处理markdown形式的txt文档

[litongyun233]

预处理文档，把PDF转换为markdown形式的txt文档，发现分割效果不是很好，想优化一下，请给我返回针对txt文本（UnstructuredFileLoader）的读取方式和chunk的切分方式的代码路径。@dosu-bot

[dosubot[bot]]

Based on the information provided, the UnstructuredFileLoader class in the Langchain-Chatchat codebase uses a specific reading method and chunk splitting strategy for handling and segmenting PDFs converted into markdown-formatted txt documents.

The reading method is implemented in the _get_elements method of the RapidOCRPDFLoader class, which inherits from UnstructuredFileLoader. This method uses the fitz library to read through each page of the PDF document, extract the text directly, and apply OCR to images within the pages if they meet certain size thresholds. The extracted text and OCR results are then concatenated into a response string. You can find the implementation of this method in the document_loaders/mypdfloader.py file.

The chunk splitting strategy is also implemented in the _get_elements method, specifically through the partition_text function from the unstructured.partition.text module. This function partitions the text into segments or chunks based on the provided unstructured_kwargs. However, the specific strategy or algorithm used by partition_text for splitting the chunks is not detailed in the provided code snippet. To understand the exact chunk splitting strategy, you would need to look into the implementation of the partition_text function within the unstructured.partition.text module.

Unfortunately, I wasn't able to find the specific implementation of the partition_text function within the unstructured.partition.text module in the Langchain-Chatchat codebase. Also, the handling of txt documents by the UnstructuredFileLoader class is not detailed in the provided context. If you could provide more information about these aspects, I might be able to give a more precise answer.

I hope this information helps you in optimizing the segmentation of your PDFs converted into markdown-formatted txt documents. If you have any more questions or need further clarification, feel free to ask.

Sources

• document_loaders/mypdfloader.py
• document_loaders/mydocloader.py

#### About Dosu

This response is meant to be useful and save you time. It is **not meant to be a precise solution**, but rather a starting point for your own research. Help me be more useful! Please leave a 👍 if this is helpful and 👎 if it is irrelevant. If you want to continue the conversation, start your reply with @dosu-bot.

[zRzRzRzRzRzRzR]

你可以用markdowm的分词方式分词txt没问题的