Merge pull request #3424 from lunary-ai/main

Fix tool calls tracking with Lunary

litellm/integrations/lunary.py

@@ -4,7 +4,6 @@ from datetime import datetime, timezone
 import traceback
 import dotenv
 import importlib
-import sys
 
 import packaging
 
@@ -18,13 +17,33 @@ def parse_usage(usage):
         "prompt": usage["prompt_tokens"] if "prompt_tokens" in usage else 0,
     }
 
+def parse_tool_calls(tool_calls):
+    if tool_calls is None:
+        return None
+
+    def clean_tool_call(tool_call):
+
+        serialized = {
+            "type": tool_call.type,
+            "id": tool_call.id,
+            "function": {
+                "name": tool_call.function.name,
+                "arguments": tool_call.function.arguments,
+            }
+        }
+
+        return serialized
+    
+    return [clean_tool_call(tool_call) for tool_call in tool_calls]
+    
 
 def parse_messages(input):
+
     if input is None:
         return None
 
     def clean_message(message):
-        # if is strin, return as is
+        # if is string, return as is
         if isinstance(message, str):
             return message
 
@@ -38,9 +57,7 @@ def parse_messages(input):
 
         # Only add tool_calls and function_call to res if they are set
         if message.get("tool_calls"):
-            serialized["tool_calls"] = message.get("tool_calls")
-        if message.get("function_call"):
-            serialized["function_call"] = message.get("function_call")
+            serialized["tool_calls"] = parse_tool_calls(message.get("tool_calls"))
 
         return serialized
 
@@ -93,8 +110,13 @@ class LunaryLogger:
             print_verbose(f"Lunary Logging - Logging request for model {model}")
 
             litellm_params = kwargs.get("litellm_params", {})
+            optional_params = kwargs.get("optional_params", {})
             metadata = litellm_params.get("metadata", {}) or {}
 
+            if optional_params:
+                # merge into extra
+                extra = {**extra, **optional_params}
+
             tags = litellm_params.pop("tags", None) or []
 
             if extra:
@@ -104,7 +126,7 @@ class LunaryLogger:
 
             # keep only serializable types
             for param, value in extra.items():
-                if not isinstance(value, (str, int, bool, float)):
+                if not isinstance(value, (str, int, bool, float)) and param != "tools":
                     try:
                         extra[param] = str(value)
                     except:
@@ -140,7 +162,7 @@ class LunaryLogger:
                 metadata=metadata,
                 runtime="litellm",
                 tags=tags,
-                extra=extra,
+                params=extra,
             )
 
             self.lunary_client.track_event(

litellm/tests/test_lunary.py

@@ -11,7 +11,6 @@ litellm.failure_callback = ["lunary"]
 litellm.success_callback = ["lunary"]
 litellm.set_verbose = True
 
-
 def test_lunary_logging():
     try:
         response = completion(
@@ -59,9 +58,46 @@ def test_lunary_logging_with_metadata():
     except Exception as e:
         print(e)
 
+#test_lunary_logging_with_metadata()
 
-# test_lunary_logging_with_metadata()
+def test_lunary_with_tools():
 
+    import litellm
+
+    messages = [{"role": "user", "content": "What's the weather like in San Francisco, Tokyo, and Paris?"}]
+    tools = [
+        {
+            "type": "function",
+            "function": {
+                "name": "get_current_weather",
+                "description": "Get the current weather in a given location",
+                "parameters": {
+                    "type": "object",
+                    "properties": {
+                        "location": {
+                            "type": "string",
+                            "description": "The city and state, e.g. San Francisco, CA",
+                        },
+                        "unit": {"type": "string", "enum": ["celsius", "fahrenheit"]},
+                    },
+                    "required": ["location"],
+                },
+            },
+        }
+    ]
+
+    response = litellm.completion(
+        model="gpt-3.5-turbo-1106",
+        messages=messages,
+        tools=tools,
+        tool_choice="auto",  # auto is default, but we'll be explicit
+    )
+    
+    response_message = response.choices[0].message
+    print("\nLLM Response:\n", response.choices[0].message)
+
+
+#test_lunary_with_tools()
 
 def test_lunary_logging_with_streaming_and_metadata():
     try: