fix promptlayer logging

litellm/integrations/prompt_layer.py

@@ -17,8 +17,11 @@ class PromptLayerLogger:
     def log_event(self, kwargs, response_obj, start_time, end_time, print_verbose):
         # Method definition
         try:
+            if 'litellm_logging_obj' in kwargs:
+                kwargs.pop('litellm_logging_obj')
+
             print_verbose(
-                f"Prompt Layer Logging - Enters logging function for model {kwargs}"
+                f"Prompt Layer Logging - Enters logging function for model kwargs: {kwargs}\n, response: {response_obj}"
             )
 
             request_response = requests.post(
@@ -27,9 +30,7 @@ class PromptLayerLogger:
                     "function_name": "openai.ChatCompletion.create",
                     "kwargs": kwargs,
                     "tags": ["hello", "world"],
-                    "request_response": dict(
+                    "request_response": dict(response_obj),
-                        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,
@@ -39,11 +40,9 @@ class PromptLayerLogger:
                     # "prompt_version":1,
                 },
             )
-
             print_verbose(
-                f"Prompt Layer Logging - final response object: {request_response}"
+                f"Prompt Layer Logging: success - final response object: {request_response}"
             )
         except:
-            # traceback.print_exc()
+            print_verbose(f"error: Prompt Layer Error - {traceback.format_exc()}")
-            print_verbose(f"Prompt Layer Error - {traceback.format_exc()}")
             pass

litellm/tests/test_promptlayer_integration.py

@@ -1,37 +1,48 @@
-#### What this tests ####
+import sys
-#    This tests if logging to the llmonitor integration actually works
+import os
-# Adds the parent directory to the system path
+import io
-# import sys
-# import os
 
-# sys.path.insert(0, os.path.abspath('../..'))
+sys.path.insert(0, os.path.abspath('../..'))
 
-# from litellm import completion, embedding
+from litellm import completion
-# import litellm
+import litellm
 
-# litellm.success_callback = ["promptlayer"]
+litellm.success_callback = ["promptlayer"]
+litellm.set_verbose = True
+import time
 
 
-# litellm.set_verbose = True
+
+def test_promptlayer_logging():
+    try:
+        # Redirect stdout
+        old_stdout = sys.stdout
+        sys.stdout = new_stdout = io.StringIO()
 
 
-# def test_chat_openai():
+        response = completion(model="claude-instant-1.2",
-#     try:
+                              messages=[{
-#         response = completion(model="gpt-3.5-turbo",
+                                  "role": "user",
-#                               messages=[{
+                                  "content": "Hi 👋 - i'm openai"
-#                                   "role": "user",
+                              }])
-#                                   "content": "Hi 👋 - i'm openai"
-#                               }])
 
-#         print(response)
+        # Restore stdout
+        time.sleep(1)
+        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!")
+
+    except Exception as e:
+        print(e)
+
+test_promptlayer_logging()
 
-#     except Exception as e:
-#         print(e)
 
 
 
 # def test_chat_openai():
-#     litellm.success_callback = ["langfuse"]
 #     try:
 #         response = completion(model="replicate/llama-2-70b-chat:2c1608e18606fad2812020dc541930f2d0495ce32eee50074220b87300bc16e1",
 #                               messages=[{

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "litellm"
-version = "0.1.615"
+version = "0.1.618"
 description = "Library to easily interface with LLM API providers"
 authors = ["BerriAI"]
 license = "MIT License"