# Documentation - Class name: LLMImageTabularChartReader - Category: SALT/Language Toolkit/Readers - Output node: False LLMImageTabularChartReader节点专门用于将基于图像的图表解读为表格数据,将视觉信息转换为结构化文档格式。这一过程能够从代表图表的图像中提取和分析数据,便于将其整合到数据处理工作流程中。 # Input types ## Required - path - 指定需要读取的图像图表的文件路径。这对于定位和访问图像以进行数据提取至关重要。 - Comfy dtype: STRING - Python dtype: str ## Optional - max_output_tokens - 确定输出生成的最大标记数,影响提取数据的详细程度和长度。 - Comfy dtype: INT - Python dtype: int - prompt - 提供可选的文本提示,用于指导图像图表的解释,可能影响提取数据的重点或上下文。 - Comfy dtype: STRING - Python dtype: str - extra_info - 允许以字符串格式包含额外信息,可用于传递数据提取过程的额外参数或上下文。 - Comfy dtype: STRING - Python dtype: str # Output types - documents - 以结构化文档格式返回从图像图表中提取的表格数据,便于进一步分析或处理。 - Comfy dtype: DOCUMENT - Python dtype: Document ## Usage tips - Infra type: `CPU` - Common nodes: unknown ## Source code ```python class LLMImageTabularChartReader(ImageTabularChartReader): """ @NOTE: Reads an Image chart as if it were tabular data into a llama_index Document @Source: https://github.com/run-llama/llama_index/blob/main/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/image_deplot/base.py @Documentation: https://docs.llamaindex.ai/en/latest/api_reference/readers/file/#llama_index.readers.file.ImageTabularChartReader """ def __init__(self): super().__init__() @classmethod def INPUT_TYPES(cls): return { "required": { "path": ("STRING", {"default": ""}), }, "optional": { # "keep_image": ([False, True], {"default": False}), "max_output_tokens": ("INT", {"default": 512}), "prompt": ("STRING", {"multiline": True, "dynamicPrompts": False, "default": ""}), "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, max_output_tokens:int=512, prompt:str=None, 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) self._max_output_tokens = max_output_tokens if prompt and len(prompt) > 2: self._prompt = prompt extra_info = read_extra_info(extra_info) data = self.load_data(path, extra_info) return (data, ) ```