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| 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" |
|
|
| 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?$", filename, re.IGNORECASE): |
| callback(0.1, "Start to parse.") |
| excel_parser = ExcelParser() |
| sections = excel_parser.html(binary, 1000000000) |
|
|
| elif re.search(r"\.(txt|md|markdown)$", 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) |
|
|