■ ChatOpenAI 클래스의 with_structured_output 메소드에서 Pydantic 객체를 전달해 구조화된 데이터를 받는 방법을 보여준다.
▶ main.py
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import os from typing import Optional from langchain_core.pydantic_v1 import BaseModel, Field from langchain_openai import ChatOpenAI os.environ["OPENAI_API_KEY"] = "<OPENAI_API_KEY>" class Joke(BaseModel): """Joke to tell user.""" setup : str = Field(description = "The setup of the joke" ) punchline : str = Field(description = "The punchline to the joke" ) rating : Optional[int] = Field(description = "How funny the joke is, from 1 to 10") chatOpenAI = ChatOpenAI(model = "gpt-3.5-turbo-0125") runnableSequence = chatOpenAI.with_structured_output(Joke) joke = runnableSequence.invoke("Tell me a joke about cats") print(joke) """ setup='Why was the cat sitting on the computer?' punchline='To keep an eye on the mouse!' rating=8 """ |
▶ requirements.txt
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aiohttp==3.9.5 aiosignal==1.3.1 annotated-types==0.7.0 anyio==4.4.0 async-timeout==4.0.3 attrs==23.2.0 certifi==2024.6.2 charset-normalizer==3.3.2 distro==1.9.0 exceptiongroup==1.2.1 frozenlist==1.4.1 greenlet==3.0.3 h11==0.14.0 httpcore==1.0.5 httpx==0.27.0 idna==3.7 jsonpatch==1.33 jsonpointer==3.0.0 langchain==0.2.5 langchain-core==0.2.7 langchain-openai==0.1.8 langchain-text-splitters==0.2.1 langsmith==0.1.77 multidict==6.0.5 numpy==1.26.4 openai==1.34.0 orjson==3.10.5 packaging==24.1 pydantic==2.7.4 pydantic_core==2.18.4 PyYAML==6.0.1 regex==2024.5.15 requests==2.32.3 sniffio==1.3.1 SQLAlchemy==2.0.30 tenacity==8.3.0 tiktoken==0.7.0 tqdm==4.66.4 typing_extensions==4.12.2 urllib3==2.2.1 yarl==1.9.4 |
※ pip install langchain langchain-openai 명령을 실행했다.