🛠️ AI-Powered Python Code Execution

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📌 Project Overview

This project provides a secure AI-powered Python code execution environment. Users can input natural language prompts, and the system:

1. Uses Hugging Face LLM to generate Python code.
2. Executes the code in a secure Docker container.
3. Debugs errors & iterates until correct output.
4. Explains the generated code.

🚀 Features:

✅ LLM-Generated Python Code (Using Hugging Face API) ✅ Secure Execution with Docker (Prevents system access) ✅ Automated Debugging & Fixes (Iterates until correct output) ✅ Explains Code & Optimizations ✅ Full-Stack Integration (Fastify backend, Next.js frontend)

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🏗️ Project Structure

ide-docker-py/
│── frontend/            # Next.js frontend (React + Tailwind CSS)
│── python-secure/       # Dockerized Python execution environment
│   ├── Dockerfile      # Defines secure Python execution container
│   ├── requirements.txt # Minimal dependencies (if needed)
│   ├── safe_executor.py # Executes AI-generated Python code securely
│── src/                # Fastify backend for LLM & execution
│   ├── server.js       # Main backend API (LLM + Docker execution)
│   ├── config.js       # Configuration settings
│  
│── docker-compose.yml  # Containerized setup for easy deployment
│── package.json        # Backend dependencies
│── README.md           # Project documentation

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🔧 Installation & Setup

1️⃣ Clone the Repository

git clone https://github.com/your-repo/ide-docker-py.git
cd ide-docker-py

2️⃣ Install Backend Dependencies

pnpm install  # Install Fastify & Hugging Face SDK

3️⃣ Set Hugging Face API Key

export HF_TOKEN="your_huggingface_api_key"

5️⃣ Start Backend Server

cd ide-docker-py
pnpm start

6️⃣ Start Frontend

cd frontend
pnpm dev

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🖥️ How It Works

1️⃣ User provides a natural language prompt (e.g., "Write a Python script to sort a list").
2️⃣ LLM (Hugging Face API) generates Python code.
3️⃣ Code runs inside a secure Docker container.
4️⃣ If errors occur, AI fixes the code & retries execution.
5️⃣ The system returns the output & explains the code.

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🐳 Docker Execution

Building & Running the Secure Python Container

cd ide-docker-py
sudo docker-compose -f docker-compose.yml up --build

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📜 API Endpoints

🔹 Generate & Execute Code

POST /execute

{
  "prompt": "Create a Python script to calculate Fibonacci numbers"
}

📤 Response:

{
  "success": true,
  "iterations": 1,
  "code": "def fibonacci(n): ...",
  "output": "0 1 1 2 3 5 ...",
  "explanation": "This script calculates Fibonacci numbers..."
}

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🤝 Contributing

🚀 Feel free to fork this repository and submit pull requests!

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⚖️ License

This project is open-source under the GNU Public License.