Content-Length: 322084 | pFad | http://reference.langchain.com/python/langgraph/graph/state/StateGraph
A graph whose nodes communicate by reading and writing to a shared state.
The signature of each node is State -> Partial<State>.
Each state key can optionally be annotated with a reducer function that
will be used to aggregate the values of that key received from multiple nodes.
The signature of a reducer function is (Value, Value) -> Value.
StateGraph is a builder class and cannot be used directly for execution.
You must first call .compile() to create an executable graph that supports
methods like invoke(), stream(), astream(), and ainvoke(). See the
CompiledStateGraph documentation for more details.
StateGraph(
self,
state_schema: type[StateT],
context_schema: type[ContextT] | None = None,
*,
input_schema: type[InputT] | None = None,
output_schema: type[OutputT] | None = None,
**kwargs: Unpack[DeprecatedKwargs] = {}
)The config_schema parameter is deprecated in v0.6.0 and support will be removed in v2.0.0.
Please use context_schema instead to specify the schema for run-scoped context.
Example:
from langchain_core.runnables import RunnableConfig
from typing_extensions import Annotated, TypedDict
from langgraph.checkpoint.memory import InMemorySaver
from langgraph.graph import StateGraph
from langgraph.runtime import Runtime
def reducer(a: list, b: int | None) -> list:
if b is not None:
return a + [b]
return a
class State(TypedDict):
x: Annotated[list, reducer]
class Context(TypedDict):
r: float
graph = StateGraph(state_schema=State, context_schema=Context)
def node(state: State, runtime: Runtime[Context]) -> dict:
r = runtime.context.get("r", 1.0)
x = state["x"][-1]
next_value = x * r * (1 - x)
return {"x": next_value}
graph.add_node("A", node)
graph.set_entry_point("A")
graph.set_finish_point("A")
compiled = graph.compile()
step1 = compiled.invoke({"x": 0.5}, context={"r": 3.0})
# {'x': [0.5, 0.75]}| Name | Type | Description |
|---|---|---|
state_schema* | type[StateT] | The schema class that defines the state. |
context_schema | type[ContextT] | None | Default: NoneThe schema class that defines the runtime context. Use this to expose immutable context data to your nodes, like |
input_schema | type[InputT] | None | Default: NoneThe schema class that defines the input to the graph. |
output_schema | type[OutputT] | None | Default: NoneThe schema class that defines the output from the graph. |
Add a new node to the StateGraph.
Add a directed edge from the start node (or list of start nodes) to the end node.
When a single start node is provided, the graph will wait for that node to complete before executing the end node. When multiple start nodes are provided, the graph will wait for ALL of the start nodes to complete before executing the end node.
Add a conditional edge from the starting node to any number of destination nodes.
Add a sequence of nodes that will be executed in the provided order.
Specifies the first node to be called in the graph.
Equivalent to calling add_edge(START, key).
Sets a conditional entry point in the graph.
Marks a node as a finish point of the graph.
If the graph reaches this node, it will cease execution.
Compiles the StateGraph into a CompiledStateGraph object.
The compiled graph implements the Runnable interface and can be invoked,
streamed, batched, and run asynchronously.
Fetched URL: http://reference.langchain.com/python/langgraph/graph/state/StateGraph
Alternative Proxies: