Memory in the Multi-Input Chain

Most memory objects assume a single input. In this notebook, we go over how to add memory to a chain that has multiple inputs. We will add memory to a question/answering chain. This chain takes as inputs both related documents and a user question.

from langchain_chroma import Chroma
from langchain_openai import OpenAIEmbeddings
from langchain_text_splitters import CharacterTextSplitter

API Reference:

• OpenAIEmbeddings
• CharacterTextSplitter

with open("../../state_of_the_union.txt") as f:
    state_of_the_union = f.read()
text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)
texts = text_splitter.split_text(state_of_the_union)

embeddings = OpenAIEmbeddings()

docsearch = Chroma.from_texts(
    texts, embeddings, metadatas=[{"source": i} for i in range(len(texts))]
)

Running Chroma using direct local API.
Using DuckDB in-memory for database. Data will be transient.

query = "What did the president say about Justice Breyer"
docs = docsearch.similarity_search(query)

from langchain.chains.question_answering import load_qa_chain
from langchain.memory import ConversationBufferMemory
from langchain_core.prompts import PromptTemplate
from langchain_openai import OpenAI

API Reference:

• load_qa_chain
• ConversationBufferMemory
• PromptTemplate
• OpenAI

template = """You are a chatbot having a conversation with a human.

Given the following extracted parts of a long document and a question, create a final answer.

{context}

{chat_history}
Human: {human_input}
Chatbot:"""

prompt = PromptTemplate(
    input_variables=["chat_history", "human_input", "context"], template=template
)
memory = ConversationBufferMemory(memory_key="chat_history", input_key="human_input")
chain = load_qa_chain(
    OpenAI(temperature=0), chain_type="stuff", memory=memory, prompt=prompt
)

query = "What did the president say about Justice Breyer"
chain({"input_documents": docs, "human_input": query}, return_only_outputs=True)

{'output_text': ' Tonight, I’d like to honor someone who has dedicated his life to serve this country: Justice Stephen Breyer—an Army veteran, Constitutional scholar, and retiring Justice of the United States Supreme Court. Justice Breyer, thank you for your service.'}

print(chain.memory.buffer)

Human: What did the president say about Justice Breyer
AI:  Tonight, I’d like to honor someone who has dedicated his life to serve this country: Justice Stephen Breyer—an Army veteran, Constitutional scholar, and retiring Justice of the United States Supreme Court. Justice Breyer, thank you for your service.