HANDS-ON PYTHON PROGRAMMING FOR AI-POWERED KNOWLEDGE SYSTEMS

Stop building toy chatbots. It's time to engineer professional, enterprise-grade AI systems.
Are you a Python developer watching the AI revolution from the sidelines, wondering how to bridge the enormous gap between simple demos and the robust, scalable AI applications that companies are desperate to build? Do you see the potential of Large Language Models but feel lost when it comes to grounding them in private data, evaluating their performance, and deploying them as real-world, production-ready services? This book is the bridge you've been searching for.
This is not another high-level overview of AI concepts. It is a practical, hands-on, end-to-end guide to building sophisticated AI-powered knowledge systems using the most powerful and modern toolset available today: LangChain, LlamaIndex, and FastAPI.
We cut through the hype and focus on the real-world engineering challenges. You will learn the architectural patterns and best practices required to build systems that are not just intelligent, but also reliable, efficient, and secure. We tackle the hard problems head-on: How do you build a Retrieval-Augmented Generation (RAG) pipeline that minimizes hallucinations and provides accurate, citable answers? How do you evolve that pipeline into an autonomous agent that can use tools to interact with databases and APIs? And how do you take that entire complex system, containerize it with Docker, and deploy it to the cloud with a fully automated CI/CD pipeline? This book provides the definitive answers.
By the time you finish this book, you will have transformed your skills and your career trajectory. You will not just know about AI; you will have built it.
Imagine being able to:

• Architect and Build Advanced RAG Pipelines: Go beyond basic retrieval to implement hybrid search, query transformations, and reranking models for maximum precision.
• Master Agentic Workflows: Engineer autonomous agents with custom tools and conversational memory, enabling them to perform complex, multi-step tasks.
• Evaluate and Optimize Like a Pro: Use data-driven frameworks like RAGAs to measure your system's quality and make intelligent trade-offs between speed, cost, and accuracy.
• Deploy with Confidence: Serve your AI through a high-performance FastAPI backend, containerize your entire application stack with Docker, and automate your deployments to the cloud using GitHub Actions.

This book will give you more than just knowledge; it will give you a portfolio-worthy project and the proven skills of a senior AI Engineer, ready to lead in the new era of software development.
The future of software is intelligent, and the demand for engineers who can build these systems is exploding. Don't just watch the future happen. Be the one who builds it.