instructor/docs/concepts/patching.md

Patching

Instructor enhances client functionality with three new keywords for backwards compatibility. This allows use of the enhanced client as usual, with structured output benefits.

• response_model: Defines the response type for chat.completions.create.
• max_retries: Determines retry attempts for failed chat.completions.create validations.
• validation_context: Provides extra context to the validation process.

There are three methods for structured output:

1. Function Calling: The primary method. Use this for stability and testing.
2. Tool Calling: Useful in specific scenarios; lacks the reasking feature of OpenAI's tool calling API.
3. JSON Mode: Offers closer adherence to JSON but with more potential validation errors. Suitable for specific non-function calling clients.

Function Calling

from openai import OpenAI
import instructor

client = instructor.patch(OpenAI())

Tool Calling

import instructor
from instructor import Mode

client = instructor.patch(OpenAI(), mode=Mode.TOOL_CALL)

JSON Mode

import instructor
from instructor import Mode
from openai import OpenAI

client = instructor.patch(OpenAI(), mode=Mode.JSON)

Schema Integration

In JSON Mode, the schema is part of the system message:

import instructor
from openai import OpenAI

client = instructor.patch(OpenAI())

response = client.chat.completions.create(
    model="gpt-3.5-turbo-1106",
    response_format={"type": "json_object"},
    messages=[
        {
            "role": "system",
            "content": f"Match your response to this json_schema: \n{UserExtract.model_json_schema()['properties']}",
        },
        {
            "role": "user",
            "content": "Extract jason is 25 years old",
        },
    ],
)
user = UserExtract.from_response(response, mode=Mode.JSON)
assert user.name.lower() == "jason"
assert user.age == 25