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| # 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) | |