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Create app.py
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app.py
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import os
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import gradio as gr
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import pyarabic.araby as araby
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import pandas as pd
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import re
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from datasets import load_dataset
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from datasets import Features
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from datasets import Value
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from datasets import Dataset
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Secret_token = os.getenv('HF_token')
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books = load_dataset('FDSRashid/Hadith_info', data_files='Books.csv', token=Secret_token)['train'].to_pandas()
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books.loc[:, 'book_type'] = books['book_type'].apply(lambda x: x.replace('"', '')[2:])
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books.loc[:, 'Book_Name'] = books['Book_Name'].apply(lambda x: x.replace('"', ''))
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books.loc[:, 'Author'] = books['Author'].apply(lambda x: x.replace('"', ''))
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books = books.drop(columns = ['field5', 'field6', 'field7', 'field8'])
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def book_retriever(name):
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if 'ALL' in name:
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return books
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else:
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full_names = name.replace(', ', '|').replace(',', '|')
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return books[(books['Book_Name'].apply(lambda x: araby.strip_diacritics(x)).str.contains(araby.strip_diacritics(name), regex=True)) | (books['Author'].apply(lambda x: araby.strip_diacritics(x)).str.contains(araby.strip_diacritics(name), regex=True)) | (books['Book_ID'].astype(str).isin(full_names.split('|')))]
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with gr.Blocks() as demo:
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text_input = gr.Textbox()
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text_output = gr.DataFrame(wrap=True)
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text_button = gr.Button("Search")
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text_button.click(narrator_retriever, inputs=text_input, outputs=text_output)
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demo.launch()
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