Chandana is a powerful application that combines translation capabilities with an intelligent question-answering system. It features a Flask backend API and a React frontend interface.
Chandana is live and accessible at: Chandana
- Team Name: ramyaparsania4
- Team Members:
- Translation Service: Supports multiple language translation using Google Translator
- Smart Q&A System: Context-aware question answering using LLaMA 3 model via Groq
- Semantic Search: Utilizes sentence transformers for intelligent context matching
- Modern Frontend: React-based user interface for seamless interaction
- Responsive Design: Optimized for various screen sizes
- Retrieving relevant information: Utilizes semantic search to retrieve the most relevant information from the context and return the most relevant audio
- Flask (Python web framework)
- NLTK for natural language processing
- SentenceTransformer for text embeddings
- Groq API for LLM integration
- deep-translator for translation services
- React
- Material UI components
- Axios for API calls
- Python 3.8+
- Node.js and npm
- Groq API key
- Environment variables set up
Please make sure to run the backend locally before running the frontend, and enter the API keys in the .env file
- Clone the repository:
git clone https://github.com/melohub-xbit/MLFiesta-FatalErrors- Install backend dependencies:
pip install -r requirements.txt- Setup environment variables in a .env file like this:
GROQ_API_KEY=your_groq_api_key
HUGGINGFACE_TOKEN=your_huggingface_token- Install frontend dependencies (or use the deployed frontend link to use our application):
cd frontend
npm install- Start the backend server:
python main.py- Start the frontend server (no need to do this if using the deployed frontend link):
cd frontend
npm startAnd you can run our application from the frontend page that opens up
Find the Youtube link at: MLFiesta Demo