Update app.py

app.py

@@ -3,18 +3,28 @@ from transformers import pipeline
 
 model = pipeline("token-classification", model="benchaffe/Bert-RAdam-Large", aggregation_strategy="simple")
 
+def to_serializable(obj):
+    if isinstance(obj, (float, int, str, bool, type(None))):
+        return obj
+    elif isinstance(obj, dict):
+        return {k: to_serializable(v) for k, v in obj.items()}
+    elif isinstance(obj, list):
+        return [to_serializable(i) for i in obj]
+    else:
+        return str(obj)
+
 def predict(text):
-  result = model(text)
-  with open("log.jsonl", "a") as f:
-    import json
-    from datetime import datetime
-    log_entry = {
-      "timestamp": datetime.now().isoformat(),
-      "input": text,
-      "prediction": result
-    }
-    f.write(json.dumps(log_entry) + "\n")
-  return result
+    result = model(text)
+    with open("log.jsonl", "a") as f:
+        import json
+        from datetime import datetime
+        log_entry = {
+          "timestamp": datetime.now().isoformat(),
+          "input": text,
+          "prediction": to_serializable(result)
+        }
+        f.write(json.dumps(log_entry) + "\n")
+    return result
 
 interface = gr.Interface(fn=predict, inputs="text", outputs="json", title="Abbreviation Detector")
 interface.launch()