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feat: add paddleocr parser (#12513)

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### What problem does this PR solve?

Add PaddleOCR as a new PDF parser.

### Type of change

- [x] New Feature (non-breaking change which adds functionality)
This commit is contained in:
Lin Manhui
2026-01-09 17:48:45 +08:00
committed by GitHub
parent 6abf55c048
commit 2e09db02f3
34 changed files with 1510 additions and 453 deletions
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92
rag/app/manual.py
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@ -20,8 +20,7 @@ import re
from common.constants import ParserType
from io import BytesIO
from rag.nlp import rag_tokenizer, tokenize, tokenize_table, bullets_category, title_frequency, tokenize_chunks, \
docx_question_level, attach_media_context
from rag.nlp import rag_tokenizer, tokenize, tokenize_table, bullets_category, title_frequency, tokenize_chunks, docx_question_level, attach_media_context
from common.token_utils import num_tokens_from_string
from deepdoc.parser import PdfParser, DocxParser
from deepdoc.parser.figure_parser import vision_figure_parser_pdf_wrapper, vision_figure_parser_docx_wrapper
@ -36,18 +35,12 @@ class Pdf(PdfParser):
self.model_speciess = ParserType.MANUAL.value
super().__init__()
def __call__(self, filename, binary=None, from_page=0,
to_page=100000, zoomin=3, callback=None):
def __call__(self, filename, binary=None, from_page=0, to_page=100000, zoomin=3, callback=None):
from timeit import default_timer as timer
start = timer()
callback(msg="OCR started")
self.__images__(
filename if not binary else binary,
zoomin,
from_page,
to_page,
callback
)
self.__images__(filename if not binary else binary, zoomin, from_page, to_page, callback)
callback(msg="OCR finished ({:.2f}s)".format(timer() - start))
logging.debug("OCR: {}".format(timer() - start))
@ -71,8 +64,7 @@ class Pdf(PdfParser):
for b in self.boxes:
b["text"] = re.sub(r"([\t 　]|\u3000){2,}", " ", b["text"].strip())
return [(b["text"], b.get("layoutno", ""), self.get_position(b, zoomin))
for i, b in enumerate(self.boxes)], tbls
return [(b["text"], b.get("layoutno", ""), self.get_position(b, zoomin)) for i, b in enumerate(self.boxes)], tbls
class Docx(DocxParser):
@ -80,12 +72,12 @@ class Docx(DocxParser):
pass
def get_picture(self, document, paragraph):
img = paragraph._element.xpath('.//pic:pic')
img = paragraph._element.xpath(".//pic:pic")
if not img:
return None
try:
img = img[0]
embed = img.xpath('.//a:blip/@r:embed')[0]
embed = img.xpath(".//a:blip/@r:embed")[0]
related_part = document.part.related_parts[embed]
image = related_part.image
if image is not None:
@ -111,7 +103,7 @@ class Docx(DocxParser):
new_width = max(width1, width2)
new_height = height1 + height2
new_image = Image.new('RGB', (new_width, new_height))
new_image = Image.new("RGB", (new_width, new_height))
new_image.paste(img1, (0, 0))
new_image.paste(img2, (0, height1))
@ -119,8 +111,7 @@ class Docx(DocxParser):
return new_image
def __call__(self, filename, binary=None, from_page=0, to_page=100000, callback=None):
self.doc = Document(
filename) if not binary else Document(BytesIO(binary))
self.doc = Document(filename) if not binary else Document(BytesIO(binary))
pn = 0
last_answer, last_image = "", None
question_stack, level_stack = [], []
@ -128,19 +119,19 @@ class Docx(DocxParser):
for p in self.doc.paragraphs:
if pn > to_page:
break
question_level, p_text = 0, ''
question_level, p_text = 0, ""
if from_page <= pn < to_page and p.text.strip():
question_level, p_text = docx_question_level(p)
if not question_level or question_level > 6: # not a question
last_answer = f'{last_answer}\n{p_text}'
last_answer = f"{last_answer}\n{p_text}"
current_image = self.get_picture(self.doc, p)
last_image = self.concat_img(last_image, current_image)
else: # is a question
if last_answer or last_image:
sum_question = '\n'.join(question_stack)
sum_question = "\n".join(question_stack)
if sum_question:
ti_list.append((f'{sum_question}\n{last_answer}', last_image))
last_answer, last_image = '', None
ti_list.append((f"{sum_question}\n{last_answer}", last_image))
last_answer, last_image = "", None
i = question_level
while question_stack and i <= level_stack[-1]:
@ -149,15 +140,15 @@ class Docx(DocxParser):
question_stack.append(p_text)
level_stack.append(question_level)
for run in p.runs:
if 'lastRenderedPageBreak' in run._element.xml:
if "lastRenderedPageBreak" in run._element.xml:
pn += 1
continue
if 'w:br' in run._element.xml and 'type="page"' in run._element.xml:
if "w:br" in run._element.xml and 'type="page"' in run._element.xml:
pn += 1
if last_answer:
sum_question = '\n'.join(question_stack)
sum_question = "\n".join(question_stack)
if sum_question:
ti_list.append((f'{sum_question}\n{last_answer}', last_image))
ti_list.append((f"{sum_question}\n{last_answer}", last_image))
tbls = []
for tb in self.doc.tables:
@ -182,26 +173,19 @@ class Docx(DocxParser):
return ti_list, tbls
def chunk(filename, binary=None, from_page=0, to_page=100000,
lang="Chinese", callback=None, **kwargs):
def chunk(filename, binary=None, from_page=0, to_page=100000, lang="Chinese", callback=None, **kwargs):
"""
Only pdf is supported.
Only pdf is supported.
"""
parser_config = kwargs.get(
"parser_config", {
"chunk_token_num": 512, "delimiter": "\n!?。；！？", "layout_recognize": "DeepDOC"})
parser_config = kwargs.get("parser_config", {"chunk_token_num": 512, "delimiter": "\n!?。；！？", "layout_recognize": "DeepDOC"})
pdf_parser = None
doc = {
"docnm_kwd": filename
}
doc = {"docnm_kwd": filename}
doc["title_tks"] = rag_tokenizer.tokenize(re.sub(r"\.[a-zA-Z]+$", "", doc["docnm_kwd"]))
doc["title_sm_tks"] = rag_tokenizer.fine_grained_tokenize(doc["title_tks"])
# is it English
eng = lang.lower() == "english" # pdf_parser.is_english
if re.search(r"\.pdf$", filename, re.IGNORECASE):
layout_recognizer, parser_model_name = normalize_layout_recognizer(
parser_config.get("layout_recognize", "DeepDOC")
)
layout_recognizer, parser_model_name = normalize_layout_recognizer(parser_config.get("layout_recognize", "DeepDOC"))
if isinstance(layout_recognizer, bool):
layout_recognizer = "DeepDOC" if layout_recognizer else "Plain Text"
@ -222,8 +206,9 @@ def chunk(filename, binary=None, from_page=0, to_page=100000,
pdf_cls=Pdf,
layout_recognizer=layout_recognizer,
mineru_llm_name=parser_model_name,
paddleocr_llm_name=parser_model_name,
parse_method="manual",
**kwargs
**kwargs,
)
def _normalize_section(section):
@ -252,7 +237,7 @@ def chunk(filename, binary=None, from_page=0, to_page=100000,
if not sections and not tbls:
return []
if name in ["tcadp", "docling", "mineru"]:
if name in ["tcadp", "docling", "mineru", "paddleocr"]:
parser_config["chunk_token_num"] = 0
callback(0.8, "Finish parsing.")
@ -264,8 +249,7 @@ def chunk(filename, binary=None, from_page=0, to_page=100000,
for txt, _, _ in sections:
for t, lvl in pdf_parser.outlines:
tks = set([t[i] + t[i + 1] for i in range(len(t) - 1)])
tks_ = set([txt[i] + txt[i + 1]
for i in range(min(len(t), len(txt) - 1))])
tks_ = set([txt[i] + txt[i + 1] for i in range(min(len(t), len(txt) - 1))])
if len(set(tks & tks_)) / max([len(tks), len(tks_), 1]) > 0.8:
levels.append(lvl)
break
@ -274,8 +258,7 @@ def chunk(filename, binary=None, from_page=0, to_page=100000,
else:
bull = bullets_category([txt for txt, _, _ in sections])
most_level, levels = title_frequency(
bull, [(txt, lvl) for txt, lvl, _ in sections])
most_level, levels = title_frequency(bull, [(txt, lvl) for txt, lvl, _ in sections])
assert len(sections) == len(levels)
sec_ids = []
@ -285,25 +268,21 @@ def chunk(filename, binary=None, from_page=0, to_page=100000,
sid += 1
sec_ids.append(sid)
sections = [(txt, sec_ids[i], poss)
for i, (txt, _, poss) in enumerate(sections)]
sections = [(txt, sec_ids[i], poss) for i, (txt, _, poss) in enumerate(sections)]
for (img, rows), poss in tbls:
if not rows:
continue
sections.append((rows if isinstance(rows, str) else rows[0], -1,
[(p[0] + 1 - from_page, p[1], p[2], p[3], p[4]) for p in poss]))
sections.append((rows if isinstance(rows, str) else rows[0], -1, [(p[0] + 1 - from_page, p[1], p[2], p[3], p[4]) for p in poss]))
def tag(pn, left, right, top, bottom):
if pn + left + right + top + bottom == 0:
return ""
return "@@{}\t{:.1f}\t{:.1f}\t{:.1f}\t{:.1f}##" \
.format(pn, left, right, top, bottom)
return "@@{}\t{:.1f}\t{:.1f}\t{:.1f}\t{:.1f}##".format(pn, left, right, top, bottom)
chunks = []
last_sid = -2
tk_cnt = 0
for txt, sec_id, poss in sorted(sections, key=lambda x: (
x[-1][0][0], x[-1][0][3], x[-1][0][1])):
for txt, sec_id, poss in sorted(sections, key=lambda x: (x[-1][0][0], x[-1][0][3], x[-1][0][1])):
poss = "\t".join([tag(*pos) for pos in poss])
if tk_cnt < 32 or (tk_cnt < 1024 and (sec_id == last_sid or sec_id == -1)):
if chunks:
@ -330,14 +309,13 @@ def chunk(filename, binary=None, from_page=0, to_page=100000,
elif re.search(r"\.docx?$", filename, re.IGNORECASE):
docx_parser = Docx()
ti_list, tbls = docx_parser(filename, binary,
from_page=0, to_page=10000, callback=callback)
ti_list, tbls = docx_parser(filename, binary, from_page=0, to_page=10000, callback=callback)
tbls = vision_figure_parser_docx_wrapper(sections=ti_list, tbls=tbls, callback=callback, **kwargs)
res = tokenize_table(tbls, doc, eng)
for text, image in ti_list:
d = copy.deepcopy(doc)
if image:
d['image'] = image
d["image"] = image
d["doc_type_kwd"] = "image"
tokenize(d, text, eng)
res.append(d)
@ -353,9 +331,7 @@ def chunk(filename, binary=None, from_page=0, to_page=100000,
if __name__ == "__main__":
import sys
def dummy(prog=None, msg=""):
pass
chunk(sys.argv[1], callback=dummy)