Update app.py

app.py

@@ -33,7 +33,7 @@ def load_vectorstore(model):
                                                embed_instruction='Represent the Financial paragraph for retrieval: ')
         return FAISS.load_local('vanguard_embeddings_inst', emb)
 
-#default embeddings
+#default embeddings and store
 vectorstore = load_vectorstore(model_options['all-mpnet-base-v2'])
 
 def on_value_change(change):
@@ -73,6 +73,10 @@ def get_chain(vectorstore):
         condense_question_prompt=CONDENSE_QUESTION_PROMPT,
     )
     return qa_chain
+
+def load_chain():
+    chain = get_chain(vectorstore)
+    return chain
     
     
 class ChatWrapper:
@@ -102,6 +106,7 @@ block = gr.Blocks(css=".gradio-container {background-color: lightgray}")
 with block:
     with gr.Row():
         gr.Markdown("<h3><center>Chat-Your-Data (Investor Education)</center></h3>")
+        enbed_but = gr.Button(value='Load QA Chain')
 
     with gr.Row():
         embeddings = gr.Radio(choices=model_options_list,value=model_options_list[0], label='Choose your Embedding Model',
@@ -109,7 +114,7 @@ with block:
         embeddings.change(on_value_change, embeddings)
     
     vectorstore = load_vectorstore(embeddings.value)
-    chain = get_chain(vectorstore)
+    
     chatbot = gr.Chatbot()
 
     chat = ChatWrapper()
@@ -143,10 +148,13 @@ with block:
     agent_state = gr.State()
 
     
-    submit.click(chat, inputs=[message, state, chain], outputs=[chatbot, state])
-    message.submit(chat, inputs=[message, state, chain], outputs=[chatbot, state])
+    submit.click(chat, inputs=[message, state, agent_state], outputs=[chatbot, state])
+    message.submit(chat, inputs=[message, state, agent_state], outputs=[chatbot, state])
 
-    # agent_state = chain
+    embed_but.change(
+        load_chain,
+        outputs=[agent_state],
+    )
 
     gr.Markdown("![visitor badge](https://visitor-badge.glitch.me/badge?page_id=nickmuchi-investor-chatchain)")