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from app.tapex import execute_query |
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import gradio as gr |
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def main(): |
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description = "Querying a csv using TAPEX model. You can ask a question about tabular data. TAPAS model " \ |
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"will produce the result. Finetuned TAPEX model runs on max 5000 rows and 20 columns data. " \ |
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"A sample data of shopify store sales is provided" |
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article = "<p style='text-align: center'><a href='https://unscrambl.com/' target='_blank'>Unscrambl</a> | <a href='https://huggingface.co/google/tapas-base-finetuned-wtq' target='_blank'>TAPAS Model</a></p><center><img src='https://visitor-badge.glitch.me/badge?page_id=abaranovskij_tablequery' alt='visitor badge'></center>" |
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iface = gr.Interface(fn=execute_query, |
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inputs=[gr.Textbox(label="Search query"), |
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gr.File(label="CSV file")], |
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outputs=[gr.JSON(label="Result"), |
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gr.Dataframe(label="All data")], |
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examples=[ |
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["What is the highest order_amount?", "shopify.csv"], |
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["Which user_id has the highest order_amount?", "shopify.csv"], |
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["Which payment method was used the most?", "shopify.csv"] |
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], |
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title="Table Question Answering (TAPEX)", |
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description=description, |
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article=article, |
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allow_flagging='never') |
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iface.launch(enable_queue=True) |
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if __name__ == "__main__": |
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main() |
