Build an AI Chatbot that Understands Documents | Gemini API + LangChain + FastAPI + Python Tutorial

Description

🚀 Project Overview: In this video, I’ll show you how to build a document-understanding AI chatbot from scratch using Gemini API, LangChain, FastAPI, and Python. This chatbot isn’t just chatting — it can read, process, and answer questions from your documents (PDFs, text files, etc.) with real understanding. 💡 What You’ll Learn: How to integrate Gemini API (Google’s powerful GenAI model) How to use LangChain for document loading, text splitting, and retrieval How to set up FastAPI as the backend to serve AI responses How to handle document ingestion and chat-based Q&A How to deploy your chatbot for real use ⚙️ Tech Stack: Python 🐍 | LangChain | Gemini API | FastAPI | HTML/JS Frontend (optional) 🔥 Features: ✅ Upload and process your own documents ✅ Ask contextual questions about the content ✅ Stream responses from Gemini in real time ✅ Fully API-driven architecture for future scaling 📁 Project Files: (You can add your GitHub link here once uploaded) 👉 GitHub Repository: https://github.com/AK-AITech/Chatbot.git 00:00 - Intro & Demo 00:27 - Overview 03:43 - Phase 1: Environment Setup & .env Configuration 05:34 - Theory on LangChain 08:30 - App Script (Backend Logic) 25:29 - Start Script & Testing 28:55 - index.html Frontend Integration 34:08 - Chrome DB Explanation 34:50 - FastAPI Docs Validation & Final Output