Update app.py

app.py

@@ -675,8 +675,22 @@ def predict_ner_batch(req: BatchNERRequest):
     labels = [l.lower() for l in (req.entity_types or default_types)]
     # GLiNER handles batches natively
     #batch_entities = models["ner"].predict_entities(req.texts, labels)
-    batch_entities = [
-        models["ner"].predict_entities(text, labels) 
-        for text in req.texts
-    ]
+
+    batch_entities = []
+    for text in req.texts:
+        # Force conversion to string and handle empty cases
+        clean_text = str(text or "").strip()
+        if not clean_text:
+            batch_entities.append([])
+            continue
+        try:
+            batch_entities.append(models["ner"].predict_entities(clean_text, labels))
+        except:
+            batch_entities.append([])
+          
+    
+    # batch_entities = [
+    #     models["ner"].predict_entities(text, labels) 
+    #     for text in req.texts
+    # ]
     return BatchNERResult(results=batch_entities)