【AI大模型应用开发】【LangChain系列】8. 重要组件介绍：如何运用LangChain表达式语言LCEL中的RunnableParallel和RunnablePassthrough？

from langchain_community.vectorstores import FAISS
from langchain_core.output_parsers import StrOutputParser
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.runnables import RunnablePassthrough
from langchain_openai import ChatOpenAI, OpenAIEmbeddings
vectorstore = FAISS.from_texts(
    ["harrison worked at kensho"], embedding=OpenAIEmbeddings()
)
retriever = vectorstore.as_retriever()
template = """Answer the question based only on the following context:
{context}
Question: {question}
"""
prompt = ChatPromptTemplate.from_template(template)
model = ChatOpenAI()
retrieval_chain = (
    {"context": retriever, "question": RunnablePassthrough()}
    | prompt
    | model
    | StrOutputParser()
)
retrieval_chain.invoke("where did harrison work?")

{"context": retriever, "question": RunnablePassthrough()}
RunnableParallel({"context": retriever, "question": RunnablePassthrough()})
RunnableParallel(context=retriever, question=RunnablePassthrough())

from langchain_core.prompts import ChatPromptTemplate
from langchain_core.runnables import RunnableParallel
from langchain_openai import ChatOpenAI
model = ChatOpenAI()
joke_chain = ChatPromptTemplate.from_template("tell me a joke about {topic}") | model
poem_chain = (
    ChatPromptTemplate.from_template("write a 2-line poem about {topic}") | model
)
map_chain = RunnableParallel(joke=joke_chain, poem=poem_chain)
map_chain.invoke({"topic": "bear"})

{'joke': AIMessage(content="Why don't bears wear shoes?\n\nBecause they have bear feet!"),
 'poem': AIMessage(content="In the wild's embrace, bear roams free,\nStrength and grace, a majestic decree.")}

from langchain_core.runnables import RunnableParallel, RunnablePassthrough
runnable = RunnableParallel(
    passed=RunnablePassthrough(),
    extra=RunnablePassthrough.assign(mult=lambda x: x["num"] * 3),
    modified=lambda x: x["num"] + 1,
)
runnable.invoke({"num": 1})

{'passed': {'num': 1}, 'extra': {'num': 1, 'mult': 3}, 'modified': 2}