diff --git a/litellm/main.py b/litellm/main.py
index 4e53f99258..64049c31d1 100644
--- a/litellm/main.py
+++ b/litellm/main.py
@@ -5487,7 +5487,9 @@ async def ahealth_check(
         model_params["litellm_logging_obj"] = litellm_logging_obj
 
         mode_handlers = {
-            "chat": lambda: litellm.acompletion(**model_params),
+            "chat": lambda: litellm.acompletion(
+                **model_params,
+            ),
             "completion": lambda: litellm.atext_completion(
                 **_filter_model_params(model_params),
                 prompt=prompt or "test",
@@ -5544,12 +5546,7 @@ async def ahealth_check(
                 "error": f"error:{str(e)}. Missing `mode`. Set the `mode` for the model - https://docs.litellm.ai/docs/proxy/health#embedding-models  \nstacktrace: {stack_trace}"
             }
 
-        error_to_return = (
-            str(e)
-            + "\nHave you set 'mode' - https://docs.litellm.ai/docs/proxy/health#embedding-models"
-            + "\nstack trace: "
-            + stack_trace
-        )
+        error_to_return = str(e) + "\nstack trace: " + stack_trace
 
         raw_request_typed_dict = litellm_logging_obj.model_call_details.get(
             "raw_request_typed_dict"
diff --git a/litellm/proxy/health_endpoints/_health_endpoints.py b/litellm/proxy/health_endpoints/_health_endpoints.py
index d269bcf84a..378c94aacb 100644
--- a/litellm/proxy/health_endpoints/_health_endpoints.py
+++ b/litellm/proxy/health_endpoints/_health_endpoints.py
@@ -3,13 +3,14 @@ import copy
 import os
 import traceback
 from datetime import datetime, timedelta
-from typing import Literal, Optional, Union
+from typing import Any, Dict, Literal, Optional, Union
 
 import fastapi
 from fastapi import APIRouter, Depends, HTTPException, Request, Response, status
 
 import litellm
 from litellm._logging import verbose_proxy_logger
+from litellm.constants import HEALTH_CHECK_TIMEOUT_SECONDS
 from litellm.proxy._types import (
     AlertType,
     CallInfo,
@@ -21,6 +22,7 @@ from litellm.proxy._types import (
 from litellm.proxy.auth.user_api_key_auth import user_api_key_auth
 from litellm.proxy.health_check import (
     _clean_endpoint_data,
+    _update_litellm_params_for_health_check,
     perform_health_check,
     run_with_timeout,
 )
@@ -626,9 +628,9 @@ async def test_model_connection(
             "realtime",
         ]
     ] = fastapi.Body("chat", description="The mode to test the model with"),
-    prompt: Optional[str] = fastapi.Body(None, description="Test prompt for the model"),
-    timeout: Optional[int] = fastapi.Body(
-        30, description="Timeout in seconds for the health check"
+    litellm_params: Dict = fastapi.Body(
+        None,
+        description="Parameters for litellm.completion, litellm.embedding for the health check",
     ),
     user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth),
 ):
@@ -644,10 +646,14 @@ async def test_model_connection(
       -H 'Authorization: Bearer sk-1234' \\
       -H 'Content-Type: application/json' \\
       -d '{
-        "model": "openai/gpt-3.5-turbo",
-        "mode": "chat",
-        "prompt": "Hello, world!",
-        "timeout": 30
+        "litellm_params": {
+            "model": "gpt-4",
+            "custom_llm_provider": "azure_ai",
+            "litellm_credential_name": null,
+            "api_key": "6xxxxxxx",
+            "api_base": "https://litellm8397336933.openai.azure.com/openai/deployments/gpt-4o/chat/completions?api-version=2024-10-21",
+        },
+        "mode": "chat"
       }'
     ```
     
@@ -655,23 +661,26 @@ async def test_model_connection(
         dict: A dictionary containing the health check result with either success information or error details.
     """
     try:
-        # Create basic params for the model
-        model_params = await request.json()
-        model_params.pop("mode")
-
-        # Run the health check with timeout
+        # Include health_check_params if provided
+        litellm_params = _update_litellm_params_for_health_check(
+            model_info={},
+            litellm_params=litellm_params,
+        )
+        mode = mode or litellm_params.pop("mode", None)
         result = await run_with_timeout(
             litellm.ahealth_check(
-                model_params,
+                model_params=litellm_params,
                 mode=mode,
-                prompt=prompt,
-                input=[prompt] if prompt else ["test from litellm"],
+                prompt="test from litellm",
+                input=["test from litellm"],
             ),
-            timeout,
+            HEALTH_CHECK_TIMEOUT_SECONDS,
         )
 
         # Clean the result for display
-        cleaned_result = _clean_endpoint_data({**model_params, **result}, details=True)
+        cleaned_result = _clean_endpoint_data(
+            {**litellm_params, **result}, details=True
+        )
 
         return {
             "status": "error" if "error" in result else "success",