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| import logging |
| from tika import parser |
| from io import BytesIO |
| from docx import Document |
| from timeit import default_timer as timer |
| import re |
| from deepdoc.parser.pdf_parser import PlainParser |
| from rag.nlp import rag_tokenizer, naive_merge, tokenize_table, tokenize_chunks, find_codec, concat_img, \ |
| naive_merge_docx, tokenize_chunks_docx |
| from deepdoc.parser import PdfParser, ExcelParser, DocxParser, HtmlParser, JsonParser, MarkdownParser, TxtParser |
| from rag.utils import num_tokens_from_string |
| from PIL import Image |
| from functools import reduce |
| from markdown import markdown |
| from docx.image.exceptions import UnrecognizedImageError, UnexpectedEndOfFileError, InvalidImageStreamError |
|
|
|
|
| class Docx(DocxParser): |
| def __init__(self): |
| pass |
|
|
| def get_picture(self, document, paragraph): |
| img = paragraph._element.xpath('.//pic:pic') |
| if not img: |
| return None |
| img = img[0] |
| embed = img.xpath('.//a:blip/@r:embed')[0] |
| related_part = document.part.related_parts[embed] |
| try: |
| image_blob = related_part.image.blob |
| except UnrecognizedImageError: |
| logging.info("Unrecognized image format. Skipping image.") |
| return None |
| except UnexpectedEndOfFileError: |
| logging.info("EOF was unexpectedly encountered while reading an image stream. Skipping image.") |
| return None |
| except InvalidImageStreamError: |
| logging.info("The recognized image stream appears to be corrupted. Skipping image.") |
| return None |
| try: |
| image = Image.open(BytesIO(image_blob)).convert('RGB') |
| return image |
| except Exception: |
| return None |
|
|
| 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 = [] |
| last_image = None |
| for p in self.doc.paragraphs: |
| if pn > to_page: |
| break |
| if from_page <= pn < to_page: |
| if p.text.strip(): |
| if p.style and p.style.name == 'Caption': |
| former_image = None |
| if lines and lines[-1][1] and lines[-1][2] != 'Caption': |
| former_image = lines[-1][1].pop() |
| elif last_image: |
| former_image = last_image |
| last_image = None |
| lines.append((self.__clean(p.text), [former_image], p.style.name)) |
| else: |
| current_image = self.get_picture(self.doc, p) |
| image_list = [current_image] |
| if last_image: |
| image_list.insert(0, last_image) |
| last_image = None |
| lines.append((self.__clean(p.text), image_list, p.style.name if p.style else "")) |
| else: |
| if current_image := self.get_picture(self.doc, p): |
| if lines: |
| lines[-1][1].append(current_image) |
| else: |
| last_image = current_image |
| 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 |
| new_line = [(line[0], reduce(concat_img, line[1]) if line[1] else None) for line in lines] |
|
|
| tbls = [] |
| for tb in self.doc.tables: |
| html = "<table>" |
| for r in tb.rows: |
| html += "<tr>" |
| 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"<td>{c.text}</td>" if span == 1 else f"<td colspan='{span}'>{c.text}</td>" |
| html += "</tr>" |
| html += "</table>" |
| tbls.append(((None, html), "")) |
| return new_line, tbls |
|
|
|
|
| class Pdf(PdfParser): |
| def __call__(self, filename, binary=None, from_page=0, |
| to_page=100000, zoomin=3, callback=None): |
| start = timer() |
| first_start = start |
| callback(msg="OCR started") |
| self.__images__( |
| filename if not binary else binary, |
| zoomin, |
| from_page, |
| to_page, |
| callback |
| ) |
| callback(msg="OCR finished ({:.2f}s)".format(timer() - start)) |
| logging.info("OCR({}~{}): {:.2f}s".format(from_page, to_page, timer() - start)) |
|
|
| start = timer() |
| self._layouts_rec(zoomin) |
| callback(0.63, "Layout analysis ({:.2f}s)".format(timer() - start)) |
|
|
| start = timer() |
| self._table_transformer_job(zoomin) |
| callback(0.65, "Table analysis ({:.2f}s)".format(timer() - start)) |
|
|
| start = timer() |
| self._text_merge() |
| callback(0.67, "Text merged ({:.2f}s)".format(timer() - start)) |
| tbls = self._extract_table_figure(True, zoomin, True, True) |
| |
| self._concat_downward() |
| |
|
|
| logging.info("layouts cost: {}s".format(timer() - first_start)) |
| return [(b["text"], self._line_tag(b, zoomin)) |
| for b in self.boxes], tbls |
|
|
|
|
| class Markdown(MarkdownParser): |
| def __call__(self, filename, binary=None): |
| if binary: |
| encoding = find_codec(binary) |
| txt = binary.decode(encoding, errors="ignore") |
| else: |
| with open(filename, "r") as f: |
| txt = f.read() |
| remainder, tables = self.extract_tables_and_remainder(f'{txt}\n') |
| sections = [] |
| tbls = [] |
| for sec in remainder.split("\n"): |
| if num_tokens_from_string(sec) > 3 * self.chunk_token_num: |
| sections.append((sec[:int(len(sec) / 2)], "")) |
| sections.append((sec[int(len(sec) / 2):], "")) |
| else: |
| if sec.strip().find("#") == 0: |
| sections.append((sec, "")) |
| elif sections and sections[-1][0].strip().find("#") == 0: |
| sec_, _ = sections.pop(-1) |
| sections.append((sec_ + "\n" + sec, "")) |
| else: |
| sections.append((sec, "")) |
|
|
| for table in tables: |
| tbls.append(((None, markdown(table, extensions=['markdown.extensions.tables'])), "")) |
| return sections, 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'. |
| """ |
|
|
| is_english = lang.lower() == "english" |
| parser_config = kwargs.get( |
| "parser_config", { |
| "chunk_token_num": 128, "delimiter": "\n!?。;!?", "layout_recognize": "DeepDOC"}) |
| doc = { |
| "docnm_kwd": filename, |
| "title_tks": rag_tokenizer.tokenize(re.sub(r"\.[a-zA-Z]+$", "", filename)) |
| } |
| doc["title_sm_tks"] = rag_tokenizer.fine_grained_tokenize(doc["title_tks"]) |
| res = [] |
| pdf_parser = None |
| if re.search(r"\.docx$", filename, re.IGNORECASE): |
| callback(0.1, "Start to parse.") |
| sections, tables = Docx()(filename, binary) |
| res = tokenize_table(tables, doc, is_english) |
|
|
| callback(0.8, "Finish parsing.") |
| st = timer() |
|
|
| chunks, images = naive_merge_docx( |
| sections, int(parser_config.get( |
| "chunk_token_num", 128)), parser_config.get( |
| "delimiter", "\n!?。;!?")) |
|
|
| if kwargs.get("section_only", False): |
| return chunks |
|
|
| res.extend(tokenize_chunks_docx(chunks, doc, is_english, images)) |
| logging.info("naive_merge({}): {}".format(filename, timer() - st)) |
| return res |
|
|
| elif re.search(r"\.pdf$", filename, re.IGNORECASE): |
| pdf_parser = Pdf() |
| if parser_config.get("layout_recognize", "DeepDOC") == "Plain Text": |
| pdf_parser = PlainParser() |
| sections, tables = pdf_parser(filename if not binary else binary, from_page=from_page, to_page=to_page, |
| callback=callback) |
| res = tokenize_table(tables, doc, is_english) |
|
|
| elif re.search(r"\.xlsx?$", filename, re.IGNORECASE): |
| callback(0.1, "Start to parse.") |
| excel_parser = ExcelParser() |
| if parser_config.get("html4excel"): |
| sections = [(_, "") for _ in excel_parser.html(binary, 12) if _] |
| else: |
| sections = [(_, "") for _ in excel_parser(binary) if _] |
|
|
| elif re.search(r"\.(txt|py|js|java|c|cpp|h|php|go|ts|sh|cs|kt|sql)$", filename, re.IGNORECASE): |
| callback(0.1, "Start to parse.") |
| sections = TxtParser()(filename, binary, |
| parser_config.get("chunk_token_num", 128), |
| parser_config.get("delimiter", "\n!?;。;!?")) |
| callback(0.8, "Finish parsing.") |
|
|
| elif re.search(r"\.(md|markdown)$", filename, re.IGNORECASE): |
| callback(0.1, "Start to parse.") |
| sections, tables = Markdown(int(parser_config.get("chunk_token_num", 128)))(filename, binary) |
| res = tokenize_table(tables, doc, is_english) |
| callback(0.8, "Finish parsing.") |
|
|
| elif re.search(r"\.(htm|html)$", filename, re.IGNORECASE): |
| callback(0.1, "Start to parse.") |
| sections = HtmlParser()(filename, binary) |
| sections = [(_, "") for _ in sections if _] |
| callback(0.8, "Finish parsing.") |
|
|
| elif re.search(r"\.json$", filename, re.IGNORECASE): |
| callback(0.1, "Start to parse.") |
| chunk_token_num = int(parser_config.get("chunk_token_num", 128)) |
| sections = JsonParser(chunk_token_num)(binary) |
| sections = [(_, "") for _ in sections if _] |
| 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) |
| if doc_parsed.get('content', None) is not None: |
| sections = doc_parsed['content'].split('\n') |
| sections = [(_, "") for _ in sections if _] |
| callback(0.8, "Finish parsing.") |
| else: |
| callback(0.8, f"tika.parser got empty content from {filename}.") |
| logging.warning(f"tika.parser got empty content from {filename}.") |
| return [] |
|
|
| else: |
| raise NotImplementedError( |
| "file type not supported yet(pdf, xlsx, doc, docx, txt supported)") |
|
|
| st = timer() |
| chunks = naive_merge( |
| sections, int(parser_config.get( |
| "chunk_token_num", 128)), parser_config.get( |
| "delimiter", "\n!?。;!?")) |
| if kwargs.get("section_only", False): |
| return chunks |
|
|
| res.extend(tokenize_chunks(chunks, doc, is_english, pdf_parser)) |
| logging.info("naive_merge({}): {}".format(filename, timer() - st)) |
| 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) |
|
|