AI/참고/instructor-main/docs/examples/using_decimals.md

title, description

title	description
Working with Decimal Types in Instructor	Learn how to use Python Decimal types for precise financial calculations and numeric data extraction with Instructor.

See Also

• Types - Working with different data types
• Fields - Customizing field validation
• Field Validation - Field-level validation patterns
• Validation - Core validation concepts

Using Decimals

Extract precise decimal values for financial calculations using Python's Decimal type.

from decimal import Decimal
from pydantic import BaseModel, field_validator
import instructor


class Receipt(BaseModel):
    item: str
    price: Decimal

    @field_validator('price', mode='before')
    @classmethod
    def parse_price(cls, v):
        if isinstance(v, str):
            return Decimal(v)
        return v


client = instructor.from_provider("openai/gpt-4.1-mini")

receipt = client.create(
    messages=[{"role": "user", "content": "Coffee costs $4.99"}],
    response_model=Receipt,
)

print(f"Item: {receipt.item}")
print(f"Price: {receipt.price}")  # Decimal('4.99')
print(f"Type: {type(receipt.price)}")  # <class 'decimal.Decimal'>

The field_validator ensures string values from LLM responses are properly converted to Decimal objects for precise financial calculations.