ragflow/rag/app/one.py

#  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 rag.app import laws
from rag.nlp import huqie, is_english, tokenize, naive_merge, tokenize_table, add_positions
from deepdoc.parser import PdfParser, ExcelParser
from rag.settings import cron_logger


class Pdf(PdfParser):
    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(msg="OCR finished")

        from timeit import default_timer as timer
        start = timer()
        self._layouts_rec(zoomin)
        callback(0.63, "Layout analysis finished.")
        print("paddle layouts:", timer() - start)
        self._table_transformer_job(zoomin)
        callback(0.65, "Table analysis finished.")
        self._text_merge()
        callback(0.67, "Text merging finished")
        tbls = self._extract_table_figure(True, zoomin, True, True)
        self._concat_downward()

        sections = [(b["text"], self.get_position(b, zoomin)) for i, b in enumerate(self.boxes)]
        for (img, rows), poss in tbls:
            sections.append((rows if isinstance(rows, str) else rows[0],
                             [(p[0] + 1 - from_page, p[1], p[2], p[3], p[4]) for p in poss]))
        return [txt for txt, _ in sorted(sections, key=lambda x: (x[-1][0][0], x[-1][0][3], x[-1][0][1]))]


def chunk(filename, binary=None, from_page=0, to_page=100000, lang="Chinese", callback=None, **kwargs):
    """
        Supported file formats are docx, pdf, excel, txt.
        One file forms a chunk which maintains original text order.
    """

    eng = lang.lower() == "english"#is_english(cks)

    sections = []
    if re.search(r"\.docx?$", filename, re.IGNORECASE):
        callback(0.1, "Start to parse.")
        for txt in laws.Docx()(filename, binary):
            sections.append(txt)
        callback(0.8, "Finish parsing.")
    elif re.search(r"\.pdf$", filename, re.IGNORECASE):
        pdf_parser = Pdf()
        sections = pdf_parser(filename if not binary else binary, to_page=to_page, callback=callback)
    elif re.search(r"\.xlsx?$", filename, re.IGNORECASE):
        callback(0.1, "Start to parse.")
        excel_parser = ExcelParser()
        sections = [excel_parser.html(binary)]
    elif re.search(r"\.txt$", 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
        sections = txt.split("\n")
        sections = [(l, "") for l in sections if l]
        callback(0.8, "Finish parsing.")
    else:
        raise NotImplementedError("file type not supported yet(docx, pdf, txt supported)")

    doc = {
        "docnm_kwd": filename,
        "title_tks": huqie.qie(re.sub(r"\.[a-zA-Z]+$", "", filename))
    }
    doc["title_sm_tks"] = huqie.qieqie(doc["title_tks"])
    tokenize(doc, "\n".join(sections), eng)
    return [doc]


if __name__ == "__main__":
    import sys


    def dummy(prog=None, msg=""):
        pass


    chunk(sys.argv[1], from_page=0, to_page=10, callback=dummy)