fix(utils.py): support 'drop_params' for 'parallel_tool_calls'

Closes https://github.com/BerriAI/litellm/issues/4584

 OpenAI-only param

litellm/llms/watsonx.py

@@ -1,28 +1,31 @@
-import json, types, time  # noqa: E401
 import asyncio
+import json  # noqa: E401
+import time
+import types
+from contextlib import asynccontextmanager, contextmanager
 from datetime import datetime
 from enum import Enum
-from contextlib import asynccontextmanager, contextmanager
 from typing import (
+    Any,
+    AsyncContextManager,
+    AsyncGenerator,
+    AsyncIterator,
     Callable,
+    ContextManager,
     Dict,
     Generator,
-    AsyncGenerator,
     Iterator,
-    AsyncIterator,
-    Optional,
-    Any,
-    Union,
     List,
-    ContextManager,
-    AsyncContextManager,
+    Optional,
+    Union,
 )
 
 import httpx  # type: ignore
 import requests  # type: ignore
+
 import litellm
-from litellm.utils import ModelResponse, Usage, get_secret
 from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler
+from litellm.utils import ModelResponse, Usage, get_secret
 
 from .base import BaseLLM
 from .prompt_templates import factory as ptf
@@ -287,8 +290,8 @@ class IBMWatsonXAI(BaseLLM):
         )
 
     def _get_api_params(
-        self, 
-        params: dict, 
+        self,
+        params: dict,
         print_verbose: Optional[Callable] = None,
         generate_token: Optional[bool] = True,
     ) -> dict:
@@ -440,7 +443,7 @@ class IBMWatsonXAI(BaseLLM):
         acompletion=None,
         litellm_params=None,
         logger_fn=None,
-        timeout=None
+        timeout=None,
     ):
         """
         Send a text generation request to the IBM Watsonx.ai API.
@@ -547,7 +550,9 @@ class IBMWatsonXAI(BaseLLM):
         except Exception as e:
             raise WatsonXAIError(status_code=500, message=str(e))
 
-    def _process_embedding_response(self, json_resp: dict, model_response:Union[ModelResponse,None]=None) -> ModelResponse:
+    def _process_embedding_response(
+        self, json_resp: dict, model_response: Union[ModelResponse, None] = None
+    ) -> ModelResponse:
         if model_response is None:
             model_response = ModelResponse(model=json_resp.get("model_id", None))
         results = json_resp.get("results", [])
@@ -563,10 +568,14 @@ class IBMWatsonXAI(BaseLLM):
         model_response["object"] = "list"
         model_response["data"] = embedding_response
         input_tokens = json_resp.get("input_token_count", 0)
-        model_response.usage = Usage(
-            prompt_tokens=input_tokens,
-            completion_tokens=0,
-            total_tokens=input_tokens,
+        setattr(
+            model_response,
+            "usage",
+            Usage(
+                prompt_tokens=input_tokens,
+                completion_tokens=0,
+                total_tokens=input_tokens,
+            ),
         )
         return model_response
 
@@ -580,7 +589,7 @@ class IBMWatsonXAI(BaseLLM):
         optional_params=None,
         encoding=None,
         print_verbose=None,
-        aembedding=None
+        aembedding=None,
     ):
         """
         Send a text embedding request to the IBM Watsonx.ai API.
@@ -593,8 +602,8 @@ class IBMWatsonXAI(BaseLLM):
             if k not in optional_params:
                 optional_params[k] = v
 
-        model_response['model'] = model
-        
+        model_response["model"] = model
+
         # Load auth variables from environment variables
         if isinstance(input, str):
             input = [input]
@@ -685,6 +694,7 @@ class IBMWatsonXAI(BaseLLM):
             return json_resp
         return [res["model_id"] for res in json_resp["resources"]]
 
+
 class RequestManager:
     """
     A class to handle sync/async HTTP requests to the IBM Watsonx.ai API.
@@ -744,7 +754,7 @@ class RequestManager:
 
     @contextmanager
     def request(
-        self, 
+        self,
         request_params: dict,
         stream: bool = False,
         input: Optional[Any] = None,