Skip to content

Question-answering chatbot using OpenAI's GPT-3.5-turbo model, DeepLake for the vector database, and the Whisper API for voice transcription. The chatbot also uses Eleven Labs to generate audio responses.

License

Notifications You must be signed in to change notification settings

peterw/JarvisBase

Repository files navigation

JarvisBase

Question-answering chatbot using OpenAI's GPT-3.5-turbo model, DeepLake for the vector database, and the Whisper API for voice transcription. The chatbot also uses Eleven Labs to generate audio responses.

Basic Idea

  1. Get all the Huggingface Hub Python Library Articles
  2. Embed them with Deeplake
  3. Allow the user to record their voice or type their query
  4. Generate the repsonse and make an audio recording using elevenlabs

Installation

Clone the repository.

    git clone https://github.com/peterw/QnA.git

Install dependencies:

    pip install -r requirements.txt

Get your OpenAi API keys, Activeloop APi Keys and Eleven Labs API Keys and add them to your .env file.

Usage

To set up and run this project, follow these steps:

  1. Run the scrape.py script to embed the Intercom articles first

     python scrape.py
    
  2. Start the app

     streamlit run chat.py
    

Type your query in the input field and press enter. If you have a microphone, you can click the record button and transcribe your audio. Click the transcribe button to get the text. The bot will display the response in the chat history, and it will also be spoken using the Eleven Labs API.

Sponsors

✨ Find profitable ideas faster: Exploding Insights

License

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

About

Question-answering chatbot using OpenAI's GPT-3.5-turbo model, DeepLake for the vector database, and the Whisper API for voice transcription. The chatbot also uses Eleven Labs to generate audio responses.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages