Update app.py

app.py

@@ -61,13 +61,14 @@ google_api_key = os.environ['gemini_key']
 HF_key = os.environ['HF_token']
 cohere_api_key = os.environ['cohere_api']
 
+current_dir = os.getcwd()
 
 def langchain_document_loader():
     """
     Load documents from the temporary directory (TMP_DIR). 
     Files can be in txt, pdf, CSV or docx format.
     """
-    current_dir = os.getcwd()
+    #current_dir = os.getcwd()
     #TMP_DIR = current_dir
     global documents
     documents = []
@@ -162,7 +163,7 @@ embeddings_HuggingFace = select_embeddings_model(LLM_service="HuggingFace")
 
 def create_vectorstore(embeddings,documents,vectorstore_name):
     """Create a Chroma vector database."""
-    persist_directory = (LOCAL_VECTOR_STORE_DIR.as_posix() + "/" + vectorstore_name)
+    persist_directory = (current_dir + "/" + vectorstore_name)
     vector_store = Chroma.from_documents(
         documents=documents,
         embedding=embeddings,
@@ -212,7 +213,7 @@ print("vector_store_google:",vector_store_google._collection.count(),"chunks.")
 """
 
 vector_store_HF = Chroma(
-    persist_directory = LOCAL_VECTOR_STORE_DIR.as_posix() + "/Vit_All_HF_Embeddings",
+    persist_directory = current_dir + "/Vit_All_HF_Embeddings",
     embedding_function=embeddings_HuggingFace)
 print("vector_store_HF:",vector_store_HF._collection.count(),"chunks.")