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A Streamlit-based application that summarizes content from YouTube videos and websites using LangChain and the Groq LLM API. Easily input any URL to get quick, insightful summaries with just a click!

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title emoji colorFrom colorTo sdk app_file pinned
Text Summarization Using LangChain
😁
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streamlit
app.py
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RapidRecap 📑

Overview

A Streamlit-based application that summarizes content from YouTube videos and websites using the Gemma-7b-It model from Groq. Easily input any URL to get quick, insightful summaries with just a click! 🚀

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Table of Contents

Installation

To get started, you need to create a Conda environment. Follow these steps:

  1. Create a Conda environment:
    conda create -p venv python=3.11 -y
    
  2. Activate the environment:
    conda activate langchain-summarizer
    
  3. Install the required packages: You can install the required packages using the requirements.txt file. Then, run:
    pip install -r requirements.txt
    
  4. Add a .env file: Create a .env file in the root directory of your project to store your Groq API Key. Add the following line to the file:
    GROQ_API_KEY=your_groq_api_key_here
    

Usage

  1. Ensure you have your Groq API Key stored in the .env file.
  2. Run the application:
    streamlit run app.py
    
  3. Open your web browser and navigate to http://localhost:8501 to access the application.

Acknowledgements

  • LangChain: For providing the framework to build language model applications.
  • Groq: For the powerful Gemma-7b-It model.
  • Streamlit: For making it easy to create web applications in Python.
  • YouTube and Web Sources: For the content being summarized.

License

This project is licensed under the GNU License - see the LICENSE file for details

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A Streamlit-based application that summarizes content from YouTube videos and websites using LangChain and the Groq LLM API. Easily input any URL to get quick, insightful summaries with just a click!

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