Created QandA AI app

app.py

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+import gradio as gr
+from transformers import pipeline
+
+# Part 1: Load the model ONCE
+print("Loading the MobileBERT model...")
+info_extractor = pipeline("question-answering", model="csarron/mobilebert-uncased-squad-v2")
+print("Model loaded successfully!")
+
+# Part 2: Create the function that the UI will call
+# This function takes the document and question from the UI,
+# gets the answer from the model, and returns it.
+def extract_information(context, question):
+    print(f"Extracting answer for question: '{question}'")
+    result = info_extractor(question=question, context=context)
+    return result['answer']
+
+# Part 3: Build and launch the Gradio Interface
+print("Launching Gradio interface...")
+iface = gr.Interface(
+    fn=extract_information,
+    inputs=[
+        gr.Textbox(lines=7, label="Document", placeholder="Paste the document or text you want to ask questions about..."),
+        gr.Textbox(label="Question", placeholder="What specific detail are you looking for?")
+    ],
+    outputs=gr.Textbox(label="Answer"),
+    title="💡 Efficient Information Extractor",
+    description="Ask a question about the document below to pull out specific details using a MobileBERT model."
+)
+
+iface.launch()

requirements.txt

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+gradio
+transformers
+torch