Update app.py

app.py

@@ -2,9 +2,27 @@
 from langchain_community.vectorstores import Qdrant
 from langchain_community.embeddings import SentenceTransformerEmbeddings
 from qdrant_client import QdrantClient
+from transformers import AutoModel, AutoTokenizer
+import os
 import pandas as pd
 import gradio as gd
 
+# Get the current directory
+current_directory = os.getcwd()
+
+# Define the model name
+model_name = 'sentence-transformers/clip-ViT-B-32'
+
+# Load the model and tokenizer
+model = AutoModel.from_pretrained(model_name)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+# Save the model and tokenizer to the current directory
+model.save_pretrained(current_directory)
+tokenizer.save_pretrained(current_directory)
+
+print(f"Model and tokenizer saved in the current directory: {current_directory}")
+
 embeddings = SentenceTransformerEmbeddings(model_name='sentence-transformers/clip-ViT-B-32')
 
 def get_results(search_results):