Action Model

Overview

Action Model is a FastAPI-based application that interacts with an LLM (GPT-4o-mini) to generate, validate, and execute Bash commands in a controlled environment. The system uses LangGraph for state management and Docker for script execution.

Features

🛠 FastAPI Backend: Provides an API for handling user queries.

⚡ Asynchronous Execution: Uses async/await for non-blocking operations.

🤖 LLM Integration: Interacts with GPT-4o-mini to generate and validate Bash commands.

🔍 Command Validation: Ensures that generated commands are correct before execution.

🖥 Bash Script Execution: Runs validated commands inside a controlled Docker environment.

📜 Session-Based Communication: Supports thread-based execution with a session ID.

File Structure

.
├── fast.py           # FastAPI application
├── main.py           # CLI-based interaction
├── model.py          # LangGraph state management & LLM interactions
├── script.py         # Bash script execution logic
├── templates/        # Prompt templates for LLM
├── requirements.txt  # Python dependencies
└── README.md         # Documentation

Installation & Usage (Docker)

Prerequisites

• Docker (for script execution)
• OpenAI API Key (required for LLM interactions)

Steps

1. Clone the repository

   git clone https://github.com/noxs1d/action-model.git
   cd action-model

2. Set up environment variables

   export OPENAI_API_KEY=your_api_key_here

3. Build the Docker image

   docker build -t action-model .

4. Run the container

   docker run -p 8000:8000 --env OPENAI_API_KEY=$OPENAI_API_KEY --name action-model action-model

The API will be available at http://localhost:8000/docs.

Future Improvements

• 🛡 Enhance Security: Implement command whitelisting to prevent dangerous operations.
• 🚀 Improve Async Handling: Replace blocking subprocess.run() with asyncio.create_subprocess_exec().
• ✅ Add Unit Tests: Use pytest to ensure API stability.
• 📊 Implement Logging: Improve debugging with structured logs.

Author

Nurmukhammed