📝 Multi-Feature AI Summarizer

An all-in-one AI-powered summarization platform built with Streamlit, Hugging Face Transformers, and Google Gemini, capable of summarizing text, PDFs, speech, YouTube videos, and news articles from a single web interface.

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🚀 Features

📄 Text Summarization

• Summarize long text into concise, readable summaries.
• Adjustable minimum and maximum summary length.
• Automatically chunks large documents before summarization.
• Powered by facebook/bart-large-cnn.

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🎤 Speech Summarization

• Records live speech using the microphone.
• Converts speech to text using Google Speech Recognition.
• Generates AI-powered summaries using Google Gemini.
• Automatically stops recording after prolonged inactivity.

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📚 PDF Summarizer & Question Answering

• Upload PDF documents.
• Extracts text automatically.
• Generates document summaries.
• Ask natural language questions about the uploaded PDF.
• Uses extractive Question Answering with RoBERTa.

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▶️ YouTube Video Summarizer

• Paste any YouTube video URL.
• Fetches the video's transcript automatically.
• Generates detailed notes and summaries using Google Gemini.
• Displays the video thumbnail for preview.

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📰 News Article Summarizer

• Upload a CSV containing news articles.
• Automatically summarizes every article.
• Displays results article-by-article.
• Supports batch summarization.

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🛠️ Tech Stack

Frontend

• Streamlit

AI Models

• Facebook BART Large CNN
• Deepset RoBERTa SQuAD2
• Google Gemini Pro

Libraries

• Transformers
• PyPDF2
• Pandas
• SpeechRecognition
• YouTube Transcript API
• python-dotenv

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📂 Project Structure

.
├── allinone.py
├── .env
├── requirements.txt
└── README.md

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⚙️ Installation

Clone the repository

git clone https://github.com/yourusername/multi-feature-ai-summarizer.git

cd multi-feature-ai-summarizer

Create a virtual environment

python -m venv venv

Activate it:

Windows

venv\Scripts\activate

macOS/Linux

source venv/bin/activate

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Install dependencies

pip install -r requirements.txt

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Configure Environment Variables

Create a .env file.

GOOGLE_API_KEY=YOUR_GEMINI_API_KEY

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Run the application

streamlit run allinone.py

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📸 Application Modules

• 📄 Text Summarization
• 🎤 Speech Summarization
• 📚 PDF Summarizer & Q&A
• ▶️ YouTube Video Summarizer
• 📰 News Article Summarizer

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🧠 AI Models Used

Task	Model
Text Summarization	facebook/bart-large-cnn
PDF Question Answering	deepset/roberta-base-squad2
Speech Summary	Google Gemini Pro
YouTube Summary	Google Gemini Pro

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✨ Highlights

• Unified AI summarization platform
• Supports multiple input formats
• Automatic text chunking for long documents
• Interactive Streamlit interface
• Extractive Question Answering over PDFs
• Live speech transcription
• Batch article summarization
• Modular architecture for easy feature expansion

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🔮 Future Improvements

• Multi-language summarization
• OCR support for scanned PDFs
• Upload DOCX and PPT files
• Audio file summarization
• Translation before summarization
• Summary export as PDF or DOCX
• Chat with uploaded documents
• User authentication and history

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🤝 Contributing

Contributions are welcome!

1. Fork the repository
2. Create a new feature branch

git checkout -b feature-name

3. Commit your changes

git commit -m "Add feature"

4. Push the branch

git push origin feature-name

5. Open a Pull Request

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📜 License

This project is licensed under the MIT License.

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👨‍💻 Author

Subhakar Tadimalla

Computer Science Engineering Student

AI • Machine Learning • Full Stack Development • Open Source