# 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 re from copy import deepcopy from io import BytesIO from timeit import default_timer as timer from nltk import word_tokenize from openpyxl import load_workbook from rag.nlp import is_english, random_choices, find_codec, qbullets_category, add_positions, has_qbullet, docx_question_level from rag.nlp import rag_tokenizer, tokenize_table, concat_img from rag.settings import cron_logger from deepdoc.parser import PdfParser, ExcelParser, DocxParser from docx import Document from PIL import Image from markdown import markdown class Excel(ExcelParser): def __call__(self, fnm, binary=None, callback=None): if not binary: wb = load_workbook(fnm) else: wb = load_workbook(BytesIO(binary)) total = 0 for sheetname in wb.sheetnames: total += len(list(wb[sheetname].rows)) res, fails = [], [] for sheetname in wb.sheetnames: ws = wb[sheetname] rows = list(ws.rows) for i, r in enumerate(rows): q, a = "", "" for cell in r: if not cell.value: continue if not q: q = str(cell.value) elif not a: a = str(cell.value) else: break if q and a: res.append((q, a)) else: fails.append(str(i + 1)) if len(res) % 999 == 0: callback(len(res) * 0.6 / total, ("Extract Q&A: {}".format(len(res)) + (f"{len(fails)} failure, line: %s..." % (",".join(fails[:3])) if fails else ""))) callback(0.6, ("Extract Q&A: {}. ".format(len(res)) + ( f"{len(fails)} failure, line: %s..." % (",".join(fails[:3])) if fails else ""))) self.is_english = is_english( [rmPrefix(q) for q, _ in random_choices(res, k=30) if len(q) > 1]) return res class Pdf(PdfParser): def __call__(self, filename, binary=None, from_page=0, to_page=100000, zoomin=3, callback=None): start = timer() callback(msg="OCR is running...") self.__images__( filename if not binary else binary, zoomin, from_page, to_page, callback ) callback(msg="OCR finished") cron_logger.info("OCR({}~{}): {}".format(from_page, to_page, timer() - start)) start = timer() self._layouts_rec(zoomin, drop=False) callback(0.63, "Layout analysis finished.") 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._naive_vertical_merge() # self._concat_downward() #self._filter_forpages() cron_logger.info("layouts: {}".format(timer() - start)) sections = [b["text"] for b in self.boxes] bull_x0_list = [] q_bull, reg = qbullets_category(sections) if q_bull == -1: raise ValueError("Unable to recognize Q&A structure.") qai_list = [] last_q, last_a, last_tag = '', '', '' last_index = -1 last_box = {'text':''} last_bull = None def sort_key(element): tbls_pn = element[1][0][0] tbls_top = element[1][0][3] return tbls_pn, tbls_top tbls.sort(key=sort_key) tbl_index = 0 last_pn, last_bottom = 0, 0 tbl_pn, tbl_left, tbl_right, tbl_top, tbl_bottom, tbl_tag, tbl_text = 1, 0, 0, 0, 0, '@@0\t0\t0\t0\t0##', '' for box in self.boxes: section, line_tag = box['text'], self._line_tag(box, zoomin) has_bull, index = has_qbullet(reg, box, last_box, last_index, last_bull, bull_x0_list) last_box, last_index, last_bull = box, index, has_bull line_pn = float(line_tag.lstrip('@@').split('\t')[0]) line_top = float(line_tag.rstrip('##').split('\t')[3]) tbl_pn, tbl_left, tbl_right, tbl_top, tbl_bottom, tbl_tag, tbl_text = self.get_tbls_info(tbls, tbl_index) if not has_bull: # No question bullet if not last_q: if tbl_pn < line_pn or (tbl_pn == line_pn and tbl_top <= line_top): # image passed tbl_index += 1 continue else: sum_tag = line_tag sum_section = section while ((tbl_pn == last_pn and tbl_top>= last_bottom) or (tbl_pn > last_pn)) \ and ((tbl_pn == line_pn and tbl_top <= line_top) or (tbl_pn < line_pn)): # add image at the middle of current answer sum_tag = f'{tbl_tag}{sum_tag}' sum_section = f'{tbl_text}{sum_section}' tbl_index += 1 tbl_pn, tbl_left, tbl_right, tbl_top, tbl_bottom, tbl_tag, tbl_text = self.get_tbls_info(tbls, tbl_index) last_a = f'{last_a}{sum_section}' last_tag = f'{last_tag}{sum_tag}' else: if last_q: while ((tbl_pn == last_pn and tbl_top>= last_bottom) or (tbl_pn > last_pn)) \ and ((tbl_pn == line_pn and tbl_top <= line_top) or (tbl_pn < line_pn)): # add image at the end of last answer last_tag = f'{last_tag}{tbl_tag}' last_a = f'{last_a}{tbl_text}' tbl_index += 1 tbl_pn, tbl_left, tbl_right, tbl_top, tbl_bottom, tbl_tag, tbl_text = self.get_tbls_info(tbls, tbl_index) image, poss = self.crop(last_tag, need_position=True) qai_list.append((last_q, last_a, image, poss)) last_q, last_a, last_tag = '', '', '' last_q = has_bull.group() _, end = has_bull.span() last_a = section[end:] last_tag = line_tag last_bottom = float(line_tag.rstrip('##').split('\t')[4]) last_pn = line_pn if last_q: qai_list.append((last_q, last_a, *self.crop(last_tag, need_position=True))) return qai_list, tbls def get_tbls_info(self, tbls, tbl_index): if tbl_index >= len(tbls): return 1, 0, 0, 0, 0, '@@0\t0\t0\t0\t0##', '' tbl_pn = tbls[tbl_index][1][0][0]+1 tbl_left = tbls[tbl_index][1][0][1] tbl_right = tbls[tbl_index][1][0][2] tbl_top = tbls[tbl_index][1][0][3] tbl_bottom = tbls[tbl_index][1][0][4] tbl_tag = "@@{}\t{:.1f}\t{:.1f}\t{:.1f}\t{:.1f}##" \ .format(tbl_pn, tbl_left, tbl_right, tbl_top, tbl_bottom) tbl_text = ''.join(tbls[tbl_index][0][1]) return tbl_pn, tbl_left, tbl_right, tbl_top, tbl_bottom, tbl_tag, tbl_text 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] image = related_part.image image = Image.open(BytesIO(image.blob)).convert('RGB') return image def __call__(self, filename, binary=None, from_page=0, to_page=100000, callback=None): self.doc = Document( filename) if not binary else Document(BytesIO(binary)) pn = 0 last_answer, last_image = "", None question_stack, level_stack = [], [] qai_list = [] for p in self.doc.paragraphs: if pn > to_page: break question_level, p_text = 0, '' if from_page <= pn < to_page and p.text.strip(): question_level, p_text = docx_question_level(p) if not question_level or question_level > 6: # not a question last_answer = f'{last_answer}\n{p_text}' current_image = self.get_picture(self.doc, p) last_image = concat_img(last_image, current_image) else: # is a question if last_answer or last_image: sum_question = '\n'.join(question_stack) if sum_question: qai_list.append((sum_question, last_answer, last_image)) last_answer, last_image = '', None i = question_level while question_stack and i <= level_stack[-1]: question_stack.pop() level_stack.pop() question_stack.append(p_text) level_stack.append(question_level) 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 if last_answer: sum_question = '\n'.join(question_stack) if sum_question: qai_list.append((sum_question, last_answer, last_image)) tbls = [] for tb in self.doc.tables: html= "" for r in tb.rows: html += "" 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"" if span == 1 else f"" html += "" html += "
{c.text}{c.text}
" tbls.append(((None, html), "")) return qai_list, tbls def rmPrefix(txt): return re.sub( r"^(问题|答案|回答|user|assistant|Q|A|Question|Answer|问|答)[\t:: ]+", "", txt.strip(), flags=re.IGNORECASE) def beAdocPdf(d, q, a, eng, image, poss): qprefix = "Question: " if eng else "问题:" aprefix = "Answer: " if eng else "回答:" d["content_with_weight"] = "\t".join( [qprefix + rmPrefix(q), aprefix + rmPrefix(a)]) d["content_ltks"] = rag_tokenizer.tokenize(q) d["content_sm_ltks"] = rag_tokenizer.fine_grained_tokenize(d["content_ltks"]) d["image"] = image add_positions(d, poss) return d def beAdocDocx(d, q, a, eng, image): qprefix = "Question: " if eng else "问题:" aprefix = "Answer: " if eng else "回答:" d["content_with_weight"] = "\t".join( [qprefix + rmPrefix(q), aprefix + rmPrefix(a)]) d["content_ltks"] = rag_tokenizer.tokenize(q) d["content_sm_ltks"] = rag_tokenizer.fine_grained_tokenize(d["content_ltks"]) d["image"] = image return d def beAdoc(d, q, a, eng): qprefix = "Question: " if eng else "问题:" aprefix = "Answer: " if eng else "回答:" d["content_with_weight"] = "\t".join( [qprefix + rmPrefix(q), aprefix + rmPrefix(a)]) d["content_ltks"] = rag_tokenizer.tokenize(q) d["content_sm_ltks"] = rag_tokenizer.fine_grained_tokenize(d["content_ltks"]) return d def mdQuestionLevel(s): match = re.match(r'#*', s) return (len(match.group(0)), s.lstrip('#').lstrip()) if match else (0, s) def chunk(filename, binary=None, lang="Chinese", callback=None, **kwargs): """ Excel and csv(txt) format files are supported. If the file is in excel format, there should be 2 column question and answer without header. And question column is ahead of answer column. And it's O.K if it has multiple sheets as long as the columns are rightly composed. If it's in csv format, it should be UTF-8 encoded. Use TAB as delimiter to separate question and answer. All the deformed lines will be ignored. Every pair of Q&A will be treated as a chunk. """ eng = lang.lower() == "english" res = [] doc = { "docnm_kwd": filename, "title_tks": rag_tokenizer.tokenize(re.sub(r"\.[a-zA-Z]+$", "", filename)) } if re.search(r"\.xlsx?$", filename, re.IGNORECASE): callback(0.1, "Start to parse.") excel_parser = Excel() for q, a in excel_parser(filename, binary, callback): res.append(beAdoc(deepcopy(doc), q, a, eng)) return res elif re.search(r"\.(txt|csv)$", filename, re.IGNORECASE): callback(0.1, "Start to parse.") txt = "" if binary: encoding = find_codec(binary) txt = binary.decode(encoding, errors="ignore") else: with open(filename, "r") as f: while True: l = f.readline() if not l: break txt += l lines = txt.split("\n") comma, tab = 0, 0 for l in lines: if len(l.split(",")) == 2: comma += 1 if len(l.split("\t")) == 2: tab += 1 delimiter = "\t" if tab >= comma else "," fails = [] question, answer = "", "" i = 0 while i < len(lines): arr = lines[i].split(delimiter) if len(arr) != 2: if question: answer += "\n" + lines[i] else: fails.append(str(i+1)) elif len(arr) == 2: if question and answer: res.append(beAdoc(deepcopy(doc), question, answer, eng)) question, answer = arr i += 1 if len(res) % 999 == 0: callback(len(res) * 0.6 / len(lines), ("Extract Q&A: {}".format(len(res)) + ( f"{len(fails)} failure, line: %s..." % (",".join(fails[:3])) if fails else ""))) if question: res.append(beAdoc(deepcopy(doc), question, answer, eng)) callback(0.6, ("Extract Q&A: {}".format(len(res)) + ( f"{len(fails)} failure, line: %s..." % (",".join(fails[:3])) if fails else ""))) return res elif re.search(r"\.pdf$", filename, re.IGNORECASE): callback(0.1, "Start to parse.") pdf_parser = Pdf() qai_list, tbls = pdf_parser(filename if not binary else binary, from_page=0, to_page=10000, callback=callback) for q, a, image, poss in qai_list: res.append(beAdocPdf(deepcopy(doc), q, a, eng, image, poss)) return res elif re.search(r"\.(md|markdown)$", filename, re.IGNORECASE): callback(0.1, "Start to parse.") txt = "" if binary: encoding = find_codec(binary) txt = binary.decode(encoding, errors="ignore") else: with open(filename, "r") as f: while True: l = f.readline() if not l: break txt += l lines = txt.split("\n") last_question, last_answer = "", "" question_stack, level_stack = [], [] code_block = False level_index = [-1] * 7 for index, l in enumerate(lines): if l.strip().startswith('```'): code_block = not code_block question_level, question = 0, '' if not code_block: question_level, question = mdQuestionLevel(l) if not question_level or question_level > 6: # not a question last_answer = f'{last_answer}\n{l}' else: # is a question if last_answer.strip(): sum_question = '\n'.join(question_stack) if sum_question: res.append(beAdoc(deepcopy(doc), sum_question, markdown(last_answer, extensions=['markdown.extensions.tables']), eng)) last_answer = '' i = question_level while question_stack and i <= level_stack[-1]: question_stack.pop() level_stack.pop() question_stack.append(question) level_stack.append(question_level) if last_answer.strip(): sum_question = '\n'.join(question_stack) if sum_question: res.append(beAdoc(deepcopy(doc), sum_question, markdown(last_answer, extensions=['markdown.extensions.tables']), eng)) return res elif re.search(r"\.docx$", filename, re.IGNORECASE): docx_parser = Docx() qai_list, tbls = docx_parser(filename, binary, from_page=0, to_page=10000, callback=callback) res = tokenize_table(tbls, doc, eng) for q, a, image in qai_list: res.append(beAdocDocx(deepcopy(doc), q, a, eng, image)) return res raise NotImplementedError( "Excel, csv(txt), pdf, markdown and docx format files are supported.") if __name__ == "__main__": import sys def dummy(prog=None, msg=""): pass chunk(sys.argv[1], from_page=0, to_page=10, callback=dummy)