Learn Fastapi

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Learn Fastapi

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Author : Diego Rodrigues
language : en
Publisher: StudioD21
Release Date : 2025-03-20

Learn Fastapi written by Diego Rodrigues and has been published by StudioD21 this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-20 with Business & Economics categories.

FastAPI is one of the most efficient frameworks for building modern APIs with Python, widely used by companies like Microsoft, Uber, and Netflix due to its high performance and native support for static typing and asynchronous operations. This book provides a comprehensive guide, from installation and initial setup to the implementation of scalable and secure APIs for real-world applications. The content covers project structuring with APIRouter, advanced request handling, authentication with JWT and OAuth2, integration with PostgreSQL, MySQL, and MongoDB, and performance optimization with Redis and Memcached. It also includes essential techniques for efficient deployment on cloud services like AWS Lambda, Google Cloud Run, and Azure Functions, test automation with Pytest, and monitoring with Prometheus and Grafana. Each chapter follows the TECHWRITE 2.1 methodology, combining structured theory and practice, with explanatory code, best practices, and solutions for common errors. Whether developing REST APIs, microservices, or real-time applications with WebSockets, this book provides the necessary tools to apply FastAPI in robust and scalable projects. Ideal for developers looking to build modern APIs and optimize workflows, LEARN FastAPI: From Fundamentals to Practical Applications is a technical and objective guide for professional use of the framework. TAGS: Python Java Linux Kali HTML ASP.NET Ada Assembly BASIC Borland Delphi C C# C++ CSS Cobol Compilers DHTML Fortran General JavaScript LISP PHP Pascal Perl Prolog RPG Ruby SQL Swift UML Elixir Haskell VBScript Visual Basic XHTML XML XSL Django Flask Ruby on Rails Angular React Vue.js Node.js Laravel Spring Hibernate .NET Core Express.js TensorFlow PyTorch Jupyter Notebook Keras Bootstrap Foundation jQuery SASS LESS Scala Groovy MATLAB R Objective-C Rust Go Kotlin TypeScript Dart SwiftUI Xamarin React Native NumPy Pandas SciPy Matplotlib Seaborn D3.js OpenCV NLTK PySpark BeautifulSoup Scikit-learn XGBoost CatBoost LightGBM FastAPI Redis RabbitMQ Kubernetes Docker Jenkins Terraform Ansible Vagrant GitHub GitLab CircleCI Regression Logistic Regression Decision Trees Random Forests chatgpt grok AI ML K-Means Clustering Support Vector Machines Gradient Boosting Neural Networks LSTMs CNNs GANs ANDROID IOS MACOS WINDOWS Nmap Metasploit Framework Wireshark Aircrack-ng John the Ripper Burp Suite SQLmap Maltego Autopsy Volatility IDA Pro OllyDbg YARA Snort ClamAV Netcat Tcpdump Foremost Cuckoo Sandbox Fierce HTTrack Kismet Hydra Nikto OpenVAS Nessus ZAP Radare2 Binwalk GDB OWASP Amass Dnsenum Dirbuster Wpscan Responder Setoolkit Searchsploit Recon-ng BeEF AWS Google Cloud IBM Azure Databricks Nvidia Meta Power BI IoT CI/CD Hadoop Spark Dask SQLAlchemy Web Scraping MySQL Big Data Science OpenAI ChatGPT Handler RunOnUiThread() Qiskit Q# Cassandra Bigtable VIRUS MALWARE Information Pen Test Cybersecurity Linux Distributions Ethical Hacking Vulnerability Analysis System Exploration Wireless Attacks Web Application Security Malware Analysis Social Engineering Social Engineering Toolkit SET Computer Science IT Professionals Careers Expertise Library Training Operating Systems Security Testing Penetration Test Cycle Mobile Techniques Industry Global Trends Tools Framework Network Security Courses Tutorials Challenges Landscape Cloud Threats Compliance Research Technology Flutter Ionic Web Views Capacitor APIs REST GraphQL Firebase Redux Provider Bitrise Actions Material Design Cupertino Fastlane Appium Selenium Jest Visual Studio AR VR sql deepseek mysql startup digital marketing

Building Data Science Applications With Fastapi

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Author : Francois Voron
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-10-08

Building Data Science Applications With Fastapi written by Francois Voron and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-08 with Computers categories.

Get well-versed with FastAPI features and best practices for testing, monitoring, and deployment to run high-quality and robust data science applications Key FeaturesCover the concepts of the FastAPI framework, including aspects relating to asynchronous programming, type hinting, and dependency injectionDevelop efficient RESTful APIs for data science with modern PythonBuild, test, and deploy high performing data science and machine learning systems with FastAPIBook Description FastAPI is a web framework for building APIs with Python 3.6 and its later versions based on standard Python-type hints. With this book, you'll be able to create fast and reliable data science API backends using practical examples. This book starts with the basics of the FastAPI framework and associated modern Python programming language concepts. You'll be taken through all the aspects of the framework, including its powerful dependency injection system and how you can use it to communicate with databases, implement authentication and integrate machine learning models. Later, you'll cover best practices relating to testing and deployment to run a high-quality and robust application. You'll also be introduced to the extensive ecosystem of Python data science packages. As you progress, you'll learn how to build data science applications in Python using FastAPI. The book also demonstrates how to develop fast and efficient machine learning prediction backends and test them to achieve the best performance. Finally, you'll see how to implement a real-time face detection system using WebSockets and a web browser as a client. By the end of this FastAPI book, you'll have not only learned how to implement Python in data science projects but also how to maintain and design them to meet high programming standards with the help of FastAPI. What you will learnExplore the basics of modern Python and async I/O programmingGet to grips with basic and advanced concepts of the FastAPI frameworkImplement a FastAPI dependency to efficiently run a machine learning modelIntegrate a simple face detection algorithm in a FastAPI backendIntegrate common Python data science libraries in a web backendDeploy a performant and reliable web backend for a data science applicationWho this book is for This Python data science book is for data scientists and software developers interested in gaining knowledge of FastAPI and its ecosystem to build data science applications. Basic knowledge of data science and machine learning concepts and how to apply them in Python is recommended.

Building Python Web Apis With Fastapi

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Author : Abdulazeez Abdulazeez Adeshina
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-07-29

Building Python Web Apis With Fastapi written by Abdulazeez Abdulazeez Adeshina and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-07-29 with Computers categories.

Discover FastAPI features and best practices for building and deploying high-quality web APIs from scratch Key Features • A practical guide to developing production-ready web APIs rapidly in Python • Learn how to put FastAPI into practice by implementing it in real-world scenarios • Explore FastAPI, its syntax, and configurations for deploying applications Book Description RESTful web services are commonly used to create APIs for web-based applications owing to their light weight and high scalability. This book will show you how FastAPI, a high-performance web framework for building RESTful APIs in Python, allows you to build robust web APIs that are simple and intuitive and makes it easy to build quickly with very little boilerplate code. This book will help you set up a FastAPI application in no time and show you how to use FastAPI to build a REST API that receives and responds to user requests. You'll go on to learn how to handle routing and authentication while working with databases in a FastAPI application. The book walks you through the four key areas: building and using routes for create, read, update, and delete (CRUD) operations; connecting the application to SQL and NoSQL databases; securing the application built; and deploying your application locally or to a cloud environment. By the end of this book, you'll have developed a solid understanding of the FastAPI framework and be able to build and deploy robust REST APIs. What you will learn • Set up a FastAPI application that is fully functional and secure • Understand how to handle errors from requests and send proper responses in FastAPI • Integrate and connect your application to a SQL and NoSQL (MongoDB) database • Perform CRUD operations using SQL and FastAPI • Manage concurrency in FastAPI applications • Implement authentication in a FastAPI application • Deploy a FastAPI application to any platform Who this book is for This book is for Python developers who want to learn FastAPI in a pragmatic way to create robust web APIs with ease. If you are a Django or Flask developer looking to try something new that's faster, more efficient, and produces fewer bugs, this FastAPI Python book is for you. The book assumes intermediate-level knowledge of Python programming.

Building Data Science Applications With Fastapi Second Edition

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Author : François Voron
language : en
Publisher:
Release Date : 2023-07-31

Building Data Science Applications With Fastapi Second Edition written by François Voron and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-31 with categories.

Learn all the features and best practices of FastAPI to build, deploy, and monitor powerful data science and AI apps, like object detection or image generation.Purchase of the print or Kindle book includes a free PDF eBookKey FeaturesUncover the secrets of FastAPI, including async I/O, type hinting, and dependency injectionLearn to add authentication, authorization, and interaction with databases in a FastAPI backendDevelop real-world projects using pre-trained AI modelsBook DescriptionBuilding Data Science Applications with FastAPI is the go-to resource for creating efficient and dependable data science API backends. This second edition incorporates the latest Python and FastAPI advancements, along with two new AI projects - a real-time object detection system and a text-to-image generation platform using Stable Diffusion. The book starts with the basics of FastAPI and modern Python programming. You'll grasp FastAPI's robust dependency injection system, which facilitates seamless database communication, authentication implementation, and ML model integration. As you progress, you'll learn testing and deployment best practices, guaranteeing high-quality, resilient applications. Throughout the book, you'll build data science applications using FastAPI with the help of projects covering common AI use cases, such as object detection and text-to-image generation. These hands-on experiences will deepen your understanding of using FastAPI in real-world scenarios. By the end of this book, you'll be well equipped to maintain, design, and monitor applications to meet the highest programming standards using FastAPI, empowering you to create fast and reliable data science API backends with ease while keeping up with the latest advancements.What you will learnExplore the basics of modern Python and async I/O programmingGet to grips with basic and advanced concepts of the FastAPI frameworkDeploy a performant and reliable web backend for a data science applicationIntegrate common Python data science libraries into a web backendIntegrate an object detection algorithm into a FastAPI backendBuild a distributed text-to-image AI system with Stable DiffusionAdd metrics and logging and learn how to monitor themWho this book is forThis book is for data scientists and software developers interested in gaining knowledge of FastAPI and its ecosystem to build data science applications. Basic knowledge of data science and machine learning concepts and how to apply them in Python is recommended.

Getting Started With Fastapi

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Author : Andrés Cruz Yoris
language : en
Publisher: Andres Cruz
Release Date :

Getting Started With Fastapi written by Andrés Cruz Yoris and has been published by Andres Cruz this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.

FastAPI is a great web framework for creating web APIs with Python; It offers us multiple features with which it is possible to create modular, well-structured, scalable APIs with many options such as validations, formats, typing, among others. When you install FastAPI, two very important modules are installed: Pydantic that allows the creation of models for data validation. Starlette, which is a lightweight ASGI tooltip, used to create asynchronous (or synchronous) web services in Python. With these packages, we have the basics to create APIs, but we can easily extend a FastAPI project with other modules to provide the application with more features, such as the database, template engines, among others. FastAPI is a high-performance, easy-to-learn, start-up framework; It is ideal for creating all kinds of sites that not only consist of APIs, but we can install a template manager to return complete web pages. This book is mostly practical, we will learn the basics of FastAPI, knowing its main features based on a small application that we will extend chapter after chapter and whose content you can see below: Chapter 1: We present some essential commands to develop in FastApi , we will prepare the environment and we will give an introduction to the framework . Chapter 2: One of the main factors in FastApi is the creation of resources for the API through functions, in this section we will deal with the basics of this, introducing routing between multiple files as well as the different options for the arguments and parameters of these routes. Chapter 3: In this section, learn how to handle HTTP status codes from API methods and also handle errors/exceptions from API methods. Chapter 4: In this section we will see how to create sample data to use from the automatic documentation that FastAPI offers for each of the API methods. Chapter 5: In this chapter we will see how to implement the upload of files, knowing the different existing variants in FastAPI. Chapter 6: In this chapter we will see how to connect a FastAPI application to a relational database such as MySQL. Chapter 7: In this chapter we will see installing and using a template engine in Python, specifically Jinja, with which we can return responses in HTML format. Chapter 8: In this chapter we will see installing and using a template engine in Python, specifically Jinja, with which we can return responses in HTML format. Chapter 9: In this chapter we will learn how to use dependencies. Chapter 10: In this chapter we will see how to use middleware to intercept requests to API methods and execute some procedure before the request or after generating the response. Chapter 11: In this chapter we will see how to create a user module, to register users, login, generate access tokens and logout. Chapter 12: In this chapter we will learn about some particularities and functionalities of FastAPI such as the use of annotations and the Ellipsis operator. Chapter 13: In this chapter we will see how to implement unit tests. Chapter 14: In this chapter we will know some general aspects applied to FastAPI.

Fastapi

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Author : Bill Lubanovic
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2023-11-06

Fastapi written by Bill Lubanovic and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-06 with Computers categories.

FastAPI is a young yet solid framework that takes advantage of newer Python features in a clean design. As its name implies, FastAPI is indeed fast, rivaling similar frameworks in languages such as Golang. With this practical book, developers familiar with Python will learn how FastAPI lets you accomplish more in less time with less code. Author Bill Lubanovic covers the nuts and bolts of FastAPI development with how-to guides on various topics such as forms, database access, graphics, maps, and more that will take you beyond the basics. This book also includes how-to guides that will get you up to speed on RESTful APIs, data validation, authorization, and performance. With its similarities to frameworks like Flask and Django, you'll find it easy to get started with FastAPI. Through the course of this book, you will: Learn how to build web applications with FastAPI Understand the differences between FastAPI, Starlette, and pydantic Learn two features that set FastAPI apart: asynchronous functions and data type checking and validation Examine new features of Python 3.8+, especially type annotations Understand the differences between sync and async Python Learn how to connect with external APIs and services

Machine Learning Deployment Made Simple

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Author : Bryan C Diego
language : en
Publisher: Independently Published
Release Date : 2025-12

Machine Learning Deployment Made Simple written by Bryan C Diego and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-12 with Computers categories.

Machine Learning Deployment Made Simple: FastAPI, ONNX, and Python for Modern AI Systems Are you curious about artificial intelligence but feel overwhelmed by jargon, code, and complicated tools? Do you want to see your own machine learning models come to life-deployed and working in real-world applications-even if you've never written a line of Python before? This book is your friendly invitation into the world of modern AI deployment, designed especially for complete beginners and those who think "I'm not technical enough." Take the Fear Out of AI and Coding You don't need a PhD or a programming background to master machine learning deployment. With warmth, encouragement, and clear explanations, this book guides you step by step, from your very first install to running your own machine learning models online. You'll learn with real examples and build practical skills at your own pace. Every chapter is crafted to empower, reassure, and nurture your progress, no matter how much (or how little) experience you start with. What Makes This Book Different? Beginner-Friendly and Non-Intimidating Every concept-whether it's FastAPI, ONNX, or Python basics-is broken down into small, digestible steps, with plain English explanations and hands-on examples that anyone can follow. Mistakes Are Welcome The book normalizes the learning curve. You'll see how errors, bugs, and detours are not failures-they're stepping stones. Each chapter celebrates your small wins and encourages you to keep going, making learning to code and deploy AI a joyful, pressure-free experience. Real-World, Practical Skills Move beyond theory. You'll create and deploy actual machine learning models, connect them to web APIs, and see how they can solve real problems-from image recognition to simple data predictions. By the end, you'll have projects you can share and be proud of. Step-by-Step Confidence Building You'll set up your development environment, understand essential Python and machine learning foundations, and use FastAPI and ONNX to turn your models into deployable applications. Each chapter builds your skills naturally, giving you a sense of accomplishment at every stage. Supportive and Encouraging Tone Written as a supportive companion, the book reassures you: "You can do this!" Practical checkpoints, troubleshooting tips, and gentle explanations are there whenever you feel stuck. Key Takeaways and Benefits: Set up Python and all necessary tools, even if you're a total beginner. Train, convert, and deploy machine learning models using industry-standard frameworks (FastAPI, ONNX, Python). Learn best practices for API development, security, and performance-demystified for beginners. Gain confidence with coding and problem-solving by seeing mistakes as part of the learning journey. Discover how AI can solve real-world problems and how you can be part of this exciting field, no matter your background. Your Invitation to a New Skillset If you've ever doubted your ability to enter the tech world, this book is written for you. With "Machine Learning Deployment Made Simple," you'll unlock the tools, guidance, and motivation you need to start coding, deploying, and creating with AI-no experience required. Don't let uncertainty hold you back. Pick up this book and let's take the first step together toward a future where you turn ideas into reality, one line of code at a time. Start your empowering AI journey today-your future as a confident creator begins here.

Building High Performance Web Apis With Fastapi

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Author : Girish Vas
language : en
Publisher: Orange Education Pvt Ltd
Release Date : 2025-09-26

Building High Performance Web Apis With Fastapi written by Girish Vas and has been published by Orange Education Pvt Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-09-26 with Computers categories.

TAGLINE Master FastAPI to Build Secure, High-performance Web APIs with Modern Python— from Fundamentals to Full-scale Applications. KEY FEATURES ● Comprehensive coverage of FastAPI from fundamentals to deployment. ● Build production-ready APIs by integrating authentication, databases, and async programming. ● Practical guidance on testing, scaling, and securing APIs for production. DESCRIPTION APIs are the backbone of today’s interconnected digital world, powering everything from mobile apps to enterprise systems. Building them to be fast, scalable, and secure is critical for modern software success. Building High-Performance Web APIs with FastAPI shows you how to achieve exactly that—using Python’s cutting-edge FastAPI framework. Starting with RESTful API fundamentals and FastAPI’s core principles, you will set up your development environment, install the framework, and explore its key features. You will progress through designing and validating data models with Pydantic, implementing authentication and authorization, handling file uploads, and integrating relational databases like SQLite, PostgreSQL, and MySQL. From there, you will master testing and debugging techniques, learn deployment strategies with Docker and Kubernetes, and scale your APIs with best practices for performance and security. Real-world projects and step-by-step examples make each concept easy to grasp and apply. Thus, by the end, you will have the skills and confidence to design, build, and deploy production-ready APIs that meet today’s performance and reliability standards. Hence, whether you are a developer, architect, or engineer, Building High-Performance Web APIs with FastAPI is your roadmap to mastering high-performance API development—start building the APIs your users deserve. WHAT WILL YOU LEARN ● Understand FastAPI’s architecture and RESTful API principles. ● Set up a complete development environment, and install FastAPI. ● Design and validate request/response models with Pydantic. ● Implement authentication, authorization, and file handling. ● Connect to databases (SQLite, PostgreSQL, and MySQL) with SQLAlchemy. ● Deploy and scale FastAPI applications, using Docker and Kubernetes. WHO IS THIS BOOK FOR? This book is tailored for Python developers, backend engineers, full-stack developers, and API architects with basic programming and HTTP knowledge who want to master modern API development. Familiarity with Python syntax and core web concepts will help readers quickly apply FastAPI to real-world, production-grade projects. TABLE OF CONTENTS 1. Introduction to FastAPI and RESTful APIs 2. Setting Up the Development Environment 3. Installing FastAPI 4. Core Features of FastAPI 5. Dependency Injection 6. Request and Response Models with Pydantic 7. Authentication and Authorization 8. File Uploading 9. Connecting to Databases 10. Testing and Debugging 11. Deployment and Scalability 12. Managing Application Configuration 13. Building Practical Projects 14. Future of FastAPI 15. Appendices Index

Fast Api

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Author : Corey B Audrey
language : en
Publisher: Independently Published
Release Date : 2023-01-21

Fast Api written by Corey B Audrey and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-21 with categories.

Are you ready to build fast and powerful web APIs? Look no further than Fast API: A Beginner's Guide to Building Fast and Powerful Web APIs. It covers everything you need to know about building web APIs with FastAPI, including its features, setup, and usage, as well as advanced topics such as handling errors, authentication and authorization, and deployment. It also covers building web applications with Pyramid and Dash, and shows you how to integrate them with FastAPI for additional functionality. And with detailed explanations of best practices and tips for building web applications and APIs with FastAPI, you'll be able to create high-performance, maintainable, and robust web applications in no time. This guidebook is not only an easy-to-read but also easy-to-implement instruction manual. It is filled with hands-on examples, and the integration of Pyramid and Dash frameworks makes the learning process even more enjoyable. But that's not all - it also provides you with resources for learning and developing with FastAPI, including tutorials, libraries, and community resources, so you can continue to improve your skills and stay up-to-date on the latest updates and features. The author, Corey B. Audrey is highly skilled in Java, ASP .NET MVC, and Python, and has some experience with frontend frameworks. He has a wealth of experience consulting on IT Systems, Cloud, DevOps, and Enterprise applications, and has already designed solutions for over 250 clients, many of which are Fortune 500 companies. Audrey also has experience in building laboratory information management systems (LIMS) and hybrid mobile applications as a consultant and has a unique expertise in building world-class APIs. Who is this book for: This book is for those who wish to learn about APIs, Fast API, who wish to build fast and powerful web APIs. It is perfect for developers of all levels, whether you're just starting out or looking to take your API development skills to the next level. What you'll learn in the book: To create your first API endpoint with FastAPI. Integrating both Pyramid and Dash with FastAPI to provide additional functionality and improve the performance of your web applications. TABLE OF CONTENTS Chapter 1: Introduction. 3 Chapter 2: Getting Started With Fast Api 9 Chapter 3: Advanced Features Of Fast Api 21 Chapter 4: Building Web Applications With Pyramid And Dash 29 Chapter 5: Best Practices And Tips. 37 Chapter 6: Conclusion. 43 So don't wait any longer to take your API development to the next level. Order your copy now and start building fast, powerful web APIs today!

Fastapi For Generative Ai

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Author : Drake Duncan
language : en
Publisher: Independently Published
Release Date : 2025-06-08

Fastapi For Generative Ai written by Drake Duncan and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-08 with Computers categories.

FastAPI for Generative AI: Build and Deploy Scalable AI Applications with Python Unlock the power of FastAPI, Python, and Generative AI to build real-world, scalable applications that deliver blazing-fast performance and intelligent results. Whether you're integrating LLMs, diffusion models, or deploying AI APIs to production, this comprehensive guide walks you through every step with clear code, best practices, and hands-on projects. This is the definitive guide for developers, machine learning engineers, and backend architects building AI-powered web services using FastAPI. What You'll Learn Build RESTful and WebSocket-based APIs optimized for AI models Serve text-generation and image-generation models using FastAPI and Python Handle asynchronous processing, background tasks, and streaming outputs Secure endpoints with OAuth2, JWT tokens, and role-based access control (RBAC) Use Docker, GitHub Actions, and Render/Fly.io for full CI/CD deployments Integrate with Hugging Face Transformers, Diffusers, and modern AI libraries Develop a complete multi-model chat and image web app with frontend integration 1. Build Scalable AI APIs with FastAPI and Python Learn how to structure high-performance endpoints for machine learning workloads using FastAPI's async architecture. 2. Serve Generative Models Like GPT and Stable Diffusion Deploy language and image models using Hugging Face libraries, optimized for real-world inference. 3. Stream Responses with WebSockets and Server-Sent Events Deliver token-by-token LLM responses and real-time image generation feedback using FastAPI's async capabilities. 4. Secure Production-Grade AI Endpoints Implement authentication, rate limiting, and logging for mission-critical AI applications. 5. Deploy Your AI App with Docker, CI/CD, and Cloud Platforms Use containerization and GitHub Actions to launch to Render, Fly.io, or AWS. 6. Integrate Frontend Interfaces Using Streamlit or React Connect user-friendly frontends to your AI backend for real-time interaction and demo-ready delivery. 7. Real-World Project: Generative AI Chat + Image App Follow a complete walkthrough of building a multi-modal generative AI app, from architecture to deployment. Who This Book Is For Backend developers building intelligent APIs AI engineers deploying LLMs or diffusion models in production Python developers exploring modern web frameworks MLOps professionals scaling generative AI systems Teams building AI SaaS platforms, agentic tools, or custom inference endpoints Unlike generic AI or FastAPI books, FastAPI for Generative AI focuses specifically on real-time generative workloads, delivering both depth and practicality. You'll not only learn how to serve models-you'll learn how to build robust, deployable products around them.