A lightweight AI-powered tool to generate chapter-wise summaries from book PDFs using semantic retrieval and abstractive summarization. Developed as part of a remote research internship at IIT Kanpur.
- 🔍 Semantic Search with FAISS: Retrieves the most relevant content chunks using sentence-level embeddings.
- 🤖 Abstractive Summarization: Utilizes
facebook/bart-large-cnnfor high-quality, context-aware summaries. - 📄 PDF Parsing: Automatically extracts and processes text from user-uploaded book PDFs.
- 🧠 Custom Retrieval-Augmented Generation (RAG): Combines vector search and transformer-based summarization.
- Python 3.10+
- Hugging Face Transformers
- SentenceTransformers
- FAISS
- PyPDF2 for PDF text extraction
- Google Colab (recommended for execution)