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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.

ASIN ‏ : ‎ B0FCMQ5VP2
Accessibility ‏ : ‎ Learn more
Publication date ‏ : ‎ June 9, 2025
Language ‏ : ‎ English
File size ‏ : ‎ 523 KB
Screen Reader ‏ : ‎ Supported
Enhanced typesetting ‏ : ‎ Enabled
X-Ray ‏ : ‎ Not Enabled
Word Wise ‏ : ‎ Not Enabled
Print length ‏ : ‎ 205 pages
Page Flip ‏ : ‎ Enabled