# Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # from io import BytesIO from docx import Document import re from deepdoc.parser.pdf_parser import PlainParser from rag.app import laws from rag.nlp import huqie, is_english, tokenize, naive_merge, tokenize_table, add_positions, tokenize_chunks from deepdoc.parser import PdfParser, ExcelParser, DocxParser from rag.settings import cron_logger class Docx(DocxParser): def __init__(self): pass def __clean(self, line): line = re.sub(r"\u3000", " ", line).strip() return line def __call__(self, filename, binary=None, from_page=0, to_page=100000): self.doc = Document( filename) if not binary else Document(BytesIO(binary)) pn = 0 lines = [] for p in self.doc.paragraphs: if pn > to_page: break if from_page <= pn < to_page and p.text.strip(): lines.append(self.__clean(p.text)) for run in p.runs: if 'lastRenderedPageBreak' in run._element.xml: pn += 1 continue if 'w:br' in run._element.xml and 'type="page"' in run._element.xml: pn += 1 tbls = [] for tb in self.doc.tables: html= "" for r in tb.rows: html += "" i = 0 while i < len(r.cells): span = 1 c = r.cells[i] for j in range(i+1, len(r.cells)): if c.text == r.cells[j].text: span += 1 i = j i += 1 html += f"" if span == 1 else f"" html += "" html += "
{c.text}{c.text}
" tbls.append(((None, html), "")) return [(l, "") for l in lines if l], tbls class Pdf(PdfParser): def __call__(self, filename, binary=None, from_page=0, to_page=100000, zoomin=3, callback=None): callback(msg="OCR is running...") self.__images__( filename if not binary else binary, zoomin, from_page, to_page, callback ) callback(msg="OCR finished") from timeit import default_timer as timer start = timer() self._layouts_rec(zoomin) callback(0.63, "Layout analysis finished.") print("paddle layouts:", timer() - start) self._table_transformer_job(zoomin) callback(0.65, "Table analysis finished.") self._text_merge() callback(0.67, "Text merging finished") tbls = self._extract_table_figure(True, zoomin, True, True) #self._naive_vertical_merge() self._concat_downward() #self._filter_forpages() cron_logger.info("paddle layouts:".format( (timer() - start) / (self.total_page + 0.1))) return [(b["text"], self._line_tag(b, zoomin)) for b in self.boxes], tbls def chunk(filename, binary=None, from_page=0, to_page=100000, lang="Chinese", callback=None, **kwargs): """ Supported file formats are docx, pdf, excel, txt. This method apply the naive ways to chunk files. Successive text will be sliced into pieces using 'delimiter'. Next, these successive pieces are merge into chunks whose token number is no more than 'Max token number'. """ eng = lang.lower() == "english" # is_english(cks) parser_config = kwargs.get( "parser_config", { "chunk_token_num": 128, "delimiter": "\n!?。;!?", "layout_recognize": True}) doc = { "docnm_kwd": filename, "title_tks": huqie.qie(re.sub(r"\.[a-zA-Z]+$", "", filename)) } doc["title_sm_tks"] = huqie.qieqie(doc["title_tks"]) res = [] pdf_parser = None sections = [] if re.search(r"\.docx?$", filename, re.IGNORECASE): callback(0.1, "Start to parse.") sections, tbls = Docx()(filename, binary) res = tokenize_table(tbls, doc, eng) callback(0.8, "Finish parsing.") elif re.search(r"\.pdf$", filename, re.IGNORECASE): pdf_parser = Pdf( ) if parser_config.get("layout_recognize", True) else PlainParser() sections, tbls = pdf_parser(filename if not binary else binary, from_page=from_page, to_page=to_page, callback=callback) res = tokenize_table(tbls, doc, eng) elif re.search(r"\.xlsx?$", filename, re.IGNORECASE): callback(0.1, "Start to parse.") excel_parser = ExcelParser() sections = [(excel_parser.html(binary), "")] elif re.search(r"\.txt$", filename, re.IGNORECASE): callback(0.1, "Start to parse.") txt = "" if binary: txt = binary.decode("utf-8") else: with open(filename, "r") as f: while True: l = f.readline() if not l: break txt += l sections = txt.split("\n") sections = [(l, "") for l in sections if l] callback(0.8, "Finish parsing.") else: raise NotImplementedError( "file type not supported yet(docx, pdf, txt supported)") chunks = naive_merge( sections, parser_config.get( "chunk_token_num", 128), parser_config.get( "delimiter", "\n!?。;!?")) res.extend(tokenize_chunks(chunks, doc, eng, pdf_parser)) return res if __name__ == "__main__": import sys def dummy(prog=None, msg=""): pass chunk(sys.argv[1], from_page=0, to_page=10, callback=dummy)