Update app.py

app.py

@@ -9,11 +9,10 @@ analysis = pipeline("text-classification", model='ZephyruSalsify/FinNews_Sentime
 classification = pipeline("text-classification", model="nickmuchi/finbert-tone-finetuned-finance-topic-classification", token=access+token)
 
 st.set_page_config(page_title="Financial News Analysis", page_icon="♕")
-st.header("Make Analysis for Financial News")
 
 # Streamlit application layout
 st.title("Financial News Analysis")
-st.write("Classify corresponding Topic and Trend for Financial News")
+st.write("Analyze corresponding Topic and Trend for Financial News!")
 st.image("./Fin.jpg", use_column_width = True)
 
 # Text input for user to enter the text
@@ -30,19 +29,19 @@ if st.button("Analyze"):
     max_score_1 = float('-inf')
     max_label_1 = ''
     
-    for result in results_1:
-        if result['score'] > max_score_1:
-            max_score_1 = result['score']
-            max_label_1 = result['label']
+    for result_1 in results_1:
+        if result_1['score'] > max_score_1:
+            max_score_1 = result_1['score']
+            max_label_1 = result_1['label']
 
     # Display the classification result
     max_score_2 = float('-inf')
     max_label_2 = ''
     
-    for result in results_2:
-        if result['score'] > max_score_2:
-            max_score_2 = result['score']
-            max_label_2 = result['label']
+    for result_2 in results_2:
+        if result_2['score'] > max_score_2:
+            max_score_2 = result_2['score']
+            max_label_2 = result_2['label']
             
 st.write("Financial Text:", text)
 st.write("Trend:", max_label_1)