Update app.py

app.py

@@ -44,7 +44,7 @@ st.subheader("You can tag your input CSV file of theses and dissertations with L
 tab1, tab2, tab3 = st.tabs(["📈 Load Data", "📃 Tagged ETDs", "📓 Download Data"])
 with tab1:
 #===load data===
-    if uploaded_file is not None:
+if uploaded_file is not None:
     df = pd.read_csv(uploaded_file, encoding='latin-1')
     st.dataframe(df)
        
@@ -52,20 +52,20 @@ with tab1:
 with tab2:
 #===tagged ETDs===
 # Tag the "Abstract" column with the corresponding categories
-df['category'] = df['Abstract'].apply(predict_category)
-st.dataframe(df)
+    df['category'] = df['Abstract'].apply(predict_category)
+    st.dataframe(df)
 # Function to predict the category for a given abstract
 def predict_category(abstract):
 # Preprocess the abstract
-abstract_preprocessed = preprocessing.transform([abstract])
+    abstract_preprocessed = preprocessing.transform([abstract])
 # Make prediction
-prediction = svm_classifier.predict(abstract_preprocessed)
-return prediction
+    prediction = svm_classifier.predict(abstract_preprocessed)
+    return prediction
 
 with tab3:
 #===download result===
 # Create a download button
-    if st.sidebar.button("Download"):
+if st.sidebar.button("Download"):
     csv = df.to_csv(index=False)
     b64 = base64.b64encode(csv.encode()).decode()
     href = f'<a href="data:file/csv;base64,{b64}" download="results.csv">Download csv file</a>'