This project provides OpenClaw AI Agent framework users with a visual management panel, simplifying installation, configuration, diagnostics, and repair. It targets both novice and expert users, offering an intuitive GUI enhanced by a built-in AI assistant that streamlines complex tasks and troubleshooting.

How It Works

The panel is built using Rust with Tauri v2 for a performant, cross-platform native backend, and Vanilla JS with Vite for a lightweight, fast frontend. Its core innovation is an integrated AI assistant capable of tool calling, image recognition, and multi-modal interaction. This AI can directly execute system commands, read/write files, and interact with users to diagnose issues, automate repairs, and even assist in generating bug reports and pull requests.

Quick Start & Requirements

• Primary Install/Run:
  • Desktop: Download and install .dmg (macOS), .exe/.msi (Windows), or .AppImage/.deb/.rpm (Linux) from GitHub Releases.
  • Linux Server (Web): curl -fsSL https://raw.githubusercontent.com/qingchencloud/clawpanel/main/scripts/linux-deploy.sh | bash
  • Docker: docker run -d --name clawpanel --restart unless-stopped -p 1420:1420 -v clawpanel-data:/root/.openclaw node:22-slim sh -c "apt-get update && apt-get install -y git && npm install -g @qingchencloud/openclaw-zh --registry https://registry.npmmirror.com && git clone https://github.com/qingchencloud/clawpanel.git /app && cd /app && npm install && npx vite --port 1420 --host 0.0.0.0"
• Prerequisites: For building from source: Node.js >= 18, Rust (stable), Tauri v2. Windows users may need Git installed and Node.js added to the system PATH.
• Links: 官网: claw.qt.cool, Downloads: GitHub Releases, Linux Deploy Guide, Docker Deploy Guide.

Highlighted Details

• AI Assistant: Features 4 operation modes (Chat, Plan, Execute, Infinite), 8 distinct tools (e.g., run_command, read_file, ask_user), and interactive Q&A for system management.
• Image Recognition: Supports multi-modal input by allowing users to paste or drag-and-drop screenshots for AI analysis and conversation.
• Automated Operations: AI can automatically gather system information, list directories, analyze configurations, and generate health check reports.
• Developer Assistance: AI aids in bug reporting by collecting logs and environment details for GitHub Issues, and can generate code fixes via Git commands for PRs.

Maintenance & Community

The project welcomes contributions via Issues and Pull Requests, with details in CONTRIBUTING.md. Community channels include QQ groups, WeChat groups, Discord, Yuanbao Pai, and GitHub Discussions. Sponsorship from "慈云数据服务团队" is acknowledged.

Licensing & Compatibility

The project is released under the MIT License, which is permissive for commercial use and integration into closed-source projects.

Limitations & Caveats

On macOS, unsigned application builds may be blocked by Gatekeeper, requiring manual user intervention. On Windows, Node.js PATH detection might fail for non-standard installations, necessitating manual PATH configuration or restarting the application.