Update app.py

app.py

@@ -22,12 +22,19 @@ def inference(input_doc):
     outputs = model(**inputs)
     probs = torch.softmax(outputs.logits, dim=1).squeeze().tolist()
     class_idx = {'공포': 0, '놀람': 1, '분노': 2, '슬픔': 3, '중립': 4, '행복': 5, '혐오': 6}
-    return {class_name: prob for class_name, prob in zip(class_idx, probs)}
+    results = {class_name: prob for class_name, prob in zip(class_idx, probs)}
+    # Find the class with the highest probability
+    max_prob_class = max(results, key=results.get)
+    max_prob = results[max_prob_class]
+    # Display results
+    print(f"가장 강하게 나타난 감정: {max_prob_class}")
+    for class_name, prob in results.items():
+        print(f"{class_name}: {prob:.2%}")
 
 # Set up the Streamlit interface
-st.title('Sentiment Analysis with BERT')
-user_input = st.text_area("Enter text here:")
-if st.button('Analyze'):
+st.title('감정분석(Sentiment Analysis): 아래에 글을 입력하면 공포,놀람,분노,슬픔,중립,행복,혐오가 포함된 정도를 비율로 알려드립니다')
+user_input = st.text_area("이 곳에 글 입력(100자 이하 권장):")
+if st.button('시작'):
     result = inference(user_input)
     st.write(result)