Agent Frameworks Overview
⚠️ This page is just unchecked AI-generated sample data to demonstrate the resource structure for flatmap-docs-kit.
Discover the powerful world of AI agent frameworks in Java. These frameworks enable you to build intelligent, autonomous systems that can reason, plan, and execute complex tasks.
🤖 What Are AI Agents?
AI agents are autonomous software systems that can:
- Perceive their environment through various inputs
- Reason about situations and make decisions
- Act by executing tasks or providing responses
- Learn from feedback to improve over time
🎯 Featured Frameworks
LangGraph4J
The Java implementation of LangGraph, enabling you to build stateful, multi-step AI applications with complex workflows and memory management.
ADK (Agent Development Kit)
A comprehensive toolkit for building production-ready AI agents with built-in support for state machines, tool integration, and monitoring.
LangChain4J Agents
Extend LangChain4J with agent capabilities for building conversational AI systems and task-oriented assistants.
🚀 Key Capabilities
Each framework provides:
- State Management - Maintain context across interactions
- Tool Integration - Connect to external APIs and services
- Memory Systems - Remember past interactions and learn
- Workflow Orchestration - Coordinate complex multi-step processes
- Monitoring & Observability - Track agent performance and behavior
🔧 Getting Started
Choose your framework based on your needs:
Framework | Best For | Complexity | Production Ready |
---|---|---|---|
LangGraph4J | Complex workflows | High | Yes |
ADK | Enterprise agents | Medium | Yes |
LangChain4J | Simple agents | Low | Yes |
📚 Learning Path
- Start with LangChain4J for basic agent concepts
- Move to ADK for production applications
- Explore LangGraph4J for advanced workflows
Ready to build your first AI agent? Let's get started!