openai[patch]: reduce tested constraints on strict schema adherence for Responses API (#31290)

Scheduled testing started failing today because the Responses API
stopped raising `BadRequestError` for a schema that was previously
invalid when `strict=True`.

Although docs still say that [some type-specific keywords are not yet
supported](https://platform.openai.com/docs/guides/structured-outputs#some-type-specific-keywords-are-not-yet-supported)
(including `minimum` and `maximum` for numbers), the below appears to
run and correctly respect the constraints:
```python
import json
import openai

maximums = list(range(1, 11))
arg_values = []
for maximum in maximums:

    tool = {
        "type": "function",
        "name": "magic_function",
        "description": "Applies a magic function to an input.",
        "parameters": {
            "properties": {
                "input": {"maximum": maximum, "minimum": 0, "type": "integer"}
            },
            "required": ["input"],
            "type": "object",
            "additionalProperties": False
        },
        "strict": True
    }
    
    client = openai.OpenAI()
    
    response = client.responses.create(
        model="gpt-4.1",
        input=[{"role": "user", "content": "What is the value of magic_function(3)? Use the tool."}],
        tools=[tool],
    )
    function_call = next(item for item in response.output if item.type == "function_call")
    args = json.loads(function_call.arguments)
    arg_values.append(args["input"])


print(maximums)
print(arg_values)

# [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
# [1, 2, 3, 3, 3, 3, 3, 3, 3, 3]
```
Until yesterday this raised BadRequestError.

The same is not true of Chat Completions, which appears to still raise
BadRequestError
```python
tool = {
    "type": "function",
    "function": {
        "name": "magic_function",
        "description": "Applies a magic function to an input.",
        "parameters": {
            "properties": {
                "input": {"maximum": 5, "minimum": 0, "type": "integer"}
            },
            "required": ["input"],
            "type": "object",
            "additionalProperties": False
        },
        "strict": True
    }
}

response = client.chat.completions.create(
    model="gpt-4.1",
    messages=[{"role": "user", "content": "What is the value of magic_function(3)? Use the tool."}],
    tools=[tool],
)
response  # raises BadRequestError
```

Here we update tests accordingly.

libs/partners/openai/tests/integration_tests/chat_models/test_base.py

@@ -680,8 +680,7 @@ def test_image_token_counting_png() -> None:
     assert expected == actual
 
 
-@pytest.mark.parametrize("use_responses_api", [False, True])
-def test_tool_calling_strict(use_responses_api: bool) -> None:
+def test_tool_calling_strict() -> None:
     """Test tool calling with strict=True."""
 
     class magic_function(BaseModel):
@@ -689,9 +688,7 @@ def test_tool_calling_strict(use_responses_api: bool) -> None:
 
         input: int
 
-    model = ChatOpenAI(
-        model="gpt-4o", temperature=0, use_responses_api=use_responses_api
-    )
+    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.
@@ -720,6 +717,48 @@ def test_tool_calling_strict(use_responses_api: bool) -> None:
         next(model_with_invalid_tool_schema.stream(query))
 
 
+def test_tool_calling_strict_responses() -> None:
+    """Test tool calling with strict=True.
+
+    Responses API appears to have fewer constraints on schema when strict=True.
+    """
+
+    class magic_function_notrequired_arg(BaseModel):
+        """Applies a magic function to an input."""
+
+        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)
+    # Having a not-required argument in the schema remains invalid.
+    model_with_invalid_tool_schema = model.bind_tools(
+        [magic_function_notrequired_arg], 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))
+
+
 @pytest.mark.parametrize("use_responses_api", [False, True])
 @pytest.mark.parametrize(
     ("model", "method"),