This repository contains two Python scripts that demonstrate how to create a chatbot using Streamlit, OpenAI GPT-3.5-turbo, and Activeloop's Deep Lake.

The chatbot searches a dataset stored in Deep Lake to find relevant information and generates responses based on the user's input.

github.py: This script clones a git repository, processes the text documents, computes embeddings using OpenAIEmbeddings, and stores the embeddings in a DeepLake instance.

chat.py: This script creates a Streamlit web application that interacts with the user and the DeepLake instance to generate chatbot responses using OpenAI GPT-3.5-turbo.

Before getting started, be sure to sign up for an Activeloop and OpenAI account and create API keys. You'll also want to create a Deep Lake dataset, which will generate a dataset path in the format hub://{username}/{repo_name} (where you define the repo_name).

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

1. Install the required packages with pip:

   pip install -r requirements.txt
   

2. Copy the .env.example file to .env and replace the variables, including API keys, GitHub URL, and site / Deep Lake information.
3. Run the github.py script to embed the GitHub repo, thus, storing the data in the specified Activeloop Deep Lake.
4. Run the Streamlit chat app, which should default to http://localhost:8502 and allow you to ask questions about the repo:

   streamlit run chat.py