o i! @sdZddlmZddlmZmZddlmZddlm Z m Z m Z m Z m Z mZddlmZddlmZddlmZmZmZed d d Zed d d Zed d d Zedd d ZeddGddde eeefZGddde eeeefZGddde eeeefZee e e e fZ eddGddde eeeefZeGdddeeee fZ Gdddeeee eeee fee BfZ!dS)zStep-based graph execution components. This module provides the core abstractions for step-based graph execution, including step contexts, step functions, and step nodes that bridge between the v1 and v2 graph execution systems. ) annotations) AsyncIterator Awaitable) dataclass)AnyGenericProtocolcast get_originoverload)TypeVar)NodeID)BaseNodeEndGraphRunContextStateTT)infer_varianceDepsTInputTOutputTF)initc@sdeZdZUdZded< ded< ded< dd d ZedddZedddZedddZ dS) StepContextaMContext information passed to step functions during graph execution. The step context provides access to the current graph state, dependencies, and input data for a step. Type Parameters: StateT: The type of the graph state DepsT: The type of the dependencies InputT: The type of the input data r_stater_depsr_inputsstatedepsinputscC||_||_||_dSN)rrr)selfrrrr!^/var/www/html/karishye-ai-python/venv/lib/python3.10/site-packages/pydantic_graph/beta/step.py__init__, zStepContext.__init__returncC|jSr)rr r!r!r"r1zStepContext.statecCr&r)rr'r!r!r"r5r(zStepContext.depscCr&)zkThe input data for this step. This must be a property to ensure correct variance behavior )rr'r!r!r"r9szStepContext.inputsN)rrrrrr)r%r)r%r)r%r) __name__ __module__ __qualname____doc____annotations__r#propertyrrrr!r!r!r"rs     rc@eZdZdZd ddZdS) StepFunctionabProtocol for step functions that can be executed in the graph. Step functions are async callables that receive a step context and return a result. Type Parameters: StateT: The type of the graph state DepsT: The type of the dependencies InputT: The type of the input data OutputT: The type of the output data ctx"StepContext[StateT, DepsT, InputT]r%Awaitable[OutputT]cCst)zExecute the step function with the given context. Args: ctx: The step context containing state, dependencies, and inputs Returns: An awaitable that resolves to the step's output NotImplementedErrorr r1r!r!r"__call__Ns zStepFunction.__call__N)r1r2r%r3r)r*r+r,r7r!r!r!r"r0B r0c@r/) StreamFunctionaoProtocol for stream functions that can be executed in the graph. Stream functions are async callables that receive a step context and return an async iterator. Type Parameters: StateT: The type of the graph state DepsT: The type of the dependencies InputT: The type of the input data OutputT: The type of the output data r1r2r%AsyncIterator[OutputT]ccst)zExecute the stream function with the given context. Args: ctx: The step context containing state, dependencies, and inputs Returns: An async iterator yielding the streamed output r4r6r!r!r"r7fs zStreamFunction.__call__N)r1r2r%r;r8r!r!r!r"r:Zr9r:c@sxeZdZUdZded< ded< ded< dd dd d ZedddZeddddZ edddZ ddddZ dS)StepaA step in the graph execution that wraps a step function. Steps represent individual units of execution in the graph, encapsulating a step function along with metadata like ID and label. Type Parameters: StateT: The type of the graph state DepsT: The type of the dependencies InputT: The type of the input data OutputT: The type of the output data r id,StepFunction[StateT, DepsT, InputT, OutputT]_call str | NonelabelN)rAcallcCrr)r=r?rA)r r=rBrAr!r!r"r#r$z Step.__init__r%cCr&)zXThe step function to execute. This needs to be a property for proper variance inference.)r?r'r!r!r"rBsz Step.callrNoneStepNode[StateT, DepsT]cCdSrr!r rr!r!r"as_nodez Step.as_nodercCrErr!rFr!r!r"rGrH InputT | NonecCs t||S)zCreate a step node with bound inputs. Args: inputs: The input data to bind to this step, or None Returns: A [`StepNode`][pydantic_graph.beta.step.StepNode] with this step and the bound inputs )StepNoderFr!r!r"rGs )r=r rBr>rAr@)r%r>r)rrCr%rD)rrr%rD)rrIr%rD) r)r*r+r,r-r#r.rBr rGr!r!r!r"r<ws    r<c@s0eZdZUdZded< ded< d d d Zd S)rJaIA base node that represents a step with bound inputs. StepNode bridges between the v1 and v2 graph execution systems by wrapping a [`Step`][pydantic_graph.beta.step.Step] with bound inputs in a BaseNode interface. It is not meant to be run directly but rather used to indicate transitions to v2-style steps. zStep[StateT, DepsT, Any, Any]steprrr1GraphRunContext[StateT, DepsT]r%'BaseNode[StateT, DepsT, Any] | End[Any]cs td)a Attempt to run the step node. Args: ctx: The graph execution context Returns: The result of step execution Raises: NotImplementedError: Always raised as StepNode is not meant to be run directly z`StepNode` is not meant to be run directly, it is meant to be used in `BaseNode` subclasses to indicate a transition to v2-style steps.r4r6r!r!r"runs z StepNode.runN)r1rLr%rM)r)r*r+r,r-rNr!r!r!r"rJs rJcs@eZdZUdZded< ddddfd d ZdddZZS)NodeStepa A step that wraps a BaseNode type for execution. NodeStep allows v1-style BaseNode classes to be used as steps in the v2 graph execution system. It validates that the input is of the expected node type and runs it with the appropriate graph context. "type[BaseNode[StateT, DepsT, Any]] node_typeN)r=rAr= NodeID | NonerAr@cs2tj|p t||j|dt|p||_dS)aInitialize a node step. Args: node_type: The BaseNode class this step will execute id: Optional unique identifier, defaults to the node's get_node_id() label: Optional human-readable label for this step )r=rBrAN)superr#r get_node_id _call_noder rQ)r rQr=rA __class__r!r"r#s zNodeStep.__init__r1StepContext[StateT, DepsT, Any]r%rMcsZ|j}t||jstd|d|jtttttf|}| t |j |j dIdHS)aAExecute the wrapped node with the step context. Args: ctx: The step context containing the node instance to run Returns: The result of running the node, either another BaseNode or End Raises: ValueError: If the input node is not of the expected type zNode z is not of type )rrN) r isinstancerQ ValueErrorr rrrrrNrrr)r r1noder!r!r"rUs  zNodeStep._call_node)rQrPr=rRrAr@)r1rXr%rM)r)r*r+r,r-r#rU __classcell__r!r!rVr"rOs rON)"r, __future__rcollections.abcrr dataclassesrtypingrrrr r r typing_extensionsr pydantic_graph.beta.id_typesr pydantic_graph.nodesrrrrrrrrr0r:AnyStepFunctionr<rJrOr!r!r!r"s.         (02"