langgraph-state-graph

# langgraph-state-graph Build stateful agent workflows using LangGraph's StateGraph pattern. Design state schemas, create nodes, define edges with conditional routing, and enable persistence. ## Overview LangGraph is a library for building stateful, multi-actor applications with LLMs. The StateGraph is the core abstraction that enables: - Cyclical computation graphs (unlike DAGs) - State persistence and checkpointing - Human-in-the-loop interaction patterns - Conditional branching and routing - Multi-agent coordination ## Capabilities ### State Schema Design - Define typed state schemas with TypedDict or Pydantic - Configure state channels for message passing - Set up reducer functions for state updates - Design accumulator patterns for conversation history ### Graph Construction - Create nodes as functions or runnables - Define edges (normal, conditional, entry points) - Configure start and end nodes - Implement routing logic for conditional edges ### Persistence & Checkpointing - Configure checkpoint backends (SQLite, PostgreSQL, Redis) - Enable state snapshots at each step - Support for resuming interrupted workflows - Thread-based conversation persistence ### Human-in-the-Loop - Insert interrupt points in workflows - Collect human feedback before continuing - Support approval gates and input collection - Resume from interrupt with updated state ## Usage ### Basic StateGraph Pattern ```python from typing import TypedDict, Annotated from langgraph.graph import St...