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| | from rag.nlp import find_codec |
| | import readability |
| | import html_text |
| | import chardet |
| |
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|
| | def get_encoding(file): |
| | with open(file,'rb') as f: |
| | tmp = chardet.detect(f.read()) |
| | return tmp['encoding'] |
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|
| | class RAGFlowHtmlParser: |
| | def __call__(self, fnm, binary=None): |
| | txt = "" |
| | if binary: |
| | encoding = find_codec(binary) |
| | txt = binary.decode(encoding, errors="ignore") |
| | else: |
| | with open(fnm, "r",encoding=get_encoding(fnm)) as f: |
| | txt = f.read() |
| | return self.parser_txt(txt) |
| |
|
| | @classmethod |
| | def parser_txt(cls, txt): |
| | if not isinstance(txt, str): |
| | raise TypeError("txt type should be str!") |
| | html_doc = readability.Document(txt) |
| | title = html_doc.title() |
| | content = html_text.extract_text(html_doc.summary(html_partial=True)) |
| | txt = f"{title}\n{content}" |
| | sections = txt.split("\n") |
| | return sections |
| |
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