| 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') | |
| edge_info = dataset.to_pandas() | |
| def subset_city_year(year = 50, city = ['المدينه', 'بغداد', 'كوفة', 'بصرة']): | |
| edges = edge_info[(edge_info['Year'] == year) & (edge_info['City'].isin(city))] | |
| return edges | |
| def get_narrators(year = 50, city = ['المدينه', 'بغداد', 'كوفة', 'بصرة']): | |
| df = subset_city_year(year, city) | |
| 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'}) | |
| app = gradio.Interface(get_narrators, | |
| [gradio.Dropdown(choices = cities, value = ['المدينه', 'بغداد', 'كوفة', 'بصرة'], multiselect=True), | |
| gradio.Slider(min_year, max_year, value = 0, label = 'Begining', info = 'Choose The Year to Retrieve Narrators'), | |
| ], | |
| gr.Dataframe()).launch() | |