Update app.py

app.py

@@ -12,7 +12,7 @@ from datetime import datetime
 import logging
 
 date = datetime.now().strftime(r"%Y-%m-%d")
-model_classes ={
+model_classes = {
     0: "Ads",
     1: "Apps",
     2: "Battery",
@@ -29,6 +29,7 @@ model_classes ={
     13: "WiFi",
 }
 
+
 @st.cache
 def load_t5():
     model = AutoModelForSeq2SeqLM.from_pretrained("t5-base")
@@ -78,7 +79,7 @@ hide_streamlit_style = """
 st.markdown(hide_streamlit_style, unsafe_allow_html=True)
 
 ps = st.empty()
-if st.button("Process",type="primary"):
+if st.button("Process", type="primary"):
     if uploaded_file is not None:
         if uploaded_file.name.split(".")[-1] in ["xls", "xlsx"]:
 
@@ -99,7 +100,7 @@ if st.button("Process",type="primary"):
                 summary = []
 
                 for x in stqdm(range(len(text))):
-                     if st.button("Cancel"):
+                    if st.button("Cancel"):
                         break
                     try:
                         summary.append(
@@ -147,8 +148,7 @@ if st.button("Process",type="primary"):
                 for x in stqdm(range(len(text))):
                     if st.button("Cancel"):
                         break
-                    
-            
+
                     tokens_input = tokenizer.encode(
                         "summarize: " + text[x],
                         return_tensors="pt",
@@ -204,7 +204,8 @@ if st.button("Process",type="primary"):
 
                 summary = []
                 for x in stqdm(range(len(text))):
-                     if st.button("Cancel"):
+
+                    if st.button("Cancel"):
                         break
                     try:
                         summary.append(model.predict(text[x])[0])