Update app.py

app.py

@@ -34,11 +34,16 @@ def chunk_text(text, chunk_size=500, overlap=50):
     return chunks
 
 # Step 3: Generate Embeddings
+@st.cache_resource(show_spinner=False)
+def load_embedding_model():
+    return SentenceTransformer("sentence-transformers/all-MiniLM-L6-v2")
+
 def generate_embeddings(chunks):
-    model = SentenceTransformer('all-MiniLM-L6-v2')  # Use your preferred model
-    embeddings = model.encode(chunks)
+    model = load_embedding_model()
+    embeddings = model.encode(chunks, show_progress_bar=True)
     return embeddings
 
+
 # Step 4: Store Embeddings in FAISS
 def store_embeddings_in_faiss(embeddings):
     dimension = len(embeddings[0])