litellm/llms/sagemaker/completion/transformation.py

@@ -37,7 +37,6 @@ class SagemakerConfig(BaseConfig):
     """
 
     max_new_tokens: Optional[int] = None
-    max_completion_tokens: Optional[int] = None
     top_p: Optional[float] = None
     temperature: Optional[float] = None
     return_full_text: Optional[bool] = None
@@ -45,7 +44,6 @@ class SagemakerConfig(BaseConfig):
     def __init__(
         self,
         max_new_tokens: Optional[int] = None,
-        max_completion_tokens: Optional[int] = None,
         top_p: Optional[float] = None,
         temperature: Optional[float] = None,
         return_full_text: Optional[bool] = None,
@@ -67,7 +65,7 @@ class SagemakerConfig(BaseConfig):
         )
 
     def get_supported_openai_params(self, model: str) -> List:
-        return ["stream", "temperature", "max_tokens", "max_completion_tokens", "top_p", "stop", "n"]
+        return ["stream", "temperature", "max_tokens", "top_p", "stop", "n"]
 
     def map_openai_params(
         self,
@@ -104,8 +102,6 @@ class SagemakerConfig(BaseConfig):
                 if value == 0:
                     value = 1
                 optional_params["max_new_tokens"] = value
-            if param == "max_completion_tokens":
-                optional_params["max_new_tokens"] = value
         non_default_params.pop("aws_sagemaker_allow_zero_temp", None)
         return optional_params
 

litellm/model_prices_and_context_window_backup.json

@@ -7058,17 +7058,6 @@
         "source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#foundation_models",
         "supports_tool_choice": true
     },
-    "command-a-03-2025": {
-        "max_tokens": 8000,
-        "max_input_tokens": 256000,
-        "max_output_tokens": 8000,
-        "input_cost_per_token": 0.0000025,
-        "output_cost_per_token": 0.00001,
-        "litellm_provider": "cohere_chat",
-        "mode": "chat",
-        "supports_function_calling": true,
-        "supports_tool_choice": true
-    },
     "command-r": {
         "max_tokens": 4096,
         "max_input_tokens": 128000,

litellm/proxy/common_request_processing.py

@@ -108,13 +108,7 @@ class ProxyBaseLLMRequestProcessing:
         user_api_key_dict: UserAPIKeyAuth,
         proxy_logging_obj: ProxyLogging,
         proxy_config: ProxyConfig,
-        route_type: Literal[
+        route_type: Literal["acompletion", "aresponses", "_arealtime"],
-            "acompletion",
-            "aresponses",
-            "_arealtime",
-            "aget_responses",
-            "adelete_responses",
-        ],
         version: Optional[str] = None,
         user_model: Optional[str] = None,
         user_temperature: Optional[float] = None,
@@ -184,13 +178,7 @@ class ProxyBaseLLMRequestProcessing:
         request: Request,
         fastapi_response: Response,
         user_api_key_dict: UserAPIKeyAuth,
-        route_type: Literal[
+        route_type: Literal["acompletion", "aresponses", "_arealtime"],
-            "acompletion",
-            "aresponses",
-            "_arealtime",
-            "aget_responses",
-            "adelete_responses",
-        ],
         proxy_logging_obj: ProxyLogging,
         general_settings: dict,
         proxy_config: ProxyConfig,

litellm/proxy/common_utils/http_parsing_utils.py

@@ -1,5 +1,5 @@
 import json
-from typing import Any, Dict, List, Optional
+from typing import Dict, List, Optional
 
 import orjson
 from fastapi import Request, UploadFile, status
@@ -147,11 +147,11 @@ def check_file_size_under_limit(
 
     if llm_router is not None and request_data["model"] in router_model_names:
         try:
-            deployment: Optional[Deployment] = (
+            deployment: Optional[
-                llm_router.get_deployment_by_model_group_name(
+                Deployment
+            ] = llm_router.get_deployment_by_model_group_name(
                 model_group_name=request_data["model"]
             )
-            )
             if (
                 deployment
                 and deployment.litellm_params is not None
@@ -185,23 +185,3 @@ def check_file_size_under_limit(
             )
 
     return True
-
-
-async def get_form_data(request: Request) -> Dict[str, Any]:
-    """
-    Read form data from request
-
-    Handles when OpenAI SDKs pass form keys as `timestamp_granularities[]="word"` instead of `timestamp_granularities=["word", "sentence"]`
-    """
-    form = await request.form()
-    form_data = dict(form)
-    parsed_form_data: dict[str, Any] = {}
-    for key, value in form_data.items():
-
-        # OpenAI SDKs pass form keys as `timestamp_granularities[]="word"` instead of `timestamp_granularities=["word", "sentence"]`
-        if key.endswith("[]"):
-            clean_key = key[:-2]
-            parsed_form_data.setdefault(clean_key, []).append(value)
-        else:
-            parsed_form_data[key] = value
-    return parsed_form_data

litellm/proxy/proxy_config.yaml

@@ -1,8 +1,16 @@
 model_list:
-  - model_name: openai/*
+  - model_name: azure-computer-use-preview
     litellm_params:
-      model: openai/*
+      model: azure/computer-use-preview
-      api_key: os.environ/OPENAI_API_KEY
+      api_key: mock-api-key
+      api_version: mock-api-version
+      api_base: https://mock-endpoint.openai.azure.com
+  - model_name: azure-computer-use-preview
+    litellm_params:
+      model: azure/computer-use-preview-2
+      api_key: mock-api-key-2
+      api_version: mock-api-version-2
+      api_base: https://mock-endpoint-2.openai.azure.com
 
 router_settings:
   optional_pre_call_checks: ["responses_api_deployment_check"]

litellm/proxy/proxy_server.py

@@ -179,7 +179,6 @@ from litellm.proxy.common_utils.html_forms.ui_login import html_form
 from litellm.proxy.common_utils.http_parsing_utils import (
     _read_request_body,
     check_file_size_under_limit,
-    get_form_data,
 )
 from litellm.proxy.common_utils.load_config_utils import (
     get_config_file_contents_from_gcs,
@@ -805,9 +804,9 @@ model_max_budget_limiter = _PROXY_VirtualKeyModelMaxBudgetLimiter(
     dual_cache=user_api_key_cache
 )
 litellm.logging_callback_manager.add_litellm_callback(model_max_budget_limiter)
-redis_usage_cache: Optional[RedisCache] = (
+redis_usage_cache: Optional[
-    None  # redis cache used for tracking spend, tpm/rpm limits
+    RedisCache
-)
+] = None  # redis cache used for tracking spend, tpm/rpm limits
 user_custom_auth = None
 user_custom_key_generate = None
 user_custom_sso = None
@@ -1133,9 +1132,9 @@ async def update_cache(  # noqa: PLR0915
         _id = "team_id:{}".format(team_id)
         try:
             # Fetch the existing cost for the given user
-            existing_spend_obj: Optional[LiteLLM_TeamTable] = (
+            existing_spend_obj: Optional[
-                await user_api_key_cache.async_get_cache(key=_id)
+                LiteLLM_TeamTable
-            )
+            ] = await user_api_key_cache.async_get_cache(key=_id)
             if existing_spend_obj is None:
                 # do nothing if team not in api key cache
                 return
@@ -2807,9 +2806,9 @@ async def initialize(  # noqa: PLR0915
         user_api_base = api_base
         dynamic_config[user_model]["api_base"] = api_base
     if api_version:
-        os.environ["AZURE_API_VERSION"] = (
+        os.environ[
-            api_version  # set this for azure - litellm can read this from the env
+            "AZURE_API_VERSION"
-        )
+        ] = api_version  # set this for azure - litellm can read this from the env
     if max_tokens:  # model-specific param
         dynamic_config[user_model]["max_tokens"] = max_tokens
     if temperature:  # model-specific param
@@ -4121,7 +4120,7 @@ async def audio_transcriptions(
     data: Dict = {}
     try:
         # Use orjson to parse JSON data, orjson speeds up requests significantly
-        form_data = await get_form_data(request)
+        form_data = await request.form()
         data = {key: value for key, value in form_data.items() if key != "file"}
 
         # Include original request and headers in the data
@@ -7759,9 +7758,9 @@ async def get_config_list(
                             hasattr(sub_field_info, "description")
                             and sub_field_info.description is not None
                         ):
-                            nested_fields[idx].field_description = (
+                            nested_fields[
-                                sub_field_info.description
+                                idx
-                            )
+                            ].field_description = sub_field_info.description
                         idx += 1
 
                     _stored_in_db = None

litellm/proxy/response_api_endpoints/endpoints.py

@@ -106,50 +106,8 @@ async def get_response(
     -H "Authorization: Bearer sk-1234"
     ```
     """
-    from litellm.proxy.proxy_server import (
+    # TODO: Implement response retrieval logic
-        _read_request_body,
+    pass
-        general_settings,
-        llm_router,
-        proxy_config,
-        proxy_logging_obj,
-        select_data_generator,
-        user_api_base,
-        user_max_tokens,
-        user_model,
-        user_request_timeout,
-        user_temperature,
-        version,
-    )
-
-    data = await _read_request_body(request=request)
-    data["response_id"] = response_id
-    processor = ProxyBaseLLMRequestProcessing(data=data)
-    try:
-        return await processor.base_process_llm_request(
-            request=request,
-            fastapi_response=fastapi_response,
-            user_api_key_dict=user_api_key_dict,
-            route_type="aget_responses",
-            proxy_logging_obj=proxy_logging_obj,
-            llm_router=llm_router,
-            general_settings=general_settings,
-            proxy_config=proxy_config,
-            select_data_generator=select_data_generator,
-            model=None,
-            user_model=user_model,
-            user_temperature=user_temperature,
-            user_request_timeout=user_request_timeout,
-            user_max_tokens=user_max_tokens,
-            user_api_base=user_api_base,
-            version=version,
-        )
-    except Exception as e:
-        raise await processor._handle_llm_api_exception(
-            e=e,
-            user_api_key_dict=user_api_key_dict,
-            proxy_logging_obj=proxy_logging_obj,
-            version=version,
-        )
 
 
 @router.delete(
@@ -178,50 +136,8 @@ async def delete_response(
     -H "Authorization: Bearer sk-1234"
     ```
     """
-    from litellm.proxy.proxy_server import (
+    # TODO: Implement response deletion logic
-        _read_request_body,
+    pass
-        general_settings,
-        llm_router,
-        proxy_config,
-        proxy_logging_obj,
-        select_data_generator,
-        user_api_base,
-        user_max_tokens,
-        user_model,
-        user_request_timeout,
-        user_temperature,
-        version,
-    )
-
-    data = await _read_request_body(request=request)
-    data["response_id"] = response_id
-    processor = ProxyBaseLLMRequestProcessing(data=data)
-    try:
-        return await processor.base_process_llm_request(
-            request=request,
-            fastapi_response=fastapi_response,
-            user_api_key_dict=user_api_key_dict,
-            route_type="adelete_responses",
-            proxy_logging_obj=proxy_logging_obj,
-            llm_router=llm_router,
-            general_settings=general_settings,
-            proxy_config=proxy_config,
-            select_data_generator=select_data_generator,
-            model=None,
-            user_model=user_model,
-            user_temperature=user_temperature,
-            user_request_timeout=user_request_timeout,
-            user_max_tokens=user_max_tokens,
-            user_api_base=user_api_base,
-            version=version,
-        )
-    except Exception as e:
-        raise await processor._handle_llm_api_exception(
-            e=e,
-            user_api_key_dict=user_api_key_dict,
-            proxy_logging_obj=proxy_logging_obj,
-            version=version,
-        )
 
 
 @router.get(

litellm/proxy/route_llm_request.py

@@ -47,8 +47,6 @@ async def route_request(
         "amoderation",
         "arerank",
         "aresponses",
-        "aget_responses",
-        "adelete_responses",
         "_arealtime",  # private function for realtime API
     ],
 ):

litellm/responses/utils.py

@@ -176,16 +176,6 @@ class ResponsesAPIRequestUtils:
                 response_id=response_id,
             )
 
-    @staticmethod
-    def get_model_id_from_response_id(response_id: Optional[str]) -> Optional[str]:
-        """Get the model_id from the response_id"""
-        if response_id is None:
-            return None
-        decoded_response_id = (
-            ResponsesAPIRequestUtils._decode_responses_api_response_id(response_id)
-        )
-        return decoded_response_id.get("model_id") or None
-
 
 class ResponseAPILoggingUtils:
     @staticmethod

litellm/router.py

@@ -739,12 +739,6 @@ class Router:
             litellm.afile_content, call_type="afile_content"
         )
         self.responses = self.factory_function(litellm.responses, call_type="responses")
-        self.aget_responses = self.factory_function(
-            litellm.aget_responses, call_type="aget_responses"
-        )
-        self.adelete_responses = self.factory_function(
-            litellm.adelete_responses, call_type="adelete_responses"
-        )
 
     def validate_fallbacks(self, fallback_param: Optional[List]):
         """
@@ -3087,8 +3081,6 @@ class Router:
             "anthropic_messages",
             "aresponses",
             "responses",
-            "aget_responses",
-            "adelete_responses",
             "afile_delete",
             "afile_content",
         ] = "assistants",
@@ -3143,11 +3135,6 @@ class Router:
                     original_function=original_function,
                     **kwargs,
                 )
-            elif call_type in ("aget_responses", "adelete_responses"):
-                return await self._init_responses_api_endpoints(
-                    original_function=original_function,
-                    **kwargs,
-                )
             elif call_type in ("afile_delete", "afile_content"):
                 return await self._ageneric_api_call_with_fallbacks(
                     original_function=original_function,
@@ -3158,28 +3145,6 @@ class Router:
 
         return async_wrapper
 
-    async def _init_responses_api_endpoints(
-        self,
-        original_function: Callable,
-        **kwargs,
-    ):
-        """
-        Initialize the Responses API endpoints on the router.
-
-        GET, DELETE Responses API Requests encode the model_id in the response_id, this function decodes the response_id and sets the model to the model_id.
-        """
-        from litellm.responses.utils import ResponsesAPIRequestUtils
-
-        model_id = ResponsesAPIRequestUtils.get_model_id_from_response_id(
-            kwargs.get("response_id")
-        )
-        if model_id is not None:
-            kwargs["model"] = model_id
-        return await self._ageneric_api_call_with_fallbacks(
-            original_function=original_function,
-            **kwargs,
-        )
-
     async def _pass_through_assistants_endpoint_factory(
         self,
         original_function: Callable,

model_prices_and_context_window.json

@@ -7058,17 +7058,6 @@
         "source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#foundation_models",
         "supports_tool_choice": true
     },
-    "command-a-03-2025": {
-        "max_tokens": 8000,
-        "max_input_tokens": 256000,
-        "max_output_tokens": 8000,
-        "input_cost_per_token": 0.0000025,
-        "output_cost_per_token": 0.00001,
-        "litellm_provider": "cohere_chat",
-        "mode": "chat",
-        "supports_function_calling": true,
-        "supports_tool_choice": true
-    },
     "command-r": {
         "max_tokens": 4096,
         "max_input_tokens": 128000,

tests/litellm/llms/sagemaker/test_sagemaker_common_utils.py

@@ -8,7 +8,7 @@ import pytest
 
 sys.path.insert(0, os.path.abspath("../../../../.."))
 from litellm.llms.sagemaker.common_utils import AWSEventStreamDecoder
-from litellm.llms.sagemaker.completion.transformation import SagemakerConfig
+
 
 @pytest.mark.asyncio
 async def test_aiter_bytes_unicode_decode_error():
@@ -95,37 +95,3 @@ async def test_aiter_bytes_valid_chunk_followed_by_unicode_error():
         # Verify we got our valid chunk despite the subsequent error
         assert len(chunks) == 1
         assert chunks[0]["text"] == "hello"  # Verify the content of the valid chunk
-
-class TestSagemakerTransform:
-    def setup_method(self):
-        self.config = SagemakerConfig()
-        self.model = "test"
-        self.logging_obj = MagicMock()
-
-    def test_map_mistral_params(self):
-        """Test that parameters are correctly mapped"""
-        test_params = {"temperature": 0.7, "max_tokens": 200, "max_completion_tokens": 256}
-
-        result = self.config.map_openai_params(
-            non_default_params=test_params,
-            optional_params={},
-            model=self.model,
-            drop_params=False,
-        )
-
-        # The function should properly map max_completion_tokens to max_tokens and override max_tokens
-        assert result == {"temperature": 0.7, "max_new_tokens": 256}
-
-    def test_mistral_max_tokens_backward_compat(self):
-        """Test that parameters are correctly mapped"""
-        test_params = {"temperature": 0.7, "max_tokens": 200,}
-
-        result = self.config.map_openai_params(
-            non_default_params=test_params,
-            optional_params={},
-            model=self.model,
-            drop_params=False,
-        )
-
-        # The function should properly map max_tokens if max_completion_tokens is not provided
-        assert result == {"temperature": 0.7, "max_new_tokens": 200}

tests/litellm/proxy/common_utils/test_http_parsing_utils.py

@@ -18,7 +18,6 @@ from litellm.proxy.common_utils.http_parsing_utils import (
     _read_request_body,
     _safe_get_request_parsed_body,
     _safe_set_request_parsed_body,
-    get_form_data,
 )
 
 
@@ -148,53 +147,3 @@ async def test_circular_reference_handling():
     assert (
         "proxy_server_request" not in result2
     )  # This will pass, showing the cache pollution
-
-
-@pytest.mark.asyncio
-async def test_get_form_data():
-    """
-    Test that get_form_data correctly handles form data with array notation.
-    Tests audio transcription parameters as a specific example.
-    """
-    # Create a mock request with transcription form data
-    mock_request = MagicMock()
-
-    # Create mock form data with array notation for timestamp_granularities
-    mock_form_data = {
-        "file": "file_object",  # In a real request this would be an UploadFile
-        "model": "gpt-4o-transcribe",
-        "include[]": "logprobs",  # Array notation
-        "language": "en",
-        "prompt": "Transcribe this audio file",
-        "response_format": "json",
-        "stream": "false",
-        "temperature": "0.2",
-        "timestamp_granularities[]": "word",  # First array item
-        "timestamp_granularities[]": "segment",  # Second array item (would overwrite in dict, but handled by the function)
-    }
-
-    # Mock the form method to return the test data
-    mock_request.form = AsyncMock(return_value=mock_form_data)
-
-    # Call the function being tested
-    result = await get_form_data(mock_request)
-
-    # Verify regular form fields are preserved
-    assert result["file"] == "file_object"
-    assert result["model"] == "gpt-4o-transcribe"
-    assert result["language"] == "en"
-    assert result["prompt"] == "Transcribe this audio file"
-    assert result["response_format"] == "json"
-    assert result["stream"] == "false"
-    assert result["temperature"] == "0.2"
-
-    # Verify array fields are correctly parsed
-    assert "include" in result
-    assert isinstance(result["include"], list)
-    assert "logprobs" in result["include"]
-
-    assert "timestamp_granularities" in result
-    assert isinstance(result["timestamp_granularities"], list)
-    # Note: In a real MultiDict, both values would be present
-    # But in our mock dictionary the second value overwrites the first
-    assert "segment" in result["timestamp_granularities"]

tests/llm_translation/base_llm_unit_tests.py

@@ -947,8 +947,6 @@ class BaseLLMChatTest(ABC):
                 second_response.choices[0].message.content is not None
                 or second_response.choices[0].message.tool_calls is not None
             )
-        except litellm.ServiceUnavailableError:
-            pytest.skip("Model is overloaded")
         except litellm.InternalServerError:
             pytest.skip("Model is overloaded")
         except litellm.RateLimitError:

tests/openai_endpoints_tests/test_e2e_openai_responses_api.py

@@ -77,22 +77,6 @@ def test_basic_response():
     )
     print("basic response=", response)
 
-    # get the response
-    response = client.responses.retrieve(response.id)
-    print("GET response=", response)
-
-
-    # delete the response
-    delete_response = client.responses.delete(response.id)
-    print("DELETE response=", delete_response)
-
-    # try getting the response again, we should not get it back 
-    get_response = client.responses.retrieve(response.id)
-    print("GET response after delete=", get_response)
-
-    with pytest.raises(Exception):
-        get_response = client.responses.retrieve(response.id)
-
 
 def test_streaming_response():
     client = get_test_client()

tests/router_unit_tests/test_router_endpoints.py

@@ -6,7 +6,7 @@ from typing import Optional
 from dotenv import load_dotenv
 from fastapi import Request
 from datetime import datetime
-from unittest.mock import AsyncMock, patch, MagicMock
+from unittest.mock import AsyncMock, patch
 
 sys.path.insert(
     0, os.path.abspath("../..")
@@ -553,67 +553,9 @@ def test_initialize_router_endpoints():
     assert hasattr(router, "aanthropic_messages")
     assert hasattr(router, "aresponses")
     assert hasattr(router, "responses")
-    assert hasattr(router, "aget_responses")
+
-    assert hasattr(router, "adelete_responses")
     # Verify the endpoints are callable
     assert callable(router.amoderation)
     assert callable(router.aanthropic_messages)
     assert callable(router.aresponses)
     assert callable(router.responses)
-    assert callable(router.aget_responses)
-    assert callable(router.adelete_responses)
-
-
-@pytest.mark.asyncio
-async def test_init_responses_api_endpoints():
-    """
-    A simpler test for _init_responses_api_endpoints that focuses on the basic functionality
-    """
-    from litellm.responses.utils import ResponsesAPIRequestUtils
-    # Create a router with a basic model
-    router = Router(
-        model_list=[
-            {
-                "model_name": "test-model",
-                "litellm_params": {
-                    "model": "openai/test-model",
-                    "api_key": "fake-api-key",
-                },
-            }
-        ]
-    )
-    
-    # Just mock the _ageneric_api_call_with_fallbacks method
-    router._ageneric_api_call_with_fallbacks = AsyncMock()
-    
-    # Add a mock implementation of _get_model_id_from_response_id to the Router instance
-    ResponsesAPIRequestUtils.get_model_id_from_response_id = MagicMock(return_value=None)
-    
-    # Call without a response_id (no model extraction should happen)
-    await router._init_responses_api_endpoints(
-        original_function=AsyncMock(),
-        thread_id="thread_xyz"
-    )
-    
-    # Verify _ageneric_api_call_with_fallbacks was called but model wasn't changed
-    first_call_kwargs = router._ageneric_api_call_with_fallbacks.call_args.kwargs
-    assert "model" not in first_call_kwargs
-    assert first_call_kwargs["thread_id"] == "thread_xyz"
-    
-    # Reset the mock
-    router._ageneric_api_call_with_fallbacks.reset_mock()
-    
-    # Change the return value for the second call
-    ResponsesAPIRequestUtils.get_model_id_from_response_id.return_value = "claude-3-sonnet"
-    
-    # Call with a response_id
-    await router._init_responses_api_endpoints(
-        original_function=AsyncMock(),
-        response_id="resp_claude_123"
-    )
-    
-    # Verify model was updated in the kwargs
-    second_call_kwargs = router._ageneric_api_call_with_fallbacks.call_args.kwargs
-    assert second_call_kwargs["model"] == "claude-3-sonnet"
-    assert second_call_kwargs["response_id"] == "resp_claude_123"
-

tests/router_unit_tests/test_router_helper_utils.py

@@ -1157,14 +1157,3 @@ def test_cached_get_model_group_info(model_list):
     # Verify the cache info shows hits
     cache_info = router._cached_get_model_group_info.cache_info()
     assert cache_info.hits > 0  # Should have at least one cache hit
-
-
-def test_init_responses_api_endpoints(model_list):
-    """Test if the '_init_responses_api_endpoints' function is working correctly"""
-    from typing import Callable
-    router = Router(model_list=model_list)
-
-    assert router.aget_responses is not None
-    assert isinstance(router.aget_responses, Callable)
-    assert router.adelete_responses is not None
-    assert isinstance(router.adelete_responses, Callable)

ui/litellm-dashboard/src/app/page.tsx

@@ -151,7 +151,7 @@ export default function CreateKeyPage() {
     if (redirectToLogin) {
       window.location.href = (proxyBaseUrl || "") + "/sso/key/generate"
     }
-  }, [redirectToLogin])
+  }, [token, authLoading])
 
   useEffect(() => {
     if (!token) {
@@ -223,7 +223,7 @@ export default function CreateKeyPage() {
     }
   }, [accessToken, userID, userRole]);
 
-  if (authLoading || redirectToLogin) {
+  if (authLoading) {
     return <LoadingScreen />
   }
 

ui/litellm-dashboard/src/components/all_keys_table.tsx

@@ -450,8 +450,6 @@ export function AllKeysTable({
               columns={columns.filter(col => col.id !== 'expander') as any}
               data={filteredKeys as any}
               isLoading={isLoading}
-              loadingMessage="🚅 Loading keys..."
-              noDataMessage="No keys found"
               getRowCanExpand={() => false}
               renderSubComponent={() => <></>}
             />

ui/litellm-dashboard/src/components/mcp_tools/index.tsx

@@ -26,8 +26,6 @@ function DataTableWrapper({
       isLoading={isLoading}
       renderSubComponent={renderSubComponent}
       getRowCanExpand={getRowCanExpand}
-      loadingMessage="🚅 Loading tools..."
-      noDataMessage="No tools found"
     />
   );
 }

ui/litellm-dashboard/src/components/view_logs/table.tsx

@@ -26,8 +26,6 @@ interface DataTableProps<TData, TValue> {
   expandedRequestId?: string | null;
   onRowExpand?: (requestId: string | null) => void;
   setSelectedKeyIdInfoView?: (keyId: string | null) => void;
-  loadingMessage?: string;
-  noDataMessage?: string;
 }
 
 export function DataTable<TData extends { request_id: string }, TValue>({
@@ -38,8 +36,6 @@ export function DataTable<TData extends { request_id: string }, TValue>({
   isLoading = false,
   expandedRequestId,
   onRowExpand,
-  loadingMessage = "🚅 Loading logs...",
-  noDataMessage = "No logs found",
 }: DataTableProps<TData, TValue>) {
   const table = useReactTable({
     data,
@@ -118,7 +114,7 @@ export function DataTable<TData extends { request_id: string }, TValue>({
             <TableRow>
               <TableCell colSpan={columns.length} className="h-8 text-center">
                 <div className="text-center text-gray-500">
-                  <p>{loadingMessage}</p>
+                  <p>🚅 Loading logs...</p>
                 </div>
               </TableCell>
             </TableRow>
@@ -151,7 +147,7 @@ export function DataTable<TData extends { request_id: string }, TValue>({
           : <TableRow>
               <TableCell colSpan={columns.length} className="h-8 text-center">
                 <div className="text-center text-gray-500">
-                  <p>{noDataMessage}</p>
+                  <p>No logs found</p>
                 </div>
               </TableCell>
             </TableRow>