An AI-powered document learning assistant built using Streamlit, LangChain, FAISS, and Ollama that enables users to upload PDFs and interact with documents through contextual chat, semantic retrieval, automated summaries, MCQ generation, and flashcards.
- 📄 Chat with PDF using RAG
- 🔍 Semantic document retrieval
- 🧠 AI-generated summaries
- ❓ MCQ generation
- 📌 Flashcard generation
- 📚 Context-aware question answering
- 🗂 Vector embeddings with FAISS
- 🖥 Local LLM inference using Ollama
- ⚡ Interactive Streamlit interface
- Python
- Streamlit
- LangChain
- FAISS
- Ollama
- Llama 3
- PyPDF2
PDF Upload → Text Extraction → Chunking → Embeddings → FAISS Vector Store → Retriever → LLM → Response Generation
git clone <your-repo-link>
cd <repo-name>pip install -r requirements.txtDownload Ollama:
Pull Required Models:
ollama pull llama3
ollama pull nomic-embed-textstreamlit run app.py- PDF export
- Multi-document RAG
- Citation-aware responses
- Study modes
- Voice interaction
- Authentication system
Nitesh Verma