Doc Chat Studio: Building a Production-Grade RAG AI with LangChain, FAISS & Streamlit
In recent years, Retrieval-Augmented Generation (RAG) has emerged as one of the most powerful architectural patterns for enterprise AI applications. Instead of relying solely on a large language model’s memory, RAG grounds responses in your own documents , ensuring accuracy, transparency, and trust. In this blog, we’ll deep-dive into Doc Chat Studio , an AI-powered document chat application built using Python, LangChain, FAISS, HuggingFace embeddings, and Streamlit . This project demonstrates how to design a multi-step, agentic RAG pipeline that supports real-world document formats like PDFs, DOCX, Markdown, and text files. 🚀 What Is Doc Chat Studio? Doc Chat Studio is an interactive AI application that allows users to: Upload multiple documents (PDF, Word, Markdown, TXT) Index them using semantic embeddings Ask natural language questions Receive context-aware, source-cited answers Maintain conversation memory across multiple questions Unlike basic chatbots, ...