🚀 Talk-Brief AI: Interact with YouTube or Website

Welcome to the Talk-Brief AI repository! This project leverages LangChain and Google's gemini-1.5-flash LLM to provide users with concise overviews of content from YouTube videos or websites. The application is built using Streamlit, making it easy to deploy as a web app for summarizing lengthy or complex online content.

🔗 Project Deployment

The project is currently hosted with the help of Streamlit. You can access the live version of the application through this link.

📚 Table of Contents

• 🚀 Talk-Brief AI: Interact with YouTube or Website
• 🔗 Project Deployment
• ✨ Features
• 🛠️ Installation
• 📄 Usage
• 🔄 Summarization Methods
• 🖼️ Example
• 📜 License
• 📄 References

✨ Features

• Google API Integration: Securely integrates with Google's Generative AI models using your API key.
• YouTube and Website Support: Handles both YouTube video URLs and regular website URLs for content summarization.
• Automatic Best Summarization Technique Recommendation: Automatically calculates the number of tokens in the text to recommend the most appropriate summarization method.
• Multiple Summarization Techniques:
  • Stuff Chain: Ideal for short texts, providing a straightforward summary.
  • Map-Reduce: Best for medium-length texts, breaking down the content into chunks before combining the results.
  • Refine: Suitable for long texts, refining the summary iteratively to ensure accuracy and coherence.
• User-Friendly Interface: Simple, interactive UI built with Streamlit.

🛠️ Installation

1. Clone this repository to your local machine.

   git clone https://github.com/neuromindlabs/TalkBriefAI.git

2. Navigate to the project directory.

   cd talk-brief-ai

3. Install the required dependencies.

   pip install -r requirements.txt

📄 Usage

1. Run the Application:

   streamlit run app.py

2. Provide Your Google API Key:
   • Enter your Google API Key in the sidebar. If you don’t have one, follow the provided link to obtain it.
3. Enter a URL:
   • Input a YouTube video URL or any website URL in the main input field.
4. Select Summarization Type:
   • Based on the calculated token count, a suggested summarization type will be displayed. You can select it or choose another method.
5. Generate Summary:
   • Click on the "Get an overview of the Content from YT or Website" button to generate the summary.

🔄 Summarization Methods

• Stuff Chain: Best suited for short documents or small text content. It runs a simple summarization on the provided text.
• Map-Reduce: Breaks down large texts into smaller chunks, summarizes them individually, and then combines them into a cohesive summary.
• Refine: Iteratively refines the summary, ensuring that key details are not lost, even in lengthy documents.

🖼️ Example - 3/3.ADD GIF

📜 License

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

📄 References

• LangChain: For providing the tools to create advanced summarization chains.
• Streamlit: For making it easy to build and deploy interactive web apps.
• Google Generative AI: For powering the language models used in the summarization process.