Building Generative AI Services with FastAPI

Ready to build production-grade applications with generative AI? This practical guide takes you through designing and deploying AI services using the FastAPI web framework. Learn how to integrate models that process text, images, audio, and video while seamlessly interacting with databases, filesystems, websites, and APIs. Whether you’re a web developer, data scientist, or DevOps engineer, this book equips you with the tools to build scalable, real-time AI applications.

Author Alireza Parandeh provides clear explanations and hands-on examples covering authentication, concurrency, caching, and retrieval-augmented generation (RAG) with vector databases. You’ll also explore best practices for testing AI outputs, optimizing performance, and securing microservices. With containerized deployment using Docker, you’ll be ready to launch AI-powered applications confidently in the cloud.

• Build generative AI services that interact with databases, filesystems, websites, and APIs
• Manage concurrency in AI workloads and handle long-running tasks
• Stream AI-generated outputs in real time via WebSocket and server-sent events
• Secure services with authentication, content filtering, throttling, and rate limiting
• Optimize AI performance with caching, batch processing, and fine-tuning techniques

Table of Contents

Part I. Developing Al Services

Chapter 1. Introduction

Chapter 2. Getting Started with FastAPI

Chapter 3. Al Integration and Model Serving

Chapter 4. Implementing Type-Safe Al Services

Part II. Communicating with External Systems

Chapter 5. Achieving Concurrency in Al Workloads

Chapter 6. Real-Time Communication with Generative Models

Chapter 7. Integrating Databases into Al Services

Part Ill. Securing, Optimizing, Testing, and Deploying Al Services

Chapter 8. Authentication and Authorization

Chapter 9. Securing Al Services

Chapter 10. Optimizing Al Services

Chapter 11 . Testing Al Services

Chapter 12. Deployment of Al Services

About the Author

Alireza Parandeh is a chartered engineer (CEng) with the UK engineering council, a Microsoft and Google Certified Developer, Data Engineer and Data Scientist. He has a strong background in web development, data science and machine learning having led engineering teams at large multinational consultancies and tech startups in London. Ali’s portfolio of clients include Network Rail, High-Speed Train 2, Transport for London, International Fertilizer’s Association and the Department for Transport.

As a passionate educator, Ali dedicates his free time to teaching data science and web development through meetups and online platforms. In 2019, he founded London’s Beginners Machine Learning (BML) group, a Microsoft-sponsored meetup aimed at helping professionals break into the field of Data Science & AI and obtain cloud certifications which has since grown to over 1,500 members.