Code-Revive

Code Revive is an innovative application that enables developers to convert codebases between different programming languages seamlessly. Powered by the LLAMA 3 model, this app utilizes the GROQ API and is built with Streamlit, providing an intuitive and interactive user interface for efficient code translation.

Features

• Language Conversion: Convert code snippets or entire codebases from one programming language to another with high accuracy.
• Interactive Interface: A user-friendly web application built with Streamlit for real-time code input and output display.
• GROQ API Integration: Leverage the GROQ API for efficient querying and data manipulation to optimize the conversion process.
• Documentation and Support: Documentation on the Code Base.

Technologies Used

• LLAMA 3: A state-of-the-art language model for advanced language processing.
• Streamlit: A framework for building interactive web applications with ease.
• GROQ API: A powerful query language and API for efficient data handling.

Installation

To set up Code Revive locally, follow these steps:

1. Clone the repository

   git clone https://github.com/wepandas4/Code-Revive.git
   cd Code-Revive

2. Create a virtual environment

   python -m venv venv
   venv\Scripts\activate # On Linux use `source venv/bin/activate`

3. Install the required packages

   pip install -r requirements.txt

4. Replace Groq API

    client = Groq(api_key='YOUR_API_KEY')

5. Run the Streamlit app

   streamlit run app.py

Usage

1. Open your web browser and go to http://localhost:8501.
2. Input your codebase Zip file.
3. Select the target programming language from the dropdown menu.
4. Click the "Convert" button to see the converted code in real-time.

Contributing

Contributions are welcome! If you'd like to contribute to Code Revive, please follow these guidelines:

1. Fork the repository.
2. Create a new branch (git checkout -b feature/YourFeature).
3. Make your changes and commit them (git commit -m 'Add some feature').
4. Push to the branch (git push origin feature/YourFeature).
5. Open a pull request.

Acknowledgments

• Special thanks to the contributors and the open-source community for their support.
• Acknowledgment of the developers of LLAMA 3 and GROQ API for their groundbreaking technologies.

About the Team

This project was developed by our dedicated team. We are proud of our collective efforts and the innovative solutions we've created!

Team Member	GitHub Profile	Email
Priyanka M K	Priyaaaa2	priyankamk2903@gmail.com
Sumukh C	Sumu004	sumukhchaluvaraj@gmail.com
Ravi J Gowda	RaviGowda29	ravigowdaedu29@gmail.com
Yashwanth M	yashwanthm3012	dev.yashwanthm3012@gmail.com

We appreciate the hard work and collaboration that made this project possible!