📺 YouTube LLM Summarizer

🚀 AI-powered YouTube Video Summarization with Streamlit

This project extracts transcripts from YouTube videos using YouTubeTranscriptAPI or Whisper, then summarizes them using Groq's LLM. The app is built with Streamlit and runs in a Dockerized environment for easy deployment.

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🚀 Features

✅ Extracts YouTube transcripts automatically
✅ Uses Whisper for speech-to-text if transcripts are unavailable
✅ Summarizes content using Groq LLM
✅ Provides a simple Streamlit UI for easy interaction
✅ Dockerized for seamless deployment

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📂 Project Structure

📁 youtube-llm-summarizer  
│── 📄 app.py               # Streamlit UI for summarization  
│── 📄 summarizer.py        # Core logic for transcript extraction & summarization  
│── 📄 Dockerfile           # Docker configuration  
│── 📄 docker-compose.yml   # Docker Compose setup  
│── 📄 .env                 # Environment variables  
│── 📄 requirements.txt     # Python dependencies  
│── 📁 temp/                # Temporary storage for audio files

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🛠️ Installation & Setup

1️⃣ Clone the Repository

git clone https://github.com/ArchitJ6/youtube-llm-summarizer.git
cd youtube-llm-summarizer

2️⃣ Set Up Environment Variables

Create a .env file in the root directory and add your API keys:

GROQ_API_KEY=your_groq_api_key

3️⃣ Run with Docker Compose

docker-compose up --build

This will:

• Pull the necessary dependencies
• Set up the Streamlit app in a container
• Run the app on http://localhost:8501

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🎬 How to Use

1. Open http://localhost:8501
2. Enter a YouTube video URL
3. Click "Summarize"
4. View the generated summary

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📦 Running Without Docker

If you prefer to run locally:

pip install -r requirements.txt
streamlit run app.py

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🛠️ Built With

• Python 🐍
• Streamlit 📊
• YouTubeTranscriptAPI 🎥
• Whisper 🎙️
• Groq LLM 🧠
• Docker & Docker Compose 🐳

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📝 License

This project is licensed under the MIT License.