77 lines
2.6 KiB
Markdown
77 lines
2.6 KiB
Markdown
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# Documentation
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- Class name: LLMUnstructuredReader
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- Category: SALT/Language Toolkit/Readers
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- Output node: False
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LLMUnstructuredReader节点旨在读取和处理非结构化文件，将其转换为适合llama_index系统进行索引和进一步分析的格式。它支持多种文件类型，是将原始数据转换为结构化文档格式的多功能工具。
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# Input types
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## Required
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- path
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- 指定需要读取的非结构化文件的文件路径。这对于定位和访问要处理的文件至关重要。
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- Comfy dtype: STRING
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- Python dtype: str
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- split_documents
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- 一个布尔标志，指示是否应根据特定标准将输入文件拆分为多个文档。这会影响数据的分段和结构化方式。
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- Comfy dtype: COMBO[BOOLEAN]
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- Python dtype: bool
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## Optional
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- extra_info
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- 一个可选的字符串，包含JSON格式的附加信息或参数，可用于自定义读取过程。
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- Comfy dtype: STRING
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- Python dtype: str
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# Output types
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- documents
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- 来自非结构化文件的已处理数据，以文档或文档列表的形式构造，可用于索引和分析。
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- Comfy dtype: DOCUMENT
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- Python dtype: tuple
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## Usage tips
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- Infra type: `CPU`
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- Common nodes: unknown
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## Source code
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```python
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class LLMUnstructuredReader(UnstructuredReader):
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"""
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@NOTE: Reads unstructured (most kinds of) files into a llama_index Document
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@Source: https://github.com/run-llama/llama_index/blob/main/llama-index-integrations/readers/llama-index-readers-file/llama_index/readers/file/unstructured/base.py
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@Documentation: https://docs.llamaindex.ai/en/latest/api_reference/readers/file/#llama_index.readers.file.UnstructuredReader
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"""
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def __init__(self):
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super().__init__()
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@classmethod
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def INPUT_TYPES(cls):
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return {
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"required": {
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"path": ("STRING", {"default": ""}),
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"split_documents": ([False, True], { "default": False})
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},
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"optional": {
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"extra_info": ("STRING", {"multiline": True, "dynamicPrompts": False, "default": "{}"}),
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}
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}
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RETURN_TYPES = ("DOCUMENT", )
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RETURN_NAMES = ("documents",)
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FUNCTION = "execute"
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CATEGORY = f"{MENU_NAME}/{SUB_MENU_NAME}/Readers"
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def execute(self, path:str, extra_info:str, split_documents:bool = False):
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get_full_path(1, path)
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if not os.path.exists(path):
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raise FileNotFoundError(f"No file available at: {path}")
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path = Path(path)
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extra_info = read_extra_info(extra_info)
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data = self.load_data(path, extra_info, split_documents)
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return (data, )
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```
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