Update app.py

app.py

@@ -160,16 +160,20 @@ def create_vector_database(loaded_documents):
 
     # Initialize HuggingFace embeddings
     embeddings = HuggingFaceEmbeddings(
-        model_name="sentence-transformers/all-MiniLM-L6-v2"
+        # model_name="sentence-transformers/all-MiniLM-L6-v2"
+        model_name = "BAAI/bge-large-en"
     )
 
     # Create and persist a Chroma vector database from the chunked documents
     db = Chroma.from_documents(
         documents=chunked_documents,
         embedding=embeddings,
+        persist_directory=persist_directory
         # persist_directory=DB_DIR,
     )
-    db.persist()
+    # db.persist()
+    db = Chroma(persist_directory=persist_directory, 
+                  embedding_function=embedding)
     return db
 
 def set_custom_prompt_condense():