Update app.py

app.py

@@ -1,14 +1,13 @@
 from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM
 import gradio as gr
-import pandas as pd
 
-# Load the Hugging Face model with device mapping for resource optimization
+# Load the Hugging Face model
 model_name = "fbellame/llama2-pdf-to-quizz-13b"
 tokenizer = AutoTokenizer.from_pretrained(model_name)
 model = AutoModelForCausalLM.from_pretrained(model_name, device_map="auto")
 quiz_pipeline = pipeline("text2text-generation", model=model, tokenizer=tokenizer)
 
-# Example quiz data (replace with your dynamic generation logic)
+# Example quiz data (replace with dynamic generation logic)
 quiz_data = [
     {
         "question": "What is the purpose of transformers in power systems?",
@@ -54,6 +53,7 @@ def evaluate_question(rating, feedback, email, discipline, experience):
 def generate_mailto_link():
     if not feedback_list:
         return "No feedback to send."
+    
     subject = "Feedback for Train the Trainer App"
     body_lines = ["Feedback for Train the Trainer App:\n"]
     for entry in feedback_list:
@@ -66,7 +66,8 @@ def generate_mailto_link():
         body_lines.append(f"Experience: {entry['experience']} years\n")
         body_lines.append("\n---\n")
     body = "\n".join(body_lines)
-    mailto_link = f"mailto:[email protected]?subject={subject}&body={body.replace(' ', '%20').replace('\n', '%0A')}"
+    body_encoded = body.replace(" ", "%20").replace("\n", "%0A")
+    mailto_link = f"mailto:[email protected]?subject={subject}&body={body_encoded}"
     return mailto_link
 
 # Gradio Interface