SpringTutorials
    Spring AI Tutorials
    Tutorial 02

    Spring AI Core – A Comprehensive Deep Dive

    Master Spring AI architecture, prompt engineering, advisors, chat configuration, streaming, and structured output

    What You'll Learn

    8 comprehensive sections covering Spring AI from fundamentals to advanced patterns

    Spring AI Fundamentals

    Prompt Engineering with Spring AI

    Advisor-Based AI Workflows

    Chat Configuration and Controls

    Working with ChatClient Responses

    Real-Time AI Interactions

    Structured Output and Type Safety

    Advanced Response Mapping

    1
    Spring AI Fundamentals

    1.1

    Deep Dive into Spring AI Core Architecture

    Explore the foundational architecture of Spring AI, understanding how components interact to enable AI capabilities.

    1.2

    Understanding Message Roles in Large Language Models

    Learn about System, User, and Assistant roles and how they shape conversations with LLMs.

    1.3

    Default Behaviors and Configurations in Spring AI

    Master the default settings and how to customize Spring AI for your specific needs.

    Coming Soon

    Detailed content for this section is being prepared. Check back soon for in-depth explanations, code examples, and best practices.

    2
    Prompt Engineering with Spring AI

    2.1

    Building Dynamic Prompts Using Prompt Templates

    Create flexible, reusable prompts that adapt to different contexts and user inputs.

    2.2

    Why Prompt Stuffing Fails for Large-Scale Data Scenarios

    Understand the limitations of prompt stuffing and when to use alternative approaches.

    2.3

    Best Practices for Prompt Design in Production Systems

    Learn production-ready patterns for designing effective and maintainable prompts.

    Coming Soon

    Detailed content for this section is being prepared. Check back soon for in-depth explanations, code examples, and best practices.

    3
    Advisor-Based AI Workflows

    3.1

    Introduction to Advisors in Spring AI Pipelines

    Discover how Advisors enable modular, pluggable AI behavior in your applications.

    3.2

    Using Built-in Advisors for Plug-and-Play Intelligence

    Leverage Spring AI's built-in advisors for common AI patterns and use cases.

    3.3

    Creating Custom Advisors to Tailor AI Behavior

    Build your own advisors to implement custom business logic and AI behaviors.

    Coming Soon

    Detailed content for this section is being prepared. Check back soon for in-depth explanations, code examples, and best practices.

    4
    Chat Configuration and Controls

    4.1

    Understanding ChatOptions and Their Role

    Learn what ChatOptions are and how they control AI model behavior.

    4.2

    Configuring ChatOptions for Fine-Grained AI Control

    Master the art of configuring ChatOptions for precise control over AI responses.

    4.3

    Managing Temperature, Tokens, and Model Behavior

    Fine-tune temperature, token limits, and other parameters for optimal results.

    Coming Soon

    Detailed content for this section is being prepared. Check back soon for in-depth explanations, code examples, and best practices.

    5
    Working with ChatClient Responses

    5.1

    Spring AI ChatClient Overview

    Get a comprehensive understanding of the ChatClient and its capabilities.

    5.2

    Exploring Different ChatClient Response Types

    Learn about various response types and when to use each one.

    5.3

    Handling Synchronous and Asynchronous Responses

    Master both sync and async patterns for handling AI responses effectively.

    Coming Soon

    Detailed content for this section is being prepared. Check back soon for in-depth explanations, code examples, and best practices.

    6
    Real-Time AI Interactions

    6.1

    Streaming AI Responses Using the stream() API

    Implement streaming responses for real-time AI interactions.

    6.2

    Building Real-Time, Token-by-Token AI Experiences

    Create engaging UIs that display AI responses as they're generated.

    6.3

    Use Cases for Streaming in Chat and UI Applications

    Explore practical applications of streaming in modern AI-powered interfaces.

    Coming Soon

    Detailed content for this section is being prepared. Check back soon for in-depth explanations, code examples, and best practices.

    7
    Structured Output and Type Safety

    7.1

    Transforming AI Text Output into Strongly Typed Objects

    Convert raw AI text responses into type-safe Java objects.

    7.2

    Mastering Structured Output in Spring AI

    Deep dive into Spring AI's structured output capabilities and patterns.

    7.3

    Using Bean, List, and Map Output Converters

    Learn to use different output converters for various data structures.

    Coming Soon

    Detailed content for this section is being prepared. Check back soon for in-depth explanations, code examples, and best practices.

    8
    Advanced Response Mapping

    8.1

    Mapping AI Responses to List<POJO>

    Handle collections of objects returned from AI responses.

    8.2

    Leveraging ParameterizedTypeReference for Generic Type Safety

    Use Java generics effectively with Spring AI response mapping.

    8.3

    Handling Complex and Nested AI Response Structures

    Master techniques for parsing deeply nested AI response data.

    Coming Soon

    Detailed content for this section is being prepared. Check back soon for in-depth explanations, code examples, and best practices.

    What You'll Master

    Spring AI Architecture

    Core components and their interactions

    Prompt Engineering

    Templates, best practices, and production patterns

    Advisor Workflows

    Built-in and custom advisors for AI pipelines

    Chat Configuration

    ChatOptions, temperature, and model controls

    Response Handling

    Sync, async, and streaming patterns

    Structured Output

    Type-safe response mapping and converters

    💬 Comments & Discussion