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chore: import upstream snapshot with attribution
2026-07-13 13:36:38 +08:00

165 lines
5.1 KiB
Python

from itertools import product
from pydantic import BaseModel, field_validator
from openai.types.chat import ChatCompletion
from typing_extensions import TypedDict
import pytest
import instructor
from .util import models, modes
class UserExtract(BaseModel):
name: str
age: int
class UserExtractTypedDict(TypedDict):
name: str
age: int
@pytest.mark.parametrize("model, mode", product(models, modes))
def test_typed_dict(model, mode, client):
if mode in {
instructor.Mode.RESPONSES_TOOLS,
instructor.Mode.RESPONSES_TOOLS_WITH_INBUILT_TOOLS,
}:
pytest.skip("Avoiding testing responses tools with openai")
client = instructor.patch(client, mode=mode)
model = client.chat.completions.create(
model=model,
response_model=UserExtractTypedDict,
max_retries=2,
messages=[
{"role": "user", "content": "Extract jason is 25 years old"},
],
)
assert isinstance(model, BaseModel), "Should be instance of a pydantic model"
assert model.name.lower() == "jason"
assert model.age == 25
assert hasattr(model, "_raw_response"), (
"The raw response should be available from OpenAI"
)
@pytest.mark.parametrize("model, mode", product(models, modes))
def test_runmodel(model, mode, client):
if mode in {
instructor.Mode.RESPONSES_TOOLS,
instructor.Mode.RESPONSES_TOOLS_WITH_INBUILT_TOOLS,
}:
pytest.skip("Avoiding testing responses tools with openai")
client = instructor.patch(client, mode=mode)
model = client.chat.completions.create(
model=model,
response_model=UserExtract,
max_retries=2,
messages=[
{"role": "user", "content": "Extract jason is 25 years old"},
],
)
assert isinstance(model, UserExtract), "Should be instance of UserExtract"
assert model.name.lower() == "jason"
assert model.age == 25
assert hasattr(model, "_raw_response"), (
"The raw response should be available from OpenAI"
)
ChatCompletion(**model._raw_response.model_dump())
@pytest.mark.parametrize("model, mode", product(models, modes))
@pytest.mark.asyncio
async def test_runmodel_async(model, mode, aclient):
if mode in {
instructor.Mode.RESPONSES_TOOLS,
instructor.Mode.RESPONSES_TOOLS_WITH_INBUILT_TOOLS,
}:
pytest.skip("Avoiding testing responses tools with openai")
aclient = instructor.patch(aclient, mode=mode)
model = await aclient.chat.completions.create(
model=model,
response_model=UserExtract,
max_retries=2,
messages=[
{"role": "user", "content": "Extract jason is 25 years old"},
],
)
assert isinstance(model, UserExtract), "Should be instance of UserExtract"
assert model.name.lower() == "jason"
assert model.age == 25
assert hasattr(model, "_raw_response"), (
"The raw response should be available from OpenAI"
)
ChatCompletion(**model._raw_response.model_dump())
class UserExtractValidated(BaseModel):
name: str
age: int
@field_validator("name")
@classmethod
def validate_name(cls, v):
if v.upper() != v:
raise ValueError(
"Name should have all letters in uppercase. Make sure to use the `uppercase` form of the name"
)
return v
@pytest.mark.parametrize("model, mode", product(models, modes))
def test_runmodel_validator(model, mode, client):
if mode in {
instructor.Mode.RESPONSES_TOOLS,
instructor.Mode.RESPONSES_TOOLS_WITH_INBUILT_TOOLS,
}:
pytest.skip("Avoiding testing responses tools with openai")
client = instructor.patch(client, mode=mode)
model = client.chat.completions.create(
model=model,
response_model=UserExtractValidated,
max_retries=2,
messages=[
{"role": "user", "content": "Extract jason is 25 years old"},
],
)
assert isinstance(model, UserExtractValidated), "Should be instance of UserExtract"
assert model.name == "JASON"
assert hasattr(model, "_raw_response"), (
"The raw response should be available from OpenAI"
)
ChatCompletion(**model._raw_response.model_dump())
@pytest.mark.parametrize("model, mode", product(models, modes))
@pytest.mark.asyncio
async def test_runmodel_async_validator(model, mode, aclient):
if mode in {
instructor.Mode.RESPONSES_TOOLS,
instructor.Mode.RESPONSES_TOOLS_WITH_INBUILT_TOOLS,
}:
pytest.skip("Avoiding testing responses tools with openai")
aclient = instructor.patch(aclient, mode=mode)
model = await aclient.chat.completions.create(
model=model,
response_model=UserExtractValidated,
max_retries=2,
messages=[
{"role": "user", "content": "Extract jason is 25 years old"},
],
)
assert isinstance(model, UserExtractValidated), "Should be instance of UserExtract"
assert model.name == "JASON"
assert hasattr(model, "_raw_response"), (
"The raw response should be available from OpenAI"
)
ChatCompletion(**model._raw_response.model_dump())