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import os | |
import gradio as gr | |
from huggingface_hub import InferenceClient | |
# Get your Hugging Face token from environment variables (set this in your Space's secrets) | |
HF_TOKEN = os.getenv("HF_TOKEN") | |
# Initialize the inference client | |
client = InferenceClient( | |
provider="hf-inference", | |
api_key=HF_TOKEN, | |
) | |
# Define the function to use in Gradio | |
def answer_question(question, context): | |
if not HF_TOKEN: | |
return "HF_TOKEN not found. Please set it in the environment variables." | |
try: | |
result = client.question_answering( | |
question=question, | |
context=context, | |
model="deepset/roberta-base-squad2", | |
) | |
return result["answer"] | |
except Exception as e: | |
return f"Error: {str(e)}" | |
# Gradio Interface | |
iface = gr.Interface( | |
fn=answer_question, | |
inputs=[ | |
gr.Textbox(label="Question"), | |
gr.Textbox(label="Context", lines=5), | |
], | |
outputs="text", | |
title="Question Answering with RoBERTa", | |
description="Enter a question and context. The model will find the answer from the context.", | |
) | |
# Launch for Hugging Face Space | |
if __name__ == "__main__": | |
iface.launch() | |