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21 Commits

Author SHA1 Message Date
copilot-swe-agent[bot]
817ef94742 Implement Telegram topic isolation feature - share conversations across topics
Co-authored-by: Soulter <37870767+Soulter@users.noreply.github.com>
2025-08-16 16:30:18 +00:00
copilot-swe-agent[bot]
10e91fe375 Initial plan 2025-08-16 16:18:47 +00:00
Soulter
02a9769b35 fix: 补充工具调用轮数上限配置 2025-08-14 23:51:22 +08:00
Soulter
7640f11bfc docs: update readme 2025-08-14 17:28:51 +08:00
Soulter
9fa44dbcfa docs: update readme 2025-08-14 14:16:22 +08:00
Copilot
2cae941bae Fix incomplete Gemini streaming responses in chat history (#2429)
* Initial plan

* Fix incomplete Gemini streaming responses in chat history

Co-authored-by: Soulter <37870767+Soulter@users.noreply.github.com>

---------

Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: Soulter <37870767+Soulter@users.noreply.github.com>
Co-authored-by: Raven95676 <Raven95676@gmail.com>
2025-08-14 11:56:50 +08:00
Copilot
bc0784f41d fix: enable_thinking parameter for qwen3 models in non-streaming calls (#2424)
* Initial plan

* Fix ModelScope enable_thinking parameter for non-streaming calls

Co-authored-by: Soulter <37870767+Soulter@users.noreply.github.com>

* Tighten enable_thinking condition to only Qwen/Qwen3 models

Co-authored-by: Soulter <37870767+Soulter@users.noreply.github.com>

* qwen3 model handle

* Update astrbot/core/provider/sources/openai_source.py

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

---------

Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: Soulter <37870767+Soulter@users.noreply.github.com>
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
2025-08-14 11:18:29 +08:00
Copilot
c57d75e01a feat: add comprehensive GitHub Copilot instructions for AstrBot development (#2426)
* Initial plan

* Initial progress - completed repository exploration and dependency installation

Co-authored-by: Soulter <37870767+Soulter@users.noreply.github.com>

* Complete copilot-instructions.md with comprehensive development guide

Co-authored-by: Soulter <37870767+Soulter@users.noreply.github.com>

* Update copilot-instructions.md

---------

Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: Soulter <37870767+Soulter@users.noreply.github.com>
2025-08-13 23:31:28 +08:00
RC-CHN
73edeae013 perf: 优化hint渲染方式,为部分类型供应商添加默认的温度选项 (#2321)
* feat:为webchat页面添加一个手动上传文件按钮(目前只处理图片)

* fix:上传后清空value,允许触发change事件以多次上传同一张图片

* perf:webchat页面消息发送后清空图片预览缩略图,维持与文本信息行为一致

* perf:将文件输入的值重置为空字符串以提升浏览器兼容性

* feat:webchat文件上传按钮支持多选文件上传

* fix:释放blob URL以防止内存泄漏

* perf:并行化sendMessage中的图片获取逻辑

* perf:优化hint渲染方式,为部分类型供应商添加默认的温度选项
2025-08-12 21:53:06 +08:00
MUKAPP
7d46314dc8 fix: 修复注册文件时由于 file:/// 前缀,导致文件被误判为不存在的问题 (#2325)
fixes #2222
2025-08-12 21:47:31 +08:00
你们的饺子
d5a53a89eb fix: 修复插件的 terminate 无法被正常调用的问题 (#2352) 2025-08-12 21:41:19 +08:00
dependabot[bot]
a85bc510dd chore(deps): bump actions/checkout in the github-actions group (#2400)
Bumps the github-actions group with 1 update: [actions/checkout](https://github.com/actions/checkout).


Updates `actions/checkout` from 4 to 5
- [Release notes](https://github.com/actions/checkout/releases)
- [Changelog](https://github.com/actions/checkout/blob/main/CHANGELOG.md)
- [Commits](https://github.com/actions/checkout/compare/v4...v5)

---
updated-dependencies:
- dependency-name: actions/checkout
  dependency-version: '5'
  dependency-type: direct:production
  update-type: version-update:semver-major
  dependency-group: github-actions
...

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
2025-08-12 15:15:28 +08:00
Soulter
2beea7d218 📦 release: v3.5.24 2025-08-07 20:36:59 +08:00
Soulter
a93cd3dd5f feat: compshare provider 2025-08-07 20:25:45 +08:00
Soulter
db4d02c2e2 docs: add 1panel deployment method 2025-08-02 19:01:49 +08:00
Soulter
fd7811402b fix: 添加对 metadata 中 description 字段的支持,确保元数据完整性
fixes: #2245
2025-08-02 16:01:10 +08:00
你们的饺子
eb0325e627 fix: 修复了 OpenAI 类型的 LLM 空内容响应导致的无法解析 completion 的错误。 (#2279) 2025-08-02 15:46:11 +08:00
IGCrystal
8b4b04ec09 fix(i18n): add missing noTemplates key (#2292) 2025-08-02 14:16:59 +08:00
Larch-C
9f32c9280f chore: update and rename PLUGIN_PUBLISH.md to PLUGIN_PUBLISH.yml (#2289) 2025-08-02 14:16:19 +08:00
yrk111222
4fcd09cfa8 feat: add ModelScope API support (#2230)
* add ModelScope API support

* update
2025-08-02 14:14:08 +08:00
Misaka Mikoto
7a8d65d37d feat: add plugins local cache and remote file MD5 validation (#2211)
* 修改openai的嵌入模型默认维度为1024

* 为插件市场添加本地缓存
- 优先使用api获取,获取失败时则使用本地缓存
- 每次获取后会更新本地缓存
- 如果获取结果为空,判定为获取失败,使用本地缓存
- 前端页面添加刷新按钮,用于手动刷新本地缓存

* feat: 增强插件市场缓存机制,支持MD5校验以确保数据有效性

---------

Co-authored-by: Soulter <905617992@qq.com>
2025-08-02 14:03:53 +08:00
33 changed files with 826 additions and 615 deletions

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@@ -1,31 +0,0 @@
---
name: '🥳 发布插件'
title: "[Plugin] 插件名"
about: 提交插件到插件市场
labels: [ "plugin-publish" ]
assignees: ''
---
欢迎发布插件到插件市场!
## 插件基本信息
请将插件信息填写到下方的 Json 代码块中。`tags`(插件标签)和 `social_link`(社交链接)选填。
```json
{
"name": "插件名",
"desc": "插件介绍",
"author": "作者名",
"repo": "插件仓库链接",
"tags": [],
"social_link": ""
}
```
## 检查
- [ ] 我的插件经过完整的测试
- [ ] 我的插件不包含恶意代码
- [ ] 我已阅读并同意遵守该项目的 [行为准则](https://docs.github.com/zh/site-policy/github-terms/github-community-code-of-conduct)。

View File

@@ -0,0 +1,56 @@
name: 🥳 发布插件
description: 提交插件到插件市场
title: "[Plugin] 插件名"
labels: ["plugin-publish"]
assignees: []
body:
- type: markdown
attributes:
value: |
欢迎发布插件到插件市场!
- type: markdown
attributes:
value: |
## 插件基本信息
请将插件信息填写到下方的 JSON 代码块中。其中 `tags`(插件标签)和 `social_link`(社交链接)选填。
不熟悉 JSON ?现在可以从 [这里](https://plugins.astrbot.app/#/submit) 获取你的 JSON 啦!获取到了记得复制粘贴过来哦!
- type: textarea
id: plugin-info
attributes:
label: 插件信息
description: 请在下方代码块中填写您的插件信息确保反引号包裹了JSON
value: |
```json
{
"name": "插件名",
"desc": "插件介绍",
"author": "作者名",
"repo": "插件仓库链接",
"tags": [],
"social_link": ""
}
```
validations:
required: true
- type: markdown
attributes:
value: |
## 检查
- type: checkboxes
id: checks
attributes:
label: 插件检查清单
description: 请确认以下所有项目
options:
- label: 我的插件经过完整的测试
required: true
- label: 我的插件不包含恶意代码
required: true
- label: 我已阅读并同意遵守该项目的 [行为准则](https://docs.github.com/zh/site-policy/github-terms/github-community-code-of-conduct)。
required: true

63
.github/copilot-instructions.md vendored Normal file
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@@ -0,0 +1,63 @@
# AstrBot Development Instructions
AstrBot is a multi-platform LLM chatbot and development framework written in Python with a Vue.js dashboard. It supports multiple messaging platforms (QQ, Telegram, Discord, etc.) and various LLM providers (OpenAI, Anthropic, Google Gemini, etc.).
Always reference these instructions first and fallback to search or bash commands only when you encounter unexpected information that does not match the info here.
## Working Effectively
### Bootstrap and Install Dependencies
- **Python 3.10+ required** - Check `.python-version` file
- Install UV package manager: `pip install uv`
- Install project dependencies: `uv sync` -- takes 6-7 minutes. NEVER CANCEL. Set timeout to 10+ minutes.
- Create required directories: `mkdir -p data/plugins data/config data/temp`
### Running the Application
- Run main application: `uv run main.py` -- starts in ~3 seconds
- Application creates WebUI on http://localhost:6185 (default credentials: `astrbot`/`astrbot`)
- Application loads plugins automatically from `packages/` and `data/plugins/` directories
### Dashboard Build (Vue.js/Node.js)
- **Prerequisites**: Node.js 20+ and npm 10+ required
- Navigate to dashboard: `cd dashboard`
- Install dashboard dependencies: `npm install` -- takes 2-3 minutes. NEVER CANCEL. Set timeout to 5+ minutes.
- Build dashboard: `npm run build` -- takes 25-30 seconds. NEVER CANCEL.
- Dashboard creates optimized production build in `dashboard/dist/`
### Testing
- Do not generate test files for now.
### Code Quality and Linting
- Install ruff linter: `uv add --dev ruff`
- Check code style: `uv run ruff check .` -- takes <1 second
- Check formatting: `uv run ruff format --check .` -- takes <1 second
- Fix formatting: `uv run ruff format .`
- **ALWAYS** run `uv run ruff check .` and `uv run ruff format .` before committing changes
### Plugin Development
- Plugins load from `packages/` (built-in) and `data/plugins/` (user-installed)
- Plugin system supports function tools and message handlers
- Key plugins: python_interpreter, web_searcher, astrbot, reminder, session_controller
### Common Issues and Workarounds
- **Dashboard download fails**: Known issue with "division by zero" error - application still works
- **Import errors in tests**: Ensure `uv run` is used to run tests in proper environment
=- **Build timeouts**: Always set appropriate timeouts (10+ minutes for uv sync, 5+ minutes for npm install)
## CI/CD Integration
- GitHub Actions workflows in `.github/workflows/`
- Docker builds supported via `Dockerfile`
- Pre-commit hooks enforce ruff formatting and linting
## Docker Support
- Primary deployment method: `docker run soulter/astrbot:latest`
- Compose file available: `compose.yml`
- Exposes ports: 6185 (WebUI), 6195 (WeChat), 6199 (QQ), etc.
- Volume mount required: `./data:/AstrBot/data`
## Multi-language Support
- Documentation in Chinese (README.md), English (README_en.md), Japanese (README_ja.md)
- UI supports internationalization
- Default language is Chinese
Remember: This is a production chatbot framework with real users. Always test thoroughly and ensure changes don't break existing functionality.

View File

@@ -13,7 +13,7 @@ jobs:
contents: write
steps:
- name: Checkout repository
uses: actions/checkout@v4
uses: actions/checkout@v5
- name: Dashboard Build
run: |
@@ -70,7 +70,7 @@ jobs:
needs: build-and-publish-to-github-release
steps:
- name: Checkout repository
uses: actions/checkout@v4
uses: actions/checkout@v5
- name: Set up Python
uses: actions/setup-python@v5

View File

@@ -56,7 +56,7 @@ jobs:
# your codebase is analyzed, see https://docs.github.com/en/code-security/code-scanning/creating-an-advanced-setup-for-code-scanning/codeql-code-scanning-for-compiled-languages
steps:
- name: Checkout repository
uses: actions/checkout@v4
uses: actions/checkout@v5
# Initializes the CodeQL tools for scanning.
- name: Initialize CodeQL

View File

@@ -17,7 +17,7 @@ jobs:
runs-on: ubuntu-latest
steps:
- name: Checkout
uses: actions/checkout@v4
uses: actions/checkout@v5
with:
fetch-depth: 0

View File

@@ -11,7 +11,7 @@ jobs:
runs-on: ubuntu-latest
steps:
- name: Checkout repository
uses: actions/checkout@v4
uses: actions/checkout@v5
- name: npm install, build
run: |

View File

@@ -12,7 +12,7 @@ jobs:
steps:
- name: Pull The Codes
uses: actions/checkout@v4
uses: actions/checkout@v5
with:
fetch-depth: 0 # Must be 0 so we can fetch tags

View File

@@ -27,57 +27,50 @@ _✨ 易上手的多平台 LLM 聊天机器人及开发框架 ✨_
AstrBot 是一个松耦合、异步、支持多消息平台部署、具有易用的插件系统和完善的大语言模型LLM接入功能的聊天机器人及开发框架。
<!-- [![codecov](https://img.shields.io/codecov/c/github/soulter/astrbot?style=for-the-badge)](https://codecov.io/gh/Soulter/AstrBot)
-->
> [!WARNING]
>
> 请务必修改默认密码以及保证 AstrBot 版本 >= 3.5.13。
## ✨ 近期更新
<details><summary>1. AstrBot 现已自带知识库能力</summary>
📚 详见[文档](https://astrbot.app/use/knowledge-base.html)
![image](https://github.com/user-attachments/assets/28b639b0-bb5c-4958-8e94-92ae8cfd1ab4)
</details>
2. AstrBot 现已支持接入 [MCP](https://modelcontextprotocol.io/) 服务器!
## ✨ 主要功能
> [!NOTE]
> 🪧 我们正基于前沿科研成果,设计并实现适用于角色扮演和情感陪伴的长短期记忆模型及情绪控制模型,旨在提升对话的真实性与情感表达能力。敬请期待 `v3.6.0` 版本!
1. **大语言模型对话**。支持各种大语言模型,包括 OpenAI API、Google Gemini、Llama、Deepseek、ChatGLM 等,支持接入本地部署的大模型,通过 Ollama、LLMTuner。具有多轮对话、人格情境、多模态能力支持图片理解、语音转文字Whisper
2. **多消息平台接入**。支持接入 QQOneBot、QQ 官方机器人平台、QQ 频道、企业微信、微信公众号、飞书、Telegram、钉钉、Discord、KOOK、VoceChat。支持速率限制、白名单、关键词过滤、百度内容审核
3. **Agent**。原生支持部分 Agent 能力,如代码执行器、自然语言待办、网页搜索。对接 [Dify 平台](https://dify.ai/),便捷接入 Dify 智能助手、知识库和 Dify 工作流。
4. **插件扩展**。深度优化的插件机制,支持[开发插件](https://astrbot.app/dev/plugin.html)扩展功能,极简开发。已支持安装多个插件。
5. **可视化管理面板**。支持可视化修改配置、插件管理、日志查看等功能,降低配置难度。集成 WebChat可在面板上与大模型对话。
6. **高稳定性、高模块化**。基于事件总线和流水线的架构设计,高度模块化,低耦合。
> [!TIP]
> WebUI 在线体验 Demo: [https://demo.astrbot.app/](https://demo.astrbot.app/)
>
> 用户名: `astrbot`, 密码: `astrbot`。
1. **大模型对话**。支持接入多种大模型服务。支持多模态、工具调用、MCP、原生知识库、人设等功能。
2. **多消息平台支持**。支持接入 QQ、企业微信、微信公众号、飞书、Telegram、钉钉、Discord、KOOK 等平台。支持速率限制、白名单、百度内容审核。
3. **Agent**。完善适配的 Agentic 能力。支持多轮工具调用、内置沙盒代码执行器、网页搜索等功能。
4. **插件扩展**。深度优化的插件机制,支持[开发插件](https://astrbot.app/dev/plugin.html)扩展功能,社区插件生态丰富
5. **WebUI**。可视化配置和管理机器人,功能齐全
## ✨ 使用方式
#### Docker 部署
推荐使用 Docker / Docker Compose 方式部署 AstrBot。
请参阅官方文档 [使用 Docker 部署 AstrBot](https://astrbot.app/deploy/astrbot/docker.html#%E4%BD%BF%E7%94%A8-docker-%E9%83%A8%E7%BD%B2-astrbot) 。
#### 宝塔面板部署
AstrBot 与宝塔面板合作,已上架至宝塔面板。
请参阅官方文档 [宝塔面板部署](https://astrbot.app/deploy/astrbot/btpanel.html) 。
#### 1Panel 部署
AstrBot 已由 1Panel 官方上架至 1Panel 面板。
请参阅官方文档 [1Panel 部署](https://astrbot.app/deploy/astrbot/1panel.html) 。
#### 在 雨云 上部署
AstrBot 已由雨云官方上架至云应用平台,可一键部署。
[![Deploy on RainYun](https://rainyun-apps.cn-nb1.rains3.com/materials/deploy-on-rainyun-en.svg)](https://app.rainyun.com/apps/rca/store/5994?ref=NjU1ODg0)
#### 在 Replit 上部署
社区贡献的部署方式。
[![Run on Repl.it](https://repl.it/badge/github/Soulter/AstrBot)](https://repl.it/github/Soulter/AstrBot)
#### Windows 一键安装器部署
请参阅官方文档 [使用 Windows 一键安装器部署 AstrBot](https://astrbot.app/deploy/astrbot/windows.html) 。
#### 宝塔面板部署
请参阅官方文档 [宝塔面板部署](https://astrbot.app/deploy/astrbot/btpanel.html) 。
#### CasaOS 部署
社区贡献的部署方式。
@@ -101,24 +94,8 @@ git clone https://github.com/AstrBotDevs/AstrBot && cd AstrBot
uv run main.py
```
或者,直接通过 uvx 安装 AstrBot
```bash
mkdir astrbot && cd astrbot
uvx astrbot init
# uvx astrbot run
```
或者请参阅官方文档 [通过源码部署 AstrBot](https://astrbot.app/deploy/astrbot/cli.html) 。
#### 在 Replit 上部署
[![Run on Repl.it](https://repl.it/badge/github/Soulter/AstrBot)](https://repl.it/github/Soulter/AstrBot)
#### 在 雨云 上部署
[![Deploy on RainYun](https://rainyun-apps.cn-nb1.rains3.com/materials/deploy-on-rainyun-en.svg)](https://app.rainyun.com/apps/rca/store/5994?ref=NjU1ODg0)
## ⚡ 消息平台支持情况
| 平台 | 支持性 |

View File

@@ -117,6 +117,9 @@ def build_plug_list(plugins_dir: Path) -> list:
# 从 metadata.yaml 加载元数据
metadata = load_yaml_metadata(plugin_dir)
if "desc" not in metadata and "description" in metadata:
metadata["desc"] = metadata["description"]
# 如果成功加载元数据,添加到结果列表
if metadata and all(
k in metadata for k in ["name", "desc", "version", "author", "repo"]

View File

@@ -6,7 +6,7 @@ import os
from astrbot.core.utils.astrbot_path import get_astrbot_data_path
VERSION = "3.5.23"
VERSION = "3.5.24"
DB_PATH = os.path.join(get_astrbot_data_path(), "data_v3.db")
# 默认配置
@@ -65,6 +65,7 @@ DEFAULT_CONFIG = {
"show_tool_use_status": False,
"streaming_segmented": False,
"separate_provider": True,
"max_agent_step": 30
},
"provider_stt_settings": {
"enable": False,
@@ -599,7 +600,9 @@ CONFIG_METADATA_2 = {
"timeout": 120,
"model_config": {
"model": "gpt-4o-mini",
"temperature": 0.4
},
"hint": "也兼容所有与OpenAI API兼容的服务。"
},
"Azure OpenAI": {
"id": "azure",
@@ -613,6 +616,7 @@ CONFIG_METADATA_2 = {
"timeout": 120,
"model_config": {
"model": "gpt-4o-mini",
"temperature": 0.4
},
},
"xAI": {
@@ -626,9 +630,11 @@ CONFIG_METADATA_2 = {
"timeout": 120,
"model_config": {
"model": "grok-2-latest",
"temperature": 0.4
},
},
"Anthropic": {
"hint": "注意Claude系列模型的温度调节范围为0到1.0,超出可能导致报错",
"id": "claude",
"provider": "anthropic",
"type": "anthropic_chat_completion",
@@ -640,9 +646,11 @@ CONFIG_METADATA_2 = {
"model_config": {
"model": "claude-3-5-sonnet-latest",
"max_tokens": 4096,
"temperature": 0.2
},
},
"Ollama": {
"hint":"启用前请确保已正确安装并运行 Ollama 服务端Ollama默认不带鉴权无需修改key",
"id": "ollama_default",
"provider": "ollama",
"type": "openai_chat_completion",
@@ -652,6 +660,7 @@ CONFIG_METADATA_2 = {
"api_base": "http://localhost:11434/v1",
"model_config": {
"model": "llama3.1-8b",
"temperature": 0.4
},
},
"LM Studio": {
@@ -677,6 +686,7 @@ CONFIG_METADATA_2 = {
"timeout": 120,
"model_config": {
"model": "gemini-1.5-flash",
"temperature": 0.4
},
},
"Gemini": {
@@ -690,6 +700,7 @@ CONFIG_METADATA_2 = {
"timeout": 120,
"model_config": {
"model": "gemini-2.0-flash-exp",
"temperature": 0.4
},
"gm_resp_image_modal": False,
"gm_native_search": False,
@@ -716,6 +727,7 @@ CONFIG_METADATA_2 = {
"timeout": 120,
"model_config": {
"model": "deepseek-chat",
"temperature": 0.4
},
},
"302.AI": {
@@ -729,6 +741,7 @@ CONFIG_METADATA_2 = {
"timeout": 120,
"model_config": {
"model": "gpt-4.1-mini",
"temperature": 0.4
},
},
"硅基流动": {
@@ -742,6 +755,7 @@ CONFIG_METADATA_2 = {
"api_base": "https://api.siliconflow.cn/v1",
"model_config": {
"model": "deepseek-ai/DeepSeek-V3",
"temperature": 0.4
},
},
"PPIO派欧云": {
@@ -755,6 +769,20 @@ CONFIG_METADATA_2 = {
"timeout": 120,
"model_config": {
"model": "deepseek/deepseek-r1",
"temperature": 0.4
},
},
"优云智算": {
"id": "compshare",
"provider": "compshare",
"type": "openai_chat_completion",
"provider_type": "chat_completion",
"enable": True,
"key": [],
"api_base": "https://api.modelverse.cn/v1",
"timeout": 120,
"model_config": {
"model": "moonshotai/Kimi-K2-Instruct",
},
},
"Kimi": {
@@ -768,6 +796,7 @@ CONFIG_METADATA_2 = {
"api_base": "https://api.moonshot.cn/v1",
"model_config": {
"model": "moonshot-v1-8k",
"temperature": 0.4
},
},
"智谱 AI": {
@@ -796,6 +825,7 @@ CONFIG_METADATA_2 = {
"dify_query_input_key": "astrbot_text_query",
"variables": {},
"timeout": 60,
"hint": "请确保你在 AstrBot 里设置的 APP 类型和 Dify 里面创建的应用的类型一致!"
},
"阿里云百炼应用": {
"id": "dashscope",
@@ -814,6 +844,20 @@ CONFIG_METADATA_2 = {
"variables": {},
"timeout": 60,
},
"ModelScope": {
"id": "modelscope",
"provider": "modelscope",
"type": "openai_chat_completion",
"provider_type": "chat_completion",
"enable": True,
"key": [],
"timeout": 120,
"api_base": "https://api-inference.modelscope.cn/v1",
"model_config": {
"model": "Qwen/Qwen3-32B",
"temperature": 0.4
},
},
"FastGPT": {
"id": "fastgpt",
"provider": "fastgpt",
@@ -835,7 +879,7 @@ CONFIG_METADATA_2 = {
"model": "whisper-1",
},
"Whisper(本地加载)": {
"whisper_hint": "(不用修改我)",
"hint": "启用前请 pip 安装 openai-whisper 库N卡用户大约下载 2GB主要是 torch 和 cudaCPU 用户大约下载 1 GB并且安装 ffmpeg。否则将无法正常转文字。",
"provider": "openai",
"type": "openai_whisper_selfhost",
"provider_type": "speech_to_text",
@@ -844,7 +888,7 @@ CONFIG_METADATA_2 = {
"model": "tiny",
},
"SenseVoice(本地加载)": {
"sensevoice_hint": "(不用修改我)",
"hint": "启用前请 pip 安装 funasr、funasr_onnx、torchaudio、torch、modelscope、jieba 库默认使用CPU大约下载 1 GB并且安装 ffmpeg。否则将无法正常转文字。",
"type": "sensevoice_stt_selfhost",
"provider": "sensevoice",
"provider_type": "speech_to_text",
@@ -866,7 +910,7 @@ CONFIG_METADATA_2 = {
"timeout": "20",
},
"Edge TTS": {
"edgetts_hint": "提示:使用这个服务前需要安装有 ffmpeg并且可以直接在终端调用 ffmpeg 指令。",
"hint": "提示:使用这个服务前需要安装有 ffmpeg并且可以直接在终端调用 ffmpeg 指令。",
"id": "edge_tts",
"provider": "microsoft",
"type": "edge_tts",
@@ -1686,6 +1730,10 @@ CONFIG_METADATA_2 = {
"type": "bool",
"hint": "启用后,若平台不支持流式回复,会分段输出。目前仅支持 aiocqhttp 两个平台,不支持或无需使用流式分段输出的平台会静默忽略此选项",
},
"max_agent_step": {
"description": "工具调用轮数上限",
"type": "int",
},
},
},
"persona": {

View File

@@ -2,6 +2,8 @@ import asyncio
import os
import uuid
import time
from urllib.parse import urlparse, unquote
import platform
class FileTokenService:
@@ -15,7 +17,9 @@ class FileTokenService:
async def _cleanup_expired_tokens(self):
"""清理过期的令牌"""
now = time.time()
expired_tokens = [token for token, (_, expire) in self.staged_files.items() if expire < now]
expired_tokens = [
token for token, (_, expire) in self.staged_files.items() if expire < now
]
for token in expired_tokens:
self.staged_files.pop(token, None)
@@ -32,15 +36,35 @@ class FileTokenService:
Raises:
FileNotFoundError: 当路径不存在时抛出
"""
# 处理 file:///
try:
parsed_uri = urlparse(file_path)
if parsed_uri.scheme == "file":
local_path = unquote(parsed_uri.path)
if platform.system() == "Windows" and local_path.startswith("/"):
local_path = local_path[1:]
else:
# 如果没有 file:/// 前缀,则认为是普通路径
local_path = file_path
except Exception:
# 解析失败时,按原路径处理
local_path = file_path
async with self.lock:
await self._cleanup_expired_tokens()
if not os.path.exists(file_path):
raise FileNotFoundError(f"文件不存在: {file_path}")
if not os.path.exists(local_path):
raise FileNotFoundError(
f"文件不存在: {local_path} (原始输入: {file_path})"
)
file_token = str(uuid.uuid4())
expire_time = time.time() + (timeout if timeout is not None else self.default_timeout)
self.staged_files[file_token] = (file_path, expire_time)
expire_time = time.time() + (
timeout if timeout is not None else self.default_timeout
)
# 存储转换后的真实路径
self.staged_files[file_token] = (local_path, expire_time)
return file_token
async def handle_file(self, file_token: str) -> str:

View File

@@ -223,9 +223,10 @@ class TelegramPlatformAdapter(Platform):
message.type = MessageType.GROUP_MESSAGE
message.group_id = str(update.message.chat.id)
if update.message.message_thread_id:
# Topic Group
# Topic Group - keep topic info in group_id for message routing,
# but use base group_id for session_id to share conversations
message.group_id += "#" + str(update.message.message_thread_id)
message.session_id = message.group_id
# session_id remains the base group_id for shared conversation
message.message_id = str(update.message.message_id)
message.sender = MessageMember(
@@ -349,6 +350,13 @@ class TelegramPlatformAdapter(Platform):
session_id=message.session_id,
client=self.client,
)
# Store topic information for shared conversations
if message.type == MessageType.GROUP_MESSAGE and "#" in message.group_id:
group_id, topic_id = message.group_id.split("#")
message_event.set_extra("telegram_topic_id", topic_id)
message_event.set_extra("telegram_base_group_id", group_id)
self.commit_event(message_event)
def get_client(self) -> ExtBot:

View File

@@ -66,7 +66,9 @@ class TelegramPlatformEvent(AstrMessageEvent):
return chunks
@classmethod
async def send_with_client(cls, client: ExtBot, message: MessageChain, user_name: str):
async def send_with_client(
cls, client: ExtBot, message: MessageChain, user_name: str
):
image_path = None
has_reply = False
@@ -148,7 +150,7 @@ class TelegramPlatformEvent(AstrMessageEvent):
"chat_id": user_name,
}
if message_thread_id:
payload["reply_to_message_id"] = message_thread_id
payload["message_thread_id"] = message_thread_id
delta = ""
current_content = ""

View File

@@ -470,6 +470,10 @@ class ProviderGoogleGenAI(Provider):
raise
continue
# Accumulate the complete response text for the final response
accumulated_text = ""
final_response = None
async for chunk in result:
llm_response = LLMResponse("assistant", is_chunk=True)
@@ -481,23 +485,37 @@ class ProviderGoogleGenAI(Provider):
chunk, llm_response
)
yield llm_response
break
return
if chunk.text:
accumulated_text += chunk.text
llm_response.result_chain = MessageChain(chain=[Comp.Plain(chunk.text)])
yield llm_response
if chunk.candidates[0].finish_reason:
llm_response = LLMResponse("assistant", is_chunk=False)
if not chunk.candidates[0].content.parts:
llm_response.result_chain = MessageChain(chain=[Comp.Plain(" ")])
else:
llm_response.result_chain = self._process_content_parts(
chunk, llm_response
# Process the final chunk for potential tool calls or other content
if chunk.candidates[0].content.parts:
final_response = LLMResponse("assistant", is_chunk=False)
final_response.result_chain = self._process_content_parts(
chunk, final_response
)
yield llm_response
break
# Yield final complete response with accumulated text
if not final_response:
final_response = LLMResponse("assistant", is_chunk=False)
# Set the complete accumulated text in the final response
if accumulated_text:
final_response.result_chain = MessageChain(
chain=[Comp.Plain(accumulated_text)]
)
elif not final_response.result_chain:
# If no text was accumulated and no final response was set, provide empty space
final_response.result_chain = MessageChain(chain=[Comp.Plain(" ")])
yield final_response
async def text_chat(
self,
prompt: str,

View File

@@ -99,6 +99,11 @@ class ProviderOpenAIOfficial(Provider):
for key in to_del:
del payloads[key]
# 针对 qwen3 模型的特殊处理:非流式调用必须设置 enable_thinking=false
model = payloads.get("model", "")
if "qwen3" in model.lower():
extra_body["enable_thinking"] = False
completion = await self.client.chat.completions.create(
**payloads, stream=False, extra_body=extra_body
)
@@ -176,7 +181,7 @@ class ProviderOpenAIOfficial(Provider):
raise Exception("API 返回的 completion 为空。")
choice = completion.choices[0]
if choice.message.content:
if choice.message.content is not None:
# text completion
completion_text = str(choice.message.content).strip()
llm_response.result_chain = MessageChain().message(completion_text)
@@ -210,7 +215,7 @@ class ProviderOpenAIOfficial(Provider):
"API 返回的 completion 由于内容安全过滤被拒绝(非 AstrBot)。"
)
if not llm_response.completion_text and not llm_response.tools_call_args:
if llm_response.completion_text is None and not llm_response.tools_call_args:
logger.error(f"API 返回的 completion 无法解析:{completion}")
raise Exception(f"API 返回的 completion 无法解析:{completion}")

View File

@@ -809,11 +809,11 @@ class PluginManager:
if star_metadata.star_cls is None:
return
if hasattr(star_metadata.star_cls, "__del__"):
if '__del__' in star_metadata.star_cls_type.__dict__:
asyncio.get_event_loop().run_in_executor(
None, star_metadata.star_cls.__del__
)
elif hasattr(star_metadata.star_cls, "terminate"):
elif 'terminate' in star_metadata.star_cls_type.__dict__:
await star_metadata.star_cls.terminate()
async def turn_on_plugin(self, plugin_name: str):

View File

@@ -1,6 +1,8 @@
import traceback
import aiohttp
import os
import json
from datetime import datetime
import ssl
import certifi
@@ -75,15 +77,33 @@ class PluginRoute(Route):
async def get_online_plugins(self):
custom = request.args.get("custom_registry")
force_refresh = request.args.get("force_refresh", "false").lower() == "true"
cache_file = "data/plugins.json"
if custom:
urls = [custom]
else:
urls = ["https://api.soulter.top/astrbot/plugins"]
urls = [
"https://api.soulter.top/astrbot/plugins",
"https://github.com/AstrBotDevs/AstrBot_Plugins_Collection/raw/refs/heads/main/plugin_cache_original.json",
]
# 新增:创建 SSL 上下文,使用 certifi 提供的根证书
# 如果不是强制刷新,先检查缓存是否有效
cached_data = None
if not force_refresh:
# 先检查MD5是否匹配如果匹配则使用缓存
if await self._is_cache_valid(cache_file):
cached_data = self._load_plugin_cache(cache_file)
if cached_data:
logger.debug("缓存MD5匹配使用缓存的插件市场数据")
return Response().ok(cached_data).__dict__
# 尝试获取远程数据
remote_data = None
ssl_context = ssl.create_default_context(cafile=certifi.where())
connector = aiohttp.TCPConnector(ssl=ssl_context)
for url in urls:
try:
async with aiohttp.ClientSession(
@@ -91,14 +111,123 @@ class PluginRoute(Route):
) as session:
async with session.get(url) as response:
if response.status == 200:
result = await response.json()
return Response().ok(result).__dict__
remote_data = await response.json()
# 检查远程数据是否为空
if not remote_data or (
isinstance(remote_data, dict) and len(remote_data) == 0
):
logger.warning(f"远程插件市场数据为空: {url}")
continue # 继续尝试其他URL或使用缓存
logger.info("成功获取远程插件市场数据")
# 获取最新的MD5并保存到缓存
current_md5 = await self._get_remote_md5()
self._save_plugin_cache(
cache_file, remote_data, current_md5
)
return Response().ok(remote_data).__dict__
else:
logger.error(f"请求 {url} 失败,状态码:{response.status}")
except Exception as e:
logger.error(f"请求 {url} 失败,错误:{e}")
return Response().error("获取插件列表失败").__dict__
# 如果远程获取失败,尝试使用缓存数据
if not cached_data:
cached_data = self._load_plugin_cache(cache_file)
if cached_data:
logger.warning("远程插件市场数据获取失败,使用缓存数据")
return Response().ok(cached_data, "使用缓存数据,可能不是最新版本").__dict__
return Response().error("获取插件列表失败,且没有可用的缓存数据").__dict__
async def _is_cache_valid(self, cache_file: str) -> bool:
"""检查缓存是否有效基于MD5"""
try:
if not os.path.exists(cache_file):
return False
# 加载缓存文件
with open(cache_file, "r", encoding="utf-8") as f:
cache_data = json.load(f)
cached_md5 = cache_data.get("md5")
if not cached_md5:
logger.debug("缓存文件中没有MD5信息")
return False
# 获取远程MD5
remote_md5 = await self._get_remote_md5()
if not remote_md5:
logger.warning("无法获取远程MD5将使用缓存")
return True # 如果无法获取远程MD5认为缓存有效
is_valid = cached_md5 == remote_md5
logger.debug(
f"插件数据MD5: 本地={cached_md5}, 远程={remote_md5}, 有效={is_valid}"
)
return is_valid
except Exception as e:
logger.warning(f"检查缓存有效性失败: {e}")
return False
async def _get_remote_md5(self) -> str:
"""获取远程插件数据的MD5"""
try:
ssl_context = ssl.create_default_context(cafile=certifi.where())
connector = aiohttp.TCPConnector(ssl=ssl_context)
async with aiohttp.ClientSession(
trust_env=True, connector=connector
) as session:
async with session.get(
"https://api.soulter.top/astrbot/plugins-md5"
) as response:
if response.status == 200:
data = await response.json()
return data.get("md5", "")
else:
logger.error(f"获取MD5失败状态码{response.status}")
return ""
except Exception as e:
logger.error(f"获取远程MD5失败: {e}")
return ""
def _load_plugin_cache(self, cache_file: str):
"""加载本地缓存的插件市场数据"""
try:
if os.path.exists(cache_file):
with open(cache_file, "r", encoding="utf-8") as f:
cache_data = json.load(f)
# 检查缓存是否有效
if "data" in cache_data and "timestamp" in cache_data:
logger.debug(
f"加载缓存文件: {cache_file}, 缓存时间: {cache_data['timestamp']}"
)
return cache_data["data"]
except Exception as e:
logger.warning(f"加载插件市场缓存失败: {e}")
return None
def _save_plugin_cache(self, cache_file: str, data, md5: str = None):
"""保存插件市场数据到本地缓存"""
try:
# 确保目录存在
os.makedirs(os.path.dirname(cache_file), exist_ok=True)
cache_data = {
"timestamp": datetime.now().isoformat(),
"data": data,
"md5": md5 or "",
}
with open(cache_file, "w", encoding="utf-8") as f:
json.dump(cache_data, f, ensure_ascii=False, indent=2)
logger.debug(f"插件市场数据已缓存到: {cache_file}, MD5: {md5}")
except Exception as e:
logger.warning(f"保存插件市场缓存失败: {e}")
async def get_plugins(self):
_plugin_resp = []

10
changelogs/v3.5.24.md Normal file
View File

@@ -0,0 +1,10 @@
# What's Changed
> 新版本预告: v4.0.0 即将发布。
1. 新增: 添加对 ModelScope、Compshare优云智算的模版支持。
2. 优化: 增加插件数据缓存,优化插件市场数据获取时的稳定性。
其他更新:
1. 现已支持在 1Panel 平台通过应用商城快捷部署 AstrBot。详见[在 1Panel 部署 AstrBot](https://docs.astrbot.app/deploy/astrbot/1panel.html)

View File

@@ -1,10 +1,10 @@
<script setup>
import { VueMonacoEditor } from '@guolao/vue-monaco-editor'
import { ref } from 'vue'
import { ref, computed } from 'vue'
import ListConfigItem from './ListConfigItem.vue'
import { useI18n } from '@/i18n/composables'
defineProps({
const props = defineProps({
metadata: {
type: Object,
required: true
@@ -16,11 +16,21 @@ defineProps({
metadataKey: {
type: String,
required: true
},
isEditing: {
type: Boolean,
default: false
}
})
const { t } = useI18n()
const filteredIterable = computed(() => {
if (!props.iterable) return {}
const { hint, ...rest } = props.iterable
return rest
})
const dialog = ref(false)
const currentEditingKey = ref('')
const currentEditingLanguage = ref('json')
@@ -54,7 +64,19 @@ function saveEditedContent() {
<v-card-text class="px-0 py-1">
<!-- Object Type Configuration -->
<div v-if="metadata[metadataKey]?.type === 'object' || metadata[metadataKey]?.config_template" class="object-config">
<div v-for="(val, key, index) in iterable" :key="key" class="config-item">
<!-- Provider-level hint -->
<v-alert
v-if="iterable.hint && !isEditing"
type="info"
variant="tonal"
class="mb-4"
border="start"
density="compact"
>
{{ iterable.hint }}
</v-alert>
<div v-for="(val, key, index) in filteredIterable" :key="key" class="config-item">
<!-- Nested Object -->
<div v-if="metadata[metadataKey].items[key]?.type === 'object'" class="nested-object">
<div v-if="metadata[metadataKey].items[key] && !metadata[metadataKey].items[key]?.invisible" class="nested-container">

View File

@@ -75,8 +75,7 @@
"usage": "Usage: Enter \"/kb use {name}\" in the chat page",
"tabs": {
"upload": "Upload Files",
"search": "Search Content",
"fromURL": "From URL"
"search": "Search Content"
}
},
"upload": {
@@ -133,26 +132,5 @@
"deleteFailed": "Deletion failed",
"deleteKnowledgeBaseFailed": "Failed to delete knowledge base",
"getEmbeddingModelListFailed": "Failed to get embedding model list"
},
"importFromUrl": {
"title": "Import from URL",
"urlLabel": "Web Page URL",
"urlPlaceholder": "Enter the URL of the web page to extract knowledge from",
"optionsTitle": "Import Options",
"tooltip": "These options control how text is extracted and processed from the URL content.\nLeave blank to use the plugin's default settings.\nEnabling LLM text repair and summary may take a long time.",
"useLlmRepairLabel": "Enable LLM Text Repair",
"useClusteringSummaryLabel": "Enable Clustering Summary",
"repairLlmProviderIdLabel": "Text Repair Model",
"summarizeLlmProviderIdLabel": "Summarize Model",
"embeddingProviderIdLabel": "Embedding Model",
"chunkSizeLabel": "Chunk Size",
"chunkOverlapLabel": "Chunk Overlap",
"startImport": "Start Import",
"importing": "Importing...",
"importSuccess": "Import Successful",
"importFailed": "Import Failed",
"uploadingChunks": "Content extracted successfully, uploading chunks...",
"preRequisite": "Hint: Please go to the plugin market to install astrbot_plugin_url_2_knowledge_base and follow the instructions in the plugin documentation to complete the playwright installation before using this feature.",
"allChunksUploaded": "All chunks uploaded successfully"
}
}
}

View File

@@ -32,7 +32,8 @@
"cancel": "Cancel",
"actions": "Actions",
"back": "Back",
"selectFile": "Select File"
"selectFile": "Select File",
"refresh": "Refresh"
},
"status": {
"enabled": "Enabled",

View File

@@ -24,6 +24,7 @@
"addPlatform": "Add Platform Adapter",
"connectTitle": "Connect {name}",
"viewTutorial": "View Tutorial",
"noTemplates": "No platform templates available",
"idConflict": {
"title": "ID Conflict Warning",
"message": "Detected duplicate ID \"{id}\". Please use a new ID.",

View File

@@ -75,8 +75,7 @@
"usage": "使用方式: 在聊天页中输入 \"/kb use {name}\"",
"tabs": {
"upload": "上传文件",
"search": "搜索内容",
"fromURL": "从URL导入"
"search": "搜索内容"
}
},
"upload": {
@@ -133,26 +132,5 @@
"deleteFailed": "删除失败",
"deleteKnowledgeBaseFailed": "删除知识库失败",
"getEmbeddingModelListFailed": "获取嵌入模型列表失败"
},
"importFromUrl": {
"title": "从 URL 导入",
"urlLabel": "网页 URL",
"urlPlaceholder": "请输入要提取知识的网页地址",
"optionsTitle": "导入选项",
"tooltip": "这些选项控制如何从URL内容中提取和处理文本。\n留空将使用插件的默认设置。\n启用LLM文本修复和摘要后可能花费时间较长。",
"useLlmRepairLabel": "启用LLM文本修复",
"useClusteringSummaryLabel": "启用聚类摘要",
"repairLlmProviderIdLabel": "文本修复模型",
"summarizeLlmProviderIdLabel": "摘要模型",
"embeddingProviderIdLabel": "嵌入模型",
"chunkSizeLabel": "分片长度",
"chunkOverlapLabel": "重叠长度",
"startImport": "开始导入",
"importing": "正在导入...",
"importSuccess": "导入成功",
"importFailed": "导入失败",
"uploadingChunks": "内容提取成功,正在上传分片...",
"preRequisite": "提示:请先前往插件市场安装 astrbot_plugin_url_2_knowledge_base 并根据插件文档内的指示完成 playwright 安装后才可使用本功能",
"allChunksUploaded": "所有分片上传成功"
}
}
}

View File

@@ -32,7 +32,8 @@
"cancel": "取消",
"actions": "操作",
"back": "返回",
"selectFile": "选择文件"
"selectFile": "选择文件",
"refresh": "刷新"
},
"status": {
"enabled": "启用",

View File

@@ -24,6 +24,7 @@
"addPlatform": "添加平台适配器",
"connectTitle": "接入 {name}",
"viewTutorial": "查看接入教程",
"noTemplates": "暂无平台模板",
"idConflict": {
"title": "ID 冲突警告",
"message": "检测到 ID \"{id}\" 重复。请使用一个新的 ID。",

View File

@@ -159,7 +159,11 @@ export const useCommonStore = defineStore({
if (!force && this.pluginMarketData.length > 0) {
return Promise.resolve(this.pluginMarketData);
}
return axios.get('/api/plugin/market_list')
// 如果是强制刷新,添加 force_refresh 参数
const url = force ? '/api/plugin/market_list?force_refresh=true' : '/api/plugin/market_list';
return axios.get(url)
.then((res) => {
let data = []
for (let key in res.data.data) {

View File

@@ -71,6 +71,7 @@ const uploadTab = ref('file');
const showPluginFullName = ref(false);
const marketSearch = ref("");
const filterKeys = ['name', 'desc', 'author'];
const refreshingMarket = ref(false);
const plugin_handler_info_headers = computed(() => [
{ title: tm('table.headers.eventType'), key: 'event_type_h' },
@@ -560,6 +561,25 @@ const newExtension = async () => {
}
};
// 刷新插件市场数据
const refreshPluginMarket = async () => {
refreshingMarket.value = true;
try {
// 强制刷新插件市场数据
const data = await commonStore.getPluginCollections(true);
pluginMarketData.value = data;
trimExtensionName();
checkAlreadyInstalled();
checkUpdate();
toast(tm('messages.refreshSuccess'), "success");
} catch (err) {
toast(tm('messages.refreshFailed') + " " + err, "error");
} finally {
refreshingMarket.value = false;
}
};
// 生命周期
onMounted(async () => {
await getExtensions();
@@ -851,8 +871,20 @@ onMounted(async () => {
<div class="mt-4">
<div class="d-flex align-center mb-2" style="justify-content: space-between;">
<h2>{{ tm('market.allPlugins') }}</h2>
<v-switch v-model="showPluginFullName" :label="tm('market.showFullName')" hide-details density="compact"
style="margin-left: 12px" />
<div class="d-flex align-center">
<v-btn
variant="tonal"
size="small"
@click="refreshPluginMarket"
:loading="refreshingMarket"
class="mr-2"
>
<v-icon>mdi-refresh</v-icon>
{{ tm('buttons.refresh') }}
</v-btn>
<v-switch v-model="showPluginFullName" :label="tm('market.showFullName')" hide-details density="compact"
style="margin-left: 12px" />
</div>
</div>
<v-col cols="12" md="12" style="padding: 0px;">

View File

@@ -233,6 +233,7 @@
:iterable="newSelectedProviderConfig"
:metadata="metadata['provider_group']?.metadata"
metadataKey="provider"
:is-editing="updatingMode"
/>
</v-card-text>
@@ -549,6 +550,7 @@ export default {
'ollama': 'https://registry.npmmirror.com/@lobehub/icons-static-svg/latest/files/icons/ollama.svg',
'google': 'https://registry.npmmirror.com/@lobehub/icons-static-svg/latest/files/icons/gemini-color.svg',
'deepseek': 'https://registry.npmmirror.com/@lobehub/icons-static-svg/latest/files/icons/deepseek.svg',
'modelscope': 'https://registry.npmmirror.com/@lobehub/icons-static-svg/latest/files/icons/modelscope.svg',
'zhipu': 'https://registry.npmmirror.com/@lobehub/icons-static-svg/latest/files/icons/zhipu.svg',
'siliconflow': 'https://registry.npmmirror.com/@lobehub/icons-static-svg/latest/files/icons/siliconcloud.svg',
'moonshot': 'https://registry.npmmirror.com/@lobehub/icons-static-svg/latest/files/icons/kimi.svg',

View File

@@ -12,9 +12,7 @@
:loading="installing">
{{ tm('notInstalled.install') }}
</v-btn>
<ConsoleDisplayer v-show="installing"
style="background-color: #fff; max-height: 300px; margin-top: 16px; max-width: 100%"
:show-level-btns="false"></ConsoleDisplayer>
<ConsoleDisplayer v-show="installing" style="background-color: #fff; max-height: 300px; margin-top: 16px; max-width: 100%" :show-level-btns="false"></ConsoleDisplayer>
</div>
<div v-else-if="kbCollections.length == 0" class="d-flex align-center justify-center flex-column"
style="flex-grow: 1; width: 100%; height: 100%;">
@@ -77,16 +75,13 @@
<v-form @submit.prevent="submitCreateForm">
<v-text-field variant="outlined" v-model="newKB.name" :label="tm('createDialog.nameLabel')"
required></v-text-field>
<v-text-field variant="outlined" v-model="newKB.name" :label="tm('createDialog.nameLabel')" required></v-text-field>
<v-textarea v-model="newKB.description" :label="tm('createDialog.descriptionLabel')"
variant="outlined" :placeholder="tm('createDialog.descriptionPlaceholder')"
<v-textarea v-model="newKB.description" :label="tm('createDialog.descriptionLabel')" variant="outlined" :placeholder="tm('createDialog.descriptionPlaceholder')"
rows="3"></v-textarea>
<v-select v-model="newKB.embedding_provider_id" :items="embeddingProviderConfigs"
:item-props="embeddingModelProps" :label="tm('createDialog.embeddingModelLabel')"
variant="outlined" class="mt-2">
:item-props="embeddingModelProps" :label="tm('createDialog.embeddingModelLabel')" variant="outlined" class="mt-2">
</v-select>
<small>{{ tm('createDialog.tips') }}</small>
@@ -94,10 +89,8 @@
</v-card-text>
<v-card-actions>
<v-spacer></v-spacer>
<v-btn color="error" variant="text" @click="showCreateDialog = false">{{ tm('createDialog.cancel')
}}</v-btn>
<v-btn color="primary" variant="text" @click="submitCreateForm">{{ tm('createDialog.create')
}}</v-btn>
<v-btn color="error" variant="text" @click="showCreateDialog = false">{{ tm('createDialog.cancel') }}</v-btn>
<v-btn color="primary" variant="text" @click="submitCreateForm">{{ tm('createDialog.create') }}</v-btn>
</v-card-actions>
</v-card>
</v-dialog>
@@ -121,8 +114,7 @@
</v-card-text>
<v-card-actions>
<v-spacer></v-spacer>
<v-btn color="primary" variant="text" @click="showEmojiPicker = false">{{ tm('emojiPicker.close')
}}</v-btn>
<v-btn color="primary" variant="text" @click="showEmojiPicker = false">{{ tm('emojiPicker.close') }}</v-btn>
</v-card-actions>
</v-card>
</v-dialog>
@@ -142,177 +134,89 @@
<div v-if="currentKB._embedding_provider_config" class="px-6 py-2">
<v-chip class="mr-2" color="primary" variant="tonal" size="small" rounded="sm">
<v-icon start size="small">mdi-database</v-icon>
{{ tm('contentDialog.embeddingModel') }}: {{
currentKB._embedding_provider_config.embedding_model }}
{{ tm('contentDialog.embeddingModel') }}: {{ currentKB._embedding_provider_config.embedding_model }}
</v-chip>
<v-chip color="secondary" variant="tonal" size="small" rounded="sm">
<v-icon start size="small">mdi-vector-point</v-icon>
{{ tm('contentDialog.vectorDimension') }}: {{
currentKB._embedding_provider_config.embedding_dimensions }}
{{ tm('contentDialog.vectorDimension') }}: {{ currentKB._embedding_provider_config.embedding_dimensions }}
</v-chip>
<small style="margin-left: 8px;">💡 使用方式: 在聊天页中输入 /kb use {{ currentKB.collection_name }}</small>
</div>
<v-card-text>
<v-tabs v-model="activeTab">
<v-tab value="import">导入数据</v-tab>
<v-tab value="upload">{{ tm('contentDialog.tabs.upload') }}</v-tab>
<v-tab value="search">{{ tm('contentDialog.tabs.search') }}</v-tab>
</v-tabs>
<v-window v-model="activeTab" class="mt-4">
<!-- 导入数据标签页 -->
<v-window-item value="import">
<div class="import-container pa-4">
<div class="mb-8">
<h2>导入数据</h2>
<p class="text-subtitle-1">选择数据源并导入内容到知识库</p>
<!-- 上传文件标签页 -->
<v-window-item value="upload">
<div class="upload-container pa-4">
<div class="text-center mb-4">
<h3>{{ tm('upload.title') }}</h3>
<p class="text-subtitle-1">{{ tm('upload.subtitle') }}</p>
</div>
<!-- 数据源选择下拉列表 -->
<v-select
v-model="dataSource"
:items="dataSourceOptions"
:label="'数据源选择'"
variant="outlined"
item-title="title"
item-value="value"
prepend-inner-icon="mdi-database"
></v-select>
<!-- 从文件导入 -->
<div v-if="dataSource === 'file'" class="mt-4">
<div class="upload-zone" @dragover.prevent @drop.prevent="onFileDrop"
@click="triggerFileInput">
<input type="file" ref="fileInput" style="display: none" @change="onFileSelected" />
<v-icon size="48" color="primary">mdi-cloud-upload</v-icon>
<p class="mt-2">{{ tm('upload.dropzone') }}</p>
</div>
<!-- 分片长度和重叠长度设置 -->
<v-card class="mt-4 chunk-settings-card" variant="outlined" color="grey-lighten-4">
<v-card-title class="pa-4 pb-0 d-flex align-center">
<v-icon color="primary" class="mr-2">mdi-puzzle-outline</v-icon>
<span class="text-subtitle-1 font-weight-bold">{{
tm('upload.chunkSettings.title') }}</span>
<v-tooltip location="top">
<template v-slot:activator="{ props }">
<v-icon v-bind="props" class="ml-2" size="small" color="grey">
mdi-information-outline
</v-icon>
</template>
<span>
{{ tm('upload.chunkSettings.tooltip') }}
</span>
</v-tooltip>
</v-card-title>
<v-card-text class="pa-4 pt-2">
<div class="d-flex flex-wrap" style="gap: 8px">
<v-text-field v-model="chunkSize"
:label="tm('upload.chunkSettings.chunkSizeLabel')" type="number"
:hint="tm('upload.chunkSettings.chunkSizeHint')" persistent-hint
variant="outlined" density="comfortable" class="flex-grow-1 chunk-field"
prepend-inner-icon="mdi-text-box-outline" min="50"></v-text-field>
<v-text-field v-model="overlap"
:label="tm('upload.chunkSettings.overlapLabel')" type="number"
:hint="tm('upload.chunkSettings.overlapHint')" persistent-hint
variant="outlined" density="comfortable" class="flex-grow-1 chunk-field"
prepend-inner-icon="mdi-vector-intersection" min="0"></v-text-field>
</div>
</v-card-text>
</v-card>
<div class="selected-files mt-4" v-if="selectedFile">
<div type="info" variant="tonal" class="d-flex align-center">
<div>
<v-icon class="me-2">{{ getFileIcon(selectedFile.name) }}</v-icon>
<span style="font-weight: 1000;">{{ selectedFile.name }}</span>
</div>
<v-btn size="small" color="error" variant="text" @click="selectedFile = null">
<v-icon>mdi-close</v-icon>
</v-btn>
</div>
<div class="text-center mt-4">
<v-btn color="primary" variant="elevated" :loading="uploading"
:disabled="!selectedFile" @click="uploadFile">
{{ tm('upload.upload') }}
</v-btn>
</div>
</div>
<div class="upload-progress mt-4" v-if="uploading">
<v-progress-linear indeterminate color="primary"></v-progress-linear>
</div>
<div class="upload-zone" @dragover.prevent @drop.prevent="onFileDrop"
@click="triggerFileInput">
<input type="file" ref="fileInput" style="display: none" @change="onFileSelected" />
<v-icon size="48" color="primary">mdi-cloud-upload</v-icon>
<p class="mt-2">{{ tm('upload.dropzone') }}</p>
</div>
<!-- 从URL导入 -->
<div v-if="dataSource === 'url'" class="from-url-container">
<v-alert type="info" variant="tonal" class="mb-4" border>
{{ tm('importFromUrl.preRequisite') }}
</v-alert>
<v-text-field v-model="importUrl" :label="tm('importFromUrl.urlLabel')"
:placeholder="tm('importFromUrl.urlPlaceholder')" variant="outlined" class="mb-4" hide-details></v-text-field>
<!-- 优化后的分片长度和重叠长度设置 -->
<v-card class="mt-4 chunk-settings-card" variant="outlined" color="grey-lighten-4">
<v-card-title class="pa-4 pb-0 d-flex align-center">
<v-icon color="primary" class="mr-2">mdi-puzzle-outline</v-icon>
<span class="text-subtitle-1 font-weight-bold">{{ tm('upload.chunkSettings.title') }}</span>
<v-tooltip location="top">
<template v-slot:activator="{ props }">
<v-icon v-bind="props" class="ml-2" size="small" color="grey">
mdi-information-outline
</v-icon>
</template>
<span>
{{ tm('upload.chunkSettings.tooltip') }}
</span>
</v-tooltip>
</v-card-title>
<v-card-text class="pa-4 pt-2">
<div class="d-flex flex-wrap" style="gap: 8px">
<v-text-field v-model="chunkSize" :label="tm('upload.chunkSettings.chunkSizeLabel')" type="number"
:hint="tm('upload.chunkSettings.chunkSizeHint')" persistent-hint variant="outlined"
density="comfortable" class="flex-grow-1 chunk-field"
prepend-inner-icon="mdi-text-box-outline" min="50"></v-text-field>
<v-card class="mb-4" variant="outlined" color="grey-lighten-4">
<v-card-title class="pa-4 pb-0 d-flex align-center">
<v-icon color="primary" class="mr-2">mdi-cog-outline</v-icon>
<span class="text-subtitle-1 font-weight-bold">{{ tm('importFromUrl.optionsTitle') }}</span>
<v-tooltip location="top">
<template v-slot:activator="{ props }">
<v-icon v-bind="props" class="ml-2" size="small" color="grey">mdi-information-outline</v-icon>
</template>
<span>{{ tm('importFromUrl.tooltip') }}</span>
</v-tooltip>
</v-card-title>
<v-card-text class="pa-4 pt-2">
<v-row>
<v-col cols="12" md="6">
<v-switch hide-details v-model="importOptions.use_llm_repair" :label="tm('importFromUrl.useLlmRepairLabel')"
color="primary" inset></v-switch>
</v-col>
<v-col cols="12" md="6">
<v-switch v-model="importOptions.use_clustering_summary" hide-details
:label="tm('importFromUrl.useClusteringSummaryLabel')" color="primary" inset></v-switch>
</v-col>
<v-row class="pa-4">
<!-- Optional Repair Selector -->
<v-col v-if="importOptions.use_llm_repair" :md="optionalSelectorColWidth" cols="12">
<v-select v-model="importOptions.repair_llm_provider_id" :items="llmProviderConfigs" item-value="id"
:item-props="llmModelProps" :label="tm('importFromUrl.repairLlmProviderIdLabel')" variant="outlined"
clearable hide-details></v-select>
</v-col>
<v-text-field v-model="overlap" :label="tm('upload.chunkSettings.overlapLabel')" type="number"
:hint="tm('upload.chunkSettings.overlapHint')" persistent-hint variant="outlined"
density="comfortable" class="flex-grow-1 chunk-field"
prepend-inner-icon="mdi-vector-intersection" min="0"></v-text-field>
</div>
</v-card-text>
</v-card>
<!-- Optional Summary Selector -->
<v-col v-if="importOptions.use_clustering_summary" :md="optionalSelectorColWidth" cols="12">
<v-select v-model="importOptions.summarize_llm_provider_id" :items="llmProviderConfigs" item-value="id"
:item-props="llmModelProps" :label="tm('importFromUrl.summarizeLlmProviderIdLabel')" variant="outlined"
clearable hide-details></v-select>
</v-col>
<v-col cols="12" md="6">
<v-select v-model="importOptions.embedding_provider_id" :items="embeddingProviderConfigs" item-value="id"
:item-props="embeddingModelProps" :label="tm('importFromUrl.embeddingProviderIdLabel')"
variant="outlined" clearable hide-details></v-select>
</v-col>
<v-col cols="12" md="3">
<v-text-field v-model="importOptions.chunk_size" :label="tm('importFromUrl.chunkSizeLabel')" type="number"
variant="outlined" clearable hide-details></v-text-field>
</v-col>
<v-col cols="12" md="3">
<v-text-field v-model="importOptions.chunk_overlap" :label="tm('importFromUrl.chunkOverlapLabel')"
type="number" variant="outlined" clearable hide-details></v-text-field>
</v-col>
</v-row>
</v-row>
</v-card-text>
</v-card>
<div class="text-center">
<v-btn color="primary" variant="elevated" :loading="importing" :disabled="!importUrl" @click="startImportFromUrl">
{{ tm('importFromUrl.startImport') }}
<div class="selected-files mt-4" v-if="selectedFile">
<div type="info" variant="tonal" class="d-flex align-center">
<div>
<v-icon class="me-2">{{ getFileIcon(selectedFile.name) }}</v-icon>
<span style="font-weight: 1000;">{{ selectedFile.name }}</span>
</div>
<v-btn size="small" color="error" variant="text" @click="selectedFile = null">
<v-icon>mdi-close</v-icon>
</v-btn>
</div>
<div class="text-center mt-4">
<v-btn color="primary" variant="elevated" :loading="uploading"
:disabled="!selectedFile" @click="uploadFile">
{{ tm('upload.upload') }}
</v-btn>
</div>
</div>
<div class="upload-progress mt-4" v-if="uploading">
<v-progress-linear indeterminate color="primary"></v-progress-linear>
</div>
</div>
</v-window-item>
@@ -321,13 +225,12 @@
<v-window-item value="search">
<div class="search-container pa-4">
<v-form @submit.prevent="searchKnowledgeBase" class="d-flex align-center">
<v-text-field v-model="searchQuery" :label="tm('search.queryLabel')"
append-icon="mdi-magnify" variant="outlined" class="flex-grow-1 me-2"
@click:append="searchKnowledgeBase" @keyup.enter="searchKnowledgeBase"
:placeholder="tm('search.queryPlaceholder')" hide-details></v-text-field>
<v-text-field v-model="searchQuery" :label="tm('search.queryLabel')" append-icon="mdi-magnify"
variant="outlined" class="flex-grow-1 me-2" @click:append="searchKnowledgeBase"
@keyup.enter="searchKnowledgeBase" :placeholder="tm('search.queryPlaceholder')"
hide-details></v-text-field>
<v-select v-model="topK" :items="[3, 5, 10, 20]"
:label="tm('search.resultCountLabel')" variant="outlined"
<v-select v-model="topK" :items="[3, 5, 10, 20]" :label="tm('search.resultCountLabel')" variant="outlined"
style="max-width: 120px;" hide-details></v-select>
</v-form>
@@ -350,8 +253,7 @@
<v-spacer></v-spacer>
<v-chip v-if="result.score" size="small" color="primary"
variant="tonal">
{{ tm('search.relevance') }}: {{ Math.round(result.score * 100)
}}%
{{ tm('search.relevance') }}: {{ Math.round(result.score * 100) }}%
</v-chip>
</div>
<div class="search-content">{{ result.content }}</div>
@@ -382,11 +284,8 @@
</v-card-text>
<v-card-actions>
<v-spacer></v-spacer>
<v-btn color="grey-darken-1" variant="text" @click="showDeleteDialog = false">{{
tm('deleteDialog.cancel')
}}</v-btn>
<v-btn color="error" variant="text" @click="deleteKnowledgeBase" :loading="deleting">{{
tm('deleteDialog.delete') }}</v-btn>
<v-btn color="grey-darken-1" variant="text" @click="showDeleteDialog = false">{{ tm('deleteDialog.cancel') }}</v-btn>
<v-btn color="error" variant="text" @click="deleteKnowledgeBase" :loading="deleting">{{ tm('deleteDialog.delete') }}</v-btn>
</v-card-actions>
</v-card>
</v-dialog>
@@ -461,12 +360,7 @@ export default {
collection_name: '',
emoji: ''
},
activeTab: 'import',
dataSource: 'file',
dataSourceOptions: [
{ title: '从文件', value: 'file', icon: 'mdi-file-upload' },
{ title: '从URL', value: 'url', icon: 'mdi-web' }
],
activeTab: 'upload',
selectedFile: null,
chunkSize: null,
overlap: null,
@@ -481,78 +375,20 @@ export default {
collection_name: ''
},
deleting: false,
embeddingProviderConfigs: [],
llmProviderConfigs: [],
// URL导入相关数据
importUrl: '',
importOptions: {
use_llm_repair: true,
use_clustering_summary: false,
repair_llm_provider_id: null,
summarize_llm_provider_id: null,
embedding_provider_id: null,
chunk_size: 300,
chunk_overlap: 50,
},
importing: false,
pollingInterval: null,
}
},
computed: {
optionalSelectorColWidth() {
const repairOn = this.importOptions.use_llm_repair;
const summaryOn = this.importOptions.use_clustering_summary;
if (repairOn && summaryOn) {
return 6; // Both on, each takes half
}
return 12; // Only one is on, it takes full width
}
},
watch: {
llmProviderConfigs: {
handler(newVal) {
if (newVal && newVal.length > 0) {
if (!this.importOptions.repair_llm_provider_id) {
this.importOptions.repair_llm_provider_id = newVal[0].id;
}
if (!this.importOptions.summarize_llm_provider_id) {
this.importOptions.summarize_llm_provider_id = newVal[0].id;
}
}
},
immediate: true,
deep: true
},
embeddingProviderConfigs: {
handler(newVal) {
if (newVal && newVal.length > 0) {
if (!this.importOptions.embedding_provider_id) {
this.importOptions.embedding_provider_id = newVal[0].id;
}
}
},
immediate: true,
deep: true
embeddingProviderConfigs: []
}
},
mounted() {
this.checkPlugin();
this.getEmbeddingProviderList();
this.getLlmProviderList();
},
methods: {
llmModelProps(providerConfig) {
return {
title: providerConfig.llm_model || providerConfig.id,
subtitle: `Provider ID: ${providerConfig.id}`,
}
},
embeddingModelProps(providerConfig) {
return {
title: providerConfig.embedding_model,
subtitle: this.tm('createDialog.providerInfo', {
id: providerConfig.id,
dimensions: providerConfig.embedding_dimensions
subtitle: this.tm('createDialog.providerInfo', {
id: providerConfig.id,
dimensions: providerConfig.embedding_dimensions
}),
}
},
@@ -664,8 +500,7 @@ export default {
},
resetContentDialog() {
this.activeTab = 'import';
this.dataSource = 'file';
this.activeTab = 'upload';
this.selectedFile = null;
this.searchQuery = '';
this.searchResults = [];
@@ -673,13 +508,6 @@ export default {
// 重置分片长度和重叠长度参数
this.chunkSize = null;
this.overlap = null;
// 重置URL导入相关数据
this.importUrl = '';
this.importing = false;
if (this.pollingInterval) {
clearInterval(this.pollingInterval);
this.pollingInterval = null;
}
},
triggerFileInput() {
@@ -876,178 +704,8 @@ export default {
openUrl(url) {
window.open(url, '_blank');
},
getLlmProviderList() {
axios.get('/api/config/provider/list', {
params: {
provider_type: 'chat_completion'
}
})
.then(response => {
if (response.data.status === 'ok') {
this.llmProviderConfigs = response.data.data || [];
} else {
this.showSnackbar(response.data.message || 'Failed to get LLM provider list', 'error');
}
})
.catch(error => {
console.error('Error fetching LLM providers:', error);
this.showSnackbar('Failed to get LLM provider list', 'error');
});
},
// URL导入相关方法
async startImportFromUrl() {
if (!this.importUrl) {
this.showSnackbar('Please enter a URL', 'warning');
return;
}
this.importing = true;
try {
const payload = {
url: this.importUrl,
...Object.fromEntries(Object.entries(this.importOptions).filter(([_, v]) => v !== '' && v !== null && v !== undefined))
};
console.log('Starting URL import with payload:', JSON.stringify(payload, null, 2));
const addTaskResponse = await axios.post('/api/plug/url_2_kb/add', payload);
if (!addTaskResponse.data.task_id) {
throw new Error(addTaskResponse.data.message || 'Failed to start import task: No task_id received.');
}
const taskId = addTaskResponse.data.task_id;
this.pollTaskStatus(taskId);
} catch (error) {
const errorMessage = error.response?.data?.message || error.message || 'An unknown error occurred.';
this.showSnackbar(`Error: ${errorMessage}`, 'error');
this.importing = false;
}
},
pollTaskStatus(taskId) {
this.pollingInterval = setInterval(async () => {
try {
const statusResponse = await axios.post(`/api/plug/url_2_kb/status`, { task_id: taskId });
const taskData = statusResponse.data;
const taskStatus = taskData.status;
if (taskStatus === 'completed') {
clearInterval(this.pollingInterval);
this.pollingInterval = null;
this.showSnackbar(this.tm('importFromUrl.uploadingChunks'), 'info');
this.handleImportResult(taskData);
} else if (taskStatus === 'failed') {
clearInterval(this.pollingInterval);
this.pollingInterval = null;
const failureReason = taskData.result || 'Unknown reason.';
this.showSnackbar(`${this.tm('importFromUrl.importFailed')}: ${failureReason}`, 'error');
this.importing = false;
}
} catch (error) {
clearInterval(this.pollingInterval);
this.pollingInterval = null;
const errorMessage = error.response?.data?.message || error.message || 'An unknown error occurred during polling.';
this.showSnackbar(`Polling Error: ${errorMessage}`, 'error');
this.importing = false;
}
}, 3000);
},
async handleImportResult(data) {
const chunks = [];
const result = data.result;
// 1. Handle overall summary
if (result.overall_summary) {
chunks.push({ content: result.overall_summary, filename: 'overall_summary.txt' });
}
// 2. Handle topic summaries
if (result.topics && result.topics.length > 0) {
result.topics.forEach(topic => {
if (topic.topic_summary) {
chunks.push({ content: topic.topic_summary, filename: `topic_${topic.topic_id}_summary.txt` });
}
});
}
// 3. Handle noise points
if (result.noise_points && result.noise_points.length > 0) {
result.noise_points.forEach((point, index) => {
const content = typeof point === 'object' && point.text ? point.text : point;
chunks.push({ content: content, filename: `noise_${index + 1}.txt` });
});
}
if (chunks.length === 0) {
this.showSnackbar('URL processed, but no text chunks were extracted.', 'info');
this.importing = false;
return;
}
let successCount = 0;
let failCount = 0;
for (let i = 0; i < chunks.length; i++) {
const chunk = chunks[i];
try {
await this.uploadChunkAsFile(chunk.content, chunk.filename);
successCount++;
} catch (error) {
failCount++;
}
}
if (failCount === 0) {
this.showSnackbar(this.tm('importFromUrl.allChunksUploaded'), 'success');
} else if (successCount > 0) {
this.showSnackbar('Import partially complete. See console for details.', 'warning');
} else {
this.showSnackbar('Import failed. No chunks were uploaded.', 'error');
}
this.importing = false;
this.getKBCollections();
},
async uploadChunkAsFile(content, filename) {
const blob = new Blob([content], { type: 'text/plain' });
const file = new File([blob], filename, { type: 'text/plain' });
const formData = new FormData();
formData.append('file', file);
formData.append('collection_name', this.currentKB.collection_name);
if (this.importOptions.chunk_size && this.importOptions.chunk_size > 0) {
formData.append('chunk_size', this.importOptions.chunk_size);
}
if (this.importOptions.chunk_overlap && this.importOptions.chunk_overlap >= 0) {
formData.append('chunk_overlap', this.importOptions.chunk_overlap);
}
const response = await axios.post('/api/plug/alkaid/kb/collection/add_file', formData, {
headers: {
'Content-Type': 'multipart/form-data'
}
});
if (response.data.status !== 'ok') {
throw new Error(response.data.message || 'Chunk upload failed');
}
return response.data;
},
},
beforeUnmount() {
if (this.pollingInterval) {
clearInterval(this.pollingInterval);
}
},
}
}
</script>
@@ -1240,13 +898,4 @@ export default {
.chunk-field:focus-within :deep(.v-field__prepend-inner) {
opacity: 1;
}
.import-container,
.from-url-container {
min-height: 400px;
}
.data-source-select :deep(.v-field__prepend-inner) {
padding-right: 12px;
}
</style>

View File

@@ -1316,6 +1316,16 @@ UID: {user_id} 此 ID 可用于设置管理员。
except BaseException as e:
logger.error(f"处理引用图片失败: {e}")
# Add Telegram topic context for shared conversations
if event.get_platform_name() == "telegram":
topic_id = event.get_extra("telegram_topic_id")
base_group_id = event.get_extra("telegram_base_group_id")
if topic_id and base_group_id:
req.system_prompt += (
f"\n[Context: This message is from Telegram topic "
f"#{topic_id} in group {base_group_id}]\n"
)
if self.ltm:
try:
await self.ltm.on_req_llm(event, req)

View File

@@ -1,6 +1,6 @@
[project]
name = "AstrBot"
version = "3.5.23"
version = "3.5.24"
description = "易上手的多平台 LLM 聊天机器人及开发框架"
readme = "README.md"
requires-python = ">=3.10"
@@ -76,3 +76,11 @@ lint.select = [
"Q", # flake8-quotes
]
target-version = "py310"
[dependency-groups]
dev = [
"pytest>=8.4.1",
"pytest-asyncio>=1.1.0",
"pytest-cov>=6.2.1",
"ruff>=0.12.8",
]

216
uv.lock generated
View File

@@ -1,5 +1,5 @@
version = 1
revision = 2
revision = 3
requires-python = ">=3.10"
[[package]]
@@ -204,7 +204,7 @@ wheels = [
[[package]]
name = "astrbot"
version = "3.5.23"
version = "3.5.24"
source = { editable = "." }
dependencies = [
{ name = "aiocqhttp" },
@@ -250,6 +250,14 @@ dependencies = [
{ name = "wechatpy" },
]
[package.dev-dependencies]
dev = [
{ name = "pytest" },
{ name = "pytest-asyncio" },
{ name = "pytest-cov" },
{ name = "ruff" },
]
[package.metadata]
requires-dist = [
{ name = "aiocqhttp", specifier = ">=1.4.4" },
@@ -295,6 +303,14 @@ requires-dist = [
{ name = "wechatpy", specifier = ">=1.8.18" },
]
[package.metadata.requires-dev]
dev = [
{ name = "pytest", specifier = ">=8.4.1" },
{ name = "pytest-asyncio", specifier = ">=1.1.0" },
{ name = "pytest-cov", specifier = ">=6.2.1" },
{ name = "ruff", specifier = ">=0.12.8" },
]
[[package]]
name = "async-timeout"
version = "5.0.1"
@@ -313,6 +329,15 @@ wheels = [
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]
[[package]]
name = "backports-asyncio-runner"
version = "1.2.0"
source = { registry = "https://pypi.org/simple" }
sdist = { url = "https://files.pythonhosted.org/packages/8e/ff/70dca7d7cb1cbc0edb2c6cc0c38b65cba36cccc491eca64cabd5fe7f8670/backports_asyncio_runner-1.2.0.tar.gz", hash = "sha256:a5aa7b2b7d8f8bfcaa2b57313f70792df84e32a2a746f585213373f900b42162", size = 69893, upload-time = "2025-07-02T02:27:15.685Z" }
wheels = [
{ url = "https://files.pythonhosted.org/packages/a0/59/76ab57e3fe74484f48a53f8e337171b4a2349e506eabe136d7e01d059086/backports_asyncio_runner-1.2.0-py3-none-any.whl", hash = "sha256:0da0a936a8aeb554eccb426dc55af3ba63bcdc69fa1a600b5bb305413a4477b5", size = 12313, upload-time = "2025-07-02T02:27:14.263Z" },
]
[[package]]
name = "beautifulsoup4"
version = "4.13.4"
@@ -513,6 +538,96 @@ wheels = [
{ url = "https://files.pythonhosted.org/packages/e3/51/9b208e85196941db2f0654ad0357ca6388ab3ed67efdbfc799f35d1f83aa/colorlog-6.9.0-py3-none-any.whl", hash = "sha256:5906e71acd67cb07a71e779c47c4bcb45fb8c2993eebe9e5adcd6a6f1b283eff", size = 11424, upload-time = "2024-10-29T18:34:49.815Z" },
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[[package]]
name = "coverage"
version = "7.10.3"
source = { registry = "https://pypi.org/simple" }
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