Building an AI Agent System with the ReACT Pattern in Java

Short summary

This tutorial walks through implementing a ReACT (Reason + Act) pattern-based AI agent system in Java as part of a multi-phase Jarvis AI Platform project. It covers architectural decisions like separating agent orchestration from chat pipelines, using structured prompts for tool dispatch, streaming reasoning steps via WebFlux Flux, and enforcing agent lifecycle states with timeouts and cancellation checks. The implementation includes practical lessons on regex-based response parsing, exact tool-name matching, and step-counting for multi-event reasoning cycles.

• •Separates agent orchestration into its own layer (AgentController, AgentOrchestrator, AgentExecutor, AgentPlanner, ToolRegistry) without modifying existing chat pipeline
• •Uses structured prompt contracts with regex parsing for THINK/ACT/OBSERVE/FINAL_ANSWER output and streams each step to the browser via WebFlux
• •Enforces safety with max step counts, timeouts, cancellation checks, and domain-model-enforced lifecycle transitions

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