LangGraph Fundamentals

You can build a stateful agentic workflow with LangGraph by defining a StateGraph, implementing nodes as functions, and connecting them with static or conditional edges to control execution flow and orchestration.

State management in LangGraph uses Annotated types and reducers to control state updates. Reducers enable list accumulation and custom logic, ensuring nodes update shared state predictably during graph execution.

The Command API in LangGraph orchestration is used to combine state updates and routing decisions within a single node. This allows nodes to dynamically direct the execution flow while modifying the graph's state.

Yes, you can implement conditional routing in LangGraph for multi-turn conversational agents. By defining conditional edges, the graph can branch to different tools based on the current context, intent, and conversation history.

Yes, LangGraph supports both Python and TypeScript for agent state management. You can use either language to build complex, stateful agent orchestrations using StateGraphs, nodes, edges, and reducers.