refactoring code

pages/3_🤖_Chatbot.py

@@ -1,4 +1,3 @@
-# 🤖
 import streamlit as st
 
 st.set_page_config(
@@ -67,9 +66,6 @@ if empty_openai_api_key:
 
 else:
     try:
-        # if st.button('Say hello'):
-        #     st.write('Why hello there')
-
         # container for chat history
         response_container = st.container()
         # container for text box
@@ -81,16 +77,12 @@ else:
             if query:
                 with st.spinner("typing..."):
                     conversation_string = get_conversation_string()
-                    # st.code(conversation_string)
                     refined_query = query_refiner(conversation_string, query)
-                    # st.subheader("Refined Query:")
-                    # st.write(refined_query)
                     context = find_match(refined_query,
                                         pinecone_api_key=st.session_state['pinecone_api_key'],
                                         pinecone_env=st.session_state['pinecone_env'],
                                         pinecone_index_namespace=st.session_state['pinecone_index_namespace']
-                                        )
-                    # print(context)  
+                                        ) 
                     response = conversation.predict(input=f"Context:\n {context} \n\n Query:\n{query}")
                 st.session_state.requests.append(query)
                 st.session_state.responses.append(response) 

requirements.txt

@@ -1,5 +1,5 @@
 altair<5
-streamlit==1.17.0
+streamlit==1.25.0
 streamlit-chat
 langchain
 openai

utils.py

@@ -9,7 +9,8 @@ import tempfile
 import streamlit as st
 import openai
 
-@st.cache(allow_output_mutation=True)
+# To create embeddings on hard disk
+@st.cache_resource(allow_output_mutation=True)
 def get_embeddings_model():
     model = SentenceTransformer('all-MiniLM-L6-v2')
     embeddings = SentenceTransformerEmbeddings(model_name="all-MiniLM-L6-v2")

👋_Introduction.py

@@ -28,9 +28,6 @@ if 'responses' not in st.session_state:
 if 'requests' not in st.session_state:
     st.session_state['requests'] = []
 
-if 'responses' not in st.session_state:
-    st.session_state['responses'] = ["How can I assist you?"]
-
 if 'buffer_memory' not in st.session_state:
     st.session_state.buffer_memory=ConversationBufferWindowMemory(k=3,return_messages=True)