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rename get_txt to get_text (#2649)
### What problem does this PR solve? ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue)
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@ -14,7 +14,7 @@
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from rag.nlp import find_codec
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from rag.nlp import find_codec
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def get_txt(fnm: str, binary=None) -> str:
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def get_text(fnm: str, binary=None) -> str:
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txt = ""
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txt = ""
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if binary:
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if binary:
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encoding = find_codec(binary)
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encoding = find_codec(binary)
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@ -10,7 +10,6 @@
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# See the License for the specific language governing permissions and
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# limitations under the License.
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#
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#
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import copy
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from tika import parser
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from tika import parser
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import re
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import re
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from io import BytesIO
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from io import BytesIO
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@ -17,7 +17,7 @@ from io import BytesIO
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from docx import Document
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from docx import Document
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from api.db import ParserType
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from api.db import ParserType
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from deepdoc.parser.utils import get_txt
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from deepdoc.parser.utils import get_text
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from rag.nlp import bullets_category, is_english, tokenize, remove_contents_table, hierarchical_merge, \
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from rag.nlp import bullets_category, is_english, tokenize, remove_contents_table, hierarchical_merge, \
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make_colon_as_title, add_positions, tokenize_chunks, find_codec, docx_question_level
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make_colon_as_title, add_positions, tokenize_chunks, find_codec, docx_question_level
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from rag.nlp import rag_tokenizer
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from rag.nlp import rag_tokenizer
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@ -166,7 +166,7 @@ def chunk(filename, binary=None, from_page=0, to_page=100000,
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elif re.search(r"\.txt$", filename, re.IGNORECASE):
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elif re.search(r"\.txt$", filename, re.IGNORECASE):
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callback(0.1, "Start to parse.")
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callback(0.1, "Start to parse.")
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txt = get_txt(filename, binary)
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txt = get_text(filename, binary)
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sections = txt.split("\n")
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sections = txt.split("\n")
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sections = [l for l in sections if l]
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sections = [l for l in sections if l]
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callback(0.8, "Finish parsing.")
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callback(0.8, "Finish parsing.")
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@ -14,9 +14,9 @@ from tika import parser
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from io import BytesIO
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from io import BytesIO
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import re
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import re
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from deepdoc.parser.utils import get_txt
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from deepdoc.parser.utils import get_text
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from rag.app import laws
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from rag.app import laws
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from rag.nlp import rag_tokenizer, tokenize, find_codec
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from rag.nlp import rag_tokenizer, tokenize
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from deepdoc.parser import PdfParser, ExcelParser, PlainParser, HtmlParser
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from deepdoc.parser import PdfParser, ExcelParser, PlainParser, HtmlParser
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@ -84,7 +84,7 @@ def chunk(filename, binary=None, from_page=0, to_page=100000,
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elif re.search(r"\.(txt|md|markdown)$", filename, re.IGNORECASE):
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elif re.search(r"\.(txt|md|markdown)$", filename, re.IGNORECASE):
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callback(0.1, "Start to parse.")
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callback(0.1, "Start to parse.")
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txt = get_txt(filename, binary)
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txt = get_text(filename, binary)
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sections = txt.split("\n")
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sections = txt.split("\n")
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sections = [s for s in sections if s]
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sections = [s for s in sections if s]
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callback(0.8, "Finish parsing.")
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callback(0.8, "Finish parsing.")
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@ -17,14 +17,16 @@ from timeit import default_timer as timer
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from nltk import word_tokenize
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from nltk import word_tokenize
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from openpyxl import load_workbook
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from openpyxl import load_workbook
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from deepdoc.parser.utils import get_txt
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from deepdoc.parser.utils import get_text
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from rag.nlp import is_english, random_choices, find_codec, qbullets_category, add_positions, has_qbullet, docx_question_level
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from rag.nlp import is_english, random_choices, qbullets_category, add_positions, has_qbullet, docx_question_level
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from rag.nlp import rag_tokenizer, tokenize_table, concat_img
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from rag.nlp import rag_tokenizer, tokenize_table, concat_img
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from rag.settings import cron_logger
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from rag.settings import cron_logger
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from deepdoc.parser import PdfParser, ExcelParser, DocxParser
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from deepdoc.parser import PdfParser, ExcelParser, DocxParser
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from docx import Document
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from docx import Document
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from PIL import Image
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from PIL import Image
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from markdown import markdown
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from markdown import markdown
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class Excel(ExcelParser):
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class Excel(ExcelParser):
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def __call__(self, fnm, binary=None, callback=None):
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def __call__(self, fnm, binary=None, callback=None):
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if not binary:
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if not binary:
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@ -307,7 +309,7 @@ def chunk(filename, binary=None, lang="Chinese", callback=None, **kwargs):
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return res
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return res
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elif re.search(r"\.(txt|csv)$", filename, re.IGNORECASE):
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elif re.search(r"\.(txt|csv)$", filename, re.IGNORECASE):
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callback(0.1, "Start to parse.")
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callback(0.1, "Start to parse.")
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txt = get_txt(filename, binary)
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txt = get_text(filename, binary)
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lines = txt.split("\n")
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lines = txt.split("\n")
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comma, tab = 0, 0
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comma, tab = 0, 0
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for l in lines:
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for l in lines:
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@ -350,7 +352,7 @@ def chunk(filename, binary=None, lang="Chinese", callback=None, **kwargs):
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return res
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return res
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elif re.search(r"\.(md|markdown)$", filename, re.IGNORECASE):
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elif re.search(r"\.(md|markdown)$", filename, re.IGNORECASE):
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callback(0.1, "Start to parse.")
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callback(0.1, "Start to parse.")
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txt = get_txt(filename, binary)
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txt = get_text(filename, binary)
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lines = txt.split("\n")
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lines = txt.split("\n")
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last_question, last_answer = "", ""
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last_question, last_answer = "", ""
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question_stack, level_stack = [], []
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question_stack, level_stack = [], []
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@ -21,7 +21,7 @@ from dateutil.parser import parse as datetime_parse
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from api.db.services.knowledgebase_service import KnowledgebaseService
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from api.db.services.knowledgebase_service import KnowledgebaseService
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from deepdoc.parser.utils import get_text
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from deepdoc.parser.utils import get_text
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from rag.nlp import rag_tokenizer, is_english, tokenize, find_codec
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from rag.nlp import rag_tokenizer, tokenize
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from deepdoc.parser import ExcelParser
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from deepdoc.parser import ExcelParser
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