Final version, database correctly ignored

.gitignore

@@ -0,0 +1,7 @@
+.venv/
+__pycache__/
+*.pyc
+.env
+token.json
+credentials.json
+email_sorter.db

.gradio/certificate.pem

@@ -0,0 +1,31 @@
+-----BEGIN CERTIFICATE-----
+MIIFazCCA1OgAwIBAgIRAIIQz7DSQONZRGPgu2OCiwAwDQYJKoZIhvcNAQELBQAw
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+hkiG9w0BAQsFAAOCAgEAVR9YqbyyqFDQDLHYGmkgJykIrGF1XIpu+ILlaS/V9lZL
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+-----END CERTIFICATE-----

.gradio/flagged/dataset1.csv

@@ -0,0 +1,2 @@
+subject,body,output 0,output 1,timestamp
+Team Standup Reminder,Please join the daily standup meeting at 10 AM,Personal,0.3250395441164229,2025-10-02 14:26:46.167232

app.py

@@ -0,0 +1,8 @@
+# This file should be in: your_project_root/app.py
+
+from backend.app import app
+
+# The 'app' variable needs to be accessible at the top level for Hugging Face.
+# The launch block is good practice and lets you run this file locally.
+if __name__ == "__main__":
+    app.launch()

backend/app.py

@@ -0,0 +1,107 @@
+# backend/app.py (NEW VERSION USING A PRE-TRAINED MODEL)
+
+from transformers import pipeline
+import gradio as gr
+import pandas as pd
+from gmail_fetcher import fetch_latest_emails
+import database
+
+# --- This is the core change ---
+# 1. We load a pre-trained "zero-shot-classification" pipeline from Hugging Face.
+# The first time this code runs, it will automatically download the model (approx. 1.6GB).
+print("Loading zero-shot classification model...")
+classifier = pipeline("zero-shot-classification", model="facebook/bart-large-mnli")
+print("Model loaded successfully.")
+# -----------------------------
+
+database.init_db()
+
+# --- These are the labels we want to sort emails into ---
+# You can change or add to this list!
+POSSIBLE_LABELS = ["Work", "Promotions", "Personal", "Spam", "Important"]
+email_storage = {}
+
+def predict_and_save_emails(df):
+    """Takes a DataFrame of emails, classifies them, and saves to DB."""
+    if df.empty:
+        return pd.DataFrame({"Message": ["No emails to process."]})
+
+    # Get the text content for classification
+    sequences = (df['Subject'] + " " + df['Body']).tolist()
+    
+    print(f"Classifying {len(sequences)} emails...")
+    # Use the zero-shot pipeline. It's powerful but can be slow on CPU for many emails.
+    predictions = classifier(sequences, candidate_labels=POSSIBLE_LABELS)
+    print("Classification complete.")
+
+    # Extract the top label and score for each prediction
+    pred_labels = [pred['labels'][0] for pred in predictions]
+    pred_scores = [pred['scores'][0] for pred in predictions]
+
+    # Add results to the DataFrame
+    df['predicted_folder'] = pred_labels
+    df['confidence'] = pred_scores
+    
+    # Save to the database
+    database.add_email_records(df)
+    print(f"Saved {len(df)} records to the database.")
+    
+    # Format for display
+    df_display = df.copy()
+    df_display['confidence'] = [f"{score:.2%}" for score in pred_scores]
+    return df_display[["From", "Subject", "predicted_folder", "confidence"]]
+
+def fetch_and_classify_emails():
+    """Fetches emails from Gmail and triggers the classification."""
+    emails = fetch_latest_emails()
+    if not emails:
+        email_storage.clear()
+        return pd.DataFrame({"From": ["No new emails found or an error occurred."], "Subject": [""]})
+    
+    df = pd.DataFrame(emails)
+    return predict_and_save_emails(df)
+
+# --- History & Feedback Functions (Unchanged) ---
+def show_history():
+    records, columns = database.get_all_emails()
+    if not records:
+        return pd.DataFrame({"Message": ["No history found."]})
+    history_df = pd.DataFrame(records, columns=columns)
+    return history_df
+
+def save_feedback_and_refresh(record_id, corrected_label):
+    if not record_id or not corrected_label:
+        return show_history(), "Please enter a Record ID and a correct label first."
+    
+    record_id_int = int(record_id)
+    database.update_feedback(record_id_int, corrected_label)
+    
+    return show_history(), f"Success! Record {record_id_int} updated."
+
+# --- Build the Gradio Interface (Unchanged) ---
+with gr.Blocks(theme=gr.themes.Soft()) as app:
+    gr.Markdown("## 📧 Smart Email Sorter (Zero-Shot Model)")
+
+    with gr.Tab("Fetch & Classify Gmail"):
+        predict_gmail_btn = gr.Button("Fetch and Classify Latest Emails", variant="primary")
+        email_display = gr.Dataframe(headers=["From", "Subject", "predicted_folder", "confidence"], label="Fetched & Classified Emails", wrap=True)
+        predict_gmail_btn.click(fn=fetch_and_classify_emails, outputs=email_display, show_progress="full")
+
+    with gr.Tab("History & Feedback"):
+        gr.Markdown("### Prediction History & Feedback")
+        gr.Markdown("To correct a prediction, find its `id` in the table, then enter it into the textbox below.")
+        with gr.Row():
+            record_id_input = gr.Number(label="Enter Record ID to Correct")
+            feedback_label = gr.Dropdown(label="Correct Folder", choices=POSSIBLE_LABELS)
+        with gr.Row():
+            submit_feedback_btn = gr.Button("Submit Correction", variant="primary")
+            refresh_history_btn = gr.Button("Refresh History")
+        feedback_status = gr.Markdown("")
+        history_df = gr.Dataframe(label="All Saved Predictions", wrap=True)
+        app.load(fn=show_history, outputs=history_df)
+        refresh_history_btn.click(fn=show_history, outputs=history_df)
+        submit_feedback_btn.click(
+            fn=save_feedback_and_refresh, 
+            inputs=[record_id_input, feedback_label], 
+            outputs=[history_df, feedback_status]
+        )

backend/check_env.py

@@ -0,0 +1,9 @@
+# backend/check_env.py
+import sys
+import gradio
+
+print("--- Environment Diagnostics ---")
+print(f"Python Executable Path: {sys.executable}")
+print(f"Gradio Library Version: {gradio.__version__}")
+print(f"Gradio Library Path:    {gradio.__file__}")
+print("---------------------------")

backend/compare_models.py

@@ -0,0 +1,46 @@
+import joblib
+from transformers import DistilBertTokenizerFast, DistilBertForSequenceClassification
+import torch
+
+# -----------------------------
+# 1️⃣ Load baseline TF-IDF model
+# -----------------------------
+baseline_model = joblib.load("models/baseline_folder_clf.pkl")
+
+# -----------------------------
+# 2️⃣ Load transformer model
+# -----------------------------
+model_path = "models/transformer"
+tokenizer = DistilBertTokenizerFast.from_pretrained(model_path)
+model = DistilBertForSequenceClassification.from_pretrained(model_path)
+le = joblib.load(f"{model_path}/le.pkl")
+model.eval()
+
+# -----------------------------
+# 3️⃣ Sample emails for testing
+# -----------------------------
+test_emails = [
+    {"subject": "Team Standup Reminder", "body": "Please join the daily standup meeting at 10 AM."},
+    {"subject": "50% Off on Shoes", "body": "Grab the latest offer on sneakers."},
+    {"subject": "Mom's Birthday", "body": "Don't forget to call mom today."},
+]
+
+# -----------------------------
+# 4️⃣ Compare predictions
+# -----------------------------
+for email in test_emails:
+    text = email["subject"] + " " + email["body"]
+
+    # Baseline prediction
+    baseline_pred = baseline_model.predict([text])[0]
+
+    # Transformer prediction
+    inputs = tokenizer(text, truncation=True, padding=True, return_tensors="pt")
+    with torch.no_grad():
+        outputs = model(**inputs)
+        pred_id = torch.argmax(outputs.logits, dim=1).item()
+        transformer_pred = le.inverse_transform([pred_id])[0]
+
+    print(f"\nEmail: {text}")
+    print(f"Baseline prediction: {baseline_pred}")
+    print(f"Transformer prediction: {transformer_pred}")

backend/credential.env

@@ -0,0 +1,2 @@
+GMAIL_USER="iamsurya195@gmail.com"
+GMAIL_PASSWORD="acqy dxst pwkl aymz"

backend/database.py

@@ -0,0 +1,56 @@
+# backend/database.py (ROBUST VERSION)
+import sqlite3
+from datetime import datetime
+
+DB_NAME = "email_sorter.db"
+
+def init_db():
+    """Initializes the database using a context manager for safety."""
+    with sqlite3.connect(DB_NAME) as conn:
+        cursor = conn.cursor()
+        cursor.execute('''
+            CREATE TABLE IF NOT EXISTS emails (
+                id INTEGER PRIMARY KEY AUTOINCREMENT,
+                timestamp TEXT NOT NULL,
+                email_from TEXT,
+                subject TEXT,
+                body TEXT,
+                predicted_folder TEXT,
+                confidence REAL,
+                user_feedback TEXT 
+            )
+        ''')
+    print("Database initialized successfully.")
+
+def add_email_records(records_df):
+    """Adds multiple email records from a pandas DataFrame using a context manager."""
+    with sqlite3.connect(DB_NAME) as conn:
+        records_df['timestamp'] = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+        records_df['user_feedback'] = None
+        
+        df_to_save = records_df.rename(columns={
+            'From': 'email_from',
+            'Subject': 'subject',
+            'Body': 'body'
+        })
+        
+        db_columns = ['timestamp', 'email_from', 'subject', 'body', 'predicted_folder', 'confidence', 'user_feedback']
+        df_to_save = df_to_save[[col for col in db_columns if col in df_to_save.columns]]
+
+        df_to_save.to_sql('emails', conn, if_exists='append', index=False)
+
+def get_all_emails():
+    """Fetches all email records using a context manager."""
+    with sqlite3.connect(DB_NAME) as conn:
+        cursor = conn.cursor()
+        cursor.execute("SELECT id, timestamp, email_from, subject, predicted_folder, confidence, user_feedback FROM emails ORDER BY timestamp DESC")
+        records = cursor.fetchall()
+        columns = [description[0] for description in cursor.description]
+    return records, columns
+
+def update_feedback(record_id, corrected_label):
+    """Updates the user_feedback for a specific record using a context manager."""
+    with sqlite3.connect(DB_NAME) as conn:
+        cursor = conn.cursor()
+        cursor.execute("UPDATE emails SET user_feedback = ? WHERE id = ?", (corrected_label, record_id))
+    print(f"Updated record ID {record_id} with feedback: {corrected_label}")

backend/gmail_fetcher.py

@@ -0,0 +1,100 @@
+import imaplib
+import email
+from email.header import decode_header
+import os
+from dotenv import load_dotenv
+from bs4 import BeautifulSoup # A library for parsing HTML
+
+# Load the environment variables from your .env file
+load_dotenv() 
+
+def fetch_latest_emails(num_emails=10):
+    try:
+        # Get credentials securely from the .env file
+        username = os.getenv("GMAIL_USER")
+        password = os.getenv("GMAIL_PASSWORD")
+
+        if not username or not password:
+            print("Error: GMAIL_USER and GMAIL_PASSWORD must be set in the .env file.")
+            return []
+
+        # Connect to Gmail's server
+        mail = imaplib.IMAP4_SSL("imap.gmail.com")
+        mail.login(username, password)
+        mail.select("inbox")
+
+        # Search for all emails and get their IDs
+        result, data = mail.search(None, "ALL")
+        mail_ids = data[0].split()
+        
+        emails = []
+        # Fetch the most recent emails based on num_emails
+        for i in mail_ids[-num_emails:]:
+            result, data = mail.fetch(i, "(RFC822)")
+            raw_email = data[0][1]
+            msg = email.message_from_bytes(raw_email)
+
+            # Decode the subject line safely
+            subject, encoding = decode_header(msg["Subject"])[0]
+            if isinstance(subject, bytes):
+                subject = subject.decode(encoding or "utf-8", errors="ignore")
+
+            # Get the sender's address
+            from_ = msg.get("From", "")
+
+            # --- Improved Body Parsing ---
+            body = ""
+            if msg.is_multipart():
+                for part in msg.walk():
+                    content_type = part.get_content_type()
+                    content_disposition = str(part.get("Content-Disposition"))
+
+                    # Skip attachments
+                    if "attachment" not in content_disposition:
+                        if content_type == "text/plain":
+                            try:
+                                body = part.get_payload(decode=True).decode()
+                                break # Found plain text, stop searching
+                            except:
+                                continue
+                        elif content_type == "text/html":
+                             # If we only find HTML, parse it to get clean text
+                            try:
+                                html_body = part.get_payload(decode=True).decode()
+                                soup = BeautifulSoup(html_body, "html.parser")
+                                body = soup.get_text()
+                            except:
+                                continue
+            else:
+                # For non-multipart emails, just get the payload
+                try:
+                    body = msg.get_payload(decode=True).decode()
+                except:
+                    body = ""
+
+            emails.append({
+                "From": from_,
+                "Subject": subject,
+                "Body": body.strip()
+            })
+        
+        mail.logout()
+        # Return emails in reverse order to show the newest one first
+        return emails[::-1]
+
+    except Exception as e:
+        print(f"An error occurred while fetching emails: {e}")
+        return []
+
+# NEW, ROBUST CODE for the end of gmail_fetcher.py
+if __name__ == "__main__":
+    latest_emails = fetch_latest_emails()
+    if latest_emails:
+        print(f"Successfully fetched {len(latest_emails)} emails.")
+        for e in latest_emails:
+            # Safely encode and decode each part to prevent crashes in the terminal
+            safe_from = e['From'].encode('utf-8', 'replace').decode('utf-8')
+            safe_subject = e['Subject'].encode('utf-8', 'replace').decode('utf-8')
+            safe_body = e['Body'][:100].encode('utf-8', 'replace').decode('utf-8')
+            
+            print(f"From: {safe_from}\nSubject: {safe_subject}\nBody: {safe_body}...\n")

backend/gradio_app.py

@@ -0,0 +1,52 @@
+import pandas as pd
+import torch
+from transformers import DistilBertTokenizerFast, DistilBertForSequenceClassification
+import joblib
+import gradio as gr
+
+# -----------------------------
+# Load trained transformer
+# -----------------------------
+model_path = "./models/transformer"
+model = DistilBertForSequenceClassification.from_pretrained(model_path)
+tokenizer = DistilBertTokenizerFast.from_pretrained(model_path)
+le = joblib.load(f"{model_path}/le.pkl")
+model.eval()
+
+# -----------------------------
+# Prediction function for CSV
+# -----------------------------
+def predict_csv(file):
+    df = pd.read_csv(file.name)
+    if 'subject' not in df.columns or 'body' not in df.columns:
+        return "CSV must have 'subject' and 'body' columns."
+    
+    texts = df['subject'] + " " + df['body']
+    predictions = []
+    
+    for text in texts:
+        inputs = tokenizer(text, truncation=True, padding=True, return_tensors="pt")
+        with torch.no_grad():
+            outputs = model(**inputs)
+            pred_id = torch.argmax(outputs.logits, dim=1).item()
+            pred_label = le.inverse_transform([pred_id])[0]
+        predictions.append(pred_label)
+    
+    df['predicted_folder'] = predictions
+    return df  # Gradio will display as a table
+
+# -----------------------------
+# Gradio interface
+# -----------------------------
+iface = gr.Interface(
+    fn=predict_csv,
+    inputs=gr.File(label="Upload CSV"),
+    outputs=gr.Dataframe(label="Predicted Folders"),
+    title="Smart Email Sorter (Transformer) - CSV Upload",
+    description="Upload a CSV with 'subject' and 'body' columns to predict email folders."
+)
+
+# -----------------------------
+# Launch
+# -----------------------------
+iface.launch(share=True)

data/emails_sample.csv

@@ -0,0 +1,170 @@
+subject,body,folder
+Team Standup Reminder,"Please join the daily standup meeting at 10 AM.",Work
+Project Deadline,"Final submission for the AI project is due tomorrow.",Work
+Meeting Invitation,"You are invited to the client meeting at 2 PM.",Work
+Code Review,"Please review the latest PR in GitHub.",Work
+Performance Review,"Your annual performance review is scheduled for Friday.",Work
+50% Off on Sneakers,"Grab the latest offer on sneakers before it ends.",Promotions
+Black Friday Sale,"Don’t miss our Black Friday deals this weekend.",Promotions
+New Arrivals: Electronics,"Check out our newest gadgets now.",Promotions
+Holiday Discounts,"Save big on your holiday shopping today.",Promotions
+Summer Sale,"Up to 70% off on summer collection.",Promotions
+Mom's Birthday,"Don’t forget to call mom today.",Personal
+Dad’s Anniversary,"Wish your dad a happy anniversary.",Personal
+Friend’s Wedding,"Join us for John and Emily’s wedding this Saturday.",Personal
+Grocery Reminder,"Buy milk, eggs, and bread on your way home.",Personal
+Doctor Appointment,"Remember your check-up tomorrow at 3 PM.",Personal
+Your Amazon Order,"Your order has been shipped and will arrive soon.",Updates
+Flight Confirmation,"Your flight booking has been confirmed.",Updates
+Package Delivered,"Your package has been delivered to your address.",Updates
+Account Update,"Your account password was changed successfully.",Updates
+Subscription Renewal,"Your subscription will renew on the 5th of next month.",Updates
+Workshop Registration,"You are registered for the AI workshop on Saturday.",Work
+Promo Code Inside,"Use code SAVE20 to get a discount today.",Promotions
+Birthday Wishes,"Happy Birthday! Wishing you a wonderful year ahead.",Personal
+System Maintenance,"Scheduled maintenance will occur this Sunday at midnight.",Updates
+Weekly Report,Please submit your weekly report by Friday.,Work
+Team Meeting,The design team meeting is scheduled at 3 PM.,Work
+Password Reset,Click here to reset your account password.,Updates
+Flight Reminder,Your flight to New York is tomorrow at 9 AM.,Updates
+Birthday Party,You're invited to Jake's birthday party this Saturday.,Personal
+Gym Membership,Renew your gym membership for the next month.,Personal
+Discount on Laptops,Get up to 30% off on selected laptops.,Promotions
+Black Friday Deals,Don't miss our Black Friday sale!,Promotions
+Doctor Appointment,Your appointment with Dr. Smith is confirmed.,Personal
+Project Update,The project documentation has been uploaded.,Work
+Invoice #67890,Invoice has been processed and attached.,Updates
+Conference Registration,Register now for the AI conference 2025.,Work
+Holiday Plans,Let's plan our holiday trip for next month.,Personal
+Subscription Renewal,Your magazine subscription will expire soon.,Updates
+Flash Sale,Summer flash sale: up to 50% off!,Promotions
+Client Feedback,Client has approved the latest design draft.,Work
+Dinner Plans,Are you free for dinner tomorrow evening?,Personal
+Amazon Promotion,Exclusive Amazon deals just for you!,Promotions
+Password Change,Your password was changed successfully.,Updates
+Meeting Agenda,Here is the agenda for tomorrow's meeting.,Work
+Family Gathering,Family dinner at Mom's place this weekend.,Personal
+Coupon Offer,Use code SAVE20 for instant discount.,Promotions
+Event Reminder,Reminder: Webinar starts at 5 PM today.,Updates
+Presentation Slides,Slides for Monday's presentation are ready.,Work
+Weekend Sale,Weekend sale: shoes and bags up to 40% off!,Promotions
+Travel Itinerary,Your travel itinerary has been emailed.,Updates
+Birthday Reminder,Don't forget Sarah's birthday next week.,Personal
+Product Launch,New product launch scheduled for next week.,Promotions
+Meeting Notes,Notes from yesterday's client meeting.,Work
+Doctor Checkup,Time for your annual health checkup.,Personal
+Project Deadline Reminder,The project report is due by Friday,Work
+Team Lunch,Join us for lunch at 1 PM,Work
+Meeting Rescheduled,The meeting has been moved to 3 PM,Work
+Client Feedback,The client has approved the design,Work
+Invoice Received,Please review the attached invoice,Work
+Salary Slip,Your salary slip for September is attached,Work
+Weekly Report,Submit your weekly progress report,Work
+Performance Review,Your performance review is scheduled for Monday,Work
+Task Assignment,New tasks have been assigned to you,Work
+Budget Approval,The budget for Q4 has been approved,Work
+Happy Birthday,Wish you a very happy birthday,Personal
+Dinner Tonight,Are you free for dinner tonight?,Personal
+Call Mom,Don’t forget to call mom today,Personal
+Friend’s Wedding,We are invited to a friend’s wedding,Personal
+Gym Session,Reminder for your gym session at 6 PM,Personal
+Vacation Plan,Let's plan the vacation for December,Personal
+Book Club,Book club meeting is scheduled this Friday,Personal
+Doctor Appointment,Your doctor appointment is confirmed,Personal
+Car Service,Reminder for car service next week,Personal
+Movie Night,Do you want to watch a movie tonight?,Personal
+Flash Sale,Sneakers at 50% off this weekend,Promotions
+Limited Offer,Buy one get one free on all shirts,Promotions
+Mega Discount,Get up to 70% off on electronics,Promotions
+Holiday Sale,Special discounts for the holiday season,Promotions
+Coupon Code,Use code SAVE20 for 20% off,Promotions
+Clearance Sale,Clearance sale on all winter clothes,Promotions
+Free Shipping,Free shipping for orders above $50,Promotions
+Weekend Deals,Exclusive weekend deals available now,Promotions
+New Arrivals,Check out new arrivals this week,Promotions
+Special Offer,Special offer ends tonight,Promotions
+Amazon Order,Your order has been shipped,Updates
+Delivery Confirmation,Your package has been delivered,Updates
+Password Reset,Click the link to reset your password,Updates
+Subscription Renewal,Your subscription is due for renewal,Updates
+Account Alert,Unusual activity detected in your account,Updates
+Flight Ticket,Your flight booking is confirmed,Updates
+Event Reminder,Reminder: Webinar starts at 5 PM,Updates
+Appointment Confirmation,Your appointment is confirmed,Updates
+Service Update,Service will be down for maintenance tonight,Updates
+System Notification,Your system password will expire soon,Updates
+Facebook Notification,You have 3 new friend requests,Social
+Instagram Like,Someone liked your post,Social
+Twitter Mention,You were mentioned in a tweet,Social
+LinkedIn Message,You have a new LinkedIn message,Social
+YouTube Comment,Someone commented on your video,Social
+Snapchat Snap,You received a new snap,Social
+TikTok Follower,You have a new follower on TikTok,Social
+Reddit Reply,Your comment received a reply,Social
+Pinterest Pin,Your pin has been saved by someone,Social
+WhatsApp Message,You have a new message on WhatsApp,Social
+Meeting Agenda,Please review the agenda before the meeting,Work
+Client Call,Your client call is scheduled for tomorrow,Work
+Project Update,Project milestones updated in the tracker,Work
+Team Outing,Team outing planned for Friday evening,Work
+Budget Review,Please review the updated budget,Work
+Training Session,Mandatory training session tomorrow,Work
+Task Reminder,Reminder: Complete the assigned task,Work
+Presentation Slides,Slides for Monday presentation attached,Work
+Conference Registration,Register for the upcoming conference,Work
+Report Submission,Submit your quarterly report,Work
+Family Reunion,Don’t forget the family reunion this weekend,Personal
+Grocery Shopping,Remember to buy groceries,Personal
+Birthday Party,You are invited to a birthday party,Personal
+Yoga Class,Your yoga class starts at 7 AM,Personal
+Friend Call,Call your friend in the evening,Personal
+Music Concert,Tickets booked for the concert,Personal
+Weekend Trip,Plan for the weekend trip,Personal
+Pet Vaccination,Your pet vaccination appointment is scheduled,Personal
+Home Repair,Plumber will arrive tomorrow,Personal
+Car Insurance,Car insurance renewal due next month,Personal
+Special Discount,Limited time special discount on electronics,Promotions
+Summer Sale,Hot summer sale starts now,Promotions
+Flash Offer,Flash offer: 30% off on all items,Promotions
+Deal of the Day,Grab the deal of the day now,Promotions
+Promo Code,Use code EXTRA10 to get 10% off,Promotions
+Buy Now,Limited stock available,Promotions
+Seasonal Sale,Seasonal sale ending soon,Promotions
+Discount Voucher,Your discount voucher is valid for one week,Promotions
+Clearance Offer,Clearance offer on all items,Promotions
+Exclusive Offer,Exclusive offer for loyal customers,Promotions
+Package Shipped,Your package is on the way,Updates
+Delivery Scheduled,Delivery scheduled for tomorrow,Updates
+Tracking Info,Track your shipment online,Updates
+Subscription Confirmation,Your subscription has been confirmed,Updates
+Account Update,Your account details have been updated,Updates
+Flight Reminder,Reminder: Flight departs at 6 PM,Updates
+Service Notification,Service update: New features added,Updates
+System Alert,Alert: Software update required,Updates
+Payment Confirmation,Payment received successfully,Updates
+Security Alert,Unusual login detected,Updates
+Friend Request,You have a new friend request,Social
+Post Like,Someone liked your social media post,Social
+New Message,You received a new message on Messenger,Social
+Comment Reply,Someone replied to your comment,Social
+Follower Alert,You have a new follower,Social
+Video Like,Someone liked your uploaded video,Social
+Event Invite,You are invited to an event,Social
+Group Message,New message in your group,Social
+Snap Notification,You have a new snap,Social
+Story View,Someone viewed your story,Social
+Newsletter Update,Company newsletter: October edition,Updates
+Payment Reminder,Reminder: Pay your utility bill,Updates
+Appointment Reminder,Doctor appointment reminder,Updates
+Workshop Invite,Invitation to workshop tomorrow,Work
+Project Kickoff,Project kickoff meeting scheduled,Work
+Client Feedback Request,Please provide feedback for client project,Work
+Team Celebration,Team celebration planned for Friday,Work
+Training Reminder,Reminder: Complete online training session,Work
+Weekly Sync,Weekly team sync scheduled,Work
+Monthly Report,Monthly report submission due,Work
+Birthday Reminder,Wish your colleague a happy birthday,Personal
+Dinner Invitation,Dinner at my place tonight,Personal
+Weekend Plans,Plan your weekend activities,Personal
+Concert Tickets,Tickets booked for music concert,Personal
+Yoga Reminder,Yoga class starts at 6 AM,Personal

deploy.sh

@@ -0,0 +1,28 @@
+#!/bin/bash
+
+# This is a shell script to automate the deployment process to Hugging Face.
+# The 'echo' commands just print messages to the terminal so we can see the progress.
+
+echo "-------------------------------------"
+echo "Starting deployment to Hugging Face..."
+echo "-------------------------------------"
+
+# Step 1: Add all new and changed files to Git
+echo "=> Adding all files..."
+git add .
+
+# Step 2: Commit the changes with a message.
+# You can change the message in the quotes below each time if you want.
+echo "=> Committing files..."
+git commit -m "Update and deploy application"
+
+# Step 3: Push the code to the Hugging Face Space.
+# This assumes your remote is named 'space' and your local branch is 'master'.
+# It pushes your local 'master' branch to the 'main' branch on Hugging Face.
+echo "=> Pushing to Hugging Face..."
+git push --force space master:main
+
+echo "-------------------------------------"
+echo "✅ Deployment script finished."
+echo "Check your Hugging Face Space for the build status."
+echo "-------------------------------------"

predicted_emails.csv

@@ -0,0 +1,9 @@
+subject,body,predicted_folder
+Team Standup Reminder,Please join the daily standup meeting at 10 AM.,Work
+50% Off on Shoes,Grab the latest offer on sneakers.,Promotions
+Mom's Birthday,Don't forget to call mom today.,Personal
+Your Amazon Order,Your order has been shipped.,Updates
+Project Deadline,Reminder: Submit the project by tomorrow.,Work
+Weekend Plans,Are we still on for the hiking trip this weekend?,Personal
+Invoice #12345,Your invoice has been generated and attached.,Updates
+Dinner Invitation,Join us for dinner at 7 PM tonight.,Personal

requirements.txt

@@ -0,0 +1,87 @@
+accelerate==1.10.1
+aiofiles==24.1.0
+aiohappyeyeballs==2.6.1
+aiohttp==3.12.15
+aiosignal==1.4.0
+annotated-types==0.7.0
+anyio==4.11.0
+attrs==25.3.0
+audioop-lts==0.2.2
+beautifulsoup4==4.14.2
+Brotli==1.1.0
+certifi==2025.8.3
+charset-normalizer==3.4.3
+click==8.3.0
+colorama==0.4.6
+datasets==4.1.1
+dill==0.4.0
+fastapi==0.118.0
+ffmpy==0.6.1
+filelock==3.19.1
+frozenlist==1.7.0
+fsspec==2025.9.0
+gradio==5.48.0
+gradio_client==1.13.3
+groovy==0.1.2
+h11==0.16.0
+httpcore==1.0.9
+httpx==0.28.1
+huggingface-hub==0.35.3
+idna==3.10
+Jinja2==3.1.6
+joblib==1.5.2
+markdown-it-py==4.0.0
+MarkupSafe==3.0.3
+mdurl==0.1.2
+mpmath==1.3.0
+multidict==6.6.4
+multiprocess==0.70.16
+networkx==3.5
+numpy==2.3.3
+orjson==3.11.3
+packaging==25.0
+pandas==2.3.3
+pillow==11.3.0
+propcache==0.3.2
+psutil==7.1.0
+pyarrow==21.0.0
+pydantic==2.11.9
+pydantic_core==2.33.2
+pydub==0.25.1
+Pygments==2.19.2
+python-dateutil==2.9.0.post0
+python-dotenv==1.1.1
+python-multipart==0.0.20
+pytz==2025.2
+PyYAML==6.0.3
+regex==2025.9.18
+requests==2.32.5
+rich==14.1.0
+ruff==0.13.2
+safehttpx==0.1.6
+safetensors==0.6.2
+scikit-learn==1.7.2
+scipy==1.16.2
+semantic-version==2.10.0
+setuptools==65.5.0
+shellingham==1.5.4
+six==1.17.0
+sniffio==1.3.1
+soupsieve==2.8
+starlette==0.48.0
+sympy==1.14.0
+threadpoolctl==3.6.0
+tokenizers==0.22.1
+tomlkit==0.13.3
+torch==2.8.0
+tqdm==4.67.1
+transformers==4.56.2
+typer==0.19.2
+typing-inspection==0.4.2
+typing_extensions==4.15.0
+tzdata==2025.2
+urllib3==2.5.0
+uvicorn==0.37.0
+websockets==15.0.1
+xxhash==3.5.0
+yarl==1.20.1