■ ModelMetaclass 클래스의 schema 메소드를 사용해 도구 스키마 딕셔너리를 구하는 방법을 보여준다.
▶ main.py
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from langchain_core.tools import tool from typing import Annotated from typing import List @tool def multiply_by_max( a : Annotated[str , "scale factor" ], b : Annotated[List[int], "list of ints over which to take maximum"] ) -> int: """Multiply a by the maximum of b.""" return a * max(b) # multiply_by_max 함수는 StructuredTool 타입이다. modelMetaclass = multiply_by_max.args_schema dictionary = modelMetaclass.schema() print(dictionary) """ { 'description' : 'Multiply a by the maximum of b.', 'properties' : { 'a' : { 'description' : 'scale factor', 'title' : 'A', 'type' : 'string' }, 'b' : { 'description' : 'list of ints over which to take maximum', 'items' : {'type' : 'integer'}, 'title' : 'B', 'type' : 'array' } }, 'required' : ['a', 'b'], 'title' : 'multiply_by_max', 'type' : 'object' } """ |
▶ requirements.txt
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aiohappyeyeballs==2.4.0 aiohttp==3.10.5 aiosignal==1.3.1 annotated-types==0.7.0 anyio==4.4.0 attrs==24.2.0 certifi==2024.8.30 charset-normalizer==3.3.2 frozenlist==1.4.1 greenlet==3.1.0 h11==0.14.0 httpcore==1.0.5 httpx==0.27.2 idna==3.10 jsonpatch==1.33 jsonpointer==3.0.0 langchain==0.3.0 langchain-core==0.3.1 langchain-text-splitters==0.3.0 langsmith==0.1.121 multidict==6.1.0 numpy==1.26.4 orjson==3.10.7 packaging==24.1 pydantic==2.9.2 pydantic_core==2.23.4 PyYAML==6.0.2 requests==2.32.3 sniffio==1.3.1 SQLAlchemy==2.0.35 tenacity==8.5.0 typing_extensions==4.12.2 urllib3==2.2.3 yarl==1.11.1 |
※ pip install langchain 명령을 실행했다.