wecode-ai/Wegent

# Wegent > A self-hostable AI workspace for chat, coding, knowledge bases, automation, and local execution. English | [简体中文](README_zh.md) [](https://python.org) [](https://fastapi.tiangolo.com) [](https://nextjs.org) [](https://docker.com) [](https://claude.ai) [](https://ai.google.dev) [](https://github.com/wecode-ai/wegent/releases) [Quick Start](#-quick-start) · [Core Scenarios](#core-scenarios) · [How It Grows](#how-it-grows) · [Documentation](https://wecode-ai.github.io/wegent-docs/) · [Development Guide](https://wecode-ai.github.io/wegent-docs/docs/category/developer-guide) --- ## Why Wegent Wegent is a self-hostable AI workspace for managing chat, coding tasks, knowledge bases, automation, and local execution in one place. You can ask questions over your own materials, hand code repositories to AI, turn recurring information checks into automated feeds, and let your team use the same assistants from DingTalk, Telegram, or other tools. When a task needs local repositories or intranet access, it can run on your own machine. - Start privately: Launch a self-hosted workspace with one command and begin with chat and knowledge Q&A. - Grow into team workflows: Share common assistants, models, tools, and knowledge bases instead of configuring them repeatedly. - Choose where work runs: Run coding tasks, automation, and local-device jobs in the environment that fits the job. - Fit existing tools: Bring AI into your current workflow through APIs or IM bots. --- ## 🚀 Quick Start Prerequisite: Docker and Docker Compose. ``bash curl -fsSL https://raw.githubusercontent.com/wecode-ai/Wegent/main/install.sh | bash -s -- --standalone This starts the default Standalone mode: one container with SQLite for local trials and lightweight deployments. Then open http://localhost:3000 in your browser. ### Deployment Modes | Mode | Best For | |------|----------| | **Standalone** (default) | Single container + SQLite, best for personal trials and lightweight deployments | | **Standard** | Multi-container + MySQL + Redis, best for teams and production | | **Development** | Source startup + hot reload, best for development and extensions | bash # Standalone mode (default) curl -fsSL https://raw.githubusercontent.com/wecode-ai/Wegent/main/install.sh | bash -s -- --standalone # Standard mode curl -fsSL https://raw.githubusercontent.com/wecode-ai/Wegent/main/install.sh | bash -s -- --standard # Development mode git clone https://github.com/wecode-ai/Wegent.git && cd Wegent && ./start.sh Common Commands bash # Standalone mode docker logs -f wegent-standalone docker restart wegent-standalone # Standard mode docker compose logs -f docker compose down docker compose up -d # Development mode ./start.sh --status ./start.sh --restart ./start.sh --stop `` See [Standalone Mode](docs/en/deployment/standalone-mode.md) and [Quick Start](docs/en/getting-started/quick-start.md) for details. --- ## Core Scenarios ### Chat, Group Chat, and File Handling Set up a private AI chat entrypoint. Wegent supports multiple models, multi-turn history, group chat with @mentions, file parsing, clarifying questions, answer checking, and long-term memory. When needed, AI can also read files, run commands, or generate diagrams. ### Let AI Work on Code Repositories Let AI work on code in isolated environments. Wegent connects to GitHub, GitLab, Gitea, and Gerrit so agents can clarify requirements, create branches, modify code, run tests, commit changes, and open pull requests. ### Track Information and Publish Feeds Turn AI into a continuously running task trigger. Set schedules or event triggers so AI can summarize information, analyze webpages, filter notifications, and publish results as a feed. ### Knowledge Q&A Upload documents, import webpages, or sync DingTalk multi-dimensional tables to build team knowledge bases. Wegent handles parsing, conversion, indexing, and retrieval so AI can answer with your own materials. ### Local Device Execution Install a local runner on your own machine and connect it securely to Wegent. Tasks can switch between cloud environments and local devices, which is useful when AI needs access to local repositories, intranet resources, or dedicated development environments. ### Team Tools and Existing Systems Connect Wegent agents to DingTalk, Telegram, and other IM tools, or call them from existing applications through an API. --- ## How It Grows You do not need to learn every concept upfront. Wegent can start as a private AI workspace: choose a model, cre