Update app.py

app.py

@@ -195,14 +195,14 @@ if create_vectorstores:
         vectorstore_name="Vit_All_OpenAI_Embeddings",
     )
     print("vector_store_OpenAI:",vector_store_OpenAI._collection.count(),"chunks.")
-    """
+
     vector_store_google,new_vectorstore_name = create_vectorstore(
         embeddings=embeddings_google,
         documents = chunks,
         vectorstore_name="Vit_All_Google_Embeddings"
     )
     print("vector_store_google:",vector_store_google._collection.count(),"chunks.")
-    
+    """ 
     
     vector_store_HF = create_vectorstore(
         embeddings=embeddings_HuggingFace,
@@ -217,12 +217,12 @@ vector_store_OpenAI = Chroma(
     persist_directory = LOCAL_VECTOR_STORE_DIR.as_posix() + "/Vit_All_OpenAI_Embeddings",
     embedding_function=embeddings_OpenAI)
 print("vector_store_OpenAI:",vector_store_OpenAI._collection.count(),"chunks.")
-"""
+
 vector_store_google = Chroma(
     persist_directory = current_dir + "/Vit_All_Google_Embeddings",
     embedding_function=embeddings_google)
 print("vector_store_google:",vector_store_google._collection.count(),"chunks.")
-
+"""
 
 vector_store_HF = Chroma(
     persist_directory = current_dir + "/Vit_All_HF_Embeddings",
@@ -254,7 +254,7 @@ vectorstore,search_type="similarity",k=4,score_threshold=None
 
 # similarity search
 #base_retriever_OpenAI = Vectorstore_backed_retriever(vector_store_OpenAI,"similarity",k=10)
-base_retriever_google = Vectorstore_backed_retriever(vector_store_google,"similarity",k=10)
+#base_retriever_google = Vectorstore_backed_retriever(vector_store_google,"similarity",k=10)
 base_retriever_HF = Vectorstore_backed_retriever(vector_store_HF,"similarity",k=10)
 
 
@@ -645,7 +645,7 @@ chain = ConversationalRetrievalChain.from_llm(
         LLM_provider="Google",api_key=google_api_key,temperature=0.1,
         model_name="gemini-pro"),
     memory=create_memory("gemini-pro"),
-    retriever = base_retriever_google,  #base_retriever_HF
+    retriever = base_retriever_HF,  #base_retriever_HF
     llm=instantiate_LLM(
         LLM_provider="Google",api_key=google_api_key,temperature=0.5,
         model_name="gemini-pro"),