diff --git a/litellm/litellm_core_utils/llm_response_utils/convert_dict_to_response.py b/litellm/litellm_core_utils/llm_response_utils/convert_dict_to_response.py
index 28d546796db..dacd21f426e 100644
--- a/litellm/litellm_core_utils/llm_response_utils/convert_dict_to_response.py
+++ b/litellm/litellm_core_utils/llm_response_utils/convert_dict_to_response.py
@@ -7,6 +7,7 @@ from typing import Dict, Iterable, List, Literal, Optional, Union
 
 import litellm
 from litellm._logging import verbose_logger
+from litellm.constants import RESPONSE_FORMAT_TOOL_NAME
 from litellm.types.utils import (
     ChatCompletionDeltaToolCall,
     ChatCompletionMessageToolCall,
@@ -313,6 +314,23 @@ class LiteLLMResponseObjectHandler:
         return transformed_logprobs
 
 
+def _should_convert_tool_call_to_json_mode(
+    tool_calls: Optional[List[ChatCompletionMessageToolCall]] = None,
+    convert_tool_call_to_json_mode: Optional[bool] = None,
+) -> bool:
+    """
+    Determine if tool calls should be converted to JSON mode
+    """
+    if (
+        convert_tool_call_to_json_mode
+        and tool_calls is not None
+        and len(tool_calls) == 1
+        and tool_calls[0]["function"]["name"] == RESPONSE_FORMAT_TOOL_NAME
+    ):
+        return True
+    return False
+
+
 def convert_to_model_response_object(  # noqa: PLR0915
     response_object: Optional[dict] = None,
     model_response_object: Optional[
@@ -397,10 +415,9 @@ def convert_to_model_response_object(  # noqa: PLR0915
 
                 message: Optional[Message] = None
                 finish_reason: Optional[str] = None
-                if (
-                    convert_tool_call_to_json_mode
-                    and tool_calls is not None
-                    and len(tool_calls) == 1
+                if _should_convert_tool_call_to_json_mode(
+                    tool_calls=tool_calls,
+                    convert_tool_call_to_json_mode=convert_tool_call_to_json_mode,
                 ):
                     # to support 'json_schema' logic on older models
                     json_mode_content_str: Optional[str] = tool_calls[0][
diff --git a/litellm/llms/azure/chat/gpt_transformation.py b/litellm/llms/azure/chat/gpt_transformation.py
index 00e336d69a9..3f450fefa5a 100644
--- a/litellm/llms/azure/chat/gpt_transformation.py
+++ b/litellm/llms/azure/chat/gpt_transformation.py
@@ -3,6 +3,7 @@ from typing import TYPE_CHECKING, Any, List, Optional, Union
 from httpx._models import Headers, Response
 
 import litellm
+from litellm.constants import RESPONSE_FORMAT_TOOL_NAME
 from litellm.litellm_core_utils.prompt_templates.factory import (
     convert_to_azure_openai_messages,
 )
@@ -201,14 +202,14 @@ class AzureOpenAIConfig(BaseConfig):
                     _tool_choice = ChatCompletionToolChoiceObjectParam(
                         type="function",
                         function=ChatCompletionToolChoiceFunctionParam(
-                            name=schema_name
+                            name=RESPONSE_FORMAT_TOOL_NAME
                         ),
                     )
 
                     _tool = ChatCompletionToolParam(
                         type="function",
                         function=ChatCompletionToolParamFunctionChunk(
-                            name=schema_name, parameters=json_schema
+                            name=RESPONSE_FORMAT_TOOL_NAME, parameters=json_schema
                         ),
                     )
 
diff --git a/tests/llm_translation/test_azure_openai.py b/tests/llm_translation/test_azure_openai.py
index 0e9be710e2a..1306c536501 100644
--- a/tests/llm_translation/test_azure_openai.py
+++ b/tests/llm_translation/test_azure_openai.py
@@ -283,3 +283,61 @@ def test_azure_openai_gpt_4o_naming(monkeypatch):
         print(mock_post.call_args.kwargs)
 
         assert "tool_calls" not in mock_post.call_args.kwargs
+
+
+def test_azure_gpt_4o_with_tool_call_and_response_format():
+    from litellm import completion
+    from typing import Optional
+    from pydantic import BaseModel
+    import litellm
+
+    class InvestigationOutput(BaseModel):
+        alert_explanation: Optional[str] = None
+        investigation: Optional[str] = None
+        conclusions_and_possible_root_causes: Optional[str] = None
+        next_steps: Optional[str] = None
+        related_logs: Optional[str] = None
+        app_or_infra: Optional[str] = None
+        external_links: Optional[str] = None
+
+    tools = [
+        {
+            "type": "function",
+            "function": {
+                "name": "get_current_time",
+                "description": "Returns the current date and time",
+                "strict": True,
+                "parameters": {
+                    "properties": {
+                        "timezone": {
+                            "type": "string",
+                            "description": "The timezone to get the current time for (e.g., 'UTC', 'America/New_York')",
+                        }
+                    },
+                    "required": ["timezone"],
+                    "type": "object",
+                    "additionalProperties": False,
+                },
+            },
+        }
+    ]
+
+    response = litellm.completion(
+        model="azure/gpt-4o",
+        messages=[
+            {
+                "role": "system",
+                "content": "You are a tool-calling AI assist provided with common devops and IT tools that you can use to troubleshoot problems or answer questions.\nWhenever possible you MUST first use tools to investigate then answer the question.",
+            },
+            {"role": "user", "content": "What is the current date and time in NYC?"},
+        ],
+        drop_params=True,
+        temperature=0.00000001,
+        tools=tools,
+        tool_choice="auto",
+        response_format=InvestigationOutput,  # commenting this line will cause the output to be correct
+    )
+
+    assert response.choices[0].finish_reason == "tool_calls"
+
+    print(response.to_json())