Adding memory

This shows how to add memory to an arbitrary chain. Right now, you can use the memory classes but need to hook it up manually

from langchain.chat_models import ChatOpenAI
from langchain.memory import ConversationBufferMemory
from langchain.schema.runnable import RunnableMap
from langchain.prompts import ChatPromptTemplate, MessagesPlaceholder

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

API Reference:

• ChatOpenAI
• ConversationBufferMemory
• RunnableMap
• ChatPromptTemplate
• MessagesPlaceholder

memory = ConversationBufferMemory(return_messages=True)

memory.load_memory_variables({})

    {'history': []}

chain = RunnableMap({
    "input": lambda x: x["input"],
    "memory": memory.load_memory_variables
}) | {
    "input": lambda x: x["input"],
    "history": lambda x: x["memory"]["history"]
} | prompt | model

inputs = {"input": "hi im bob"}
response = chain.invoke(inputs)
response

    AIMessage(content='Hello Bob! How can I assist you today?', additional_kwargs={}, example=False)

memory.save_context(inputs, {"output": response.content})

memory.load_memory_variables({})

    {'history': [HumanMessage(content='hi im bob', additional_kwargs={}, example=False),
      AIMessage(content='Hello Bob! How can I assist you today?', additional_kwargs={}, example=False)]}

inputs = {"input": "whats my name"}
response = chain.invoke(inputs)
response

    AIMessage(content='Your name is Bob.', additional_kwargs={}, example=False)