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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. | |
| # | |
| from tika import parser | |
| from io import BytesIO | |
| import re | |
| from rag.app import laws | |
| from rag.nlp import rag_tokenizer, tokenize, find_codec | |
| from deepdoc.parser import PdfParser, ExcelParser, 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, drop=False) | |
| callback(0.63, "Layout analysis finished.") | |
| print("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._concat_downward() | |
| sections = [(b["text"], self.get_position(b, zoomin)) | |
| for i, b in enumerate(self.boxes)] | |
| for (img, rows), poss in tbls: | |
| if not rows:continue | |
| sections.append((rows if isinstance(rows, str) else rows[0], | |
| [(p[0] + 1 - from_page, p[1], p[2], p[3], p[4]) for p in poss])) | |
| return [(txt, "") for txt, _ in sorted(sections, key=lambda x: ( | |
| x[-1][0][0], x[-1][0][3], x[-1][0][1]))], None | |
| def chunk(filename, binary=None, from_page=0, to_page=100000, | |
| lang="Chinese", callback=None, **kwargs): | |
| """ | |
| Supported file formats are docx, pdf, excel, txt. | |
| One file forms a chunk which maintains original text order. | |
| """ | |
| eng = lang.lower() == "english" # is_english(cks) | |
| if re.search(r"\.docx$", filename, re.IGNORECASE): | |
| callback(0.1, "Start to parse.") | |
| sections = [txt for txt in laws.Docx()(filename, binary) if txt] | |
| callback(0.8, "Finish parsing.") | |
| elif re.search(r"\.pdf$", filename, re.IGNORECASE): | |
| pdf_parser = Pdf() if kwargs.get( | |
| "parser_config", {}).get( | |
| "layout_recognize", True) else PlainParser() | |
| sections, _ = pdf_parser( | |
| filename if not binary else binary, to_page=to_page, callback=callback) | |
| sections = [s for s, _ in sections if s] | |
| elif re.search(r"\.xlsx?$", filename, re.IGNORECASE): | |
| callback(0.1, "Start to parse.") | |
| excel_parser = ExcelParser() | |
| sections = excel_parser.html(binary, 1000000000) | |
| elif re.search(r"\.txt$", 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 = [s for s in sections if s] | |
| callback(0.8, "Finish parsing.") | |
| elif re.search(r"\.(htm|html)$", filename, re.IGNORECASE): | |
| callback(0.1, "Start to parse.") | |
| sections = HtmlParser()(filename, binary) | |
| sections = [s for s in sections if s] | |
| callback(0.8, "Finish parsing.") | |
| elif re.search(r"\.doc$", 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] | |
| callback(0.8, "Finish parsing.") | |
| else: | |
| raise NotImplementedError( | |
| "file type not supported yet(doc, docx, pdf, txt supported)") | |
| 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"]) | |
| tokenize(doc, "\n".join(sections), eng) | |
| return [doc] | |
| if __name__ == "__main__": | |
| import sys | |
| def dummy(prog=None, msg=""): | |
| pass | |
| chunk(sys.argv[1], from_page=0, to_page=10, callback=dummy) | |