Summarize YouTube Videos with Gemini and Langchain

This project allows you to extract the transcript of a YouTube video and use Google's Gemini model (via the Google Generative AI library) in combination with Langchain to generate a concise summary directly in a Streamlit application.

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Screenshot

Here’s what the application looks like in action:

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Overview

• Purpose: Provide a simple and elegant web interface to:

  1. Extract a video's transcript from YouTube.
  2. Automatically summarize that transcript using Google's Gemini model.
  3. Display the video itself and the resulting summary on a single page.

• Key Technologies:

  • Streamlit: Quickly build data and AI web apps in Python.
  • Google Generative AI: Access to Google’s LLMs (Gemini in this case).
  • YouTube Transcript API: Retrieve subtitles (transcripts) from YouTube videos.
  • Langchain: A framework for orchestrating LLM usage.
  • Python-dotenv: Manages environment variables securely.

Prerequisites

1. Python 3.7+
   Make sure you have Python installed on your system.

2. Google API Key

   • You need a Google Cloud developer account and must enable the Generative AI (PaLM) API.
   • Create and obtain your GOOGLE_API_KEY to use the Gemini model.

3. Package Installation
   In the project directory, run:

   pip install -r requirements.txt

   If you don’t have a requirements.txt file yet, create one containing the packages used:

   streamlit
   google-generativeai
   youtube_transcript_api
   langchain
   langchain_google_genai
   python-dotenv
   

4. Environment Variables
   Create a .env file at the project root with the following content:

   GOOGLE_API_KEY=YOUR_KEY_HERE
   

• .env: File that stores the GOOGLE_API_KEY environment variable.
• requirements.txt: List of the necessary libraries to run the application.
• app.py: Main script containing the Streamlit code.

How to Run

1. Clone this repository (or download as a ZIP and extract):

   git clone https://github.com/your-username/your-repo.git

2. Navigate to the project folder:

   cd your-repo

3. Install dependencies:

   pip install -r requirements.txt

4. Create the .env file with your API key, for example:

   GOOGLE_API_KEY=YOUR_API_KEY_HERE
   

5. Start the application:

   streamlit run app.py

6. Open your browser at the URL provided by Streamlit (usually http://localhost:8501).

Usage

1. Paste the YouTube video link: Enter the URL in the text input field.
2. Wait for the transcript: The app automatically fetches the subtitles (transcript) from the video.
3. Summary: The Gemini model processes the transcript and displays a summary on the same page.
4. Optional: Click on "View full transcript" to see the entire video transcript.

Customization

• You can change the look and feel (colors, fonts, sizes) by editing the <style> section within app.py.
• To switch to a different LLM model, modify the model parameter when instantiating GoogleGenerativeAI.

Contributing

Contributions are welcome! Follow these steps:

1. Fork this repository.
2. Create a new branch for your feature or bug fix:

   git checkout -b my-new-feature

3. Commit your changes.
4. Open a pull request (PR) for this repository.

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_{Note: Make sure the YouTube video has subtitles (automatic or creator-provided) to successfully retrieve the transcript.}