Create app.py

app.py

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+from app.tapas import execute_query
+import gradio as gr
+
+
+def main():
+    description = "Querying a csv using TAPAS model. You can ask a question about tabular data. TAPAS model " \
+                  "will produce the result. Finetuned TAPAS model runs on max 500 rows and 10 columns data. " \
+                  "A sample data of shopify store sales is provided"
+
+    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>"
+
+    iface = gr.Interface(fn=execute_query,
+                         inputs=[gr.Textbox(label="Search query"),
+                                 gr.File(label="CSV file")],
+                         outputs=[gr.JSON(label="Result"),
+                                  gr.Dataframe(label="All data")],
+                         examples=[
+                             ["What is the highest order_amount?", "shopify.csv"],
+                             ["Which user_id has the highest order_amount?", "shopify.csv"],
+                             ["Which payment method was used the most?", "shopify.csv"]
+                         ],
+                         title="Table Question Answering (TAPAS)",
+                         description=description,
+                         article=article,
+                         allow_flagging='never')
+    # Use this config when running on Docker
+    # iface.launch(server_name="0.0.0.0", server_port=7000)
+    iface.launch(enable_queue=True)
+
+
+if __name__ == "__main__":
+    main()