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import gradio as gr | |
from transformers import pipeline | |
# Load model | |
qa_pipeline = pipeline("question-answering", model="distilbert-base-cased-distilled-squad") | |
# Function to generate answers | |
def answer_question(context, question): | |
if not context or not question: | |
return "⚠️ Please enter both a text passage and a question!" | |
result = qa_pipeline(question=question, context=context) | |
return result["answer"] | |
# Create Gradio UI | |
gr.Interface( | |
fn=answer_question, | |
inputs=[gr.Textbox(lines=7, placeholder="Enter your text passage here..."), gr.Textbox(placeholder="Ask a question based on the text...")], | |
outputs="text", | |
title="🤔 AI Q&A Assistant", | |
description="Enter a passage and ask a question about it. The AI will find the best answer for you!", | |
allow_flagging="never" | |
).launch() |