openclaw-workspace

Summary

Taruns Claw is an AI assistant workspace engineered to support and manage intelligent agents. It includes both backend and frontend components, with a focus on personalized memory, user context, and modular customization. The workspace provides a structured approach for managing agent identity, tools, memory, and user information.

Included Assets

• Core Workspace Files:

  • AGENTS.md — Workspace overview and daily workflow for the AI agent.
  • SOUL.md — Defines assistant philosophy, boundaries, and behavior guidelines.
  • TOOLS.md — Local environment-specific setup notes (e.g., devices, aliases).
  • HEARTBEAT.md — Task scheduling for periodic checks.
  • IDENTITY.md — AI assistant’s identity details.
  • USER.md — Profile and context for the primary user (Tarun).
  • memory/YYYY-MM-DD.md — Daily memory logs for session continuity.

• Backend (Python):

  • backend/server.py — FastAPI app, integrates MongoDB, handles API/websocket, manages agent gateway, WhatsApp monitor, and environment configs.
  • backend/backend_test.py — API test runner script.
  • backend/gateway_config.py — Secure environment variable & secret management for gateway processes.
  • backend/install_moltbot_deps.sh — Installs Node.js and required persistent dependencies.
  • backend/supervisor_client.py — Supervisor client for gateway process control.
  • backend/whatsapp_monitor.py — Monitors and resolves WhatsApp registration state.

• Frontend (JavaScript/React):

  • frontend/README.md — Quickstart for Create React App-based frontend.
  • frontend/package.json — Frontend dependencies and scripts.
  • frontend/jsconfig.json — Path alias and base URL setup.
  • frontend/craco.config.js — Custom CRACO/Webpack and environment configuration.
  • frontend/components.json — UI kit configuration and component aliases.

How to Use

1. Workspace Structure & Memory:

   • Begin each agent session by reviewing SOUL.md, USER.md, and recent memory/YYYY-MM-DD.md files.
   • Update memory files to track context and decisions. Use MEMORY.md only for curated, long-term knowledge (main session only).

2. Backend:

   • Ensure Python dependencies are installed.
   • Configure environment variables (such as MONGO_URL) as required by backend/server.py.
   • Use backend/install_moltbot_deps.sh on supported Linux systems to install Node.js and other persistent dependencies for gateway operations.
   • Run backend/server.py to start the API service.

3. Frontend:

   • Navigate to the frontend directory.
   • Run npm install to install dependencies.
   • Use npm start to launch the development server (http://localhost:3000), or npm run build for a production build.
   • Configure UI and components via components.json and CRACO as needed.

4. Agent Customization:

   • Add or modify skills, environment notes, or device setups in TOOLS.md.
   • Define and adapt assistant behaviors and philosophy via SOUL.md and IDENTITY.md.

Notes

• The workspace is designed for clarity and modularity; the AI agent relies on the provided Markdown files for both its memory and operational philosophy.
• Backend components require Python 3.8+ and MongoDB.
• The frontend is built with React and fully bootstrapped with Create React App.
• For persistent backend operations, Node.js is auto-installed to /root by the provided script (Linux only).
• Workspace memory logs (memory/) should be maintained for assistant continuity but do not store sensitive secrets unless explicitly intended.
• See frontend/README.md for further details on React app management.

This workspace provides a complete personal AI agent environment with explicit, file-driven memory and modular backend/frontend architecture.