{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.
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How to add Memory to an LLMChain
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How to add Memory to an Agent
By Harrison Chase
    
      © Copyright 2023, Harrison Chase.
      
  Last updated on Jun 16, 2023.
rtdocs_stable/api.python.langchain.com/en/stable/modules/memory/examples/adding_memory_chain_multiple_inputs.html