A step-by-step guide to integrating Amazon Bedrock AgentCore memory into a Spring AI application. Covers adding Maven dependencies, configuring short/long-term memory in AWS Management Console, setting up a MemoryConfig class with sliding window ChatMemory (20 messages), and building a stateful REST controller that maintains conversation history using Spring AI's advisor pattern. Includes curl commands for testing and an end-to-end flow diagram.
Table of contents
Step 1: Add the Ai model and AgentCore memory dependenciesStep 2: Create Short/Long Term in AWS Management ConsoleStep 3: Add the following memory-related properties.Step 4: Add the below MemoryConfig class.Step 5: Create the ChatRequest and ChatResponse classes as shown below.Step 6: Add the below ShortTermController class.Step 7: verifyEnd-to-End FlowReferencesMahendra Rao BSort: