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Add Q&A and Book, fix task running bugs (#50)
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@ -4,14 +4,8 @@ from nltk import word_tokenize
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from rag.nlp import stemmer, huqie
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def callback__(progress, msg, func):
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if not func :return
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func(progress, msg)
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BULLET_PATTERN = [[
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r"第[零一二三四五六七八九十百]+编",
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r"第[零一二三四五六七八九十百]+(编|部分)",
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r"第[零一二三四五六七八九十百]+章",
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r"第[零一二三四五六七八九十百]+节",
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r"第[零一二三四五六七八九十百]+条",
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@ -22,6 +16,8 @@ BULLET_PATTERN = [[
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r"[0-9]{,2}\.[0-9]{,2}\.[0-9]{,2}",
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r"[0-9]{,2}\.[0-9]{,2}\.[0-9]{,2}\.[0-9]{,2}",
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], [
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r"第[零一二三四五六七八九十百]+章",
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r"第[零一二三四五六七八九十百]+节",
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r"[零一二三四五六七八九十百]+[ 、]",
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r"[\((][零一二三四五六七八九十百]+[\))]",
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r"[\((][0-9]{,2}[\))]",
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@ -54,7 +50,7 @@ def bullets_category(sections):
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def is_english(texts):
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eng = 0
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for t in texts:
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if re.match(r"[a-zA-Z]", t.strip()):
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if re.match(r"[a-zA-Z]{2,}", t.strip()):
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eng += 1
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if eng / len(texts) > 0.8:
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return True
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@ -70,3 +66,26 @@ def tokenize(d, t, eng):
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d["content_sm_ltks"] = huqie.qieqie(d["content_ltks"])
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def remove_contents_table(sections, eng=False):
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i = 0
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while i < len(sections):
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def get(i):
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nonlocal sections
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return (sections[i] if type(sections[i]) == type("") else sections[i][0]).strip()
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if not re.match(r"(contents|目录|目次|table of contents|致谢|acknowledge)$", re.sub(r"( | |\u3000)+", "", get(i).split("@@")[0], re.IGNORECASE)):
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i += 1
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continue
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sections.pop(i)
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if i >= len(sections): break
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prefix = get(i)[:3] if not eng else " ".join(get(i).split(" ")[:2])
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while not prefix:
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sections.pop(i)
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if i >= len(sections): break
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prefix = get(i)[:3] if not eng else " ".join(get(i).split(" ")[:2])
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sections.pop(i)
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if i >= len(sections) or not prefix: break
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for j in range(i, min(i+128, len(sections))):
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if not re.match(prefix, get(j)):
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continue
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for _ in range(i, j):sections.pop(i)
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break
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