■ LlamaParse 클래스의 생성자에서 use_vendor_multimodal_model/vendor_multimodal_model_name 인자를 사용해 LlamaParse 객체를 만드는 방법을 보여준다.
※ LLAMA_CLOUD_API_KEY 환경 변수 값은 .env 파일에 정의한다.
※ OPENAI_API_KEY 환경 변수 값은 .env 파일에 정의한다.
▶ main.py
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from dotenv import load_dotenv from llama_parse import LlamaParse load_dotenv() parsingInstruction = "You are parsing a brief of AI Report. Please extract tables in markdown format." llamaParse = LlamaParse( use_vendor_multimodal_model = True, vendor_multimodal_model_name = "openai-gpt4o", result_type = "markdown", verbose = False, language = "ko", parsing_instruction = parsingInstruction ) documentList = llamaParse.load_data(file_path = "SPRI_AI_Brief_2023년12월호_F.pdf") langchainDocumentList = [document.to_langchain_format() for document in documentList] print(len(langchainDocumentList)) """ 23 """ |
▶ 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 async-timeout==4.0.3 attrs==24.3.0 certifi==2024.12.14 charset-normalizer==3.4.1 click==8.1.8 dataclasses-json==0.6.7 Deprecated==1.2.15 dirtyjson==1.0.8 exceptiongroup==1.2.2 filetype==1.2.0 frozenlist==1.5.0 fsspec==2024.12.0 greenlet==3.1.1 h11==0.14.0 httpcore==1.0.7 httpx==0.28.1 httpx-sse==0.4.0 idna==3.10 joblib==1.4.2 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 llama-index-core==0.12.10.post1 llama-parse==0.5.19 marshmallow==3.25.1 multidict==6.1.0 mypy-extensions==1.0.0 nest-asyncio==1.6.0 networkx==3.4.2 nltk==3.9.1 numpy==1.26.4 orjson==3.10.14 packaging==24.2 pillow==11.1.0 propcache==0.2.1 pydantic==2.10.5 pydantic-settings==2.7.1 pydantic_core==2.27.2 python-dotenv==1.0.1 PyYAML==6.0.2 regex==2024.11.6 requests==2.32.3 requests-toolbelt==1.0.0 sniffio==1.3.1 SQLAlchemy==2.0.37 tenacity==9.0.0 tiktoken==0.8.0 tqdm==4.67.1 typing-inspect==0.9.0 typing_extensions==4.12.2 urllib3==2.3.0 wrapt==1.17.1 yarl==1.18.3 |
※ pip install python-dotenv llama-parse langchain langchain-community 명령을 실행했다.
