peterw / Chat-with-Github-Repo

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.

Chat-with-Github-Repo

This repository contains 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 from any Git repository and generates responses based on the user's input.

Files

• src/utils/process.py: This script clones a Git repository, processes the text documents, computes embeddings using OpenAIEmbeddings, and stores the embeddings in a DeepLake instance.

• src/utils/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.

• src/main.py: This script contains the command line interface (CLI) that allows you to run the chatbot application.

Setup

Before getting started, be sure to sign up for an Activeloop and OpenAI account and create API keys.

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

1. Clone the repository and navigate to the project directory:

git clone https://github.com/peterw/Chat-with-Git-Repo.git
cd Chat-with-Git-Repo

2. Install the required packages with pip:

pip install -r requirements.txt

For development dependencies, you can install them using the following command:

pip install -r dev-requirements.txt

3. Set the environment variables:

Copy the .env.example file:

cp .env.example .env

Provide your API keys and username:

OPENAI_API_KEY=your_openai_api_key
ACTIVELOOP_TOKEN=your_activeloop_api_token
ACTIVELOOP_USERNAME=your_activeloop_username

4. Use the CLI to run the chatbot application. You can either process a Git repository or start the chat application using an existing dataset.

For complete CLI instructions run python src/main.py --help

To process a Git repository, use the process subcommand:

python src/main.py process --repo-url https://github.com/username/repo_name

You can also specify additional options, such as file extensions to include while processing the repository, the name for the Activeloop dataset, or the destination to clone the repository:

python src/main.py process --repo-url https://github.com/username/repo_name --include-file-extensions .md .txt --activeloop-dataset-name my-dataset --repo-destination repos

To start the chat application using an existing dataset, use the chat subcommand:

python src/main.py chat --activeloop-dataset-name my-dataset

The Streamlit chat app will run, and you can interact with the chatbot at http://localhost:8501 (or the next available port) to ask questions about the repository.

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License

MIT License