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import gradio as gr
from transformers import pipeline
# Load the model from Hugging Face
qa_pipeline = pipeline("question-answering", model="nikhilwani/question_answering")
# Define the QA function
def answer_question(context, question):
result = qa_pipeline(question=question, context=context)
return result["answer"]
# Create a Gradio app using the new syntax for Gradio 5.5.0
with gr.Blocks() as demo:
gr.Markdown("# Question Answering")
gr.Markdown("Provide context and ask a question to get an answer.")
with gr.Row():
context_input = gr.Textbox(lines=5, placeholder="Enter the context here...", label="Context")
question_input = gr.Textbox(placeholder="Ask your question here...", label="Question")
with gr.Row():
submit_button = gr.Button("Submit")
output_box = gr.Textbox(label="Answer")
# Connect the function to the components
submit_button.click(answer_question, inputs=[context_input, question_input], outputs=output_box)
# Launch the app
demo.launch()
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