import numpy as np
import gradio as gr
import os
import pandas as pd
from datasets import load_dataset

Secret_token = os.getenv('token')

dataset = load_dataset('FDSRashid/hadith_info',data_files = 'Basic_Edge_Information.csv', token = Secret_token, split = 'train')
dataset2 = load_dataset('FDSRashid/hadith_info',data_files = 'masteredgecityratiosapplied_updated_with_ID_mapping_to_NEO4J.csv', token = Secret_token, split = 'train')
edge_info = dataset.to_pandas()
taraf_info = dataset2.to_pandas()
cities = taraf_info['City'].unique().tolist()
min_year = int(taraf_info['Year'].min())
max_year = int(taraf_info['Year'].max())

def subset_city_year( city , year ):
    edges = taraf_info[(taraf_info['Year'] == year) & (taraf_info['City'].isin(city))]
    return edges



def get_narrators( city , year ):
    try:
        df = subset_city_year(city, year)
        narrators = edge_info[edge_info['Edge_ID'].isin(df['ID'])]
        return narrators['Edge_Name'].reset_index().drop('index', axis = 1).rename(columns = {'Edge_Name': 'Teacher To Student'})
    except Exception as e:
        return str(e)


with gr.Blocks() as demo:
  Places = gr.Dropdown(choices = cities, value = ['المدينه', 'بغداد', 'كوفة', 'بصرة'], multiselect=True, label = 'Location')
  Last_Year = gr.Slider(min_year, max_year, value = 50, label = 'End', info = 'Choose the  year to display Narrators')
  btn = gr.Button('Submit')
  btn.click(fn = get_narrators, inputs = [Places, Last_Year], outputs = gr.DataFrame())
  demo.launch()