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# 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 copy | |
from tika import parser | |
import re | |
from io import BytesIO | |
from rag.nlp import bullets_category, is_english, tokenize, remove_contents_table, \ | |
hierarchical_merge, make_colon_as_title, naive_merge, random_choices, tokenize_table, add_positions, \ | |
tokenize_chunks, find_codec | |
from rag.nlp import rag_tokenizer | |
from deepdoc.parser import PdfParser, DocxParser, PlainParser, HtmlParser | |
class Pdf(PdfParser): | |
def __call__(self, filename, binary=None, from_page=0, | |
to_page=100000, zoomin=3, callback=None): | |
callback(msg="OCR is running...") | |
self.__images__( | |
filename if not binary else binary, | |
zoomin, | |
from_page, | |
to_page, | |
callback) | |
callback(msg="OCR finished") | |
from timeit import default_timer as timer | |
start = timer() | |
self._layouts_rec(zoomin) | |
callback(0.67, "Layout analysis finished") | |
print("layouts:", timer() - start) | |
self._table_transformer_job(zoomin) | |
callback(0.68, "Table analysis finished") | |
self._text_merge() | |
tbls = self._extract_table_figure(True, zoomin, True, True) | |
self._naive_vertical_merge() | |
self._filter_forpages() | |
self._merge_with_same_bullet() | |
callback(0.75, "Text merging finished.") | |
callback(0.8, "Text extraction finished") | |
return [(b["text"] + self._line_tag(b, zoomin), b.get("layoutno", "")) | |
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, txt. | |
Since a book is long and not all the parts are useful, if it's a PDF, | |
please setup the page ranges for every book in order eliminate negative effects and save elapsed computing time. | |
""" | |
doc = { | |
"docnm_kwd": filename, | |
"title_tks": rag_tokenizer.tokenize(re.sub(r"\.[a-zA-Z]+$", "", filename)) | |
} | |
doc["title_sm_tks"] = rag_tokenizer.fine_grained_tokenize(doc["title_tks"]) | |
pdf_parser = None | |
sections, tbls = [], [] | |
if re.search(r"\.docx$", filename, re.IGNORECASE): | |
callback(0.1, "Start to parse.") | |
doc_parser = DocxParser() | |
# TODO: table of contents need to be removed | |
sections, tbls = doc_parser( | |
binary if binary else filename, from_page=from_page, to_page=to_page) | |
remove_contents_table(sections, eng=is_english( | |
random_choices([t for t, _ in sections], k=200))) | |
tbls = [((None, lns), None) for lns in tbls] | |
callback(0.8, "Finish parsing.") | |
elif re.search(r"\.pdf$", filename, re.IGNORECASE): | |
pdf_parser = Pdf() if kwargs.get( | |
"parser_config", {}).get( | |
"layout_recognize", True) else PlainParser() | |
sections, tbls = pdf_parser(filename if not binary else binary, | |
from_page=from_page, to_page=to_page, callback=callback) | |
elif re.search(r"\.txt$", 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] | |
remove_contents_table(sections, eng=is_english( | |
random_choices([t for t, _ in sections], k=200))) | |
callback(0.8, "Finish parsing.") | |
elif re.search(r"\.(htm|html)$", filename, re.IGNORECASE): | |
callback(0.1, "Start to parse.") | |
sections = HtmlParser()(filename, binary) | |
sections = [(l, "") for l in sections if l] | |
remove_contents_table(sections, eng=is_english( | |
random_choices([t for t, _ in sections], k=200))) | |
callback(0.8, "Finish parsing.") | |
elif re.search(r"\.doc$", 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] | |
remove_contents_table(sections, eng=is_english( | |
random_choices([t for t, _ in sections], k=200))) | |
callback(0.8, "Finish parsing.") | |
else: | |
raise NotImplementedError( | |
"file type not supported yet(doc, docx, pdf, txt supported)") | |
make_colon_as_title(sections) | |
bull = bullets_category( | |
[t for t in random_choices([t for t, _ in sections], k=100)]) | |
if bull >= 0: | |
chunks = ["\n".join(ck) | |
for ck in hierarchical_merge(bull, sections, 5)] | |
else: | |
sections = [s.split("@") for s, _ in sections] | |
sections = [(pr[0], "@" + pr[1]) if len(pr) == 2 else (pr[0], '') for pr in sections ] | |
chunks = naive_merge( | |
sections, kwargs.get( | |
"chunk_token_num", 256), kwargs.get( | |
"delimer", "\n。;!?")) | |
# is it English | |
# is_english(random_choices([t for t, _ in sections], k=218)) | |
eng = lang.lower() == "english" | |
res = tokenize_table(tbls, doc, eng) | |
res.extend(tokenize_chunks(chunks, doc, eng, pdf_parser)) | |
return res | |
if __name__ == "__main__": | |
import sys | |
def dummy(prog=None, msg=""): | |
pass | |
chunk(sys.argv[1], from_page=1, to_page=10, callback=dummy) | |