Update app.py

app.py

@@ -9,6 +9,7 @@ from langchain.embeddings import HuggingFaceEmbeddings
 from langchain.text_splitter import RecursiveCharacterTextSplitter
 from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
 from langchain.vectorstores import Chroma
+from langchain.embeddings import HuggingFaceBgeEmbeddings
 from langchain.document_loaders import (
     CSVLoader,
     DirectoryLoader,
@@ -160,9 +161,11 @@ def create_vector_database(loaded_documents):
     chunked_documents = text_splitter.split_documents(loaded_documents)
 
     # Initialize HuggingFace embeddings
-    embeddings = HuggingFaceEmbeddings(
-        model_name="sentence-transformers/all-MiniLM-L6-v2"
-        # model_name = "BAAI/bge-large-en"
+    # embeddings = HuggingFaceEmbeddings(
+    #     model_name="sentence-transformers/all-MiniLM-L6-v2"
+    # )
+    embeddings = HuggingFaceBgeEmbeddings(
+        model_name = "BAAI/bge-large-en"
     )
 
     # Create and persist a Chroma vector database from the chunked documents