add to standard tests and override for Azure legacy tests

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

@@ -1,7 +1,7 @@
 """Standard LangChain interface tests"""
 
 import os
-from typing import Type
+from typing import Optional, Type
 
 import pytest
 from langchain_core.language_models import BaseChatModel
@@ -55,6 +55,10 @@ def chat_model_params(self) -> dict:
             "azure_endpoint": OPENAI_API_BASE,
         }
 
+    @property
+    def structured_output_method(self) -> Optional[str]:
+        return "function_calling"
+
     @pytest.mark.xfail(reason="Not yet supported.")
     def test_usage_metadata_streaming(self, model: BaseChatModel) -> None:
         super().test_usage_metadata_streaming(model)

libs/standard-tests/langchain_tests/integration_tests/chat_models.py

@@ -1,6 +1,6 @@
 import base64
 import json
-from typing import List, Optional, cast
+from typing import Any, List, Optional, cast
 
 import httpx
 import pytest
@@ -191,6 +191,20 @@ def tool_choice_value(self) -> Optional[str]:
             def has_structured_output(self) -> bool:
                 return True
 
+    .. dropdown:: structured_output_method
+
+        Optional string property that can be used to override the default ``method``
+        parameter for ``with_structured_output``. Useful for testing different
+        models.
+
+        Example:
+
+        .. code-block:: python
+
+            @property
+            def structured_output_method(self) -> Optional[str]:
+                return "function_calling"
+
     .. dropdown:: supports_json_mode
 
         Boolean property indicating whether the chat model supports JSON mode in
@@ -1126,20 +1140,21 @@ def has_tool_calling(self) -> bool:
         if not self.has_tool_calling:
             pytest.skip("Test requires tool calling.")
 
+        kwargs: dict[str, Any] = {}
+        if self.structured_output_method:
+            kwargs["method"] = self.structured_output_method
+
         Joke = _get_joke_class()
         # Pydantic class
-        # Type ignoring since the interface only officially supports pydantic 1
-        # or pydantic.v1.BaseModel but not pydantic.BaseModel from pydantic 2.
-        # We'll need to do a pass updating the type signatures.
-        chat = model.with_structured_output(Joke)  # type: ignore[arg-type]
+        chat = model.with_structured_output(Joke, **kwargs)
         result = chat.invoke("Tell me a joke about cats.")
         assert isinstance(result, Joke)
 
         for chunk in chat.stream("Tell me a joke about cats."):
             assert isinstance(chunk, Joke)
 
         # Schema
-        chat = model.with_structured_output(Joke.model_json_schema())
+        chat = model.with_structured_output(Joke.model_json_schema(), **kwargs)
         result = chat.invoke("Tell me a joke about cats.")
         assert isinstance(result, dict)
         assert set(result.keys()) == {"setup", "punchline"}
@@ -1179,21 +1194,22 @@ def has_tool_calling(self) -> bool:
         if not self.has_tool_calling:
             pytest.skip("Test requires tool calling.")
 
+        kwargs: dict[str, Any] = {}
+        if self.structured_output_method:
+            kwargs["method"] = self.structured_output_method
+
         Joke = _get_joke_class()
 
         # Pydantic class
-        # Type ignoring since the interface only officially supports pydantic 1
-        # or pydantic.v1.BaseModel but not pydantic.BaseModel from pydantic 2.
-        # We'll need to do a pass updating the type signatures.
-        chat = model.with_structured_output(Joke)  # type: ignore[arg-type]
+        chat = model.with_structured_output(Joke, **kwargs)
         result = await chat.ainvoke("Tell me a joke about cats.")
         assert isinstance(result, Joke)
 
         async for chunk in chat.astream("Tell me a joke about cats."):
             assert isinstance(chunk, Joke)
 
         # Schema
-        chat = model.with_structured_output(Joke.model_json_schema())
+        chat = model.with_structured_output(Joke.model_json_schema(), **kwargs)
         result = await chat.ainvoke("Tell me a joke about cats.")
         assert isinstance(result, dict)
         assert set(result.keys()) == {"setup", "punchline"}
@@ -1237,22 +1253,26 @@ def has_tool_calling(self) -> bool:
         if not self.has_tool_calling:
             pytest.skip("Test requires tool calling.")
 
+        kwargs: dict[str, Any] = {}
+        if self.structured_output_method:
+            kwargs["method"] = self.structured_output_method
+
         class Joke(BaseModelV1):  # Uses langchain_core.pydantic_v1.BaseModel
             """Joke to tell user."""
 
             setup: str = FieldV1(description="question to set up a joke")
             punchline: str = FieldV1(description="answer to resolve the joke")
 
         # Pydantic class
-        chat = model.with_structured_output(Joke)
+        chat = model.with_structured_output(Joke, **kwargs)
         result = chat.invoke("Tell me a joke about cats.")
         assert isinstance(result, Joke)
 
         for chunk in chat.stream("Tell me a joke about cats."):
             assert isinstance(chunk, Joke)
 
         # Schema
-        chat = model.with_structured_output(Joke.schema())
+        chat = model.with_structured_output(Joke.schema(), **kwargs)
         result = chat.invoke("Tell me a joke about cats.")
         assert isinstance(result, dict)
         assert set(result.keys()) == {"setup", "punchline"}
@@ -1293,6 +1313,10 @@ def has_tool_calling(self) -> bool:
         if not self.has_tool_calling:
             pytest.skip("Test requires tool calling.")
 
+        kwargs = {}
+        if self.structured_output_method:
+            kwargs["method"] = self.structured_output_method
+
         class Joke(BaseModel):
             """Joke to tell user."""
 
@@ -1301,7 +1325,7 @@ class Joke(BaseModel):
                 default=None, description="answer to resolve the joke"
             )
 
-        chat = model.with_structured_output(Joke)  # type: ignore[arg-type]
+        chat = model.with_structured_output(Joke, **kwargs)  # type: ignore[arg-type]
         setup_result = chat.invoke(
             "Give me the setup to a joke about cats, no punchline."
         )

libs/standard-tests/langchain_tests/unit_tests/chat_models.py

@@ -132,6 +132,11 @@ def has_structured_output(self) -> bool:
             is not BaseChatModel.with_structured_output
         )
 
+    @property
+    def structured_output_method(self) -> Optional[str]:
+        """If specified, override default for with_structured_output."""
+        return None
+
     @property
     def supports_json_mode(self) -> bool:
         """(bool) whether the chat model supports JSON mode."""
@@ -299,6 +304,20 @@ def tool_choice_value(self) -> Optional[str]:
             def has_structured_output(self) -> bool:
                 return True
 
+    .. dropdown:: structured_output_method
+
+        Optional string property that can be used to override the default ``method``
+        parameter for ``with_structured_output``. Useful for testing different
+        models.
+
+        Example:
+
+        .. code-block:: python
+
+            @property
+            def structured_output_method(self) -> Optional[str]:
+                return "function_calling"
+
     .. dropdown:: supports_json_mode
 
         Boolean property indicating whether the chat model supports JSON mode in