ZifSSKJr SSKJrJrJr SSKJrJrJ r SSK J r SSK J r SSKJrJr SSKJrJr SSKJr SS KJrJr SS KJr S r\"S S S 9"SS55r\"S S S 9"SS55rSSjr"SS\\\SS9r\"S0\D6"SS\\55r \ "SS\SSS9r!SSSjjr"g) ) annotations) dataclassfieldreplace)AnyGenericcast) BaseStore)BaseUser) TypedDictUnpack)CONFCONFIG_KEY_RUNTIME) get_config) _DC_KWARGS StreamWriter)ContextT)r ExecutionInfoRuntime ServerInfo get_runtimeT)frozenslotsc\rSrSr%SrS\S'S\S'S\S'SrS\S 'SrS\S 'S rS \S 'Sr S\S'SSjr Sr g)rzORead-only execution info/metadata for the execution of current thread/run/node.str checkpoint_id checkpoint_nstask_idNz str | None thread_idrun_idint node_attemptz float | Nonenode_first_attempt_timec [U40UD6$)zAReturn a new execution info object with selected fields replaced.rself overridess k/var/www/eduai.edurigo.com/question_generate/ques_gen_env/lib/python3.13/site-packages/langgraph/runtime.pypatchExecutionInfo.patch5st)y)))r*rreturnr) __name__ __module__ __qualname____firstlineno____doc____annotations__r r!r$r%r,__static_attributes__r/r.r+rrscY6= L0 Iz HFJAL#<,0\0F*r.rc@\rSrSr%SrS\S'S\S'SrS\S'S rg) r:zmMetadata injected by LangGraph Server. None when running open-source LangGraph without LangSmith deployments.r assistant_idgraph_idNzBaseUser | Noneuserr/)r1r2r3r4r5r6r<r7r/r.r+rr:s%w5M1 D/ r.rcgNr/)_s r+_no_op_stream_writerr@Ms#r.cR\rSrSr%S\S'S\S'S\S'S\S 'S \S 'S \S 'Srg)_RuntimeOverridesPrcontextBaseStore | Nonestorer stream_writerrpreviousrexecution_infoServerInfo | None server_infor/N)r1r2r3r4r6r7r/r.r+rBrBPs%  M!!""r.rBF)totalc\rSrSr%Sr\"SS9rS\S'\"SS9rS\S'\"\ S9r S \S '\"SS9r S \S '\"SS9r S \S'\"SS9r S\S'SSjrSSjrSSjrSrg)rYaConvenience class that bundles run-scoped context and other runtime utilities. This class is injected into graph nodes and middleware. It provides access to `context`, `store`, `stream_writer`, `previous`, and `execution_info`. !!! note "Accessing `config`" `Runtime` does not include `config`. To access `RunnableConfig`, you can inject it directly by adding a `config: RunnableConfig` parameter to your node function (recommended), or use `get_config()` from `langgraph.config`. !!! note `ToolRuntime` (from `langgraph.prebuilt`) is a subclass that provides similar functionality but is designed specifically for tools. It shares `context`, `store`, and `stream_writer` with `Runtime`, and adds tool-specific attributes like `config`, `state`, and `tool_call_id`. !!! version-added "Added in version v0.6.0" Example: ```python from typing import TypedDict from langgraph.graph import StateGraph from dataclasses import dataclass from langgraph.runtime import Runtime from langgraph.store.memory import InMemoryStore @dataclass class Context: # (1)! user_id: str class State(TypedDict, total=False): response: str store = InMemoryStore() # (2)! store.put(("users",), "user_123", {"name": "Alice"}) def personalized_greeting(state: State, runtime: Runtime[Context]) -> State: '''Generate personalized greeting using runtime context and store.''' user_id = runtime.context.user_id # (3)! name = "unknown_user" if runtime.store: if memory := runtime.store.get(("users",), user_id): name = memory.value["name"] response = f"Hello {name}! Nice to see you again." return {"response": response} graph = ( StateGraph(state_schema=State, context_schema=Context) .add_node("personalized_greeting", personalized_greeting) .set_entry_point("personalized_greeting") .set_finish_point("personalized_greeting") .compile(store=store) ) result = graph.invoke({}, context=Context(user_id="user_123")) print(result) # > {'response': 'Hello Alice! Nice to see you again.'} ``` 1. Define a schema for the runtime context. 2. Create a store to persist memories and other information. 3. Use the runtime context to access the `user_id`. N)defaultrrDrErFrrGrrHzExecutionInfo | NonerIrJrKc [UR=(d URUR=(d URUR[La URO URUR c UR O UR UR =(d UR UR=(d URS9$)z{Merge two runtimes together. If a value is not provided in the other runtime, the value from the current runtime is used. )rDrFrGrHrIrK)rrDrFrGr@rHrIrK)r)others r+merge Runtime.merges MM1T\\+++""*>> --##&+nn&N(>2&+4%8K"8w *>* *  r.rN)rDrFrGrHrIcx[[[[5[R [ 55nU$)zGet the runtime for the current graph run. Args: context_schema: Optional schema used for type hinting the return type of the runtime. Returns: The runtime for the current graph run. )r rrrrgetr)context_schemaruntimes r+rrs-78$jl4&8&<&<=O&PQG Nr.)r?rr0Noner/r>)r_ztype[ContextT] | Noner0r\)# __future__r dataclassesrrrtypingrrr langgraph.store.baser langgraph_sdk.auth.typesr typing_extensionsr r langgraph._internal._constantsrrlanggraph.configrlanggraph.typesrrlanggraph.typingr__all__rrr@rBrDEFAULT_RUNTIMErr/r.r+rns"11%%*-/C'4%  $d#**$*B $d#$$.# 78#4E# Z@ gh@ @ F  &  r.