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fix(VanillaReplayStrategy): replay_instructions -> instructions (#849)
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openadapt/strategies/vanilla.py

Lines changed: 7 additions & 7 deletions
Original file line numberDiff line numberDiff line change
@@ -35,20 +35,20 @@ class VanillaReplayStrategy(strategies.base.BaseReplayStrategy):
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def __init__(
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self,
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recording: models.Recording,
38-
replay_instructions: str = "",
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instructions: str = "",
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process_events: bool = PROCESS_EVENTS,
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) -> None:
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"""Initialize the VanillaReplayStrategy.
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Args:
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recording (models.Recording): The recording object.
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replay_instructions (str): Natural language instructions
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instructions (str): Natural language instructions
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for how recording should be replayed.
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process_events (bool): Flag indicating whether to process the events.
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Defaults to True.
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"""
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super().__init__(recording)
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self.replay_instructions = replay_instructions
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self.instructions = instructions
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self.process_events = process_events
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self.action_history = []
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self.action_event_idx = 0
@@ -89,7 +89,7 @@ def get_next_action_event(
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window_event,
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action_events,
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self.action_history,
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self.replay_instructions,
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self.instructions,
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)
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if not action_event:
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raise StopIteration()
@@ -161,7 +161,7 @@ def generate_action_event(
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current_window_event: models.WindowEvent,
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recorded_actions: list[models.ActionEvent],
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replayed_actions: list[models.ActionEvent],
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replay_instructions: str,
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instructions: str,
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) -> models.ActionEvent:
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"""Modify the given ActionEvents according to the given replay instructions.
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@@ -176,7 +176,7 @@ def generate_action_event(
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recording
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replayed_actions (list[models.ActionEvent]): list of actions produced during
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current replay
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replay_instructions (str): proposed modifications in natural language
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instructions (str): proposed modifications in natural language
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instructions
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Returns:
@@ -195,7 +195,7 @@ def generate_action_event(
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current_window=current_window_dict,
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recorded_actions=recorded_action_dicts,
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replayed_actions=replayed_action_dicts,
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replay_instructions=replay_instructions,
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replay_instructions=instructions,
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)
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prompt_adapter = adapters.get_default_prompt_adapter()
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content = prompt_adapter.prompt(

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