What is LangGraph and how does it enable stateful agent applications?

LangGraph is a framework from LangChain for building stateful, multi-step agent applications as directed graphs. Each node in the graph represents a processing step such as an LLM call, tool execution, or conditional logic, and edges define the flow between steps. LangGraph provides built-in state management that persists across graph execution, enabling complex multi-turn interactions with memory. Key features include conditional branching based on LLM output or state conditions, parallel execution of independent branches, human-in-the-loop approval gates at critical decision points, subgraph composition for modular agent design, and streaming support for real-time response delivery. LangGraph supports both synchronous and asynchronous execution. It provides checkpointing for durable execution across failures. For multi-agent systems, LangGraph enables defining communication patterns and handoffs between agents. The graph-based approach makes complex agent workflows more transparent and debuggable compared to opaque chain-based approaches.