JARVIS Minimal Autonomous AI

🚀 Project Purpose

A highly efficient, local autonomous AI assistant inspired by fictional AIs (JARVIS, HAL 9000, etc.), capable of planning, executing, and synthesizing tasks using LLMs and system resources. Designed for maximum maintainability and minimal code size.

🏗️ Architecture Overview

• agent_core.py: All core agent logic (planning, execution, LLM/Blackbox integration, safety, hardware checks)
• hardware.py: Hardware/resource monitoring (VRAM, RAM, CPU, temperature)
• Entry Points:
  • jarvis_agent_main.py: GUI interface
  • jarvis/scripts/jarvis_cli.py: Command-line interface
  • jarvis_ultimate_master.py: Master controller (for advanced orchestration)

All entry points are thin wrappers around the shared core agent.

⚡ Quick Start

1. Install dependencies:

   pip install -r requirements.txt

2. Run the GUI:

   python jarvis_agent_main.py

3. Run the CLI:

   python jarvis/scripts/jarvis_cli.py

4. Run the Master Controller:

   python jarvis_ultimate_master.py

🧩 Extending JARVIS

• Add new entry points by importing and using AgentCore.
• Add new LLM or Blackbox integrations by passing a compatible client to AgentCore.
• All hardware/resource checks are handled in hardware.py.

🛠️ Troubleshooting

• Ensure all dependencies are installed (requirements.txt).
• For LLM/Blackbox integration, replace the DummyLLMClient in entry points with your real client.
• Hardware/resource errors will be reported by the agent if limits are exceeded.

📁 Project Structure

jarvis/scripts/
  agent_core.py      # Core agent logic
  hardware.py        # Hardware/resource monitoring
  jarvis_cli.py      # CLI entry point
jarvis_agent_main.py # GUI entry point
jarvis_ultimate_master.py # Master controller

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JARVIS Minimal Autonomous AI — All the power, none of the bloat.