66 lines
1.7 KiB
Python
66 lines
1.7 KiB
Python
from pydantic import BaseModel, model_validator
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from openai import OpenAI
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import instructor
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client = instructor.from_openai(
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client=OpenAI(),
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mode=instructor.Mode.TOOLS,
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)
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class Item(BaseModel):
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name: str
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price: float
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quantity: int
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class Receipt(BaseModel):
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items: list[Item]
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total: float
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@model_validator(mode="after")
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def check_total(cls, values: "Receipt"):
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items = values.items
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total = values.total
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calculated_total = sum(item.price * item.quantity for item in items)
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if calculated_total != total:
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raise ValueError(
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f"Total {total} does not match the sum of item prices {calculated_total}"
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)
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return values
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def extract(url: str) -> Receipt:
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return client.chat.completions.create(
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model="gpt-4o",
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max_tokens=4000,
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response_model=Receipt,
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messages=[
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{
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"role": "user",
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"content": [
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{
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"type": "image_url",
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"image_url": {"url": url},
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},
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{
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"type": "text",
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"text": "Analyze the image and return the items in the receipt and the total amount.",
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},
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],
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}
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],
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)
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# URLs of images containing receipts. Exhibits the use of the model validator to check the total amount.
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urls = [
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"https://templates.mediamodifier.com/645124ff36ed2f5227cbf871/supermarket-receipt-template.jpg",
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"https://ocr.space/Content/Images/receipt-ocr-original.jpg",
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]
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for url in urls:
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receipt = extract(url)
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print(receipt)
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