Update app.py

app.py

@@ -1,7 +1,86 @@
-import streamlit as st
-from transformers import pipeline
-pipe  = pipeline('sentiment-analysis')
-text =st.text_area('enter')
-if text:
-    out = pipe(text)
-    st.json(out)
+import imaplib
+import email
+from transformers import BartForConditionalGeneration, BartTokenizer, pipeline
+import torch
+import email.header
+
+model_name = 'facebook/bart-large-cnn'
+tokenizer = BartTokenizer.from_pretrained(model_name)
+model = BartForConditionalGeneration.from_pretrained(model_name)
+
+sentiment_analyzer = pipeline('sentiment-analysis', model='distilbert-base-uncased')
+
+mail = imaplib.IMAP4_SSL('imap.gmail.com') 
+mail.login('[email protected]', 'fwqw pnmq ulip umjl')
+mail.select('inbox') 
+
+def generate_summary(email_text, max_length=20):
+    inputs = tokenizer([email_text], return_tensors='pt', max_length=1024, truncation=True)
+
+    with torch.no_grad():
+        summary_ids = model.generate(**inputs, max_length=max_length)
+
+    summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
+    return summary
+
+from datetime import date
+today = date.today()
+today_date = today.strftime("%d-%b-%Y")
+
+status, email_ids = mail.search(None, 'SINCE', today_date)
+email_ids = email_ids[0].split()
+
+for email_id in email_ids:
+    status, msg_data = mail.fetch(email_id, '(RFC822)')
+    raw_email = msg_data[0][1]
+    msg = email.message_from_bytes(raw_email)
+    sender = msg['From']
+
+    subject = email.header.decode_header(msg['Subject'])
+    subject_str = ""
+    for part, encoding in subject:
+        if isinstance(part, bytes):
+            if encoding:
+                subject_str += part.decode(encoding)
+            else:
+                subject_str += part.decode('utf-8')
+        else:
+            subject_str += part
+
+    body = ""
+
+    if msg.is_multipart():
+        for part in msg.walk():
+            if part.get_content_type() == "text/plain":
+                body = part.get_payload(decode=True).decode()
+                break
+    else:
+        body = msg.get_payload(decode=True).decode()
+
+    if body:
+        word_count = len(body.split())
+        if word_count < 10:
+            summary = body
+        else:
+            if word_count < 50:
+                summary = generate_summary(body, max_length=20)
+            else:
+                summary = generate_summary(body, max_length=50)
+
+        sentiment_result = sentiment_analyzer(summary)
+        label = sentiment_result[0]['label']
+        score = sentiment_result[0]['score']
+
+        if score >= 0.53:
+            email_label = "Important"
+        else:
+            email_label = "Not Important"
+
+        print(f"From: {sender}")
+        print(f"Email Subject: {subject_str}")
+        print(f"Generated Summary: {summary}")
+        print(f"Sentiment Label: {email_label}")
+        print(f"Sentiment Score: {score}")
+        print("-" * 50)
+
+mail.logout()