Update README.md

README.md

@@ -1,6 +1,63 @@
----
-language:
-- en
-library_name: transformers
-pipeline_tag: summarization
----
+import imaplib
+import email
+from transformers import BartForConditionalGeneration, BartTokenizer, pipeline
+
+# Load pre-trained model and tokenizer for summarization
+model_name = 'facebook/bart-large-cnn'
+tokenizer = BartTokenizer.from_pretrained(model_name)
+model = BartForConditionalGeneration.from_pretrained(model_name)
+
+# Load sentiment analysis model
+sentiment_analyzer = pipeline('sentiment-analysis', model='distilbert-base-uncased')
+
+# Connect to your email account
+mail = imaplib.IMAP4_SSL('imap.gmail.com')  # Example for Gmail, adjust accordingly
+mail.login('[email protected]', 'your_password')
+mail.select('inbox')  # Select the mailbox you want to retrieve emails from
+
+# Function to generate summary
+def generate_summary(email_text):
+    inputs = tokenizer([email_text], return_tensors='pt', max_length=1024, truncation=True)
+
+    with torch.no_grad():
+        summary_ids = model.generate(**inputs)
+
+    summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
+    return summary
+
+# Search for all emails
+status, messages = mail.search(None, 'ALL')
+message_ids = messages[0].split()
+
+# Process and summarize the latest 10 emails received today
+for msg_id in message_ids[-10:]:
+    status, msg_data = mail.fetch(msg_id, '(RFC822)')
+    raw_email = msg_data[0][1]
+    msg = email.message_from_bytes(raw_email)
+    sender = msg['From']
+    subject = msg['subject']
+    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:
+        summary = generate_summary(body)
+
+        # Perform sentiment analysis on the summary
+        sentiment_result = sentiment_analyzer(summary)
+        label = sentiment_result[0]['label']
+        score = sentiment_result[0]['score']
+
+        print(f"From: {sender}")
+        print(f"Email Subject: {subject}")
+        print(f"Generated Summary: {summary}")
+        print(f"Sentiment: {label}, Score: {score}")
+        print("-" * 50)
+
+mail.logout()