Building Chatbot Applications

Introduction

Building a chatbot with Spring AI combines the ChatClient, prompt templates, and conversation memory to create an interactive assistant in a Spring Boot application. You manage conversation context, structure prompts, and optionally ground answers in your own data with retrieval. The result is a maintainable, production-ready chatbot.

Definition

Chatbot applications use AI models to provide interactive conversational experiences.

Types

Web-based Chatbots

Chatbots integrated into web applications

API-based Chatbots

Chatbot services exposed via REST APIs

Streaming Chatbots

Real-time streaming chat applications

Multi-modal Chatbots

Chatbots with text, voice, and image capabilities

Use Cases

• Customer service automation
• Virtual assistants
• Educational tutoring
• Healthcare support
• E-commerce assistance

Implementation

Spring AI provides abstractions for managing conversations, context, and AI responses.

In Practice

A Spring AI chatbot typically keeps conversation history, applies a system prompt to set behavior, and uses retrieval from a vector store to answer questions about specific content. Streaming responses improve perceived speed, and structured output helps integrate the bot with the rest of the application.

Key Points

• Conversation state management
• Context preservation
• Response streaming
• Multi-modal interactions

References

• Spring AI Chatbot — Building chatbots with Spring AI