Update app.py

app.py

@@ -1,54 +1,59 @@
-import streamlit as st
-from utils import load_model, preprocess_text
-import nltk
-
-nltk.download('stopwords')
-model = load_model('./models/best_model.joblib')
-
-min_words_number = 100
-
-def check_generated_text(text):
-    filtered_text = preprocess_text(text)
-    prediction = model.predict([filtered_text])
-    return not int(prediction[0])
-
-# Load styles
-with open("styles.css") as f:
-    st.markdown(f"<style>{f.read()}</style>", unsafe_allow_html=True)
-
-# Title
-st.title("Generated Text Checker")
-
-# Initialize session state
-if "check_clicked" not in st.session_state:
-    st.session_state.check_clicked = False
-
-# Use a form to isolate the check action
-with st.form("text_check_form"):
-    user_input = st.text_area(
-        f"Enter text to check",
-        height=400,
-        placeholder=f"Paste your generated text here... it should be at least {min_words_number} words"
-    )
-    submitted = st.form_submit_button("Check text")
-
-# Handle form submission
-if submitted:
-    st.session_state.check_clicked = True
-
-# Only run check when button is clicked
-if st.session_state.check_clicked:
-    with st.spinner("Checking text..."):
-        current_length = len(user_input.split())
-        
-        if current_length >= min_words_number:
-            result = check_generated_text(user_input)
-            if result:
-                st.info("✅ The text appears to be human-written!")
-            else:
-                st.info("🤖 The text appears to be AI-generated.")
-        else:
-            st.warning(f"Please enter at least {min_words_number} words.")
-                
-    # Reset check state
+import streamlit as st
+from utils import load_model, preprocess_text
+import nltk
+
+try:
+    nltk.data.find('corpora/stopwords')
+except LookupError:
+    nltk.download('stopwords', quiet=True)
+
+    
+model = load_model('./models/best_model.joblib')
+
+min_words_number = 100
+
+def check_generated_text(text):
+    filtered_text = preprocess_text(text)
+    prediction = model.predict([filtered_text])
+    return not int(prediction[0])
+
+# Load styles
+with open("styles.css") as f:
+    st.markdown(f"<style>{f.read()}</style>", unsafe_allow_html=True)
+
+# Title
+st.title("Generated Text Checker")
+
+# Initialize session state
+if "check_clicked" not in st.session_state:
+    st.session_state.check_clicked = False
+
+# Use a form to isolate the check action
+with st.form("text_check_form"):
+    user_input = st.text_area(
+        f"Enter text to check",
+        height=400,
+        placeholder=f"Paste your generated text here... it should be at least {min_words_number} words"
+    )
+    submitted = st.form_submit_button("Check text")
+
+# Handle form submission
+if submitted:
+    st.session_state.check_clicked = True
+
+# Only run check when button is clicked
+if st.session_state.check_clicked:
+    with st.spinner("Checking text..."):
+        current_length = len(user_input.split())
+        
+        if current_length >= min_words_number:
+            result = check_generated_text(user_input)
+            if result:
+                st.info("✅ The text appears to be human-written!")
+            else:
+                st.info("🤖 The text appears to be AI-generated.")
+        else:
+            st.warning(f"Please enter at least {min_words_number} words.")
+                
+    # Reset check state
     st.session_state.check_clicked = False