Create app.py

app.py

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+# app.py
+import pandas as pd
+from transformers import pipeline
+import gradio as gr
+
+# Load synthetic data
+df = pd.read_csv("synthetic_profit.csv")
+
+# Initialize TAPAS QA pipeline
+qa = pipeline(
+    "table-question-answering",
+    model="google/tapas-base-finetuned-sqa",
+    tokenizer="google/tapas-base-finetuned-sqa"
+)
+
+def answer(query: str) -> str:
+    res = qa(table=df, query=query)
+    return f"**Answer:** {res['answer']} _(agg: {res['aggregate']})_"
+
+demo = gr.Interface(
+    fn=answer,
+    inputs=gr.Textbox(lines=2, placeholder="e.g. What was profit margin for Product B in EMEA Q2 2024?"),
+    outputs="markdown",
+    title="S/4HANA Profitability Chat",
+    description="Ask questions of synthetic S/4HANA data using TAPAS"
+)
+
+if __name__ == "__main__":
+    demo.launch()