| 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() | |
| 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().rename(columns = {'Edge_Name': 'Teacher To Student'}) | |
| except Exception as e: | |
| return str(e) | |
| app = gr.Interface(get_narrators, | |
| [gr.Dropdown(choices = cities, value = ['المدينه', 'بغداد', 'كوفة', 'بصرة'], multiselect=True), | |
| gr.Slider(-11,800, value = 50, label = 'Year', info = 'Choose The Year to Retrieve Narrators'), | |
| ], | |
| 'dataframe', live = True) | |
| app.launch() | |