Skip to content

Latest commit

 

History

History
134 lines (87 loc) · 2.86 KB

README.md

File metadata and controls

134 lines (87 loc) · 2.86 KB

Cheat Code — Your DSA Helper

Cheat Code is a Python-based GenAI-powered DSA assistant that helps you analyze and understand Data Structures & Algorithms problems using automation and AI.

⚠️ Disclaimer This project is built strictly for learning and experimentation purposes. It is NOT intended for cheating in interviews, exams, or competitive programming platforms.

🚀 Features

  • 🧠 AI-assisted DSA problem solving
  • 📸 Screenshot / image-based problem input
  • ☁️ Cloudinary image upload integration
  • ⚡ Groq LLM integration for fast responses
  • 🛠️ Modular and extendable Python utilities

📂 Project Structure

cheat-code/
├── main.py                # Main entry point
├── utils/                 # Helper utilities
├── requirements.txt       # Python dependencies
├── pyproject.toml         # Project configuration
├── README.md
└── .gitignore

🎬 Demo Video

You can watch the demo video directly below: https://res.cloudinary.com/dsloz7tfz/video/upload/v1767334920/Screen_Recording_2026-01-02_104618_1_uufsti.mp4

🛠️ Step-by-Step Setup Guide (UV Package Manager)

Step 1: Clone the Repository

git clone https://github.com/Tridib2510/cheat-code.git
cd cheat-code

Step 2: Install Dependencies Using UV

uv install

This will automatically create an isolated environment and install all required dependencies.

Step 3: Set Up Environment Variables

Create a .env file in the root directory of the project:

touch .env

Add the following variables to the .env file:

CLOUDINARY_CLOUD_NAME=your_cloudinary_cloud_name
CLOUDINARY_API_KEY=your_cloudinary_api_key
CLOUDINARY_API_SECRET=your_cloudinary_api_secret

GROQ_API_KEY=your_groq_api_key

🔑 Get API Keys From

Step 4: Run the Application with UV

uv run main.py

This ensures your project runs inside the UV-managed environment with all dependencies loaded.

🎯 Project Purpose

  • Learn how GenAI integrates with real-world developer tools
  • Experiment with vision + LLM pipelines
  • Build an AI-powered coding assistant
  • Create a strong portfolio project

🧩 Future Improvements

  • 🔍 Improved problem detection
  • 🧠 Better reasoning and explanations
  • 🖥️ GUI / Desktop application
  • 🔐 Safety & misuse prevention

🤝 Contributing

Contributions are welcome!

  1. Fork the repository
  2. Create a new branch
  3. Commit your changes
  4. Open a Pull Request

📜 License

This project is licensed under the MIT License.

⭐ If you find this project useful, consider giving it a star! Happy coding 🚀