# 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
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
from deepdoc.parser import PdfParser, ExcelParser, DocxParser
from rag.settings import cron_logger
class Docx(DocxParser):
def __init__(self):
pass
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 = []
for p in self.doc.paragraphs:
if pn > to_page:
break
if from_page <= pn < to_page and p.text.strip():
lines.append(self.__clean(p.text))
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
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 [(l, "") for l in lines if l], tbls
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)
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))
return [(b["text"], self._line_tag(b, zoomin))
for b in self.boxes], 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)
callback(0.8, "Finish parsing.")
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 = [(excel_parser.html(binary), "")]
elif re.search(r"\.(txt|md|py|js|java|c|cpp|h|php|go|ts|sh|cs|kt)$", filename, re.IGNORECASE):
callback(0.1, "Start to parse.")
txt = ""
if binary:
encoding = find_codec(binary)
txt = binary.decode(encoding, errors="ignore")
else:
with open(filename, "r") as f:
while True:
l = f.readline()
if not l:
break
txt += l
sections = txt.split("\n")
sections = [(l, "") for l in sections if l]
callback(0.8, "Finish parsing.")
elif re.search(r"\.doc$", 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(doc, docx, pdf, txt supported)")
st = timer()
chunks = naive_merge(
sections, parser_config.get(
"chunk_token_num", 128), parser_config.get(
"delimiter", "\n!?。；！？"))
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)