Update app.py

app.py

@@ -2,18 +2,17 @@ import gradio as gr
 from transformers import pipeline
 question_gen = pipeline("text2text-generation", model="valhalla/t5-base-qg-hl")
 
-def generate_questions(input_text, num_questions, question_type):
-    highlighted_text = input_text
-    if question_type == "mcq":
-        prefix = "generate questions:"
-    elif question_type == "subjective":
-        prefix = "generate descriptive questions:"
+def generate_questions(text, num_questions, question_type):
+    # Insert highlight tags around the first sentence for question generation
+    sentences = text.split('.')
+    if len(sentences) > 1:
+        highlighted = f"<hl> {sentences[0].strip()} <hl>." + '.'.join(sentences[1:])
     else:
-        prefix = "generate questions:"
-    prompt = f"{prefix} {highlighted_text}"
-    questions = question_gen(prompt, max_length=64, num_return_sequences=num_questions)
-    return [q['generated_text'] for q in questions]
+        highlighted = f"<hl> {text.strip()} <hl>"
 
+    prompt = f"generate questions: {highlighted}"
+    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)])
 with gr.Blocks() as demo:
     gr.Markdown("# AI Mock Test Generator")
     input_text = gr.Textbox(lines=10, label="Paste text or content here")