# 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. # import copy from tika import parser import re from io import BytesIO from rag.nlp import bullets_category, is_english, tokenize, remove_contents_table, \ hierarchical_merge, make_colon_as_title, naive_merge, random_choices, tokenize_table, add_positions, \ tokenize_chunks, find_codec from rag.nlp import rag_tokenizer from deepdoc.parser import PdfParser, DocxParser, PlainParser, HtmlParser 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(0.67, "Layout analysis finished") print("layouts:", timer() - start) self._table_transformer_job(zoomin) callback(0.68, "Table analysis finished") self._text_merge() tbls = self._extract_table_figure(True, zoomin, True, True) self._naive_vertical_merge() self._filter_forpages() self._merge_with_same_bullet() callback(0.75, "Text merging finished.") callback(0.8, "Text extraction finished") return [(b["text"] + self._line_tag(b, zoomin), b.get("layoutno", "")) 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, txt. Since a book is long and not all the parts are useful, if it's a PDF, please setup the page ranges for every book in order eliminate negative effects and save elapsed computing time. """ doc = { "docnm_kwd": filename, "title_tks": rag_tokenizer.tokenize(re.sub(r"\.[a-zA-Z]+$", "", filename)) } doc["title_sm_tks"] = rag_tokenizer.fine_grained_tokenize(doc["title_tks"]) pdf_parser = None sections, tbls = [], [] if re.search(r"\.docx$", filename, re.IGNORECASE): callback(0.1, "Start to parse.") doc_parser = DocxParser() # TODO: table of contents need to be removed sections, tbls = doc_parser( binary if binary else filename, from_page=from_page, to_page=to_page) remove_contents_table(sections, eng=is_english( random_choices([t for t, _ in sections], k=200))) tbls = [((None, lns), None) for lns in tbls] callback(0.8, "Finish parsing.") elif re.search(r"\.pdf$", filename, re.IGNORECASE): pdf_parser = Pdf() if kwargs.get( "parser_config", {}).get( "layout_recognize", True) else PlainParser() sections, tbls = pdf_parser(filename if not binary else binary, from_page=from_page, to_page=to_page, callback=callback) elif re.search(r"\.txt$", filename, re.IGNORECASE): callback(0.1, "Start to parse.") txt = "" if binary: encoding = find_codec(binary) txt = binary.decode(encoding, errors="ignore") 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] remove_contents_table(sections, eng=is_english( random_choices([t for t, _ in sections], k=200))) callback(0.8, "Finish parsing.") elif re.search(r"\.(htm|html)$", filename, re.IGNORECASE): callback(0.1, "Start to parse.") sections = HtmlParser()(filename, binary) sections = [(l, "") for l in sections if l] remove_contents_table(sections, eng=is_english( random_choices([t for t, _ in sections], k=200))) callback(0.8, "Finish parsing.") elif re.search(r"\.doc$", filename, re.IGNORECASE): callback(0.1, "Start to parse.") binary = BytesIO(binary) doc_parsed = parser.from_buffer(binary) sections = doc_parsed['content'].split('\n') sections = [(l, "") for l in sections if l] remove_contents_table(sections, eng=is_english( random_choices([t for t, _ in sections], k=200))) callback(0.8, "Finish parsing.") else: raise NotImplementedError( "file type not supported yet(doc, docx, pdf, txt supported)") make_colon_as_title(sections) bull = bullets_category( [t for t in random_choices([t for t, _ in sections], k=100)]) if bull >= 0: chunks = ["\n".join(ck) for ck in hierarchical_merge(bull, sections, 5)] else: sections = [s.split("@") for s, _ in sections] sections = [(pr[0], "@" + pr[1]) if len(pr) == 2 else (pr[0], '') for pr in sections ] chunks = naive_merge( sections, kwargs.get( "chunk_token_num", 256), kwargs.get( "delimer", "\n。;!?")) # is it English # is_english(random_choices([t for t, _ in sections], k=218)) eng = lang.lower() == "english" res = tokenize_table(tbls, doc, eng) 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=1, to_page=10, callback=dummy)