■ ArxivLoader 클래스의 생성자에서 query/load_max_docs/load_all_available_meta 인자를 사용해 ArxivLoader 객체를 만드는 방법을 보여준다.
▶ main.py
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from langchain_community.document_loaders import ArxivLoader arxivLoader = ArxivLoader( query = "Chain of thought", load_max_docs = 2, # 로드할 최대 문서 수이나 아래의 경우 3건이 로드되었다. load_all_available_meta = True ) documentList = arxivLoader.load() for document in documentList: print(document.metadata["Title"]) """ Contrastive Chain-of-Thought Prompting Beyond Chain-of-Thought, Effective Graph-of-Thought Reasoning in Language Models Table as Thought: Exploring Structured Thoughts in LLM Reasoning """ |
▶ requirements.txt
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aiohappyeyeballs==2.4.4 aiohttp==3.11.11 aiosignal==1.3.2 annotated-types==0.7.0 anyio==4.8.0 arxiv==2.1.3 async-timeout==4.0.3 attrs==24.3.0 certifi==2024.12.14 charset-normalizer==3.4.1 dataclasses-json==0.6.7 exceptiongroup==1.2.2 feedparser==6.0.11 frozenlist==1.5.0 greenlet==3.1.1 h11==0.14.0 httpcore==1.0.7 httpx==0.28.1 httpx-sse==0.4.0 idna==3.10 jsonpatch==1.33 jsonpointer==3.0.0 langchain==0.3.14 langchain-community==0.3.14 langchain-core==0.3.29 langchain-text-splitters==0.3.5 langsmith==0.2.10 marshmallow==3.25.1 multidict==6.1.0 mypy-extensions==1.0.0 numpy==1.26.4 orjson==3.10.14 packaging==24.2 propcache==0.2.1 pydantic==2.10.5 pydantic-settings==2.7.1 pydantic_core==2.27.2 PyMuPDF==1.25.1 python-dotenv==1.0.1 PyYAML==6.0.2 requests==2.32.3 requests-toolbelt==1.0.0 sgmllib3k==1.0.0 sniffio==1.3.1 SQLAlchemy==2.0.37 tenacity==9.0.0 typing-inspect==0.9.0 typing_extensions==4.12.2 urllib3==2.3.0 yarl==1.18.3 |
※ pip install langchain-community arxiv pymupdf 명령을 실행했다.