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openai[patch]: update tests for strict schemas (#31306)

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Following recent [changes](https://platform.openai.com/docs/changelog).
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ccurme 2025-05-21 18:06:17 -04:00 committed by GitHub
parent 53d6286539
commit beacedd6b3
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1 changed files with 9 additions and 69 deletions
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78
libs/partners/openai/tests/integration_tests/chat_models/test_base.py
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@ -23,9 +23,9 @@ from langchain_core.messages import (
)
from langchain_core.outputs import ChatGeneration, ChatResult, LLMResult
from langchain_core.prompts import ChatPromptTemplate
from langchain_tests.integration_tests.chat_models import _validate_tool_call_message
from langchain_tests.integration_tests.chat_models import (
magic_function as invalid_magic_function,
_validate_tool_call_message,
magic_function,
)
from pydantic import BaseModel, Field
@ -680,44 +680,8 @@ def test_image_token_counting_png() -> None:
assert expected == actual
def test_tool_calling_strict() -> None:
"""Test tool calling with strict=True."""
class magic_function(BaseModel):
"""Applies a magic function to an input."""
input: int
model = ChatOpenAI(model="gpt-4.1", temperature=0)
model_with_tools = model.bind_tools([magic_function], strict=True)
# invalid_magic_function adds metadata to schema that isn't supported by OpenAI.
model_with_invalid_tool_schema = model.bind_tools(
[invalid_magic_function], strict=True
)
# Test invoke
query = "What is the value of magic_function(3)? Use the tool."
response = model_with_tools.invoke(query)
_validate_tool_call_message(response)
# Test invalid tool schema
with pytest.raises(openai.BadRequestError):
model_with_invalid_tool_schema.invoke(query)
# Test stream
full: Optional[BaseMessageChunk] = None
for chunk in model_with_tools.stream(query):
full = chunk if full is None else full + chunk # type: ignore
assert isinstance(full, AIMessage)
_validate_tool_call_message(full)
# Test invalid tool schema
with pytest.raises(openai.BadRequestError):
next(model_with_invalid_tool_schema.stream(query))
def test_tool_calling_strict_responses() -> None:
@pytest.mark.parametrize("use_responses_api", [False, True])
def test_tool_calling_strict(use_responses_api: bool) -> None:
"""Test tool calling with strict=True.
Responses API appears to have fewer constraints on schema when strict=True.
@ -728,11 +692,11 @@ def test_tool_calling_strict_responses() -> None:
input: Optional[int] = Field(default=None)
model = ChatOpenAI(model="gpt-4.1", temperature=0, use_responses_api=True)
# invalid_magic_function adds metadata to schema that as of 2025-05-20 appears
# supported by the Responses API, but not Chat Completions. We expect tool calls
# from this schema to be valid.
model_with_tools = model.bind_tools([invalid_magic_function], strict=True)
model = ChatOpenAI(
model="gpt-4.1", temperature=0, use_responses_api=use_responses_api
)
# N.B. magic_function adds metadata to schema (min/max for number fields)
model_with_tools = model.bind_tools([magic_function], strict=True)
# Having a not-required argument in the schema remains invalid.
model_with_invalid_tool_schema = model.bind_tools(
[magic_function_notrequired_arg], strict=True
@ -803,30 +767,6 @@ def test_structured_output_strict(
assert isinstance(chunk, dict) # for mypy
assert set(chunk.keys()) == {"setup", "punchline"}
# Invalid schema with optional fields:
class InvalidJoke(BaseModelProper):
"""Joke to tell user."""
setup: str = FieldProper(description="question to set up a joke")
# Invalid field, can't have default value.
punchline: str = FieldProper(
default="foo", description="answer to resolve the joke"
)
chat = llm.with_structured_output(InvalidJoke, method=method, strict=True)
with pytest.raises(openai.BadRequestError):
chat.invoke("Tell me a joke about cats.")
with pytest.raises(openai.BadRequestError):
next(chat.stream("Tell me a joke about cats."))
chat = llm.with_structured_output(
InvalidJoke.model_json_schema(), method=method, strict=True
)
with pytest.raises(openai.BadRequestError):
chat.invoke("Tell me a joke about cats.")
with pytest.raises(openai.BadRequestError):
next(chat.stream("Tell me a joke about cats."))
@pytest.mark.parametrize("use_responses_api", [False, True])
@pytest.mark.parametrize(("model", "method"), [("gpt-4o-2024-08-06", "json_schema")])