Update app.py

app.py

@@ -1,34 +1,34 @@
-# import libraries
-import streamlit as st
-import predict
-import logging
-
-# Logging configuration
-logging.basicConfig(level=logging.DEBUG, format='%(asctime)s - %(levelname)s - %(message)s')
-
-# Load necessary components
-df = predict.load_dataset()
-model, tokenizer = predict.load_model_and_tokenizer()
-
-if df is not None and model is not None and tokenizer is not None:
-    # Preprocess dataset and prepare stopwords and stemmer
-    manual_stopwords = ["di", "ke", "dari", "yang", "dan", "atau", "dengan", "untuk", "ini", "itu", "aja", "saja", "lah", "bri", "brimo", "aplikasi", "rekening", "coba", "yg", "ke", "untuk", "nya", "saya", "dia", "dan", "sangat", "video", "login", "apk", "jadi", "akun", "malah", "uang", "banget", "dalam", "atm", "padahal"]
-    stop_words = set(predict.stopwords.words('indonesian'))
-    stop_words.update(manual_stopwords)
-    factory = predict.StemmerFactory()
-    stemmer = factory.create_stemmer()
-    df['label'] = df['score'].apply(predict.map_labels)
-
-    navigation = st.sidebar.selectbox('Choose Page:', ('predictor', 'eda'))
-
-    if navigation == 'predictor':
-        predict.run(model, tokenizer, stop_words, stemmer)
-    # elif navigation == 'eda':
-    #     eda.run()
-else:
-    if df is None:
-        logging.error("Failed to load dataset.")
-        st.error("Failed to load the dataset. Please check the dataset file.")
-    if model is None or tokenizer is None:
-        logging.error("Failed to load model or tokenizer.")
+# import libraries
+import streamlit as st
+import predict
+import logging
+
+# Logging configuration
+logging.basicConfig(level=logging.DEBUG, format='%(asctime)s - %(levelname)s - %(message)s')
+
+# Load necessary components
+df = predict.load_dataset()
+model, tokenizer = predict.load_model_and_tokenizer()
+
+if df is not None and model is not None and tokenizer is not None:
+    # Preprocess dataset and prepare stopwords and stemmer
+    manual_stopwords = ["di", "ke", "dari", "yang", "dan", "atau", "dengan", "untuk", "ini", "itu", "aja", "saja", "lah", "bri", "brimo", "aplikasi", "rekening", "coba", "yg", "ke", "untuk", "nya", "saya", "dia", "dan", "sangat", "video", "login", "apk", "jadi", "akun", "malah", "uang", "banget", "dalam", "atm", "padahal"]
+    stop_words = set(predict.stopwords.words('indonesian'))
+    stop_words.update(manual_stopwords)
+    factory = predict.StemmerFactory()
+    stemmer = factory.create_stemmer()
+    df['label'] = df['score'].apply(predict.map_labels)
+
+    navigation = st.sidebar.selectbox('Choose Page:', ('predictor'))
+
+    if navigation == 'predictor':
+        predict.run(model, tokenizer, stop_words, stemmer)
+    # elif navigation == 'eda':
+    #     eda.run()
+else:
+    if df is None:
+        logging.error("Failed to load dataset.")
+        st.error("Failed to load the dataset. Please check the dataset file.")
+    if model is None or tokenizer is None:
+        logging.error("Failed to load model or tokenizer.")
         st.error("Failed to load the model or tokenizer. Please check the model file.")