Spring AI ChatMemory: Concepts, Practical Setup, and Common Issues

This guide explains how Spring AI abstracts LLM conversation memory using a three‑layer architecture, demonstrates configuring MessageWindowChatMemory with a sliding‑window strategy, shows two ways to register the memory advisor, and provides complete Maven, YAML, and Java code examples with test screenshots.

ChatMemoryConversation MemoryJava

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Spring AI ChatMemory: Concepts, Practical Setup, and Common Issues

The Dominant Programmer

Apr 27, 2026 · Backend Development

Add AI Chat Memory and Redis Persistence to Spring Boot using LangChain4j

This guide shows how to integrate LangChain4j with Alibaba Baichuan's DashScope model in a Spring Boot application, enabling per‑user AI chat memory identified by @MemoryId, isolating conversations, and persisting the sliding‑window message history to Redis with TTL handling.

AI chatbotAlibaba BaichuanConversation Memory

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Add AI Chat Memory and Redis Persistence to Spring Boot using LangChain4j

James' Growth Diary

Apr 25, 2026 · Artificial Intelligence

Choosing the Right AI Memory: Truncation, Summarization, or Vector Retrieval

This article breaks down LangChain.js's three memory strategies—window truncation, summary compression, and vector‑store retrieval—explaining their inner workings, code setup, trade‑offs in token cost and information retention, and provides a decision guide for selecting the best approach in multi‑turn LLM conversations.

Conversation MemoryLLMLangChain

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Choosing the Right AI Memory: Truncation, Summarization, or Vector Retrieval