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Jason
42 lines
1016 B
Python
42 lines
1016 B
Python
from typing import List
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import enum
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import openai
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from pydantic import BaseModel
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from instructor import patch
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patch()
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# Define new Enum class for multiple labels
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class MultiLabels(str, enum.Enum):
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BILLING = "billing"
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GENERAL_QUERY = "general_query"
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HARDWARE = "hardware"
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# Adjust the prediction model to accommodate a list of labels
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class MultiClassPrediction(BaseModel):
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predicted_labels: List[MultiLabels]
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# Modify the classify function
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def multi_classify(data: str) -> MultiClassPrediction:
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return openai.ChatCompletion.create(
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model="gpt-3.5-turbo-0613",
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response_model=MultiClassPrediction,
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messages=[
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{
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"role": "user",
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"content": f"Classify the following support ticket: {data}",
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},
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],
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) # type: ignore
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# Example using a support ticket
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ticket = (
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"My account is locked and I can't access my billing info. Phone is also broken."
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)
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prediction = multi_classify(ticket)
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print(prediction)
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