JSON structured Output using Funcchain with OenAI

Example

See openai_json_mode.py

This example will showcase how funcchain enables OpenAI to output even the type int as JSON.

This example demonstrates using the funcchain library and pydantic to create a FruitSalad model, sum its contents, and output the total in a Result model as an integer.

Full Code Example

from funcchain import chain
from pydantic import BaseModel

class FruitSalad(BaseModel):
    bananas: int = 0
    apples: int = 0

def sum_fruits(fruit_salad: FruitSalad) -> int:
    """
    Sum the number of fruits in a fruit salad.
    """
    return chain()

if __name__ == "__main__":
    fruit_salad = FruitSalad(bananas=3, apples=5)
    assert sum_fruits(fruit_salad) == 8

Instructions

Step-by-step

Necessary Imports

funcchain for chaining functionality, and pydantic for the data models.

from funcchain import chain, settings
from pydantic import BaseModel

Defining the Data Models

We define two Pydantic models: FruitSalad with integer fields for the number of bananas and apples. Of course feel free to change those classes according to your needs but use of pydantic is required.

class FruitSalad(BaseModel):
    bananas: int = 0
    apples: int = 0

Summing Function

The sum_fruits function is intended to take a FruitSalad object and use chain() for solving this task with an LLM. The result is returned then returned as integer.

def sum_fruits(fruit_salad: FruitSalad) -> int:
    """
    Sum the number of fruits in a fruit salad.
    """
    return chain()

Execution Block

fruit_salad = FruitSalad(bananas=3, apples=5)
assert sum_fruits(fruit_salad) == 8

In the primary execution section of the script, we instantiate a FruitSalad object with predefined quantities of bananas and apples. We then verify that the sum_fruits function accurately calculates the total count of fruits, which should be 8 in this case.