Multilingual AI Chat System
Multilingual AI Chat is a robust cross-platform chat application that supports both text and voice interactions across multiple languages.
It combines powerful open-source technologies to deliver a seamless and intelligent chat experience.
The project focuses on accessibility, performance, and privacy, running key components locally to ensure data security and speed.
Key Features
- Y-Shaped Pipeline – Unified processing architecture for both text and voice inputs
- Retrieval Augmented Generation (RAG) – Professional-grade information retrieval using FAISS
- Multilingual Support – Native support for English, Hindi, Tamil, and Telugu
- Cross-Platform Access – Available on iOS, Android, and Web
- Local Intelligence – Uses local models for embeddings and transcription for privacy
- Extensible Design – Easily add new languages or document sources
Tech Stack
The system is built using high-performance modern tools:
- Groq (Llama 3.3-70b) – Blazing-fast text generation
- HuggingFace – Local semantic embeddings (all-MiniLM-L6-v2)
- OpenAI Whisper – Accurate local audio transcription
- FastAPI – High-performance Python backend
- Expo (React Native) – Universal frontend for mobile and web
Project Goals
- Deliver a robust, multilingual AI chat experience
- Enable seamless text and voice input for all users
- Provide an open-source base for experimentation and learning
- Maintain a clean and extensible architecture for future growth
Open Source & Community
Multilingual AI Chat System is an open-source project built for the community.
We welcome contributors, researchers, and developers to explore and improve the project.
Contributing
Contributions are welcome! Please check the GitHub repository for details on how to contribute.
Here is how you can contribute:
- Fork the project
- Create your feature branch (
git checkout -b feature/AmazingFeature) - Commit your changes (
git commit -m 'Add some AmazingFeature') - Push to the branch (
git push origin feature/AmazingFeature) - Open a Pull Request