GitHub Automated Analysis with LangChain, ChatGPT, and Streamlit: Find the Most Complex Repository

In this video, we will show you how to use LangChain, ChatGPT, and Streamlit to automate GitHub analysis and find the most complex repository of a GitHub account. LangChain is a library that allows you to combine large language models (LLMs) with other sources of computation or knowledge. ChatGPT is an LLM from OpenAI that can be used for a variety of tasks, including natural language generation, translation, and question answering. Streamlit is a Python library that makes it easy to create interactive web applications.

We will show you how to use LangChain to create a chain that queries ChatGPT to perform data analysis on a GitHub repository. This chain will be able to answer questions about the repository, such as the number of stars, the number of forks, and the most popular commit messages. We will then use Streamlit to create a web application that allows you to interact with the chain and find the most complex repository of a GitHub account.

This video is for anyone who wants to learn how to use LangChain, ChatGPT, and Streamlit to automate GitHub analysis and find the most complex repository. No prior experience with any of the libraries is required.

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