fix(mavvrik_focus): guard against malformed Tags JSON in token merge

json.loads on the existing Tags value had no error handling; a
malformed value would raise JSONDecodeError and abort the entire
export window instead of just skipping that row's token merge.

litellm/integrations/mavvrik_focus/mavvrik_focus_logger.py

@@ -60,7 +60,10 @@ def _with_token_tags(data: pl.DataFrame, normalized: pl.DataFrame) -> pl.DataFra
     has_both = "prompt_tokens" in available and "completion_tokens" in available
 
     def _merge(tags_json: str, row: dict) -> str:
-        tags = json.loads(tags_json) if tags_json else {}
+        try:
+            tags = json.loads(tags_json) if tags_json else {}
+        except (TypeError, ValueError):
+            tags = {}
         for key in available:
             value = row.get(key)
             if value is not None:

tests/test_litellm/integrations/mavvrik_focus/test_mavvrik_focus_logger.py

@@ -88,6 +88,20 @@ def test_with_token_tags_merges_prompt_and_completion_tokens() -> None:
     }
 
 
+def test_with_token_tags_recovers_from_malformed_tags_json() -> None:
+    data = pl.DataFrame({"prompt_tokens": [57], "completion_tokens": [753]})
+    normalized = pl.DataFrame({"Tags": ["not-valid-json"]})
+
+    result = _with_token_tags(data, normalized)
+
+    tags = json.loads(result["Tags"][0])
+    assert tags == {
+        "prompt_tokens": "57",
+        "completion_tokens": "753",
+        "total_tokens": "810",
+    }
+
+
 def test_with_token_tags_omits_total_when_only_one_token_column_present() -> None:
     data = pl.DataFrame({"prompt_tokens": [57]})
     normalized = pl.DataFrame({"Tags": [json.dumps({"model": "azure/gpt-4o-mini"})]})