outputing hawkishness score

app.py

@@ -1,14 +1,16 @@
+from typing import Any
+
 from transformers import pipeline, LongformerForSequenceClassification, LongformerTokenizer, Trainer
 import gradio as gr
 
 
-def predict_fn(text: str) -> str:
+def predict_fn(text: str) -> dict[str, Any]:
     model = LongformerForSequenceClassification.from_pretrained("model")
     tokenizer = LongformerTokenizer.from_pretrained("allenai/longformer-base-4096")
-
     p = pipeline("sentiment-analysis", model=model, tokenizer=tokenizer)
-    return p(text)[0]["label"]
+    results = p(text)
+    factor = 100 if results[0]['label'] == 'Hawkish' else -100
+    return {"label": results[0]['label'], "hawkishness_score": round(results[0]['score'] * factor, 0)}
 
 
 gr.Interface(predict_fn, "textbox", "label").launch()
-