add memory to chatbot

recipes/natural_language_processing/chatbot/chatbot_ui.py

@@ -1,7 +1,8 @@
 from langchain_openai import ChatOpenAI
 from langchain.chains import LLMChain
 from langchain_community.callbacks import StreamlitCallbackHandler
-from langchain_core.prompts import ChatPromptTemplate
+from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
+from langchain.memory import ConversationBufferWindowMemory
 import streamlit as st
 import requests
 import time
@@ -37,18 +38,28 @@ def checking_model_service():
 for msg in st.session_state.messages:
     st.chat_message(msg["role"]).write(msg["content"])
 
+@st.cache_resource()
+def memory():
+    memory = ConversationBufferWindowMemory(return_messages=True,k=10)
+    return memory
+
 llm = ChatOpenAI(base_url=model_service, 
-             api_key="sk-no-key-required",
-             streaming=True,
-             callbacks=[StreamlitCallbackHandler(st.container(),
-                                                expand_new_thoughts=True,
-                                                collapse_completed_thoughts=True)])
+        api_key="sk-no-key-required",
+        streaming=True,
+        callbacks=[StreamlitCallbackHandler(st.empty(),
+                                            expand_new_thoughts=True,
+                                            collapse_completed_thoughts=True)])
+
 prompt = ChatPromptTemplate.from_messages([
     ("system", "You are world class technical advisor."),
+    MessagesPlaceholder(variable_name="history"),
     ("user", "{input}")
 ])
 
-chain = LLMChain(llm=llm, prompt=prompt)
+chain = LLMChain(llm=llm, 
+                prompt=prompt,
+                verbose=False,
+                memory=memory())
 
 if prompt := st.chat_input():
     st.session_state.messages.append({"role": "user", "content": prompt})