codekingpro/portable-devtools
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S j5 r19Sr g)r �O av Run-scoped control surface for cooperative draining.20 21Intended for a single graph run. Create a fresh `RunControl` per run;22reusing a control after `request_drain()` leaves it drained.23 24Safe to call from any thread: the drain request is represented by a25single attribute write, so no lock is needed for this signal.26If more mutable state is added here, add synchronization.27��
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� r1 ra F)�totalc �( � \ rS rSr% Sr\" SS9rS\S' \" SS9rS\S' \" \ S9r30S \S31' \" \ S9r S \S ' \" SS9r
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\S' \" SS9rS\S' \" SS9rS\S' \" SS9rS\S' SS jr S S jrS S jr\S S j5 r\S S j5 rSrg) r �| a� Convenience class that bundles run-scoped context and other runtime utilities.32 33This class is injected into graph nodes and middleware. It provides access to34`context`, `store`, `stream_writer`, `previous`, and `execution_info`.35 36!!! note "Accessing `config`"37 38 `Runtime` does not include `config`. To access `RunnableConfig`, you can inject39 it directly by adding a `config: RunnableConfig` parameter to your node function40 (recommended), or use `get_config()` from `langgraph.config`.41 42!!! note43 `ToolRuntime` (from `langgraph.prebuilt`) is a subclass that provides similar44 functionality but is designed specifically for tools. It shares `context`, `store`,45 and `stream_writer` with `Runtime`, and adds tool-specific attributes like `config`,46 `state`, and `tool_call_id`.47 48!!! version-added "Added in version v0.6.0"49 50Example:51 52```python53from typing import TypedDict54from langgraph.graph import StateGraph55from dataclasses import dataclass56from langgraph.runtime import Runtime57from langgraph.store.memory import InMemoryStore58 59 60@dataclass61class Context: # (1)!62 user_id: str63 64 65class State(TypedDict, total=False):66 response: str67 68 69store = InMemoryStore() # (2)!70store.put(("users",), "user_123", {"name": "Alice"})71 72 73def personalized_greeting(state: State, runtime: Runtime[Context]) -> State:74 '''Generate personalized greeting using runtime context and store.'''75 user_id = runtime.context.user_id # (3)!76 name = "unknown_user"77 if runtime.store:78 if memory := runtime.store.get(("users",), user_id):79 name = memory.value["name"]80 81 response = f"Hello {name}! Nice to see you again."82 return {"response": response}83 84 85graph = (86 StateGraph(state_schema=State, context_schema=Context)87 .add_node("personalized_greeting", personalized_greeting)88 .set_entry_point("personalized_greeting")89 .set_finish_point("personalized_greeting")90 .compile(store=store)91)92 93result = graph.invoke({}, context=Context(user_id="user_123"))94print(result)95# > {'response': 'Hello Alice! Nice to see you again.'}96```97 981. Define a schema for the runtime context.992. Create a store to persist memories and other information.1003. Use the runtime context to access the `user_id`.101N)�defaultr rc rd re r rf rg rh r ri zExecutionInfo | Nonerj rk rl rm rn c �. � [ UR =( d U R UR =( d U R UR [ La UR O U R UR102 [ La UR103 O U R104 UR c U R O UR UR =( d U R UR =( d U R UR =( d U R S9$ )z{Merge two runtimes together.105 106If a value is not provided in the other runtime, the value from the current runtime is used.107)rc re rf rh ri rj rl rn ) r rc re rf r] rh r_ ri rj rl rn )r, �others r. �merge�
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�4�� 115�(*�>�*� �*� 116� �S� �S� �O� �Or1 r N)rc re rf rh ri rj rn c �x � [ [ [ [ 5 [ R [ 5 5 nU$ )z�Get the runtime for the current graph run.117 118Args:119 context_schema: Optional schema used for type hinting the return type of the runtime.120 121Returns:122 The runtime for the current graph run.123)r124 r r r r �getr )�context_schema�runtimes r. r r ( s- � � �7�8�$�j�l�4�&8�&<�&<�=O�&P�Q�G� �Nr1 )r\ r r3 rT rS r2 rE )r� ztype[ContextT] | Noner3 r� )'�125__future__r �collections.abcr � dataclassesr r r �typingr r r126 �langgraph.store.baser �langgraph_sdk.auth.typesr �typing_extensionsr
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