Update app.py

app.py

@@ -12,7 +12,19 @@ model = AutoModelForCausalLM.from_pretrained(model_name)
 def analyze_email(email):
     prompt = f"""
     Analyze the email with the following criteria:
-    ...
+    1. Is the email a phishing attempt? (Yes/No)
+    2. Does the email create a sense of urgency? (Yes/No)
+    3. Are there grammatical errors? (List the errors or respond with "None.")
+    4. Does the email show intention to deceive or steal sensitive information? (Yes/No)
+    5. Is the greeting customized or generalized? (Customized/Generalized)
+    6. Does the email include a valid customer ID or reference number? (Yes/No)
+    7. Is the sender’s email address suspicious or spoofed? (Yes/No, and explain if suspicious)
+    8. Is the email requesting sensitive information such as passwords, bank details, or verification codes? (Yes/No)
+    9. Is there a hyperlink in the email? If yes, does the link appear suspicious (e.g., misspelled domain, shortened URL)? (Yes/No, and explain)
+   10. Is the tone of the email overly formal or informal, and does it match the sender’s usual style? (Formal/Informal, and Yes/No for match)
+   11. Does the email refer to any specific past transaction or interaction? (Yes/No)
+   12. Are there any noticeable inconsistencies, such as mismatched branding, incorrect logos, or unusual formatting? (List issues or respond with "None.")
+   13. Does the email encourage you to bypass standard security procedures? (Yes/No)
     Email: {email}
     """
     inputs = tokenizer(prompt, return_tensors="pt", truncation=True)