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

In [1]:

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}")
])

In [2]:

memory = ConversationBufferMemory(return_messages=True)

In [3]:

memory.load_memory_variables({})

Out [3]:

{'history': []}

In [4]:

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

In [5]:

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

Out [5]:

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

In [6]:

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

In [7]:

memory.load_memory_variables({})

Out [7]:

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

In [8]:

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

Out [8]:

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

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Adding memory

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