Special value to indicate that graph should interrupt on all nodes.
How the stream method should emit outputs.
"values": Emit all values in the state after each step, including interrupts.
When used with functional API, values are emitted once at the end of the workflow."updates": Emit only the node or task names and updates returned by the nodes or tasks after each step.
If multiple updates are made in the same step (e.g. multiple nodes are run) then those updates are emitted separately."custom": Emit custom data using from inside nodes or tasks using StreamWriter."messages": Emit LLM messages token-by-token together with metadata for any LLM invocations inside nodes or tasks."checkpoints": Emit an event when a checkpoint is created, in the same format as returned by get_state()."tasks": Emit events when tasks start and finish, including their results and errors."debug": Emit "checkpoints" and "tasks" events for debugging purposes.Type variable used to represent graph run scoped context.
Defaults to None.
Type variable used to represent the input to a StateGraph.
Defaults to StateT.
Type variable used to represent the output of a StateGraph.
Defaults to StateT.
Type variable used to represent the state in a graph.
One or more commands to update the graph's state and send messages to nodes.
Typed container returned by invoke() / ainvoke() with version="v2".
Snapshot of the state of the graph at the beginning of a step.
A discriminated union of all v2 stream part types.
Use part["type"] to narrow the type:
async for part in graph.astream(input, version="v2"):
if part["type"] == "values":
part["data"] # OutputT — full state (pydantic/dataclass/dict)
elif part["type"] == "messages":
part["data"] # tuple[BaseMessage, dict] — (message, metadata)
elif part["type"] == "custom":
part["data"] # Any — user-defined