fix alert types

Author: Mandolaro

src/judgeval/common/tracer.py

@@ -18,7 +18,7 @@
 import json
 from contextlib import contextmanager, asynccontextmanager, AbstractAsyncContextManager, AbstractContextManager # Import context manager bases
 from dataclasses import dataclass, field
-from datetime import datetime
+from datetime import datetime, timezone
 from http import HTTPStatus
 from typing import (
     Any,
@@ -594,7 +594,7 @@ def save(self, overwrite: bool = False) -> Tuple[str, dict]:
             "trace_id": self.trace_id,
             "name": self.name,
             "project_name": self.project_name,
-            "created_at": datetime.utcfromtimestamp(self.start_time).isoformat(),
+            "created_at": datetime.fromtimestamp(self.start_time, timezone.utc).isoformat(),
             "duration": total_duration,
             "trace_spans": [span.model_dump() for span in self.trace_spans],
             "evaluation_runs": [run.model_dump() for run in self.evaluation_runs],

src/judgeval/rules.py

@@ -142,7 +142,8 @@ def model_dump(self, **kwargs):
                     # Create standardized metric representation needed by server API
                     metric_data = {
                         "score_type": "",
-                        "threshold": 0.0
+                        "threshold": 0.0,
+                        "name": ""
                     }
 
                     # First try to use object's own serialization methods
@@ -180,6 +181,16 @@ def model_dump(self, **kwargs):
                             # Use condition threshold if metric doesn't have one
                             metric_data['threshold'] = self.conditions[i].threshold
 
+                    # Make sure name is set
+                    if not metric_data.get('name'):
+                        if hasattr(metric_obj, '__name__'):
+                            metric_data['name'] = metric_obj.__name__
+                        elif hasattr(metric_obj, 'name'):
+                            metric_data['name'] = metric_obj.name
+                        else:
+                            # Fallback to score_type if available
+                            metric_data['name'] = metric_data.get('score_type', str(metric_obj))
+                    
                     # Update the condition with our properly serialized metric
                     condition["metric"] = metric_data