diff --git a/litellm/llms/openai.py b/litellm/llms/openai.py
index 01887616c..da89b7796 100644
--- a/litellm/llms/openai.py
+++ b/litellm/llms/openai.py
@@ -718,8 +718,22 @@ class OpenAIChatCompletion(BaseLLM):
             return convert_to_model_response_object(response_object=response, model_response_object=model_response, response_type="image_generation")  # type: ignore
         except OpenAIError as e:
             exception_mapping_worked = True
+            ## LOGGING
+            logging_obj.post_call(
+                input=prompt,
+                api_key=api_key,
+                additional_args={"complete_input_dict": data},
+                original_response=str(e),
+            )
             raise e
         except Exception as e:
+            ## LOGGING
+            logging_obj.post_call(
+                input=prompt,
+                api_key=api_key,
+                additional_args={"complete_input_dict": data},
+                original_response=str(e),
+            )
             if hasattr(e, "status_code"):
                 raise OpenAIError(status_code=e.status_code, message=str(e))
             else:
diff --git a/litellm/main.py b/litellm/main.py
index df5982c9c..b6fb15f1a 100644
--- a/litellm/main.py
+++ b/litellm/main.py
@@ -3076,7 +3076,7 @@ def image_generation(
             custom_llm_provider=custom_llm_provider,
             **non_default_params,
         )
-        logging = litellm_logging_obj
+        logging: Logging = litellm_logging_obj
         logging.update_environment_variables(
             model=model,
             user=user,
diff --git a/litellm/tests/test_custom_callback_input.py b/litellm/tests/test_custom_callback_input.py
index a61cc843e..266303df1 100644
--- a/litellm/tests/test_custom_callback_input.py
+++ b/litellm/tests/test_custom_callback_input.py
@@ -819,47 +819,49 @@ async def test_async_embedding_azure_caching():
 # Image Generation
 
 
-# ## Test OpenAI + Sync
-# def test_image_generation_openai():
-#     try:
-#         customHandler_success = CompletionCustomHandler()
-#         customHandler_failure = CompletionCustomHandler()
-#         litellm.callbacks = [customHandler_success]
+## Test OpenAI + Sync
+def test_image_generation_openai():
+    try:
+        customHandler_success = CompletionCustomHandler()
+        customHandler_failure = CompletionCustomHandler()
+        # litellm.callbacks = [customHandler_success]
 
-#         litellm.set_verbose = True
+        # litellm.set_verbose = True
 
-#         response = litellm.image_generation(
-#             prompt="A cute baby sea otter", model="dall-e-3"
-#         )
+        # response = litellm.image_generation(
+        #     prompt="A cute baby sea otter", model="dall-e-3"
+        # )
 
-#         print(f"response: {response}")
-#         assert len(response.data) > 0
+        # print(f"response: {response}")
+        # assert len(response.data) > 0
 
-#         print(f"customHandler_success.errors: {customHandler_success.errors}")
-#         print(f"customHandler_success.states: {customHandler_success.states}")
-#         assert len(customHandler_success.errors) == 0
-#         assert len(customHandler_success.states) == 3  # pre, post, success
-#         # test failure callback
-#         litellm.callbacks = [customHandler_failure]
-#         try:
-#             response = litellm.image_generation(
-#                 prompt="A cute baby sea otter", model="dall-e-4"
-#             )
-#         except:
-#             pass
-#         print(f"customHandler_failure.errors: {customHandler_failure.errors}")
-#         print(f"customHandler_failure.states: {customHandler_failure.states}")
-#         assert len(customHandler_failure.errors) == 0
-#         assert len(customHandler_failure.states) == 3  # pre, post, failure
-#     except litellm.RateLimitError as e:
-#         pass
-#     except litellm.ContentPolicyViolationError:
-#         pass  # OpenAI randomly raises these errors - skip when they occur
-#     except Exception as e:
-#         pytest.fail(f"An exception occurred - {str(e)}")
+        # print(f"customHandler_success.errors: {customHandler_success.errors}")
+        # print(f"customHandler_success.states: {customHandler_success.states}")
+        # assert len(customHandler_success.errors) == 0
+        # assert len(customHandler_success.states) == 3  # pre, post, success
+        # test failure callback
+        litellm.callbacks = [customHandler_failure]
+        try:
+            response = litellm.image_generation(
+                prompt="A cute baby sea otter",
+                model="dall-e-2",
+                api_key="my-bad-api-key",
+            )
+        except:
+            pass
+        print(f"customHandler_failure.errors: {customHandler_failure.errors}")
+        print(f"customHandler_failure.states: {customHandler_failure.states}")
+        assert len(customHandler_failure.errors) == 0
+        assert len(customHandler_failure.states) == 3  # pre, post, failure
+    except litellm.RateLimitError as e:
+        pass
+    except litellm.ContentPolicyViolationError:
+        pass  # OpenAI randomly raises these errors - skip when they occur
+    except Exception as e:
+        pytest.fail(f"An exception occurred - {str(e)}")
 
 
-# test_image_generation_openai()
+test_image_generation_openai()
 ## Test OpenAI + Async
 
 ## Test Azure + Sync
diff --git a/litellm/utils.py b/litellm/utils.py
index d8f535ca4..ed86f2fae 100644
--- a/litellm/utils.py
+++ b/litellm/utils.py
@@ -2030,14 +2030,15 @@ def client(original_function):
                 start_time=start_time,
             )
             ## check if metadata is passed in
+            litellm_params = {}
             if "metadata" in kwargs:
-                litellm_params = {"metadata": kwargs["metadata"]}
-                logging_obj.update_environment_variables(
-                    model=model,
-                    user="",
-                    optional_params={},
-                    litellm_params=litellm_params,
-                )
+                litellm_params["metadata"] = kwargs["metadata"]
+            logging_obj.update_environment_variables(
+                model=model,
+                user="",
+                optional_params={},
+                litellm_params=litellm_params,
+            )
             return logging_obj
         except Exception as e:
             import logging