Add application file

app.py

@@ -13,7 +13,6 @@ Original file is located at
 using the E5 model as the embedding model and translated dataset from huggingface
 """
 
-!pip install sentence_transformers
 
 """## Downloading the Embedding model"""
 
@@ -29,7 +28,6 @@ model = SentenceTransformer("intfloat/multilingual-e5-large").to('cuda')
 
 """## Downloading Translated data from english to arabic"""
 
-!pip3 install datasets
 from datasets import load_dataset
 
 
@@ -106,14 +104,6 @@ print(len(combined_list))
 
 embeddings1 = model.encode(combined_list)
 
-from sentence_transformers import SentenceTransformer
-import nltk
-nltk.download('punkt')
-from nltk.tokenize import word_tokenize
-import math
-from scipy import spatial
-import scipy
-
 def semantic_search(query, embeddings1, combined_list):
     query_embedding = model.encode(query)