A simple yet powerful Streamlit web app that summarizes YouTube videos and web pages using LangChain and Groq LLMs. Built for speed, simplicity, and flexibility.
- 📺 Summarize YouTube video transcripts automatically.
- 🌐 Summarize public web pages (e.g., Wikipedia, blogs, articles).
- 🧠 Choose between:
- Basic Summarization (Stuff) – quick, single-pass summary.
- Advanced Summarization (Map-Reduce) – better for longer content.
- 🤖 Select Groq LLMs like
gemma2-9b-it,llama-3.1-8b-instant, etc. - 🔥 Control creativity with a temperature slider.
- 📊 Shows summary length and document statistics.
- 🎈 Intuitive and interactive UI with Streamlit.
The app takes a URL and produces a clean, concise summary using LLMs.
- LangChain – for prompt templating, chaining, and document loading.
- Groq API – LLM inference via high-speed transformer models.
- Streamlit – UI framework for rapid prototyping.
- FAISS (included but not yet active) – scalable vector search (for future extensions).
- Python 3.9+
- Python 3.9 or higher
- A valid Groq API key
-
Clone the repository:
git clone https://github.com/your-username/groqchain-summarizer.git cd groqchain-summarizer -
Create a virtual environment (recommended):
python -m venv venv source venv/bin/activate # On Windows: venv\Scripts\activate
-
Install the dependencies:
pip install -r requirements.txt
-
Run the app:
streamlit run app.py
- Enter your Groq API key in the sidebar.
- Choose summarization method (Basic or Advanced).
- Select a model and temperature.
- Paste a YouTube video URL or web page URL.
- Click Summarize.
- 🎉 Get your concise summary!
├── app.py # Main Streamlit app
├── requirements.txt # Python dependencies
├── README.md # Project documentation
└── assets/
└── screenshot.png # App screenshot
- Add FAISS-based document memory.
- Upload PDF/docx content.
- Save and export summaries.
- Integrate other LLM providers.