Youtube Video Summarizer 🎥✨

This program provides concise summaries of YouTube videos to help users decide whether they should watch them.

Table of Contents

• Overview
• Example Output
  • Summary
  • Decision
• Usage
  • How to Run
• Contributing

Overview 🚀

This repository contains a sophisticated program that utilizes OpenAI's GPT-3.5 Turbo model to generate summarized versions of YouTube videos. The aim is to assist users in understanding the essence of the video content and make informed decisions regarding their viewership.

Example Output 💡

The program processes a YouTube video transcript and generates a summarized text. Here's an example of the output:

What's going on, guys? Welcome back. In this video today, we're going to learn how to render LaTeX formulas into images using Python. Let's get right into it ... [rest of the transcript]

Summary 📝

This YouTube video instructs viewers on rendering LaTeX formulas into images using Python. The tutorial demonstrates the conversion of LaTeX formulas into PNG images, suitable for integration into blog posts or documents. The presenter explains the process step by step, covering package installation and coding requirements to generate the images. Additionally, the video offers examples of different LaTeX formulas and how to convert them into images. Overall, this tutorial provides a practical and efficient method for automating the conversion of LaTeX formulas into image files.

Decision ✅

Based on the summary, individuals interested in learning how to convert LaTeX formulas into images using Python will find value in watching this video. The presenter delivers clear explanations and a step-by-step walkthrough, facilitating easy comprehension and implementation of the provided code. Furthermore, the video showcases practical examples and use cases for converting LaTeX formulas into image files.

Usage 🛠️

How to Run 🏃

To utilize this program, follow these steps:

1. Clone this repository to your local machine.
2. Install the necessary dependencies using npm or yarn.
3. Replace <API KEY> in the code with your OpenAI API key.
4. Run the program.

Contributing 🙌

Contributions are highly encouraged! If you'd like to enhance this program or propose new features, please feel free to open an issue or submit a pull request.