Python AI Compiler Engine

A Multi-Output Python Runner with AI Assistance
© 2025 **Pratipal Kumar Singh

🚀 Overview

This project is a lightweight Python compiler/runner that executes user-provided code in a safe, sandboxed environment and returns structured output.
It also supports saving results as PNG or JPG images, along with optional Gemini-powered AI features such as:

• Code explanation
• Error debugging
• Smart test-case suggestions
• Code formatting

This system is ideal for internship platforms, coding assessments, training portals, and project-based learning.

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🔧 Features

• Execute Python code safely
• Capture stdout, stderr, runtime, and exit codes
• Save output as PNG/JPG using Pillow
• Download results as .txt
• Sandbox restrictions: limited resources, isolated execution
• AI Integration (optional)
  • Error explanation
  • Code enhancement
  • Test-case generation
• REST API + CLI support
• Industrial use-case ready

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📂 Folder Structure (Suggested)

PYTHON-COMPILER-ENGINE/
├─ README.md
├─ LICENSE
├─ requirements.txt
└─ index.html

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🛠️ Installation

Requirements

• Python 3.10+
• pip
• (Optional) Gemini AI API Key

Install dependencies

python -m venv .venv      # Windows: .venv\Scripts\activate
pip install -r requirements.txt

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🔐 Environment Variables

Create a .env file:

GEMINI_API_KEY=your_key_here
GEMINI_ENDPOINT=https://api.gemini.example/v1
APP_SECRET_KEY=random_string

Never commit .env to GitHub.

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▶️ Usage

🖥️ CLI Example

python run_code.py --file main.py --save-image output.png

🌐 REST API Example

POST /run

{
  "language": "python",
  "source": "print('Hello AI Compiler!')",
  "save_image": true,
  "image_format": "png"
}

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🖼️ Output Image Handling

• Outputs rendered using Pillow
• Monospaced fonts for clarity
• Optionally render in HTML and capture screenshot using headless browser

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🤖 AI Integration (Optional)

import requests, os

resp = requests.post(
    f"{os.getenv('GEMINI_ENDPOINT')}/v1/assist",
    headers={"Authorization": f"Bearer {os.getenv('GEMINI_API_KEY')}"},
    json={"prompt": "Explain this Python error: ..."}
)

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🔒 Security

To safely execute untrusted code:

• Use Docker/Firecracker sandbox
• Strict timeouts
• Disable network
• Memory and CPU limits
• Isolate filesystem

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🤝 Contributing

1. Fork repo
2. Create feature branch
3. Submit PR
4. Ensure tests pass

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📜 License

Released under the MIT License.
© 2025 Pratipal Kumar Singh — All rights reserved where applicable.

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📬 Contact

For queries or collaborations:
Pratipal Kumar Singh
kumarpratipal123@gmail.com