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dd0ebbea35
### What problem does this PR solve? #4543 ### Type of change - [x] New Feature (non-breaking change which adds functionality)
140 lines
4.9 KiB
Python
140 lines
4.9 KiB
Python
#
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# Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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import logging
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from tika import parser
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from io import BytesIO
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import re
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from deepdoc.parser.utils import get_text
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from rag.app import naive
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from rag.nlp import rag_tokenizer, tokenize
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from deepdoc.parser import PdfParser, ExcelParser, PlainParser, HtmlParser
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class Pdf(PdfParser):
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def __call__(self, filename, binary=None, from_page=0,
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to_page=100000, zoomin=3, callback=None):
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from timeit import default_timer as timer
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start = timer()
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callback(msg="OCR started")
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self.__images__(
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filename if not binary else binary,
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zoomin,
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from_page,
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to_page,
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callback
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)
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callback(msg="OCR finished ({:.2f}s)".format(timer() - start))
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start = timer()
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self._layouts_rec(zoomin, drop=False)
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callback(0.63, "Layout analysis ({:.2f}s)".format(timer() - start))
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logging.debug("layouts cost: {}s".format(timer() - start))
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start = timer()
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self._table_transformer_job(zoomin)
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callback(0.65, "Table analysis ({:.2f}s)".format(timer() - start))
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start = timer()
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self._text_merge()
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callback(0.67, "Text merged ({:.2f}s)".format(timer() - start))
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tbls = self._extract_table_figure(True, zoomin, True, True)
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self._concat_downward()
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sections = [(b["text"], self.get_position(b, zoomin))
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for i, b in enumerate(self.boxes)]
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for (img, rows), poss in tbls:
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if not rows:
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continue
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sections.append((rows if isinstance(rows, str) else rows[0],
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[(p[0] + 1 - from_page, p[1], p[2], p[3], p[4]) for p in poss]))
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return [(txt, "") for txt, _ in sorted(sections, key=lambda x: (
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x[-1][0][0], x[-1][0][3], x[-1][0][1]))], None
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def chunk(filename, binary=None, from_page=0, to_page=100000,
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lang="Chinese", callback=None, **kwargs):
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"""
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Supported file formats are docx, pdf, excel, txt.
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One file forms a chunk which maintains original text order.
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"""
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eng = lang.lower() == "english" # is_english(cks)
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if re.search(r"\.docx$", filename, re.IGNORECASE):
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callback(0.1, "Start to parse.")
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sections, tbls = naive.Docx()(filename, binary)
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sections = [s for s, _ in sections if s]
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for (_, html), _ in tbls:
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sections.append(html)
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callback(0.8, "Finish parsing.")
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elif re.search(r"\.pdf$", filename, re.IGNORECASE):
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pdf_parser = Pdf()
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if kwargs.get("layout_recognize", "DeepDOC") == "Plain Text":
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pdf_parser = PlainParser()
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sections, _ = pdf_parser(
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filename if not binary else binary, to_page=to_page, callback=callback)
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sections = [s for s, _ in sections if s]
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elif re.search(r"\.xlsx?$", filename, re.IGNORECASE):
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callback(0.1, "Start to parse.")
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excel_parser = ExcelParser()
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sections = excel_parser.html(binary, 1000000000)
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elif re.search(r"\.(txt|md|markdown)$", filename, re.IGNORECASE):
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callback(0.1, "Start to parse.")
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txt = get_text(filename, binary)
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sections = txt.split("\n")
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sections = [s for s in sections if s]
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callback(0.8, "Finish parsing.")
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elif re.search(r"\.(htm|html)$", filename, re.IGNORECASE):
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callback(0.1, "Start to parse.")
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sections = HtmlParser()(filename, binary)
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sections = [s for s in sections if s]
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callback(0.8, "Finish parsing.")
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elif re.search(r"\.doc$", filename, re.IGNORECASE):
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callback(0.1, "Start to parse.")
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binary = BytesIO(binary)
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doc_parsed = parser.from_buffer(binary)
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sections = doc_parsed['content'].split('\n')
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sections = [s for s in sections if s]
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callback(0.8, "Finish parsing.")
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else:
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raise NotImplementedError(
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"file type not supported yet(doc, docx, pdf, txt supported)")
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doc = {
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"docnm_kwd": filename,
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"title_tks": rag_tokenizer.tokenize(re.sub(r"\.[a-zA-Z]+$", "", filename))
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}
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doc["title_sm_tks"] = rag_tokenizer.fine_grained_tokenize(doc["title_tks"])
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tokenize(doc, "\n".join(sections), eng)
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return [doc]
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if __name__ == "__main__":
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import sys
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def dummy(prog=None, msg=""):
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pass
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chunk(sys.argv[1], from_page=0, to_page=10, callback=dummy)
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