The RAG-based Intelligent Conversational AI Agent combines a vector store-backed retrieval layer with Google’s Gemini LLM via LangChain to power context-rich, conversational knowledge extraction. Users ingest and index documents—PDFs, web pages, or databases—into a vector database. When a query is posed, the agent retrieves top relevant passages, feeds them into a prompt template, and generates concise, accurate answers. Modular components allow customization of data sources, vector stores, prompt engineering, and LLM backends. This open-source framework simplifies the development of domain-specific Q&A bots, knowledge explorers, and research assistants, delivering scalable, real-time insights from large document collections.

PDFChatto is a revolutionary tool that transforms PDFs into interactive knowledge sources. By simply uploading a PDF, users can instantly engage in a conversation with the document, asking questions, conducting research, or exploring the content. The AI provides clear, concise answers in real-time and can even read responses aloud. Ideal for students, researchers, educators, legal experts, and lifelong learners, PDFChatto makes it easier than ever to extract insights and information from PDF documents.