Building a Data Driven Chatbot (RAG) using Python 3 LangChain, OpenAI and MySQL 8.x

Using GenAI LangChain to Solve Real World Use Cases

Enterprise have massive amount of data locked in their databases. This Book will show one of the most popular ways to unlock them and use them in modern GenAI ChatBots.

Binit Datta

Enterprise have massive amount of data locked in their databases. This Book will show one of the most popular ways to unlock them and use them in modern GenAI ChatBots.

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About the Book

The rapid advancements in Generative AI (Gen AI) are reshaping how modern applications are designed, built, and deployed. As AI-driven systems become a cornerstone of contemporary software, it is increasingly important for developers to learn how to effectively integrate Gen AI capabilities into production-ready solutions.

This book is a hands-on guide to developing intelligent, conversational applications powered by Python 3.12. You’ll learn how to build a full-stack chatbot system using Flask, LangChain, and the OpenAI API, supported by a robust Flask REST API and a MySQL 8 database for persistent storage.

Through clear examples and practical walkthroughs, you'll create a Gen AI-powered chatbot application that includes:

· A Web-Based Chat Interface with Flask – An interactive user interface that allows users to engage with the chatbot through natural language.

· A LangChain-Powered Conversational Engine – Harnessing LangChain’s capabilities to manage conversation history, memory, and agent tools.

· Integration with the OpenAI API – Connecting your app with OpenAI’s powerful models to generate intelligent and contextual responses.

· A Flask REST API Backend – A modular RESTful architecture to handle order-related operations including creation, updates, cancellations, and status tracking.

· A MySQL 8 Database – A reliable relational database backend for storing user data, order information, and conversation logs.

Whether you're a seasoned developer or just beginning your AI journey, this book equips you with the skills to build scalable, AI-driven chatbot applications from the ground up using modern Python tools and frameworks.

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Binit Datta

Binit Datta is a strategic, customer-centric technology leader with over three decades of experience designing, building, and operating large-scale enterprise systems across more than ten business verticals and numerous Fortune 50 organizations. His career has been defined by a rare ability to bridge deep technical execution with business outcomes—using architecture not as an academic exercise, but as a practical tool to deliver reliability, scalability, and measurable customer value.

With expertise spanning enterprise architecture, identity and access management, cloud platforms, security, and modern application development, Binit has consistently worked at the intersection of systems that must perform under real-world pressure. He is particularly known for his focus on prevention over cure—helping organizations avoid costly production failures through deep system understanding, fast root-cause analysis, and disciplined architectural thinking.

A passionate mentor and lifelong learner, Binit believes the most valuable technologists are those who can see beyond silos—understanding applications, platforms, and identity infrastructure as a single, interconnected system. In an era increasingly shaped by generative AI, his work advocates for the enduring importance of human judgment, architectural fluency, and customer-focused problem solving.

This book reflects that philosophy: written for practitioners who want to understand not just how systems work, but why they behave the way they do—and how that understanding translates into lower MTTR, stronger customer trust, and sustained product innovation.

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