Create app.py

app.py

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+import pyarabic.araby as araby
+import pandas as pd
+import numpy as np
+import re
+from datasets import load_dataset
+from datasets import Features
+from datasets import Value
+from datasets import Dataset
+
+
+Secret_token = os.getenv('HF_token')
+
+dataset = load_dataset("FDSRashid/embed_matn", token = Secret_token)
+books = load_dataset('FDSRashid/Hadith_info', data_files='Books.csv', token=Secret_token)['train'].to_pandas()
+df = dataset["train"].to_pandas()
+
+
+dataset = load_dataset("FDSRashid/hadith_info", data_files = 'All_Matns.csv',token = Secret_token, features = features)
+matn_info = dataset['train'].to_pandas()
+matn_info = matn_info.drop(97550)
+matn_info = matn_info.drop(307206)
+matn_info['taraf_ID'] = matn_info['taraf_ID'].replace('KeyAbsent', -1)
+matn_info['taraf_ID'] = matn_info['taraf_ID'].astype(int)
+
+matn_info['Book ID'] = matn_info['bookid_hadithid'].apply(lambda x: int(x.split('_')[0]))
+matn_info['Hadith Number'] = matn_info['bookid_hadithid'].apply(lambda x: int(x.split('_')[1]))
+matn_info = matn_info.join(books, on='Book ID')
+cols_to_use = df.columns.difference(matn_info.columns)
+
+joined_df = matn_info.merge(df[cols_to_use], left_index=True, right_on='__index_level_0__')
+df = joined_df.copy()
+
+
+