Spring AI Chatbot Memory: Implementing Context Retention for Intelligent Conversations

Building Intelligent Chatbots with Spring AI: Implementing Conversational Memory “ Context retention capability is the defining feature separating basic Q&A tools from true conversational AI systems. This comprehensive guide explores how to implement persistent memory in chatbots using Spring AI framework for natural human-machine dialogues. 1. Environment Setup and Technology Stack Core Component Dependencies The solution leverages: Spring Boot 3.5.0: Microservice framework Spring AI 1.0.0-M6: Core AI integration library Java 17: Primary development language Ollama: Local LLM runtime environment Maven Configuration <?xml version=”1.0″ encoding=”UTF-8″?> <project xmlns=”http://maven.apache.org/POM/4.0.0″ xmlns:xsi=”http://www.w3.org/2001/XMLSchema-instance” xsi:schemaLocation=”http://maven.apache.org/POM/4.0.0 https://maven.apache.org/xsd/maven-4.0.0.xsd”> <modelVersion>4.0.0</modelVersion> <parent> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter-parent</artifactId> <version>3.5.0</version> </parent> <groupId>com.example</groupId> <artifactId>test</artifactId> <version>0.0.1-SNAPSHOT</version> <properties> <java.version>17</java.version> …