This session explores LangGraph4J, a powerful Java framework for building stateful, multi-agent workflows using cyclical graphs, and shows how it seamlessly integrates with LangChain4J to supercharge your LLM-based systems.

LangGraph4J supports asynchronous execution, debugging checkpoints, and multi-agent collaboration, and can be integrated smoothly with LangChain4J's unified APIs for LLM interactions, prompt management, and advanced patterns such as Retrieval-Augmented Generation (RAG).

We’ll walk through a real-world example of asynchronous execution, streaming responses, and modular graph composition.