■ RunnablePassthrough 클래스의 assign 메소드에서 커스텀 함수를 설정해 동적 체인을 만드는 방법을 보여준다.
※ OPENAI_API_KEY 환경 변수 값은 .env 파일에 정의한다.
▶ main.py
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from dotenv import load_dotenv from langchain_core.prompts import ChatPromptTemplate from langchain_openai import ChatOpenAI from langchain_core.output_parsers import StrOutputParser from langchain_core.runnables import chain from langchain_core.runnables import Runnable from langchain_core.runnables import RunnablePassthrough load_dotenv() contextualizePromptTemplateString = """Convert the latest user question into a standalone question given the chat history. Don't answer the question, return the question and nothing else (no descriptive text).""" contextualizePromptTemplate = ChatPromptTemplate.from_messages( [ ("system" , contextualizePromptTemplateString), ("placeholder", "{chat_history}"), ("human" , "{question}"), ] ) chatOpenAI = ChatOpenAI(model = "gpt-3.5-turbo-0125") contextualizeRunnableSequence = contextualizePromptTemplate | chatOpenAI | StrOutputParser() systemMessageString = "Answer the user question given the following context :\n\n{context}." qnaChatPromptTemplate = ChatPromptTemplate.from_messages([("system", systemMessageString), ("human", "{question}")]) @chain def contextualizeIfNeeded(inputDictionary : dict) -> Runnable: if inputDictionary.get("chat_history"): return contextualizeRunnableSequence else: return RunnablePassthrough() @chain def fakeRetriever(_ : dict) -> str: return "egypt's population in 2024 is about 111 million" questionRunnableAssign = RunnablePassthrough.assign(question = contextualizeIfNeeded) contextRunnableSequence = questionRunnableAssign.assign(context = fakeRetriever) runnableSequence = contextRunnableSequence | qnaChatPromptTemplate | chatOpenAI | StrOutputParser() responseString = runnableSequence.invoke( { "question" : "what about egypt", "chat_history" : [ ("human", "what's the population of indonesia"), ("ai" , "about 276 million") ] } ) print(responseString) """ Egypt's population in 2024 is about 111 million. """ |
▶ requirements.txt
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annotated-types==0.7.0 anyio==4.4.0 certifi==2024.6.2 charset-normalizer==3.3.2 distro==1.9.0 exceptiongroup==1.2.1 h11==0.14.0 httpcore==1.0.5 httpx==0.27.0 idna==3.7 jsonpatch==1.33 jsonpointer==3.0.0 langchain-core==0.2.9 langchain-openai==0.1.9 langsmith==0.1.81 openai==1.35.3 orjson==3.10.5 packaging==24.1 pydantic==2.7.4 pydantic_core==2.18.4 python-dotenv==1.0.1 PyYAML==6.0.1 regex==2024.5.15 requests==2.32.3 sniffio==1.3.1 tenacity==8.4.1 tiktoken==0.7.0 tqdm==4.66.4 typing_extensions==4.12.2 urllib3==2.2.2 |
※ pip install python-dotenv langchain-openai 명령을 실행했다.