openai[patch]: enable Azure structured output, parallel_tool_calls=Fa… (#26599)

…lse, tool_choice=required

response_format=json_schema, tool_choice=required, parallel_tool_calls
are all supported for gpt-4o on azure.

libs/partners/openai/langchain_openai/chat_models/base.py

@@ -454,6 +454,23 @@ class BaseChatOpenAI(BaseChatModel):
     making requests to OpenAI compatible APIs, such as vLLM."""
     include_response_headers: bool = False
     """Whether to include response headers in the output message response_metadata."""
+    disabled_params: Optional[Dict[str, Any]] = Field(default=None)
+    """Parameters of the OpenAI client or chat.completions endpoint that should be 
+    disabled for the given model.
+    
+    Should be specified as ``{"param": None | ['val1', 'val2']}`` where the key is the 
+    parameter and the value is either None, meaning that parameter should never be
+    used, or it's a list of disabled values for the parameter.
+    
+    For example, older models may not support the 'parallel_tool_calls' parameter at 
+    all, in which case ``disabled_params={"parallel_tool_calls: None}`` can ben passed 
+    in.
+    
+    If a parameter is disabled then it will not be used by default in any methods, e.g.
+    in :meth:`~langchain_openai.chat_models.base.ChatOpenAI.with_structured_output`.
+    However this does not prevent a user from directly passed in the parameter during
+    invocation. 
+    """
 
     model_config = ConfigDict(populate_by_name=True)
 
@@ -1401,12 +1418,11 @@ class BaseChatOpenAI(BaseChatModel):
                     "Received None."
                 )
             tool_name = convert_to_openai_tool(schema)["function"]["name"]
-            llm = self.bind_tools(
-                [schema],
-                tool_choice=tool_name,
-                parallel_tool_calls=False,
-                strict=strict,
+            bind_kwargs = self._filter_disabled_params(
+                tool_choice=tool_name, parallel_tool_calls=False, strict=strict
             )
+
+            llm = self.bind_tools([schema], **bind_kwargs)
             if is_pydantic_schema:
                 output_parser: Runnable = PydanticToolsParser(
                     tools=[schema],  # type: ignore[list-item]
@@ -1456,6 +1472,21 @@ class BaseChatOpenAI(BaseChatModel):
         else:
             return llm | output_parser
 
+    def _filter_disabled_params(self, **kwargs: Any) -> Dict[str, Any]:
+        if not self.disabled_params:
+            return kwargs
+        filtered = {}
+        for k, v in kwargs.items():
+            # Skip param
+            if k in self.disabled_params and (
+                self.disabled_params[k] is None or v in self.disabled_params[k]
+            ):
+                continue
+            # Keep param
+            else:
+                filtered[k] = v
+        return filtered
+
 
 class ChatOpenAI(BaseChatOpenAI):
     """OpenAI chat model integration.
@@ -2114,7 +2145,7 @@ def _oai_structured_outputs_parser(ai_msg: AIMessage) -> PydanticBaseModel:
     else:
         raise ValueError(
             "Structured Output response does not have a 'parsed' field nor a 'refusal' "
-            "field."
+            "field. Received message:\n\n{ai_msg}"
         )