diff --git a/openadapt/strategies/vanilla.py b/openadapt/strategies/vanilla.py index 75227d799..0f9fea9ba 100644 --- a/openadapt/strategies/vanilla.py +++ b/openadapt/strategies/vanilla.py @@ -35,20 +35,20 @@ class VanillaReplayStrategy(strategies.base.BaseReplayStrategy): def __init__( self, recording: models.Recording, - replay_instructions: str = "", + instructions: str = "", process_events: bool = PROCESS_EVENTS, ) -> None: """Initialize the VanillaReplayStrategy. Args: recording (models.Recording): The recording object. - replay_instructions (str): Natural language instructions + instructions (str): Natural language instructions for how recording should be replayed. process_events (bool): Flag indicating whether to process the events. Defaults to True. """ super().__init__(recording) - self.replay_instructions = replay_instructions + self.instructions = instructions self.process_events = process_events self.action_history = [] self.action_event_idx = 0 @@ -89,7 +89,7 @@ def get_next_action_event( window_event, action_events, self.action_history, - self.replay_instructions, + self.instructions, ) if not action_event: raise StopIteration() @@ -161,7 +161,7 @@ def generate_action_event( current_window_event: models.WindowEvent, recorded_actions: list[models.ActionEvent], replayed_actions: list[models.ActionEvent], - replay_instructions: str, + instructions: str, ) -> models.ActionEvent: """Modify the given ActionEvents according to the given replay instructions. @@ -176,7 +176,7 @@ def generate_action_event( recording replayed_actions (list[models.ActionEvent]): list of actions produced during current replay - replay_instructions (str): proposed modifications in natural language + instructions (str): proposed modifications in natural language instructions Returns: @@ -195,7 +195,7 @@ def generate_action_event( current_window=current_window_dict, recorded_actions=recorded_action_dicts, replayed_actions=replayed_action_dicts, - replay_instructions=replay_instructions, + replay_instructions=instructions, ) prompt_adapter = adapters.get_default_prompt_adapter() content = prompt_adapter.prompt(