Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/aquibali01/voice-to-text-and-voice-chatbot

Voice-to-Voice Chatbot using Whisper, LLaMA, and Groq API
https://github.com/aquibali01/voice-to-text-and-voice-chatbot

chatbot gtts llama8b llm opeai python voice whisper

Last synced: 23 days ago
JSON representation

Voice-to-Voice Chatbot using Whisper, LLaMA, and Groq API

Awesome Lists containing this project

README 

        
# Voice-to-Voice Chatbot using Whisper, LLaMA, and Groq API



This project is a real-time voice-to-voice chatbot that leverages OpenAI's Whisper for speech-to-text transcription, LLaMA 8B via the Groq API for generating responses, and Google Text-to-Speech (gTTS) for converting text back into speech. The chatbot interface is built using Gradio, allowing users to interact with the bot by speaking or uploading audio files.



## Features



- **Speech-to-Text**: Convert spoken language into text using OpenAI's Whisper model.

- **AI-Generated Responses**: Use LLaMA 8B via the Groq API to generate intelligent responses based on the transcribed text.

- **Text-to-Speech**: Convert the generated text responses back into speech using Google Text-to-Speech (gTTS).

- **Real-Time Interaction**: The chatbot works in real-time, allowing users to interact through a microphone or by uploading audio files via a web interface.

  

## Prerequisites



Before you begin, ensure you have met the following requirements:



- Python 3.7 or higher installed on your local machine or Google Colab.

- A Groq API key. You can sign up for an API key [here](https://groq.com/).

- [Google Colab](https://colab.research.google.com/) or a local Python environment with necessary libraries installed.



## Installation



Follow these steps to set up the project:



1. **Clone the Repository:**



   git clone https://github.com/aquibali01/voice-to-voice-chatbot.git

   

   cd voice-to-voice-chatbot



3. **Install Dependencies:**



Install the required Python libraries:

    

    pip install -r requirements.txt



Alternatively, if you are using Google Colab, you can install the libraries using:



    !pip install gradio groq-api openai-whisper gtts



Set Up Groq API Key:



Add your Groq API key to the environment variables:



    export GROQ_API_KEY='your_groq_api_key'



In Google Colab, you can set the API key using:



    import os

    os.environ['GROQ_API_KEY'] = 'your_groq_api_key'



Usage



To start the chatbot, run the main script:



    python voice_to_voice_chatbot.py



Or in Google Colab:



Copy the script to a code cell and execute.



The Gradio interface will launch, allowing you to interact with the chatbot.

Interacting with the Chatbot



Using Microphone: Speak directly into the microphone. The chatbot will transcribe your speech, generate a response, and play it back as audio.



Uploading Audio: Upload a pre-recorded audio file. The chatbot will transcribe the audio, generate a response, and convert the response back to speech.



**Project Structure**



    voice-to-voice-chatbot/

    ├── voice_to_voice_chatbot.py  # Main script to run the chatbot

    ├── requirements.txt       # List of Python dependencies

    ├── README.md              # Project documentation

    └── .gitignore             # Git ignore file



**Troubleshooting**



Common Issues



ModuleNotFoundError: Ensure you have installed the correct version of the Whisper module with 



    !pip install -U openai-whisper



Groq API Key Error: Double-check your API key and ensure it is set in the environment variables correctly.



**Contributing**



Contributions are welcome! Please fork this repository, create a new branch, and submit a pull request with your changes.



**License**

This project is licensed under the MIT License. See the LICENSE file for details.