updated the app.py

app.py

@@ -49,7 +49,6 @@ except Exception as e:
     tokenizer = AutoTokenizer.from_pretrained(fallback_model)
     model = AutoModelForCausalLM.from_pretrained(fallback_model)
 
-# Function to generate a formatted email
 def generate_email(recipient_name, recipient_email, industry, recipient_role, details):
     prompt = (
         f"Write a short professional email to {recipient_name}, "
@@ -85,10 +84,23 @@ def generate_email(recipient_name, recipient_email, industry, recipient_role, de
 
         # Format the email
         formatted_email = f"""\
-To: {recipient_name} 
+To: {recipient_name} <{recipient_email}>
+Subject: Collaboration Opportunity
+
+{email_body}
+
+Best regards,
+Jane Smith
+Android Developer
+Albertsons
+[Your Contact Information]
 """
         return formatted_email
 
+    except Exception as e:
+        logging.error(f"Error generating email: {str(e)}")
+        return f"Error generating email: {str(e)}"
+
 # Create Gradio interface
 iface = gr.Interface(
     fn=generate_email,
@@ -99,11 +111,15 @@ iface = gr.Interface(
         gr.Textbox(lines=1, label="Recipient Role (e.g., Manager, Director)"),
         gr.Textbox(lines=5, label="Personal/Company Details (e.g., name, product)"),
     ],
-    outputs="text",
+    outputs=gr.Textbox(lines=10, label="Generated Email or Error Message"),
     title="EmailGenie: AI-Powered Email Generator",
-    description="Automate the creation of personalized emails to increase engagement and conversion rates. Enter details to generate tailored emails."
+    description="Automate the creation of personalized emails. Enter details to generate tailored emails."
 )
 
 # Launch the app
 if __name__ == '__main__':
     iface.launch()
+
+# Log model information
+logging.info(f"Model name: {model.config._name_or_path}")
+logging.info(f"Model parameters: {model.num_parameters()}")