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from typing import Any, Optional, Tuple
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from uuid import uuid4
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from .schemas import OpenAIFunctionToolSchema
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class BaseTool:
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"""Base class for tools.
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A tool should support the following methods:
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- `to_openai_function_tool_schema`: return the tool schema in OpenAI format.
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- `create`: create a tool instance for a trajectory.
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- `execute`: execute the tool.
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- `calc_reward`: calculate the reward respect to tool state.
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- `release`: release the tool instance.
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"""
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def __init__(self, config: dict, tool_schema: OpenAIFunctionToolSchema):
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self.config = config
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self.name = tool_schema.function.name
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self.tool_schema = tool_schema
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def get_openai_tool_schema(self) -> OpenAIFunctionToolSchema:
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return self.tool_schema
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async def create(self, instance_id: Optional[str] = None, **kwargs) -> str:
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"""Create a tool instance.
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Args:
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instance_id: The instance id of the tool.
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Returns:
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The instance id of the tool.
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"""
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if instance_id is None:
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return str(uuid4())
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else:
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return instance_id
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async def execute(self, instance_id: str, parameters: dict[str, Any], **kwargs) -> Tuple[str, float, dict]:
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"""Execute the tool.
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Args:
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instance_id: The instance id of the tool.
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parameters: The json string of the parameters of the tool.
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Returns: tool_response, tool_reward_score, tool_metrics
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tool_response: The response str of the tool.
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tool_reward_score: The step reward score of the tool.
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tool_metrics: The metrics of the tool.
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"""
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return "Updated the tool state.", 0.0, {}
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async def calc_reward(self, instance_id: str, **kwargs) -> float:
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"""Calculate the reward of the tool.
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Args:
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instance_id: The instance id of the tool.
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Returns:
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The reward of the tool.
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"""
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return 0.0
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async def release(self, instance_id: str, **kwargs) -> None:
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"""Release the tool instance.
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Args:
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instance_id: The instance id of the tool.
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"""
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pass
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