diff --git a/litellm/integrations/prompt_layer.py b/litellm/integrations/prompt_layer.py
index 4bf2089de2..39a80940b7 100644
--- a/litellm/integrations/prompt_layer.py
+++ b/litellm/integrations/prompt_layer.py
@@ -2,12 +2,11 @@
 #    On success, logs events to Promptlayer
 import dotenv, os
 import requests
-import requests
+from pydantic import BaseModel
 
 dotenv.load_dotenv()  # Loading env variables using dotenv
 import traceback
 
-
 class PromptLayerLogger:
     # Class variables or attributes
     def __init__(self):
@@ -25,16 +24,30 @@ class PromptLayerLogger:
             for optional_param in kwargs["optional_params"]:
                 new_kwargs[optional_param] = kwargs["optional_params"][optional_param]
 
+            # Extract PromptLayer tags from metadata, if such exists
+            tags = []
+            metadata = {}
+            if "metadata" in kwargs["litellm_params"]:
+                if "pl_tags" in kwargs["litellm_params"]["metadata"]:
+                    tags = kwargs["litellm_params"]["metadata"]["pl_tags"]
+
+                # Remove "pl_tags" from metadata
+                metadata = {k:v for k, v in kwargs["litellm_params"]["metadata"].items() if k != "pl_tags"}
+
             print_verbose(
                 f"Prompt Layer Logging - Enters logging function for model kwargs: {new_kwargs}\n, response: {response_obj}"
             )
 
+            # python-openai >= 1.0.0 returns Pydantic objects instead of jsons
+            if isinstance(response_obj, BaseModel):
+                response_obj = response_obj.model_dump()
+
             request_response = requests.post(
                 "https://api.promptlayer.com/rest/track-request",
                 json={
                     "function_name": "openai.ChatCompletion.create",
                     "kwargs": new_kwargs,
-                    "tags": ["hello", "world"],
+                    "tags": tags,
                     "request_response": dict(response_obj),
                     "request_start_time": int(start_time.timestamp()),
                     "request_end_time": int(end_time.timestamp()),
@@ -45,22 +58,23 @@ class PromptLayerLogger:
                     # "prompt_version":1,
                 },
             )
+
+            response_json = request_response.json()
+            if not request_response.json().get("success", False):
+                raise Exception("Promptlayer did not successfully log the response!")
+
             print_verbose(
                 f"Prompt Layer Logging: success - final response object: {request_response.text}"
             )
-            response_json = request_response.json()
-            if "success" not in request_response.json():
-                raise Exception("Promptlayer did not successfully log the response!")
 
             if "request_id" in response_json:
-                print(kwargs["litellm_params"]["metadata"])
-                if kwargs["litellm_params"]["metadata"] is not None:
+                if metadata:
                     response = requests.post(
                         "https://api.promptlayer.com/rest/track-metadata",
                         json={
                             "request_id": response_json["request_id"],
                             "api_key": self.key,
-                            "metadata": kwargs["litellm_params"]["metadata"],
+                            "metadata": metadata,
                         },
                     )
                     print_verbose(
diff --git a/litellm/tests/test_promptlayer_integration.py b/litellm/tests/test_promptlayer_integration.py
index 9f0af1af8d..e869aa5515 100644
--- a/litellm/tests/test_promptlayer_integration.py
+++ b/litellm/tests/test_promptlayer_integration.py
@@ -7,11 +7,12 @@ sys.path.insert(0, os.path.abspath("../.."))
 from litellm import completion
 import litellm
 
+import pytest
+
 litellm.success_callback = ["promptlayer"]
 litellm.set_verbose = True
 import time
 
-
 # def test_promptlayer_logging():
 #     try:
 #         # Redirect stdout
@@ -58,15 +59,41 @@ def test_promptlayer_logging_with_metadata():
         sys.stdout = old_stdout
         output = new_stdout.getvalue().strip()
         print(output)
-        if "LiteLLM: Prompt Layer Logging: success" not in output:
-            raise Exception("Required log message not found!")
+
+        assert "Prompt Layer Logging: success" in output
 
     except Exception as e:
-        print(e)
+        pytest.fail(f"Error occurred: {e}")
 
 
+def test_promptlayer_logging_with_metadata_tags():
+    try:
+        # Redirect stdout
+        old_stdout = sys.stdout
+        sys.stdout = new_stdout = io.StringIO()
+
+        response = completion(
+            model="gpt-3.5-turbo",
+            messages=[{"role": "user", "content": "Hi 👋 - i'm ai21"}],
+            temperature=0.2,
+            max_tokens=20,
+            metadata={"model": "ai21", "pl_tags": ["env:dev"]},
+            mock_response="this is a mock response"
+        )
+
+        # Restore stdout
+        time.sleep(1)
+        sys.stdout = old_stdout
+        output = new_stdout.getvalue().strip()
+        print(output)
+
+        assert "Prompt Layer Logging: success" in output
+
+    except Exception as e:
+        pytest.fail(f"Error occurred: {e}")
+
 test_promptlayer_logging_with_metadata()
-
+test_promptlayer_logging_with_metadata_tags()
 
 # def test_chat_openai():
 #     try: