updates to litedebugger dashboard

litellm/integrations/litedebugger.py

@@ -6,7 +6,8 @@ class LiteDebugger:
     dashboard_url = None
 
     def __init__(self, email=None):
-        self.api_url = "https://api.litellm.ai/debugger"
+        # self.api_url = "https://api.litellm.ai/debugger"
+        self.api_url = "http://0.0.0.0:4000/debugger"
         self.validate_environment(email)
         pass
 
@@ -88,13 +89,14 @@ class LiteDebugger:
                     headers={"content-type": "application/json"},
                     data=json.dumps(litellm_data_obj),
                 )
-            elif "embedding" in response_obj:
+            elif "data" in response_obj and isinstance(response_obj["data"], list) and len(response_obj["data"]) > 0 and "embedding" in response_obj["data"][0]:
+                print(f"messages: {messages}")
                 litellm_data_obj = {
                     "response_time": response_time,
                     "model": response_obj["model"],
                     "total_cost": total_cost,
                     "messages": messages,
-                    "response": response_obj["embedding"][:5],
+                    "response": str(response_obj["data"][0]["embedding"][:5]),
                     "end_user": end_user,
                     "litellm_call_id": litellm_call_id,
                     "status": "success",

litellm/main.py

@@ -815,7 +815,7 @@ def embedding(
             )
             ## EMBEDDING CALL
             response = openai.Embedding.create(input=input, engine=model)
-            print_verbose(f"response_value: {str(response)[:50]}")
+            print_verbose(f"response_value: {str(response)[:100]}")
         elif model in litellm.open_ai_embedding_models:
             openai.api_type = "openai"
             openai.api_base = "https://api.openai.com/v1"
@@ -833,7 +833,7 @@ def embedding(
             )
             ## EMBEDDING CALL
             response = openai.Embedding.create(input=input, model=model)
-            print_verbose(f"response_value: {str(response)[:50]}")
+            print_verbose(f"response_value: {str(response)[:100]}")
         else:
             args = locals()
             raise ValueError(f"No valid embedding model args passed in - {args}")

litellm/tests/test_embedding.py

@@ -9,7 +9,7 @@ import litellm
 from litellm import embedding, completion
 from infisical import InfisicalClient
 
-# # litellm.set_verbose = True
+litellm.set_verbose = True
 # litellm.secret_manager_client = InfisicalClient(token=os.environ["INFISICAL_TOKEN"])
 
 
@@ -19,6 +19,7 @@ def test_openai_embedding():
             model="text-embedding-ada-002", input=["good morning from litellm"]
         )
         # Add any assertions here to check the response
-        print(f"response: {str(response)}")
+        # print(f"response: {str(response)}")
     except Exception as e:
         pytest.fail(f"Error occurred: {e}")
+test_openai_embedding()

litellm/utils.py

@@ -899,7 +899,7 @@ def handle_failure(exception, traceback_exception, start_time, end_time, args,
                     print_verbose("reaches lite_debugger for logging!")
                     print_verbose(f"liteDebuggerClient: {liteDebuggerClient}")
                     model = args[0] if len(args) > 0 else kwargs["model"]
-                    messages = args[1] if len(args) > 1 else kwargs.get("messages", {"role": "user", "content": kwargs.get("input", "")})
+                    messages = args[1] if len(args) > 1 else kwargs.get("messages", [{"role": "user", "content": ' '.join(kwargs.get("input", ""))}])
                     result = {
                         "model": model,
                         "created": time.time(),
@@ -1031,7 +1031,7 @@ def handle_success(args, kwargs, result, start_time, end_time):
                 elif callback == "lite_debugger":
                     print_verbose("reaches lite_debugger for logging!")
                     print_verbose(f"liteDebuggerClient: {liteDebuggerClient}")
-                    messages = args[1] if len(args) > 1 else kwargs.get("messages", {"role": "user", "content": kwargs.get("input")}) 
+                    messages = args[1] if len(args) > 1 else kwargs.get("messages", [{"role": "user", "content": ' '.join(kwargs.get("input", ""))}])
                     liteDebuggerClient.log_event(
                         model=model,
                         messages=messages,

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "litellm"
-version = "0.1.459"
+version = "0.1.460"
 description = "Library to easily interface with LLM API providers"
 authors = ["BerriAI"]
 license = "MIT License"