Update app.py

app.py

@@ -29,10 +29,10 @@ from langchain.prompts import PromptTemplate
 
 prefix_messages = [{"role": "system", "content": "You are a helpful assistant that is very good at answering questions about investments using the information given."}]
 
-model_options = {'all-mpnet-base-v2': "sentence-transformers/all-mpnet-base-v2",
-                'instructor-base': "hkunlp/instructor-base"}
+site_options = {'US': 'vanguard_embeddings_US',
+                'AUS': 'vanguard_embeddings'}
 
-model_options_list = list(model_options.keys())
+site_options_list = list(site_options.keys())
 
 memory = ConversationBufferMemory(memory_key='chat_history', return_messages=True, output_key='answer')
 
@@ -66,28 +66,21 @@ def load_prompt():
         
     return prompt
     
-def load_vectorstore(model):
+def load_vectorstore(site):
     '''load embeddings and vectorstore'''
-
-    if 'mpnet' in model:
-        
-        emb = HuggingFaceEmbeddings(model_name=model)
-        return FAISS.load_local('vanguard-embeddings', emb)
-
-    elif 'instructor'in model:
         
-        emb = HuggingFaceInstructEmbeddings(model_name=model,
-                                               query_instruction='Represent the Financial question for retrieving supporting paragraphs: ',
-                                               embed_instruction='Represent the Financial paragraph for retrieval: ')
-        return FAISS.load_local('vanguard_embeddings_inst', emb)
+    emb = HuggingFaceEmbeddings(model_name="all-mpnet-base-v2")
+    
+    return FAISS.load_local(site, emb)
 
 #default embeddings and store
-vectorstore = load_vectorstore(model_options['all-mpnet-base-v2'])
+vectorstore = load_vectorstore(website_options_list_options[0])
 
-def on_value_change(change):
-    '''When radio changes, change the embeddings'''
+def on_value_change(site):
+    '''When radio changes, change the website reference data'''
+    
     global vectorstore
-    vectorstore = load_vectorstore(model_options[change])
+    vectorstore = load_vectorstore(site)
     
 # vectorstore = load_vectorstore('vanguard-embeddings',sbert_emb)
     
@@ -165,15 +158,11 @@ with block:
         gr.Markdown("<h3><center>Chat-Your-Data (Investor Education)</center></h3>")
         embed_but = gr.Button(value='Load QA Chain')
     with gr.Row():
-        websites = gr.Radio(choices=data_options,value=data_options[0],label='Select US or AUS website data',
+        websites = gr.Radio(choices=site_options_list,value=site_options_list[0],label='Select US or AUS website data',
                 interactive=True)
         websites.change(on_value_change, websites)
-    with gr.Row():
-        embeddings = gr.Radio(choices=model_options_list,value=model_options_list[0], label='Choose your Embedding Model',
-                             interactive=True)
-        embeddings.change(on_value_change, embeddings)
     
-    vectorstore = load_vectorstore(embeddings.value)
+    vectorstore = load_vectorstore(websites.value)
     
     chatbot = gr.Chatbot()