Update app.py

app.py

@@ -5,17 +5,18 @@ import pandas as pd
 import torch
 from pathlib import Path  
 import time
+from datetime import datetime
 
 model = SentenceTransformer('intfloat/multilingual-e5-large-instruct')
 print("load model")
-print(time.time())
+print(datetime.fromtimestamp(time.time()))
 
 hadiths = pd.read_csv('all_hadiths_clean.csv', delimiter=",")
 document_embeddings = torch.load('encoded_hadiths_multilingual-e5-large-instruct (1).sav',map_location ='cpu')
 #file = open('encoded_hadiths_multilingual-e5-large-instruct (1).sav','rb')
 #document_embeddings = pickle.load(file)
 print("load hadiths")
-print(time.time())
+print(datetime.fromtimestamp(time.time()))
 
 # Define the function to categorize ages
 def categorize_source(source):
@@ -44,21 +45,21 @@ def find(query):
         get_detailed_instruct(task, query)
     ]
     print("start")
-    print(time.time())
+    print(datetime.fromtimestamp(time.time()))
     
     query_embeddings = model.encode(queries, convert_to_tensor=True, normalize_embeddings=True)
     print("embed query")
-    print(time.time())
+    print(datetime.fromtimestamp(time.time()))
     
     scores = (query_embeddings @ document_embeddings.T) * 100
     print("consine similarity")
-    print(time.time())
+    print(datetime.fromtimestamp(time.time()))
 
     # insert the similarity value to dataframe & sort it
     hadiths['similarity'] = scores.tolist()[0]
     sorted_hadiths = hadiths.sort_values(by='similarity', ascending=False)
     print("sort hadiths")
-    print(time.time())
+    print(datetime.fromtimestamp(time.time()))
     
     results = sorted_hadiths.head(3).drop(columns=['id', 'hadith_id', 'chain_indx'])
     results['source_cat'] = results['source'].apply(categorize_source)
@@ -72,7 +73,7 @@ def find(query):
     results = results.drop(columns=['source', 'chapter_no', 'hadith_no', 'chapter', 'similarity', 'text_ar', 'text_en'])
     
     print("prepare results")
-    print(time.time())
+    print(datetime.fromtimestamp(time.time()))
     
     #return sorted_quran
     #filepath = Path(query+'.csv')