AI Voice Assistant using Groq, Llama 3 and Deepgram

This repository contains an AI Voice Assistant application built with Python and React, utilizing Deepgram for speech-to-text and text-to-speech functionality, and Llama 3 with Groq for natural language processing.

You can access a live demo of the AI Voice Assistant application in this link.

For a detailed walkthrough of the code and the technologies used, check out our blog post series:

• Part 1: A local Python voice assistant app.
• Part 2: A Python backend with FastAPI & WebSockets.
• Part 3: An interactive React user interface.

This project was developed by CodeAwake, and is licensed under the MIT License.

Structure

The repository is organized into two main folders:

• backend/: Contains the Python FastAPI backend code and a simple local Python assistant.
• frontend/: Contains the React Next.js frontend code.

Installation

Prerequisites ✅

• Python 3.11 or higher
• Node.js 18.17 or higher
• Poetry (Python package manager)

Backend

1. Navigate to the backend folder and install the Python dependencies using Poetry:

   cd backend
   poetry install

2. Create a .env file in the backend folder copying the .env.example file provided and set the required environment variables:

   • GROQ_API_KEY: Your Groq API key.
   • DEEPGRAM_API_KEY: Your Deepgram API key.

Frontend

1. Navigate to the frontend folder and install the JavaScript dependencies:

   cd frontend
   npm install

2. Create a .env file in the frontend folder copying the .env.example file provided that includes the required environment variable:

   • NEXT_PUBLIC_WEBSOCKET_URL: The WebSocket URL to connect to the backend API.

Running the Application

Local Python Assistant

You can run the local Python assistant script using the provided Poetry script:

cd backend
poetry run local-assistant

Full-Stack Web Application

To run the full-stack web application:

1. Activate the virtual environment for the backend and start the backend server:

   cd backend
   poetry shell
   fastapi dev app/main.py

2. In a separate terminal, start the frontend server:

   cd frontend
   npm run dev

3. Open your web browser and visit http://localhost:3000 to access the application.