fireworks[patch]: support "any" tool_choice (#18343)

per https://readme.fireworks.ai/docs/function-calling

libs/partners/fireworks/langchain_fireworks/chat_models.py

@@ -579,7 +579,9 @@ class ChatFireworks(BaseChatModel):
         self,
         tools: Sequence[Union[Dict[str, Any], Type[BaseModel], Callable, BaseTool]],
         *,
-        tool_choice: Optional[Union[dict, str, Literal["auto", "none"], bool]] = None,
+        tool_choice: Optional[
+            Union[dict, str, Literal["auto", "any", "none"], bool]
+        ] = None,
         **kwargs: Any,
     ) -> Runnable[LanguageModelInput, BaseMessage]:
         """Bind tool-like objects to this chat model.
@@ -592,9 +594,10 @@ class ChatFireworks(BaseChatModel):
                 models, callables, and BaseTools will be automatically converted to
                 their schema dictionary representation.
             tool_choice: Which tool to require the model to call.
-                Must be the name of the single provided function or
+                Must be the name of the single provided function,
                 "auto" to automatically determine which function to call
-                (if any), or a dict of the form:
+                with the option to not call any function, "any" to enforce that some
+                function is called, or a dict of the form:
                 {"type": "function", "function": {"name": <<tool_name>>}}.
             **kwargs: Any additional parameters to pass to the
                 :class:`~langchain.runnable.Runnable` constructor.
@@ -602,7 +605,9 @@ class ChatFireworks(BaseChatModel):
 
         formatted_tools = [convert_to_openai_tool(tool) for tool in tools]
         if tool_choice is not None and tool_choice:
-            if isinstance(tool_choice, str) and (tool_choice not in ("auto", "none")):
+            if isinstance(tool_choice, str) and (
+                tool_choice not in ("auto", "any", "none")
+            ):
                 tool_choice = {"type": "function", "function": {"name": tool_choice}}
             if isinstance(tool_choice, dict) and (len(formatted_tools) != 1):
                 raise ValueError(