ragflow / rag /app /presentation.py
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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
import re
from io import BytesIO
from PIL import Image
from rag.nlp import tokenize, is_english
from rag.nlp import rag_tokenizer
from deepdoc.parser import PdfParser, PptParser, PlainParser
from PyPDF2 import PdfReader as pdf2_read
class Ppt(PptParser):
def __call__(self, fnm, from_page, to_page, callback=None):
txts = super().__call__(fnm, from_page, to_page)
callback(0.5, "Text extraction finished.")
import aspose.slides as slides
import aspose.pydrawing as drawing
imgs = []
with slides.Presentation(BytesIO(fnm)) as presentation:
for i, slide in enumerate(presentation.slides[from_page: to_page]):
buffered = BytesIO()
slide.get_thumbnail(
0.5, 0.5).save(
buffered, drawing.imaging.ImageFormat.jpeg)
imgs.append(Image.open(buffered))
assert len(imgs) == len(
txts), "Slides text and image do not match: {} vs. {}".format(len(imgs), len(txts))
callback(0.9, "Image extraction finished")
self.is_english = is_english(txts)
return [(txts[i], imgs[i]) for i in range(len(txts))]
class Pdf(PdfParser):
def __init__(self):
super().__init__()
def __garbage(self, txt):
txt = txt.lower().strip()
if re.match(r"[0-9\.,%/-]+$", txt):
return True
if len(txt) < 3:
return True
return False
def __call__(self, filename, binary=None, from_page=0,
to_page=100000, zoomin=3, callback=None):
callback(msg="OCR is running...")
self.__images__(filename if not binary else binary,
zoomin, from_page, to_page, callback)
callback(0.8, "Page {}~{}: OCR finished".format(
from_page, min(to_page, self.total_page)))
assert len(self.boxes) == len(self.page_images), "{} vs. {}".format(
len(self.boxes), len(self.page_images))
res = []
for i in range(len(self.boxes)):
lines = "\n".join([b["text"] for b in self.boxes[i]
if not self.__garbage(b["text"])])
res.append((lines, self.page_images[i]))
callback(0.9, "Page {}~{}: Parsing finished".format(
from_page, min(to_page, self.total_page)))
return res
class PlainPdf(PlainParser):
def __call__(self, filename, binary=None, from_page=0,
to_page=100000, callback=None, **kwargs):
self.pdf = pdf2_read(filename if not binary else BytesIO(binary))
page_txt = []
for page in self.pdf.pages[from_page: to_page]:
page_txt.append(page.extract_text())
callback(0.9, "Parsing finished")
return [(txt, None) for txt in page_txt]
def chunk(filename, binary=None, from_page=0, to_page=100000,
lang="Chinese", callback=None, **kwargs):
"""
The supported file formats are pdf, pptx.
Every page will be treated as a chunk. And the thumbnail of every page will be stored.
PPT file will be parsed by using this method automatically, setting-up for every PPT file is not necessary.
"""
eng = lang.lower() == "english"
doc = {
"docnm_kwd": filename,
"title_tks": rag_tokenizer.tokenize(re.sub(r"\.[a-zA-Z]+$", "", filename))
}
doc["title_sm_tks"] = rag_tokenizer.fine_grained_tokenize(doc["title_tks"])
res = []
if re.search(r"\.pptx?$", filename, re.IGNORECASE):
ppt_parser = Ppt()
for pn, (txt, img) in enumerate(ppt_parser(
filename if not binary else binary, from_page, 1000000, callback)):
d = copy.deepcopy(doc)
pn += from_page
d["image"] = img
d["page_num_int"] = [pn + 1]
d["top_int"] = [0]
d["position_int"] = [(pn + 1, 0, img.size[0], 0, img.size[1])]
tokenize(d, txt, eng)
res.append(d)
return res
elif re.search(r"\.pdf$", filename, re.IGNORECASE):
pdf_parser = Pdf() if kwargs.get(
"parser_config", {}).get(
"layout_recognize", True) else PlainPdf()
for pn, (txt, img) in enumerate(pdf_parser(filename, binary,
from_page=from_page, to_page=to_page, callback=callback)):
d = copy.deepcopy(doc)
pn += from_page
if img:
d["image"] = img
d["page_num_int"] = [pn + 1]
d["top_int"] = [0]
d["position_int"] = [
(pn + 1, 0, img.size[0] if img else 0, 0, img.size[1] if img else 0)]
tokenize(d, txt, eng)
res.append(d)
return res
raise NotImplementedError(
"file type not supported yet(pptx, pdf supported)")
if __name__ == "__main__":
import sys
def dummy(a, b):
pass
chunk(sys.argv[1], callback=dummy)