Update app.py

app.py

@@ -2,11 +2,21 @@ import gradio as gr
 from transformers import pipeline
 
 # Load the question generation model
-question_gen = pipeline("text2text-generation", model="iarfmoose/t5-base-question-generator")
+question_gen = pipeline("text2text-generation", model="valhalla/t5-base-qg-hl")
 
 # Function to generate questions
 def generate_questions(text, num_questions, question_type):
-    prompt = f"generate questions: {text}"
+    # Highlight the answer in the context using <hl> tags
+    # For simplicity, we'll highlight the first sentence
+    sentences = text.strip().split('.')
+    if len(sentences) > 1:
+        answer = sentences[0].strip()
+        context = '. '.join(sentences[1:]).strip()
+    else:
+        answer = text.strip()
+        context = text.strip()
+
+    prompt = f"generate question: <hl> {answer} <hl> {context}"
     results = question_gen(prompt, max_length=128, num_return_sequences=num_questions)
     return "\n\n".join([f"{i+1}. {r['generated_text']}" for i, r in enumerate(results)])