app.py

import streamlit as st
from transformers import pipeline, AutoModelForSequenceClassification, AutoTokenizer
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"]

    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)
        predictions = predictions.cpu().detach().numpy()
        sentiment_index = np.argmax(predictions)
        sentiment_confidence = predictions[0][sentiment_index]
        sentiment = "Positive" if sentiment_index == 1 else "Negative"

        if sentiment == "Positive":
            return "positive", (f"This email is not spam (Confidence: {spam_confidence:.2f}).\n"
                                f"Sentiment: {sentiment} (Confidence: {sentiment_confidence:.2f}). No follow-up needed.")
        else:
            return "negative", (f"This email is not spam (Confidence: {spam_confidence:.2f}).\n"
                                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 variables
    if "email_body" not in st.session_state:
        st.session_state.email_body = ""
    if "result" not in st.session_state:
        st.session_state.result = ""
    if "result_type" not in st.session_state:
        st.session_state.result_type = ""

    # Collapsible instructions section
    with st.expander("How to Use", expanded=False):
        st.write("""
        - Type or paste an email into the text box.
        - Alternatively, click one of the sample buttons to load a predefined email.
        - Press 'Analyze Email' to check if it’s spam and analyze its sentiment.
        - Use 'Clear' to reset the input and result.
        """)

    # Input text area for email content
    email_body = st.text_area("Email Body", value=st.session_state.email_body, height=200, key="email_input")

    # Define sample emails and their snippets for buttons
    sample_spam = """
Subject: Urgent: Verify Your Account Now!
Dear Customer,
We have detected unusual activity on your account. To prevent suspension, please verify your login details immediately by clicking the link below:
[Click Here to Verify](http://totally-legit-site.com/verify)
Failure to verify within 24 hours will result in your account being locked. This is for your security.
Best regards,
The Security Team
    """
    spam_snippet = "Subject: Urgent: Verify Your Account Now! Dear Customer, We have detected unusual activity..."

    sample_not_spam_positive = """
Subject: Great Experience with HKTV mall
Dear Sir,
I just received my order and I’m really impressed with the speed of the delivery. Keep up the good work.
Best regards,
Emily
    """
    positive_snippet = "Subject: Great Experience with HKTV mall Dear Sir, I just received my order and I’m really..."

    sample_not_spam_negative = """
Subject: Issue with Recent Delivery
Dear Support,
I received my package today, but it was damaged, and two items were missing. This is really frustrating—please let me know how we can resolve this as soon as possible.
Thanks,
Sarah
    """
    negative_snippet = "Subject: Issue with Recent Delivery Dear Support, I received my package today, but..."

    # Custom CSS for styling buttons and result boxes
    st.markdown("""
        <style>
        /* Sample buttons (smaller text) */
        div.stButton > button[kind="secondary"] {
            font-size: 12px;
            padding: 5px 10px;
            background-color: #f0f0f0;
            color: #333333;
            border: 1px solid #cccccc;
            border-radius: 3px;
        }
        /* Analyze Email button (larger, orange) */
        div.stButton > button[kind="primary"] {
            background-color: #FF5733;
            color: white;
            font-size: 18px;
            padding: 12px 24px;
            border: none;
            border-radius: 5px;
            margin-right: 10px;
        }
        div.stButton > button[kind="primary"]:hover {
            background-color: #E74C3C;
        }
        /* Clear button (aligned with Analyze, gray) */
        div.stButton > button[kind="secondary"][key="clear"] {
            background-color: #d3d3d3;
            color: #333333;
            font-size: 18px;
            padding: 12px 24px;
            border: none;
            border-radius: 5px;
        }
        div.stButton > button[kind="secondary"][key="clear"]:hover {
            background-color: #b0b0b0;
        }
        /* Result boxes */
        .spam-result {
            background-color: #ffdddd; /* Softer red */
            padding: 10px;
            border-radius: 5px;
            border: 1px solid #ffaaaa;
        }
        .positive-result {
            background-color: #d4edda; /* Softer green */
            padding: 10px;
            border-radius: 5px;
            border: 1px solid #a3d7a9;
        }
        .negative-result {
            background-color: #fff4e6; /* Softer orange */
            padding: 10px;
            border-radius: 5px;
            border: 1px solid #ffd6a5;
        }
        </style>
    """, unsafe_allow_html=True)

    # Subheading for sample buttons
    st.subheader("Examples")

    # Sample buttons layout (3 columns)
    col1, col2, col3 = st.columns(3)
    with col1:
        if st.button(spam_snippet, key="spam_sample"):
            st.session_state.email_body = sample_spam
            st.session_state.result = ""
            st.session_state.result_type = ""
            st.rerun()
    with col2:
        if st.button(positive_snippet, key="positive_sample"):
            st.session_state.email_body = sample_not_spam_positive
            st.session_state.result = ""
            st.session_state.result_type = ""
            st.rerun()
    with col3:
        if st.button(negative_snippet, key="negative_sample"):
            st.session_state.email_body = sample_not_spam_negative
            st.session_state.result = ""
            st.session_state.result_type = ""
            st.rerun()

    # 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"):
            if email_body:
                with st.spinner("Analyzing email..."):
                    result_type, result = analyze_email(email_body)
                    st.session_state.result = result
                    st.session_state.result_type = result_type
            else:
                st.session_state.result = "Please enter an email body or select a sample to analyze."
                st.session_state.result_type = ""
    with col_clear:
        if st.button("Clear", key="clear"):
            st.session_state.email_body = ""
            st.session_state.result = ""
            st.session_state.result_type = ""
            st.rerun()

    # 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)
        elif st.session_state.result_type == "positive":
            st.markdown(f'<div class="positive-result">{st.session_state.result}</div>', unsafe_allow_html=True)
        elif st.session_state.result_type == "negative":
            st.markdown(f'<div class="negative-result">{st.session_state.result}</div>', unsafe_allow_html=True)
        else:
            st.write(st.session_state.result)  # For error messages

# Run the app
if __name__ == "__main__":
    main()