Understand Ollama and LangChain Chat History in 10 minutes

from langchain_community.llms import Ollama
from langchain_core.messages import HumanMessage, AIMessage
from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder


llm = Ollama(model="llama3")

chat_history = []

prompt_template = ChatPromptTemplate.from_messages(
    [
        (
            "system",
            "You are an AI named Mike, you answer questions with simple answers and no funny stuff.",
        ),
        MessagesPlaceholder(variable_name="chat_history"),
        ("human", "{input}"),
    ]
)

chain = prompt_template | llm


def start_app():
    while True:
        question = input("You: ")
        if question == "done":
            return

        # response = llm.invoke(question)
        response = chain.invoke({"input": question, "chat_history": chat_history})
        chat_history.append(HumanMessage(content=question))
        chat_history.append(AIMessage(content=response))

        print("AI:" + response)


if __name__ == "__main__":
    start_app()