diff --git a/litellm/integrations/prompt_layer.py b/litellm/integrations/prompt_layer.py
index 783434e8f..e1cdb666e 100644
--- a/litellm/integrations/prompt_layer.py
+++ b/litellm/integrations/prompt_layer.py
@@ -1,5 +1,5 @@
 #### What this does ####
-#    On success, logs events to Helicone
+#    On success, logs events to Promptlayer
 import dotenv, os
 import requests
 import requests
@@ -7,32 +7,34 @@ import requests
 dotenv.load_dotenv()  # Loading env variables using dotenv
 import traceback
 
-class PromptLayer:
+class PromptLayerLogger:
     # Class variables or attributes
     def __init__(self):
         # Instance variables
         self.key = os.getenv("PROMPTLAYER_API_KEY")
 
-    def log_event(self, model, response_obj, start_time, end_time, print_verbose):
+    def log_event(self, kwargs, response_obj, start_time, end_time, print_verbose):
         # Method definition
         try:
             print_verbose(
-                f"Prompt Layer Logging - Enters logging function for model {model}"
+                f"Prompt Layer Logging - Enters logging function for model {kwargs}"
             )
 
             request_response = requests.post(
-            "https://api.promptlayer.com/rest/track-request",
+                "https://api.promptlayer.com/rest/track-request",
                 json={
-                    "function_name": "openai.Completion.create",
-                    "kwargs": {"engine": "text-ada-001", "prompt": "My name is"},
+                    "function_name": "openai.ChatCompletion.create",
+                    "kwargs": kwargs,
                     "tags": ["hello", "world"],
-                    "request_response": response_obj,
-                    "request_start_time": start_time,
-                    "request_end_time": end_time,
-                    "prompt_id": "<PROMPT ID>",
-                    "prompt_input_variables": "<Dictionary of variables for prompt>",
-                    "prompt_version":1,
-                    "api_key": self.key
+                    "request_response": dict(response_obj), # TODO: Check if we need  a dict
+                    "request_start_time": int(start_time.timestamp()),
+                    "request_end_time": int(end_time.timestamp()),
+                    "api_key": self.key,
+                    # Optional params for PromptLayer
+                    # "prompt_id": "<PROMPT ID>",
+                    # "prompt_input_variables": "<Dictionary of variables for prompt>",
+                    # "prompt_version":1,
+
                 },
             )
 
diff --git a/litellm/tests/test_promptlayer_integration.py b/litellm/tests/test_promptlayer_integration.py
new file mode 100644
index 000000000..2a43d5373
--- /dev/null
+++ b/litellm/tests/test_promptlayer_integration.py
@@ -0,0 +1,31 @@
+# #### What this tests ####
+# #    This tests if logging to the llmonitor integration actually works
+# # Adds the parent directory to the system path
+# import sys
+# import os
+
+# sys.path.insert(0, os.path.abspath('../..'))
+
+# from litellm import completion, embedding
+# import litellm
+
+# litellm.success_callback = ["promptlayer"]
+
+
+# litellm.set_verbose = True
+
+
+# def test_chat_openai():
+#     try:
+#         response = completion(model="gpt-3.5-turbo",
+#                               messages=[{
+#                                   "role": "user",
+#                                   "content": "Hi 👋 - i'm openai"
+#                               }])
+
+#         print(response)
+
+#     except Exception as e:
+#         print(e)
+
+# # test_chat_openai()
diff --git a/litellm/utils.py b/litellm/utils.py
index 296ec308e..96d094088 100644
--- a/litellm/utils.py
+++ b/litellm/utils.py
@@ -13,6 +13,8 @@ from .integrations.helicone import HeliconeLogger
 from .integrations.aispend import AISpendLogger
 from .integrations.berrispend import BerriSpendLogger
 from .integrations.supabase import Supabase
+from .integrations.llmonitor import LLMonitorLogger
+from .integrations.prompt_layer import PromptLayerLogger
 from .integrations.litedebugger import LiteDebugger
 from openai.error import OpenAIError as OriginalError
 from openai.openai_object import OpenAIObject
@@ -35,6 +37,7 @@ posthog = None
 slack_app = None
 alerts_channel = None
 heliconeLogger = None
+promptLayerLogger = None
 aispendLogger = None
 berrispendLogger = None
 supabaseClient = None
@@ -729,7 +732,7 @@ def load_test_model(
 
 
 def set_callbacks(callback_list):
-    global sentry_sdk_instance, capture_exception, add_breadcrumb, posthog, slack_app, alerts_channel, heliconeLogger, aispendLogger, berrispendLogger, supabaseClient, liteDebuggerClient, llmonitorLogger
+    global sentry_sdk_instance, capture_exception, add_breadcrumb, posthog, slack_app, alerts_channel, heliconeLogger, aispendLogger, berrispendLogger, supabaseClient, liteDebuggerClient, llmonitorLogger, promptLayerLogger
     try:
         for callback in callback_list:
             print_verbose(f"callback: {callback}")
@@ -784,6 +787,8 @@ def set_callbacks(callback_list):
                 heliconeLogger = HeliconeLogger()
             elif callback == "llmonitor":
                 llmonitorLogger = LLMonitorLogger()
+            elif callback == "promptlayer":
+                promptLayerLogger = PromptLayerLogger()
             elif callback == "aispend":
                 aispendLogger = AISpendLogger()
             elif callback == "berrispend":
@@ -1053,6 +1058,16 @@ def handle_success(args, kwargs, result, start_time, end_time):
                         run_id=kwargs["litellm_call_id"],
                         print_verbose=print_verbose,
                     )
+                elif callback == "promptlayer":
+                    print_verbose("reaches promptlayer for logging!")
+                    promptLayerLogger.log_event(
+                        kwargs=kwargs,
+                        response_obj=result,
+                        start_time=start_time,
+                        end_time=end_time,
+                        print_verbose=print_verbose,
+
+                    )
                 elif callback == "aispend":
                     print_verbose("reaches aispend for logging!")
                     model = args[0] if len(args) > 0 else kwargs["model"]