foundationagents--openmanus
Kaeyoung
41 行
1.6 KiB
Python
41 行
1.6 KiB
Python
from pydantic import Field
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from app.llm import LLM
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from app.prompt.validator import TEXT_VALIDATION_PROMPT, USER_CONTENT
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from app.tool.base import BaseTool
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_VALIDATE_DESCRIPTION = """
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This tool evaluates the quality and completeness of a subtask result against a set of predefined criteria.
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It checks whether the result fully satisfies task requirements, maintains high quality in terms of clarity, accuracy, and formatting,
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and determines whether improvements have been made in comparison to prior versions.
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If the result is satisfactory or improvements are minimal, it returns "The step result has already reached the requirement.".
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Otherwise, it provides detailed feedback and a revised version of the result that meets all requirements and is ready for downstream use.
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"""
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class Validator(BaseTool):
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llm: LLM = Field(default_factory=LLM, description="Language model instance")
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name: str = "validator"
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description: str = _VALIDATE_DESCRIPTION
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parameters: dict = {}
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async def validate(self, request: str, history: str):
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"""Abstract method for result validate logic.
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Args:
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step_result: The result string to validate.
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"""
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system_content = TEXT_VALIDATION_PROMPT
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user_content = USER_CONTENT.format(request=request, history=history)
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feedback = await self.llm.ask(
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messages=[{"role": "user", "content": user_content}],
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system_msgs=[{"role": "system", "content": system_content}],
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)
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return feedback
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async def execute(self, request: str, history: str) -> str:
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"""Finish the current execution"""
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return await self.validate(request, history)
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