cohere: add with_structured_output to ChatCohere (#19730)

**Description:** Adds support for `with_structured_output` to Cohere,
which supports single function calling.

---------

Co-authored-by: BeatrixCohere <128378696+BeatrixCohere@users.noreply.github.com>

libs/partners/cohere/langchain_cohere/chat_models.py

@@ -12,6 +12,7 @@ from typing import (
 )
 
 from cohere.types import NonStreamedChatResponse, ToolCall
+from langchain_core._api import beta
 from langchain_core.callbacks import (
     AsyncCallbackManagerForLLMRun,
     CallbackManagerForLLMRun,
@@ -30,12 +31,20 @@ from langchain_core.messages import (
     HumanMessage,
     SystemMessage,
 )
+from langchain_core.output_parsers.base import OutputParserLike
+from langchain_core.output_parsers.openai_tools import (
+    JsonOutputKeyToolsParser,
+    PydanticToolsParser,
+)
 from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
 from langchain_core.pydantic_v1 import BaseModel
 from langchain_core.runnables import Runnable
 from langchain_core.tools import BaseTool
 
-from langchain_cohere.cohere_agent import _format_to_cohere_tools
+from langchain_cohere.cohere_agent import (
+    _convert_to_cohere_tool,
+    _format_to_cohere_tools,
+)
 from langchain_cohere.llms import BaseCohere
 
 
@@ -165,6 +174,39 @@ class ChatCohere(BaseChatModel, BaseCohere):
         formatted_tools = _format_to_cohere_tools(tools)
         return super().bind(tools=formatted_tools, **kwargs)
 
+    @beta()
+    def with_structured_output(
+        self,
+        schema: Union[Dict, Type[BaseModel]],
+        **kwargs: Any,
+    ) -> Runnable[LanguageModelInput, Union[Dict, BaseModel]]:
+        """Model wrapper that returns outputs formatted to match the given schema.
+
+        Args:
+            schema: The output schema as a dict or a Pydantic class. If a Pydantic class
+                then the model output will be an object of that class. If a dict then
+                the model output will be a dict.
+
+        Returns:
+            A Runnable that takes any ChatModel input and returns either a dict or
+            Pydantic class as output.
+        """
+        if kwargs:
+            raise ValueError(f"Received unsupported arguments {kwargs}")
+        is_pydantic_schema = isinstance(schema, type) and issubclass(schema, BaseModel)
+        llm = self.bind_tools([schema])
+        if is_pydantic_schema:
+            output_parser: OutputParserLike = PydanticToolsParser(
+                tools=[schema], first_tool_only=True
+            )
+        else:
+            key_name = _convert_to_cohere_tool(schema)["name"]
+            output_parser = JsonOutputKeyToolsParser(
+                key_name=key_name, first_tool_only=True
+            )
+
+        return llm | output_parser
+
     @property
     def _identifying_params(self) -> Dict[str, Any]:
         """Get the identifying parameters."""