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---
title: Text Summarization Using LangChain
emoji: 😁
colorFrom: blue
colorTo: red
sdk: streamlit
app_file: app.py
pinned: false
---
# 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](#installation)
- [Usage](#usage)
- [Requirements](#requirements)
- [Acknowledgements](#acknowledgements)
- [License](#license)
## 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](LICENSE) file for details
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