This project is a Retrieval-Augmented Generation (RAG) AI Agent that allows users to upload PDF documents and ask natural language questions about their content. The system processes PDFs, generates vector embeddings, stores them in Qdrant Vector Database, and retrieves relevant context to generate accurate answers using an LLM.
- PDF Upload and Processing
- Intelligent Text Chunking
- Semantic Search using Vector Embeddings
- Qdrant Vector Database Integration
- LLM-Powered Context-Aware Answers
- Streamlit User Interface
- Source Attribution for Responses
- Scalable RAG Architecture