ebook: Building AI Web APIs with ASP.NET Core. Serving Models and Chat Endpoints
Unlock the Future of Application Development by Mastering AI Backend APIs with ASP.NET Core!
The AI revolution is here, but powerful models are useless without robust, scalable, and secure backend infrastructure to serve them. This book is the definitive guide for experienced .NET developers looking to bridge the gap between traditional web development and the high-performance demands of modern AI applications. Move beyond simple CRUD APIs and learn to build the backbone of the next generation of intelligent software.
Written for production-focused engineers, this comprehensive volume deconstructs every critical component of an enterprise-grade AI Web API. You will progress from foundational architectural decisions to advanced real-time communication patterns, culminating in the creation of a complete backend for a ChatGPT-clone.
Inside, you will master:
High-Performance Architecture: Learn to choose between Controllers and Minimal APIs and leverage Dependency Injection to manage the lifecycle of heavy AI models, preventing costly memory leaks and performance bottlenecks.
Real-Time Streaming: Build incredibly responsive user experiences by streaming LLM tokens and audio data with Server-Sent Events (SSE), SignalR, and low-level WebSockets.
Efficient Microservices Communication: Supercharge your internal service communication by replacing slow REST/JSON calls with high-throughput gRPC and Protocol Buffers.
Production-Grade Resilience: Fortify your application against network failures and API outages by implementing essential resilience patterns like Retries and Circuit Breakers with Polly.
Security & Cost Control: Secure your endpoints with JWTs and API Keys, manage costs with intelligent Hybrid Caching, and protect your resources from abuse with sophisticated, policy-based Rate Limiting.
Complete Observability: Instrument your entire application with OpenTelemetry to gain deep insights into traces, metrics, and structured logs, making it easy to diagnose latency and errors in a distributed system.
OpenAI Compatibility: Learn to create OpenAI-compatible plugin specifications, allowing your API to be seamlessly integrated into the broader AI ecosystem.
This is not a theoretical overview; it is a practical, hands-on guide packed with code examples, architectural diagrams, and best practices forged in real-world scenarios. By the time you finish this book, you will have the skills and confidence to design, build, and deploy AI backend APIs that are not only intelligent but also scalable, secure, and resilient.
Stop just using AI—start building the platforms that power it. Grab your copy and become a leader in the new era of software development!
Table of contents:
Chapter 1: Anatomy of an ASP.NET Core Project
Chapter 2: Controllers vs Minimal APIs - Performance Choices
Chapter 3: Dependency Injection (DI) Service Lifetimes
Chapter 4: Middleware Pipelines and Request Handling
Chapter 5: Configuration and Options Pattern (Managing API Keys)
Chapter 6: Server-Sent Events (SSE) for Streaming LLM Tokens
Chapter 7: SignalR - Building Real-Time Chat Channels
Chapter 8: WebSockets - Low Latency Audio Streaming
Chapter 9: gRPC for High-Performance Inter-Service AI Calls
Chapter 10: Background Services (IHostedService) for Model Loading
Chapter 11: Consuming OpenAI/Azure APIs with HttpClientFactory
Chapter 12: Resilience Patterns - Retries and Circuit Breakers (Polly)
Chapter 13: Caching Responses to Save API Costs (HybridCache)
Chapter 14: Rate Limiting Users in AI Applications
Chapter 15: Creating an OpenAI-Compatible Plugin Specification
Chapter 16: Authentication (JWT) & API Key Management
Chapter 17: Logging & Telemetry with OpenTelemetry
Chapter 18: API Documentation with Swagger/OpenAPI
Chapter 19: Error Handling and ProblemDetails
Chapter 20: Capstone - Building a 'ChatGPT-Clone' Backend API
The book consists of over 400 pages (if printed) and includes flowcharts that illustrate the main concepts. Each chapter is structured as follows: it begins with the basic theoretical principles, followed by a simple example explained in detail. Next, a more advanced, complex example is presented, also analyzed step by step.
Each chapter then offers five exercises with detailed requirements, accompanied by complete solutions and in-depth instructor analyses. Even if you don’t have time to work through the exercises, you can still read them and study the solutions to learn from the practical cases.
This eBook is part of the C# and AI Masterclass series, which guides you from the fundamentals of programming—even if you’re starting from scratch—up to advanced artificial intelligence, showing how to integrate AI across various aspects of enterprise-level programming.
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