File size: 7,051 Bytes
cdba7f7 ee82924 0cfb2df 977d825 51482f3 b085dec cfd6ece 0cfb2df 51482f3 0cfb2df 1cc01e0 0cfb2df a8294f2 cdba7f7 51482f3 b9d91e7 54ec234 51482f3 b83edb4 279ca43 3cefaa0 51482f3 cdba7f7 b83edb4 f666f56 b83edb4 f666f56 b83edb4 4e03dc3 f1ccc7f f666f56 977d825 79ada0b 51482f3 79ada0b a8294f2 1ed30a6 a8294f2 f666f56 79ada0b 51482f3 cfd6ece 51482f3 cfd6ece f666f56 51482f3 ae35e13 51482f3 0cfb2df 51482f3 b085dec 51482f3 79ada0b f1ccc7f f666f56 79ada0b bcb7249 b085dec 08bab63 b085dec c46aa24 51482f3 a8294f2 d54aa01 b5b25b4 51482f3 79ada0b 51482f3 407b252 a8294f2 51482f3 b085dec ee82924 a8294f2 79ada0b ee82924 51482f3 977d825 79ada0b b085dec 977d825 51482f3 a8294f2 e34cb81 51482f3 a8294f2 51482f3 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 |
# 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)
|