VoxChain

VoxChain is a cutting-edge, real-time voice-to-voice AI chat application. It allows users to have natural spoken conversations with an AI assistant. The system captures audio, transcribes it locally, processes it through a Large Language Model (LLM), and synthesizes a spoken response back to the user—all in real-time.

✨ Features

• 🗣️ Voice-to-Voice Interaction: Seamless audio input and output.
• ⚡ Real-time Transcription: Uses OpenAI's Whisper model for accurate speech-to-text.
• 🧠 Intelligent Responses: Powered by LangChain and HuggingFace (Qwen 2.5) for conversational intelligence.
• 🔊 Text-to-Speech: Converts AI text responses back to audio using gTTS (Google Text-to-Speech).
• 🎨 Glassmorphism UI: A beautiful, modern interface built with React and CSS variables.
• 🔌 WebSocket Streaming: Low-latency communication between frontend and backend.
• 🐳 Dockerized: Fully containerized for easy deployment.

🛠️ Tech Stack

Frontend

• Framework: React TS
• node: v20

Backend

• Framework: FastAPI
• Language: Python 3.12.3
• Protocol: WebSockets
• AI Models:
  • Transcription: OpenAI Whisper (small model)
  • LLM: HuggingFace (Qwen/Qwen2.5-1.5B-Instruct)
  • TTS: gTTS

Infrastructure

• Containerization: Docker & Docker Compose
• System Dependencies: FFmpeg (for audio processing)

🚀 Getting Started

Prerequisites

• Not fully configured for running: Docker & Docker Compose
• For local dev without Docker:
  • Node.js v20
  • Python 3.12.3
  • FFmpeg installed and added to system PATH.

👨‍💻 Manual Local Development

Please prefer to run services individually:

Environment Setup

Create a .env file in the root directory (copy from .env.example):

cp .env.example .env

Important: You must add your HuggingFace API Token in .env:

HUGGINGFACE_API_TOKEN=your_token_here

Frontend

cd frontend
npm install
cp .env.example .env
npm run dev

Backend

1. Ensure FFmpeg is installed on your system.
2. Create virtual environment:

   cd backend
   cp .env.example .env
   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies:

   pip install -r requirements.txt

4. Run server:

   uvicorn main:app --reload --host 0.0.0.0 --port 8000

📁 Project Structure

voxchain/
├── backend/                # FastAPI Python Backend
│   ├── api/                # WebSocket Routes
│   ├── services/           # Core AI Services (LLM, Transcriber, Synthesizer)
│   ├── main.py             # Entry point
│   ├── requirements.txt    # Python deps
│   └── Dockerfile
├── frontend/               # React Frontend
│   ├── src/
│   │   ├── components/     # UI Components (AudioPlayer, InputArea, etc.)
│   │   ├── hooks/          # Custom hooks (useVoiceChat)
│   │   └── App.tsx         # Main App logic
│   └── Dockerfile
├── docker-compose.yml      # Orchestration
└── README.md