memoryscope.core.operation.base_workflow

class memoryscope.core.operation.base_workflow.BaseWorkflow(name: str, memoryscope_context: ~memoryscope.core.utils.singleton.singleton.<locals>._singleton, workflow: str = '', **kwargs)

基类：object

__init__(name: str, memoryscope_context: ~memoryscope.core.utils.singleton.singleton.<locals>._singleton, workflow: str = '', **kwargs)

workflow_print_console(*args, **kwargs)

init_workers(is_backend: bool = False, **kwargs)

Initializes worker instances based on the configuration for each worker defined in G_CONTEXT.worker_config. Each worker can be set to run in a multithreaded mode depending on the is_backend flag or the worker's individual configuration.

参数:

• is_backend (bool, optional) -- A flag indicating whether the workers should be initialized in a

• False. (backend context. Defaults to)

• **kwargs -- Additional keyword arguments to be passed during worker initialization.

抛出:

RuntimeError -- If a worker mentioned in self.worker_dict does not exist in G_CONTEXT.worker_config.

备注

This method modifies self.worker_dict in-place, replacing the keys with actual worker instances.

run_workflow(**kwargs)

Executes the workflow by orchestrating the steps defined in self.workflow_worker_list. This method supports both sequential and parallel execution of sub-workflows based on the structure of self.workflow_worker_list.

If a workflow part consists of a single item, it is executed sequentially. For parts with multiple items, they are submitted for parallel execution using a thread pool. The workflow will stop if any sub-workflow returns False.

参数:

**kwargs -- Additional keyword arguments to be passed to context.