# Documentation - Class name: LLMImageVisionLLMReader - Category: SALT/Language Toolkit/Readers - Output node: False LLMImageVisionLLMReader节点旨在读取和处理图像文件,利用大型语言模型(LLMs)来解释和提取视觉内容中的信息。它的目标是通过LLMs的视角,架起视觉数据与文本分析之间的桥梁,从而实现对图像的更深入理解。 # Input types ## Required - path - 指定要处理的图像文件路径。这是一个至关重要的参数,因为它决定了节点将要分析的视觉数据的来源。 - Comfy dtype: STRING - Python dtype: str ## Optional - extra_info - 以字符串格式提供可选的额外信息,可用于影响图像的处理过程。这可能包括特定任务的设置或参数。 - Comfy dtype: STRING - Python dtype: str # Output types - documents - 将处理后的数据以文档形式返回,封装了LLM从图像中提取的见解。 - Comfy dtype: DOCUMENT - Python dtype: List[Document] ## Usage tips - Infra type: `CPU` - Common nodes: unknown ## Source code ```python class LLMImageVisionLLMReader(ImageVisionLLMReader): """ @NOTE: Not sure what this does yet @Source: https://github.com/run-llama/llama_index/blob/main/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/image_vision_llm/base.py @Documentation:https://docs.llamaindex.ai/en/latest/api_reference/readers/file/#llama_index.readers.file.ImageVisionLLMReader """ def __init__(self): super().__init__() @classmethod def INPUT_TYPES(cls): return { "required": { "path": ("STRING", {"default": ""}), #"warning": ("STRING", {"default":"WARNING: This downloads a 15GB file in two parts."}), }, "optional": { "extra_info": ("STRING", {"multiline": True, "dynamicPrompts": False, "default": "{}"}), } } RETURN_TYPES = ("DOCUMENT", ) RETURN_NAMES = ("documents",) FUNCTION = "execute" CATEGORY = f"{MENU_NAME}/{SUB_MENU_NAME}/Readers" def execute(self, path:str, warning:str, extra_info:str): get_full_path(1, path) if not os.path.exists(path): raise FileNotFoundError(f"No file available at: {path}") path = Path(path) extra_info = read_extra_info(extra_info) data = self.load_data(path, extra_info) return (data, ) ```