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|
| | from docx import Document |
| | import re |
| | import pandas as pd |
| | from collections import Counter |
| | from rag.nlp import rag_tokenizer |
| | from io import BytesIO |
| |
|
| |
|
| | class RAGFlowDocxParser: |
| |
|
| | def __extract_table_content(self, tb): |
| | df = [] |
| | for row in tb.rows: |
| | df.append([c.text for c in row.cells]) |
| | return self.__compose_table_content(pd.DataFrame(df)) |
| |
|
| | def __compose_table_content(self, df): |
| |
|
| | def blockType(b): |
| | patt = [ |
| | ("^(20|19)[0-9]{2}[年/-][0-9]{1,2}[月/-][0-9]{1,2}日*$", "Dt"), |
| | (r"^(20|19)[0-9]{2}年$", "Dt"), |
| | (r"^(20|19)[0-9]{2}[年/-][0-9]{1,2}月*$", "Dt"), |
| | ("^[0-9]{1,2}[月/-][0-9]{1,2}日*$", "Dt"), |
| | (r"^第*[一二三四1-4]季度$", "Dt"), |
| | (r"^(20|19)[0-9]{2}年*[一二三四1-4]季度$", "Dt"), |
| | (r"^(20|19)[0-9]{2}[ABCDE]$", "DT"), |
| | ("^[0-9.,+%/ -]+$", "Nu"), |
| | (r"^[0-9A-Z/\._~-]+$", "Ca"), |
| | (r"^[A-Z]*[a-z' -]+$", "En"), |
| | (r"^[0-9.,+-]+[0-9A-Za-z/$¥%<>()()' -]+$", "NE"), |
| | (r"^.{1}$", "Sg") |
| | ] |
| | for p, n in patt: |
| | if re.search(p, b): |
| | return n |
| | tks = [t for t in rag_tokenizer.tokenize(b).split() if len(t) > 1] |
| | if len(tks) > 3: |
| | if len(tks) < 12: |
| | return "Tx" |
| | else: |
| | return "Lx" |
| |
|
| | if len(tks) == 1 and rag_tokenizer.tag(tks[0]) == "nr": |
| | return "Nr" |
| |
|
| | return "Ot" |
| |
|
| | if len(df) < 2: |
| | return [] |
| | max_type = Counter([blockType(str(df.iloc[i, j])) for i in range( |
| | 1, len(df)) for j in range(len(df.iloc[i, :]))]) |
| | max_type = max(max_type.items(), key=lambda x: x[1])[0] |
| |
|
| | colnm = len(df.iloc[0, :]) |
| | hdrows = [0] |
| | if max_type == "Nu": |
| | for r in range(1, len(df)): |
| | tys = Counter([blockType(str(df.iloc[r, j])) |
| | for j in range(len(df.iloc[r, :]))]) |
| | tys = max(tys.items(), key=lambda x: x[1])[0] |
| | if tys != max_type: |
| | hdrows.append(r) |
| |
|
| | lines = [] |
| | for i in range(1, len(df)): |
| | if i in hdrows: |
| | continue |
| | hr = [r - i for r in hdrows] |
| | hr = [r for r in hr if r < 0] |
| | t = len(hr) - 1 |
| | while t > 0: |
| | if hr[t] - hr[t - 1] > 1: |
| | hr = hr[t:] |
| | break |
| | t -= 1 |
| | headers = [] |
| | for j in range(len(df.iloc[i, :])): |
| | t = [] |
| | for h in hr: |
| | x = str(df.iloc[i + h, j]).strip() |
| | if x in t: |
| | continue |
| | t.append(x) |
| | t = ",".join(t) |
| | if t: |
| | t += ": " |
| | headers.append(t) |
| | cells = [] |
| | for j in range(len(df.iloc[i, :])): |
| | if not str(df.iloc[i, j]): |
| | continue |
| | cells.append(headers[j] + str(df.iloc[i, j])) |
| | lines.append(";".join(cells)) |
| |
|
| | if colnm > 3: |
| | return lines |
| | return ["\n".join(lines)] |
| |
|
| | def __call__(self, fnm, from_page=0, to_page=100000000): |
| | self.doc = Document(fnm) if isinstance( |
| | fnm, str) else Document(BytesIO(fnm)) |
| | pn = 0 |
| | secs = [] |
| | for p in self.doc.paragraphs: |
| | if pn > to_page: |
| | break |
| |
|
| | runs_within_single_paragraph = [] |
| | for run in p.runs: |
| | if pn > to_page: |
| | break |
| | if from_page <= pn < to_page and p.text.strip(): |
| | runs_within_single_paragraph.append(run.text) |
| |
|
| | |
| | if 'lastRenderedPageBreak' in run._element.xml: |
| | pn += 1 |
| |
|
| | secs.append(("".join(runs_within_single_paragraph), p.style.name if hasattr(p.style, 'name') else '')) |
| |
|
| | tbls = [self.__extract_table_content(tb) for tb in self.doc.tables] |
| | return secs, tbls |
| |
|