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XYBotV2
🤖 功能丰富的微信机器人框架 | AI对话、对接Dify、积分系统、游戏互动、每日新闻、天气查询 | 非Hook非Web实现 | 支持 Windows✅ Linux✅ MacOS✅ | 全新架构解决XYBot第一代痛点!
Stars: 137
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XYBot V2 is a feature-rich WeChat robot framework that supports various interactive functions and gameplays. It provides AI chat, daily news updates, song requests, weather queries, and gaming functionalities like Gomoku and Warthunder player lookup. The tool is open-source and intended for learning and research purposes only, not for commercial or illegal activities. Users must comply with relevant laws and respect WeChat's copyrights and privacy. The tool's functionalities can be extended through a plugin system, allowing for dynamic loading/unloading of plugins.
README:
XYBot V2 是一个功能丰富的微信机器人框架,支持多种互动功能和游戏玩法。
- 这个项目免费开源,不存在收费。
- 本工具仅供学习和技术研究使用,不得用于任何商业或非法行为。
- 本工具的作者不对本工具的安全性、完整性、可靠性、有效性、正确性或适用性做任何明示或暗示的保证,也不对本工具的使用或滥用造成的任何直接或间接的损失、责任、索赔、要求或诉讼承担任何责任。
- 本工具的作者保留随时修改、更新、删除或终止本工具的权利,无需事先通知或承担任何义务。
- 本工具的使用者应遵守相关法律法规,尊重微信的版权和隐私,不得侵犯微信或其他第三方的合法权益,不得从事任何违法或不道德的行为。
- 本工具的使用者在下载、安装、运行或使用本工具时,即表示已阅读并同意本免责声明。如有异议,请立即停止使用本工具,并删除所有相关文件。
- 🤖 AI聊天 - 支持文字、图片、语音等多模态交互
- 📰 每日新闻 - 自动推送每日新闻
- 🎵 点歌系统 - 支持在线点歌
- 🌤️ 天气查询 - 查询全国各地天气
- 🎮 游戏功能 - 五子棋、战争雷霆玩家查询等
- 📝 每日签到 - 支持连续签到奖励
- 🎲 抽奖系统 - 多种抽奖玩法
- 🧧 红包系统 - 群内发积分红包
- 💰 积分交易 - 用户间积分转账
- 📊 积分排行 - 查看积分排名
- ⚙️ 插件管理 - 动态加载/卸载插件
- 👥 白名单管理 - 控制机器人使用权限
- 📊 积分管理 - 管理员可调整用户积分
- 🔄 签到重置 - 重置所有用户签到状态
XYBot V2 采用插件化设计,所有功能都以插件形式实现。主要插件包括:
- 👨💼 AdminPoint - 积分管理
- 🔄 AdminSignInReset - 签到重置
- 🛡️ AdminWhitelist - 白名单管理
- 🤖 Ai - AI聊天
- 📊 BotStatus - 机器人状态
- 📱 GetContact - 获取通讯录
- 🌤️ GetWeather - 天气查询
- 🎮 Gomoku - 五子棋游戏
- 🌅 GoodMorning - 早安问候
- 📈 Leaderboard - 积分排行
- 🎲 LuckyDraw - 幸运抽奖
- 📋 Menu - 菜单系统
- 🎵 Music - 点歌系统
- 📰 News - 新闻推送
- 💱 PointTrade - 积分交易
- 💰 QueryPoint - 积分查询
- 🎯 RandomMember - 随机群成员
- 🖼️ RandomPicture - 随机图片
- 🧧 RedPacket - 红包系统
- ✍️ SignIn - 每日签到
✈️ Warthunder - 战争雷霆查询
需要安装 Docker 和 Docker Compose:
- 🐋 Docker 安装: https://docs.docker.com/get-started/get-docker/
- 🔄 Docker Compose 安装: https://docs.docker.com/compose/install/
- ⬇️ 拉取最新镜像
# 克隆项目
git clone https://github.com/HenryXiaoYang/XYBotV2.git
cd XYBotV2
# 拉取镜像
docker-compose pull
- 🚀 启动容器
# 首次启动
docker-compose up -d
# 查看容器状态
docker-compose ps
- 📱 查看日志然后登录微信
# 查看日志获取登录二维码
docker-compose logs -f xybotv2
扫描终端显示的二维码完成登录。(如果扫不出来,可以打开链接扫码)。首次登录成功后,需要挂机4小时。之后机器人就会自动开始正常运行。
- ⚙️ 配置文件修改
# 查看数据卷位置
docker volume inspect xybotv2
# 编辑对应目录下的配置文件
xybotv2-volumes-dir/_data/main_config.toml
xybotv2-volumes-dir/_data/plugins/all_in_one_config.toml
修改配置后需要重启容器使配置生效:
docker-compose restart xybotv2
[!TIP] 如果是修改插件配置则可使用热加载、热卸载、热重载指令,不用重启机器人。
- 🔌 Redis 连接失败
- 检查 DragonFly 服务是否正常运行
- 确认 main_config.toml 中的 redis-host 配置是否正确
⚠️ 配置文件修改未生效
- 重启容器:
docker-compose restart xybotv2
- 检查配置文件权限是否正确
- 📝 日志查看
# 查看实时日志
docker-compose logs -f xybotv2
# 查看最近100行日志
docker-compose logs --tail=100 xybotv2
-
安装 Python 3.11 (必须是3.11版本): https://www.python.org/downloads/release/python-3119/
- 在安装过程中勾选 "Add Python to PATH" 选项
- 或者手动添加:
- 右键点击 "此电脑" -> "属性" -> "高级系统设置" -> "环境变量"
- 在 "系统变量" 中找到 Path,点击 "编辑"
- 添加 Python 安装目录(如
C:\Python311
)和 Scripts 目录(如C:\Python311\Scripts
)
-
安装 ffmpeg:
- 从 ffmpeg官网 下载 Windows 版本
- 解压到合适的目录(如
C:\ffmpeg
) - 添加环境变量:
- 右键点击 "此电脑" -> "属性" -> "高级系统设置" -> "环境变量"
- 在 "系统变量" 中找到 Path,点击 "编辑"
- 添加 ffmpeg 的 bin 目录路径(如
C:\ffmpeg\bin
)
- 设置 IMAGEIO_FFMPEG_EXE 环境变量:
- 在 "系统变量" 中点击 "新建"
- 变量名输入:
IMAGEIO_FFMPEG_EXE
- 变量值输入 ffmpeg.exe 的完整路径(如
C:\ffmpeg\bin\ffmpeg.exe
)
- 重启命令提示符或 PowerShell 使环境变量生效
- 验证安装:
ffmpeg -version
-
安装 Redis:
- 从 Redis 下载最新版本 (目前是7.4.2)
- 下载并解压
Redis-x64-5.0.14.1.zip
- 在命令行执行:
# 进入目录 cd Redis-x64-5.0.14.1 # 启动Redis服务 start redis-server.exe
# 克隆项目
git clone https://github.com/HenryXiaoYang/XYBotV2.git
# 小白:直接 Github Download ZIP
cd XYBotV2
# 创建虚拟环境
python -m venv venv
.\venv\Scripts\activate
# 安装依赖
pip install -r requirements.txt
# 使用镜像源安装
pip install -r requirements.txt -i https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple
# 确保Redis服务已启动
redis-cli ping # 如果返回PONG则表示Redis正常运行
# 启动机器人
python main.py
- 扫描终端显示的二维码完成登录。如果扫不出来,可以打开二维码下面的链接扫码。
- 首次登录成功后,需要挂机4小时。之后机器人就会开始正常运行。
主配置: main_config.toml 主配置文件
插件配置: plugins/all_in_one_config.toml 插件配置文件
这几个插件需要配置API密钥才可正常工作:
-
🤖 Ai
-
🌤️ GetWeather
-
如果机器人正在运行,需要重启才能使主配置生效:
# 按Ctrl+C停止机器人 # 重新启动 python main.py
[!TIP] 如果是修改插件配置则可使用热加载、热卸载、热重载指令,不用重启机器人。
# Ubuntu/Debian
sudo apt update
sudo apt install python3.11 python3.11-venv redis-server ffmpeg
# CentOS/RHEL
sudo yum install epel-release # 如果需要EPEL仓库
sudo yum install python3.11 redis ffmpeg
sudo systemctl start redis
sudo systemctl enable redis
# 设置 IMAGEIO_FFMPEG_EXE 环境变量
echo 'export IMAGEIO_FFMPEG_EXE=$(which ffmpeg)' >> ~/.bashrc
source ~/.bashrc
# 如果使用其他shell(如zsh),则需要:
# echo 'export IMAGEIO_FFMPEG_EXE=$(which ffmpeg)' >> ~/.zshrc
# source ~/.zshrc
# 克隆项目
git clone https://github.com/HenryXiaoYang/XYBotV2.git
# 小白:直接 Github Download ZIP
cd XYBotV2
# 创建虚拟环境
python3.11 -m venv venv
source venv/bin/activate
# 安装依赖
pip install -r requirements.txt
# 使用镜像源安装
pip install -r requirements.txt -i https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple
- 🚀 启动机器人
# 确保在虚拟环境中
source venv/bin/activate
# 检查Redis服务状态
systemctl status redis
# 如果Redis未运行,启动服务
sudo systemctl start redis
# 设置Redis开机自启
sudo systemctl enable redis
# 验证Redis连接
redis-cli ping
# 如果返回PONG表示连接正常
# 启动机器人
python3 main.py
- 📱 登录微信
- 扫描终端显示的二维码完成登录。如果扫不出来,可以打开二维码下面的链接扫码。
- 首次登录成功后,需要挂机4小时。之后机器人就会开始正常运行。
- ⚙️ 配置文件修改
主配置: main_config.toml 主配置文件
插件配置: plugins/all_in_one_config.toml 插件配置文件
这几个插件需要配置API密钥才可正常工作:
-
🤖 Ai
-
🌤️ GetWeather
-
如果机器人正在运行,需要重启才能使主配置生效:
# 按Ctrl+C停止机器人 # 重新启动 python main.py
[!TIP] 如果是修改插件配置则可使用热加载、热卸载、热重载指令,不用重启机器人。
提交代码时请使用 feat: something
作为说明,支持的标识如下:
-
feat
新功能(feature) -
fix
修复bug -
docs
文档(documentation) -
style
格式(不影响代码运行的变动) -
ref
重构(即不是新增功能,也不是修改bug的代码变动) -
perf
性能优化(performance) -
test
增加测试 -
chore
构建过程或辅助工具的变动 -
revert
撤销
- 与网络相关的报错
- 检查网络连接,是否能ping通微信服务器
- 尝试关闭代理软件,尝试重启电脑
- 尝试重启XYBot和Redis
- 如是Docker部署,检查Docker容器网络是否能连接到微信服务器和Dragonfly数据库
-
正在运行
相关的报错
- 将占用9000端口的进程强制结束
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h2ogpt
h2oGPT is an Apache V2 open-source project that allows users to query and summarize documents or chat with local private GPT LLMs. It features a private offline database of any documents (PDFs, Excel, Word, Images, Video Frames, Youtube, Audio, Code, Text, MarkDown, etc.), a persistent database (Chroma, Weaviate, or in-memory FAISS) using accurate embeddings (instructor-large, all-MiniLM-L6-v2, etc.), and efficient use of context using instruct-tuned LLMs (no need for LangChain's few-shot approach). h2oGPT also offers parallel summarization and extraction, reaching an output of 80 tokens per second with the 13B LLaMa2 model, HYDE (Hypothetical Document Embeddings) for enhanced retrieval based upon LLM responses, a variety of models supported (LLaMa2, Mistral, Falcon, Vicuna, WizardLM. With AutoGPTQ, 4-bit/8-bit, LORA, etc.), GPU support from HF and LLaMa.cpp GGML models, and CPU support using HF, LLaMa.cpp, and GPT4ALL models. Additionally, h2oGPT provides Attention Sinks for arbitrarily long generation (LLaMa-2, Mistral, MPT, Pythia, Falcon, etc.), a UI or CLI with streaming of all models, the ability to upload and view documents through the UI (control multiple collaborative or personal collections), Vision Models LLaVa, Claude-3, Gemini-Pro-Vision, GPT-4-Vision, Image Generation Stable Diffusion (sdxl-turbo, sdxl) and PlaygroundAI (playv2), Voice STT using Whisper with streaming audio conversion, Voice TTS using MIT-Licensed Microsoft Speech T5 with multiple voices and Streaming audio conversion, Voice TTS using MPL2-Licensed TTS including Voice Cloning and Streaming audio conversion, AI Assistant Voice Control Mode for hands-free control of h2oGPT chat, Bake-off UI mode against many models at the same time, Easy Download of model artifacts and control over models like LLaMa.cpp through the UI, Authentication in the UI by user/password via Native or Google OAuth, State Preservation in the UI by user/password, Linux, Docker, macOS, and Windows support, Easy Windows Installer for Windows 10 64-bit (CPU/CUDA), Easy macOS Installer for macOS (CPU/M1/M2), Inference Servers support (oLLaMa, HF TGI server, vLLM, Gradio, ExLLaMa, Replicate, OpenAI, Azure OpenAI, Anthropic), OpenAI-compliant, Server Proxy API (h2oGPT acts as drop-in-replacement to OpenAI server), Python client API (to talk to Gradio server), JSON Mode with any model via code block extraction. Also supports MistralAI JSON mode, Claude-3 via function calling with strict Schema, OpenAI via JSON mode, and vLLM via guided_json with strict Schema, Web-Search integration with Chat and Document Q/A, Agents for Search, Document Q/A, Python Code, CSV frames (Experimental, best with OpenAI currently), Evaluate performance using reward models, and Quality maintained with over 1000 unit and integration tests taking over 4 GPU-hours.
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serverless-chat-langchainjs
This sample shows how to build a serverless chat experience with Retrieval-Augmented Generation using LangChain.js and Azure. The application is hosted on Azure Static Web Apps and Azure Functions, with Azure Cosmos DB for MongoDB vCore as the vector database. You can use it as a starting point for building more complex AI applications.
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react-native-vercel-ai
Run Vercel AI package on React Native, Expo, Web and Universal apps. Currently React Native fetch API does not support streaming which is used as a default on Vercel AI. This package enables you to use AI library on React Native but the best usage is when used on Expo universal native apps. On mobile you get back responses without streaming with the same API of `useChat` and `useCompletion` and on web it will fallback to `ai/react`
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LLamaSharp
LLamaSharp is a cross-platform library to run 🦙LLaMA/LLaVA model (and others) on your local device. Based on llama.cpp, inference with LLamaSharp is efficient on both CPU and GPU. With the higher-level APIs and RAG support, it's convenient to deploy LLM (Large Language Model) in your application with LLamaSharp.
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gpt4all
GPT4All is an ecosystem to run powerful and customized large language models that work locally on consumer grade CPUs and any GPU. Note that your CPU needs to support AVX or AVX2 instructions. Learn more in the documentation. A GPT4All model is a 3GB - 8GB file that you can download and plug into the GPT4All open-source ecosystem software. Nomic AI supports and maintains this software ecosystem to enforce quality and security alongside spearheading the effort to allow any person or enterprise to easily train and deploy their own on-edge large language models.
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ChatGPT-Telegram-Bot
ChatGPT Telegram Bot is a Telegram bot that provides a smooth AI experience. It supports both Azure OpenAI and native OpenAI, and offers real-time (streaming) response to AI, with a faster and smoother experience. The bot also has 15 preset bot identities that can be quickly switched, and supports custom bot identities to meet personalized needs. Additionally, it supports clearing the contents of the chat with a single click, and restarting the conversation at any time. The bot also supports native Telegram bot button support, making it easy and intuitive to implement required functions. User level division is also supported, with different levels enjoying different single session token numbers, context numbers, and session frequencies. The bot supports English and Chinese on UI, and is containerized for easy deployment.
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twinny
Twinny is a free and open-source AI code completion plugin for Visual Studio Code and compatible editors. It integrates with various tools and frameworks, including Ollama, llama.cpp, oobabooga/text-generation-webui, LM Studio, LiteLLM, and Open WebUI. Twinny offers features such as fill-in-the-middle code completion, chat with AI about your code, customizable API endpoints, and support for single or multiline fill-in-middle completions. It is easy to install via the Visual Studio Code extensions marketplace and provides a range of customization options. Twinny supports both online and offline operation and conforms to the OpenAI API standard.
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agnai
Agnaistic is an AI roleplay chat tool that allows users to interact with personalized characters using their favorite AI services. It supports multiple AI services, persona schema formats, and features such as group conversations, user authentication, and memory/lore books. Agnaistic can be self-hosted or run using Docker, and it provides a range of customization options through its settings.json file. The tool is designed to be user-friendly and accessible, making it suitable for both casual users and developers.
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sweep
Sweep is an AI junior developer that turns bugs and feature requests into code changes. It automatically handles developer experience improvements like adding type hints and improving test coverage.
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teams-ai
The Teams AI Library is a software development kit (SDK) that helps developers create bots that can interact with Teams and Microsoft 365 applications. It is built on top of the Bot Framework SDK and simplifies the process of developing bots that interact with Teams' artificial intelligence capabilities. The SDK is available for JavaScript/TypeScript, .NET, and Python.
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ai-guide
This guide is dedicated to Large Language Models (LLMs) that you can run on your home computer. It assumes your PC is a lower-end, non-gaming setup.
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classifai
Supercharge WordPress Content Workflows and Engagement with Artificial Intelligence. Tap into leading cloud-based services like OpenAI, Microsoft Azure AI, Google Gemini and IBM Watson to augment your WordPress-powered websites. Publish content faster while improving SEO performance and increasing audience engagement. ClassifAI integrates Artificial Intelligence and Machine Learning technologies to lighten your workload and eliminate tedious tasks, giving you more time to create original content that matters.
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chatbot-ui
Chatbot UI is an open-source AI chat app that allows users to create and deploy their own AI chatbots. It is easy to use and can be customized to fit any need. Chatbot UI is perfect for businesses, developers, and anyone who wants to create a chatbot.
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BricksLLM
BricksLLM is a cloud native AI gateway written in Go. Currently, it provides native support for OpenAI, Anthropic, Azure OpenAI and vLLM. BricksLLM aims to provide enterprise level infrastructure that can power any LLM production use cases. Here are some use cases for BricksLLM: * Set LLM usage limits for users on different pricing tiers * Track LLM usage on a per user and per organization basis * Block or redact requests containing PIIs * Improve LLM reliability with failovers, retries and caching * Distribute API keys with rate limits and cost limits for internal development/production use cases * Distribute API keys with rate limits and cost limits for students
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uAgents
uAgents is a Python library developed by Fetch.ai that allows for the creation of autonomous AI agents. These agents can perform various tasks on a schedule or take action on various events. uAgents are easy to create and manage, and they are connected to a fast-growing network of other uAgents. They are also secure, with cryptographically secured messages and wallets.
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griptape
Griptape is a modular Python framework for building AI-powered applications that securely connect to your enterprise data and APIs. It offers developers the ability to maintain control and flexibility at every step. Griptape's core components include Structures (Agents, Pipelines, and Workflows), Tasks, Tools, Memory (Conversation Memory, Task Memory, and Meta Memory), Drivers (Prompt and Embedding Drivers, Vector Store Drivers, Image Generation Drivers, Image Query Drivers, SQL Drivers, Web Scraper Drivers, and Conversation Memory Drivers), Engines (Query Engines, Extraction Engines, Summary Engines, Image Generation Engines, and Image Query Engines), and additional components (Rulesets, Loaders, Artifacts, Chunkers, and Tokenizers). Griptape enables developers to create AI-powered applications with ease and efficiency.