Working with something that behaves like List[Model] but is a Pydantic object.

[Mr-Ruben]

Forgive me it this has been resolved, and/or I didn't understand it properly.

A few days ago many open issues were closed just because there were pre-2025 and it sparked some research.

In particular,
#1146 (comment)
#1103

Disclaimer: I may not know what I am talking about.

Here is what I tested, and it works well, so far.

!pip install pydantic openai instructor

import pydantic
import openai
import instructor

# prompt: make notebook to print all outputs, not just the last one

from IPython.core.interactiveshell import InteractiveShell
InteractiveShell.ast_node_interactivity = "all"

# For OpenAI
from google.colab import userdata
OPENAI_API_KEY=userdata.get('OPENAI_API_KEY')

import instructor
from openai import OpenAI
from pydantic import BaseModel


# Create an instructor-patched client
client = instructor.from_openai(OpenAI(api_key=OPENAI_API_KEY
                                       #, base_url=
                                      ))

The key is here

from typing import TypeVar, Generic, List
from pydantic import RootModel, TypeAdapter, BaseModel


class Pet(BaseModel):
    name: str
    age: int

# ===== The key is here ==========

T = TypeVar("T")

class ListOfX(RootModel[List[T]], Generic[T]):
    def __iter__(self):
        return iter(self.root)

    def __getitem__(self, item):
        return self.root[item]

pets = [Pet(name="Dog", age=2), Pet(name="Cat", age=3)]

pets = TypeAdapter(ListOfX[Pet]).validate_python(pets)

for p in pets:
    print(p)
    p.model_dump()

# Because it is a class, you can add extra properties/attributes/etc
pets._hidden = True
pets._hidden

name='Dog' age=2
name='Cat' age=3



True

prompt="Give me the name and age of 5 pokemons"

# This fails with `KeyError: 'properties'`
# pets=client.chat.completions.create(
#     model="gpt-4o-mini",
#     response_model=ListOfX[Pet],
#     messages=[
#         {"role": "user", "content": prompt}
#     ],
# )

# But this does not fail
pets=client.chat.completions.create(
    model="gpt-4o-mini",
    response_model=List[Pet],
    messages=[
        {"role": "user", "content": prompt}
    ],
)

pets

for pet in pets:
    #print(pet.name, pet.age)
    print(pet)
    # check if it has .model_dump()
    if hasattr(pet, "model_dump"):
      pet.model_dump()

[Pet(name='Pikachu', age=3),
 Pet(name='Charmander', age=2),
 Pet(name='Bulbasaur', age=4),
 Pet(name='Squirtle', age=1),
 Pet(name='Eevee', age=5)]


name='Pikachu' age=3
{'name': 'Pikachu', 'age': 3}

name='Charmander' age=2
{'name': 'Charmander', 'age': 2}

name='Bulbasaur' age=4
{'name': 'Bulbasaur', 'age': 4}

name='Squirtle' age=1
{'name': 'Squirtle', 'age': 1}

name='Eevee' age=5
{'name': 'Eevee', 'age': 5}

The output of this IS an object but it looks just like List[Pets]

OR I am missing something.

pets_list_class=TypeAdapter(ListOfX[Pet]).validate_python(pets)

pets_list_class

if hasattr(pets_list_class, "model_dump"):
  pets_list_class.model_dump()

for pet in pets_list_class:
    print(pet)
    # check if it has .model_dump()
    if hasattr(pet, "model_dump"):
      pet.model_dump()

ListOfX[Pet](root=[Pet(name='Pikachu', age=3), Pet(name='Charmander', age=2), Pet(name='Bulbasaur', age=4), Pet(name='Squirtle', age=1), Pet(name='Eevee', age=5)])


[{'name': 'Pikachu', 'age': 3},
 {'name': 'Charmander', 'age': 2},
 {'name': 'Bulbasaur', 'age': 4},
 {'name': 'Squirtle', 'age': 1},
 {'name': 'Eevee', 'age': 5}]

name='Pikachu' age=3
{'name': 'Pikachu', 'age': 3}

name='Charmander' age=2
{'name': 'Charmander', 'age': 2}

name='Bulbasaur' age=4
{'name': 'Bulbasaur', 'age': 4}

name='Squirtle' age=1
{'name': 'Squirtle', 'age': 1}

name='Eevee' age=5
{'name': 'Eevee', 'age': 5}