Create app.py

app.py

@@ -0,0 +1,32 @@
+import gradio as gr
+from transformers import pipeline
+
+# Initialize the question-answering pipeline
+qa_pipeline = pipeline("question-answering")
+
+def answer_question(context, question):
+    """
+    Function to run the QA pipeline and get the answer.
+    
+    :param context: The context in which the question is asked.
+    :param question: The question that needs to be answered.
+    :return: Answer from the QA model.
+    """
+    result = qa_pipeline({'context': context, 'question': question})
+    return result['answer']
+
+# Create the Gradio interface
+interface = gr.Interface(
+    fn=answer_question,
+    inputs=[
+        gr.Textbox(label="Context", placeholder="Enter context here...", lines=4),  # Left-side input
+        gr.Textbox(label="Question", placeholder="Ask a question here...", lines=1)  # Right-side input
+    ],
+    outputs="text",  # Output as text
+    live=True,  # Optional: Display results as the user types
+    layout="horizontal"  # Align inputs side by side
+)
+
+# Launch the interface
+if __name__ == "__main__":
+    interface.launch()