Update app.py

app.py

@@ -12,11 +12,11 @@ def load_models():
 
 def sentiment_analysis(text, sentiment_analyzer):
     try:
-        result = sentiment_analyzer(text)[0]["generated_text"] #Adjusted max and min lengths.
+        result = sentiment_analyzer(text)[0]
         return result
     except Exception as e:
         print(f"sentiment_analysis error for '{text}': {e}. Returning 'sentiment_analysis Failed'")
-        return "sentiment_analysis Failed"
+        return {"label": "sentiment_analysis Failed", "score": 0.0}
 
 
 # Generate a narrative story using the GPT-2 genre-based story generator
@@ -50,10 +50,17 @@ def main():
     if st.button("Analyze"): # Added a button
         if text:
             with st.spinner("Analyzing sentiment..."):
-                text_en = translate_text(text, target_language='en', source_language='zh-TW', delay=1)
-                sentiment_output = sentiment_analysis(text_en, sentiment_analyzer)
-                st.write("### Sentiment:")
-                st.write(sentiment_output)
+                text_en = translate_text(text, target_language='en', source_language='zh-TW')
+                sentiment_result = sentiment_analysis(text_en, sentiment_analyzer)
+                label_map = {"LABEL_0": 'negative', "LABEL_1": 'neutral', "LABEL_2": 'positive'} # direct mapping
+                try:
+                    sentiment_label = label_map.get(sentiment_result['label'], 'Unknown')
+                    sentiment_score = sentiment_result['score']
+                    st.write(f"### Sentiment: {sentiment_label}")
+                    st.write(f"Score: {sentiment_score:.4f}")
+                except (KeyError, ValueError):
+                    st.write("Error processing sentiment result.")
+                    st.write(sentiment_result)
 
             with st.spinner("Summarizing News..."):
                 story = summarize_news(text, summarizer)