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40 lines
1.1 KiB
Python
40 lines
1.1 KiB
Python
from typing import Union
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from utils import llm_call
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from promptflow._core.tool import InputSetting
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from promptflow.connections import AzureOpenAIConnection, OpenAIConnection
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from promptflow.core import tool
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@tool(
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input_settings={
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"deployment_name": InputSetting(
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enabled_by="connection",
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enabled_by_type=["AzureOpenAIConnection"],
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capabilities={"completion": False, "chat_completion": True, "embeddings": False},
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),
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"model": InputSetting(enabled_by="connection", enabled_by_type=["OpenAIConnection"]),
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}
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)
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def generate_question(
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connection: Union[OpenAIConnection, AzureOpenAIConnection],
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generate_question_prompt: str,
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deployment_name: str = "",
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model: str = "",
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context: str = None,
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temperature: float = 0.2,
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):
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"""
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Generates a question based on the given context.
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Returns:
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str: The generated seed question.
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"""
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# text chunk is not valid, just skip test data gen.
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if not context:
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return ""
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seed_question = llm_call(connection, model, deployment_name, generate_question_prompt, temperature=temperature)
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return seed_question
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