Basic Extraction Patterns

Simple Object Extraction

Here we extract basic objects from text with Instructor

Import the necessary libraries

from pydantic import BaseModel, Field
import instructor
from openai import OpenAI

Define the Person class with Pydantic

class Person(BaseModel):
    """Extract person information from text."""
    name: str = Field(description="The person's full name")
    age: int = Field(description="The person's age in years")
    occupation: str = Field(description="The person's current job title or role")

Patch the OpenAI client with Instructor

client = instructor.from_openai(OpenAI())

Extract the data from text

person = client.chat.completions.create(
    model="gpt-3.5-turbo",
    response_model=Person,
    messages=[
        {"role": "user", "content": "John Doe is a 30-year-old software engineer."}
    ]
)

Print the extracted structured data
Output:
Name: John Doe
Age: 30
Occupation: software engineer

print(f"Name: {person.name}")
print(f"Age: {person.age}")
print(f"Occupation: {person.occupation}")

Running the Example

First, install Instructor and any dependencies

$ pip install instructor pydantic

Run the Python script

$ python simple-object.py

Further Information

Documentation link 1