Upload 2 files

app.py

@@ -1,26 +1,19 @@
 import gradio as gr
 from transformers import pipeline
 
-# ✅ Use the correct pipeline task
+# Correct pipeline task
 question_generator = pipeline("text2text-generation", model="valhalla/t5-base-e2e-qg")
 
 def generate_questions(text):
-    # Split text into chunks (optional)
-    chunks = text.split(". ")
-    questions = []
-    for chunk in chunks:
-        if len(chunk.strip()) > 0:
-            result = question_generator(chunk, max_length=64)[0]['generated_text']
-            questions.append(f"❓ {result}")
-    return "\n".join(questions)
+    inputs = f"generate questions: {text}"
+    outputs = question_generator(inputs, max_length=256, do_sample=False)
+    return outputs[0]["generated_text"]
 
-# Gradio interface
-interface = gr.Interface(
+iface = gr.Interface(
     fn=generate_questions,
-    inputs=gr.Textbox(lines=15, placeholder="Paste your long text here..."),
+    inputs=gr.Textbox(lines=10, label="Enter your paragraph"),
     outputs="text",
-    title="🔍 Generate Questions from Text",
-    description="Uses a T5 model to generate questions from a multi-sentence paragraph."
+    title="🔍 Generate Questions from Text"
 )
 
-interface.launch()
+iface.launch()