Update app.py

app.py

@@ -2,6 +2,7 @@ import os
 import pandas as pd
 import gradio as gr
 
+
 def download_sheet_df(doc_id, sheet_id=0, header=0):
     sheet_url = f'https://docs.google.com/spreadsheets/d/{doc_id}/export?format=csv&gid={sheet_id}'
     return pd.read_csv(sheet_url, header=header)
@@ -10,10 +11,12 @@ df = download_sheet_df(os.environ["SHEET_ID_SECRET"])
 
 def find_reviews(uid):
     review_list = []
+    rows = []
     try:
         for reviewer_n in [1, 2, 3, 4]:
             df_u = df[df[f"Reviewer_{reviewer_n}_UID_NUMBER_myucla"].astype(int) == int(uid)].copy()
             if len(df_u) == 1 and str(df_u.iloc[0]["Question 1 Response Edited"]) != "nan":
+                rows.append(df_u.iloc[0]["Unnamed: 0"])
                 review_list.append(df_u.iloc[0][["Full_Name_myucla", "Question 1 Response Edited"]])
     except ValueError:
         pass
@@ -21,6 +24,9 @@ def find_reviews(uid):
         raise e
     if len(review_list) == 0:
         review_list = pd.DataFrame([{"Error": "UID Not Found"}])
+        print(f"Not Found uid: [{uid}]")
+    else:
+        print("Found rows:", sorted(rows))
     return review_list[:3]
 
 demo = gr.Interface(
@@ -28,4 +34,4 @@ demo = gr.Interface(
     inputs="text", 
     outputs=gr.Dataframe(headers=["Name", "Presentation Path"]),
 )
-demo.launch(debug=False)
+demo.launch(debug=False)