Production-Ready RAG Chatbot Demo using Groq | LangChain | Docker | HuggingFace | FastAPI | Ragas

Description

In this video, I demonstrate a production-style RAG (Retrieval-Augmented Generation) PDF chatbot built using Groq, LangChain, FastAPI, Streamlit, Docker, and Chromadb. The application allows users to upload PDF documents and chat with them intelligently using semantic search and LLM-powered responses. 🚀 Features: - PDF Upload & Ingestion - AI Chat with Documents - Semantic Search using Chromadb - Groq LLM Integration - FastAPI Backend - Streamlit Frontend - Dockerized Deployment - RAGAS Evaluation 🛠 Tech Stack: - Python - LangChain - Groq - FastAPI - Streamlit - Docker - Chromadb - HuggingFace Embeddings - RAGAS 📊 RAGAS Scores: - Faithfulness: 1.0000 - Context Precision: 1.0000 - Context Recall: 1.0000 - Answer Relevancy: 0.9149 This project focuses on building a scalable and enterprise-style AI knowledge assistant rather than a simple demo chatbot. #AI #RAG #LangChain #Groq #FastAPI #Streamlit #Docker #LLM #Python #ArtificialIntelligence