How do you implement conversation memory?

from langchain_core.chat_history import BaseChatMessageHistory
from langchain_community.chat_message_histories import ChatMessageHistory
from langchain_core.runnables.history import RunnableWithMessageHistory
from langchain_openai import ChatOpenAI
from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder

# In-memory store (swap for Redis, DynamoDB etc. in production)
store = {}

def get_session_history(session_id: str) -> BaseChatMessageHistory:
    if session_id not in store:
        store[session_id] = ChatMessageHistory()
    return store[session_id]

prompt = ChatPromptTemplate.from_messages([
    ("system", "You are a helpful assistant."),
    MessagesPlaceholder("history"),
    ("human", "{input}"),
])

chain = prompt | ChatOpenAI()

chain_with_memory = RunnableWithMessageHistory(
    chain,
    get_session_history,
    input_messages_key="input",
    history_messages_key="history",
)

# session_id identifies the conversation thread
chain_with_memory.invoke(
    {"input": "My name is Alice."},
    config={"configurable": {"session_id": "alice-123"}},
)
chain_with_memory.invoke(
    {"input": "What is my name?"},
    config={"configurable": {"session_id": "alice-123"}},
)