How to use vector databases to make AI context-aware.
Built-in tools for Retrieval-Augmented Generation, including document readers, splitters, and embedding transformers. Inside "Spring AI in Action"
Implementing safety measures in AI applications. Observability: Monitoring Gen AI apps from the start. Spring AI in Action PDF & eBook spring ai in action pdf github link
for portable communication with providers like OpenAI and Anthropic. RAG (Retrieval Augmented Generation):
Code to implement conversational AI using Spring AI abstractions. Testing & Evaluation: Examples of how to test AI responses. Why You Need This Book How to use vector databases to make AI context-aware
| Chapter | Title | | :------ | :---- | | 1 | Getting started with Spring AI | | 2 | Evaluating generated responses | | 3 | Submitting prompts for generation | | 4 | Talking with your documents | | 5 | Enabling conversational memory | | 6 | Activating tool-driven generation | | 7 | Applying Model Context Protocol | | 8 | Generating with voice and pictures | | 9 | Observing AI operations | | 10 | Safeguarding generative AI | | 11 | Applying generative AI patterns | | 12 | Employing agents |
Tool calling (function calling) allows AI models to invoke real APIs and fetch live data. The repository is an excellent reference for weather and stock price examples. Observability: Monitoring Gen AI apps from the start
: The primary repository for the book's sample code. It includes branches for different Spring AI versions (e.g., main for 1.0.3 and spring-ai-1.1.0 for newer updates).
The official GitHub repository for the code examples from the book Spring AI in Action