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YouTube Video Summarizer

This repository contains a Python application built with Streamlit that converts YouTube video transcripts into detailed notes using Google's Generative AI.

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Overview

The application allows users to input a YouTube video URL, which is then used to extract the transcript using the youtube_transcript_api. The extracted transcript is then fed into Google's Generative AI model (Gemini Pro) along with a predefined prompt to generate a detailed summary of the video content.

Features

  • YouTube Video URL Input: Users can input the URL of the YouTube video they want to summarize.

  • Thumbnail Display: The application displays the thumbnail image of the input YouTube video.

  • Transcript Extraction: Utilizes the youtube_transcript_api to extract the transcript from the provided YouTube video URL.

  • Generation of Detailed Notes: Utilizes Google's Generative AI model (Gemini Pro) to generate a detailed summary of the video content based on the extracted transcript and a predefined prompt.

  • Streamlit Interface: The application is built using Streamlit, allowing for a user-friendly and interactive interface.

Installation and Usage

  1. Clone the Repository:

    git clone https://github.com/HimanshuGitCode/Youtube-Video-Summarizer.git

  2. Install Dependencies:

    pip install -r requirements.txt

  3. Run the Application:

    streamlit run app.py

  4. Input YouTube Video URL: Enter the YouTube video URL in the provided text input field and click on the "Get Detailed Notes" button.

  5. View Detailed Notes: Once the detailed notes are generated, they will be displayed on the interface.

Dependencies

  • streamlit: Open-source Python library that makes it easy to create web apps for machine learning and data science.
  • dotenv: Loads environment variables from a .env file.
  • google.generativeai: Google's Generative AI library for content generation.
  • youtube_transcript_api: Python library for extracting transcripts from YouTube videos.

Contributing

Contributions to the project are welcome! Feel free to open issues or pull requests on the GitHub repository.

License

This project is licensed under the MIT License. See the LICENSE file for details.

For more information and contributions, visit the GitHub repository.