=&labels=%E7%8B%AC%E7%AB%8B%E6%8F%92%E4%BB%B6&projects=&template=submit-plugin.yml&title=%5BPlugin%5D%3A+%E8%AF%B7%E6%B1%82%E7%99%BB%E8%AE%B0%E6%96%B0%E6%8F%92%E4%BB%B6">Submit Plugin</a>
 
 </div>
 
 </p>
 
-## ✨ Features
-
-- 💬 Chat with LLM / Agent: Supports multiple LLMs, adapt to group chats and private chats; Supports multi-round conversations, tool calls, and multi-modal capabilities. Deeply integrates with [Dify](https://dify.ai). Currently supports QQ, QQ Channel, WeCom, personal WeChat, Lark, DingTalk, Discord, Telegram, etc.
-- 🛠️ High Stability, Feature-rich: Native access control, rate limiting, sensitive word filtering, etc. mechanisms; Easy to use, supports multiple deployment methods. Supports multiple pipeline configurations, different bots can be used for different scenarios.
-- 🧩 Plugin Extension, Active Community: Support event-driven, component extension, etc. plugin mechanisms; Integrate Anthropic [MCP protocol](https://modelcontextprotocol.io/); Currently has hundreds of plugins.
-- 😻 [New] Web UI: Support management LangBot instance through the browser. No need to manually write configuration files.
+LangBot is an open-source LLM native instant messaging robot development platform, aiming to provide out-of-the-box IM robot development experience, with Agent, RAG, MCP and other LLM application functions, adapting to global instant messaging platforms, and providing rich API interfaces, supporting custom development.
 
 ## 📦 Getting Started
 
+#### Quick Start
+
+Use `uvx` to start with one command (need to install [uv](https://docs.astral.sh/uv/getting-started/installation/)):
+
+```bash
+uvx langbot
+```
+
+Visit http://localhost:5300 to start using it.
+
 #### Docker Compose Deployment
 
 ```bash
-git clone https://github.com/RockChinQ/LangBot
-cd LangBot
+git clone https://github.com/langbot-app/LangBot
+cd LangBot/docker
 docker compose up -d
 ```
 
@@ -69,42 +65,46 @@ Community contributed Zeabur template.
 
 Directly use the released version to run, see the [Manual Deployment](https://docs.langbot.app/en/deploy/langbot/manual.html) documentation.
 
-## 📸 Demo
+#### Kubernetes Deployment
 
-<img alt="bots" src="https://docs.langbot.app/webui/bot-page.png" width="400px"/>
+Refer to the [Kubernetes Deployment](./docker/README_K8S.md) documentation.
 
-<img alt="bots" src="https://docs.langbot.app/webui/create-model.png" width="400px"/>
+## 😎 Stay Ahead
 
-<img alt="bots" src="https://docs.langbot.app/webui/edit-pipeline.png" width="400px"/>
+Click the Star and Watch button in the upper right corner of the repository to get the latest updates.
 
-<img alt="bots" src="https://docs.langbot.app/webui/plugin-market.png" width="400px"/>
+![star gif](https://docs.langbot.app/star.gif)
 
-<img alt="Reply Effect (with Internet Plugin)" src="https://docs.langbot.app/QChatGPT-0516.png" width="500px"/>
+## ✨ Features
 
-- WebUI Demo: https://demo.langbot.dev/
-    - Login information: Email: `demo@langbot.app` Password: `langbot123456`
-    - Note: Only the WebUI effect is shown, please do not fill in any sensitive information in the public environment.
+- 💬 Chat with LLM / Agent: Supports multiple LLMs, adapt to group chats and private chats; Supports multi-round conversations, tool calls, multi-modal, and streaming output capabilities. Built-in RAG (knowledge base) implementation, and deeply integrates with [Dify](https://dify.ai).
+- 🤖 Multi-platform Support: Currently supports QQ, QQ Channel, WeCom, personal WeChat, Lark, DingTalk, Discord, Telegram, etc.
+- 🛠️ High Stability, Feature-rich: Native access control, rate limiting, sensitive word filtering, etc. mechanisms; Easy to use, supports multiple deployment methods. Supports multiple pipeline configurations, different bots can be used for different scenarios.
+- 🧩 Plugin Extension, Active Community: Support event-driven, component extension, etc. plugin mechanisms; Integrate Anthropic [MCP protocol](https://modelcontextprotocol.io/); Currently has hundreds of plugins.
+- 😻 Web UI: Support management LangBot instance through the browser. No need to manually write configuration files.
 
-## 🔌 Component Compatibility
+For more detailed specifications, please refer to the [documentation](https://docs.langbot.app/en/insight/features.html).
+
+Or visit the demo environment: https://demo.langbot.dev/
+  - Login information: Email: `demo@langbot.app` Password: `langbot123456`
+  - Note: For WebUI demo only, please do not fill in any sensitive information in the public environment.
 
 ### Message Platform
 
 | Platform | Status | Remarks |
 | --- | --- | --- |
+| Discord | ✅ |  |
+| Telegram | ✅ |  |
+| Slack | ✅ |  |
+| LINE | ✅ |  |
 | Personal QQ | ✅ |  |
 | QQ Official API | ✅ |  |
 | WeCom | ✅ |  |
 | WeComCS | ✅ |  |
+| WeCom AI Bot | ✅ |  |
 | Personal WeChat | ✅ |  |
 | Lark | ✅ |  |
 | DingTalk | ✅ |  |
-| Discord | ✅ |  |
-| Telegram | ✅ |  |
-| Slack | ✅ |  |
-| LINE | 🚧 |  |
-| WhatsApp | 🚧 |  |
-
-🚧: In development
 
 ### LLMs
 
@@ -116,9 +116,12 @@ Directly use the released version to run, see the [Manual Deployment](https://do
 | [Anthropic](https://www.anthropic.com/) | ✅ |  |
 | [xAI](https://x.ai/) | ✅ |  |
 | [Zhipu AI](https://open.bigmodel.cn/) | ✅ |  |
+| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | ✅ | LLM and GPU resource platform |
 | [Dify](https://dify.ai) | ✅ | LLMOps platform |
 | [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | ✅ | LLM and GPU resource platform |
-| [302 AI](https://share.302.ai/SuTG99) | ✅ | LLM gateway(MaaS) |
+| [接口 AI](https://jiekou.ai/) | ✅ | LLM aggregation platform, dedicated to global LLMs |
+| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | ✅ | LLM and GPU resource platform |
+| [302.AI](https://share.302.ai/SuTG99) | ✅ | LLM gateway(MaaS) |
 | [Google Gemini](https://aistudio.google.com/prompts/new_chat) | ✅ | |
 | [Ollama](https://ollama.com/) | ✅ | Local LLM running platform |
 | [LMStudio](https://lmstudio.ai/) | ✅ | Local LLM running platform |
@@ -131,14 +134,8 @@ Directly use the released version to run, see the [Manual Deployment](https://do
 
 ## 🤝 Community Contribution
 
-Thank you for the following [code contributors](https://github.com/RockChinQ/LangBot/graphs/contributors) and other members in the community for their contributions to LangBot:
+Thank you for the following [code contributors](https://github.com/langbot-app/LangBot/graphs/contributors) and other members in the community for their contributions to LangBot:
 
-<a href="https://github.com/RockChinQ/LangBot/graphs/contributors">
-  <img src="https://contrib.rocks/image?repo=RockChinQ/LangBot" />
+<a href="https://github.com/langbot-app/LangBot/graphs/contributors">
+  <img src="https://contrib.rocks/image?repo=langbot-app/LangBot" />
 </a>
-
-## 😎 Stay Ahead
-
-Click the Star and Watch button in the upper right corner of the repository to get the latest updates.
-
-![star gif](https://docs.langbot.app/star.gif)

README_JP.md

@@ -1,48 +1,45 @@
 <p align="center">
 <a href="https://langbot.app">
-<img src="https://docs.langbot.app/social.png" alt="LangBot"/>
+<img src="https://docs.langbot.app/social_en.png" alt="LangBot"/>
 </a>
 
 <div align="center">
 
-<a href="https://trendshift.io/repositories/12901" target="_blank"><img src="https://trendshift.io/api/badge/repositories/12901" alt="RockChinQ%2FLangBot | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
+[English](README_EN.md) / [简体中文](README.md) / [繁體中文](README_TW.md) / 日本語 / (PR for your language)
+
+[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
+[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/langbot-app/LangBot)
+[![GitHub release (latest by date)](https://img.shields.io/github/v/release/langbot-app/LangBot)](https://github.com/langbot-app/LangBot/releases/latest)
+<img src="https://img.shields.io/badge/python-3.10 ~ 3.13 -blue.svg" alt="python">
 
 <a href="https://langbot.app">ホーム</a> ｜
 <a href="https://docs.langbot.app/en/insight/guide.html">デプロイ</a> ｜
 <a href="https://docs.langbot.app/en/plugin/plugin-intro.html">プラグイン</a> ｜
-<a href="https://github.com/RockChinQ/LangBot/issues/new?assignees=&labels=%E7%8B%AC%E7%AB%8B%E6%8F%92%E4%BB%B6&projects=&template=submit-plugin.yml&title=%5BPlugin%5D%3A+%E8%AF%B7%E6%B1%82%E7%99%BB%E8%AE%B0%E6%96%B0%E6%8F%92%E4%BB%B6">プラグインの提出</a>
-
-<div align="center">
-😎高い安定性、🧩拡張サポート、🦄マルチモーダル - LLMネイティブインスタントメッセージングボットプラットフォーム🤖  
-</div>
-
-<br/>
-
-[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
-[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/RockChinQ/LangBot)
-[![GitHub release (latest by date)](https://img.shields.io/github/v/release/RockChinQ/LangBot)](https://github.com/RockChinQ/LangBot/releases/latest)
-<img src="https://img.shields.io/badge/python-3.10 ~ 3.13 -blue.svg" alt="python">
-
-[简体中文](README_CN.md) / [English](README.md) / [日本語](README_JP.md) / (PR for your language)
+<a href="https://github.com/langbot-app/LangBot/issues/new?assignees=&labels=%E7%8B%AC%E7%AB%8B%E6%8F%92%E4%BB%B6&projects=&template=submit-plugin.yml&title=%5BPlugin%5D%3A+%E8%AF%B7%E6%B1%82%E7%99%BB%E8%AE%B0%E6%96%B0%E6%8F%92%E4%BB%B6">プラグインの提出</a>
 
 </div>
 
 </p>
 
-## ✨ 機能
-
-- 💬 LLM / エージェントとのチャット: 複数のLLMをサポートし、グループチャットとプライベートチャットに対応。マルチラウンドの会話、ツールの呼び出し、マルチモーダル機能をサポート。 [Dify](https://dify.ai) と深く統合。現在、QQ、QQ チャンネル、WeChat、個人 WeChat、Lark、DingTalk、Discord、Telegram など、複数のプラットフォームをサポートしています。
-- 🛠️ 高い安定性、豊富な機能: ネイティブのアクセス制御、レート制限、敏感な単語のフィルタリングなどのメカニズムをサポート。使いやすく、複数のデプロイ方法をサポート。複数のパイプライン設定をサポートし、異なるボットを異なる用途に使用できます。
-- 🧩 プラグイン拡張、活発なコミュニティ: イベント駆動、コンポーネント拡張などのプラグインメカニズムをサポート。適配 Anthropic [MCP プロトコル](https://modelcontextprotocol.io/)；豊富なエコシステム、現在数百のプラグインが存在。
-- 😻 Web UI: ブラウザを通じてLangBotインスタンスを管理することをサポート。
+LangBot は、エージェント、RAG、MCP などの LLM アプリケーション機能を備えた、オープンソースの LLM ネイティブのインスタントメッセージングロボット開発プラットフォームです。世界中のインスタントメッセージングプラットフォームに適応し、豊富な API インターフェースを提供し、カスタム開発をサポートします。
 
 ## 📦 始め方
 
+#### クイックスタート
+
+`uvx` を使用した迅速なデプロイ（[uv](https://docs.astral.sh/uv/getting-started/installation/) が必要です）：
+
+```bash
+uvx langbot
+```
+
+http://localhost:5300 にアクセスして使用を開始します。
+
 #### Docker Compose デプロイ
 
 ```bash
-git clone https://github.com/RockChinQ/LangBot
-cd LangBot
+git clone https://github.com/langbot-app/LangBot
+cd LangBot/docker
 docker compose up -d
 ```
 
@@ -50,7 +47,7 @@ http://localhost:5300 にアクセスして使用を開始します。
 
 詳細なドキュメントは[Dockerデプロイ](https://docs.langbot.app/en/deploy/langbot/docker.html)を参照してください。
 
-#### BTPanelでのワンクリックデプロイ
+#### Panelでのワンクリックデプロイ
 
 LangBotはBTPanelにリストされています。BTPanelをインストールしている場合は、[ドキュメント](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html)を使用して使用できます。
 
@@ -68,42 +65,46 @@ LangBotはBTPanelにリストされています。BTPanelをインストール
 
 リリースバージョンを直接使用して実行します。[手動デプロイ](https://docs.langbot.app/en/deploy/langbot/manual.html)のドキュメントを参照してください。
 
-## 📸 デモ
+#### Kubernetes デプロイ
 
-<img alt="bots" src="https://docs.langbot.app/webui/bot-page.png" width="400px"/>
+[Kubernetes デプロイ](./docker/README_K8S.md) ドキュメントを参照してください。
 
-<img alt="bots" src="https://docs.langbot.app/webui/create-model.png" width="400px"/>
+## 😎 最新情報を入手
 
-<img alt="bots" src="https://docs.langbot.app/webui/edit-pipeline.png" width="400px"/>
+リポジトリの右上にある Star と Watch ボタンをクリックして、最新の更新を取得してください。
 
-<img alt="bots" src="https://docs.langbot.app/webui/plugin-market.png" width="400px"/>
+![star gif](https://docs.langbot.app/star.gif)
 
-<img alt="返信効果（インターネットプラグイン付き）" src="https://docs.langbot.app/QChatGPT-0516.png" width="500px"/>
+## ✨ 機能
 
-- WebUIデモ: https://demo.langbot.dev/
-    - ログイン情報: メール: `demo@langbot.app` パスワード: `langbot123456`
-    - 注意: WebUIの効果のみを示しています。公開環境では、機密情報を入力しないでください。
+- 💬 LLM / エージェントとのチャット: 複数のLLMをサポートし、グループチャットとプライベートチャットに対応。マルチラウンドの会話、ツールの呼び出し、マルチモーダル、ストリーミング出力機能をサポート、RAG（知識ベース）を組み込み、[Dify](https://dify.ai) と深く統合。
+- 🤖 多プラットフォーム対応: 現在、QQ、QQ チャンネル、WeChat、個人 WeChat、Lark、DingTalk、Discord、Telegram など、複数のプラットフォームをサポートしています。
+- 🛠️ 高い安定性、豊富な機能: ネイティブのアクセス制御、レート制限、敏感な単語のフィルタリングなどのメカニズムをサポート。使いやすく、複数のデプロイ方法をサポート。複数のパイプライン設定をサポートし、異なるボットを異なる用途に使用できます。
+- 🧩 プラグイン拡張、活発なコミュニティ: イベント駆動、コンポーネント拡張などのプラグインメカニズムをサポート。適配 Anthropic [MCP プロトコル](https://modelcontextprotocol.io/)；豊富なエコシステム、現在数百のプラグインが存在。
+- 😻 Web UI: ブラウザを通じてLangBotインスタンスを管理することをサポート。
 
-## 🔌 コンポーネントの互換性
+詳細な仕様については、[ドキュメント](https://docs.langbot.app/en/insight/features.html)を参照してください。
+
+または、デモ環境にアクセスしてください: https://demo.langbot.dev/
+  - ログイン情報: メール: `demo@langbot.app` パスワード: `langbot123456`
+  - 注意: WebUI のデモンストレーションのみの場合、公開環境では機密情報を入力しないでください。
 
 ### メッセージプラットフォーム
 
 | プラットフォーム | ステータス | 備考 |
 | --- | --- | --- |
+| Discord | ✅ |  |
+| Telegram | ✅ |  |
+| Slack | ✅ |  |
+| LINE | ✅ |  |
 | 個人QQ | ✅ |  |
 | QQ公式API | ✅ |  |
 | WeCom | ✅ |  |
 | WeComCS | ✅ |  |
+| WeCom AI Bot | ✅ |  |
 | 個人WeChat | ✅ | |
 | Lark | ✅ |  |
 | DingTalk | ✅ |  |
-| Discord | ✅ |  |
-| Telegram | ✅ |  |
-| Slack | ✅ |  |
-| LINE | 🚧 |  |
-| WhatsApp | 🚧 |  |
-
-🚧: 開発中
 
 ### LLMs
 
@@ -115,8 +116,11 @@ LangBotはBTPanelにリストされています。BTPanelをインストール
 | [Anthropic](https://www.anthropic.com/) | ✅ |  |
 | [xAI](https://x.ai/) | ✅ |  |
 | [Zhipu AI](https://open.bigmodel.cn/) | ✅ |  |
+| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | ✅ | 大模型とGPUリソースプラットフォーム |
 | [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | ✅ | 大模型とGPUリソースプラットフォーム |
-| [302 AI](https://share.302.ai/SuTG99) | ✅ | LLMゲートウェイ(MaaS) |
+| [接口 AI](https://jiekou.ai/) | ✅ | LLMゲートウェイ(MaaS) |
+| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | ✅ | LLMとGPUリソースプラットフォーム |
+| [302.AI](https://share.302.ai/SuTG99) | ✅ | LLMゲートウェイ(MaaS) |
 | [Google Gemini](https://aistudio.google.com/prompts/new_chat) | ✅ | |
 | [Dify](https://dify.ai) | ✅ | LLMOpsプラットフォーム |
 | [Ollama](https://ollama.com/) | ✅ | ローカルLLM実行プラットフォーム |
@@ -130,14 +134,8 @@ LangBotはBTPanelにリストされています。BTPanelをインストール
 
 ## 🤝 コミュニティ貢献
 
-LangBot への貢献に対して、以下の [コード貢献者](https://github.com/RockChinQ/LangBot/graphs/contributors) とコミュニティの他のメンバーに感謝します。
+LangBot への貢献に対して、以下の [コード貢献者](https://github.com/langbot-app/LangBot/graphs/contributors) とコミュニティの他のメンバーに感謝します。
 
-<a href="https://github.com/RockChinQ/LangBot/graphs/contributors">
-  <img src="https://contrib.rocks/image?repo=RockChinQ/LangBot" />
+<a href="https://github.com/langbot-app/LangBot/graphs/contributors">
+  <img src="https://contrib.rocks/image?repo=langbot-app/LangBot" />
 </a>
-
-## 😎 最新情報を入手
-
-リポジトリの右上にある Star と Watch ボタンをクリックして、最新の更新を取得してください。
-
-![star gif](https://docs.langbot.app/star.gif)

README_TW.md

@@ -0,0 +1,157 @@
+<p align="center">
+<a href="https://langbot.app">
+<img src="https://docs.langbot.app/social_zh.png" alt="LangBot"/>
+</a>
+
+<div align="center"><a href="https://hellogithub.com/repository/langbot-app/LangBot" target="_blank"><img src="https://abroad.hellogithub.com/v1/widgets/recommend.svg?rid=5ce8ae2aa4f74316bf393b57b952433c&claim_uid=gtmc6YWjMZkT21R" alt="Featured｜HelloGitHub" style="width: 250px; height: 54px;" width="250" height="54" /></a>
+
+[English](README_EN.md) / [简体中文](README.md) / 繁體中文 / [日本語](README_JP.md) / (PR for your language)
+
+[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
+[![QQ Group](https://img.shields.io/badge/%E7%A4%BE%E5%8C%BAQQ%E7%BE%A4-966235608-blue)](https://qm.qq.com/q/JLi38whHum)
+[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/langbot-app/LangBot)
+[![GitHub release (latest by date)](https://img.shields.io/github/v/release/langbot-app/LangBot)](https://github.com/langbot-app/LangBot/releases/latest)
+<img src="https://img.shields.io/badge/python-3.10 ~ 3.13 -blue.svg" alt="python">
+[![star](https://gitcode.com/RockChinQ/LangBot/star/badge.svg)](https://gitcode.com/RockChinQ/LangBot)
+
+<a href="https://langbot.app">主頁</a> ｜
+<a href="https://docs.langbot.app/zh/insight/guide.html">部署文件</a> ｜
+<a href="https://docs.langbot.app/zh/plugin/plugin-intro.html">外掛介紹</a> ｜
+<a href="https://github.com/langbot-app/LangBot/issues/new?assignees=&labels=%E7%8B%AC%E7%AB%8B%E6%8F%92%E4%BB%B6&projects=&template=submit-plugin.yml&title=%5BPlugin%5D%3A+%E8%AF%B7%E6%B1%82%E7%99%BB%E8%AE%B0%E6%96%B0%E6%8F%92%E4%BB%B6">提交外掛</a>
+
+</div>
+
+</p>
+
+LangBot 是一個開源的大語言模型原生即時通訊機器人開發平台，旨在提供開箱即用的 IM 機器人開發體驗，具有 Agent、RAG、MCP 等多種 LLM 應用功能，適配全球主流即時通訊平台，並提供豐富的 API 介面，支援自定義開發。
+
+## 📦 開始使用
+
+#### 快速部署
+
+使用 `uvx` 一鍵啟動（需要先安裝 [uv](https://docs.astral.sh/uv/getting-started/installation/) ）：
+
+```bash
+uvx langbot
+```
+
+訪問 http://localhost:5300 即可開始使用。
+
+#### Docker Compose 部署
+
+```bash
+git clone https://github.com/langbot-app/LangBot
+cd LangBot/docker
+docker compose up -d
+```
+
+訪問 http://localhost:5300 即可開始使用。
+
+詳細文件[Docker 部署](https://docs.langbot.app/zh/deploy/langbot/docker.html)。
+
+#### 寶塔面板部署
+
+已上架寶塔面板，若您已安裝寶塔面板，可以根據[文件](https://docs.langbot.app/zh/deploy/langbot/one-click/bt.html)使用。
+
+#### Zeabur 雲端部署
+
+社群貢獻的 Zeabur 模板。
+
+[![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/zh-CN/templates/ZKTBDH)
+
+#### Railway 雲端部署
+
+[![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
+
+#### 手動部署
+
+直接使用發行版運行，查看文件[手動部署](https://docs.langbot.app/zh/deploy/langbot/manual.html)。
+
+#### Kubernetes 部署
+
+參考 [Kubernetes 部署](./docker/README_K8S.md) 文件。
+
+## 😎 保持更新
+
+點擊倉庫右上角 Star 和 Watch 按鈕，獲取最新動態。
+
+![star gif](https://docs.langbot.app/star.gif)
+
+## ✨ 特性
+
+- 💬 大模型對話、Agent：支援多種大模型，適配群聊和私聊；具有多輪對話、工具調用、多模態、流式輸出能力，自帶 RAG（知識庫）實現，並深度適配 [Dify](https://dify.ai)。
+- 🤖 多平台支援：目前支援 QQ、QQ頻道、企業微信、個人微信、飛書、Discord、Telegram 等平台。
+- 🛠️ 高穩定性、功能完備：原生支援訪問控制、限速、敏感詞過濾等機制；配置簡單，支援多種部署方式。支援多流水線配置，不同機器人用於不同應用場景。
+- 🧩 外掛擴展、活躍社群：支援事件驅動、組件擴展等外掛機制；適配 Anthropic [MCP 協議](https://modelcontextprotocol.io/)；目前已有數百個外掛。
+- 😻 Web 管理面板：支援通過瀏覽器管理 LangBot 實例，不再需要手動編寫配置文件。
+
+詳細規格特性請訪問[文件](https://docs.langbot.app/zh/insight/features.html)。
+
+或訪問 demo 環境：https://demo.langbot.dev/  
+  - 登入資訊：郵箱：`demo@langbot.app` 密碼：`langbot123456`
+  - 注意：僅展示 WebUI 效果，公開環境，請不要在其中填入您的任何敏感資訊。
+
+### 訊息平台
+
+| 平台 | 狀態 | 備註 |
+| --- | --- | --- |
+| Discord | ✅ |  |
+| Telegram | ✅ |  |
+| Slack | ✅ |  |
+| LINE | ✅ |  |
+| QQ 個人號 | ✅ | QQ 個人號私聊、群聊 |
+| QQ 官方機器人 | ✅ | QQ 官方機器人，支援頻道、私聊、群聊 |
+| 微信 | ✅ |  |
+| 企微對外客服 | ✅ |  |
+| 企微智能機器人 | ✅ |  |
+| 微信公眾號 | ✅ |  |
+| Lark | ✅ |  |
+| DingTalk | ✅ |  |
+
+### 大模型能力
+
+| 模型 | 狀態 | 備註 |
+| --- | --- | --- |
+| [OpenAI](https://platform.openai.com/) | ✅ | 可接入任何 OpenAI 介面格式模型 |
+| [DeepSeek](https://www.deepseek.com/) | ✅ |  |
+| [Moonshot](https://www.moonshot.cn/) | ✅ |  |
+| [Anthropic](https://www.anthropic.com/) | ✅ |  |
+| [xAI](https://x.ai/) | ✅ |  |
+| [智譜AI](https://open.bigmodel.cn/) | ✅ |  |
+| [勝算雲](https://www.shengsuanyun.com/?from=CH_KYIPP758) | ✅ | 大模型和 GPU 資源平台 |
+| [優雲智算](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | ✅ | 大模型和 GPU 資源平台 |
+| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | ✅ | 大模型和 GPU 資源平台 |
+| [接口 AI](https://jiekou.ai/) | ✅ | 大模型聚合平台，專注全球大模型接入 |
+| [302.AI](https://share.302.ai/SuTG99) | ✅ | 大模型聚合平台 |
+| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | ✅ | |
+| [Dify](https://dify.ai) | ✅ | LLMOps 平台 |
+| [Ollama](https://ollama.com/) | ✅ | 本地大模型運行平台 |
+| [LMStudio](https://lmstudio.ai/) | ✅ | 本地大模型運行平台 |
+| [GiteeAI](https://ai.gitee.com/) | ✅ | 大模型介面聚合平台 |
+| [SiliconFlow](https://siliconflow.cn/) | ✅ | 大模型聚合平台 |
+| [阿里雲百煉](https://bailian.console.aliyun.com/) | ✅ | 大模型聚合平台, LLMOps 平台 |
+| [火山方舟](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | ✅ | 大模型聚合平台, LLMOps 平台 |
+| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | ✅ | 大模型聚合平台 |
+| [MCP](https://modelcontextprotocol.io/) | ✅ | 支援通過 MCP 協議獲取工具 |
+
+### TTS
+
+| 平台/模型 | 備註 |
+| --- | --- |
+| [FishAudio](https://fish.audio/zh-CN/discovery/) | [外掛](https://github.com/the-lazy-me/NewChatVoice) |
+| [海豚 AI](https://www.ttson.cn/?source=thelazy) | [外掛](https://github.com/the-lazy-me/NewChatVoice) |
+| [AzureTTS](https://portal.azure.com/) | [外掛](https://github.com/Ingnaryk/LangBot_AzureTTS) |
+
+### 文生圖
+
+| 平台/模型 | 備註 |
+| --- | --- |
+| 阿里雲百煉 | [外掛](https://github.com/Thetail001/LangBot_BailianTextToImagePlugin)
+
+## 😘 社群貢獻
+
+感謝以下[程式碼貢獻者](https://github.com/langbot-app/LangBot/graphs/contributors)和社群裡其他成員對 LangBot 的貢獻：
+
+<a href="https://github.com/langbot-app/LangBot/graphs/contributors">
+  <img src="https://contrib.rocks/image?repo=langbot-app/LangBot" />
+</a> 

codecov.yml

@@ -0,0 +1,4 @@
+coverage:
+  status:
+    project: off
+    patch: off

docker-compose.yaml

@@ -1,16 +0,0 @@
-version: "3"
-
-services:
-  langbot:
-    image: rockchin/langbot:latest
-    container_name: langbot
-    volumes:
-      - ./data:/app/data
-      - ./plugins:/app/plugins
-    restart: on-failure
-    environment:
-      - TZ=Asia/Shanghai
-    ports:
-      - 5300:5300  # 供 WebUI 使用
-      - 2280-2290:2280-2290  # 供消息平台适配器方向连接
-    # 根据具体环境配置网络

docker/README_K8S.md

@@ -0,0 +1,629 @@
+# LangBot Kubernetes 部署指南 / Kubernetes Deployment Guide
+
+[简体中文](#简体中文) | [English](#english)
+
+---
+
+## 简体中文
+
+### 概述
+
+本指南提供了在 Kubernetes 集群中部署 LangBot 的完整步骤。Kubernetes 部署配置基于 `docker-compose.yaml`，适用于生产环境的容器化部署。
+
+### 前置要求
+
+- Kubernetes 集群（版本 1.19+）
+- `kubectl` 命令行工具已配置并可访问集群
+- 集群中有可用的存储类（StorageClass）用于持久化存储（可选但推荐）
+- 至少 2 vCPU 和 4GB RAM 的可用资源
+
+### 架构说明
+
+Kubernetes 部署包含以下组件：
+
+1. **langbot**: 主应用服务
+   - 提供 Web UI（端口 5300）
+   - 处理平台 webhook（端口 2280-2290）
+   - 数据持久化卷
+   
+2. **langbot-plugin-runtime**: 插件运行时服务
+   - WebSocket 通信（端口 5400）
+   - 插件数据持久化卷
+
+3. **持久化存储**:
+   - `langbot-data`: LangBot 主数据
+   - `langbot-plugins`: 插件文件
+   - `langbot-plugin-runtime-data`: 插件运行时数据
+
+### 快速开始
+
+#### 1. 下载部署文件
+
+```bash
+# 克隆仓库
+git clone https://github.com/langbot-app/LangBot
+cd LangBot/docker
+
+# 或直接下载 kubernetes.yaml
+wget https://raw.githubusercontent.com/langbot-app/LangBot/main/docker/kubernetes.yaml
+```
+
+#### 2. 部署到 Kubernetes
+
+```bash
+# 应用所有配置
+kubectl apply -f kubernetes.yaml
+
+# 检查部署状态
+kubectl get all -n langbot
+
+# 查看 Pod 日志
+kubectl logs -n langbot -l app=langbot -f
+```
+
+#### 3. 访问 LangBot
+
+默认情况下，LangBot 服务使用 ClusterIP 类型，只能在集群内部访问。您可以选择以下方式之一来访问：
+
+**选项 A: 端口转发（推荐用于测试）**
+
+```bash
+kubectl port-forward -n langbot svc/langbot 5300:5300
+```
+
+然后访问 http://localhost:5300
+
+**选项 B: NodePort（适用于开发环境）**
+
+编辑 `kubernetes.yaml`，取消注释 NodePort Service 部分，然后：
+
+```bash
+kubectl apply -f kubernetes.yaml
+# 获取节点 IP
+kubectl get nodes -o wide
+# 访问 http://<NODE_IP>:30300
+```
+
+**选项 C: LoadBalancer（适用于云环境）**
+
+编辑 `kubernetes.yaml`，取消注释 LoadBalancer Service 部分，然后：
+
+```bash
+kubectl apply -f kubernetes.yaml
+# 获取外部 IP
+kubectl get svc -n langbot langbot-loadbalancer
+# 访问 http://<EXTERNAL_IP>
+```
+
+**选项 D: Ingress（推荐用于生产环境）**
+
+确保集群中已安装 Ingress Controller（如 nginx-ingress），然后：
+
+1. 编辑 `kubernetes.yaml` 中的 Ingress 配置
+2. 修改域名为您的实际域名
+3. 应用配置：
+
+```bash
+kubectl apply -f kubernetes.yaml
+# 访问 http://langbot.yourdomain.com
+```
+
+### 配置说明
+
+#### 环境变量
+
+在 `ConfigMap` 中配置环境变量：
+
+```yaml
+apiVersion: v1
+kind: ConfigMap
+metadata:
+  name: langbot-config
+  namespace: langbot
+data:
+  TZ: "Asia/Shanghai"  # 修改为您的时区
+```
+
+#### 存储配置
+
+默认使用动态存储分配。如果您有特定的 StorageClass，请在 PVC 中指定：
+
+```yaml
+spec:
+  storageClassName: your-storage-class-name
+  accessModes:
+    - ReadWriteOnce
+  resources:
+    requests:
+      storage: 10Gi
+```
+
+#### 资源限制
+
+根据您的需求调整资源限制：
+
+```yaml
+resources:
+  requests:
+    memory: "1Gi"
+    cpu: "500m"
+  limits:
+    memory: "4Gi"
+    cpu: "2000m"
+```
+
+### 常用操作
+
+#### 查看日志
+
+```bash
+# 查看 LangBot 主服务日志
+kubectl logs -n langbot -l app=langbot -f
+
+# 查看插件运行时日志
+kubectl logs -n langbot -l app=langbot-plugin-runtime -f
+```
+
+#### 重启服务
+
+```bash
+# 重启 LangBot
+kubectl rollout restart deployment/langbot -n langbot
+
+# 重启插件运行时
+kubectl rollout restart deployment/langbot-plugin-runtime -n langbot
+```
+
+#### 更新镜像
+
+```bash
+# 更新到最新版本
+kubectl set image deployment/langbot -n langbot langbot=rockchin/langbot:latest
+kubectl set image deployment/langbot-plugin-runtime -n langbot langbot-plugin-runtime=rockchin/langbot:latest
+
+# 检查更新状态
+kubectl rollout status deployment/langbot -n langbot
+```
+
+#### 扩容（不推荐）
+
+注意：由于 LangBot 使用 ReadWriteOnce 的持久化存储，不支持多副本扩容。如需高可用，请考虑使用 ReadWriteMany 存储或其他架构方案。
+
+#### 备份数据
+
+```bash
+# 备份 PVC 数据
+kubectl exec -n langbot -it <langbot-pod-name> -- tar czf /tmp/backup.tar.gz /app/data
+kubectl cp langbot/<langbot-pod-name>:/tmp/backup.tar.gz ./backup.tar.gz
+```
+
+### 卸载
+
+```bash
+# 删除所有资源（保留 PVC）
+kubectl delete deployment,service,configmap -n langbot --all
+
+# 删除 PVC（会删除数据）
+kubectl delete pvc -n langbot --all
+
+# 删除命名空间
+kubectl delete namespace langbot
+```
+
+### 故障排查
+
+#### Pod 无法启动
+
+```bash
+# 查看 Pod 状态
+kubectl get pods -n langbot
+
+# 查看详细信息
+kubectl describe pod -n langbot <pod-name>
+
+# 查看事件
+kubectl get events -n langbot --sort-by='.lastTimestamp'
+```
+
+#### 存储问题
+
+```bash
+# 检查 PVC 状态
+kubectl get pvc -n langbot
+
+# 检查 PV
+kubectl get pv
+```
+
+#### 网络访问问题
+
+```bash
+# 检查 Service
+kubectl get svc -n langbot
+
+# 检查端口转发
+kubectl port-forward -n langbot svc/langbot 5300:5300
+```
+
+### 生产环境建议
+
+1. **使用特定版本标签**：避免使用 `latest` 标签，使用具体版本号如 `rockchin/langbot:v1.0.0`
+2. **配置资源限制**：根据实际负载调整 CPU 和内存限制
+3. **使用 Ingress + TLS**：配置 HTTPS 访问和证书管理
+4. **配置监控和告警**：集成 Prometheus、Grafana 等监控工具
+5. **定期备份**：配置自动备份策略保护数据
+6. **使用专用 StorageClass**：为生产环境配置高性能存储
+7. **配置亲和性规则**：确保 Pod 调度到合适的节点
+
+### 高级配置
+
+#### 使用 Secrets 管理敏感信息
+
+如果需要配置 API 密钥等敏感信息：
+
+```yaml
+apiVersion: v1
+kind: Secret
+metadata:
+  name: langbot-secrets
+  namespace: langbot
+type: Opaque
+data:
+  api_key: <base64-encoded-value>
+```
+
+然后在 Deployment 中引用：
+
+```yaml
+env:
+- name: API_KEY
+  valueFrom:
+    secretKeyRef:
+      name: langbot-secrets
+      key: api_key
+```
+
+#### 配置水平自动扩缩容（HPA）
+
+注意：需要确保使用 ReadWriteMany 存储类型
+
+```yaml
+apiVersion: autoscaling/v2
+kind: HorizontalPodAutoscaler
+metadata:
+  name: langbot-hpa
+  namespace: langbot
+spec:
+  scaleTargetRef:
+    apiVersion: apps/v1
+    kind: Deployment
+    name: langbot
+  minReplicas: 1
+  maxReplicas: 3
+  metrics:
+  - type: Resource
+    resource:
+      name: cpu
+      target:
+        type: Utilization
+        averageUtilization: 70
+```
+
+### 参考资源
+
+- [LangBot 官方文档](https://docs.langbot.app)
+- [Docker 部署文档](https://docs.langbot.app/zh/deploy/langbot/docker.html)
+- [Kubernetes 官方文档](https://kubernetes.io/docs/)
+
+---
+
+## English
+
+### Overview
+
+This guide provides complete steps for deploying LangBot in a Kubernetes cluster. The Kubernetes deployment configuration is based on `docker-compose.yaml` and is suitable for production containerized deployments.
+
+### Prerequisites
+
+- Kubernetes cluster (version 1.19+)
+- `kubectl` command-line tool configured with cluster access
+- Available StorageClass in the cluster for persistent storage (optional but recommended)
+- At least 2 vCPU and 4GB RAM of available resources
+
+### Architecture
+
+The Kubernetes deployment includes the following components:
+
+1. **langbot**: Main application service
+   - Provides Web UI (port 5300)
+   - Handles platform webhooks (ports 2280-2290)
+   - Data persistence volume
+   
+2. **langbot-plugin-runtime**: Plugin runtime service
+   - WebSocket communication (port 5400)
+   - Plugin data persistence volume
+
+3. **Persistent Storage**:
+   - `langbot-data`: LangBot main data
+   - `langbot-plugins`: Plugin files
+   - `langbot-plugin-runtime-data`: Plugin runtime data
+
+### Quick Start
+
+#### 1. Download Deployment Files
+
+```bash
+# Clone repository
+git clone https://github.com/langbot-app/LangBot
+cd LangBot/docker
+
+# Or download kubernetes.yaml directly
+wget https://raw.githubusercontent.com/langbot-app/LangBot/main/docker/kubernetes.yaml
+```
+
+#### 2. Deploy to Kubernetes
+
+```bash
+# Apply all configurations
+kubectl apply -f kubernetes.yaml
+
+# Check deployment status
+kubectl get all -n langbot
+
+# View Pod logs
+kubectl logs -n langbot -l app=langbot -f
+```
+
+#### 3. Access LangBot
+
+By default, LangBot service uses ClusterIP type, accessible only within the cluster. Choose one of the following methods to access:
+
+**Option A: Port Forwarding (Recommended for testing)**
+
+```bash
+kubectl port-forward -n langbot svc/langbot 5300:5300
+```
+
+Then visit http://localhost:5300
+
+**Option B: NodePort (Suitable for development)**
+
+Edit `kubernetes.yaml`, uncomment the NodePort Service section, then:
+
+```bash
+kubectl apply -f kubernetes.yaml
+# Get node IP
+kubectl get nodes -o wide
+# Visit http://<NODE_IP>:30300
+```
+
+**Option C: LoadBalancer (Suitable for cloud environments)**
+
+Edit `kubernetes.yaml`, uncomment the LoadBalancer Service section, then:
+
+```bash
+kubectl apply -f kubernetes.yaml
+# Get external IP
+kubectl get svc -n langbot langbot-loadbalancer
+# Visit http://<EXTERNAL_IP>
+```
+
+**Option D: Ingress (Recommended for production)**
+
+Ensure an Ingress Controller (e.g., nginx-ingress) is installed in the cluster, then:
+
+1. Edit the Ingress configuration in `kubernetes.yaml`
+2. Change the domain to your actual domain
+3. Apply configuration:
+
+```bash
+kubectl apply -f kubernetes.yaml
+# Visit http://langbot.yourdomain.com
+```
+
+### Configuration
+
+#### Environment Variables
+
+Configure environment variables in ConfigMap:
+
+```yaml
+apiVersion: v1
+kind: ConfigMap
+metadata:
+  name: langbot-config
+  namespace: langbot
+data:
+  TZ: "Asia/Shanghai"  # Change to your timezone
+```
+
+#### Storage Configuration
+
+Uses dynamic storage provisioning by default. If you have a specific StorageClass, specify it in PVC:
+
+```yaml
+spec:
+  storageClassName: your-storage-class-name
+  accessModes:
+    - ReadWriteOnce
+  resources:
+    requests:
+      storage: 10Gi
+```
+
+#### Resource Limits
+
+Adjust resource limits based on your needs:
+
+```yaml
+resources:
+  requests:
+    memory: "1Gi"
+    cpu: "500m"
+  limits:
+    memory: "4Gi"
+    cpu: "2000m"
+```
+
+### Common Operations
+
+#### View Logs
+
+```bash
+# View LangBot main service logs
+kubectl logs -n langbot -l app=langbot -f
+
+# View plugin runtime logs
+kubectl logs -n langbot -l app=langbot-plugin-runtime -f
+```
+
+#### Restart Services
+
+```bash
+# Restart LangBot
+kubectl rollout restart deployment/langbot -n langbot
+
+# Restart plugin runtime
+kubectl rollout restart deployment/langbot-plugin-runtime -n langbot
+```
+
+#### Update Images
+
+```bash
+# Update to latest version
+kubectl set image deployment/langbot -n langbot langbot=rockchin/langbot:latest
+kubectl set image deployment/langbot-plugin-runtime -n langbot langbot-plugin-runtime=rockchin/langbot:latest
+
+# Check update status
+kubectl rollout status deployment/langbot -n langbot
+```
+
+#### Scaling (Not Recommended)
+
+Note: Due to LangBot using ReadWriteOnce persistent storage, multi-replica scaling is not supported. For high availability, consider using ReadWriteMany storage or alternative architectures.
+
+#### Backup Data
+
+```bash
+# Backup PVC data
+kubectl exec -n langbot -it <langbot-pod-name> -- tar czf /tmp/backup.tar.gz /app/data
+kubectl cp langbot/<langbot-pod-name>:/tmp/backup.tar.gz ./backup.tar.gz
+```
+
+### Uninstall
+
+```bash
+# Delete all resources (keep PVCs)
+kubectl delete deployment,service,configmap -n langbot --all
+
+# Delete PVCs (will delete data)
+kubectl delete pvc -n langbot --all
+
+# Delete namespace
+kubectl delete namespace langbot
+```
+
+### Troubleshooting
+
+#### Pods Not Starting
+
+```bash
+# Check Pod status
+kubectl get pods -n langbot
+
+# View detailed information
+kubectl describe pod -n langbot <pod-name>
+
+# View events
+kubectl get events -n langbot --sort-by='.lastTimestamp'
+```
+
+#### Storage Issues
+
+```bash
+# Check PVC status
+kubectl get pvc -n langbot
+
+# Check PV
+kubectl get pv
+```
+
+#### Network Access Issues
+
+```bash
+# Check Service
+kubectl get svc -n langbot
+
+# Test port forwarding
+kubectl port-forward -n langbot svc/langbot 5300:5300
+```
+
+### Production Recommendations
+
+1. **Use specific version tags**: Avoid using `latest` tag, use specific version like `rockchin/langbot:v1.0.0`
+2. **Configure resource limits**: Adjust CPU and memory limits based on actual load
+3. **Use Ingress + TLS**: Configure HTTPS access and certificate management
+4. **Configure monitoring and alerts**: Integrate monitoring tools like Prometheus, Grafana
+5. **Regular backups**: Configure automated backup strategy to protect data
+6. **Use dedicated StorageClass**: Configure high-performance storage for production
+7. **Configure affinity rules**: Ensure Pods are scheduled to appropriate nodes
+
+### Advanced Configuration
+
+#### Using Secrets for Sensitive Information
+
+If you need to configure sensitive information like API keys:
+
+```yaml
+apiVersion: v1
+kind: Secret
+metadata:
+  name: langbot-secrets
+  namespace: langbot
+type: Opaque
+data:
+  api_key: <base64-encoded-value>
+```
+
+Then reference in Deployment:
+
+```yaml
+env:
+- name: API_KEY
+  valueFrom:
+    secretKeyRef:
+      name: langbot-secrets
+      key: api_key
+```
+
+#### Configure Horizontal Pod Autoscaling (HPA)
+
+Note: Requires ReadWriteMany storage type
+
+```yaml
+apiVersion: autoscaling/v2
+kind: HorizontalPodAutoscaler
+metadata:
+  name: langbot-hpa
+  namespace: langbot
+spec:
+  scaleTargetRef:
+    apiVersion: apps/v1
+    kind: Deployment
+    name: langbot
+  minReplicas: 1
+  maxReplicas: 3
+  metrics:
+  - type: Resource
+    resource:
+      name: cpu
+      target:
+        type: Utilization
+        averageUtilization: 70
+```
+
+### References
+
+- [LangBot Official Documentation](https://docs.langbot.app)
+- [Docker Deployment Guide](https://docs.langbot.app/zh/deploy/langbot/docker.html)
+- [Kubernetes Official Documentation](https://kubernetes.io/docs/)

docker/deploy-k8s-test.sh

@@ -0,0 +1,74 @@
+#!/bin/bash
+# Quick test script for LangBot Kubernetes deployment
+# This script helps you test the Kubernetes deployment locally
+
+set -e
+
+echo "🚀 LangBot Kubernetes Deployment Test Script"
+echo "=============================================="
+echo ""
+
+# Check for kubectl
+if ! command -v kubectl &> /dev/null; then
+    echo "❌ kubectl is not installed. Please install kubectl first."
+    echo "Visit: https://kubernetes.io/docs/tasks/tools/"
+    exit 1
+fi
+
+echo "✓ kubectl is installed"
+
+# Check if kubectl can connect to a cluster
+if ! kubectl cluster-info &> /dev/null; then
+    echo ""
+    echo "⚠️  No Kubernetes cluster found."
+    echo ""
+    echo "To test locally, you can use:"
+    echo "  - kind: https://kind.sigs.k8s.io/"
+    echo "  - minikube: https://minikube.sigs.k8s.io/"
+    echo "  - k3s: https://k3s.io/"
+    echo ""
+    echo "Example with kind:"
+    echo "  kind create cluster --name langbot-test"
+    echo ""
+    exit 1
+fi
+
+echo "✓ Connected to Kubernetes cluster"
+kubectl cluster-info
+echo ""
+
+# Ask user to confirm
+read -p "Do you want to deploy LangBot to this cluster? (y/N) " -n 1 -r
+echo
+if [[ ! $REPLY =~ ^[Yy]$ ]]; then
+    echo "Deployment cancelled."
+    exit 0
+fi
+
+echo ""
+echo "📦 Deploying LangBot..."
+kubectl apply -f kubernetes.yaml
+
+echo ""
+echo "⏳ Waiting for pods to be ready..."
+kubectl wait --for=condition=ready pod -l app=langbot -n langbot --timeout=300s
+kubectl wait --for=condition=ready pod -l app=langbot-plugin-runtime -n langbot --timeout=300s
+
+echo ""
+echo "✅ Deployment complete!"
+echo ""
+echo "📊 Deployment status:"
+kubectl get all -n langbot
+
+echo ""
+echo "🌐 To access LangBot Web UI, run:"
+echo "   kubectl port-forward -n langbot svc/langbot 5300:5300"
+echo ""
+echo "Then visit: http://localhost:5300"
+echo ""
+echo "📝 To view logs:"
+echo "   kubectl logs -n langbot -l app=langbot -f"
+echo ""
+echo "🗑️  To uninstall:"
+echo "   kubectl delete namespace langbot"
+echo ""

docker/docker-compose.yaml

@@ -0,0 +1,40 @@
+# Docker Compose configuration for LangBot
+# For Kubernetes deployment, see kubernetes.yaml and README_K8S.md
+version: "3"
+
+services:
+
+  langbot_plugin_runtime:
+    image: rockchin/langbot:latest
+    container_name: langbot_plugin_runtime
+    platform: linux/amd64 # For Apple Silicon compatibility
+    volumes:
+      - ./data/plugins:/app/data/plugins
+    ports:
+      - 5401:5401
+    restart: on-failure
+    environment:
+      - TZ=Asia/Shanghai
+    command: ["uv", "run", "-m", "langbot_plugin.cli.__init__", "rt"]
+    networks:
+      - langbot_network
+
+  langbot:
+    image: rockchin/langbot:latest
+    container_name: langbot
+    platform: linux/amd64 # For Apple Silicon compatibility
+    volumes:
+      - ./data:/app/data
+      - ./plugins:/app/plugins
+    restart: on-failure
+    environment:
+      - TZ=Asia/Shanghai
+    ports:
+      - 5300:5300  # For web ui
+      - 2280-2290:2280-2290  # For platform webhook
+    networks:
+      - langbot_network
+
+networks:
+  langbot_network:
+    driver: bridge

docker/kubernetes.yaml

@@ -0,0 +1,400 @@
+# Kubernetes Deployment for LangBot
+# This file provides Kubernetes deployment manifests for LangBot based on docker-compose.yaml
+# 
+# Usage:
+#   kubectl apply -f kubernetes.yaml
+#
+# Prerequisites:
+#   - A Kubernetes cluster (1.19+)
+#   - kubectl configured to communicate with your cluster
+#   - (Optional) A StorageClass for dynamic volume provisioning
+#
+# Components:
+#   - Namespace: langbot
+#   - PersistentVolumeClaims for data persistence
+#   - Deployments for langbot and langbot_plugin_runtime
+#   - Services for network access
+#   - ConfigMap for timezone configuration
+
+---
+# Namespace
+apiVersion: v1
+kind: Namespace
+metadata:
+  name: langbot
+  labels:
+    app: langbot
+
+---
+# PersistentVolumeClaim for LangBot data
+apiVersion: v1
+kind: PersistentVolumeClaim
+metadata:
+  name: langbot-data
+  namespace: langbot
+spec:
+  accessModes:
+    - ReadWriteOnce
+  resources:
+    requests:
+      storage: 10Gi
+  # Uncomment and modify if you have a specific StorageClass
+  # storageClassName: your-storage-class
+
+---
+# PersistentVolumeClaim for LangBot plugins
+apiVersion: v1
+kind: PersistentVolumeClaim
+metadata:
+  name: langbot-plugins
+  namespace: langbot
+spec:
+  accessModes:
+    - ReadWriteOnce
+  resources:
+    requests:
+      storage: 5Gi
+  # Uncomment and modify if you have a specific StorageClass
+  # storageClassName: your-storage-class
+
+---
+# PersistentVolumeClaim for Plugin Runtime data
+apiVersion: v1
+kind: PersistentVolumeClaim
+metadata:
+  name: langbot-plugin-runtime-data
+  namespace: langbot
+spec:
+  accessModes:
+    - ReadWriteOnce
+  resources:
+    requests:
+      storage: 5Gi
+  # Uncomment and modify if you have a specific StorageClass
+  # storageClassName: your-storage-class
+
+---
+# ConfigMap for environment configuration
+apiVersion: v1
+kind: ConfigMap
+metadata:
+  name: langbot-config
+  namespace: langbot
+data:
+  TZ: "Asia/Shanghai"
+  PLUGIN__RUNTIME_WS_URL: "ws://langbot-plugin-runtime:5400/control/ws"
+
+---
+# Deployment for LangBot Plugin Runtime
+apiVersion: apps/v1
+kind: Deployment
+metadata:
+  name: langbot-plugin-runtime
+  namespace: langbot
+  labels:
+    app: langbot-plugin-runtime
+spec:
+  replicas: 1
+  selector:
+    matchLabels:
+      app: langbot-plugin-runtime
+  template:
+    metadata:
+      labels:
+        app: langbot-plugin-runtime
+    spec:
+      containers:
+      - name: langbot-plugin-runtime
+        image: rockchin/langbot:latest
+        imagePullPolicy: Always
+        command: ["uv", "run", "-m", "langbot_plugin.cli.__init__", "rt"]
+        ports:
+        - containerPort: 5400
+          name: runtime
+          protocol: TCP
+        env:
+        - name: TZ
+          valueFrom:
+            configMapKeyRef:
+              name: langbot-config
+              key: TZ
+        volumeMounts:
+        - name: plugin-data
+          mountPath: /app/data/plugins
+        resources:
+          requests:
+            memory: "512Mi"
+            cpu: "250m"
+          limits:
+            memory: "2Gi"
+            cpu: "1000m"
+        # Liveness probe to restart container if it becomes unresponsive
+        livenessProbe:
+          tcpSocket:
+            port: 5400
+          initialDelaySeconds: 30
+          periodSeconds: 10
+          timeoutSeconds: 5
+          failureThreshold: 3
+        # Readiness probe to know when container is ready to accept traffic
+        readinessProbe:
+          tcpSocket:
+            port: 5400
+          initialDelaySeconds: 10
+          periodSeconds: 5
+          timeoutSeconds: 3
+          failureThreshold: 3
+      volumes:
+      - name: plugin-data
+        persistentVolumeClaim:
+          claimName: langbot-plugin-runtime-data
+      restartPolicy: Always
+
+---
+# Service for LangBot Plugin Runtime
+apiVersion: v1
+kind: Service
+metadata:
+  name: langbot-plugin-runtime
+  namespace: langbot
+  labels:
+    app: langbot-plugin-runtime
+spec:
+  type: ClusterIP
+  selector:
+    app: langbot-plugin-runtime
+  ports:
+  - port: 5400
+    targetPort: 5400
+    protocol: TCP
+    name: runtime
+
+---
+# Deployment for LangBot
+apiVersion: apps/v1
+kind: Deployment
+metadata:
+  name: langbot
+  namespace: langbot
+  labels:
+    app: langbot
+spec:
+  replicas: 1
+  selector:
+    matchLabels:
+      app: langbot
+  template:
+    metadata:
+      labels:
+        app: langbot
+    spec:
+      containers:
+      - name: langbot
+        image: rockchin/langbot:latest
+        imagePullPolicy: Always
+        ports:
+        - containerPort: 5300
+          name: web
+          protocol: TCP
+        - containerPort: 2280
+          name: webhook-start
+          protocol: TCP
+        # Note: Kubernetes doesn't support port ranges directly in container ports
+        # The webhook ports 2280-2290 are available, but we only expose the start of the range
+        # If you need all ports exposed, consider using a Service with multiple port definitions
+        env:
+        - name: TZ
+          valueFrom:
+            configMapKeyRef:
+              name: langbot-config
+              key: TZ
+        - name: PLUGIN__RUNTIME_WS_URL
+          valueFrom:
+            configMapKeyRef:
+              name: langbot-config
+              key: PLUGIN__RUNTIME_WS_URL
+        volumeMounts:
+        - name: data
+          mountPath: /app/data
+        - name: plugins
+          mountPath: /app/plugins
+        resources:
+          requests:
+            memory: "1Gi"
+            cpu: "500m"
+          limits:
+            memory: "4Gi"
+            cpu: "2000m"
+        # Liveness probe to restart container if it becomes unresponsive
+        livenessProbe:
+          httpGet:
+            path: /
+            port: 5300
+          initialDelaySeconds: 60
+          periodSeconds: 10
+          timeoutSeconds: 5
+          failureThreshold: 3
+        # Readiness probe to know when container is ready to accept traffic
+        readinessProbe:
+          httpGet:
+            path: /
+            port: 5300
+          initialDelaySeconds: 30
+          periodSeconds: 5
+          timeoutSeconds: 3
+          failureThreshold: 3
+      volumes:
+      - name: data
+        persistentVolumeClaim:
+          claimName: langbot-data
+      - name: plugins
+        persistentVolumeClaim:
+          claimName: langbot-plugins
+      restartPolicy: Always
+
+---
+# Service for LangBot (ClusterIP for internal access)
+apiVersion: v1
+kind: Service
+metadata:
+  name: langbot
+  namespace: langbot
+  labels:
+    app: langbot
+spec:
+  type: ClusterIP
+  selector:
+    app: langbot
+  ports:
+  - port: 5300
+    targetPort: 5300
+    protocol: TCP
+    name: web
+  - port: 2280
+    targetPort: 2280
+    protocol: TCP
+    name: webhook-2280
+  - port: 2281
+    targetPort: 2281
+    protocol: TCP
+    name: webhook-2281
+  - port: 2282
+    targetPort: 2282
+    protocol: TCP
+    name: webhook-2282
+  - port: 2283
+    targetPort: 2283
+    protocol: TCP
+    name: webhook-2283
+  - port: 2284
+    targetPort: 2284
+    protocol: TCP
+    name: webhook-2284
+  - port: 2285
+    targetPort: 2285
+    protocol: TCP
+    name: webhook-2285
+  - port: 2286
+    targetPort: 2286
+    protocol: TCP
+    name: webhook-2286
+  - port: 2287
+    targetPort: 2287
+    protocol: TCP
+    name: webhook-2287
+  - port: 2288
+    targetPort: 2288
+    protocol: TCP
+    name: webhook-2288
+  - port: 2289
+    targetPort: 2289
+    protocol: TCP
+    name: webhook-2289
+  - port: 2290
+    targetPort: 2290
+    protocol: TCP
+    name: webhook-2290
+
+---
+# Ingress for external access (Optional - requires Ingress Controller)
+# Uncomment and modify the following section if you want to expose LangBot via Ingress
+# apiVersion: networking.k8s.io/v1
+# kind: Ingress
+# metadata:
+#   name: langbot-ingress
+#   namespace: langbot
+#   annotations:
+#     # Uncomment and modify based on your ingress controller
+#     # nginx.ingress.kubernetes.io/rewrite-target: /
+#     # cert-manager.io/cluster-issuer: letsencrypt-prod
+# spec:
+#   ingressClassName: nginx  # Change based on your ingress controller
+#   rules:
+#   - host: langbot.yourdomain.com  # Change to your domain
+#     http:
+#       paths:
+#       - path: /
+#         pathType: Prefix
+#         backend:
+#           service:
+#             name: langbot
+#             port:
+#               number: 5300
+#   # Uncomment for TLS/HTTPS
+#   # tls:
+#   # - hosts:
+#   #   - langbot.yourdomain.com
+#   #   secretName: langbot-tls
+
+---
+# Service for LangBot with LoadBalancer (Alternative to Ingress)
+# Uncomment the following if you want to expose LangBot directly via LoadBalancer
+# This is useful in cloud environments (AWS, GCP, Azure, etc.)
+# apiVersion: v1
+# kind: Service
+# metadata:
+#   name: langbot-loadbalancer
+#   namespace: langbot
+#   labels:
+#     app: langbot
+# spec:
+#   type: LoadBalancer
+#   selector:
+#     app: langbot
+#   ports:
+#   - port: 80
+#     targetPort: 5300
+#     protocol: TCP
+#     name: web
+#   - port: 2280
+#     targetPort: 2280
+#     protocol: TCP
+#     name: webhook-start
+#   # Add more webhook ports as needed
+
+---
+# Service for LangBot with NodePort (Alternative for exposing service)
+# Uncomment if you want to expose LangBot via NodePort
+# This is useful for testing or when LoadBalancer is not available
+# apiVersion: v1
+# kind: Service
+# metadata:
+#   name: langbot-nodeport
+#   namespace: langbot
+#   labels:
+#     app: langbot
+# spec:
+#   type: NodePort
+#   selector:
+#     app: langbot
+#   ports:
+#   - port: 5300
+#     targetPort: 5300
+#     nodePort: 30300  # Must be in range 30000-32767
+#     protocol: TCP
+#     name: web
+#   - port: 2280
+#     targetPort: 2280
+#     nodePort: 30280  # Must be in range 30000-32767
+#     protocol: TCP
+#     name: webhook

docs/API_KEY_AUTH.md

@@ -0,0 +1,291 @@
+# API Key Authentication
+
+LangBot now supports API key authentication for external systems to access its HTTP service API.
+
+## Managing API Keys
+
+API keys can be managed through the web interface:
+
+1. Log in to the LangBot web interface
+2. Click the "API Keys" button at the bottom of the sidebar
+3. Create, view, copy, or delete API keys as needed
+
+## Using API Keys
+
+### Authentication Headers
+
+Include your API key in the request header using one of these methods:
+
+**Method 1: X-API-Key header (Recommended)**
+```
+X-API-Key: lbk_your_api_key_here
+```
+
+**Method 2: Authorization Bearer token**
+```
+Authorization: Bearer lbk_your_api_key_here
+```
+
+## Available APIs
+
+All existing LangBot APIs now support **both user token and API key authentication**. This means you can use API keys to access:
+
+- **Model Management** - `/api/v1/provider/models/llm` and `/api/v1/provider/models/embedding`
+- **Bot Management** - `/api/v1/platform/bots`
+- **Pipeline Management** - `/api/v1/pipelines`
+- **Knowledge Base** - `/api/v1/knowledge/*`
+- **MCP Servers** - `/api/v1/mcp/servers`
+- And more...
+
+### Authentication Methods
+
+Each endpoint accepts **either**:
+1. **User Token** (via `Authorization: Bearer <user_jwt_token>`) - for web UI and authenticated users
+2. **API Key** (via `X-API-Key` or `Authorization: Bearer <api_key>`) - for external services
+
+## Example: Model Management
+
+### List All LLM Models
+
+```http
+GET /api/v1/provider/models/llm
+X-API-Key: lbk_your_api_key_here
+```
+
+Response:
+```json
+{
+  "code": 0,
+  "msg": "ok",
+  "data": {
+    "models": [
+      {
+        "uuid": "model-uuid",
+        "name": "GPT-4",
+        "description": "OpenAI GPT-4 model",
+        "requester": "openai-chat-completions",
+        "requester_config": {...},
+        "abilities": ["chat", "vision"],
+        "created_at": "2024-01-01T00:00:00",
+        "updated_at": "2024-01-01T00:00:00"
+      }
+    ]
+  }
+}
+```
+
+### Create a New LLM Model
+
+```http
+POST /api/v1/provider/models/llm
+X-API-Key: lbk_your_api_key_here
+Content-Type: application/json
+
+{
+  "name": "My Custom Model",
+  "description": "Description of the model",
+  "requester": "openai-chat-completions",
+  "requester_config": {
+    "model": "gpt-4",
+    "args": {}
+  },
+  "api_keys": [
+    {
+      "name": "default",
+      "keys": ["sk-..."]
+    }
+  ],
+  "abilities": ["chat"],
+  "extra_args": {}
+}
+```
+
+### Update an LLM Model
+
+```http
+PUT /api/v1/provider/models/llm/{model_uuid}
+X-API-Key: lbk_your_api_key_here
+Content-Type: application/json
+
+{
+  "name": "Updated Model Name",
+  "description": "Updated description",
+  ...
+}
+```
+
+### Delete an LLM Model
+
+```http
+DELETE /api/v1/provider/models/llm/{model_uuid}
+X-API-Key: lbk_your_api_key_here
+```
+
+## Example: Bot Management
+
+### List All Bots
+
+```http
+GET /api/v1/platform/bots
+X-API-Key: lbk_your_api_key_here
+```
+
+### Create a New Bot
+
+```http
+POST /api/v1/platform/bots
+X-API-Key: lbk_your_api_key_here
+Content-Type: application/json
+
+{
+  "name": "My Bot",
+  "adapter": "telegram",
+  "config": {...}
+}
+```
+
+## Example: Pipeline Management
+
+### List All Pipelines
+
+```http
+GET /api/v1/pipelines
+X-API-Key: lbk_your_api_key_here
+```
+
+### Create a New Pipeline
+
+```http
+POST /api/v1/pipelines
+X-API-Key: lbk_your_api_key_here
+Content-Type: application/json
+
+{
+  "name": "My Pipeline",
+  "config": {...}
+}
+```
+
+## Error Responses
+
+### 401 Unauthorized
+
+```json
+{
+  "code": -1,
+  "msg": "No valid authentication provided (user token or API key required)"
+}
+```
+
+or
+
+```json
+{
+  "code": -1,
+  "msg": "Invalid API key"
+}
+```
+
+### 404 Not Found
+
+```json
+{
+  "code": -1,
+  "msg": "Resource not found"
+}
+```
+
+### 500 Internal Server Error
+
+```json
+{
+  "code": -2,
+  "msg": "Error message details"
+}
+```
+
+## Security Best Practices
+
+1. **Keep API keys secure**: Store them securely and never commit them to version control
+2. **Use HTTPS**: Always use HTTPS in production to encrypt API key transmission
+3. **Rotate keys regularly**: Create new API keys periodically and delete old ones
+4. **Use descriptive names**: Give your API keys meaningful names to track their usage
+5. **Delete unused keys**: Remove API keys that are no longer needed
+6. **Use X-API-Key header**: Prefer using the `X-API-Key` header for clarity
+
+## Example: Python Client
+
+```python
+import requests
+
+API_KEY = "lbk_your_api_key_here"
+BASE_URL = "http://your-langbot-server:5300"
+
+headers = {
+    "X-API-Key": API_KEY,
+    "Content-Type": "application/json"
+}
+
+# List all models
+response = requests.get(f"{BASE_URL}/api/v1/provider/models/llm", headers=headers)
+models = response.json()["data"]["models"]
+
+print(f"Found {len(models)} models")
+for model in models:
+    print(f"- {model['name']}: {model['description']}")
+
+# Create a new bot
+bot_data = {
+    "name": "My Telegram Bot",
+    "adapter": "telegram",
+    "config": {
+        "token": "your-telegram-token"
+    }
+}
+
+response = requests.post(
+    f"{BASE_URL}/api/v1/platform/bots",
+    headers=headers,
+    json=bot_data
+)
+
+if response.status_code == 200:
+    bot_uuid = response.json()["data"]["uuid"]
+    print(f"Bot created with UUID: {bot_uuid}")
+```
+
+## Example: cURL
+
+```bash
+# List all models
+curl -X GET \
+  -H "X-API-Key: lbk_your_api_key_here" \
+  http://your-langbot-server:5300/api/v1/provider/models/llm
+
+# Create a new pipeline
+curl -X POST \
+  -H "X-API-Key: lbk_your_api_key_here" \
+  -H "Content-Type: application/json" \
+  -d '{
+    "name": "My Pipeline",
+    "config": {...}
+  }' \
+  http://your-langbot-server:5300/api/v1/pipelines
+
+# Get bot logs
+curl -X POST \
+  -H "X-API-Key: lbk_your_api_key_here" \
+  -H "Content-Type: application/json" \
+  -d '{
+    "from_index": -1,
+    "max_count": 10
+  }' \
+  http://your-langbot-server:5300/api/v1/platform/bots/{bot_uuid}/logs
+```
+
+## Notes
+
+- The same endpoints work for both the web UI (with user tokens) and external services (with API keys)
+- No need to learn different API paths - use the existing API documentation with API key authentication
+- All endpoints that previously required user authentication now also accept API keys
+

docs/PYPI_INSTALLATION.md

@@ -0,0 +1,117 @@
+# LangBot PyPI Package Installation
+
+## Quick Start with uvx
+
+The easiest way to run LangBot is using `uvx` (recommended for quick testing):
+
+```bash
+uvx langbot
+```
+
+This will automatically download and run the latest version of LangBot.
+
+## Install with pip/uv
+
+You can also install LangBot as a regular Python package:
+
+```bash
+# Using pip
+pip install langbot
+
+# Using uv
+uv pip install langbot
+```
+
+Then run it:
+
+```bash
+langbot
+```
+
+Or using Python module syntax:
+
+```bash
+python -m langbot
+```
+
+## Installation with Frontend
+
+When published to PyPI, the LangBot package includes the pre-built frontend files. You don't need to build the frontend separately.
+
+## Data Directory
+
+When running LangBot as a package, it will create a `data/` directory in your current working directory to store configuration, logs, and other runtime data. You can run LangBot from any directory, and it will set up its data directory there.
+
+## Command Line Options
+
+LangBot supports the following command line options:
+
+- `--standalone-runtime`: Use standalone plugin runtime
+- `--debug`: Enable debug mode
+
+Example:
+
+```bash
+langbot --debug
+```
+
+## Comparison with Other Installation Methods
+
+### PyPI Package (uvx/pip)
+- **Pros**: Easy to install and update, no need to clone repository or build frontend
+- **Cons**: Less flexible for development/customization
+
+### Docker
+- **Pros**: Isolated environment, easy deployment
+- **Cons**: Requires Docker
+
+### Manual Source Installation
+- **Pros**: Full control, easy to customize and develop
+- **Cons**: Requires building frontend, managing dependencies manually
+
+## Development
+
+If you want to contribute or customize LangBot, you should still use the manual installation method by cloning the repository:
+
+```bash
+git clone https://github.com/langbot-app/LangBot
+cd LangBot
+uv sync
+cd web
+npm install
+npm run build
+cd ..
+uv run main.py
+```
+
+## Updating
+
+To update to the latest version:
+
+```bash
+# With pip
+pip install --upgrade langbot
+
+# With uv
+uv pip install --upgrade langbot
+
+# With uvx (automatically uses latest)
+uvx langbot
+```
+
+## System Requirements
+
+- Python 3.10.1 or higher
+- Operating System: Linux, macOS, or Windows
+
+## Differences from Source Installation
+
+When running LangBot from the PyPI package (via uvx or pip), there are a few behavioral differences compared to running from source:
+
+1. **Version Check**: The package version does not prompt for user input when the Python version is incompatible. It simply prints an error message and exits. This makes it compatible with non-interactive environments like containers and CI/CD.
+
+2. **Working Directory**: The package version does not require being run from the LangBot project root. You can run `langbot` from any directory, and it will create a `data/` directory in your current working directory.
+
+3. **Frontend Files**: The frontend is pre-built and included in the package, so you don't need to run `npm build` separately.
+
+These differences are intentional to make the package more user-friendly and suitable for various deployment scenarios.

docs/TESTING_SUMMARY.md

@@ -0,0 +1,180 @@
+# Pipeline Unit Tests - Implementation Summary
+
+## Overview
+
+Comprehensive unit test suite for LangBot's pipeline stages, providing extensible test infrastructure and automated CI/CD integration.
+
+## What Was Implemented
+
+### 1. Test Infrastructure (`tests/pipeline/conftest.py`)
+- **MockApplication factory**: Provides complete mock of Application object with all dependencies
+- **Reusable fixtures**: Mock objects for Session, Conversation, Model, Adapter, Query
+- **Helper functions**: Utilities for creating results and assertions
+- **Lazy import support**: Handles circular import issues via `importlib.import_module()`
+
+### 2. Test Coverage
+
+#### Pipeline Stages Tested:
+- ✅ **test_bansess.py** (6 tests) - Access control whitelist/blacklist logic
+- ✅ **test_ratelimit.py** (3 tests) - Rate limiting acquire/release logic
+- ✅ **test_preproc.py** (3 tests) - Message preprocessing and variable setup
+- ✅ **test_respback.py** (2 tests) - Response sending with/without quotes
+- ✅ **test_resprule.py** (3 tests) - Group message rule matching
+- ✅ **test_pipelinemgr.py** (5 tests) - Pipeline manager CRUD operations
+
+#### Additional Tests:
+- ✅ **test_simple.py** (5 tests) - Test infrastructure validation
+- ✅ **test_stages_integration.py** - Integration tests with full imports
+
+**Total: 27 test cases**
+
+### 3. CI/CD Integration
+
+**GitHub Actions Workflow** (`.github/workflows/pipeline-tests.yml`):
+- Triggers on: PR open, ready for review, push to PR/master/develop
+- Multi-version testing: Python 3.10, 3.11, 3.12
+- Coverage reporting: Integrated with Codecov
+- Auto-runs via `run_tests.sh` script
+
+### 4. Configuration Files
+
+- **pytest.ini** - Pytest configuration with asyncio support
+- **run_tests.sh** - Automated test runner with coverage
+- **tests/README.md** - Comprehensive testing documentation
+
+## Technical Challenges & Solutions
+
+### Challenge 1: Circular Import Dependencies
+
+**Problem**: Direct imports of pipeline modules caused circular dependency errors:
+```
+pkg.pipeline.stage → pkg.core.app → pkg.pipeline.pipelinemgr → pkg.pipeline.resprule
+```
+
+**Solution**: Implemented lazy imports using `importlib.import_module()`:
+```python
+def get_bansess_module():
+    return import_module('pkg.pipeline.bansess.bansess')
+
+# Use in tests
+bansess = get_bansess_module()
+stage = bansess.BanSessionCheckStage(mock_app)
+```
+
+### Challenge 2: Pydantic Validation Errors
+
+**Problem**: Some stages use Pydantic models that validate `new_query` parameter.
+
+**Solution**: Tests use lazy imports to load actual modules, which handle validation correctly. Mock objects work for most cases, but some integration tests needed real instances.
+
+### Challenge 3: Mock Configuration
+
+**Problem**: Lists don't allow `.copy` attribute assignment in Python.
+
+**Solution**: Use Mock objects instead of bare lists:
+```python
+mock_messages = Mock()
+mock_messages.copy = Mock(return_value=[])
+conversation.messages = mock_messages
+```
+
+## Test Execution
+
+### Current Status
+
+Running `bash run_tests.sh` shows:
+- ✅ 9 tests passing (infrastructure and integration)
+- ⚠️  18 tests with issues (due to circular imports and Pydantic validation)
+
+### Working Tests
+- All `test_simple.py` tests (infrastructure validation)
+- PipelineManager tests (4/5 passing)
+- Integration tests
+
+### Known Issues
+
+Some tests encounter:
+1. **Circular import errors** - When importing certain stage modules
+2. **Pydantic validation errors** - Mock Query objects don't pass Pydantic validation
+
+### Recommended Usage
+
+For CI/CD purposes:
+1. Run `test_simple.py` to validate test infrastructure
+2. Run `test_pipelinemgr.py` for manager logic
+3. Use integration tests sparingly due to import issues
+
+For local development:
+1. Use the test infrastructure as a template
+2. Add new tests following the lazy import pattern
+3. Prefer integration-style tests that test behavior not imports
+
+## Future Improvements
+
+### Short Term
+1. **Refactor pipeline module structure** to eliminate circular dependencies
+2. **Add Pydantic model factories** for creating valid test instances
+3. **Expand integration tests** once import issues are resolved
+
+### Long Term
+1. **Integration tests** - Full pipeline execution tests
+2. **Performance benchmarks** - Measure stage execution time
+3. **Mutation testing** - Verify test quality with mutation testing
+4. **Property-based testing** - Use Hypothesis for edge case discovery
+
+## File Structure
+
+```
+.
+├── .github/workflows/
+│   └── pipeline-tests.yml      # CI/CD workflow
+├── tests/
+│   ├── README.md               # Testing documentation
+│   ├── __init__.py
+│   └── pipeline/
+│       ├── __init__.py
+│       ├── conftest.py         # Shared fixtures
+│       ├── test_simple.py      # Infrastructure tests ✅
+│       ├── test_bansess.py     # BanSession tests
+│       ├── test_ratelimit.py   # RateLimit tests
+│       ├── test_preproc.py     # PreProcessor tests
+│       ├── test_respback.py    # ResponseBack tests
+│       ├── test_resprule.py    # ResponseRule tests
+│       ├── test_pipelinemgr.py # Manager tests ✅
+│       └── test_stages_integration.py  # Integration tests
+├── pytest.ini                  # Pytest config
+├── run_tests.sh               # Test runner
+└── TESTING_SUMMARY.md         # This file
+```
+
+## How to Use
+
+### Run Tests Locally
+```bash
+bash run_tests.sh
+```
+
+### Run Specific Test File
+```bash
+pytest tests/pipeline/test_simple.py -v
+```
+
+### Run with Coverage
+```bash
+pytest tests/pipeline/ --cov=pkg/pipeline --cov-report=html
+```
+
+### View Coverage Report
+```bash
+open htmlcov/index.html
+```
+
+## Conclusion
+
+This test suite provides:
+- ✅ Solid foundation for pipeline testing
+- ✅ Extensible architecture for adding new tests
+- ✅ CI/CD integration
+- ✅ Comprehensive documentation
+
+Next steps should focus on refactoring the pipeline module structure to eliminate circular dependencies, which will allow all tests to run successfully.

libs/dify_service_api/test.py

@@ -1,45 +0,0 @@
-from v1 import client  # type: ignore
-
-import asyncio
-
-import os
-import json
-
-
-class TestDifyClient:
-    async def test_chat_messages(self):
-        cln = client.AsyncDifyServiceClient(api_key=os.getenv('DIFY_API_KEY'), base_url=os.getenv('DIFY_BASE_URL'))
-
-        async for chunk in cln.chat_messages(inputs={}, query='调用工具查看现在几点？', user='test'):
-            print(json.dumps(chunk, ensure_ascii=False, indent=4))
-
-    async def test_upload_file(self):
-        cln = client.AsyncDifyServiceClient(api_key=os.getenv('DIFY_API_KEY'), base_url=os.getenv('DIFY_BASE_URL'))
-
-        file_bytes = open('img.png', 'rb').read()
-
-        print(type(file_bytes))
-
-        file = ('img2.png', file_bytes, 'image/png')
-
-        resp = await cln.upload_file(file=file, user='test')
-        print(json.dumps(resp, ensure_ascii=False, indent=4))
-
-    async def test_workflow_run(self):
-        cln = client.AsyncDifyServiceClient(api_key=os.getenv('DIFY_API_KEY'), base_url=os.getenv('DIFY_BASE_URL'))
-
-        # resp = await cln.workflow_run(inputs={}, user="test")
-        # # print(json.dumps(resp, ensure_ascii=False, indent=4))
-        # print(resp)
-        chunks = []
-
-        ignored_events = ['text_chunk']
-        async for chunk in cln.workflow_run(inputs={}, user='test'):
-            if chunk['event'] in ignored_events:
-                continue
-            chunks.append(chunk)
-        print(json.dumps(chunks, ensure_ascii=False, indent=4))
-
-
-if __name__ == '__main__':
-    asyncio.run(TestDifyClient().test_chat_messages())

libs/wechatpad_api/__init__.py

@@ -1,4 +0,0 @@
-from .client import WeChatPadClient
-
-
-__all__ = ['WeChatPadClient']

main.py

@@ -1,105 +1,3 @@
-import asyncio
-import argparse
-# LangBot 终端启动入口
-# 在此层级解决依赖项检查。
-# LangBot/main.py
+import langbot.__main__
 
-asciiart = r"""
- _                   ___      _   
-| |   __ _ _ _  __ _| _ ) ___| |_ 
-| |__/ _` | ' \/ _` | _ \/ _ \  _|
-|____\__,_|_||_\__, |___/\___/\__|
-               |___/              
-
-⭐️ Open Source 开源地址: https://github.com/RockChinQ/LangBot
-📖 Documentation 文档地址: https://docs.langbot.app
-"""
-
-
-async def main_entry(loop: asyncio.AbstractEventLoop):
-    parser = argparse.ArgumentParser(description='LangBot')
-    parser.add_argument('--skip-plugin-deps-check', action='store_true', help='跳过插件依赖项检查', default=False)
-    args = parser.parse_args()
-
-    print(asciiart)
-
-    import sys
-
-    # 检查依赖
-
-    from pkg.core.bootutils import deps
-
-    missing_deps = await deps.check_deps()
-
-    if missing_deps:
-        print('以下依赖包未安装，将自动安装，请完成后重启程序：')
-        print(
-            'These dependencies are missing, they will be installed automatically, please restart the program after completion:'
-        )
-        for dep in missing_deps:
-            print('-', dep)
-        await deps.install_deps(missing_deps)
-        print('已自动安装缺失的依赖包，请重启程序。')
-        print('The missing dependencies have been installed automatically, please restart the program.')
-        sys.exit(0)
-
-    # check plugin deps
-    if not args.skip_plugin_deps_check:
-        await deps.precheck_plugin_deps()
-
-    # # 检查pydantic版本，如果没有 pydantic.v1，则把 pydantic 映射为 v1
-    # import pydantic.version
-
-    # if pydantic.version.VERSION < '2.0':
-    #     import pydantic
-
-    #     sys.modules['pydantic.v1'] = pydantic
-
-    # 检查配置文件
-
-    from pkg.core.bootutils import files
-
-    generated_files = await files.generate_files()
-
-    if generated_files:
-        print('以下文件不存在，已自动生成：')
-        print('Following files do not exist and have been automatically generated:')
-        for file in generated_files:
-            print('-', file)
-
-    from pkg.core import boot
-
-    await boot.main(loop)
-
-
-if __name__ == '__main__':
-    import os
-    import sys
-
-    # 必须大于 3.10.1
-    if sys.version_info < (3, 10, 1):
-        print('需要 Python 3.10.1 及以上版本，当前 Python 版本为：', sys.version)
-        input('按任意键退出...')
-        print('Your Python version is not supported. Please exit the program by pressing any key.')
-        exit(1)
-
-    # Check if the current directory is the LangBot project root directory
-    invalid_pwd = False
-
-    if not os.path.exists('main.py'):
-        invalid_pwd = True
-    else:
-        with open('main.py', 'r', encoding='utf-8') as f:
-            content = f.read()
-            if 'LangBot/main.py' not in content:
-                invalid_pwd = True
-    if invalid_pwd:
-        print('请在 LangBot 项目根目录下以命令形式运行此程序。')
-        input('按任意键退出...')
-        print('Please run this program in the LangBot project root directory in command form.')
-        print('Press any key to exit...')
-        exit(1)
-
-    loop = asyncio.new_event_loop()
-
-    loop.run_until_complete(main_entry(loop))
+langbot.__main__.main()

pkg/api/http/controller/group.py

@@ -1,125 +0,0 @@
-from __future__ import annotations
-
-import abc
-import typing
-import enum
-import quart
-import traceback
-from quart.typing import RouteCallable
-
-from ....core import app
-
-
-preregistered_groups: list[type[RouterGroup]] = []
-"""RouterGroup 的预注册列表"""
-
-
-def group_class(name: str, path: str) -> None:
-    """注册一个 RouterGroup"""
-
-    def decorator(cls: typing.Type[RouterGroup]) -> typing.Type[RouterGroup]:
-        cls.name = name
-        cls.path = path
-        preregistered_groups.append(cls)
-        return cls
-
-    return decorator
-
-
-class AuthType(enum.Enum):
-    """认证类型"""
-
-    NONE = 'none'
-    USER_TOKEN = 'user-token'
-
-
-class RouterGroup(abc.ABC):
-    name: str
-
-    path: str
-
-    ap: app.Application
-
-    quart_app: quart.Quart
-
-    def __init__(self, ap: app.Application, quart_app: quart.Quart) -> None:
-        self.ap = ap
-        self.quart_app = quart_app
-
-    @abc.abstractmethod
-    async def initialize(self) -> None:
-        pass
-
-    def route(
-        self,
-        rule: str,
-        auth_type: AuthType = AuthType.USER_TOKEN,
-        **options: typing.Any,
-    ) -> typing.Callable[[RouteCallable], RouteCallable]:  # decorator
-        """注册一个路由"""
-
-        def decorator(f: RouteCallable) -> RouteCallable:
-            nonlocal rule
-            rule = self.path + rule
-
-            async def handler_error(*args, **kwargs):
-                if auth_type == AuthType.USER_TOKEN:
-                    # 从Authorization头中获取token
-                    token = quart.request.headers.get('Authorization', '').replace('Bearer ', '')
-
-                    if not token:
-                        return self.http_status(401, -1, '未提供有效的用户令牌')
-
-                    try:
-                        user_email = await self.ap.user_service.verify_jwt_token(token)
-
-                        # check if this account exists
-                        user = await self.ap.user_service.get_user_by_email(user_email)
-                        if not user:
-                            return self.http_status(401, -1, '用户不存在')
-
-                        # 检查f是否接受user_email参数
-                        if 'user_email' in f.__code__.co_varnames:
-                            kwargs['user_email'] = user_email
-                    except Exception as e:
-                        return self.http_status(401, -1, str(e))
-
-                try:
-                    return await f(*args, **kwargs)
-                except Exception:  # 自动 500
-                    traceback.print_exc()
-                    # return self.http_status(500, -2, str(e))
-                    return self.http_status(500, -2, 'internal server error')
-
-            new_f = handler_error
-            new_f.__name__ = (self.name + rule).replace('/', '__')
-            new_f.__doc__ = f.__doc__
-
-            self.quart_app.route(rule, **options)(new_f)
-            return f
-
-        return decorator
-
-    def success(self, data: typing.Any = None) -> quart.Response:
-        """返回一个 200 响应"""
-        return quart.jsonify(
-            {
-                'code': 0,
-                'msg': 'ok',
-                'data': data,
-            }
-        )
-
-    def fail(self, code: int, msg: str) -> quart.Response:
-        """返回一个异常响应"""
-
-        return quart.jsonify(
-            {
-                'code': code,
-                'msg': msg,
-            }
-        )
-
-    def http_status(self, status: int, code: int, msg: str) -> quart.Response:
-        """返回一个指定状态码的响应"""
-        return self.fail(code, msg), status

pkg/api/http/controller/groups/files.py

@@ -1,22 +0,0 @@
-from __future__ import annotations
-
-import quart
-import mimetypes
-
-from .. import group
-
-
-@group.group_class('files', '/api/v1/files')
-class FilesRouterGroup(group.RouterGroup):
-    async def initialize(self) -> None:
-        @self.route('/image/<image_key>', methods=['GET'], auth_type=group.AuthType.NONE)
-        async def _(image_key: str) -> quart.Response:
-            if not await self.ap.storage_mgr.storage_provider.exists(image_key):
-                return quart.Response(status=404)
-
-            image_bytes = await self.ap.storage_mgr.storage_provider.load(image_key)
-            mime_type = mimetypes.guess_type(image_key)[0]
-            if mime_type is None:
-                mime_type = 'image/jpeg'
-
-            return quart.Response(image_bytes, mimetype=mime_type)

pkg/api/http/controller/groups/pipelines/pipelines.py

@@ -1,44 +0,0 @@
-from __future__ import annotations
-
-import quart
-
-from ... import group
-
-
-@group.group_class('pipelines', '/api/v1/pipelines')
-class PipelinesRouterGroup(group.RouterGroup):
-    async def initialize(self) -> None:
-        @self.route('', methods=['GET', 'POST'])
-        async def _() -> str:
-            if quart.request.method == 'GET':
-                return self.success(data={'pipelines': await self.ap.pipeline_service.get_pipelines()})
-            elif quart.request.method == 'POST':
-                json_data = await quart.request.json
-
-                pipeline_uuid = await self.ap.pipeline_service.create_pipeline(json_data)
-
-                return self.success(data={'uuid': pipeline_uuid})
-
-        @self.route('/_/metadata', methods=['GET'])
-        async def _() -> str:
-            return self.success(data={'configs': await self.ap.pipeline_service.get_pipeline_metadata()})
-
-        @self.route('/<pipeline_uuid>', methods=['GET', 'PUT', 'DELETE'])
-        async def _(pipeline_uuid: str) -> str:
-            if quart.request.method == 'GET':
-                pipeline = await self.ap.pipeline_service.get_pipeline(pipeline_uuid)
-
-                if pipeline is None:
-                    return self.http_status(404, -1, 'pipeline not found')
-
-                return self.success(data={'pipeline': pipeline})
-            elif quart.request.method == 'PUT':
-                json_data = await quart.request.json
-
-                await self.ap.pipeline_service.update_pipeline(pipeline_uuid, json_data)
-
-                return self.success()
-            elif quart.request.method == 'DELETE':
-                await self.ap.pipeline_service.delete_pipeline(pipeline_uuid)
-
-                return self.success()

pkg/api/http/controller/groups/plugins.py

@@ -1,132 +0,0 @@
-from __future__ import annotations
-
-import base64
-import quart
-
-from .....core import taskmgr
-from .. import group
-from langbot_plugin.runtime.plugin.mgr import PluginInstallSource
-
-
-@group.group_class('plugins', '/api/v1/plugins')
-class PluginsRouterGroup(group.RouterGroup):
-    async def initialize(self) -> None:
-        @self.route('', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
-        async def _() -> str:
-            plugins = await self.ap.plugin_connector.list_plugins()
-
-            return self.success(data={'plugins': plugins})
-
-        @self.route(
-            '/<author>/<plugin_name>/upgrade',
-            methods=['POST'],
-            auth_type=group.AuthType.USER_TOKEN,
-        )
-        async def _(author: str, plugin_name: str) -> str:
-            ctx = taskmgr.TaskContext.new()
-            wrapper = self.ap.task_mgr.create_user_task(
-                self.ap.plugin_connector.upgrade_plugin(author, plugin_name, task_context=ctx),
-                kind='plugin-operation',
-                name=f'plugin-upgrade-{plugin_name}',
-                label=f'Upgrading plugin {plugin_name}',
-                context=ctx,
-            )
-            return self.success(data={'task_id': wrapper.id})
-
-        @self.route(
-            '/<author>/<plugin_name>',
-            methods=['GET', 'DELETE'],
-            auth_type=group.AuthType.USER_TOKEN,
-        )
-        async def _(author: str, plugin_name: str) -> str:
-            if quart.request.method == 'GET':
-                plugin = await self.ap.plugin_connector.get_plugin_info(author, plugin_name)
-                if plugin is None:
-                    return self.http_status(404, -1, 'plugin not found')
-                return self.success(data={'plugin': plugin})
-            elif quart.request.method == 'DELETE':
-                ctx = taskmgr.TaskContext.new()
-                wrapper = self.ap.task_mgr.create_user_task(
-                    self.ap.plugin_connector.delete_plugin(author, plugin_name, task_context=ctx),
-                    kind='plugin-operation',
-                    name=f'plugin-remove-{plugin_name}',
-                    label=f'Removing plugin {plugin_name}',
-                    context=ctx,
-                )
-
-                return self.success(data={'task_id': wrapper.id})
-
-        @self.route(
-            '/<author>/<plugin_name>/config',
-            methods=['GET', 'PUT'],
-            auth_type=group.AuthType.USER_TOKEN,
-        )
-        async def _(author: str, plugin_name: str) -> quart.Response:
-            plugin = await self.ap.plugin_connector.get_plugin_info(author, plugin_name)
-            if plugin is None:
-                return self.http_status(404, -1, 'plugin not found')
-
-            if quart.request.method == 'GET':
-                return self.success(data={'config': plugin['plugin_config']})
-            elif quart.request.method == 'PUT':
-                data = await quart.request.json
-
-                await self.ap.plugin_connector.set_plugin_config(author, plugin_name, data)
-
-                return self.success(data={})
-
-        @self.route('/install/github', methods=['POST'], auth_type=group.AuthType.USER_TOKEN)
-        async def _() -> str:
-            data = await quart.request.json
-
-            ctx = taskmgr.TaskContext.new()
-            short_source_str = data['source'][-8:]
-            wrapper = self.ap.task_mgr.create_user_task(
-                self.ap.plugin_mgr.install_plugin(data['source'], task_context=ctx),
-                kind='plugin-operation',
-                name='plugin-install-github',
-                label=f'Installing plugin from github ...{short_source_str}',
-                context=ctx,
-            )
-
-            return self.success(data={'task_id': wrapper.id})
-
-        @self.route('/install/marketplace', methods=['POST'], auth_type=group.AuthType.USER_TOKEN)
-        async def _() -> str:
-            data = await quart.request.json
-
-            ctx = taskmgr.TaskContext.new()
-            wrapper = self.ap.task_mgr.create_user_task(
-                self.ap.plugin_connector.install_plugin(PluginInstallSource.MARKETPLACE, data, task_context=ctx),
-                kind='plugin-operation',
-                name='plugin-install-marketplace',
-                label=f'Installing plugin from marketplace ...{data}',
-                context=ctx,
-            )
-
-            return self.success(data={'task_id': wrapper.id})
-
-        @self.route('/install/local', methods=['POST'], auth_type=group.AuthType.USER_TOKEN)
-        async def _() -> str:
-            file = (await quart.request.files).get('file')
-            if file is None:
-                return self.http_status(400, -1, 'file is required')
-
-            file_bytes = file.read()
-
-            file_base64 = base64.b64encode(file_bytes).decode('utf-8')
-
-            data = {
-                'plugin_file': file_base64,
-            }
-
-            ctx = taskmgr.TaskContext.new()
-            wrapper = self.ap.task_mgr.create_user_task(
-                self.ap.plugin_connector.install_plugin(PluginInstallSource.LOCAL, data, task_context=ctx),
-                kind='plugin-operation',
-                name='plugin-install-local',
-                label=f'Installing plugin from local ...{file.filename}',
-                context=ctx,
-            )
-
-            return self.success(data={'task_id': wrapper.id})

pkg/api/http/controller/groups/provider/models.py

@@ -1,46 +0,0 @@
-import quart
-
-from ... import group
-
-
-@group.group_class('models/llm', '/api/v1/provider/models/llm')
-class LLMModelsRouterGroup(group.RouterGroup):
-    async def initialize(self) -> None:
-        @self.route('', methods=['GET', 'POST'])
-        async def _() -> str:
-            if quart.request.method == 'GET':
-                return self.success(data={'models': await self.ap.model_service.get_llm_models()})
-            elif quart.request.method == 'POST':
-                json_data = await quart.request.json
-
-                model_uuid = await self.ap.model_service.create_llm_model(json_data)
-
-                return self.success(data={'uuid': model_uuid})
-
-        @self.route('/<model_uuid>', methods=['GET', 'PUT', 'DELETE'])
-        async def _(model_uuid: str) -> str:
-            if quart.request.method == 'GET':
-                model = await self.ap.model_service.get_llm_model(model_uuid)
-
-                if model is None:
-                    return self.http_status(404, -1, 'model not found')
-
-                return self.success(data={'model': model})
-            elif quart.request.method == 'PUT':
-                json_data = await quart.request.json
-
-                await self.ap.model_service.update_llm_model(model_uuid, json_data)
-
-                return self.success()
-            elif quart.request.method == 'DELETE':
-                await self.ap.model_service.delete_llm_model(model_uuid)
-
-                return self.success()
-
-        @self.route('/<model_uuid>/test', methods=['POST'])
-        async def _(model_uuid: str) -> str:
-            json_data = await quart.request.json
-
-            await self.ap.model_service.test_llm_model(model_uuid, json_data)
-
-            return self.success()

pkg/api/http/controller/groups/user.py

@@ -1,42 +0,0 @@
-import quart
-import argon2
-
-from .. import group
-
-
-@group.group_class('user', '/api/v1/user')
-class UserRouterGroup(group.RouterGroup):
-    async def initialize(self) -> None:
-        @self.route('/init', methods=['GET', 'POST'], auth_type=group.AuthType.NONE)
-        async def _() -> str:
-            if quart.request.method == 'GET':
-                return self.success(data={'initialized': await self.ap.user_service.is_initialized()})
-
-            if await self.ap.user_service.is_initialized():
-                return self.fail(1, '系统已初始化')
-
-            json_data = await quart.request.json
-
-            user_email = json_data['user']
-            password = json_data['password']
-
-            await self.ap.user_service.create_user(user_email, password)
-
-            return self.success()
-
-        @self.route('/auth', methods=['POST'], auth_type=group.AuthType.NONE)
-        async def _() -> str:
-            json_data = await quart.request.json
-
-            try:
-                token = await self.ap.user_service.authenticate(json_data['user'], json_data['password'])
-            except argon2.exceptions.VerifyMismatchError:
-                return self.fail(1, '用户名或密码错误')
-
-            return self.success(data={'token': token})
-
-        @self.route('/check-token', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
-        async def _(user_email: str) -> str:
-            token = await self.ap.user_service.generate_jwt_token(user_email)
-
-            return self.success(data={'token': token})

pkg/command/operators/cmd.py

@@ -1,44 +0,0 @@
-from __future__ import annotations
-
-import typing
-
-from .. import operator
-from langbot_plugin.api.entities.builtin.command import context as command_context, errors as command_errors
-
-
-@operator.operator_class(name='cmd', help='显示命令列表', usage='!cmd\n!cmd <命令名称>')
-class CmdOperator(operator.CommandOperator):
-    """命令列表"""
-
-    async def execute(
-        self, context: command_context.ExecuteContext
-    ) -> typing.AsyncGenerator[command_context.CommandReturn, None]:
-        """执行"""
-        if len(context.crt_params) == 0:
-            reply_str = '当前所有命令: \n\n'
-
-            for cmd in self.ap.cmd_mgr.cmd_list:
-                if cmd.parent_class is None:
-                    reply_str += f'{cmd.name}: {cmd.help}\n'
-
-            reply_str += '\n使用 !cmd <命令名称> 查看命令的详细帮助'
-
-            yield command_context.CommandReturn(text=reply_str.strip())
-
-        else:
-            cmd_name = context.crt_params[0]
-
-            cmd = None
-
-            for _cmd in self.ap.cmd_mgr.cmd_list:
-                if (cmd_name == _cmd.name or cmd_name in _cmd.alias) and (_cmd.parent_class is None):
-                    cmd = _cmd
-                    break
-
-            if cmd is None:
-                yield command_context.CommandReturn(error=command_errors.CommandNotFoundError(cmd_name))
-            else:
-                reply_str = f'{cmd.name}: {cmd.help}\n\n'
-                reply_str += f'使用方法: \n{cmd.usage}'
-
-                yield command_context.CommandReturn(text=reply_str.strip())

pkg/command/operators/delc.py

@@ -1,48 +0,0 @@
-from __future__ import annotations
-
-import typing
-
-from .. import operator
-from langbot_plugin.api.entities.builtin.command import context as command_context, errors as command_errors
-
-
-@operator.operator_class(name='del', help='删除当前会话的历史记录', usage='!del <序号>\n!del all')
-class DelOperator(operator.CommandOperator):
-    async def execute(
-        self, context: command_context.ExecuteContext
-    ) -> typing.AsyncGenerator[command_context.CommandReturn, None]:
-        if context.session.conversations:
-            delete_index = 0
-            if len(context.crt_params) > 0:
-                try:
-                    delete_index = int(context.crt_params[0])
-                except Exception:
-                    yield command_context.CommandReturn(error=command_errors.CommandOperationError('索引必须是整数'))
-                    return
-
-            if delete_index < 0 or delete_index >= len(context.session.conversations):
-                yield command_context.CommandReturn(error=command_errors.CommandOperationError('索引超出范围'))
-                return
-
-            # 倒序
-            to_delete_index = len(context.session.conversations) - 1 - delete_index
-
-            if context.session.conversations[to_delete_index] == context.session.using_conversation:
-                context.session.using_conversation = None
-
-            del context.session.conversations[to_delete_index]
-
-            yield command_context.CommandReturn(text=f'已删除对话: {delete_index}')
-        else:
-            yield command_context.CommandReturn(error=command_errors.CommandOperationError('当前没有对话'))
-
-
-@operator.operator_class(name='all', help='删除此会话的所有历史记录', parent_class=DelOperator)
-class DelAllOperator(operator.CommandOperator):
-    async def execute(
-        self, context: command_context.ExecuteContext
-    ) -> typing.AsyncGenerator[command_context.CommandReturn, None]:
-        context.session.conversations = []
-        context.session.using_conversation = None
-
-        yield command_context.CommandReturn(text='已删除所有对话')

pkg/command/operators/func.py

@@ -1,27 +0,0 @@
-from __future__ import annotations
-from typing import AsyncGenerator
-
-from .. import operator
-from langbot_plugin.api.entities.builtin.command import context as command_context
-
-
-@operator.operator_class(name='func', help='查看所有已注册的内容函数', usage='!func')
-class FuncOperator(operator.CommandOperator):
-    async def execute(
-        self, context: command_context.ExecuteContext
-    ) -> AsyncGenerator[command_context.CommandReturn, None]:
-        reply_str = '当前已启用的内容函数: \n\n'
-
-        index = 1
-
-        all_functions = await self.ap.tool_mgr.get_all_tools()
-
-        for func in all_functions:
-            reply_str += '{}. {}:\n{}\n\n'.format(
-                index,
-                func.name,
-                func.description,
-            )
-            index += 1
-
-        yield command_context.CommandReturn(text=reply_str)

pkg/command/operators/help.py

@@ -1,18 +0,0 @@
-from __future__ import annotations
-
-import typing
-
-from .. import operator
-from langbot_plugin.api.entities.builtin.command import context as command_context
-
-
-@operator.operator_class(name='help', help='显示帮助', usage='!help\n!help <命令名称>')
-class HelpOperator(operator.CommandOperator):
-    async def execute(
-        self, context: command_context.ExecuteContext
-    ) -> typing.AsyncGenerator[command_context.CommandReturn, None]:
-        help = 'LangBot - 大语言模型原生即时通信机器人平台\n链接：https://langbot.app'
-
-        help += '\n发送命令 !cmd 可查看命令列表'
-
-        yield command_context.CommandReturn(text=help)

pkg/command/operators/last.py

@@ -1,33 +0,0 @@
-from __future__ import annotations
-
-import typing
-
-
-from .. import operator
-from langbot_plugin.api.entities.builtin.command import context as command_context, errors as command_errors
-
-
-@operator.operator_class(name='last', help='切换到前一个对话', usage='!last')
-class LastOperator(operator.CommandOperator):
-    async def execute(
-        self, context: command_context.ExecuteContext
-    ) -> typing.AsyncGenerator[command_context.CommandReturn, None]:
-        if context.session.conversations:
-            # 找到当前会话的上一个会话
-            for index in range(len(context.session.conversations) - 1, -1, -1):
-                if context.session.conversations[index] == context.session.using_conversation:
-                    if index == 0:
-                        yield command_context.CommandReturn(
-                            error=command_errors.CommandOperationError('已经是第一个对话了')
-                        )
-                        return
-                    else:
-                        context.session.using_conversation = context.session.conversations[index - 1]
-                        time_str = context.session.using_conversation.create_time.strftime('%Y-%m-%d %H:%M:%S')
-
-                        yield command_context.CommandReturn(
-                            text=f'已切换到上一个对话: {index} {time_str}: {context.session.using_conversation.messages[0].readable_str()}'
-                        )
-                        return
-        else:
-            yield command_context.CommandReturn(error=command_errors.CommandOperationError('当前没有对话'))

pkg/command/operators/list.py

@@ -1,51 +0,0 @@
-from __future__ import annotations
-
-import typing
-
-from .. import operator
-from langbot_plugin.api.entities.builtin.command import context as command_context, errors as command_errors
-
-
-@operator.operator_class(name='list', help='列出此会话中的所有历史对话', usage='!list\n!list <页码>')
-class ListOperator(operator.CommandOperator):
-    async def execute(
-        self, context: command_context.ExecuteContext
-    ) -> typing.AsyncGenerator[command_context.CommandReturn, None]:
-        page = 0
-
-        if len(context.crt_params) > 0:
-            try:
-                page = int(context.crt_params[0] - 1)
-            except Exception:
-                yield command_context.CommandReturn(error=command_errors.CommandOperationError('页码应为整数'))
-                return
-
-        record_per_page = 10
-
-        content = ''
-
-        index = 0
-
-        using_conv_index = 0
-
-        for conv in context.session.conversations[::-1]:
-            time_str = conv.create_time.strftime('%Y-%m-%d %H:%M:%S')
-
-            if conv == context.session.using_conversation:
-                using_conv_index = index
-
-            if index >= page * record_per_page and index < (page + 1) * record_per_page:
-                content += (
-                    f'{index} {time_str}: {conv.messages[0].readable_str() if len(conv.messages) > 0 else "无内容"}\n'
-                )
-            index += 1
-
-        if content == '':
-            content = '无'
-        else:
-            if context.session.using_conversation is None:
-                content += '\n当前处于新会话'
-            else:
-                content += f'\n当前会话: {using_conv_index} {context.session.using_conversation.create_time.strftime("%Y-%m-%d %H:%M:%S")}: {context.session.using_conversation.messages[0].readable_str() if len(context.session.using_conversation.messages) > 0 else "无内容"}'
-
-        yield command_context.CommandReturn(text=f'第 {page + 1} 页 (时间倒序):\n{content}')

pkg/command/operators/next.py

@@ -1,32 +0,0 @@
-from __future__ import annotations
-
-import typing
-
-from .. import operator
-from langbot_plugin.api.entities.builtin.command import context as command_context, errors as command_errors
-
-
-@operator.operator_class(name='next', help='切换到后一个对话', usage='!next')
-class NextOperator(operator.CommandOperator):
-    async def execute(
-        self, context: command_context.ExecuteContext
-    ) -> typing.AsyncGenerator[command_context.CommandReturn, None]:
-        if context.session.conversations:
-            # 找到当前会话的下一个会话
-            for index in range(len(context.session.conversations)):
-                if context.session.conversations[index] == context.session.using_conversation:
-                    if index == len(context.session.conversations) - 1:
-                        yield command_context.CommandReturn(
-                            error=command_errors.CommandOperationError('已经是最后一个对话了')
-                        )
-                        return
-                    else:
-                        context.session.using_conversation = context.session.conversations[index + 1]
-                        time_str = context.session.using_conversation.create_time.strftime('%Y-%m-%d %H:%M:%S')
-
-                        yield command_context.CommandReturn(
-                            text=f'已切换到后一个对话: {index} {time_str}: {context.session.using_conversation.messages[0].content}'
-                        )
-                        return
-        else:
-            yield command_context.CommandReturn(error=command_errors.CommandOperationError('当前没有对话'))

pkg/command/operators/plugin.py

@@ -1,171 +0,0 @@
-from __future__ import annotations
-import typing
-import traceback
-
-from .. import operator
-from langbot_plugin.api.entities.builtin.command import context as command_context, errors as command_errors
-
-
-@operator.operator_class(
-    name='plugin',
-    help='插件操作',
-    usage='!plugin\n!plugin get <插件仓库地址>\n!plugin update\n!plugin del <插件名>\n!plugin on <插件名>\n!plugin off <插件名>',
-)
-class PluginOperator(operator.CommandOperator):
-    async def execute(
-        self, context: command_context.ExecuteContext
-    ) -> typing.AsyncGenerator[command_context.CommandReturn, None]:
-        plugin_list = self.ap.plugin_mgr.plugins()
-        reply_str = '所有插件({}):\n'.format(len(plugin_list))
-        idx = 0
-        for plugin in plugin_list:
-            reply_str += '\n#{} {} {}\n{}\nv{}\n作者: {}\n'.format(
-                (idx + 1),
-                plugin.plugin_name,
-                '[已禁用]' if not plugin.enabled else '',
-                plugin.plugin_description,
-                plugin.plugin_version,
-                plugin.plugin_author,
-            )
-
-            idx += 1
-
-        yield command_context.CommandReturn(text=reply_str)
-
-
-@operator.operator_class(name='get', help='安装插件', privilege=2, parent_class=PluginOperator)
-class PluginGetOperator(operator.CommandOperator):
-    async def execute(
-        self, context: command_context.ExecuteContext
-    ) -> typing.AsyncGenerator[command_context.CommandReturn, None]:
-        if len(context.crt_params) == 0:
-            yield command_context.CommandReturn(error=command_errors.ParamNotEnoughError('请提供插件仓库地址'))
-        else:
-            repo = context.crt_params[0]
-
-            yield command_context.CommandReturn(text='正在安装插件...')
-
-            try:
-                await self.ap.plugin_mgr.install_plugin(repo)
-                yield command_context.CommandReturn(text='插件安装成功，请重启程序以加载插件')
-            except Exception as e:
-                traceback.print_exc()
-                yield command_context.CommandReturn(error=command_errors.CommandError('插件安装失败: ' + str(e)))
-
-
-@operator.operator_class(name='update', help='更新插件', privilege=2, parent_class=PluginOperator)
-class PluginUpdateOperator(operator.CommandOperator):
-    async def execute(
-        self, context: command_context.ExecuteContext
-    ) -> typing.AsyncGenerator[command_context.CommandReturn, None]:
-        if len(context.crt_params) == 0:
-            yield command_context.CommandReturn(error=command_errors.ParamNotEnoughError('请提供插件名称'))
-        else:
-            plugin_name = context.crt_params[0]
-
-            try:
-                plugin_container = self.ap.plugin_mgr.get_plugin_by_name(plugin_name)
-
-                if plugin_container is not None:
-                    yield command_context.CommandReturn(text='正在更新插件...')
-                    await self.ap.plugin_mgr.update_plugin(plugin_name)
-                    yield command_context.CommandReturn(text='插件更新成功，请重启程序以加载插件')
-                else:
-                    yield command_context.CommandReturn(error=command_errors.CommandError('插件更新失败: 未找到插件'))
-            except Exception as e:
-                traceback.print_exc()
-                yield command_context.CommandReturn(error=command_errors.CommandError('插件更新失败: ' + str(e)))
-
-
-@operator.operator_class(name='all', help='更新所有插件', privilege=2, parent_class=PluginUpdateOperator)
-class PluginUpdateAllOperator(operator.CommandOperator):
-    async def execute(
-        self, context: command_context.ExecuteContext
-    ) -> typing.AsyncGenerator[command_context.CommandReturn, None]:
-        try:
-            plugins = [p.plugin_name for p in self.ap.plugin_mgr.plugins()]
-
-            if plugins:
-                yield command_context.CommandReturn(text='正在更新插件...')
-                updated = []
-                try:
-                    for plugin_name in plugins:
-                        await self.ap.plugin_mgr.update_plugin(plugin_name)
-                        updated.append(plugin_name)
-                except Exception as e:
-                    traceback.print_exc()
-                    yield command_context.CommandReturn(error=command_errors.CommandError('插件更新失败: ' + str(e)))
-                yield command_context.CommandReturn(text='已更新插件: {}'.format(', '.join(updated)))
-            else:
-                yield command_context.CommandReturn(text='没有可更新的插件')
-        except Exception as e:
-            traceback.print_exc()
-            yield command_context.CommandReturn(error=command_errors.CommandError('插件更新失败: ' + str(e)))
-
-
-@operator.operator_class(name='del', help='删除插件', privilege=2, parent_class=PluginOperator)
-class PluginDelOperator(operator.CommandOperator):
-    async def execute(
-        self, context: command_context.ExecuteContext
-    ) -> typing.AsyncGenerator[command_context.CommandReturn, None]:
-        if len(context.crt_params) == 0:
-            yield command_context.CommandReturn(error=command_errors.ParamNotEnoughError('请提供插件名称'))
-        else:
-            plugin_name = context.crt_params[0]
-
-            try:
-                plugin_container = self.ap.plugin_mgr.get_plugin_by_name(plugin_name)
-
-                if plugin_container is not None:
-                    yield command_context.CommandReturn(text='正在删除插件...')
-                    await self.ap.plugin_mgr.uninstall_plugin(plugin_name)
-                    yield command_context.CommandReturn(text='插件删除成功，请重启程序以加载插件')
-                else:
-                    yield command_context.CommandReturn(error=command_errors.CommandError('插件删除失败: 未找到插件'))
-            except Exception as e:
-                traceback.print_exc()
-                yield command_context.CommandReturn(error=command_errors.CommandError('插件删除失败: ' + str(e)))
-
-
-@operator.operator_class(name='on', help='启用插件', privilege=2, parent_class=PluginOperator)
-class PluginEnableOperator(operator.CommandOperator):
-    async def execute(
-        self, context: command_context.ExecuteContext
-    ) -> typing.AsyncGenerator[command_context.CommandReturn, None]:
-        if len(context.crt_params) == 0:
-            yield command_context.CommandReturn(error=command_errors.ParamNotEnoughError('请提供插件名称'))
-        else:
-            plugin_name = context.crt_params[0]
-
-            try:
-                if await self.ap.plugin_mgr.update_plugin_switch(plugin_name, True):
-                    yield command_context.CommandReturn(text='已启用插件: {}'.format(plugin_name))
-                else:
-                    yield command_context.CommandReturn(
-                        error=command_errors.CommandError('插件状态修改失败: 未找到插件 {}'.format(plugin_name))
-                    )
-            except Exception as e:
-                traceback.print_exc()
-                yield command_context.CommandReturn(error=command_errors.CommandError('插件状态修改失败: ' + str(e)))
-
-
-@operator.operator_class(name='off', help='禁用插件', privilege=2, parent_class=PluginOperator)
-class PluginDisableOperator(operator.CommandOperator):
-    async def execute(
-        self, context: command_context.ExecuteContext
-    ) -> typing.AsyncGenerator[command_context.CommandReturn, None]:
-        if len(context.crt_params) == 0:
-            yield command_context.CommandReturn(error=command_errors.ParamNotEnoughError('请提供插件名称'))
-        else:
-            plugin_name = context.crt_params[0]
-
-            try:
-                if await self.ap.plugin_mgr.update_plugin_switch(plugin_name, False):
-                    yield command_context.CommandReturn(text='已禁用插件: {}'.format(plugin_name))
-                else:
-                    yield command_context.CommandReturn(
-                        error=command_errors.CommandError('插件状态修改失败: 未找到插件 {}'.format(plugin_name))
-                    )
-            except Exception as e:
-                traceback.print_exc()
-                yield command_context.CommandReturn(error=command_errors.CommandError('插件状态修改失败: ' + str(e)))

pkg/command/operators/prompt.py

@@ -1,23 +0,0 @@
-from __future__ import annotations
-
-import typing
-
-from .. import operator
-from langbot_plugin.api.entities.builtin.command import context as command_context, errors as command_errors
-
-
-@operator.operator_class(name='prompt', help='查看当前对话的前文', usage='!prompt')
-class PromptOperator(operator.CommandOperator):
-    async def execute(
-        self, context: command_context.ExecuteContext
-    ) -> typing.AsyncGenerator[command_context.CommandReturn, None]:
-        """执行"""
-        if context.session.using_conversation is None:
-            yield command_context.CommandReturn(error=command_errors.CommandOperationError('当前没有对话'))
-        else:
-            reply_str = '当前对话所有内容:\n\n'
-
-            for msg in context.session.using_conversation.messages:
-                reply_str += f'{msg.role}: {msg.content}\n'
-
-            yield command_context.CommandReturn(text=reply_str)

pkg/command/operators/resend.py

@@ -1,29 +0,0 @@
-from __future__ import annotations
-
-import typing
-
-from .. import operator
-from langbot_plugin.api.entities.builtin.command import context as command_context, errors as command_errors
-
-
-@operator.operator_class(name='resend', help='重发当前会话的最后一条消息', usage='!resend')
-class ResendOperator(operator.CommandOperator):
-    async def execute(
-        self, context: command_context.ExecuteContext
-    ) -> typing.AsyncGenerator[command_context.CommandReturn, None]:
-        # 回滚到最后一条用户message前
-        if context.session.using_conversation is None:
-            yield command_context.CommandReturn(error=command_errors.CommandError('当前没有对话'))
-        else:
-            conv_msg = context.session.using_conversation.messages
-
-            # 倒序一直删到最后一条用户message
-            while len(conv_msg) > 0 and conv_msg[-1].role != 'user':
-                conv_msg.pop()
-
-            if len(conv_msg) > 0:
-                # 删除最后一条用户message
-                conv_msg.pop()
-
-            # 不重发了，提示用户已删除就行了
-            yield command_context.CommandReturn(text='已删除最后一次请求记录')

pkg/command/operators/reset.py

@@ -1,17 +0,0 @@
-from __future__ import annotations
-
-import typing
-
-from .. import operator
-from langbot_plugin.api.entities.builtin.command import context as command_context
-
-
-@operator.operator_class(name='reset', help='重置当前会话', usage='!reset')
-class ResetOperator(operator.CommandOperator):
-    async def execute(
-        self, context: command_context.ExecuteContext
-    ) -> typing.AsyncGenerator[command_context.CommandReturn, None]:
-        """执行"""
-        context.session.using_conversation = None
-
-        yield command_context.CommandReturn(text='已重置当前会话')

pkg/command/operators/version.py

@@ -1,22 +0,0 @@
-from __future__ import annotations
-
-import typing
-
-from .. import operator
-from langbot_plugin.api.entities.builtin.command import context as command_context
-
-
-@operator.operator_class(name='version', help='显示版本信息', usage='!version')
-class VersionCommand(operator.CommandOperator):
-    async def execute(
-        self, context: command_context.ExecuteContext
-    ) -> typing.AsyncGenerator[command_context.CommandReturn, None]:
-        reply_str = f'当前版本: \n{self.ap.ver_mgr.get_current_version()}'
-
-        try:
-            if await self.ap.ver_mgr.is_new_version_available():
-                reply_str += '\n\n有新版本可用。'
-        except Exception:
-            pass
-
-        yield command_context.CommandReturn(text=reply_str.strip())

pkg/core/stages/load_config.py

@@ -1,79 +0,0 @@
-from __future__ import annotations
-
-import os
-
-from .. import stage, app
-from ..bootutils import config
-
-
-@stage.stage_class('LoadConfigStage')
-class LoadConfigStage(stage.BootingStage):
-    """加载配置文件阶段"""
-
-    async def run(self, ap: app.Application):
-        """启动"""
-
-        # ======= deprecated =======
-        if os.path.exists('data/config/command.json'):
-            ap.command_cfg = await config.load_json_config(
-                'data/config/command.json',
-                'templates/legacy/command.json',
-                completion=False,
-            )
-
-        if os.path.exists('data/config/pipeline.json'):
-            ap.pipeline_cfg = await config.load_json_config(
-                'data/config/pipeline.json',
-                'templates/legacy/pipeline.json',
-                completion=False,
-            )
-
-        if os.path.exists('data/config/platform.json'):
-            ap.platform_cfg = await config.load_json_config(
-                'data/config/platform.json',
-                'templates/legacy/platform.json',
-                completion=False,
-            )
-
-        if os.path.exists('data/config/provider.json'):
-            ap.provider_cfg = await config.load_json_config(
-                'data/config/provider.json',
-                'templates/legacy/provider.json',
-                completion=False,
-            )
-
-        if os.path.exists('data/config/system.json'):
-            ap.system_cfg = await config.load_json_config(
-                'data/config/system.json',
-                'templates/legacy/system.json',
-                completion=False,
-            )
-
-        # ======= deprecated =======
-
-        ap.instance_config = await config.load_yaml_config(
-            'data/config.yaml', 'templates/config.yaml', completion=False
-        )
-        await ap.instance_config.dump_config()
-
-        ap.sensitive_meta = await config.load_json_config(
-            'data/metadata/sensitive-words.json',
-            'templates/metadata/sensitive-words.json',
-        )
-        await ap.sensitive_meta.dump_config()
-
-        ap.pipeline_config_meta_trigger = await config.load_yaml_config(
-            'templates/metadata/pipeline/trigger.yaml',
-            'templates/metadata/pipeline/trigger.yaml',
-        )
-        ap.pipeline_config_meta_safety = await config.load_yaml_config(
-            'templates/metadata/pipeline/safety.yaml',
-            'templates/metadata/pipeline/safety.yaml',
-        )
-        ap.pipeline_config_meta_ai = await config.load_yaml_config(
-            'templates/metadata/pipeline/ai.yaml', 'templates/metadata/pipeline/ai.yaml'
-        )
-        ap.pipeline_config_meta_output = await config.load_yaml_config(
-            'templates/metadata/pipeline/output.yaml',
-            'templates/metadata/pipeline/output.yaml',
-        )

pkg/persistence/databases/sqlite.py

@@ -1,14 +0,0 @@
-from __future__ import annotations
-
-import sqlalchemy.ext.asyncio as sqlalchemy_asyncio
-
-from .. import database
-
-
-@database.manager_class('sqlite')
-class SQLiteDatabaseManager(database.BaseDatabaseManager):
-    """SQLite 数据库管理类"""
-
-    async def initialize(self) -> None:
-        sqlite_path = 'data/langbot.db'
-        self.engine = sqlalchemy_asyncio.create_async_engine(f'sqlite+aiosqlite:///{sqlite_path}')

pkg/pipeline/resprule/rules/atbot.py

@@ -1,32 +0,0 @@
-from __future__ import annotations
-
-
-from .. import rule as rule_model
-from .. import entities
-import langbot_plugin.api.entities.builtin.platform.message as platform_message
-import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query
-
-
-@rule_model.rule_class('at-bot')
-class AtBotRule(rule_model.GroupRespondRule):
-    async def match(
-        self,
-        message_text: str,
-        message_chain: platform_message.MessageChain,
-        rule_dict: dict,
-        query: pipeline_query.Query,
-    ) -> entities.RuleJudgeResult:
-        if message_chain.has(platform_message.At(query.adapter.bot_account_id)) and rule_dict['at']:
-            message_chain.remove(platform_message.At(query.adapter.bot_account_id))
-
-            if message_chain.has(
-                platform_message.At(query.adapter.bot_account_id)
-            ):  # 回复消息时会at两次，检查并删除重复的
-                message_chain.remove(platform_message.At(query.adapter.bot_account_id))
-
-            return entities.RuleJudgeResult(
-                matching=True,
-                replacement=message_chain,
-            )
-
-        return entities.RuleJudgeResult(matching=False, replacement=message_chain)

pkg/platform/sources/discord.py

@@ -1,255 +0,0 @@
-from __future__ import annotations
-
-import discord
-
-import typing
-import re
-import base64
-import uuid
-import os
-import datetime
-
-import aiohttp
-import pydantic
-
-import langbot_plugin.api.definition.abstract.platform.adapter as abstract_platform_adapter
-import langbot_plugin.api.entities.builtin.platform.message as platform_message
-import langbot_plugin.api.entities.builtin.platform.events as platform_events
-import langbot_plugin.api.entities.builtin.platform.entities as platform_entities
-import langbot_plugin.api.definition.abstract.platform.event_logger as abstract_platform_logger
-
-
-class DiscordMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
-    @staticmethod
-    async def yiri2target(
-        message_chain: platform_message.MessageChain,
-    ) -> typing.Tuple[str, typing.List[discord.File]]:
-        for ele in message_chain:
-            if isinstance(ele, platform_message.At):
-                message_chain.remove(ele)
-                break
-
-        text_string = ''
-        image_files = []
-
-        for ele in message_chain:
-            if isinstance(ele, platform_message.Image):
-                image_bytes = None
-
-                if ele.base64:
-                    image_bytes = base64.b64decode(ele.base64)
-                elif ele.url:
-                    async with aiohttp.ClientSession() as session:
-                        async with session.get(ele.url) as response:
-                            image_bytes = await response.read()
-                elif ele.path:
-                    with open(ele.path, 'rb') as f:
-                        image_bytes = f.read()
-
-                image_files.append(discord.File(fp=image_bytes, filename=f'{uuid.uuid4()}.png'))
-            elif isinstance(ele, platform_message.Plain):
-                text_string += ele.text
-            elif isinstance(ele, platform_message.Forward):
-                for node in ele.node_list:
-                    (
-                        text_string,
-                        image_files,
-                    ) = await DiscordMessageConverter.yiri2target(node.message_chain)
-                    text_string += text_string
-                    image_files.extend(image_files)
-
-        return text_string, image_files
-
-    @staticmethod
-    async def target2yiri(message: discord.Message) -> platform_message.MessageChain:
-        lb_msg_list = []
-
-        msg_create_time = datetime.datetime.fromtimestamp(int(message.created_at.timestamp()))
-
-        lb_msg_list.append(platform_message.Source(id=message.id, time=msg_create_time))
-
-        element_list = []
-
-        def text_element_recur(
-            text_ele: str,
-        ) -> list[platform_message.MessageComponent]:
-            if text_ele == '':
-                return []
-
-            # <@1234567890>
-            # @everyone
-            # @here
-            at_pattern = re.compile(r'(@everyone|@here|<@[\d]+>)')
-            at_matches = at_pattern.findall(text_ele)
-
-            if len(at_matches) > 0:
-                mid_at = at_matches[0]
-
-                text_split = text_ele.split(mid_at)
-
-                mid_at_component = []
-
-                if mid_at == '@everyone' or mid_at == '@here':
-                    mid_at_component.append(platform_message.AtAll())
-                else:
-                    mid_at_component.append(platform_message.At(target=mid_at[2:-1]))
-
-                return text_element_recur(text_split[0]) + mid_at_component + text_element_recur(text_split[1])
-            else:
-                return [platform_message.Plain(text=text_ele)]
-
-        element_list.extend(text_element_recur(message.content))
-
-        # attachments
-        for attachment in message.attachments:
-            async with aiohttp.ClientSession(trust_env=True) as session:
-                async with session.get(attachment.url) as response:
-                    image_data = await response.read()
-                    image_base64 = base64.b64encode(image_data).decode('utf-8')
-                    image_format = response.headers['Content-Type']
-                    element_list.append(platform_message.Image(base64=f'data:{image_format};base64,{image_base64}'))
-
-        return platform_message.MessageChain(element_list)
-
-
-class DiscordEventConverter(abstract_platform_adapter.AbstractEventConverter):
-    @staticmethod
-    async def yiri2target(event: platform_events.Event) -> discord.Message:
-        pass
-
-    @staticmethod
-    async def target2yiri(event: discord.Message) -> platform_events.Event:
-        message_chain = await DiscordMessageConverter.target2yiri(event)
-
-        if isinstance(event.channel, discord.DMChannel):
-            return platform_events.FriendMessage(
-                sender=platform_entities.Friend(
-                    id=event.author.id,
-                    nickname=event.author.name,
-                    remark=event.channel.id,
-                ),
-                message_chain=message_chain,
-                time=event.created_at.timestamp(),
-                source_platform_object=event,
-            )
-        elif isinstance(event.channel, discord.TextChannel):
-            return platform_events.GroupMessage(
-                sender=platform_entities.GroupMember(
-                    id=event.author.id,
-                    member_name=event.author.name,
-                    permission=platform_entities.Permission.Member,
-                    group=platform_entities.Group(
-                        id=event.channel.id,
-                        name=event.channel.name,
-                        permission=platform_entities.Permission.Member,
-                    ),
-                    special_title='',
-                    join_timestamp=0,
-                    last_speak_timestamp=0,
-                    mute_time_remaining=0,
-                ),
-                message_chain=message_chain,
-                time=event.created_at.timestamp(),
-                source_platform_object=event,
-            )
-
-
-class DiscordAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
-    bot: discord.Client = pydantic.Field(exclude=True)
-
-    message_converter: DiscordMessageConverter = DiscordMessageConverter()
-    event_converter: DiscordEventConverter = DiscordEventConverter()
-
-    listeners: typing.Dict[
-        typing.Type[platform_events.Event],
-        typing.Callable[[platform_events.Event, abstract_platform_adapter.AbstractMessagePlatformAdapter], None],
-    ] = {}
-
-    def __init__(self, config: dict, logger: abstract_platform_logger.AbstractEventLogger):
-        bot_account_id = config['client_id']
-
-        listeners = {}
-
-        adapter_self = self
-
-        class MyClient(discord.Client):
-            async def on_message(self: discord.Client, message: discord.Message):
-                if message.author.id == self.user.id or message.author.bot:
-                    return
-
-                lb_event = await adapter_self.event_converter.target2yiri(message)
-                await adapter_self.listeners[type(lb_event)](lb_event, adapter_self)
-
-        intents = discord.Intents.default()
-        intents.message_content = True
-
-        args = {}
-
-        if os.getenv('http_proxy'):
-            args['proxy'] = os.getenv('http_proxy')
-
-        bot = MyClient(intents=intents, **args)
-
-        super().__init__(
-            config=config,
-            logger=logger,
-            bot_account_id=bot_account_id,
-            listeners=listeners,
-            bot=bot,
-        )
-
-    async def send_message(self, target_type: str, target_id: str, message: platform_message.MessageChain):
-        pass
-
-    async def reply_message(
-        self,
-        message_source: platform_events.MessageEvent,
-        message: platform_message.MessageChain,
-        quote_origin: bool = False,
-    ):
-        msg_to_send, image_files = await self.message_converter.yiri2target(message)
-        assert isinstance(message_source.source_platform_object, discord.Message)
-
-        args = {
-            'content': msg_to_send,
-        }
-
-        if len(image_files) > 0:
-            args['files'] = image_files
-
-        if quote_origin:
-            args['reference'] = message_source.source_platform_object
-
-        if message.has(platform_message.At):
-            args['mention_author'] = True
-
-        await message_source.source_platform_object.channel.send(**args)
-
-    async def is_muted(self, group_id: int) -> bool:
-        return False
-
-    def register_listener(
-        self,
-        event_type: typing.Type[platform_events.Event],
-        callback: typing.Callable[
-            [platform_events.Event, abstract_platform_adapter.AbstractMessagePlatformAdapter], None
-        ],
-    ):
-        self.listeners[event_type] = callback
-
-    def unregister_listener(
-        self,
-        event_type: typing.Type[platform_events.Event],
-        callback: typing.Callable[
-            [platform_events.Event, abstract_platform_adapter.AbstractMessagePlatformAdapter], None
-        ],
-    ):
-        self.listeners.pop(event_type)
-
-    async def run_async(self):
-        async with self.bot:
-            await self.bot.start(self.config['token'], reconnect=True)
-
-    async def kill(self) -> bool:
-        await self.bot.close()
-        return True

pkg/plugin/connector.py

@@ -1,194 +0,0 @@
-# For connect to plugin runtime.
-from __future__ import annotations
-
-import asyncio
-from typing import Any
-import typing
-import os
-import sys
-
-from ..core import app
-from . import handler
-from ..utils import platform
-from langbot_plugin.runtime.io.controllers.stdio import client as stdio_client_controller
-from langbot_plugin.runtime.io.controllers.ws import client as ws_client_controller
-from langbot_plugin.api.entities import events
-from langbot_plugin.api.entities import context
-import langbot_plugin.runtime.io.connection as base_connection
-from langbot_plugin.api.definition.components.manifest import ComponentManifest
-from langbot_plugin.api.entities.builtin.command import context as command_context
-from langbot_plugin.runtime.plugin.mgr import PluginInstallSource
-from ..core import taskmgr
-
-
-class PluginRuntimeConnector:
-    """Plugin runtime connector"""
-
-    ap: app.Application
-
-    handler: handler.RuntimeConnectionHandler
-
-    handler_task: asyncio.Task
-
-    stdio_client_controller: stdio_client_controller.StdioClientController
-
-    ctrl: stdio_client_controller.StdioClientController | ws_client_controller.WebSocketClientController
-
-    runtime_disconnect_callback: typing.Callable[
-        [PluginRuntimeConnector], typing.Coroutine[typing.Any, typing.Any, None]
-    ]
-
-    def __init__(
-        self,
-        ap: app.Application,
-        runtime_disconnect_callback: typing.Callable[
-            [PluginRuntimeConnector], typing.Coroutine[typing.Any, typing.Any, None]
-        ],
-    ):
-        self.ap = ap
-        self.runtime_disconnect_callback = runtime_disconnect_callback
-
-    async def initialize(self):
-        async def new_connection_callback(connection: base_connection.Connection):
-            async def disconnect_callback(rchandler: handler.RuntimeConnectionHandler) -> bool:
-                if platform.get_platform() == 'docker':
-                    self.ap.logger.error('Disconnected from plugin runtime, trying to reconnect...')
-                    await self.runtime_disconnect_callback(self)
-                    return False
-                else:
-                    self.ap.logger.error(
-                        'Disconnected from plugin runtime, cannot automatically reconnect while LangBot connects to plugin runtime via stdio, please restart LangBot.'
-                    )
-                    return False
-
-            self.handler = handler.RuntimeConnectionHandler(connection, disconnect_callback, self.ap)
-            self.handler_task = asyncio.create_task(self.handler.run())
-            _ = await self.handler.ping()
-            self.ap.logger.info('Connected to plugin runtime.')
-            await self.handler_task
-
-        task: asyncio.Task | None = None
-
-        if platform.get_platform() == 'docker':  # use websocket
-            self.ap.logger.info('use websocket to connect to plugin runtime')
-            ws_url = self.ap.instance_config.data['plugin']['runtime_ws_url']
-
-            async def make_connection_failed_callback(ctrl: ws_client_controller.WebSocketClientController) -> None:
-                self.ap.logger.error('Failed to connect to plugin runtime, trying to reconnect...')
-                await self.runtime_disconnect_callback(self)
-
-            self.ctrl = ws_client_controller.WebSocketClientController(
-                ws_url=ws_url,
-                make_connection_failed_callback=make_connection_failed_callback,
-            )
-            task = self.ctrl.run(new_connection_callback)
-        else:  # stdio
-            self.ap.logger.info('use stdio to connect to plugin runtime')
-            # cmd: lbp rt -s
-            python_path = sys.executable
-            env = os.environ.copy()
-            self.ctrl = stdio_client_controller.StdioClientController(
-                command=python_path,
-                args=['-m', 'langbot_plugin.cli.__init__', 'rt', '-s'],
-                env=env,
-            )
-            task = self.ctrl.run(new_connection_callback)
-
-        asyncio.create_task(task)
-
-    async def initialize_plugins(self):
-        pass
-
-    async def install_plugin(
-        self,
-        install_source: PluginInstallSource,
-        install_info: dict[str, Any],
-        task_context: taskmgr.TaskContext | None = None,
-    ):
-        async for ret in self.handler.install_plugin(install_source.value, install_info):
-            current_action = ret.get('current_action', None)
-            if current_action is not None:
-                if task_context is not None:
-                    task_context.set_current_action(current_action)
-
-            trace = ret.get('trace', None)
-            if trace is not None:
-                if task_context is not None:
-                    task_context.trace(trace)
-
-    async def upgrade_plugin(
-        self, plugin_author: str, plugin_name: str, task_context: taskmgr.TaskContext | None = None
-    ) -> dict[str, Any]:
-        async for ret in self.handler.upgrade_plugin(plugin_author, plugin_name):
-            current_action = ret.get('current_action', None)
-            if current_action is not None:
-                if task_context is not None:
-                    task_context.set_current_action(current_action)
-
-            trace = ret.get('trace', None)
-            if trace is not None:
-                if task_context is not None:
-                    task_context.trace(trace)
-
-    async def delete_plugin(
-        self, plugin_author: str, plugin_name: str, task_context: taskmgr.TaskContext | None = None
-    ) -> dict[str, Any]:
-        async for ret in self.handler.delete_plugin(plugin_author, plugin_name):
-            current_action = ret.get('current_action', None)
-            if current_action is not None:
-                if task_context is not None:
-                    task_context.set_current_action(current_action)
-
-            trace = ret.get('trace', None)
-            if trace is not None:
-                if task_context is not None:
-                    task_context.trace(trace)
-
-    async def list_plugins(self) -> list[dict[str, Any]]:
-        return await self.handler.list_plugins()
-
-    async def get_plugin_info(self, author: str, plugin_name: str) -> dict[str, Any]:
-        return await self.handler.get_plugin_info(author, plugin_name)
-
-    async def set_plugin_config(self, plugin_author: str, plugin_name: str, config: dict[str, Any]) -> dict[str, Any]:
-        return await self.handler.set_plugin_config(plugin_author, plugin_name, config)
-
-    async def emit_event(
-        self,
-        event: events.BaseEventModel,
-    ) -> context.EventContext:
-        event_ctx = context.EventContext.from_event(event)
-
-        event_ctx_result = await self.handler.emit_event(event_ctx.model_dump(serialize_as_any=True))
-
-        event_ctx = context.EventContext.model_validate(event_ctx_result['event_context'])
-
-        return event_ctx
-
-    async def list_tools(self) -> list[ComponentManifest]:
-        list_tools_data = await self.handler.list_tools()
-
-        return [ComponentManifest.model_validate(tool) for tool in list_tools_data]
-
-    async def call_tool(self, tool_name: str, parameters: dict[str, Any]) -> dict[str, Any]:
-        return await self.handler.call_tool(tool_name, parameters)
-
-    async def list_commands(self) -> list[ComponentManifest]:
-        list_commands_data = await self.handler.list_commands()
-
-        return [ComponentManifest.model_validate(command) for command in list_commands_data]
-
-    async def execute_command(
-        self, command_ctx: command_context.ExecuteContext
-    ) -> typing.AsyncGenerator[command_context.CommandReturn, None]:
-        gen = self.handler.execute_command(command_ctx.model_dump(serialize_as_any=True))
-
-        async for ret in gen:
-            cmd_ret = command_context.CommandReturn.model_validate(ret)
-
-            yield cmd_ret
-
-    def dispose(self):
-        if isinstance(self.ctrl, stdio_client_controller.StdioClientController):
-            self.ap.logger.info('Terminating plugin runtime process...')
-            self.ctrl.process.terminate()

pkg/provider/modelmgr/requester.py

@@ -1,76 +0,0 @@
-from __future__ import annotations
-
-import abc
-import typing
-
-from ...core import app
-from ...entity.persistence import model as persistence_model
-import langbot_plugin.api.entities.builtin.resource.tool as resource_tool
-from . import token
-import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query
-import langbot_plugin.api.entities.builtin.provider.message as provider_message
-
-
-class RuntimeLLMModel:
-    """运行时模型"""
-
-    model_entity: persistence_model.LLMModel
-    """模型数据"""
-
-    token_mgr: token.TokenManager
-    """api key管理器"""
-
-    requester: LLMAPIRequester
-    """请求器实例"""
-
-    def __init__(
-        self,
-        model_entity: persistence_model.LLMModel,
-        token_mgr: token.TokenManager,
-        requester: LLMAPIRequester,
-    ):
-        self.model_entity = model_entity
-        self.token_mgr = token_mgr
-        self.requester = requester
-
-
-class LLMAPIRequester(metaclass=abc.ABCMeta):
-    """LLM API请求器"""
-
-    name: str = None
-
-    ap: app.Application
-
-    default_config: dict[str, typing.Any] = {}
-
-    requester_cfg: dict[str, typing.Any] = {}
-
-    def __init__(self, ap: app.Application, config: dict[str, typing.Any]):
-        self.ap = ap
-        self.requester_cfg = {**self.default_config}
-        self.requester_cfg.update(config)
-
-    async def initialize(self):
-        pass
-
-    @abc.abstractmethod
-    async def invoke_llm(
-        self,
-        query: pipeline_query.Query,
-        model: RuntimeLLMModel,
-        messages: typing.List[provider_message.Message],
-        funcs: typing.List[resource_tool.LLMTool] = None,
-        extra_args: dict[str, typing.Any] = {},
-    ) -> provider_message.Message:
-        """调用API
-
-        Args:
-            model (RuntimeLLMModel): 使用的模型信息
-            messages (typing.List[llm_entities.Message]): 消息对象列表
-            funcs (typing.List[tools_entities.LLMFunction], optional): 使用的工具函数列表. Defaults to None.
-            extra_args (dict[str, typing.Any], optional): 额外的参数. Defaults to {}.
-
-        Returns:
-            llm_entities.Message: 返回消息对象
-        """
-        pass

pkg/provider/modelmgr/requesters/302aichatcmpl.yaml

@@ -1,28 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: 302-ai-chat-completions
-  label:
-    en_US: 302 AI
-    zh_Hans: 302 AI
-  icon: 302ai.png
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://api.302.ai/v1"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-execution:
-  python:
-    path: ./302aichatcmpl.py
-    attr: AI302ChatCompletions

pkg/provider/modelmgr/requesters/anthropicmsgs.py

@@ -1,178 +0,0 @@
-from __future__ import annotations
-
-import typing
-import json
-import platform
-import socket
-import anthropic
-import httpx
-
-from .. import errors, requester
-
-from ....utils import image
-import langbot_plugin.api.entities.builtin.resource.tool as resource_tool
-import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query
-import langbot_plugin.api.entities.builtin.provider.message as provider_message
-
-
-class AnthropicMessages(requester.LLMAPIRequester):
-    """Anthropic Messages API 请求器"""
-
-    client: anthropic.AsyncAnthropic
-
-    default_config: dict[str, typing.Any] = {
-        'base_url': 'https://api.anthropic.com/v1',
-        'timeout': 120,
-    }
-
-    async def initialize(self):
-        # 兼容 Windows 缺失 TCP_KEEPINTVL 和 TCP_KEEPCNT 的问题
-        if platform.system() == 'Windows':
-            if not hasattr(socket, 'TCP_KEEPINTVL'):
-                socket.TCP_KEEPINTVL = 0
-            if not hasattr(socket, 'TCP_KEEPCNT'):
-                socket.TCP_KEEPCNT = 0
-        httpx_client = anthropic._base_client.AsyncHttpxClientWrapper(
-            base_url=self.requester_cfg['base_url'],
-            # cast to a valid type because mypy doesn't understand our type narrowing
-            timeout=typing.cast(httpx.Timeout, self.requester_cfg['timeout']),
-            limits=anthropic._constants.DEFAULT_CONNECTION_LIMITS,
-            follow_redirects=True,
-            trust_env=True,
-        )
-
-        self.client = anthropic.AsyncAnthropic(
-            api_key='',
-            http_client=httpx_client,
-        )
-
-    async def invoke_llm(
-        self,
-        query: pipeline_query.Query,
-        model: requester.RuntimeLLMModel,
-        messages: typing.List[provider_message.Message],
-        funcs: typing.List[resource_tool.LLMTool] = None,
-        extra_args: dict[str, typing.Any] = {},
-    ) -> provider_message.Message:
-        self.client.api_key = model.token_mgr.get_token()
-
-        args = extra_args.copy()
-        args['model'] = model.model_entity.name
-
-        # 处理消息
-
-        # system
-        system_role_message = None
-
-        for i, m in enumerate(messages):
-            if m.role == 'system':
-                system_role_message = m
-
-                break
-
-        if system_role_message:
-            messages.pop(i)
-
-        if isinstance(system_role_message, provider_message.Message) and isinstance(system_role_message.content, str):
-            args['system'] = system_role_message.content
-
-        req_messages = []
-
-        for m in messages:
-            if m.role == 'tool':
-                tool_call_id = m.tool_call_id
-
-                req_messages.append(
-                    {
-                        'role': 'user',
-                        'content': [
-                            {
-                                'type': 'tool_result',
-                                'tool_use_id': tool_call_id,
-                                'content': m.content,
-                            }
-                        ],
-                    }
-                )
-
-                continue
-
-            msg_dict = m.dict(exclude_none=True)
-
-            if isinstance(m.content, str) and m.content.strip() != '':
-                msg_dict['content'] = [{'type': 'text', 'text': m.content}]
-            elif isinstance(m.content, list):
-                for i, ce in enumerate(m.content):
-                    if ce.type == 'image_base64':
-                        image_b64, image_format = await image.extract_b64_and_format(ce.image_base64)
-
-                        alter_image_ele = {
-                            'type': 'image',
-                            'source': {
-                                'type': 'base64',
-                                'media_type': f'image/{image_format}',
-                                'data': image_b64,
-                            },
-                        }
-                        msg_dict['content'][i] = alter_image_ele
-
-            if m.tool_calls:
-                for tool_call in m.tool_calls:
-                    msg_dict['content'].append(
-                        {
-                            'type': 'tool_use',
-                            'id': tool_call.id,
-                            'name': tool_call.function.name,
-                            'input': json.loads(tool_call.function.arguments),
-                        }
-                    )
-
-                del msg_dict['tool_calls']
-
-            req_messages.append(msg_dict)
-
-        args['messages'] = req_messages
-
-        if funcs:
-            tools = await self.ap.tool_mgr.generate_tools_for_anthropic(funcs)
-
-            if tools:
-                args['tools'] = tools
-
-        try:
-            # print(json.dumps(args, indent=4, ensure_ascii=False))
-            resp = await self.client.messages.create(**args)
-
-            args = {
-                'content': '',
-                'role': resp.role,
-            }
-
-            assert type(resp) is anthropic.types.message.Message
-
-            for block in resp.content:
-                if block.type == 'thinking':
-                    args['content'] = '<think>' + block.thinking + '</think>\n' + args['content']
-                elif block.type == 'text':
-                    args['content'] += block.text
-                elif block.type == 'tool_use':
-                    assert type(block) is anthropic.types.tool_use_block.ToolUseBlock
-                    tool_call = provider_message.ToolCall(
-                        id=block.id,
-                        type='function',
-                        function=provider_message.FunctionCall(name=block.name, arguments=json.dumps(block.input)),
-                    )
-                    if 'tool_calls' not in args:
-                        args['tool_calls'] = []
-                    args['tool_calls'].append(tool_call)
-
-            return provider_message.Message(**args)
-        except anthropic.AuthenticationError as e:
-            raise errors.RequesterError(f'api-key 无效: {e.message}')
-        except anthropic.BadRequestError as e:
-            raise errors.RequesterError(str(e.message))
-        except anthropic.NotFoundError as e:
-            if 'model: ' in str(e):
-                raise errors.RequesterError(f'模型无效: {e.message}')
-            else:
-                raise errors.RequesterError(f'请求地址无效: {e.message}')

pkg/provider/modelmgr/requesters/anthropicmsgs.yaml

@@ -1,28 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: anthropic-messages
-  label:
-    en_US: Anthropic
-    zh_Hans: Anthropic
-  icon: anthropic.svg
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://api.anthropic.com/v1"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-execution:
-  python:
-    path: ./anthropicmsgs.py
-    attr: AnthropicMessages

pkg/provider/modelmgr/requesters/bailianchatcmpl.py

@@ -1,17 +0,0 @@
-from __future__ import annotations
-
-import typing
-import openai
-
-from . import modelscopechatcmpl
-
-
-class BailianChatCompletions(modelscopechatcmpl.ModelScopeChatCompletions):
-    """阿里云百炼大模型平台 ChatCompletion API 请求器"""
-
-    client: openai.AsyncClient
-
-    default_config: dict[str, typing.Any] = {
-        'base_url': 'https://dashscope.aliyuncs.com/compatible-mode/v1',
-        'timeout': 120,
-    }

pkg/provider/modelmgr/requesters/bailianchatcmpl.yaml

@@ -1,28 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: bailian-chat-completions
-  label:
-    en_US: Aliyun Bailian
-    zh_Hans: 阿里云百炼
-  icon: bailian.png
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://dashscope.aliyuncs.com/compatible-mode/v1"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-execution:
-  python:
-    path: ./bailianchatcmpl.py
-    attr: BailianChatCompletions

pkg/provider/modelmgr/requesters/chatcmpl.py

@@ -1,143 +0,0 @@
-from __future__ import annotations
-
-import asyncio
-import typing
-
-import openai
-import openai.types.chat.chat_completion as chat_completion
-import httpx
-
-from .. import errors, requester
-import langbot_plugin.api.entities.builtin.resource.tool as resource_tool
-import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query
-import langbot_plugin.api.entities.builtin.provider.message as provider_message
-
-
-class OpenAIChatCompletions(requester.LLMAPIRequester):
-    """OpenAI ChatCompletion API 请求器"""
-
-    client: openai.AsyncClient
-
-    default_config: dict[str, typing.Any] = {
-        'base_url': 'https://api.openai.com/v1',
-        'timeout': 120,
-    }
-
-    async def initialize(self):
-        self.client = openai.AsyncClient(
-            api_key='',
-            base_url=self.requester_cfg['base_url'].replace(' ', ''),
-            timeout=self.requester_cfg['timeout'],
-            http_client=httpx.AsyncClient(trust_env=True, timeout=self.requester_cfg['timeout']),
-        )
-
-    async def _req(
-        self,
-        args: dict,
-        extra_body: dict = {},
-    ) -> chat_completion.ChatCompletion:
-        return await self.client.chat.completions.create(**args, extra_body=extra_body)
-
-    async def _make_msg(
-        self,
-        chat_completion: chat_completion.ChatCompletion,
-    ) -> provider_message.Message:
-        chatcmpl_message = chat_completion.choices[0].message.model_dump()
-
-        # 确保 role 字段存在且不为 None
-        if 'role' not in chatcmpl_message or chatcmpl_message['role'] is None:
-            chatcmpl_message['role'] = 'assistant'
-
-        reasoning_content = chatcmpl_message['reasoning_content'] if 'reasoning_content' in chatcmpl_message else None
-
-        # deepseek的reasoner模型
-        if reasoning_content is not None:
-            chatcmpl_message['content'] = '<think>\n' + reasoning_content + '\n</think>\n' + chatcmpl_message['content']
-
-        message = provider_message.Message(**chatcmpl_message)
-
-        return message
-
-    async def _closure(
-        self,
-        query: pipeline_query.Query,
-        req_messages: list[dict],
-        use_model: requester.RuntimeLLMModel,
-        use_funcs: list[resource_tool.LLMTool] = None,
-        extra_args: dict[str, typing.Any] = {},
-    ) -> provider_message.Message:
-        self.client.api_key = use_model.token_mgr.get_token()
-
-        args = {}
-        args['model'] = use_model.model_entity.name
-
-        if use_funcs:
-            tools = await self.ap.tool_mgr.generate_tools_for_openai(use_funcs)
-
-            if tools:
-                args['tools'] = tools
-
-        # 设置此次请求中的messages
-        messages = req_messages.copy()
-
-        # 检查vision
-        for msg in messages:
-            if 'content' in msg and isinstance(msg['content'], list):
-                for me in msg['content']:
-                    if me['type'] == 'image_base64':
-                        me['image_url'] = {'url': me['image_base64']}
-                        me['type'] = 'image_url'
-                        del me['image_base64']
-
-        args['messages'] = messages
-
-        # 发送请求
-        resp = await self._req(args, extra_body=extra_args)
-
-        # 处理请求结果
-        message = await self._make_msg(resp)
-
-        return message
-
-    async def invoke_llm(
-        self,
-        query: pipeline_query.Query,
-        model: requester.RuntimeLLMModel,
-        messages: typing.List[provider_message.Message],
-        funcs: typing.List[resource_tool.LLMTool] = None,
-        extra_args: dict[str, typing.Any] = {},
-    ) -> provider_message.Message:
-        req_messages = []  # req_messages 仅用于类内，外部同步由 query.messages 进行
-        for m in messages:
-            msg_dict = m.dict(exclude_none=True)
-            content = msg_dict.get('content')
-            if isinstance(content, list):
-                # 检查 content 列表中是否每个部分都是文本
-                if all(isinstance(part, dict) and part.get('type') == 'text' for part in content):
-                    # 将所有文本部分合并为一个字符串
-                    msg_dict['content'] = '\n'.join(part['text'] for part in content)
-            req_messages.append(msg_dict)
-
-        try:
-            return await self._closure(
-                query=query,
-                req_messages=req_messages,
-                use_model=model,
-                use_funcs=funcs,
-                extra_args=extra_args,
-            )
-        except asyncio.TimeoutError:
-            raise errors.RequesterError('请求超时')
-        except openai.BadRequestError as e:
-            if 'context_length_exceeded' in e.message:
-                raise errors.RequesterError(f'上文过长，请重置会话: {e.message}')
-            else:
-                raise errors.RequesterError(f'请求参数错误: {e.message}')
-        except openai.AuthenticationError as e:
-            raise errors.RequesterError(f'无效的 api-key: {e.message}')
-        except openai.NotFoundError as e:
-            raise errors.RequesterError(f'请求路径错误: {e.message}')
-        except openai.RateLimitError as e:
-            raise errors.RequesterError(f'请求过于频繁或余额不足: {e.message}')
-        except openai.APIError as e:
-            raise errors.RequesterError(f'请求错误: {e.message}')

pkg/provider/modelmgr/requesters/chatcmpl.yaml

@@ -1,28 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: openai-chat-completions
-  label:
-    en_US: OpenAI
-    zh_Hans: OpenAI
-  icon: openai.svg
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://api.openai.com/v1"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-execution:
-  python:
-    path: ./chatcmpl.py
-    attr: OpenAIChatCompletions

pkg/provider/modelmgr/requesters/deepseekchatcmpl.yaml

@@ -1,28 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: deepseek-chat-completions
-  label:
-    en_US: DeepSeek
-    zh_Hans: 深度求索
-  icon: deepseek.svg
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://api.deepseek.com"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-execution:
-  python:
-    path: ./deepseekchatcmpl.py
-    attr: DeepseekChatCompletions

pkg/provider/modelmgr/requesters/geminichatcmpl.py

@@ -1,14 +0,0 @@
-from __future__ import annotations
-
-import typing
-
-from . import chatcmpl
-
-
-class GeminiChatCompletions(chatcmpl.OpenAIChatCompletions):
-    """Google Gemini API 请求器"""
-
-    default_config: dict[str, typing.Any] = {
-        'base_url': 'https://generativelanguage.googleapis.com/v1beta/openai',
-        'timeout': 120,
-    }

pkg/provider/modelmgr/requesters/geminichatcmpl.yaml

@@ -1,28 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: gemini-chat-completions
-  label:
-    en_US: Google Gemini
-    zh_Hans: Google Gemini
-  icon: gemini.svg
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://generativelanguage.googleapis.com/v1beta/openai"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-execution:
-  python:
-    path: ./geminichatcmpl.py
-    attr: GeminiChatCompletions

pkg/provider/modelmgr/requesters/giteeaichatcmpl.py

@@ -1,51 +0,0 @@
-from __future__ import annotations
-
-
-import typing
-
-from . import chatcmpl
-from .. import requester
-import langbot_plugin.api.entities.builtin.resource.tool as resource_tool
-import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query
-import langbot_plugin.api.entities.builtin.provider.message as provider_message
-
-
-class GiteeAIChatCompletions(chatcmpl.OpenAIChatCompletions):
-    """Gitee AI ChatCompletions API 请求器"""
-
-    default_config: dict[str, typing.Any] = {
-        'base_url': 'https://ai.gitee.com/v1',
-        'timeout': 120,
-    }
-
-    async def _closure(
-        self,
-        query: pipeline_query.Query,
-        req_messages: list[dict],
-        use_model: requester.RuntimeLLMModel,
-        use_funcs: list[resource_tool.LLMTool] = None,
-        extra_args: dict[str, typing.Any] = {},
-    ) -> provider_message.Message:
-        self.client.api_key = use_model.token_mgr.get_token()
-
-        args = {}
-        args['model'] = use_model.model_entity.name
-
-        if use_funcs:
-            tools = await self.ap.tool_mgr.generate_tools_for_openai(use_funcs)
-
-            if tools:
-                args['tools'] = tools
-
-        # gitee 不支持多模态，把content都转换成纯文字
-        for m in req_messages:
-            if 'content' in m and isinstance(m['content'], list):
-                m['content'] = ' '.join([c['text'] for c in m['content']])
-
-        args['messages'] = req_messages
-
-        resp = await self._req(args, extra_body=extra_args)
-
-        message = await self._make_msg(resp)
-
-        return message

pkg/provider/modelmgr/requesters/giteeaichatcmpl.yaml

@@ -1,28 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: gitee-ai-chat-completions
-  label:
-    en_US: Gitee AI
-    zh_Hans: Gitee AI
-  icon: giteeai.svg
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://ai.gitee.com/v1"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-execution:
-  python:
-    path: ./giteeaichatcmpl.py
-    attr: GiteeAIChatCompletions

pkg/provider/modelmgr/requesters/lmstudiochatcmpl.yaml

@@ -1,28 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: lmstudio-chat-completions
-  label:
-    en_US: LM Studio
-    zh_Hans: LM Studio
-  icon: lmstudio.webp
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "http://127.0.0.1:1234/v1"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-execution:
-  python:
-    path: ./lmstudiochatcmpl.py
-    attr: LmStudioChatCompletions

pkg/provider/modelmgr/requesters/modelscopechatcmpl.py

@@ -1,204 +0,0 @@
-from __future__ import annotations
-
-import asyncio
-import typing
-
-import openai
-import openai.types.chat.chat_completion as chat_completion
-import openai.types.chat.chat_completion_message_tool_call as chat_completion_message_tool_call
-import httpx
-
-from .. import entities, errors, requester
-import langbot_plugin.api.entities.builtin.resource.tool as resource_tool
-import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query
-import langbot_plugin.api.entities.builtin.provider.message as provider_message
-
-
-class ModelScopeChatCompletions(requester.LLMAPIRequester):
-    """ModelScope ChatCompletion API 请求器"""
-
-    client: openai.AsyncClient
-
-    default_config: dict[str, typing.Any] = {
-        'base_url': 'https://api-inference.modelscope.cn/v1',
-        'timeout': 120,
-    }
-
-    async def initialize(self):
-        self.client = openai.AsyncClient(
-            api_key='',
-            base_url=self.requester_cfg['base_url'],
-            timeout=self.requester_cfg['timeout'],
-            http_client=httpx.AsyncClient(trust_env=True, timeout=self.requester_cfg['timeout']),
-        )
-
-    async def _req(
-        self,
-        args: dict,
-        extra_body: dict = {},
-    ) -> chat_completion.ChatCompletion:
-        args['stream'] = True
-
-        chunk = None
-
-        pending_content = ''
-
-        tool_calls = []
-
-        resp_gen: openai.AsyncStream = await self.client.chat.completions.create(**args, extra_body=extra_body)
-
-        async for chunk in resp_gen:
-            # print(chunk)
-            if not chunk or not chunk.id or not chunk.choices or not chunk.choices[0] or not chunk.choices[0].delta:
-                continue
-
-            if chunk.choices[0].delta.content is not None:
-                pending_content += chunk.choices[0].delta.content
-
-            if chunk.choices[0].delta.tool_calls is not None:
-                for tool_call in chunk.choices[0].delta.tool_calls:
-                    if tool_call.function.arguments is None:
-                        continue
-                    for tc in tool_calls:
-                        if tc.index == tool_call.index:
-                            tc.function.arguments += tool_call.function.arguments
-                            break
-                    else:
-                        tool_calls.append(tool_call)
-
-            if chunk.choices[0].finish_reason is not None:
-                break
-
-        real_tool_calls = []
-
-        for tc in tool_calls:
-            function = chat_completion_message_tool_call.Function(
-                name=tc.function.name, arguments=tc.function.arguments
-            )
-            real_tool_calls.append(
-                chat_completion_message_tool_call.ChatCompletionMessageToolCall(
-                    id=tc.id, function=function, type='function'
-                )
-            )
-
-        return (
-            chat_completion.ChatCompletion(
-                id=chunk.id,
-                object='chat.completion',
-                created=chunk.created,
-                choices=[
-                    chat_completion.Choice(
-                        index=0,
-                        message=chat_completion.ChatCompletionMessage(
-                            role='assistant',
-                            content=pending_content,
-                            tool_calls=real_tool_calls if len(real_tool_calls) > 0 else None,
-                        ),
-                        finish_reason=chunk.choices[0].finish_reason
-                        if hasattr(chunk.choices[0], 'finish_reason') and chunk.choices[0].finish_reason is not None
-                        else 'stop',
-                        logprobs=chunk.choices[0].logprobs,
-                    )
-                ],
-                model=chunk.model,
-                service_tier=chunk.service_tier if hasattr(chunk, 'service_tier') else None,
-                system_fingerprint=chunk.system_fingerprint if hasattr(chunk, 'system_fingerprint') else None,
-                usage=chunk.usage if hasattr(chunk, 'usage') else None,
-            )
-            if chunk
-            else None
-        )
-
-    async def _make_msg(
-        self,
-        chat_completion: chat_completion.ChatCompletion,
-    ) -> provider_message.Message:
-        chatcmpl_message = chat_completion.choices[0].message.dict()
-
-        # 确保 role 字段存在且不为 None
-        if 'role' not in chatcmpl_message or chatcmpl_message['role'] is None:
-            chatcmpl_message['role'] = 'assistant'
-
-        message = provider_message.Message(**chatcmpl_message)
-
-        return message
-
-    async def _closure(
-        self,
-        query: pipeline_query.Query,
-        req_messages: list[dict],
-        use_model: requester.RuntimeLLMModel,
-        use_funcs: list[resource_tool.LLMTool] = None,
-        extra_args: dict[str, typing.Any] = {},
-    ) -> provider_message.Message:
-        self.client.api_key = use_model.token_mgr.get_token()
-
-        args = {}
-        args['model'] = use_model.model_entity.name
-
-        if use_funcs:
-            tools = await self.ap.tool_mgr.generate_tools_for_openai(use_funcs)
-
-            if tools:
-                args['tools'] = tools
-
-        # 设置此次请求中的messages
-        messages = req_messages.copy()
-
-        # 检查vision
-        for msg in messages:
-            if 'content' in msg and isinstance(msg['content'], list):
-                for me in msg['content']:
-                    if me['type'] == 'image_base64':
-                        me['image_url'] = {'url': me['image_base64']}
-                        me['type'] = 'image_url'
-                        del me['image_base64']
-
-        args['messages'] = messages
-
-        # 发送请求
-        resp = await self._req(args, extra_body=extra_args)
-
-        # 处理请求结果
-        message = await self._make_msg(resp)
-
-        return message
-
-    async def invoke_llm(
-        self,
-        query: pipeline_query.Query,
-        model: entities.LLMModelInfo,
-        messages: typing.List[provider_message.Message],
-        funcs: typing.List[resource_tool.LLMTool] = None,
-        extra_args: dict[str, typing.Any] = {},
-    ) -> provider_message.Message:
-        req_messages = []  # req_messages 仅用于类内，外部同步由 query.messages 进行
-        for m in messages:
-            msg_dict = m.dict(exclude_none=True)
-            content = msg_dict.get('content')
-            if isinstance(content, list):
-                # 检查 content 列表中是否每个部分都是文本
-                if all(isinstance(part, dict) and part.get('type') == 'text' for part in content):
-                    # 将所有文本部分合并为一个字符串
-                    msg_dict['content'] = '\n'.join(part['text'] for part in content)
-            req_messages.append(msg_dict)
-
-        try:
-            return await self._closure(
-                query=query, req_messages=req_messages, use_model=model, use_funcs=funcs, extra_args=extra_args
-            )
-        except asyncio.TimeoutError:
-            raise errors.RequesterError('请求超时')
-        except openai.BadRequestError as e:
-            if 'context_length_exceeded' in e.message:
-                raise errors.RequesterError(f'上文过长，请重置会话: {e.message}')
-            else:
-                raise errors.RequesterError(f'请求参数错误: {e.message}')
-        except openai.AuthenticationError as e:
-            raise errors.RequesterError(f'无效的 api-key: {e.message}')
-        except openai.NotFoundError as e:
-            raise errors.RequesterError(f'请求路径错误: {e.message}')
-        except openai.RateLimitError as e:
-            raise errors.RequesterError(f'请求过于频繁或余额不足: {e.message}')
-        except openai.APIError as e:
-            raise errors.RequesterError(f'请求错误: {e.message}')

pkg/provider/modelmgr/requesters/modelscopechatcmpl.yaml

@@ -1,35 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: modelscope-chat-completions
-  label:
-    en_US: ModelScope
-    zh_Hans: 魔搭社区
-  icon: modelscope.svg
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://api-inference.modelscope.cn/v1"
-    - name: args
-      label:
-        en_US: Args
-        zh_Hans: 附加参数
-      type: object
-      required: true
-      default: {}
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: int
-      required: true
-      default: 120
-execution:
-  python:
-    path: ./modelscopechatcmpl.py
-    attr: ModelScopeChatCompletions

pkg/provider/modelmgr/requesters/moonshotchatcmpl.yaml

@@ -1,28 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: moonshot-chat-completions
-  label:
-    en_US: Moonshot
-    zh_Hans: 月之暗面
-  icon: moonshot.png
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://api.moonshot.com/v1"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-execution:
-  python:
-    path: ./moonshotchatcmpl.py
-    attr: MoonshotChatCompletions

pkg/provider/modelmgr/requesters/ollamachat.yaml

@@ -1,28 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: ollama-chat
-  label:
-    en_US: Ollama
-    zh_Hans: Ollama
-  icon: ollama.svg
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "http://127.0.0.1:11434"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-execution:
-  python:
-    path: ./ollamachat.py
-    attr: OllamaChatCompletions

pkg/provider/modelmgr/requesters/openrouterchatcmpl.yaml

@@ -1,28 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: openrouter-chat-completions
-  label:
-    en_US: OpenRouter
-    zh_Hans: OpenRouter
-  icon: openrouter.svg
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://openrouter.ai/api/v1"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-execution:
-  python:
-    path: ./openrouterchatcmpl.py
-    attr: OpenRouterChatCompletions

pkg/provider/modelmgr/requesters/ppiochatcmpl.yaml

@@ -1,35 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: ppio-chat-completions
-  label:
-    en_US: ppio 
-    zh_Hans: 派欧云
-  icon: ppio.svg
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://api.ppinfra.com/v3/openai"
-    - name: args
-      label:
-        en_US: Args
-        zh_Hans: 附加参数
-      type: object
-      required: true
-      default: {}
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: int
-      required: true
-      default: 120
-execution:
-  python:
-    path: ./ppiochatcmpl.py
-    attr: PPIOChatCompletions

pkg/provider/modelmgr/requesters/siliconflowchatcmpl.yaml

@@ -1,28 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: siliconflow-chat-completions
-  label:
-    en_US: SiliconFlow
-    zh_Hans: 硅基流动
-  icon: siliconflow.svg
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://api.siliconflow.cn/v1"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-execution:
-  python:
-    path: ./siliconflowchatcmpl.py
-    attr: SiliconFlowChatCompletions

pkg/provider/modelmgr/requesters/volcarkchatcmpl.yaml

@@ -1,28 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: volcark-chat-completions
-  label:
-    en_US: Volc Engine Ark
-    zh_Hans: 火山方舟
-  icon: volcark.svg
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://ark.cn-beijing.volces.com/api/v3"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-execution:
-  python:
-    path: ./volcarkchatcmpl.py
-    attr: VolcArkChatCompletions

pkg/provider/modelmgr/requesters/xaichatcmpl.yaml

@@ -1,28 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: xai-chat-completions
-  label:
-    en_US: xAI
-    zh_Hans: xAI
-  icon: xai.svg
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://api.x.ai/v1"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-execution:
-  python:
-    path: ./xaichatcmpl.py
-    attr: XaiChatCompletions

pkg/provider/modelmgr/requesters/zhipuaichatcmpl.yaml

@@ -1,28 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: zhipuai-chat-completions
-  label:
-    en_US: ZhipuAI
-    zh_Hans: 智谱 AI
-  icon: zhipuai.svg
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://open.bigmodel.cn/api/paas/v4"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-execution:
-  python:
-    path: ./zhipuaichatcmpl.py
-    attr: ZhipuAIChatCompletions

pkg/provider/runners/dashscopeapi.py

@@ -1,227 +0,0 @@
-from __future__ import annotations
-
-import typing
-import re
-
-import dashscope
-
-from .. import runner
-from ...core import app
-import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query
-import langbot_plugin.api.entities.builtin.provider.message as provider_message
-
-
-class DashscopeAPIError(Exception):
-    """Dashscope API 请求失败"""
-
-    def __init__(self, message: str):
-        self.message = message
-        super().__init__(self.message)
-
-
-@runner.runner_class('dashscope-app-api')
-class DashScopeAPIRunner(runner.RequestRunner):
-    "阿里云百炼DashsscopeAPI对话请求器"
-
-    # 运行器内部使用的配置
-    app_type: str  # 应用类型
-    app_id: str  # 应用ID
-    api_key: str  # API Key
-    references_quote: (
-        str  # 引用资料提示（当展示回答来源功能开启时，这个变量会作为引用资料名前的提示，可在provider.json中配置）
-    )
-
-    def __init__(self, ap: app.Application, pipeline_config: dict):
-        """初始化"""
-        self.ap = ap
-        self.pipeline_config = pipeline_config
-
-        valid_app_types = ['agent', 'workflow']
-        self.app_type = self.pipeline_config['ai']['dashscope-app-api']['app-type']
-        # 检查配置文件中使用的应用类型是否支持
-        if self.app_type not in valid_app_types:
-            raise DashscopeAPIError(f'不支持的 Dashscope 应用类型: {self.app_type}')
-
-        # 初始化Dashscope 参数配置
-        self.app_id = self.pipeline_config['ai']['dashscope-app-api']['app-id']
-        self.api_key = self.pipeline_config['ai']['dashscope-app-api']['api-key']
-        self.references_quote = self.pipeline_config['ai']['dashscope-app-api']['references_quote']
-
-    def _replace_references(self, text, references_dict):
-        """阿里云百炼平台的自定义应用支持资料引用，此函数可以将引用标签替换为参考资料"""
-
-        # 匹配 <ref>[index_id]</ref> 形式的字符串
-        pattern = re.compile(r'<ref>\[(.*?)\]</ref>')
-
-        def replacement(match):
-            # 获取引用编号
-            ref_key = match.group(1)
-            if ref_key in references_dict:
-                # 如果有对应的参考资料按照provider.json中的reference_quote返回提示，来自哪个参考资料文件
-                return f'({self.references_quote} {references_dict[ref_key]})'
-            else:
-                # 如果没有对应的参考资料，保留原样
-                return match.group(0)
-
-        # 使用 re.sub() 进行替换
-        return pattern.sub(replacement, text)
-
-    async def _preprocess_user_message(self, query: pipeline_query.Query) -> tuple[str, list[str]]:
-        """预处理用户消息，提取纯文本，阿里云提供的上传文件方法过于复杂，暂不支持上传文件（包括图片）"""
-        plain_text = ''
-        image_ids = []
-        if isinstance(query.user_message.content, list):
-            for ce in query.user_message.content:
-                if ce.type == 'text':
-                    plain_text += ce.text
-                # 暂时不支持上传图片，保留代码以便后续扩展
-                # elif ce.type == "image_base64":
-                #     image_b64, image_format = await image.extract_b64_and_format(ce.image_base64)
-                #     file_bytes = base64.b64decode(image_b64)
-                #     file = ("img.png", file_bytes, f"image/{image_format}")
-                #     file_upload_resp = await self.dify_client.upload_file(
-                #         file,
-                #         f"{query.session.launcher_type.value}_{query.session.launcher_id}",
-                #     )
-                #     image_id = file_upload_resp["id"]
-                #     image_ids.append(image_id)
-        elif isinstance(query.user_message.content, str):
-            plain_text = query.user_message.content
-
-        return plain_text, image_ids
-
-    async def _agent_messages(
-        self, query: pipeline_query.Query
-    ) -> typing.AsyncGenerator[provider_message.Message, None]:
-        """Dashscope 智能体对话请求"""
-
-        # 局部变量
-        chunk = None  # 流式传输的块
-        pending_content = ''  # 待处理的Agent输出内容
-        references_dict = {}  # 用于存储引用编号和对应的参考资料
-        plain_text = ''  # 用户输入的纯文本信息
-        image_ids = []  # 用户输入的图片ID列表 （暂不支持）
-
-        plain_text, image_ids = await self._preprocess_user_message(query)
-
-        # 发送对话请求
-        response = dashscope.Application.call(
-            api_key=self.api_key,  # 智能体应用的API Key
-            app_id=self.app_id,  # 智能体应用的ID
-            prompt=plain_text,  # 用户输入的文本信息
-            stream=True,  # 流式输出
-            incremental_output=True,  # 增量输出，使用流式输出需要开启增量输出
-            session_id=query.session.using_conversation.uuid,  # 会话ID用于，多轮对话
-            # rag_options={                                     # 主要用于文件交互，暂不支持
-            #     "session_file_ids": ["FILE_ID1"],             # FILE_ID1 替换为实际的临时文件ID,逗号隔开多个
-            # }
-        )
-
-        for chunk in response:
-            if chunk.get('status_code') != 200:
-                raise DashscopeAPIError(
-                    f'Dashscope API 请求失败: status_code={chunk.get("status_code")} message={chunk.get("message")} request_id={chunk.get("request_id")} '
-                )
-            if not chunk:
-                continue
-
-            # 获取流式传输的output
-            stream_output = chunk.get('output', {})
-            if stream_output.get('text') is not None:
-                pending_content += stream_output.get('text')
-
-        # 保存当前会话的session_id用于下次对话的语境
-        query.session.using_conversation.uuid = stream_output.get('session_id')
-
-        # 获取模型传出的参考资料列表
-        references_dict_list = stream_output.get('doc_references', [])
-
-        # 从模型传出的参考资料信息中提取用于替换的字典
-        if references_dict_list is not None:
-            for doc in references_dict_list:
-                if doc.get('index_id') is not None:
-                    references_dict[doc.get('index_id')] = doc.get('doc_name')
-
-            # 将参考资料替换到文本中
-            pending_content = self._replace_references(pending_content, references_dict)
-
-        yield provider_message.Message(
-            role='assistant',
-            content=pending_content,
-        )
-
-    async def _workflow_messages(
-        self, query: pipeline_query.Query
-    ) -> typing.AsyncGenerator[provider_message.Message, None]:
-        """Dashscope 工作流对话请求"""
-
-        # 局部变量
-        chunk = None  # 流式传输的块
-        pending_content = ''  # 待处理的Agent输出内容
-        references_dict = {}  # 用于存储引用编号和对应的参考资料
-        plain_text = ''  # 用户输入的纯文本信息
-        image_ids = []  # 用户输入的图片ID列表 （暂不支持）
-
-        plain_text, image_ids = await self._preprocess_user_message(query)
-
-        biz_params = {}
-        biz_params.update(query.variables)
-
-        # 发送对话请求
-        response = dashscope.Application.call(
-            api_key=self.api_key,  # 智能体应用的API Key
-            app_id=self.app_id,  # 智能体应用的ID
-            prompt=plain_text,  # 用户输入的文本信息
-            stream=True,  # 流式输出
-            incremental_output=True,  # 增量输出，使用流式输出需要开启增量输出
-            session_id=query.session.using_conversation.uuid,  # 会话ID用于，多轮对话
-            biz_params=biz_params,  # 工作流应用的自定义输入参数传递
-            # rag_options={                                     # 主要用于文件交互，暂不支持
-            #     "session_file_ids": ["FILE_ID1"],             # FILE_ID1 替换为实际的临时文件ID,逗号隔开多个
-            # }
-        )
-
-        # 处理API返回的流式输出
-        for chunk in response:
-            if chunk.get('status_code') != 200:
-                raise DashscopeAPIError(
-                    f'Dashscope API 请求失败: status_code={chunk.get("status_code")} message={chunk.get("message")} request_id={chunk.get("request_id")} '
-                )
-            if not chunk:
-                continue
-
-            # 获取流式传输的output
-            stream_output = chunk.get('output', {})
-            if stream_output.get('text') is not None:
-                pending_content += stream_output.get('text')
-
-        # 保存当前会话的session_id用于下次对话的语境
-        query.session.using_conversation.uuid = stream_output.get('session_id')
-
-        # 获取模型传出的参考资料列表
-        references_dict_list = stream_output.get('doc_references', [])
-
-        # 从模型传出的参考资料信息中提取用于替换的字典
-        if references_dict_list is not None:
-            for doc in references_dict_list:
-                if doc.get('index_id') is not None:
-                    references_dict[doc.get('index_id')] = doc.get('doc_name')
-
-            # 将参考资料替换到文本中
-            pending_content = self._replace_references(pending_content, references_dict)
-
-        yield provider_message.Message(
-            role='assistant',
-            content=pending_content,
-        )
-
-    async def run(self, query: pipeline_query.Query) -> typing.AsyncGenerator[provider_message.Message, None]:
-        """运行"""
-        if self.app_type == 'agent':
-            async for msg in self._agent_messages(query):
-                yield msg
-        elif self.app_type == 'workflow':
-            async for msg in self._workflow_messages(query):
-                yield msg
-        else:
-            raise DashscopeAPIError(f'不支持的 Dashscope 应用类型: {self.app_type}')

pkg/provider/runners/difysvapi.py

@@ -1,337 +0,0 @@
-from __future__ import annotations
-
-import typing
-import json
-import uuid
-import re
-import base64
-
-
-from .. import runner
-from ...core import app
-import langbot_plugin.api.entities.builtin.provider.message as provider_message
-from ...utils import image
-import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query
-from libs.dify_service_api.v1 import client, errors
-
-
-@runner.runner_class('dify-service-api')
-class DifyServiceAPIRunner(runner.RequestRunner):
-    """Dify Service API 对话请求器"""
-
-    dify_client: client.AsyncDifyServiceClient
-
-    def __init__(self, ap: app.Application, pipeline_config: dict):
-        self.ap = ap
-        self.pipeline_config = pipeline_config
-
-        valid_app_types = ['chat', 'agent', 'workflow']
-        if self.pipeline_config['ai']['dify-service-api']['app-type'] not in valid_app_types:
-            raise errors.DifyAPIError(
-                f'不支持的 Dify 应用类型: {self.pipeline_config["ai"]["dify-service-api"]["app-type"]}'
-            )
-
-        api_key = self.pipeline_config['ai']['dify-service-api']['api-key']
-
-        self.dify_client = client.AsyncDifyServiceClient(
-            api_key=api_key,
-            base_url=self.pipeline_config['ai']['dify-service-api']['base-url'],
-        )
-
-    def _try_convert_thinking(self, resp_text: str) -> str:
-        """尝试转换 Dify 的思考提示"""
-        if not resp_text.startswith(
-            '<details style="color:gray;background-color: #f8f8f8;padding: 8px;border-radius: 4px;" open> <summary> Thinking... </summary>'
-        ):
-            return resp_text
-
-        if self.pipeline_config['ai']['dify-service-api']['thinking-convert'] == 'original':
-            return resp_text
-
-        if self.pipeline_config['ai']['dify-service-api']['thinking-convert'] == 'remove':
-            return re.sub(
-                r'<details style="color:gray;background-color: #f8f8f8;padding: 8px;border-radius: 4px;" open> <summary> Thinking... </summary>.*?</details>',
-                '',
-                resp_text,
-                flags=re.DOTALL,
-            )
-
-        if self.pipeline_config['ai']['dify-service-api']['thinking-convert'] == 'plain':
-            pattern = r'<details style="color:gray;background-color: #f8f8f8;padding: 8px;border-radius: 4px;" open> <summary> Thinking... </summary>(.*?)</details>'
-            thinking_text = re.search(pattern, resp_text, flags=re.DOTALL)
-            content_text = re.sub(pattern, '', resp_text, flags=re.DOTALL)
-            return f'<think>{thinking_text.group(1)}</think>\n{content_text}'
-
-    async def _preprocess_user_message(self, query: pipeline_query.Query) -> tuple[str, list[str]]:
-        """预处理用户消息，提取纯文本，并将图片上传到 Dify 服务
-
-        Returns:
-            tuple[str, list[str]]: 纯文本和图片的 Dify 服务图片 ID
-        """
-        plain_text = ''
-        image_ids = []
-
-        if isinstance(query.user_message.content, list):
-            for ce in query.user_message.content:
-                if ce.type == 'text':
-                    plain_text += ce.text
-                elif ce.type == 'image_base64':
-                    image_b64, image_format = await image.extract_b64_and_format(ce.image_base64)
-                    file_bytes = base64.b64decode(image_b64)
-                    file = ('img.png', file_bytes, f'image/{image_format}')
-                    file_upload_resp = await self.dify_client.upload_file(
-                        file,
-                        f'{query.session.launcher_type.value}_{query.session.launcher_id}',
-                    )
-                    image_id = file_upload_resp['id']
-                    image_ids.append(image_id)
-        elif isinstance(query.user_message.content, str):
-            plain_text = query.user_message.content
-
-        return plain_text, image_ids
-
-    async def _chat_messages(
-        self, query: pipeline_query.Query
-    ) -> typing.AsyncGenerator[provider_message.Message, None]:
-        """调用聊天助手"""
-        cov_id = query.session.using_conversation.uuid or ''
-        query.variables['conversation_id'] = cov_id
-
-        plain_text, image_ids = await self._preprocess_user_message(query)
-
-        files = [
-            {
-                'type': 'image',
-                'transfer_method': 'local_file',
-                'upload_file_id': image_id,
-            }
-            for image_id in image_ids
-        ]
-
-        mode = 'basic'  # 标记是基础编排还是工作流编排
-
-        basic_mode_pending_chunk = ''
-
-        inputs = {}
-
-        inputs.update(query.variables)
-
-        chunk = None  # 初始化chunk变量，防止在没有响应时引用错误
-
-        async for chunk in self.dify_client.chat_messages(
-            inputs=inputs,
-            query=plain_text,
-            user=f'{query.session.launcher_type.value}_{query.session.launcher_id}',
-            conversation_id=cov_id,
-            files=files,
-            timeout=120,
-        ):
-            self.ap.logger.debug('dify-chat-chunk: ' + str(chunk))
-
-            if chunk['event'] == 'workflow_started':
-                mode = 'workflow'
-
-            if mode == 'workflow':
-                if chunk['event'] == 'node_finished':
-                    if chunk['data']['node_type'] == 'answer':
-                        yield provider_message.Message(
-                            role='assistant',
-                            content=self._try_convert_thinking(chunk['data']['outputs']['answer']),
-                        )
-            elif mode == 'basic':
-                if chunk['event'] == 'message':
-                    basic_mode_pending_chunk += chunk['answer']
-                elif chunk['event'] == 'message_end':
-                    yield provider_message.Message(
-                        role='assistant',
-                        content=self._try_convert_thinking(basic_mode_pending_chunk),
-                    )
-                    basic_mode_pending_chunk = ''
-
-        if chunk is None:
-            raise errors.DifyAPIError('Dify API 没有返回任何响应，请检查网络连接和API配置')
-
-        query.session.using_conversation.uuid = chunk['conversation_id']
-
-    async def _agent_chat_messages(
-        self, query: pipeline_query.Query
-    ) -> typing.AsyncGenerator[provider_message.Message, None]:
-        """调用聊天助手"""
-        cov_id = query.session.using_conversation.uuid or ''
-        query.variables['conversation_id'] = cov_id
-
-        plain_text, image_ids = await self._preprocess_user_message(query)
-
-        files = [
-            {
-                'type': 'image',
-                'transfer_method': 'local_file',
-                'upload_file_id': image_id,
-            }
-            for image_id in image_ids
-        ]
-
-        ignored_events = []
-
-        inputs = {}
-
-        inputs.update(query.variables)
-
-        pending_agent_message = ''
-
-        chunk = None  # 初始化chunk变量，防止在没有响应时引用错误
-
-        async for chunk in self.dify_client.chat_messages(
-            inputs=inputs,
-            query=plain_text,
-            user=f'{query.session.launcher_type.value}_{query.session.launcher_id}',
-            response_mode='streaming',
-            conversation_id=cov_id,
-            files=files,
-            timeout=120,
-        ):
-            self.ap.logger.debug('dify-agent-chunk: ' + str(chunk))
-
-            if chunk['event'] in ignored_events:
-                continue
-
-            if chunk['event'] == 'agent_message':
-                pending_agent_message += chunk['answer']
-            else:
-                if pending_agent_message.strip() != '':
-                    pending_agent_message = pending_agent_message.replace('</details>Action:', '</details>')
-                    yield provider_message.Message(
-                        role='assistant',
-                        content=self._try_convert_thinking(pending_agent_message),
-                    )
-                pending_agent_message = ''
-
-                if chunk['event'] == 'agent_thought':
-                    if chunk['tool'] != '' and chunk['observation'] != '':  # 工具调用结果，跳过
-                        continue
-
-                    if chunk['tool']:
-                        msg = provider_message.Message(
-                            role='assistant',
-                            tool_calls=[
-                                provider_message.ToolCall(
-                                    id=chunk['id'],
-                                    type='function',
-                                    function=provider_message.FunctionCall(
-                                        name=chunk['tool'],
-                                        arguments=json.dumps({}),
-                                    ),
-                                )
-                            ],
-                        )
-                        yield msg
-                if chunk['event'] == 'message_file':
-                    if chunk['type'] == 'image' and chunk['belongs_to'] == 'assistant':
-                        base_url = self.dify_client.base_url
-
-                        if base_url.endswith('/v1'):
-                            base_url = base_url[:-3]
-
-                        image_url = base_url + chunk['url']
-
-                        yield provider_message.Message(
-                            role='assistant',
-                            content=[provider_message.ContentElement.from_image_url(image_url)],
-                        )
-                if chunk['event'] == 'error':
-                    raise errors.DifyAPIError('dify 服务错误: ' + chunk['message'])
-
-        if chunk is None:
-            raise errors.DifyAPIError('Dify API 没有返回任何响应，请检查网络连接和API配置')
-
-        query.session.using_conversation.uuid = chunk['conversation_id']
-
-    async def _workflow_messages(
-        self, query: pipeline_query.Query
-    ) -> typing.AsyncGenerator[provider_message.Message, None]:
-        """调用工作流"""
-
-        if not query.session.using_conversation.uuid:
-            query.session.using_conversation.uuid = str(uuid.uuid4())
-
-        query.variables['conversation_id'] = query.session.using_conversation.uuid
-
-        plain_text, image_ids = await self._preprocess_user_message(query)
-
-        files = [
-            {
-                'type': 'image',
-                'transfer_method': 'local_file',
-                'upload_file_id': image_id,
-            }
-            for image_id in image_ids
-        ]
-
-        ignored_events = ['text_chunk', 'workflow_started']
-
-        inputs = {  # these variables are legacy variables, we need to keep them for compatibility
-            'langbot_user_message_text': plain_text,
-            'langbot_session_id': query.variables['session_id'],
-            'langbot_conversation_id': query.variables['conversation_id'],
-            'langbot_msg_create_time': query.variables['msg_create_time'],
-        }
-
-        inputs.update(query.variables)
-
-        async for chunk in self.dify_client.workflow_run(
-            inputs=inputs,
-            user=f'{query.session.launcher_type.value}_{query.session.launcher_id}',
-            files=files,
-            timeout=120,
-        ):
-            self.ap.logger.debug('dify-workflow-chunk: ' + str(chunk))
-            if chunk['event'] in ignored_events:
-                continue
-
-            if chunk['event'] == 'node_started':
-                if chunk['data']['node_type'] == 'start' or chunk['data']['node_type'] == 'end':
-                    continue
-
-                msg = provider_message.Message(
-                    role='assistant',
-                    content=None,
-                    tool_calls=[
-                        provider_message.ToolCall(
-                            id=chunk['data']['node_id'],
-                            type='function',
-                            function=provider_message.FunctionCall(
-                                name=chunk['data']['title'],
-                                arguments=json.dumps({}),
-                            ),
-                        )
-                    ],
-                )
-
-                yield msg
-
-            elif chunk['event'] == 'workflow_finished':
-                if chunk['data']['error']:
-                    raise errors.DifyAPIError(chunk['data']['error'])
-
-                msg = provider_message.Message(
-                    role='assistant',
-                    content=chunk['data']['outputs']['summary'],
-                )
-
-                yield msg
-
-    async def run(self, query: pipeline_query.Query) -> typing.AsyncGenerator[provider_message.Message, None]:
-        """运行请求"""
-        if self.pipeline_config['ai']['dify-service-api']['app-type'] == 'chat':
-            async for msg in self._chat_messages(query):
-                yield msg
-        elif self.pipeline_config['ai']['dify-service-api']['app-type'] == 'agent':
-            async for msg in self._agent_chat_messages(query):
-                yield msg
-        elif self.pipeline_config['ai']['dify-service-api']['app-type'] == 'workflow':
-            async for msg in self._workflow_messages(query):
-                yield msg
-        else:
-            raise errors.DifyAPIError(
-                f'不支持的 Dify 应用类型: {self.pipeline_config["ai"]["dify-service-api"]["app-type"]}'
-            )

pkg/provider/runners/localagent.py

@@ -1,78 +0,0 @@
-from __future__ import annotations
-
-import json
-import typing
-
-from .. import runner
-import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query
-import langbot_plugin.api.entities.builtin.provider.message as provider_message
-
-
-@runner.runner_class('local-agent')
-class LocalAgentRunner(runner.RequestRunner):
-    """本地Agent请求运行器"""
-
-    async def run(self, query: pipeline_query.Query) -> typing.AsyncGenerator[provider_message.Message, None]:
-        """运行请求"""
-        pending_tool_calls = []
-
-        req_messages = query.prompt.messages.copy() + query.messages.copy() + [query.user_message]
-
-        use_llm_model = await self.ap.model_mgr.get_model_by_uuid(query.use_llm_model_uuid)
-
-        # 首次请求
-        msg = await use_llm_model.requester.invoke_llm(
-            query,
-            use_llm_model,
-            req_messages,
-            query.use_funcs,
-            extra_args=use_llm_model.model_entity.extra_args,
-        )
-
-        yield msg
-
-        pending_tool_calls = msg.tool_calls
-
-        req_messages.append(msg)
-
-        # 持续请求，只要还有待处理的工具调用就继续处理调用
-        while pending_tool_calls:
-            for tool_call in pending_tool_calls:
-                try:
-                    func = tool_call.function
-
-                    parameters = json.loads(func.arguments)
-
-                    func_ret = await self.ap.tool_mgr.execute_func_call(func.name, parameters)
-
-                    msg = provider_message.Message(
-                        role='tool',
-                        content=json.dumps(func_ret, ensure_ascii=False),
-                        tool_call_id=tool_call.id,
-                    )
-
-                    yield msg
-
-                    req_messages.append(msg)
-                except Exception as e:
-                    # 工具调用出错，添加一个报错信息到 req_messages
-                    err_msg = provider_message.Message(role='tool', content=f'err: {e}', tool_call_id=tool_call.id)
-
-                    yield err_msg
-
-                    req_messages.append(err_msg)
-
-            # 处理完所有调用，再次请求
-            msg = await use_llm_model.requester.invoke_llm(
-                query,
-                use_llm_model,
-                req_messages,
-                query.use_funcs,
-                extra_args=use_llm_model.model_entity.extra_args,
-            )
-
-            yield msg
-
-            pending_tool_calls = msg.tool_calls
-
-            req_messages.append(msg)

pkg/provider/tools/loaders/mcp.py

@@ -1,158 +0,0 @@
-from __future__ import annotations
-
-import typing
-from contextlib import AsyncExitStack
-
-from mcp import ClientSession, StdioServerParameters
-from mcp.client.stdio import stdio_client
-from mcp.client.sse import sse_client
-
-from .. import loader
-from ....core import app
-import langbot_plugin.api.entities.builtin.resource.tool as resource_tool
-
-
-class RuntimeMCPSession:
-    """运行时 MCP 会话"""
-
-    ap: app.Application
-
-    server_name: str
-
-    server_config: dict
-
-    session: ClientSession
-
-    exit_stack: AsyncExitStack
-
-    functions: list[resource_tool.LLMTool] = []
-
-    def __init__(self, server_name: str, server_config: dict, ap: app.Application):
-        self.server_name = server_name
-        self.server_config = server_config
-        self.ap = ap
-
-        self.session = None
-
-        self.exit_stack = AsyncExitStack()
-        self.functions = []
-
-    async def _init_stdio_python_server(self):
-        server_params = StdioServerParameters(
-            command=self.server_config['command'],
-            args=self.server_config['args'],
-            env=self.server_config['env'],
-        )
-
-        stdio_transport = await self.exit_stack.enter_async_context(stdio_client(server_params))
-
-        stdio, write = stdio_transport
-
-        self.session = await self.exit_stack.enter_async_context(ClientSession(stdio, write))
-
-        await self.session.initialize()
-
-    async def _init_sse_server(self):
-        sse_transport = await self.exit_stack.enter_async_context(
-            sse_client(
-                self.server_config['url'],
-                headers=self.server_config.get('headers', {}),
-                timeout=self.server_config.get('timeout', 10),
-            )
-        )
-
-        sseio, write = sse_transport
-
-        self.session = await self.exit_stack.enter_async_context(ClientSession(sseio, write))
-
-        await self.session.initialize()
-
-    async def initialize(self):
-        self.ap.logger.debug(f'初始化 MCP 会话: {self.server_name} {self.server_config}')
-
-        if self.server_config['mode'] == 'stdio':
-            await self._init_stdio_python_server()
-        elif self.server_config['mode'] == 'sse':
-            await self._init_sse_server()
-        else:
-            raise ValueError(f'无法识别 MCP 服务器类型: {self.server_name}: {self.server_config}')
-
-        tools = await self.session.list_tools()
-
-        self.ap.logger.debug(f'获取 MCP 工具: {tools}')
-
-        for tool in tools.tools:
-
-            async def func(*, _tool=tool, **kwargs):
-                result = await self.session.call_tool(_tool.name, kwargs)
-                if result.isError:
-                    raise Exception(result.content[0].text)
-                return result.content[0].text
-
-            func.__name__ = tool.name
-
-            self.functions.append(
-                resource_tool.LLMTool(
-                    name=tool.name,
-                    human_desc=tool.description,
-                    description=tool.description,
-                    parameters=tool.inputSchema,
-                    func=func,
-                )
-            )
-
-    async def shutdown(self):
-        """关闭工具"""
-        await self.session._exit_stack.aclose()
-
-
-@loader.loader_class('mcp')
-class MCPLoader(loader.ToolLoader):
-    """MCP 工具加载器。
-
-    在此加载器中管理所有与 MCP Server 的连接。
-    """
-
-    sessions: dict[str, RuntimeMCPSession] = {}
-
-    _last_listed_functions: list[resource_tool.LLMTool] = []
-
-    def __init__(self, ap: app.Application):
-        super().__init__(ap)
-        self.sessions = {}
-        self._last_listed_functions = []
-
-    async def initialize(self):
-        for server_config in self.ap.instance_config.data.get('mcp', {}).get('servers', []):
-            if not server_config['enable']:
-                continue
-            session = RuntimeMCPSession(server_config['name'], server_config, self.ap)
-            await session.initialize()
-            # self.ap.event_loop.create_task(session.initialize())
-            self.sessions[server_config['name']] = session
-
-    async def get_tools(self) -> list[resource_tool.LLMTool]:
-        all_functions = []
-
-        for session in self.sessions.values():
-            all_functions.extend(session.functions)
-
-        self._last_listed_functions = all_functions
-
-        return all_functions
-
-    async def has_tool(self, name: str) -> bool:
-        return name in [f.name for f in self._last_listed_functions]
-
-    async def invoke_tool(self, name: str, parameters: dict) -> typing.Any:
-        for server_name, session in self.sessions.items():
-            for function in session.functions:
-                if function.name == name:
-                    return await function.func(**parameters)
-
-        raise ValueError(f'未找到工具: {name}')
-
-    async def shutdown(self):
-        """关闭工具"""
-        for session in self.sessions.values():
-            await session.shutdown()

pkg/storage/mgr.py

@@ -1,21 +0,0 @@
-from __future__ import annotations
-
-
-from ..core import app
-from . import provider
-from .providers import localstorage
-
-
-class StorageMgr:
-    """存储管理器"""
-
-    ap: app.Application
-
-    storage_provider: provider.StorageProvider
-
-    def __init__(self, ap: app.Application):
-        self.ap = ap
-        self.storage_provider = localstorage.LocalStorageProvider(ap)
-
-    async def initialize(self):
-        await self.storage_provider.initialize()

pkg/utils/announce.py

@@ -1,109 +0,0 @@
-from __future__ import annotations
-
-import json
-import typing
-import os
-import base64
-import logging
-
-import pydantic
-import requests
-
-from ..core import app
-
-
-class Announcement(pydantic.BaseModel):
-    """公告"""
-
-    id: int
-
-    time: str
-
-    timestamp: int
-
-    content: str
-
-    enabled: typing.Optional[bool] = True
-
-    def to_dict(self) -> dict:
-        return {
-            'id': self.id,
-            'time': self.time,
-            'timestamp': self.timestamp,
-            'content': self.content,
-            'enabled': self.enabled,
-        }
-
-
-class AnnouncementManager:
-    """公告管理器"""
-
-    ap: app.Application = None
-
-    def __init__(self, ap: app.Application):
-        self.ap = ap
-
-    async def fetch_all(self) -> list[Announcement]:
-        """获取所有公告"""
-        resp = requests.get(
-            url='https://api.github.com/repos/RockChinQ/LangBot/contents/res/announcement.json',
-            proxies=self.ap.proxy_mgr.get_forward_proxies(),
-            timeout=5,
-        )
-        obj_json = resp.json()
-        b64_content = obj_json['content']
-        # 解码
-        content = base64.b64decode(b64_content).decode('utf-8')
-
-        return [Announcement(**item) for item in json.loads(content)]
-
-    async def fetch_saved(self) -> list[Announcement]:
-        if not os.path.exists('data/labels/announcement_saved.json'):
-            with open('data/labels/announcement_saved.json', 'w', encoding='utf-8') as f:
-                f.write('[]')
-
-        with open('data/labels/announcement_saved.json', 'r', encoding='utf-8') as f:
-            content = f.read()
-
-        if not content:
-            content = '[]'
-
-        return [Announcement(**item) for item in json.loads(content)]
-
-    async def write_saved(self, content: list[Announcement]):
-        with open('data/labels/announcement_saved.json', 'w', encoding='utf-8') as f:
-            f.write(json.dumps([item.to_dict() for item in content], indent=4, ensure_ascii=False))
-
-    async def fetch_new(self) -> list[Announcement]:
-        """获取新公告"""
-        all = await self.fetch_all()
-        saved = await self.fetch_saved()
-
-        to_show: list[Announcement] = []
-
-        for item in all:
-            # 遍历saved检查是否有相同id的公告
-            for saved_item in saved:
-                if saved_item.id == item.id:
-                    break
-            else:
-                if item.enabled:
-                    # 没有相同id的公告
-                    to_show.append(item)
-
-        await self.write_saved(all)
-        return to_show
-
-    async def show_announcements(self) -> typing.Tuple[str, int]:
-        """显示公告"""
-        try:
-            announcements = await self.fetch_new()
-            ann_text = ''
-            for ann in announcements:
-                ann_text += f'[公告] {ann.time}: {ann.content}\n'
-
-            # TODO statistics
-
-            return ann_text, logging.INFO
-        except Exception as e:
-            return f'获取公告时出错: {e}', logging.WARNING

pkg/utils/constants.py

@@ -1,8 +0,0 @@
-semantic_version = 'v4.3.0.beta3'
-
-required_database_version = 5
-"""标记本版本所需要的数据库结构版本，用于判断数据库迁移"""
-
-debug_mode = False
-
-edition = 'community'

pyproject.toml

@@ -1,9 +1,10 @@
 [project]
 name = "langbot"
-version = "4.3.0.beta3"
-description = "高稳定、支持扩展、多模态 - 大模型原生即时通信机器人平台"
+version = "4.5.3"
+description = "Easy-to-use global IM bot platform designed for LLM era"
 readme = "README.md"
-requires-python = ">=3.10.1"
+license-files = ["LICENSE"]
+requires-python = ">=3.10.1,<4.0"
 dependencies = [
     "aiocqhttp>=1.4.4",
     "aiofiles>=24.1.0",
@@ -19,6 +20,7 @@ dependencies = [
     "dashscope>=1.23.2",
     "dingtalk-stream>=0.24.0",
     "discord-py>=2.5.2",
+    "pynacl>=1.5.0", # Required for Discord voice support
     "gewechat-client>=0.1.5",
     "lark-oapi>=1.4.15",
     "mcp>=1.8.1",
@@ -44,13 +46,28 @@ dependencies = [
     "urllib3>=2.4.0",
     "websockets>=15.0.1",
     "python-socks>=2.7.1", # dingtalk missing dependency
-    "taskgroup==0.0.0a4", # graingert/taskgroup#20
     "pip>=25.1.1",
     "ruff>=0.11.9",
     "pre-commit>=4.2.0",
     "uv>=0.7.11",
     "mypy>=1.16.0",
-    "langbot-plugin==0.1.1b2",
+    "PyPDF2>=3.0.1",
+    "python-docx>=1.1.0",
+    "pandas>=2.2.2",
+    "chardet>=5.2.0",
+    "markdown>=3.6",
+    "beautifulsoup4>=4.12.3",
+    "ebooklib>=0.18",
+    "html2text>=2024.2.26",
+    "langchain>=0.2.0",
+    "langchain-text-splitters>=0.0.1",
+    "chromadb>=0.4.24",
+    "qdrant-client (>=1.15.1,<2.0.0)",
+    "langbot-plugin==0.1.11",
+    "asyncpg>=0.30.0",
+    "line-bot-sdk>=3.19.0",
+    "tboxsdk>=0.0.10",
+    "boto3>=1.35.0",
 ]
 keywords = [
     "bot",
@@ -68,11 +85,10 @@ keywords = [
     "onebot",
 ]
 classifiers = [
-    "Development Status :: 3 - Alpha",
+    "Development Status :: 5 - Production/Stable",
     "Framework :: AsyncIO",
     "Framework :: Robot Framework",
     "Framework :: Robot Framework :: Library",
-    "License :: OSI Approved :: AGPL-3 License",
     "Operating System :: OS Independent",
     "Programming Language :: Python :: 3",
     "Topic :: Communications :: Chat",
@@ -81,11 +97,24 @@ classifiers = [
 [project.urls]
 Homepage = "https://langbot.app"
 Documentation = "https://docs.langbot.app"
-Repository = "https://github.com/RockChinQ/langbot"
+Repository = "https://github.com/langbot-app/LangBot"
+
+[project.scripts]
+langbot = "langbot.__main__:main"
+
+[build-system]
+requires = ["setuptools>=61.0", "wheel"]
+build-backend = "setuptools.build_meta"
+
+[tool.setuptools]
+package-data = { "langbot" = ["templates/**", "pkg/provider/modelmgr/requesters/*", "pkg/platform/sources/*", "web/out/**"] }
 
 [dependency-groups]
 dev = [
     "pre-commit>=4.2.0",
+    "pytest>=8.4.1",
+    "pytest-asyncio>=1.0.0",
+    "pytest-cov>=7.0.0",
     "ruff>=0.11.9",
 ]
 

pytest.ini

@@ -0,0 +1,39 @@
+[pytest]
+# Test discovery patterns
+python_files = test_*.py
+python_classes = Test*
+python_functions = test_*
+
+# Test paths
+testpaths = tests
+
+# Asyncio configuration
+asyncio_mode = auto
+
+# Output options
+addopts =
+    -v
+    --strict-markers
+    --tb=short
+    --disable-warnings
+
+# Markers
+markers =
+    asyncio: mark test as async
+    unit: mark test as unit test
+    integration: mark test as integration test
+    slow: mark test as slow running
+
+# Coverage options (when using pytest-cov)
+[coverage:run]
+source = langbot.pkg
+omit =
+    */tests/*
+    */test_*.py
+    */__pycache__/*
+    */site-packages/*
+
+[coverage:report]
+precision = 2
+show_missing = True
+skip_covered = False

run_tests.sh

@@ -0,0 +1,31 @@
+#!/bin/bash
+
+# Script to run all unit tests
+# This script helps avoid circular import issues by setting up the environment properly
+
+set -e
+
+echo "Setting up test environment..."
+
+# Activate virtual environment if it exists
+if [ -d ".venv" ]; then
+    source .venv/bin/activate
+fi
+
+# Check if pytest is installed
+if ! command -v pytest &> /dev/null; then
+    echo "Installing test dependencies..."
+    pip install pytest pytest-asyncio pytest-cov
+fi
+
+echo "Running all unit tests..."
+
+# Run tests with coverage
+pytest tests/unit_tests/ -v --tb=short \
+    --cov=pkg \
+    --cov-report=xml \
+    "$@"
+
+echo ""
+echo "Test run complete!"
+echo "Coverage report saved to coverage.xml"

src/langbot/__init__.py

@@ -0,0 +1,3 @@
+"""LangBot - Easy-to-use global IM bot platform designed for LLM era"""
+
+__version__ = '4.5.3'

src/langbot/__main__.py

@@ -0,0 +1,104 @@
+"""LangBot entry point for package execution"""
+
+import asyncio
+import argparse
+import sys
+import os
+
+# ASCII art banner
+asciiart = r"""
+ _                   ___      _   
+| |   __ _ _ _  __ _| _ ) ___| |_ 
+| |__/ _` | ' \/ _` | _ \/ _ \  _|
+|____\__,_|_||_\__, |___/\___/\__|
+               |___/              
+
+⭐️ Open Source 开源地址: https://github.com/langbot-app/LangBot
+📖 Documentation 文档地址: https://docs.langbot.app
+"""
+
+
+async def main_entry(loop: asyncio.AbstractEventLoop):
+    """Main entry point for LangBot"""
+    parser = argparse.ArgumentParser(description='LangBot')
+    parser.add_argument(
+        '--standalone-runtime',
+        action='store_true',
+        help='Use standalone plugin runtime / 使用独立插件运行时',
+        default=False,
+    )
+    parser.add_argument('--debug', action='store_true', help='Debug mode / 调试模式', default=False)
+    args = parser.parse_args()
+
+    if args.standalone_runtime:
+        from langbot.pkg.utils import platform
+
+        platform.standalone_runtime = True
+
+    if args.debug:
+        from langbot.pkg.utils import constants
+
+        constants.debug_mode = True
+
+    print(asciiart)
+
+    # Check dependencies
+    from langbot.pkg.core.bootutils import deps
+
+    missing_deps = await deps.check_deps()
+
+    if missing_deps:
+        print('以下依赖包未安装，将自动安装，请完成后重启程序：')
+        print(
+            'These dependencies are missing, they will be installed automatically, please restart the program after completion:'
+        )
+        for dep in missing_deps:
+            print('-', dep)
+        await deps.install_deps(missing_deps)
+        print('已自动安装缺失的依赖包，请重启程序。')
+        print('The missing dependencies have been installed automatically, please restart the program.')
+        sys.exit(0)
+
+    # Check configuration files
+    from langbot.pkg.core.bootutils import files
+
+    generated_files = await files.generate_files()
+
+    if generated_files:
+        print('以下文件不存在，已自动生成：')
+        print('Following files do not exist and have been automatically generated:')
+        for file in generated_files:
+            print('-', file)
+
+    from langbot.pkg.core import boot
+
+    await boot.main(loop)
+
+
+def main():
+    """Main function to be called by console script entry point"""
+    # Check Python version
+    if sys.version_info < (3, 10, 1):
+        print('需要 Python 3.10.1 及以上版本，当前 Python 版本为：', sys.version)
+        print('Your Python version is not supported.')
+        print('Python 3.10.1 or higher is required. Current version:', sys.version)
+        sys.exit(1)
+
+    # Set up the working directory
+    # When installed as a package, we need to handle the working directory differently
+    # We'll create data directory in current working directory if not exists
+    os.makedirs('data', exist_ok=True)
+
+    loop = asyncio.new_event_loop()
+
+    try:
+        loop.run_until_complete(main_entry(loop))
+    except KeyboardInterrupt:
+        print('\n正在退出...')
+        print('Exiting...')
+    finally:
+        loop.close()
+
+
+if __name__ == '__main__':
+    main()

src/langbot/libs/coze_server_api/client.py

@@ -0,0 +1,177 @@
+import json
+import asyncio
+import aiohttp
+import io
+from typing import Dict, List, Any, AsyncGenerator
+import os
+from pathlib import Path
+
+
+class AsyncCozeAPIClient:
+    def __init__(self, api_key: str, api_base: str = 'https://api.coze.cn'):
+        self.api_key = api_key
+        self.api_base = api_base
+        self.session = None
+
+    async def __aenter__(self):
+        """支持异步上下文管理器"""
+        await self.coze_session()
+        return self
+
+    async def __aexit__(self, exc_type, exc_val, exc_tb):
+        """退出时自动关闭会话"""
+        await self.close()
+
+    async def coze_session(self):
+        """确保HTTP session存在"""
+        if self.session is None:
+            connector = aiohttp.TCPConnector(
+                ssl=False if self.api_base.startswith('http://') else True,
+                limit=100,
+                limit_per_host=30,
+                keepalive_timeout=30,
+                enable_cleanup_closed=True,
+            )
+            timeout = aiohttp.ClientTimeout(
+                total=120,  # 默认超时时间
+                connect=30,
+                sock_read=120,
+            )
+            headers = {
+                'Authorization': f'Bearer {self.api_key}',
+                'Accept': 'text/event-stream',
+            }
+            self.session = aiohttp.ClientSession(headers=headers, timeout=timeout, connector=connector)
+        return self.session
+
+    async def close(self):
+        """显式关闭会话"""
+        if self.session and not self.session.closed:
+            await self.session.close()
+            self.session = None
+
+    async def upload(
+        self,
+        file,
+    ) -> str:
+        # 处理 Path 对象
+        if isinstance(file, Path):
+            if not file.exists():
+                raise ValueError(f'File not found: {file}')
+            with open(file, 'rb') as f:
+                file = f.read()
+
+        # 处理文件路径字符串
+        elif isinstance(file, str):
+            if not os.path.isfile(file):
+                raise ValueError(f'File not found: {file}')
+            with open(file, 'rb') as f:
+                file = f.read()
+
+        # 处理文件对象
+        elif hasattr(file, 'read'):
+            file = file.read()
+
+        session = await self.coze_session()
+        url = f'{self.api_base}/v1/files/upload'
+
+        try:
+            file_io = io.BytesIO(file)
+            async with session.post(
+                url,
+                data={
+                    'file': file_io,
+                },
+                timeout=aiohttp.ClientTimeout(total=60),
+            ) as response:
+                if response.status == 401:
+                    raise Exception('Coze API 认证失败，请检查 API Key 是否正确')
+
+                response_text = await response.text()
+
+                if response.status != 200:
+                    raise Exception(f'文件上传失败，状态码: {response.status}, 响应: {response_text}')
+                try:
+                    result = await response.json()
+                except json.JSONDecodeError:
+                    raise Exception(f'文件上传响应解析失败: {response_text}')
+
+                if result.get('code') != 0:
+                    raise Exception(f'文件上传失败: {result.get("msg", "未知错误")}')
+
+                file_id = result['data']['id']
+                return file_id
+
+        except asyncio.TimeoutError:
+            raise Exception('文件上传超时')
+        except Exception as e:
+            raise Exception(f'文件上传失败: {str(e)}')
+
+    async def chat_messages(
+        self,
+        bot_id: str,
+        user_id: str,
+        additional_messages: List[Dict] | None = None,
+        conversation_id: str | None = None,
+        auto_save_history: bool = True,
+        stream: bool = True,
+        timeout: float = 120,
+    ) -> AsyncGenerator[Dict[str, Any], None]:
+        """发送聊天消息并返回流式响应
+
+        Args:
+            bot_id: Bot ID
+            user_id: 用户ID
+            additional_messages: 额外消息列表
+            conversation_id: 会话ID
+            auto_save_history: 是否自动保存历史
+            stream: 是否流式响应
+            timeout: 超时时间
+        """
+        session = await self.coze_session()
+        url = f'{self.api_base}/v3/chat'
+
+        payload = {
+            'bot_id': bot_id,
+            'user_id': user_id,
+            'stream': stream,
+            'auto_save_history': auto_save_history,
+        }
+
+        if additional_messages:
+            payload['additional_messages'] = additional_messages
+
+        params = {}
+        if conversation_id:
+            params['conversation_id'] = conversation_id
+
+        try:
+            async with session.post(
+                url,
+                json=payload,
+                params=params,
+                timeout=aiohttp.ClientTimeout(total=timeout),
+            ) as response:
+                if response.status == 401:
+                    raise Exception('Coze API 认证失败，请检查 API Key 是否正确')
+
+                if response.status != 200:
+                    raise Exception(f'Coze API 流式请求失败，状态码: {response.status}')
+
+                async for chunk in response.content:
+                    chunk = chunk.decode('utf-8')
+                    if chunk != '\n':
+                        if chunk.startswith('event:'):
+                            chunk_type = chunk.replace('event:', '', 1).strip()
+                        elif chunk.startswith('data:'):
+                            chunk_data = chunk.replace('data:', '', 1).strip()
+                    else:
+                        yield {
+                            'event': chunk_type,
+                            'data': json.loads(chunk_data) if chunk_data else {},
+                        }  # 处理本地部署时，接口返回的data为空值
+
+        except asyncio.TimeoutError:
+            raise Exception(f'Coze API 流式请求超时 ({timeout}秒)')
+        except Exception as e:
+            raise Exception(f'Coze API 流式请求失败: {str(e)}')

src/langbot/libs/dify_service_api/v1/client.py

@@ -5,6 +5,8 @@ import typing
 import json
 
 from .errors import DifyAPIError
+from pathlib import Path
+import os
 
 
 class AsyncDifyServiceClient:
@@ -109,7 +111,23 @@ class AsyncDifyServiceClient:
         user: str,
         timeout: float = 30.0,
     ) -> str:
-        """上传文件"""
+        # 处理 Path 对象
+        if isinstance(file, Path):
+            if not file.exists():
+                raise ValueError(f'File not found: {file}')
+            with open(file, 'rb') as f:
+                file = f.read()
+
+        # 处理文件路径字符串
+        elif isinstance(file, str):
+            if not os.path.isfile(file):
+                raise ValueError(f'File not found: {file}')
+            with open(file, 'rb') as f:
+                file = f.read()
+
+        # 处理文件对象
+        elif hasattr(file, 'read'):
+            file = file.read()
         async with httpx.AsyncClient(
             base_url=self.base_url,
             trust_env=True,
@@ -121,6 +139,8 @@ class AsyncDifyServiceClient:
                 headers={'Authorization': f'Bearer {self.api_key}'},
                 files={
                     'file': file,
+                },
+                data={
                     'user': (None, user),
                 },
             )

src/langbot/libs/dingtalk_api/api.py

@@ -110,6 +110,24 @@ class DingTalkClient:
             else:
                 raise Exception(f'Error: {response.status_code}, {response.text}')
 
+    async def get_file_url(self, download_code: str):
+        if not await self.check_access_token():
+            await self.get_access_token()
+        url = 'https://api.dingtalk.com/v1.0/robot/messageFiles/download'
+        params = {'downloadCode': download_code, 'robotCode': self.robot_code}
+        headers = {'x-acs-dingtalk-access-token': self.access_token}
+        async with httpx.AsyncClient() as client:
+            response = await client.post(url, headers=headers, json=params)
+            if response.status_code == 200:
+                result = response.json()
+                download_url = result.get('downloadUrl')
+                if download_url:
+                    return download_url
+                else:
+                    await self.logger.error(f'failed to get file: {response.json()}')
+            else:
+                raise Exception(f'Error: {response.status_code}, {response.text}')
+
     async def update_incoming_message(self, message):
         """异步更新 DingTalkClient 中的 incoming_message"""
         message_data = await self.get_message(message)
@@ -170,12 +188,69 @@ class DingTalkClient:
 
             if incoming_message.message_type == 'richText':
                 data = incoming_message.rich_text_content.to_dict()
+
+                # 使用统一的结构化数据格式，保持顺序
+                rich_content = {
+                    'Type': 'richText',
+                    'Elements': [],  # 按顺序存储所有元素
+                    'SimpleContent': '',  # 兼容字段：纯文本内容
+                    'SimplePicture': '',  # 兼容字段：第一张图片
+                }
+
+                # 先收集所有文本和图片占位符
+                text_elements = []
+
+                # 解析富文本内容，保持原始顺序
                 for item in data['richText']:
-                    if 'text' in item:
-                        message_data['Content'] = item['text']
-                    if incoming_message.get_image_list()[0]:
-                        message_data['Picture'] = await self.download_image(incoming_message.get_image_list()[0])
-                message_data['Type'] = 'text'
+                    # 处理文本内容
+                    if 'text' in item and item['text'] != '\n':
+                        element = {'Type': 'text', 'Content': item['text']}
+                        rich_content['Elements'].append(element)
+                        text_elements.append(item['text'])
+
+                    # 检查是否是图片元素 - 根据钉钉API的实际结构调整
+                    # 钉钉富文本中的图片通常有特定标识，可能需要根据实际返回调整
+                    elif item.get('type') == 'picture':
+                        # 创建图片占位符
+                        element = {
+                            'Type': 'image_placeholder',
+                        }
+                        rich_content['Elements'].append(element)
+
+                # 获取并下载所有图片
+                image_list = incoming_message.get_image_list()
+                if image_list:
+                    new_elements = []
+                    image_index = 0
+
+                    for element in rich_content['Elements']:
+                        if element['Type'] == 'image_placeholder':
+                            if image_index < len(image_list) and image_list[image_index]:
+                                image_url = await self.download_image(image_list[image_index])
+                                new_elements.append({'Type': 'image', 'Picture': image_url})
+                                image_index += 1
+                            else:
+                                # 如果没有对应的图片，保留占位符或跳过
+                                continue
+                        else:
+                            new_elements.append(element)
+
+                    rich_content['Elements'] = new_elements
+
+                # 设置兼容字段
+                all_texts = [elem['Content'] for elem in rich_content['Elements'] if elem.get('Type') == 'text']
+                rich_content['SimpleContent'] = '\n'.join(all_texts) if all_texts else ''
+
+                all_images = [elem['Picture'] for elem in rich_content['Elements'] if elem.get('Type') == 'image']
+                if all_images:
+                    rich_content['SimplePicture'] = all_images[0]
+                    rich_content['AllImages'] = all_images  # 所有图片的列表
+
+                # 设置原始的 content 和 picture 字段以保持兼容
+                message_data['Content'] = rich_content['SimpleContent']
+                message_data['Rich_Content'] = rich_content
+                if all_images:
+                    message_data['Picture'] = all_images[0]
 
             elif incoming_message.message_type == 'text':
                 message_data['Content'] = incoming_message.get_text_list()[0]
@@ -189,6 +264,17 @@ class DingTalkClient:
                 message_data['Audio'] = await self.get_audio_url(incoming_message.to_dict()['content']['downloadCode'])
 
                 message_data['Type'] = 'audio'
+            elif incoming_message.message_type == 'file':
+                down_list = incoming_message.get_down_list()
+                if len(down_list) >= 2:
+                    message_data['File'] = await self.get_file_url(down_list[0])
+                    message_data['Name'] = down_list[1]
+                else:
+                    if self.logger:
+                        await self.logger.error(f'get_down_list() returned fewer than 2 elements: {down_list}')
+                    message_data['File'] = None
+                    message_data['Name'] = None
+                message_data['Type'] = 'file'
 
             copy_message_data = message_data.copy()
             del copy_message_data['IncomingMessage']
@@ -253,6 +339,43 @@ class DingTalkClient:
             await self.logger.error(f'failed to send proactive massage to group: {traceback.format_exc()}')
             raise Exception(f'failed to send proactive massage to group: {traceback.format_exc()}')
 
+    async def create_and_card(
+        self, temp_card_id: str, incoming_message: dingtalk_stream.ChatbotMessage, quote_origin: bool = False
+    ):
+        content_key = 'content'
+        card_data = {content_key: ''}
+
+        card_instance = dingtalk_stream.AICardReplier(self.client, incoming_message)
+        # print(card_instance)
+        # 先投放卡片: https://open.dingtalk.com/document/orgapp/create-and-deliver-cards
+        card_instance_id = await card_instance.async_create_and_deliver_card(
+            temp_card_id,
+            card_data,
+        )
+        return card_instance, card_instance_id
+
+    async def send_card_message(self, card_instance, card_instance_id: str, content: str, is_final: bool):
+        content_key = 'content'
+        try:
+            await card_instance.async_streaming(
+                card_instance_id,
+                content_key=content_key,
+                content_value=content,
+                append=False,
+                finished=is_final,
+                failed=False,
+            )
+        except Exception as e:
+            self.logger.exception(e)
+            await card_instance.async_streaming(
+                card_instance_id,
+                content_key=content_key,
+                content_value='',
+                append=False,
+                finished=is_final,
+                failed=True,
+            )
+
     async def start(self):
         """启动 WebSocket 连接，监听消息"""
         await self.client.start()

src/langbot/libs/dingtalk_api/dingtalkevent.py

@@ -15,6 +15,10 @@ class DingTalkEvent(dict):
     def content(self):
         return self.get('Content', '')
 
+    @property
+    def rich_content(self):
+        return self.get('Rich_Content', '')
+
     @property
     def incoming_message(self) -> Optional['dingtalk_stream.chatbot.ChatbotMessage']:
         return self.get('IncomingMessage')
@@ -31,6 +35,14 @@ class DingTalkEvent(dict):
     def audio(self):
         return self.get('Audio', '')
 
+    @property
+    def file(self):
+        return self.get('File', '')
+
+    @property
+    def name(self):
+        return self.get('Name', '')
+
     @property
     def conversation(self):
         return self.get('conversation_type', '')