mirror of
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Format file format from Windows/dos to Unix (#1949)
### What problem does this PR solve? Related source file is in Windows/DOS format, they are format to Unix format. ### Type of change - [x] Refactoring Signed-off-by: Jin Hai <haijin.chn@gmail.com>
This commit is contained in:
Jin Hai
564
rag/app/naive.py
564
rag/app/naive.py
@ -1,282 +1,282 @@
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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from tika import parser
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from io import BytesIO
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from docx import Document
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from timeit import default_timer as timer
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import re
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from deepdoc.parser.pdf_parser import PlainParser
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from rag.nlp import rag_tokenizer, naive_merge, tokenize_table, tokenize_chunks, find_codec, concat_img, naive_merge_docx, tokenize_chunks_docx
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from deepdoc.parser import PdfParser, ExcelParser, DocxParser, HtmlParser, JsonParser, MarkdownParser, TxtParser
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from rag.settings import cron_logger
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from rag.utils import num_tokens_from_string
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from PIL import Image
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from functools import reduce
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from markdown import markdown
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from docx.image.exceptions import UnrecognizedImageError
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class Docx(DocxParser):
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def __init__(self):
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pass
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def get_picture(self, document, paragraph):
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img = paragraph._element.xpath('.//pic:pic')
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if not img:
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return None
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img = img[0]
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embed = img.xpath('.//a:blip/@r:embed')[0]
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related_part = document.part.related_parts[embed]
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try:
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image_blob = related_part.image.blob
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except UnrecognizedImageError:
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print("Unrecognized image format. Skipping image.")
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return None
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try:
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image = Image.open(BytesIO(image_blob)).convert('RGB')
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return image
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except Exception as e:
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return None
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def __clean(self, line):
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line = re.sub(r"\u3000", " ", line).strip()
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return line
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def __call__(self, filename, binary=None, from_page=0, to_page=100000):
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self.doc = Document(
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filename) if not binary else Document(BytesIO(binary))
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pn = 0
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lines = []
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last_image = None
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for p in self.doc.paragraphs:
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if pn > to_page:
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break
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if from_page <= pn < to_page:
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if p.text.strip():
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if p.style and p.style.name == 'Caption':
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former_image = None
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if lines and lines[-1][1] and lines[-1][2] != 'Caption':
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former_image = lines[-1][1].pop()
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elif last_image:
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former_image = last_image
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last_image = None
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lines.append((self.__clean(p.text), [former_image], p.style.name))
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else:
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current_image = self.get_picture(self.doc, p)
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image_list = [current_image]
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if last_image:
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image_list.insert(0, last_image)
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last_image = None
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lines.append((self.__clean(p.text), image_list, p.style.name))
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else:
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if current_image := self.get_picture(self.doc, p):
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if lines:
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lines[-1][1].append(current_image)
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else:
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last_image = current_image
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for run in p.runs:
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if 'lastRenderedPageBreak' in run._element.xml:
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pn += 1
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continue
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if 'w:br' in run._element.xml and 'type="page"' in run._element.xml:
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pn += 1
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new_line = [(line[0], reduce(concat_img, line[1]) if line[1] else None) for line in lines]
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tbls = []
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for tb in self.doc.tables:
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html= "<table>"
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for r in tb.rows:
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html += "<tr>"
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i = 0
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while i < len(r.cells):
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span = 1
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c = r.cells[i]
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for j in range(i+1, len(r.cells)):
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if c.text == r.cells[j].text:
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span += 1
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i = j
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i += 1
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html += f"<td>{c.text}</td>" if span == 1 else f"<td colspan='{span}'>{c.text}</td>"
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html += "</tr>"
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html += "</table>"
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tbls.append(((None, html), ""))
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return new_line, tbls
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class Pdf(PdfParser):
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def __call__(self, filename, binary=None, from_page=0,
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to_page=100000, zoomin=3, callback=None):
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start = timer()
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callback(msg="OCR is running...")
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self.__images__(
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filename if not binary else binary,
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zoomin,
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from_page,
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to_page,
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callback
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)
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callback(msg="OCR finished")
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cron_logger.info("OCR({}~{}): {}".format(from_page, to_page, timer() - start))
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start = timer()
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self._layouts_rec(zoomin)
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callback(0.63, "Layout analysis finished.")
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self._table_transformer_job(zoomin)
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callback(0.65, "Table analysis finished.")
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self._text_merge()
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callback(0.67, "Text merging finished")
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tbls = self._extract_table_figure(True, zoomin, True, True)
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#self._naive_vertical_merge()
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self._concat_downward()
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#self._filter_forpages()
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cron_logger.info("layouts: {}".format(timer() - start))
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return [(b["text"], self._line_tag(b, zoomin))
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for b in self.boxes], tbls
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class Markdown(MarkdownParser):
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def __call__(self, filename, binary=None):
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txt = ""
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tbls = []
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if binary:
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encoding = find_codec(binary)
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txt = binary.decode(encoding, errors="ignore")
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else:
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with open(filename, "r") as f:
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txt = f.read()
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remainder, tables = self.extract_tables_and_remainder(f'{txt}\n')
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sections = []
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tbls = []
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for sec in remainder.split("\n"):
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if num_tokens_from_string(sec) > 10 * self.chunk_token_num:
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sections.append((sec[:int(len(sec)/2)], ""))
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sections.append((sec[int(len(sec)/2):], ""))
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else:
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sections.append((sec, ""))
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print(tables)
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for table in tables:
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tbls.append(((None, markdown(table, extensions=['markdown.extensions.tables'])), ""))
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return sections, tbls
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def chunk(filename, binary=None, from_page=0, to_page=100000,
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lang="Chinese", callback=None, **kwargs):
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"""
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Supported file formats are docx, pdf, excel, txt.
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This method apply the naive ways to chunk files.
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Successive text will be sliced into pieces using 'delimiter'.
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Next, these successive pieces are merge into chunks whose token number is no more than 'Max token number'.
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"""
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eng = lang.lower() == "english" # is_english(cks)
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parser_config = kwargs.get(
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"parser_config", {
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"chunk_token_num": 128, "delimiter": "\n!?。；！？", "layout_recognize": True})
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doc = {
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"docnm_kwd": filename,
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"title_tks": rag_tokenizer.tokenize(re.sub(r"\.[a-zA-Z]+$", "", filename))
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}
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doc["title_sm_tks"] = rag_tokenizer.fine_grained_tokenize(doc["title_tks"])
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res = []
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pdf_parser = None
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sections = []
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if re.search(r"\.docx$", filename, re.IGNORECASE):
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callback(0.1, "Start to parse.")
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sections, tbls = Docx()(filename, binary)
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res = tokenize_table(tbls, doc, eng) # just for table
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callback(0.8, "Finish parsing.")
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st = timer()
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chunks, images = naive_merge_docx(
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sections, int(parser_config.get(
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"chunk_token_num", 128)), parser_config.get(
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"delimiter", "\n!?。；！？"))
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if kwargs.get("section_only", False):
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return chunks
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res.extend(tokenize_chunks_docx(chunks, doc, eng, images))
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cron_logger.info("naive_merge({}): {}".format(filename, timer() - st))
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return res
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elif re.search(r"\.pdf$", filename, re.IGNORECASE):
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pdf_parser = Pdf(
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) if parser_config.get("layout_recognize", True) else PlainParser()
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sections, tbls = pdf_parser(filename if not binary else binary,
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from_page=from_page, to_page=to_page, callback=callback)
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res = tokenize_table(tbls, doc, eng)
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elif re.search(r"\.xlsx?$", filename, re.IGNORECASE):
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callback(0.1, "Start to parse.")
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excel_parser = ExcelParser()
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sections = [(l, "") for l in excel_parser.html(binary) if l]
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elif re.search(r"\.(txt|py|js|java|c|cpp|h|php|go|ts|sh|cs|kt|sql)$", filename, re.IGNORECASE):
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callback(0.1, "Start to parse.")
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sections = TxtParser()(filename,binary,
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parser_config.get("chunk_token_num", 128),
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parser_config.get("delimiter", "\n!?;。；！？"))
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callback(0.8, "Finish parsing.")
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elif re.search(r"\.(md|markdown)$", filename, re.IGNORECASE):
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callback(0.1, "Start to parse.")
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sections, tbls = Markdown(int(parser_config.get("chunk_token_num", 128)))(filename, binary)
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res = tokenize_table(tbls, doc, eng)
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callback(0.8, "Finish parsing.")
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elif re.search(r"\.(htm|html)$", filename, re.IGNORECASE):
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callback(0.1, "Start to parse.")
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sections = HtmlParser()(filename, binary)
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sections = [(l, "") for l in sections if l]
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callback(0.8, "Finish parsing.")
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elif re.search(r"\.json$", filename, re.IGNORECASE):
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callback(0.1, "Start to parse.")
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sections = JsonParser(int(parser_config.get("chunk_token_num", 128)))(binary)
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sections = [(l, "") for l in sections if l]
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callback(0.8, "Finish parsing.")
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elif re.search(r"\.doc$", filename, re.IGNORECASE):
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callback(0.1, "Start to parse.")
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binary = BytesIO(binary)
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doc_parsed = parser.from_buffer(binary)
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sections = doc_parsed['content'].split('\n')
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sections = [(l, "") for l in sections if l]
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callback(0.8, "Finish parsing.")
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else:
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raise NotImplementedError(
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"file type not supported yet(pdf, xlsx, doc, docx, txt supported)")
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st = timer()
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chunks = naive_merge(
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sections, int(parser_config.get(
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"chunk_token_num", 128)), parser_config.get(
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"delimiter", "\n!?。；！？"))
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if kwargs.get("section_only", False):
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return chunks
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res.extend(tokenize_chunks(chunks, doc, eng, pdf_parser))
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cron_logger.info("naive_merge({}): {}".format(filename, timer() - st))
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return res
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if __name__ == "__main__":
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import sys
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def dummy(prog=None, msg=""):
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pass
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chunk(sys.argv[1], from_page=0, to_page=10, callback=dummy)
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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from tika import parser
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from io import BytesIO
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from docx import Document
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from timeit import default_timer as timer
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import re
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from deepdoc.parser.pdf_parser import PlainParser
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from rag.nlp import rag_tokenizer, naive_merge, tokenize_table, tokenize_chunks, find_codec, concat_img, naive_merge_docx, tokenize_chunks_docx
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from deepdoc.parser import PdfParser, ExcelParser, DocxParser, HtmlParser, JsonParser, MarkdownParser, TxtParser
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from rag.settings import cron_logger
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from rag.utils import num_tokens_from_string
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from PIL import Image
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from functools import reduce
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from markdown import markdown
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from docx.image.exceptions import UnrecognizedImageError
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class Docx(DocxParser):
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def __init__(self):
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pass
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def get_picture(self, document, paragraph):
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img = paragraph._element.xpath('.//pic:pic')
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if not img:
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return None
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img = img[0]
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embed = img.xpath('.//a:blip/@r:embed')[0]
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related_part = document.part.related_parts[embed]
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try:
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image_blob = related_part.image.blob
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except UnrecognizedImageError:
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print("Unrecognized image format. Skipping image.")
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return None
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try:
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image = Image.open(BytesIO(image_blob)).convert('RGB')
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return image
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except Exception as e:
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return None
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def __clean(self, line):
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line = re.sub(r"\u3000", " ", line).strip()
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return line
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def __call__(self, filename, binary=None, from_page=0, to_page=100000):
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self.doc = Document(
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filename) if not binary else Document(BytesIO(binary))
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pn = 0
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lines = []
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last_image = None
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for p in self.doc.paragraphs:
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if pn > to_page:
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break
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if from_page <= pn < to_page:
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if p.text.strip():
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if p.style and p.style.name == 'Caption':
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former_image = None
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if lines and lines[-1][1] and lines[-1][2] != 'Caption':
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former_image = lines[-1][1].pop()
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elif last_image:
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former_image = last_image
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last_image = None
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lines.append((self.__clean(p.text), [former_image], p.style.name))
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else:
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current_image = self.get_picture(self.doc, p)
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image_list = [current_image]
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if last_image:
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image_list.insert(0, last_image)
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last_image = None
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lines.append((self.__clean(p.text), image_list, p.style.name))
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else:
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if current_image := self.get_picture(self.doc, p):
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if lines:
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lines[-1][1].append(current_image)
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else:
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last_image = current_image
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for run in p.runs:
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if 'lastRenderedPageBreak' in run._element.xml:
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pn += 1
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continue
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if 'w:br' in run._element.xml and 'type="page"' in run._element.xml:
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pn += 1
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new_line = [(line[0], reduce(concat_img, line[1]) if line[1] else None) for line in lines]
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tbls = []
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for tb in self.doc.tables:
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html= "<table>"
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for r in tb.rows:
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html += "<tr>"
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i = 0
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while i < len(r.cells):
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span = 1
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c = r.cells[i]
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for j in range(i+1, len(r.cells)):
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if c.text == r.cells[j].text:
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span += 1
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i = j
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i += 1
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html += f"<td>{c.text}</td>" if span == 1 else f"<td colspan='{span}'>{c.text}</td>"
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html += "</tr>"
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html += "</table>"
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tbls.append(((None, html), ""))
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return new_line, tbls
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class Pdf(PdfParser):
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def __call__(self, filename, binary=None, from_page=0,
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to_page=100000, zoomin=3, callback=None):
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start = timer()
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callback(msg="OCR is running...")
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self.__images__(
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filename if not binary else binary,
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zoomin,
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from_page,
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to_page,
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callback
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)
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callback(msg="OCR finished")
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cron_logger.info("OCR({}~{}): {}".format(from_page, to_page, timer() - start))
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start = timer()
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self._layouts_rec(zoomin)
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callback(0.63, "Layout analysis finished.")
|
||||
self._table_transformer_job(zoomin)
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callback(0.65, "Table analysis finished.")
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self._text_merge()
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callback(0.67, "Text merging finished")
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tbls = self._extract_table_figure(True, zoomin, True, True)
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#self._naive_vertical_merge()
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self._concat_downward()
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#self._filter_forpages()
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cron_logger.info("layouts: {}".format(timer() - start))
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return [(b["text"], self._line_tag(b, zoomin))
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for b in self.boxes], tbls
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class Markdown(MarkdownParser):
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def __call__(self, filename, binary=None):
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||||
txt = ""
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||||
tbls = []
|
||||
if binary:
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||||
encoding = find_codec(binary)
|
||||
txt = binary.decode(encoding, errors="ignore")
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||||
else:
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||||
with open(filename, "r") as f:
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||||
txt = f.read()
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||||
remainder, tables = self.extract_tables_and_remainder(f'{txt}\n')
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||||
sections = []
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||||
tbls = []
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||||
for sec in remainder.split("\n"):
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||||
if num_tokens_from_string(sec) > 10 * self.chunk_token_num:
|
||||
sections.append((sec[:int(len(sec)/2)], ""))
|
||||
sections.append((sec[int(len(sec)/2):], ""))
|
||||
else:
|
||||
sections.append((sec, ""))
|
||||
print(tables)
|
||||
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'.
|
||||
"""
|
||||
|
||||
eng = lang.lower() == "english" # is_english(cks)
|
||||
parser_config = kwargs.get(
|
||||
"parser_config", {
|
||||
"chunk_token_num": 128, "delimiter": "\n!?。；！？", "layout_recognize": True})
|
||||
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
|
||||
sections = []
|
||||
if re.search(r"\.docx$", filename, re.IGNORECASE):
|
||||
callback(0.1, "Start to parse.")
|
||||
sections, tbls = Docx()(filename, binary)
|
||||
res = tokenize_table(tbls, doc, eng) # just for table
|
||||
|
||||
callback(0.8, "Finish parsing.")
|
||||
st = timer()
|
||||
|
||||
chunks, images = naive_merge_docx(
|
||||
sections, int(parser_config.get(
|
||||
"chunk_token_num", 128)), parser_config.get(
|
||||
"delimiter", "\n!?。；！？"))
|
||||
|
||||
if kwargs.get("section_only", False):
|
||||
return chunks
|
||||
|
||||
res.extend(tokenize_chunks_docx(chunks, doc, eng, images))
|
||||
cron_logger.info("naive_merge({}): {}".format(filename, timer() - st))
|
||||
return res
|
||||
|
||||
elif re.search(r"\.pdf$", filename, re.IGNORECASE):
|
||||
pdf_parser = Pdf(
|
||||
) if parser_config.get("layout_recognize", True) else PlainParser()
|
||||
sections, tbls = pdf_parser(filename if not binary else binary,
|
||||
from_page=from_page, to_page=to_page, callback=callback)
|
||||
res = tokenize_table(tbls, doc, eng)
|
||||
|
||||
elif re.search(r"\.xlsx?$", filename, re.IGNORECASE):
|
||||
callback(0.1, "Start to parse.")
|
||||
excel_parser = ExcelParser()
|
||||
sections = [(l, "") for l in excel_parser.html(binary) if l]
|
||||
|
||||
elif re.search(r"\.(txt|py|js|java|c|cpp|h|php|go|ts|sh|cs|kt|sql)$", 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)$", filename, re.IGNORECASE):
|
||||
callback(0.1, "Start to parse.")
|
||||
sections, tbls = Markdown(int(parser_config.get("chunk_token_num", 128)))(filename, binary)
|
||||
res = tokenize_table(tbls, doc, eng)
|
||||
callback(0.8, "Finish parsing.")
|
||||
|
||||
elif re.search(r"\.(htm|html)$", filename, re.IGNORECASE):
|
||||
callback(0.1, "Start to parse.")
|
||||
sections = HtmlParser()(filename, binary)
|
||||
sections = [(l, "") for l in sections if l]
|
||||
callback(0.8, "Finish parsing.")
|
||||
|
||||
elif re.search(r"\.json$", filename, re.IGNORECASE):
|
||||
callback(0.1, "Start to parse.")
|
||||
sections = JsonParser(int(parser_config.get("chunk_token_num", 128)))(binary)
|
||||
sections = [(l, "") for l in sections if l]
|
||||
callback(0.8, "Finish parsing.")
|
||||
|
||||
elif re.search(r"\.doc$", 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(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, eng, pdf_parser))
|
||||
cron_logger.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)
|
||||
|
||||
Reference in New Issue
Block a user