■ create_extraction_chain_pydantic 함수를 사용해 추출기를 만드는 방법을 보여준다. (LLMChain 객체)
▶ main.py
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 |
import os from langchain_core.pydantic_v1 import BaseModel, Field from langchain_openai import ChatOpenAI from langchain_core.prompts import ChatPromptTemplate from langchain_core.runnables import RunnablePassthrough from langchain.chains import create_extraction_chain_pydantic os.environ["OPENAI_API_KEY"] = "<OPENAI_AP_KEY>" class Person(BaseModel): name : str = Field(description = "The person's name") age : int = Field(description = "The person's age" ) chatOpenAI = ChatOpenAI(model = "gpt-3.5-turbo-0125", temperature = 0) structuredOutputRunnableSequence = chatOpenAI.with_structured_output(Person) system = """You are an expert at converting user questions into database queries. You have access to a database of tutorial videos about a software library for building LLM-powered applications. Given a question, return a list of database queries optimized to retrieve the most relevant results. If there are acronyms or words you are not familiar with, do not try to rephrase them.""" chatPromptTemplate = ChatPromptTemplate.from_messages([("system", system), ("human", "{question}")]) queryAnalyzerRunnableSequence = {"question" : RunnablePassthrough()} | chatPromptTemplate | structuredOutputRunnableSequence llmChain = create_extraction_chain_pydantic(pydantic_schema = Person, llm = chatOpenAI) personList = llmChain.run("Alice is 30 years old. Bob is 25.") print(personList) """ [Person(name='Alice', age=30), Person(name='Bob', age=25)] """ |
▶ requirements.txt
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 |
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 dataclasses-json==0.6.7 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-community==0.2.5 langchain-core==0.2.7 langchain-openai==0.1.8 langchain-text-splitters==0.2.1 langsmith==0.1.77 marshmallow==3.21.3 multidict==6.0.5 mypy-extensions==1.0.0 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-inspect==0.9.0 typing_extensions==4.12.2 urllib3==2.2.1 yarl==1.9.4 |
※ bash install.sh langchain langchain-community langchain-openai 명령을 실행했다.