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

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

 OpenAI-only param

litellm/llms/openai.py

@@ -445,6 +445,7 @@ class OpenAIConfig:
             "functions",
             "max_retries",
             "extra_headers",
+            "parallel_tool_calls",
         ]  # works across all models
 
         model_specific_params = []

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,
+    Optional,
-    AsyncContextManager,
+    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
@@ -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(
+        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.
@@ -593,7 +602,7 @@ 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):
@@ -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.

litellm/main.py

@@ -108,7 +108,6 @@ from .llms.databricks import DatabricksChatCompletion
 from .llms.huggingface_restapi import Huggingface
 from .llms.openai import OpenAIChatCompletion, OpenAITextCompletion
 from .llms.predibase import PredibaseChatCompletion
-from .llms.watsonx import IBMWatsonXAI
 from .llms.prompt_templates.factory import (
     custom_prompt,
     function_call_prompt,
@@ -119,6 +118,7 @@ from .llms.prompt_templates.factory import (
 from .llms.text_completion_codestral import CodestralTextCompletion
 from .llms.triton import TritonChatCompletion
 from .llms.vertex_httpx import VertexLLM
+from .llms.watsonx import IBMWatsonXAI
 from .types.llms.openai import HttpxBinaryResponseContent
 from .types.utils import ChatCompletionMessageToolCall
 
@@ -593,6 +593,7 @@ def completion(
     tool_choice: Optional[Union[str, dict]] = None,
     logprobs: Optional[bool] = None,
     top_logprobs: Optional[int] = None,
+    parallel_tool_calls: Optional[bool] = None,
     deployment_id=None,
     extra_headers: Optional[dict] = None,
     # soon to be deprecated params by OpenAI
@@ -722,6 +723,7 @@ def completion(
         "tools",
         "tool_choice",
         "max_retries",
+        "parallel_tool_calls",
         "logprobs",
         "top_logprobs",
         "extra_headers",
@@ -932,6 +934,7 @@ def completion(
             top_logprobs=top_logprobs,
             extra_headers=extra_headers,
             api_version=api_version,
+            parallel_tool_calls=parallel_tool_calls,
             **non_default_params,
         )
 

litellm/tests/test_optional_params.py

@@ -269,7 +269,7 @@ def test_dynamic_drop_params(drop_params):
     """
     Make a call to cohere w/ drop params = True vs. false.
     """
-    if drop_params == True:
+    if drop_params is True:
         optional_params = litellm.utils.get_optional_params(
             model="command-r",
             custom_llm_provider="cohere",
@@ -306,6 +306,52 @@ def test_dynamic_drop_params_e2e():
         assert "response_format" not in mock_response.call_args.kwargs["data"]
 
 
+@pytest.mark.parametrize(
+    "model, provider, should_drop",
+    [("command-r", "cohere", True), ("gpt-3.5-turbo", "openai", False)],
+)
+def test_drop_params_parallel_tool_calls(model, provider, should_drop):
+    """
+    https://github.com/BerriAI/litellm/issues/4584
+    """
+    response = litellm.utils.get_optional_params(
+        model=model,
+        custom_llm_provider=provider,
+        response_format="json",
+        parallel_tool_calls=True,
+        drop_params=True,
+    )
+
+    print(response)
+
+    if should_drop:
+        assert "response_format" not in response
+        assert "parallel_tool_calls" not in response
+    else:
+        assert "response_format" in response
+        assert "parallel_tool_calls" in response
+
+
+def test_dynamic_drop_params_parallel_tool_calls():
+    """
+    https://github.com/BerriAI/litellm/issues/4584
+    """
+    with patch("requests.post", new=MagicMock()) as mock_response:
+        try:
+            response = litellm.completion(
+                model="command-r",
+                messages=[{"role": "user", "content": "Hey, how's it going?"}],
+                parallel_tool_calls=True,
+                drop_params=True,
+            )
+        except Exception as e:
+            pass
+
+        mock_response.assert_called_once()
+        print(mock_response.call_args.kwargs["data"])
+        assert "parallel_tool_calls" not in mock_response.call_args.kwargs["data"]
+
+
 @pytest.mark.parametrize("drop_params", [True, False, None])
 def test_dynamic_drop_additional_params(drop_params):
     """

litellm/utils.py

@@ -2393,6 +2393,7 @@ def get_optional_params(
     top_logprobs=None,
     extra_headers=None,
     api_version=None,
+    parallel_tool_calls=None,
     drop_params=None,
     additional_drop_params=None,
     **kwargs,
@@ -2470,6 +2471,7 @@ def get_optional_params(
         "top_logprobs": None,
         "extra_headers": None,
         "api_version": None,
+        "parallel_tool_calls": None,
         "drop_params": None,
         "additional_drop_params": None,
     }