Update app.py

app.py

@@ -2,11 +2,11 @@ import gradio as gr
 import pandas as pd
 from transformers import pipeline
 
-# 1) Load your synthetic SAP data
+# 1) Load your data
 df = pd.read_csv("synthetic_profit.csv")
 table = df.astype(str).to_dict(orient="records")
 
-# 2) Table‐QA pipeline with TAPEX
+# 2) TAPEX table‐QA pipeline
 qa = pipeline(
     "table-question-answering",
     model="microsoft/tapex-base-finetuned-wtq",
@@ -14,7 +14,7 @@ qa = pipeline(
     device=-1
 )
 
-# 3) Three few‐shot examples
+# 3) Few‐shot examples
 EXAMPLE_PROMPT = """
 Example 1:
 Q: What is the total revenue for Product A in EMEA in Q1 2024?
@@ -30,16 +30,19 @@ A: Filter Product=A & Region=EMEA & FiscalYear=2024 & FiscalQuarter=Q1, then sum
 """
 
 def answer_question(question: str) -> str:
-    # Prepend the examples to teach the model your pattern
     full_query = EXAMPLE_PROMPT + f"\nQ: {question}\nA:"
-    result = qa(table=table, query=full_query)
-    return result.get("answer", "No answer found.")
+    try:
+        result = qa(table=table, query=full_query)
+        return result.get("answer", "No answer found.")
+    except Exception as e:
+        # Return the actual exception message so you can debug
+        return f"❌ Pipeline error:\n{e}"
 
 # 4) Gradio UI
 iface = gr.Interface(
     fn=answer_question,
     inputs=gr.Textbox(lines=2, placeholder="Ask a basic question…", label="Your question"),
-    outputs=gr.Textbox(lines=4, label="Answer"),
+    outputs=gr.Textbox(lines=6, label="Answer"),
     title="SAP Profitability Q&A",
     description=(
         "Ask simple revenue/cost/margin questions on the synthetic SAP data. "