Update app.py

app.py

@@ -108,9 +108,14 @@ def create_vector_database(loaded_documents):
     text_splitter = RecursiveCharacterTextSplitter(chunk_size=500, chunk_overlap=30, length_function = len)
     chunked_documents = text_splitter.split_documents(loaded_documents)
 
-    embeddings = HuggingFaceBgeEmbeddings(
-        model_name = "BAAI/bge-large-en"
+    embeddings = HuggingFaceEmbeddings(
+        model_name="sentence-transformers/all-MiniLM-L6-v2"
+        # model_name = "sentence-transformers/all-mpnet-base-v2"
     )
+
+    # embeddings = HuggingFaceBgeEmbeddings(
+    #     model_name = "BAAI/bge-large-en"
+    # )
     
     # model_name = "BAAI/bge-large-en"
     # model_kwargs = {'device': 'cpu'}
@@ -121,18 +126,19 @@ def create_vector_database(loaded_documents):
     # encode_kwargs=encode_kwargs
     # )
     
-    # persist_directory = 'db'
+    persist_directory = 'db'
     # Create and persist a Chroma vector database from the chunked documents
     db = Chroma.from_documents(
         documents=chunked_documents,
-        embedding=embeddings,
-        # persist_directory=persist_directory
+        embeddings=embeddings,
+        persist_directory=persist_directory
         # persist_directory=DB_DIR,
     )
     db.persist()
     # db = Chroma(persist_directory=persist_directory, 
     #               embedding_function=embedding)
     return db
+    
 
 def set_custom_prompt():
     """