Update Demo.py

Demo.py

@@ -69,9 +69,8 @@ def create_pipeline(model):
 def fit_data(pipeline, json_data, question):
     spark_df = spark.createDataFrame([[json_data, question]]).toDF("table_json", "questions")
     model = pipeline.fit(spark_df)
-    result = model.transform(spark_df)
-    pan = result.select("answers_wtq.result", "answers_sqa.result").toPandas()
-    pan
+    res = model.transform(spark_df)
+    return res.select("answers_wtq.result", "answers_sqa.result").collect()
 
 # Sidebar content
 model = st.sidebar.selectbox(
@@ -173,10 +172,10 @@ output = fit_data(pipeline, table_json_str, text_to_analyze)
 st.markdown("---")
 st.subheader("Processed Output")
 
-# # Check if output is available
-# if output:
-#     results_wtq = output[0][0] if output[0][0] else "No results found."
-#     results_sqa = output[0][1] if output[0][1] else "No results found."
-#     st.markdown(f"**Answers from WTQ model:** {', '.join(results_wtq)}")
-#     st.markdown(f"**Answers from SQA model:** {', '.join(results_sqa)}")
-
+# Check if output is available
+if output:
+    # Extract and Display results
+    results_wtq = output[0][0] if output[0][0] else "No results found."
+    results_sqa = output[0][1] if output[0][1] else "No results found."
+    st.markdown(f"**Answers from WTQ model:** {', '.join(results_wtq)}")
+    st.markdown(f"**Answers from SQA model:** {', '.join(results_sqa)}")