import os
import time
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)

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
    except Exception as e:
        raise e
    if len(review_list) == 0:
        review_list = pd.DataFrame([{"Error": "UID Not Found"}])
        print(time.strftime("%Y-%m-%d %H:%M:%S", time.localtime()), f"Not Found uid: [{uid}]")
    else:
        print(time.strftime("%Y-%m-%d %H:%M:%S", time.localtime()), "Found rows:", sorted(rows))
    return review_list[:3]

demo = gr.Interface(
    fn=find_reviews, 
    inputs="text", 
    outputs=gr.Dataframe(headers=["Name", "Presentation Path"]),
)
demo.launch(debug=False)