10. Add ChatMessageHistory to RunnableWithMessageHistory

Chain creation method to remember previous conversations

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# API KEY A configuration file for managing environment variables
from dotenv import load_dotenv

# API KEY load information
load_dotenv()

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True

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# LangSmith Set up tracking. https://smith.langchain.com
# !pip install langchain-teddynote
from langchain_teddynote import logging

# Enter a project name.
logging.langsmith("CH05-Memory")

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 Start tracking LangSmith. 
[Project name] 
CH05-Memory 

Multi-turn Chain to remember previous conversations

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


# Prompt definition
prompt = ChatPromptTemplate.from_messages(
    [
        (
            "system",
            "you are Question-Answering This is a chatbot. Please provide answers to the questions given.",
        ),
        # For conversation records key person chat_history Please use it without any changes if possible!
        MessagesPlaceholder(variable_name="chat_history"),
        ("human", "#Question:\n{question}"),  # Use user input as a variable
    ]
)

# llm generation
llm = ChatOpenAI(model_name="gpt-4o")

# common Chain generation
chain = prompt | llm | StrOutputParser()

Create a chain that records the conversation ( chain_with_history )

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# A dictionary to store session records.
store = {}


# Function to retrieve session records based on session ID
def get_session_history(session_ids):
    print(f"[Conversation Session ID]: {session_ids}")
    if session_ids not in store:  # If the session ID is not in the store
        # Create a new ChatMessageHistory object and save it to the store.
    return store[session_ids]  # Returns the session record for the given session ID.

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chain_with_history = RunnableWithMessageHistory(
    chain,
    get_session_history,  # Function to retrieve session records
    input_messages_key="question",  # The key that the user's question will go into the template variable
    history_messages_key="chat_history",  # 기록 메시지의 키
)

Run the first question

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chain_with_history.invoke(
    # enter your question
    {"question": "My name is Teddy."},
    # Records conversations based on session ID.
    config={"configurable": {"session_id": "abc123"}},
)

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 [Dial SessionID]: abc123

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'Hello, Teddy! What can I help you with?' 

Then run the question

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chain_with_history.invoke(
    # enter your question
    {"question": "what is my name?"},
    # Records conversations based on session ID.
    config={"configurable": {"session_id": "abc123"}},
)

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[Dial SessionID]: abc123

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 'Your name is Teddy.' 

Below session_id If this is different, a new session is created.

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chain_with_history.invoke(
    # enter your question
    {"question": "what is my name?"},
    # Records conversations based on session ID.
    config={"configurable": {"session_id": "abc1234"}},
)

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 [Dial SessionID]: abc1234

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 'Sorry, but your name is unknown. If you have any questions, is there any other way to help?'