langgraph-implementationlisted

# LangGraph Implementation ## Core Concepts LangGraph builds stateful, multi-actor agent applications using a graph-based architecture: - **StateGraph**: Builder class for defining graphs with shared state - **Nodes**: Functions that read state and return partial updates - **Edges**: Define execution flow (static or conditional) - **Channels**: Internal state management (LastValue, BinaryOperatorAggregate) - **Checkpointer**: Persistence for pause/resume capabilities ## Implementation gates Use these **sequenced checks** for persistence and human-in-the-loop flows (avoid “it should work” without evidence): 1. **Checkpointed runs** - Build `config` with `{"configurable": {"thread_id": "<stable-id>"}}` before `invoke` / `ainvoke`. - **Pass:** The same `thread_id` is reused for every turn of one conversation; a new conversation uses a new id. 2. **State after a step** - **Pass:** `graph.get_state(config).values` (or equivalent) contains the keys and reducer outputs your next node or client expects; if not, fix routing, reducers, or node order before continuing. 3. **Interrupt and resume (HITL)** - **Pass:** After a pause, you have inspected pending work (`get_state`, and your LangGraph version’s interrupt listing if you rely on it) so you know **which** node is waiting and **what** resume payload shape to send. - **Pass:** `Command(resume=...)` (or equivalent) includes every field the code path after `interrupt()` reads. 4. **Checkpointer vs environment**