RAG_CHAT is an AI-powered chatbot built with Retrieval-Augmented Generation (RAG) to deliver context-aware, knowledge-grounded responses. ⚙️ Tech Stack Highlights Backend → FastAPI + LangChain/LangGraph + Qdrant (Vector DB) Frontend → Next.js (React, Tailwind) Infra → Docker Compose with isolated backend & frontend containers Data Layer → SQLite-based checkpointing for persistent conversation memory ✨ Key Features 📚 Retrieval-Augmented answers using a vector database 🔄 Persistent memory with LangGraph checkpointing 🔐 Secure design: backend isolated in its own container, frontend as the only public interface ⚡ Real-time, interactive chat UI 🔗 This project reflects my journey in AI/ML, full-stack development, and scalable system design — bringing together everything from LLM orchestration to containerized deployment.