diff --git a/litellm/utils.py b/litellm/utils.py
index 45e24847c..7f9ba2822 100644
--- a/litellm/utils.py
+++ b/litellm/utils.py
@@ -5642,38 +5642,41 @@ def _handle_invalid_parallel_tool_calls(
 
     if tool_calls is None:
         return
-
-    replacements: Dict[int, List[ChatCompletionMessageToolCall]] = defaultdict(list)
-    for i, tool_call in enumerate(tool_calls):
-        current_function = tool_call.function.name
-        function_args = json.loads(tool_call.function.arguments)
-        if current_function == "multi_tool_use.parallel":
-            verbose_logger.debug(
-                "OpenAI did a weird pseudo-multi-tool-use call, fixing call structure.."
-            )
-            for _fake_i, _fake_tool_use in enumerate(function_args["tool_uses"]):
-                _function_args = _fake_tool_use["parameters"]
-                _current_function = _fake_tool_use["recipient_name"]
-                if _current_function.startswith("functions."):
-                    _current_function = _current_function[len("functions.") :]
-
-                fixed_tc = ChatCompletionMessageToolCall(
-                    id=f"{tool_call.id}_{_fake_i}",
-                    type="function",
-                    function=Function(
-                        name=_current_function, arguments=json.dumps(_function_args)
-                    ),
+    try:
+        replacements: Dict[int, List[ChatCompletionMessageToolCall]] = defaultdict(list)
+        for i, tool_call in enumerate(tool_calls):
+            current_function = tool_call.function.name
+            function_args = json.loads(tool_call.function.arguments)
+            if current_function == "multi_tool_use.parallel":
+                verbose_logger.debug(
+                    "OpenAI did a weird pseudo-multi-tool-use call, fixing call structure.."
                 )
-                replacements[i].append(fixed_tc)
+                for _fake_i, _fake_tool_use in enumerate(function_args["tool_uses"]):
+                    _function_args = _fake_tool_use["parameters"]
+                    _current_function = _fake_tool_use["recipient_name"]
+                    if _current_function.startswith("functions."):
+                        _current_function = _current_function[len("functions.") :]
 
-    shift = 0
-    for i, replacement in replacements.items():
-        tool_calls[:] = (
-            tool_calls[: i + shift] + replacement + tool_calls[i + shift + 1 :]
-        )
-        shift += len(replacement)
+                    fixed_tc = ChatCompletionMessageToolCall(
+                        id=f"{tool_call.id}_{_fake_i}",
+                        type="function",
+                        function=Function(
+                            name=_current_function, arguments=json.dumps(_function_args)
+                        ),
+                    )
+                    replacements[i].append(fixed_tc)
 
-    return tool_calls
+        shift = 0
+        for i, replacement in replacements.items():
+            tool_calls[:] = (
+                tool_calls[: i + shift] + replacement + tool_calls[i + shift + 1 :]
+            )
+            shift += len(replacement)
+
+        return tool_calls
+    except json.JSONDecodeError:
+        # if there is a JSONDecodeError, return the original tool_calls
+        return tool_calls
 
 
 def convert_to_model_response_object(  # noqa: PLR0915
diff --git a/tests/llm_translation/test_llm_response_utils/test_convert_dict_to_chat_completion.py b/tests/llm_translation/test_llm_response_utils/test_convert_dict_to_chat_completion.py
new file mode 100644
index 000000000..20d21a39d
--- /dev/null
+++ b/tests/llm_translation/test_llm_response_utils/test_convert_dict_to_chat_completion.py
@@ -0,0 +1,697 @@
+import json
+import os
+import sys
+from datetime import datetime
+
+sys.path.insert(
+    0, os.path.abspath("../../")
+)  # Adds the parent directory to the system path
+
+import litellm
+import pytest
+from datetime import timedelta
+from litellm.utils import convert_to_model_response_object
+
+from litellm.types.utils import (
+    ModelResponse,
+    Message,
+    Choices,
+    PromptTokensDetailsWrapper,
+    CompletionTokensDetailsWrapper,
+)
+
+
+def test_convert_to_model_response_object_basic():
+    """Test basic conversion with all fields present."""
+    response_object = {
+        "id": "chatcmpl-123456",
+        "object": "chat.completion",
+        "created": 1728933352,
+        "model": "gpt-4o-2024-08-06",
+        "choices": [
+            {
+                "index": 0,
+                "message": {
+                    "role": "assistant",
+                    "content": "Hi there! How can I assist you today?",
+                    "refusal": None,
+                },
+                "finish_reason": "stop",
+            }
+        ],
+        "usage": {
+            "prompt_tokens": 19,
+            "completion_tokens": 10,
+            "total_tokens": 29,
+            "prompt_tokens_details": {"cached_tokens": 0},
+            "completion_tokens_details": {"reasoning_tokens": 0},
+        },
+        "system_fingerprint": "fp_6b68a8204b",
+    }
+
+    result = convert_to_model_response_object(
+        model_response_object=ModelResponse(),
+        response_object=response_object,
+        stream=False,
+        start_time=datetime.now(),
+        end_time=datetime.now(),
+        hidden_params=None,
+        _response_headers=None,
+        convert_tool_call_to_json_mode=False,
+    )
+
+    assert isinstance(result, ModelResponse)
+    assert result.id == "chatcmpl-123456"
+    assert len(result.choices) == 1
+    assert isinstance(result.choices[0], Choices)
+
+    # Model details
+    assert result.model == "gpt-4o-2024-08-06"
+    assert result.object == "chat.completion"
+    assert result.created == 1728933352
+
+    # Choices assertions
+    choice = result.choices[0]
+    print("choice[0]", choice)
+    assert choice.index == 0
+    assert isinstance(choice.message, Message)
+    assert choice.message.role == "assistant"
+    assert choice.message.content == "Hi there! How can I assist you today?"
+    assert choice.finish_reason == "stop"
+
+    # Usage assertions
+    assert result.usage.prompt_tokens == 19
+    assert result.usage.completion_tokens == 10
+    assert result.usage.total_tokens == 29
+    assert result.usage.prompt_tokens_details == PromptTokensDetailsWrapper(
+        cached_tokens=0
+    )
+    assert result.usage.completion_tokens_details == CompletionTokensDetailsWrapper(
+        reasoning_tokens=0
+    )
+
+    # Other fields
+    assert result.system_fingerprint == "fp_6b68a8204b"
+
+    # hidden params
+    assert result._hidden_params is not None
+
+
+def test_convert_image_input_dict_response_to_chat_completion_response():
+    """Test conversion on a response with an image input."""
+    response_object = {
+        "id": "chatcmpl-123",
+        "object": "chat.completion",
+        "created": 1677652288,
+        "model": "gpt-4o-mini",
+        "system_fingerprint": "fp_44709d6fcb",
+        "choices": [
+            {
+                "index": 0,
+                "message": {
+                    "role": "assistant",
+                    "content": "\n\nThis image shows a wooden boardwalk extending through a lush green marshland.",
+                },
+                "logprobs": None,
+                "finish_reason": "stop",
+            }
+        ],
+        "usage": {
+            "prompt_tokens": 9,
+            "completion_tokens": 12,
+            "total_tokens": 21,
+            "completion_tokens_details": {"reasoning_tokens": 0},
+        },
+    }
+
+    result = convert_to_model_response_object(
+        model_response_object=ModelResponse(),
+        response_object=response_object,
+        stream=False,
+        start_time=datetime.now(),
+        end_time=datetime.now(),
+        hidden_params=None,
+        _response_headers=None,
+        convert_tool_call_to_json_mode=False,
+    )
+
+    assert isinstance(result, ModelResponse)
+    assert result.id == "chatcmpl-123"
+    assert result.object == "chat.completion"
+    assert result.created == 1677652288
+    assert result.model == "gpt-4o-mini"
+    assert result.system_fingerprint == "fp_44709d6fcb"
+
+    assert len(result.choices) == 1
+    choice = result.choices[0]
+    assert choice.index == 0
+    assert isinstance(choice.message, Message)
+    assert choice.message.role == "assistant"
+    assert (
+        choice.message.content
+        == "\n\nThis image shows a wooden boardwalk extending through a lush green marshland."
+    )
+    assert choice.finish_reason == "stop"
+
+    assert result.usage.prompt_tokens == 9
+    assert result.usage.completion_tokens == 12
+    assert result.usage.total_tokens == 21
+    assert result.usage.completion_tokens_details == CompletionTokensDetailsWrapper(
+        reasoning_tokens=0
+    )
+
+    assert result._hidden_params is not None
+
+
+def test_convert_to_model_response_object_tool_calls_invalid_json_arguments():
+    """
+    Critical test - this is a basic response from OpenAI API
+
+    Test conversion with tool calls.
+
+    """
+    response_object = {
+        "id": "chatcmpl-AK1uqisVA9OjUNkEuE53GJc8HPYlz",
+        "choices": [
+            {
+                "index": 0,
+                "finish_reason": "length",
+                "logprobs": None,
+                "message": {
+                    "content": None,
+                    "refusal": None,
+                    "role": "assistant",
+                    "audio": None,
+                    "function_call": None,
+                    "tool_calls": [
+                        {
+                            "id": "call_GED1Xit8lU7cNsjVM6dt2fTq",
+                            "function": {
+                                "arguments": '{"location":"Boston, MA","unit":"fahren',
+                                "name": "get_current_weather",
+                            },
+                            "type": "function",
+                        }
+                    ],
+                },
+            }
+        ],
+        "created": 1729337288,
+        "model": "gpt-4o-2024-08-06",
+        "object": "chat.completion",
+        "service_tier": None,
+        "system_fingerprint": "fp_45c6de4934",
+        "usage": {
+            "completion_tokens": 10,
+            "prompt_tokens": 92,
+            "total_tokens": 102,
+            "completion_tokens_details": {"audio_tokens": None, "reasoning_tokens": 0},
+            "prompt_tokens_details": {"audio_tokens": None, "cached_tokens": 0},
+        },
+    }
+    result = convert_to_model_response_object(
+        model_response_object=ModelResponse(),
+        response_object=response_object,
+        stream=False,
+        start_time=datetime.now(),
+        end_time=datetime.now(),
+        hidden_params=None,
+        _response_headers=None,
+        convert_tool_call_to_json_mode=False,
+    )
+
+    assert isinstance(result, ModelResponse)
+    assert result.id == "chatcmpl-AK1uqisVA9OjUNkEuE53GJc8HPYlz"
+    assert len(result.choices) == 1
+    assert result.choices[0].message.content is None
+    assert len(result.choices[0].message.tool_calls) == 1
+    assert (
+        result.choices[0].message.tool_calls[0].function.name == "get_current_weather"
+    )
+    assert (
+        result.choices[0].message.tool_calls[0].function.arguments
+        == '{"location":"Boston, MA","unit":"fahren'
+    )
+    assert result.choices[0].finish_reason == "length"
+    assert result.model == "gpt-4o-2024-08-06"
+    assert result.created == 1729337288
+    assert result.usage.completion_tokens == 10
+    assert result.usage.prompt_tokens == 92
+    assert result.usage.total_tokens == 102
+    assert result.system_fingerprint == "fp_45c6de4934"
+
+
+def test_convert_to_model_response_object_tool_calls_valid_json_arguments():
+    """
+    Critical test - this is a basic response from OpenAI API
+
+    Test conversion with tool calls.
+
+    """
+    response_object = {
+        "id": "chatcmpl-AK1uqisVA9OjUNkEuE53GJc8HPYlz",
+        "choices": [
+            {
+                "index": 0,
+                "finish_reason": "length",
+                "logprobs": None,
+                "message": {
+                    "content": None,
+                    "refusal": None,
+                    "role": "assistant",
+                    "audio": None,
+                    "function_call": None,
+                    "tool_calls": [
+                        {
+                            "id": "call_GED1Xit8lU7cNsjVM6dt2fTq",
+                            "function": {
+                                "arguments": '{"location":"Boston, MA","unit":"fahrenheit"}',
+                                "name": "get_current_weather",
+                            },
+                            "type": "function",
+                        }
+                    ],
+                },
+            }
+        ],
+        "created": 1729337288,
+        "model": "gpt-4o-2024-08-06",
+        "object": "chat.completion",
+        "service_tier": None,
+        "system_fingerprint": "fp_45c6de4934",
+        "usage": {
+            "completion_tokens": 10,
+            "prompt_tokens": 92,
+            "total_tokens": 102,
+            "completion_tokens_details": {"audio_tokens": None, "reasoning_tokens": 0},
+            "prompt_tokens_details": {"audio_tokens": None, "cached_tokens": 0},
+        },
+    }
+    result = convert_to_model_response_object(
+        model_response_object=ModelResponse(),
+        response_object=response_object,
+        stream=False,
+        start_time=datetime.now(),
+        end_time=datetime.now(),
+        hidden_params=None,
+        _response_headers=None,
+        convert_tool_call_to_json_mode=False,
+    )
+
+    assert isinstance(result, ModelResponse)
+    assert result.id == "chatcmpl-AK1uqisVA9OjUNkEuE53GJc8HPYlz"
+    assert len(result.choices) == 1
+    assert result.choices[0].message.content is None
+    assert len(result.choices[0].message.tool_calls) == 1
+    assert (
+        result.choices[0].message.tool_calls[0].function.name == "get_current_weather"
+    )
+    assert (
+        result.choices[0].message.tool_calls[0].function.arguments
+        == '{"location":"Boston, MA","unit":"fahrenheit"}'
+    )
+    assert result.choices[0].finish_reason == "length"
+    assert result.model == "gpt-4o-2024-08-06"
+    assert result.created == 1729337288
+    assert result.usage.completion_tokens == 10
+    assert result.usage.prompt_tokens == 92
+    assert result.usage.total_tokens == 102
+    assert result.system_fingerprint == "fp_45c6de4934"
+
+
+def test_convert_to_model_response_object_json_mode():
+    """
+    This test is verifying that when convert_tool_call_to_json_mode is True, a single tool call's arguments are correctly converted into the message content of the response.
+    """
+    model_response_object = ModelResponse(model="gpt-3.5-turbo")
+    response_object = {
+        "choices": [
+            {
+                "message": {
+                    "role": "assistant",
+                    "tool_calls": [{"function": {"arguments": '{"key": "value"}'}}],
+                },
+                "finish_reason": None,
+            }
+        ],
+        "usage": {"total_tokens": 10, "prompt_tokens": 5, "completion_tokens": 5},
+        "model": "gpt-3.5-turbo",
+    }
+
+    # Call the function
+    result = convert_to_model_response_object(
+        model_response_object=model_response_object,
+        response_object=response_object,
+        stream=False,
+        start_time=datetime.now(),
+        end_time=datetime.now(),
+        hidden_params=None,
+        _response_headers=None,
+        convert_tool_call_to_json_mode=True,
+    )
+
+    # Assertions
+    assert isinstance(result, ModelResponse)
+    assert len(result.choices) == 1
+    assert result.choices[0].message.content == '{"key": "value"}'
+    assert result.choices[0].finish_reason == "stop"
+    assert result.model == "gpt-3.5-turbo"
+    assert result.usage.total_tokens == 10
+    assert result.usage.prompt_tokens == 5
+    assert result.usage.completion_tokens == 5
+
+
+def test_convert_to_model_response_object_function_output():
+    """
+    Test conversion with function output.
+
+    From here: https://platform.openai.com/docs/api-reference/chat/create
+
+    """
+    response_object = {
+        "id": "chatcmpl-abc123",
+        "object": "chat.completion",
+        "created": 1699896916,
+        "model": "gpt-4o-mini",
+        "choices": [
+            {
+                "index": 0,
+                "message": {
+                    "role": "assistant",
+                    "content": None,
+                    "tool_calls": [
+                        {
+                            "id": "call_abc123",
+                            "type": "function",
+                            "function": {
+                                "name": "get_current_weather",
+                                "arguments": '{\n"location": "Boston, MA"\n}',
+                            },
+                        }
+                    ],
+                },
+                "logprobs": None,
+                "finish_reason": "tool_calls",
+            }
+        ],
+        "usage": {
+            "prompt_tokens": 82,
+            "completion_tokens": 17,
+            "total_tokens": 99,
+            "completion_tokens_details": {"reasoning_tokens": 0},
+        },
+    }
+
+    result = convert_to_model_response_object(
+        model_response_object=ModelResponse(),
+        response_object=response_object,
+        stream=False,
+        start_time=datetime.now(),
+        end_time=datetime.now(),
+        hidden_params=None,
+        _response_headers=None,
+        convert_tool_call_to_json_mode=False,
+    )
+
+    assert isinstance(result, ModelResponse)
+    assert result.id == "chatcmpl-abc123"
+    assert result.object == "chat.completion"
+    assert result.created == 1699896916
+    assert result.model == "gpt-4o-mini"
+
+    assert len(result.choices) == 1
+    choice = result.choices[0]
+    assert choice.index == 0
+    assert isinstance(choice.message, Message)
+    assert choice.message.role == "assistant"
+    assert choice.message.content is None
+    assert choice.finish_reason == "tool_calls"
+
+    assert len(choice.message.tool_calls) == 1
+    tool_call = choice.message.tool_calls[0]
+    assert tool_call.id == "call_abc123"
+    assert tool_call.type == "function"
+    assert tool_call.function.name == "get_current_weather"
+    assert tool_call.function.arguments == '{\n"location": "Boston, MA"\n}'
+
+    assert result.usage.prompt_tokens == 82
+    assert result.usage.completion_tokens == 17
+    assert result.usage.total_tokens == 99
+    assert result.usage.completion_tokens_details == CompletionTokensDetailsWrapper(
+        reasoning_tokens=0
+    )
+
+    assert result._hidden_params is not None
+
+
+def test_convert_to_model_response_object_with_logprobs():
+    """
+
+    Test conversion with logprobs in the response.
+
+    From here: https://platform.openai.com/docs/api-reference/chat/create
+
+    """
+    response_object = {
+        "id": "chatcmpl-123",
+        "object": "chat.completion",
+        "created": 1702685778,
+        "model": "gpt-4o-mini",
+        "choices": [
+            {
+                "index": 0,
+                "message": {
+                    "role": "assistant",
+                    "content": "Hello! How can I assist you today?",
+                },
+                "logprobs": {
+                    "content": [
+                        {
+                            "token": "Hello",
+                            "logprob": -0.31725305,
+                            "bytes": [72, 101, 108, 108, 111],
+                            "top_logprobs": [
+                                {
+                                    "token": "Hello",
+                                    "logprob": -0.31725305,
+                                    "bytes": [72, 101, 108, 108, 111],
+                                },
+                                {
+                                    "token": "Hi",
+                                    "logprob": -1.3190403,
+                                    "bytes": [72, 105],
+                                },
+                            ],
+                        },
+                        {
+                            "token": "!",
+                            "logprob": -0.02380986,
+                            "bytes": [33],
+                            "top_logprobs": [
+                                {"token": "!", "logprob": -0.02380986, "bytes": [33]},
+                                {
+                                    "token": " there",
+                                    "logprob": -3.787621,
+                                    "bytes": [32, 116, 104, 101, 114, 101],
+                                },
+                            ],
+                        },
+                        {
+                            "token": " How",
+                            "logprob": -0.000054669687,
+                            "bytes": [32, 72, 111, 119],
+                            "top_logprobs": [
+                                {
+                                    "token": " How",
+                                    "logprob": -0.000054669687,
+                                    "bytes": [32, 72, 111, 119],
+                                },
+                                {
+                                    "token": "<|end|>",
+                                    "logprob": -10.953937,
+                                    "bytes": None,
+                                },
+                            ],
+                        },
+                        {
+                            "token": " can",
+                            "logprob": -0.015801601,
+                            "bytes": [32, 99, 97, 110],
+                            "top_logprobs": [
+                                {
+                                    "token": " can",
+                                    "logprob": -0.015801601,
+                                    "bytes": [32, 99, 97, 110],
+                                },
+                                {
+                                    "token": " may",
+                                    "logprob": -4.161023,
+                                    "bytes": [32, 109, 97, 121],
+                                },
+                            ],
+                        },
+                        {
+                            "token": " I",
+                            "logprob": -3.7697225e-6,
+                            "bytes": [32, 73],
+                            "top_logprobs": [
+                                {
+                                    "token": " I",
+                                    "logprob": -3.7697225e-6,
+                                    "bytes": [32, 73],
+                                },
+                                {
+                                    "token": " assist",
+                                    "logprob": -13.596657,
+                                    "bytes": [32, 97, 115, 115, 105, 115, 116],
+                                },
+                            ],
+                        },
+                        {
+                            "token": " assist",
+                            "logprob": -0.04571125,
+                            "bytes": [32, 97, 115, 115, 105, 115, 116],
+                            "top_logprobs": [
+                                {
+                                    "token": " assist",
+                                    "logprob": -0.04571125,
+                                    "bytes": [32, 97, 115, 115, 105, 115, 116],
+                                },
+                                {
+                                    "token": " help",
+                                    "logprob": -3.1089056,
+                                    "bytes": [32, 104, 101, 108, 112],
+                                },
+                            ],
+                        },
+                        {
+                            "token": " you",
+                            "logprob": -5.4385737e-6,
+                            "bytes": [32, 121, 111, 117],
+                            "top_logprobs": [
+                                {
+                                    "token": " you",
+                                    "logprob": -5.4385737e-6,
+                                    "bytes": [32, 121, 111, 117],
+                                },
+                                {
+                                    "token": " today",
+                                    "logprob": -12.807695,
+                                    "bytes": [32, 116, 111, 100, 97, 121],
+                                },
+                            ],
+                        },
+                        {
+                            "token": " today",
+                            "logprob": -0.0040071653,
+                            "bytes": [32, 116, 111, 100, 97, 121],
+                            "top_logprobs": [
+                                {
+                                    "token": " today",
+                                    "logprob": -0.0040071653,
+                                    "bytes": [32, 116, 111, 100, 97, 121],
+                                },
+                                {"token": "?", "logprob": -5.5247097, "bytes": [63]},
+                            ],
+                        },
+                        {
+                            "token": "?",
+                            "logprob": -0.0008108172,
+                            "bytes": [63],
+                            "top_logprobs": [
+                                {"token": "?", "logprob": -0.0008108172, "bytes": [63]},
+                                {
+                                    "token": "?\n",
+                                    "logprob": -7.184561,
+                                    "bytes": [63, 10],
+                                },
+                            ],
+                        },
+                    ]
+                },
+                "finish_reason": "stop",
+            }
+        ],
+        "usage": {
+            "prompt_tokens": 9,
+            "completion_tokens": 9,
+            "total_tokens": 18,
+            "completion_tokens_details": {"reasoning_tokens": 0},
+        },
+        "system_fingerprint": None,
+    }
+
+    result = convert_to_model_response_object(
+        model_response_object=ModelResponse(),
+        response_object=response_object,
+        stream=False,
+        start_time=datetime.now(),
+        end_time=datetime.now(),
+        hidden_params=None,
+        _response_headers=None,
+        convert_tool_call_to_json_mode=False,
+    )
+
+    assert isinstance(result, ModelResponse)
+    assert result.id == "chatcmpl-123"
+    assert result.object == "chat.completion"
+    assert result.created == 1702685778
+    assert result.model == "gpt-4o-mini"
+
+    assert len(result.choices) == 1
+    choice = result.choices[0]
+    assert choice.index == 0
+    assert isinstance(choice.message, Message)
+    assert choice.message.role == "assistant"
+    assert choice.message.content == "Hello! How can I assist you today?"
+    assert choice.finish_reason == "stop"
+
+    # Check logprobs
+    assert choice.logprobs is not None
+    assert len(choice.logprobs["content"]) == 9
+
+    # Check each logprob entry
+    expected_tokens = [
+        "Hello",
+        "!",
+        " How",
+        " can",
+        " I",
+        " assist",
+        " you",
+        " today",
+        "?",
+    ]
+    for i, logprob in enumerate(choice.logprobs["content"]):
+        assert logprob["token"] == expected_tokens[i]
+        assert isinstance(logprob["logprob"], float)
+        assert isinstance(logprob["bytes"], list)
+        assert len(logprob["top_logprobs"]) == 2
+        assert isinstance(logprob["top_logprobs"][0]["token"], str)
+        assert isinstance(logprob["top_logprobs"][0]["logprob"], float)
+        assert isinstance(logprob["top_logprobs"][0]["bytes"], (list, type(None)))
+
+    assert result.usage.prompt_tokens == 9
+    assert result.usage.completion_tokens == 9
+    assert result.usage.total_tokens == 18
+    assert result.usage.completion_tokens_details == CompletionTokensDetailsWrapper(
+        reasoning_tokens=0
+    )
+
+    assert result.system_fingerprint is None
+    assert result._hidden_params is not None
+
+
+def test_convert_to_model_response_object_error():
+    """Test error handling for None response object."""
+    with pytest.raises(Exception, match="Error in response object format"):
+        convert_to_model_response_object(
+            model_response_object=None,
+            response_object=None,
+            stream=False,
+            start_time=None,
+            end_time=None,
+            hidden_params=None,
+            _response_headers=None,
+            convert_tool_call_to_json_mode=False,
+        )