diff --git a/litellm/integrations/helicone.py b/litellm/integrations/helicone.py
index f9dff85dbf3..cb866377324 100644
--- a/litellm/integrations/helicone.py
+++ b/litellm/integrations/helicone.py
@@ -2,6 +2,7 @@
 #    On success, logs events to Helicone
 import dotenv, os
 import requests
+import litellm
 
 dotenv.load_dotenv()  # Loading env variables using dotenv
 import traceback
@@ -56,6 +57,10 @@ class HeliconeLogger:
                 else "gpt-3.5-turbo"
             )
             provider_request = {"model": model, "messages": messages}
+            if isinstance(response_obj, litellm.EmbeddingResponse) or isinstance(
+                response_obj, litellm.ModelResponse
+            ):
+                response_obj = response_obj.json()
 
             if "claude" in model:
                 provider_request, response_obj = self.claude_mapping(
diff --git a/litellm/utils.py b/litellm/utils.py
index eb124f9ba85..9b0594716ab 100644
--- a/litellm/utils.py
+++ b/litellm/utils.py
@@ -1269,7 +1269,7 @@ class Logging:
                     if callback == "helicone":
                         print_verbose("reaches helicone for logging!")
                         model = self.model
-                        messages = kwargs["messages"]
+                        messages = kwargs["input"]
                         heliconeLogger.log_success(
                             model=model,
                             messages=messages,