Wegent
An open-source AI-native operating system to define, organize, and run intelligent agent teams
Stars: 389
Wegent is an open-source AI-native operating system designed to define, organize, and run intelligent agent teams. It offers various core features such as a chat agent with multi-model support, conversation history, group chat, attachment parsing, follow-up mode, error correction mode, long-term memory, sandbox execution, and extensions. Additionally, Wegent includes a code agent for cloud-based code execution, AI feed for task triggers, AI knowledge for document management, and AI device for running tasks locally. The platform is highly extensible, allowing for custom agents, agent creation wizard, organization management, collaboration modes, skill support, MCP tools, execution engines, YAML config, and an API for easy integration with other systems.
README:
๐ An open-source AI-native operating system to define, organize, and run intelligent agent teams
English | ็ฎไฝไธญๆ
A fully open-source chat agent with powerful capabilities:
- Multi-Model Support: Compatible with Claude, OpenAI, Gemini, DeepSeek, GLM and other mainstream models
- Conversation History: Create new conversations, multi-turn dialogues, save and share chat history
- Group Chat: AI group chat where AI responds based on conversation context with @mentions
- Attachment Parsing: Send txt, pdf, ppt, doc, images and other file formats in single/group chats
- Follow-up Mode: AI asks clarifying questions to help refine your requirements
- Error Correction Mode: Multiple AI models automatically detect and correct response errors
- Long-term Memory: Supports mem0 integration for conversation memory persistence
- Sandbox Execution: Execute commands or modify files via sandbox, E2B protocol compatible
- Extensions: Customize prompts, MCP tools and Skills (includes chart drawing skill)
A cloud-based Claude Code execution engine:
- Multi-Model Configuration: Configure various Claude-compatible models
- Concurrent Execution: Run multiple coding tasks simultaneously in the cloud
- Requirement Clarification: AI analyzes code and asks questions to generate specification documents
- Git Integration: Integrate with GitHub/GitLab/Gitea/Gerrit to clone, modify and create PRs
- MCP/Skill Support: Configure MCP tools and Skills for agents
- Multi-turn Conversations: Continue conversations with follow-up questions
A cloud-based AI task trigger system:
- Full Capability Access: Tasks can use all Chat and Code mode capabilities
- Scheduled/Event Triggers: Set up cron schedules or event-based AI task execution
- Information Feed: Display AI-generated content as an information stream
- Event Filtering: Filter conditions like "only notify me if it will rain tomorrow"
A cloud-based AI document repository:
- Document Management: Upload and manage txt/doc/ppt/xls and other document formats
- Web Import: Import web pages and DingTalk multi-dimensional tables
- NotebookLM Mode: Select documents directly in notebooks for Q&A
- Online Editing: Edit text files directly in notebook mode
- Chat Integration: Reference knowledge bases in single/group chats for AI responses
Run AI tasks on your local machine with full control:
- Local Executor: Install and run the Wegent executor on your own device
- Multi-Device Management: Register and manage multiple local devices
- Default Device: Set a preferred device for quick task execution
- Secure Connection: Connect to Wegent backend via authenticated WebSocket
All features above are fully customizable:
- Custom Agents: Create custom agents in the web UI, configure prompts, MCP, Skills and multi-agent collaboration
- Agent Creation Wizard: 4-step creation: Describe requirements โ AI asks questions โ Real-time fine-tuning โ One-click create
- Organization Management: Create and join groups, share agents, models, Skills within groups
- Agent Creation Wizard: 4-step creation: Describe requirements โ AI asks questions โ Real-time fine-tuning โ One-click create
- Collaboration Modes: 4 out-of-the-box multi-Agent collaboration modes (Sequential/Parallel/Router/Loop)
- Skill Support: Dynamically load skill packages to improve Token efficiency
- MCP Tools: Model Context Protocol for calling external tools and services
- Execution Engines: ClaudeCode / Agno sandboxed isolation, Dify API proxy, Chat direct mode
- YAML Config: Kubernetes-style CRD for defining Ghost / Bot / Team / Skill
- API: OpenAI-compatible interface for easy integration with other systems
curl -fsSL https://raw.githubusercontent.com/wecode-ai/Wegent/main/install.sh | bashThen open http://localhost:3000 in your browser.
Optional: Enable RAG features with
docker compose --profile rag up -d
| Team | Purpose |
|---|---|
| chat-team | General AI assistant + Mermaid diagrams |
| translator | Multi-language translation |
| dev-team | Git workflow: branch โ code โ commit โ PR |
| wiki-team | Codebase Wiki documentation generation |
Frontend (Next.js) โ Backend (FastAPI) โ Executor Manager โ Executors (ClaudeCode/Agno/Dify/Chat)
Core Concepts:
- Ghost (prompt) + Shell (environment) + Model = Bot
- Multiple Bots + Collaboration Mode = Team
See Core Concepts | YAML Spec
We welcome contributions! Please see our Contributing Guide for details.
- ๐ Issues: GitHub Issues
- ๐ฌ Discord: Join our community
Thanks to the following developers for their contributions and efforts to make this project better. ๐ช
Made with โค๏ธ by WeCode-AI Team
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