Update app.py

app.py

@@ -3,11 +3,14 @@ from transformers import pipeline, AutoModelForSequenceClassification, AutoToken
 import torch
 import numpy as np
 
+# Function to analyze email for spam and sentiment
 def analyze_email(email_body):
+    # Load pre-trained models for spam detection and sentiment analysis
     spam_pipeline = pipeline("text-classification", model="cybersectony/phishing-email-detection-distilbert_v2.4.1")
     sentiment_model = AutoModelForSequenceClassification.from_pretrained("ISOM5240GP4/email_sentiment", num_labels=2)
     tokenizer = AutoTokenizer.from_pretrained("distilbert-base-uncased")
 
+    # Step 1: Check if email is spam
     spam_result = spam_pipeline(email_body)
     spam_label = spam_result[0]["label"]
     spam_confidence = spam_result[0]["score"]
@@ -15,6 +18,7 @@ def analyze_email(email_body):
     if spam_label == "LABEL_1":
         return "spam", f"This is a spam email (Confidence: {spam_confidence:.2f}). No follow-up needed."
     else:
+        # Step 2: Analyze sentiment for non-spam emails
         inputs = tokenizer(email_body, padding=True, truncation=True, return_tensors='pt')
         outputs = sentiment_model(**inputs)
         predictions = torch.nn.functional.softmax(outputs.logits, dim=-1)
@@ -31,11 +35,14 @@ def analyze_email(email_body):
                                 f"Sentiment: {sentiment} (Confidence: {sentiment_confidence:.2f}).\n"
                                 "**Need to Follow-Up**: This email is not spam and has negative sentiment.")
 
+# Main application function
 def main():
+    # Set page title
     st.title("EmailSentry")
+    # Set project objective
     st.write("Aims to perform analysis on incoming emails and to determine whether there is urgency or higher priority for the company to follow-up.")
 
-    # Initialize session state
+    # Initialize session state variables
     if "email_body" not in st.session_state:
         st.session_state.email_body = ""
     if "result" not in st.session_state:
@@ -43,7 +50,7 @@ def main():
     if "result_type" not in st.session_state:
         st.session_state.result_type = ""
 
-    # Collapsible instructions
+    # Collapsible instructions section
     with st.expander("How to Use", expanded=False):
         st.write("""
         - Type or paste an email into the text box.
@@ -52,10 +59,10 @@ def main():
         - Use 'Clear' to reset the input and result.
         """)
 
-    # Text area for email input
+    # Input text area for email content
     email_body = st.text_area("Email Body", value=st.session_state.email_body, height=200, key="email_input")
 
-    # Sample emails (shortened snippets for button labels)
+    # Define sample emails and their snippets for buttons
     sample_spam = """
 Subject: Urgent: Verify Your Account Now!
 Dear Customer,
@@ -85,7 +92,7 @@ Sarah
     """
     negative_snippet = "Subject: Issue with Recent Delivery Dear Support, I received my package today, but..."
 
-    # Custom CSS for buttons and result boxes
+    # Custom CSS for styling buttons and result boxes
     st.markdown("""
         <style>
         /* Sample buttons (smaller text) */
@@ -110,12 +117,12 @@ Sarah
         div.stButton > button[kind="primary"]:hover {
             background-color: #E74C3C;
         }
-        /* Clear button (gray) */
+        /* Clear button (aligned with Analyze, gray) */
         div.stButton > button[kind="secondary"][key="clear"] {
             background-color: #d3d3d3;
             color: #333333;
-            font-size: 18px; /* Match Analyze Email size */
-            padding: 12px 24px; /* Match Analyze Email padding */
+            font-size: 18px;
+            padding: 12px 24px;
             border: none;
             border-radius: 5px;
         }
@@ -147,7 +154,7 @@ Sarah
     # Subheading for sample buttons
     st.subheader("Examples")
 
-    # Sample buttons (in columns)
+    # Sample buttons layout (3 columns)
     col1, col2, col3 = st.columns(3)
     with col1:
         if st.button(spam_snippet, key="spam_sample"):
@@ -168,7 +175,7 @@ Sarah
             st.session_state.result_type = ""
             st.rerun()
 
-    # Analyze and Clear buttons (aligned in a row)
+    # Action buttons layout (Analyze and Clear)
     col_analyze, col_clear = st.columns(2)
     with col_analyze:
         if st.button("Analyze Email", key="analyze", type="primary"):
@@ -187,7 +194,7 @@ Sarah
             st.session_state.result_type = ""
             st.rerun()
 
-    # Display result with styled box
+    # Display analysis result in styled boxes
     if st.session_state.result:
         if st.session_state.result_type == "spam":
             st.markdown(f'<div class="spam-result">{st.session_state.result}</div>', unsafe_allow_html=True)
@@ -198,5 +205,6 @@ Sarah
         else:
             st.write(st.session_state.result)  # For error messages
 
+# Run the app
 if __name__ == "__main__":
     main()