A Python-based tool that, when given a GitHub user's URL, returns the most technically complex and challenging repository from that user's profile. The tool uses Langchain, OpenAI gpt-3.5-turbo model as API, and FAISS as vector store which efficient Prompt Engineering under the hood.
These instructions will help you set up the project and run it on your local machine.
- Install [Python](https://www.python.org/downloads/) 3.9.0 or later
- Set up a virtual environment if you want (Recommended)
-
Clone the repository to your local machine.
git clone https://github.com/AbhishekRP2002/Github-Automated-Analysis-Tool.git
-
Go to the project folder.
cd Github-Automated-Analysis-Tool
-
Create a virtual environment.
python -m venv venv
-
Activate the virtual environment.
- On Windows:
.\venv\Scripts\activate
- On Linux or MacOS:
source venv/bin/activate
- On Windows:
You can use
conda
or packages for setting the virtual environment.
- Install the required dependencies using the following command.
pip install -r requirements.txt
-
Run the streamlit application.
streamlit run app.py
-
Open your web browser and enter the URL shown in the terminal, usually
http://localhost:8501
-
Enjoy and tweak your Python Streamlit project!
This project is licensed under the MIT License - see the LICENSE.txt file for details.