langchain/templates/stepback-qa-prompting/stepback_qa_prompting/chain.py

from langchain.chat_models import ChatOpenAI
from langchain.prompts import ChatPromptTemplate, FewShotChatMessagePromptTemplate
from langchain.schema.output_parser import StrOutputParser
from langchain.schema.runnable import RunnableLambda
from langchain.utilities import DuckDuckGoSearchAPIWrapper

search = DuckDuckGoSearchAPIWrapper(max_results=4)


def retriever(query):
    return search.run(query)


# Few Shot Examples
examples = [
    {
        "input": "Could the members of The Police perform lawful arrests?",
        "output": "what can the members of The Police do?",
    },
    {
        "input": "Jan Sindel’s was born in what country?",
        "output": "what is Jan Sindel’s personal history?",
    },
]
# We now transform these to example messages
example_prompt = ChatPromptTemplate.from_messages(
    [
        ("human", "{input}"),
        ("ai", "{output}"),
    ]
)
few_shot_prompt = FewShotChatMessagePromptTemplate(
    example_prompt=example_prompt,
    examples=examples,
)

prompt = ChatPromptTemplate.from_messages(
    [
        (
            "system",
            "You are an expert at world knowledge. Your task is to step back "
            "and paraphrase a question to a more generic step-back question, which "
            "is easier to answer. Here are a few examples:",
        ),
        # Few shot examples
        few_shot_prompt,
        # New question
        ("user", "{question}"),
    ]
)

question_gen = prompt | ChatOpenAI(temperature=0) | StrOutputParser()

response_prompt_template = """You are an expert of world knowledge. I am going to ask you a question. Your response should be comprehensive and not contradicted with the following context if they are relevant. Otherwise, ignore them if they are not relevant.

{normal_context}
{step_back_context}

Original Question: {question}
Answer:"""  # noqa: E501
response_prompt = ChatPromptTemplate.from_template(response_prompt_template)

chain = (
    {
        # Retrieve context using the normal question
        "normal_context": RunnableLambda(lambda x: x["question"]) | retriever,
        # Retrieve context using the step-back question
        "step_back_context": question_gen | retriever,
        # Pass on the question
        "question": lambda x: x["question"],
    }
    | response_prompt
    | ChatOpenAI(temperature=0)
    | StrOutputParser()
)