Create app.py

app.py

@@ -0,0 +1,30 @@
+import os
+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)
+
+df = download_sheet_df(os.environ["SHEET_ID_SECRET"])
+
+def find_reviews(uid):
+    review_list = []
+    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":
+                review_list.append(df_u.iloc[0][["Full_Name_myucla", "Question 1 Response Edited"]])
+    except ValueError:
+        pass
+    except Exception as e:
+        raise e
+    if len(review_list) == 0:
+        review_list = pd.DataFrame([{"Error": "UID Not Found"}])
+    return review_list[:3]
+
+demo = gr.Interface(
+    fn=find_reviews, 
+    inputs="text", 
+    outputs=gr.Dataframe(headers=["Name", "Presentation Path"]),
+)
+demo.launch(debug=False)