Update app.py

app.py

@@ -25,9 +25,9 @@ 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['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')
+matn_info = pd.merge(matn_info, 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__')
@@ -42,7 +42,7 @@ def find_most_similar_matn(text, n):
     indices = np.argsort(cos_sim)[0][-n:]
     matns = df.iloc[indices]
     matns['Similarity'] = cos_sim[0][indices]
-    return matns[['Book_Name', 'matn', 'taraf_ID', 'Book ID', 'Hadith Number', 'Author', 'Similarity']]
+    return matns[['Book_Name', 'matn', 'taraf_ID', 'Book_ID', 'Hadith Number', 'Author', 'Similarity']]
 
 with gr.Blocks() as demo:
     text_input = gr.Textbox()