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48 lines
2.0 KiB
Python
48 lines
2.0 KiB
Python
from utils import ValidateObj, ValidationResult
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from promptflow.core import tool
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# The inputs section will change based on the arguments of the tool function, after you save the code
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# Adding type to arguments and return value will help the system show the types properly
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# Please update the function name/signature per need
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@tool
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def my_python_tool(
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text_chunk: str,
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text_chunk_validation_res: ValidationResult = None,
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validate_question_output: dict = None,
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validate_suggested_answer_output: dict = None,
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) -> dict:
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question_validation_res = validate_question_output["validation_res"]
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generated_suggested_answer = validate_suggested_answer_output["suggested_answer"]
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suggested_answer_validation_res = validate_suggested_answer_output["validation_res"]
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is_generation_success = generated_suggested_answer != ""
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is_text_chunk_valid = text_chunk_validation_res["pass_validation"] if text_chunk_validation_res else None
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is_seed_question_valid = question_validation_res["pass_validation"] if question_validation_res else None
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is_suggested_answer_valid = (
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suggested_answer_validation_res["pass_validation"] if suggested_answer_validation_res else None
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)
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failed_step = ""
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if not is_generation_success:
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if is_text_chunk_valid is False:
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failed_step = ValidateObj.TEXT_CHUNK
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elif is_seed_question_valid is False:
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failed_step = ValidateObj.QUESTION
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elif is_suggested_answer_valid is False:
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failed_step = ValidateObj.SUGGESTED_ANSWER
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return {
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# TODO: support more question types like multi-context etc.
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# "question_type": question_type,
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"text_chunk": text_chunk,
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"validation_summary": {"success": is_generation_success, "failed_step": failed_step},
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"validation_details": {
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ValidateObj.TEXT_CHUNK: text_chunk_validation_res,
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ValidateObj.QUESTION: question_validation_res,
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ValidateObj.SUGGESTED_ANSWER: suggested_answer_validation_res,
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},
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}
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