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- import random
- import re
- from io import BytesIO
- from nltk import word_tokenize
- from openpyxl import load_workbook
- from rag.parser import is_english, random_choices
- from rag.nlp import huqie, stemmer
-
-
- class Excel(object):
- def __call__(self, fnm, binary=None, callback=None):
- if not binary:
- wb = load_workbook(fnm)
- else:
- wb = load_workbook(BytesIO(binary))
- total = 0
- for sheetname in wb.sheetnames:
- total += len(list(wb[sheetname].rows))
-
- res, fails = [], []
- for sheetname in wb.sheetnames:
- ws = wb[sheetname]
- rows = list(ws.rows)
- for i, r in enumerate(rows):
- q, a = "", ""
- for cell in r:
- if not cell.value: continue
- if not q: q = str(cell.value)
- elif not a: a = str(cell.value)
- else: break
- if q and a: res.append((q, a))
- else: fails.append(str(i+1))
- if len(res) % 999 == 0:
- callback(len(res)*0.6/total, ("Extract Q&A: {}".format(len(res)) + (f"{len(fails)} failure, line: %s..."%(",".join(fails[:3])) if fails else "")))
-
- callback(0.6, ("Extract Q&A: {}. ".format(len(res)) + (
- f"{len(fails)} failure, line: %s..." % (",".join(fails[:3])) if fails else "")))
- self.is_english = is_english([rmPrefix(q) for q, _ in random_choices(res, k=30) if len(q)>1])
- return res
-
-
- def rmPrefix(txt):
- return re.sub(r"^(问题|答案|回答|user|assistant|Q|A|Question|Answer|问|答)[\t:: ]+", "", txt.strip(), flags=re.IGNORECASE)
-
-
- def beAdoc(d, q, a, eng):
- qprefix = "Question: " if eng else "问题:"
- aprefix = "Answer: " if eng else "回答:"
- d["content_with_weight"] = "\t".join([qprefix+rmPrefix(q), aprefix+rmPrefix(a)])
- if eng:
- d["content_ltks"] = " ".join([stemmer.stem(w) for w in word_tokenize(q)])
- else:
- d["content_ltks"] = huqie.qie(q)
- d["content_sm_ltks"] = huqie.qieqie(d["content_ltks"])
- return d
-
-
- def chunk(filename, binary=None, callback=None, **kwargs):
-
- res = []
- if re.search(r"\.xlsx?$", filename, re.IGNORECASE):
- callback(0.1, "Start to parse.")
- excel_parser = Excel()
- for q,a in excel_parser(filename, binary, callback):
- res.append(beAdoc({}, q, a, excel_parser.is_english))
- return res
- elif re.search(r"\.(txt|csv)$", filename, re.IGNORECASE):
- callback(0.1, "Start to parse.")
- txt = ""
- if binary:
- txt = binary.decode("utf-8")
- else:
- with open(filename, "r") as f:
- while True:
- l = f.readline()
- if not l: break
- txt += l
- lines = txt.split("\n")
- eng = is_english([rmPrefix(l) for l in lines[:100]])
- fails = []
- for i, line in enumerate(lines):
- arr = [l for l in line.split("\t") if len(l) > 1]
- if len(arr) != 2:
- fails.append(str(i))
- continue
- res.append(beAdoc({}, arr[0], arr[1], eng))
- if len(res) % 999 == 0:
- callback(len(res) * 0.6 / len(lines), ("Extract Q&A: {}".format(len(res)) + (
- f"{len(fails)} failure, line: %s..." % (",".join(fails[:3])) if fails else "")))
-
- callback(0.6, ("Extract Q&A: {}".format(len(res)) + (
- f"{len(fails)} failure, line: %s..." % (",".join(fails[:3])) if fails else "")))
-
- 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)
-
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