chore(internal): bump pydantic dependency

requirements-dev.lock

@@ -24,7 +24,7 @@ attrs==23.1.0
 azure-core==1.30.1
     # via azure-identity
 azure-identity==1.15.0
-black==24.4.0
+black==24.4.2
     # via inline-snapshot
 certifi==2023.7.22
     # via httpcore
@@ -39,7 +39,7 @@ click==8.1.7
     # via inline-snapshot
 colorlog==6.7.0
     # via nox
-cryptography==42.0.5
+cryptography==42.0.7
     # via azure-identity
     # via msal
     # via pyjwt
@@ -111,9 +111,9 @@ py==1.11.0
     # via pytest
 pycparser==2.22
     # via cffi
-pydantic==2.4.2
+pydantic==2.7.1
     # via openai
-pydantic-core==2.10.1
+pydantic-core==2.18.2
     # via pydantic
 pyjwt==2.8.0
     # via msal

requirements.lock

@@ -33,13 +33,13 @@ numpy==1.26.4
     # via openai
     # via pandas
     # via pandas-stubs
-pandas==2.2.1
+pandas==2.2.2
     # via openai
 pandas-stubs==2.2.1.240316
     # via openai
-pydantic==2.4.2
+pydantic==2.7.1
     # via openai
-pydantic-core==2.10.1
+pydantic-core==2.18.2
     # via pydantic
 python-dateutil==2.9.0.post0
     # via pandas
@@ -53,7 +53,7 @@ sniffio==1.3.0
     # via openai
 tqdm==4.66.1
     # via openai
-types-pytz==2024.1.0.20240203
+types-pytz==2024.1.0.20240417
     # via pandas-stubs
 typing-extensions==4.8.0
     # via openai

src/openai/_models.py

@@ -62,7 +62,7 @@
 from ._constants import RAW_RESPONSE_HEADER
 
 if TYPE_CHECKING:
-    from pydantic_core.core_schema import ModelField, ModelFieldsSchema
+    from pydantic_core.core_schema import ModelField, LiteralSchema, ModelFieldsSchema
 
 __all__ = ["BaseModel", "GenericModel"]
 
@@ -251,7 +251,9 @@ def model_dump(
             exclude_defaults: bool = False,
             exclude_none: bool = False,
             round_trip: bool = False,
-            warnings: bool = True,
+            warnings: bool | Literal["none", "warn", "error"] = True,
+            context: dict[str, Any] | None = None,
+            serialize_as_any: bool = False,
         ) -> dict[str, Any]:
             """Usage docs: https://docs.pydantic.dev/2.4/concepts/serialization/#modelmodel_dump
 
@@ -279,6 +281,10 @@ def model_dump(
                 raise ValueError("round_trip is only supported in Pydantic v2")
             if warnings != True:
                 raise ValueError("warnings is only supported in Pydantic v2")
+            if context is not None:
+                raise ValueError("context is only supported in Pydantic v2")
+            if serialize_as_any != False:
+                raise ValueError("serialize_as_any is only supported in Pydantic v2")
             return super().dict(  # pyright: ignore[reportDeprecated]
                 include=include,
                 exclude=exclude,
@@ -300,7 +306,9 @@ def model_dump_json(
             exclude_defaults: bool = False,
             exclude_none: bool = False,
             round_trip: bool = False,
-            warnings: bool = True,
+            warnings: bool | Literal["none", "warn", "error"] = True,
+            context: dict[str, Any] | None = None,
+            serialize_as_any: bool = False,
         ) -> str:
             """Usage docs: https://docs.pydantic.dev/2.4/concepts/serialization/#modelmodel_dump_json
 
@@ -324,6 +332,10 @@ def model_dump_json(
                 raise ValueError("round_trip is only supported in Pydantic v2")
             if warnings != True:
                 raise ValueError("warnings is only supported in Pydantic v2")
+            if context is not None:
+                raise ValueError("context is only supported in Pydantic v2")
+            if serialize_as_any != False:
+                raise ValueError("serialize_as_any is only supported in Pydantic v2")
             return super().json(  # type: ignore[reportDeprecated]
                 indent=indent,
                 include=include,
@@ -550,7 +562,7 @@ def _build_discriminated_union_meta(*, union: type, meta_annotations: tuple[Any,
                 field_schema = field["schema"]
 
                 if field_schema["type"] == "literal":
-                    for entry in field_schema["expected"]:
+                    for entry in cast("LiteralSchema", field_schema)["expected"]:
                         if isinstance(entry, str):
                             mapping[entry] = variant
             else:

tests/test_models.py

@@ -31,7 +31,7 @@ class NestedModel(BaseModel):
 
     # mismatched types
     m = NestedModel.construct(nested="hello!")
-    assert m.nested == "hello!"
+    assert cast(Any, m.nested) == "hello!"
 
 
 def test_optional_nested_model() -> None:
@@ -48,7 +48,7 @@ class NestedModel(BaseModel):
     # mismatched types
     m3 = NestedModel.construct(nested={"foo"})
     assert isinstance(cast(Any, m3.nested), set)
-    assert m3.nested == {"foo"}
+    assert cast(Any, m3.nested) == {"foo"}
 
 
 def test_list_nested_model() -> None:
@@ -323,7 +323,7 @@ class Model(BaseModel):
     assert len(m.items) == 2
     assert isinstance(m.items[0], Submodel1)
     assert m.items[0].level == -1
-    assert m.items[1] == 156
+    assert cast(Any, m.items[1]) == 156
 
 
 def test_union_of_lists() -> None:
@@ -355,7 +355,7 @@ class Model(BaseModel):
     assert len(m.items) == 2
     assert isinstance(m.items[0], SubModel1)
     assert m.items[0].level == -1
-    assert m.items[1] == 156
+    assert cast(Any, m.items[1]) == 156
 
 
 def test_dict_of_union() -> None:

tests/test_transform.py

@@ -260,20 +260,22 @@ class MyModel(BaseModel):
 @parametrize
 @pytest.mark.asyncio
 async def test_pydantic_model_to_dictionary(use_async: bool) -> None:
-    assert await transform(MyModel(foo="hi!"), Any, use_async) == {"foo": "hi!"}
-    assert await transform(MyModel.construct(foo="hi!"), Any, use_async) == {"foo": "hi!"}
+    assert cast(Any, await transform(MyModel(foo="hi!"), Any, use_async)) == {"foo": "hi!"}
+    assert cast(Any, await transform(MyModel.construct(foo="hi!"), Any, use_async)) == {"foo": "hi!"}
 
 
 @parametrize
 @pytest.mark.asyncio
 async def test_pydantic_empty_model(use_async: bool) -> None:
-    assert await transform(MyModel.construct(), Any, use_async) == {}
+    assert cast(Any, await transform(MyModel.construct(), Any, use_async)) == {}
 
 
 @parametrize
 @pytest.mark.asyncio
 async def test_pydantic_unknown_field(use_async: bool) -> None:
-    assert await transform(MyModel.construct(my_untyped_field=True), Any, use_async) == {"my_untyped_field": True}
+    assert cast(Any, await transform(MyModel.construct(my_untyped_field=True), Any, use_async)) == {
+        "my_untyped_field": True
+    }
 
 
 @parametrize
@@ -285,7 +287,7 @@ async def test_pydantic_mismatched_types(use_async: bool) -> None:
             params = await transform(model, Any, use_async)
     else:
         params = await transform(model, Any, use_async)
-    assert params == {"foo": True}
+    assert cast(Any, params) == {"foo": True}
 
 
 @parametrize
@@ -297,7 +299,7 @@ async def test_pydantic_mismatched_object_type(use_async: bool) -> None:
             params = await transform(model, Any, use_async)
     else:
         params = await transform(model, Any, use_async)
-    assert params == {"foo": {"hello": "world"}}
+    assert cast(Any, params) == {"foo": {"hello": "world"}}
 
 
 class ModelNestedObjects(BaseModel):
@@ -309,7 +311,7 @@ class ModelNestedObjects(BaseModel):
 async def test_pydantic_nested_objects(use_async: bool) -> None:
     model = ModelNestedObjects.construct(nested={"foo": "stainless"})
     assert isinstance(model.nested, MyModel)
-    assert await transform(model, Any, use_async) == {"nested": {"foo": "stainless"}}
+    assert cast(Any, await transform(model, Any, use_async)) == {"nested": {"foo": "stainless"}}
 
 
 class ModelWithDefaultField(BaseModel):
@@ -325,19 +327,19 @@ async def test_pydantic_default_field(use_async: bool) -> None:
     model = ModelWithDefaultField.construct()
     assert model.with_none_default is None
     assert model.with_str_default == "foo"
-    assert await transform(model, Any, use_async) == {}
+    assert cast(Any, await transform(model, Any, use_async)) == {}
 
     # should be included when the default value is explicitly given
     model = ModelWithDefaultField.construct(with_none_default=None, with_str_default="foo")
     assert model.with_none_default is None
     assert model.with_str_default == "foo"
-    assert await transform(model, Any, use_async) == {"with_none_default": None, "with_str_default": "foo"}
+    assert cast(Any, await transform(model, Any, use_async)) == {"with_none_default": None, "with_str_default": "foo"}
 
     # should be included when a non-default value is explicitly given
     model = ModelWithDefaultField.construct(with_none_default="bar", with_str_default="baz")
     assert model.with_none_default == "bar"
     assert model.with_str_default == "baz"
-    assert await transform(model, Any, use_async) == {"with_none_default": "bar", "with_str_default": "baz"}
+    assert cast(Any, await transform(model, Any, use_async)) == {"with_none_default": "bar", "with_str_default": "baz"}
 
 
 class TypedDictIterableUnion(TypedDict):