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3894de895b
### What problem does this PR solve? Add license statement. ### Type of change - [x] Refactoring Signed-off-by: Jin Hai <haijin.chn@gmail.com>
177 lines
6.9 KiB
Python
177 lines
6.9 KiB
Python
#
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# Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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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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#
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import logging
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import base64
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import datetime
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import json
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import re
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import pandas as pd
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import requests
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from api.db.services.knowledgebase_service import KnowledgebaseService
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from rag.nlp import rag_tokenizer
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from deepdoc.parser.resume import refactor
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from deepdoc.parser.resume import step_one, step_two
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from rag.utils import rmSpace
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forbidden_select_fields4resume = [
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"name_pinyin_kwd", "edu_first_fea_kwd", "degree_kwd", "sch_rank_kwd", "edu_fea_kwd"
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]
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def remote_call(filename, binary):
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q = {
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"header": {
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"uid": 1,
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"user": "kevinhu",
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"log_id": filename
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},
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"request": {
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"p": {
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"request_id": "1",
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"encrypt_type": "base64",
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"filename": filename,
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"langtype": '',
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"fileori": base64.b64encode(binary).decode('utf-8')
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},
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"c": "resume_parse_module",
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"m": "resume_parse"
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}
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}
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for _ in range(3):
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try:
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resume = requests.post(
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"http://127.0.0.1:61670/tog",
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data=json.dumps(q))
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resume = resume.json()["response"]["results"]
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resume = refactor(resume)
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for k in ["education", "work", "project",
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"training", "skill", "certificate", "language"]:
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if not resume.get(k) and k in resume:
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del resume[k]
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resume = step_one.refactor(pd.DataFrame([{"resume_content": json.dumps(resume), "tob_resume_id": "x",
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"updated_at": datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")}]))
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resume = step_two.parse(resume)
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return resume
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except Exception:
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logging.exception("Resume parser has not been supported yet!")
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return {}
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def chunk(filename, binary=None, callback=None, **kwargs):
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"""
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The supported file formats are pdf, docx and txt.
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To maximize the effectiveness, parse the resume correctly, please concat us: https://github.com/infiniflow/ragflow
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"""
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if not re.search(r"\.(pdf|doc|docx|txt)$", filename, flags=re.IGNORECASE):
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raise NotImplementedError("file type not supported yet(pdf supported)")
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if not binary:
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with open(filename, "rb") as f:
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binary = f.read()
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callback(0.2, "Resume parsing is going on...")
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resume = remote_call(filename, binary)
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if len(resume.keys()) < 7:
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callback(-1, "Resume is not successfully parsed.")
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raise Exception("Resume parser remote call fail!")
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callback(0.6, "Done parsing. Chunking...")
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logging.debug("chunking resume: " + json.dumps(resume, ensure_ascii=False, indent=2))
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field_map = {
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"name_kwd": "姓名/名字",
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"name_pinyin_kwd": "姓名拼音/名字拼音",
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"gender_kwd": "性别（男，女）",
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"age_int": "年龄/岁/年纪",
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"phone_kwd": "电话/手机/微信",
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"email_tks": "email/e-mail/邮箱",
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"position_name_tks": "职位/职能/岗位/职责",
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"expect_city_names_tks": "期望城市",
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"work_exp_flt": "工作年限/工作年份/N年经验/毕业了多少年",
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"corporation_name_tks": "最近就职(上班)的公司/上一家公司",
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"first_school_name_tks": "第一学历毕业学校",
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"first_degree_kwd": "第一学历（高中，职高，硕士，本科，博士，初中，中技，中专，专科，专升本，MPA，MBA，EMBA）",
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"highest_degree_kwd": "最高学历（高中，职高，硕士，本科，博士，初中，中技，中专，专科，专升本，MPA，MBA，EMBA）",
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"first_major_tks": "第一学历专业",
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"edu_first_fea_kwd": "第一学历标签（211，留学，双一流，985，海外知名，重点大学，中专，专升本，专科，本科，大专）",
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"degree_kwd": "过往学历（高中，职高，硕士，本科，博士，初中，中技，中专，专科，专升本，MPA，MBA，EMBA）",
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"major_tks": "学过的专业/过往专业",
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"school_name_tks": "学校/毕业院校",
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"sch_rank_kwd": "学校标签（顶尖学校，精英学校，优质学校，一般学校）",
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"edu_fea_kwd": "教育标签（211，留学，双一流，985，海外知名，重点大学，中专，专升本，专科，本科，大专）",
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"corp_nm_tks": "就职过的公司/之前的公司/上过班的公司",
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"edu_end_int": "毕业年份",
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"industry_name_tks": "所在行业",
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"birth_dt": "生日/出生年份",
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"expect_position_name_tks": "期望职位/期望职能/期望岗位",
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}
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titles = []
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for n in ["name_kwd", "gender_kwd", "position_name_tks", "age_int"]:
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v = resume.get(n, "")
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if isinstance(v, list):
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v = v[0]
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if n.find("tks") > 0:
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v = rmSpace(v)
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titles.append(str(v))
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doc = {
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"docnm_kwd": filename,
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"title_tks": rag_tokenizer.tokenize("-".join(titles) + "-简历")
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}
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doc["title_sm_tks"] = rag_tokenizer.fine_grained_tokenize(doc["title_tks"])
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pairs = []
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for n, m in field_map.items():
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if not resume.get(n):
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continue
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v = resume[n]
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if isinstance(v, list):
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v = " ".join(v)
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if n.find("tks") > 0:
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v = rmSpace(v)
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pairs.append((m, str(v)))
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doc["content_with_weight"] = "\n".join(
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["{}: {}".format(re.sub(r"（[^（）]+）", "", k), v) for k, v in pairs])
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doc["content_ltks"] = rag_tokenizer.tokenize(doc["content_with_weight"])
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doc["content_sm_ltks"] = rag_tokenizer.fine_grained_tokenize(doc["content_ltks"])
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for n, _ in field_map.items():
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if n not in resume:
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continue
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if isinstance(resume[n], list) and (
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len(resume[n]) == 1 or n not in forbidden_select_fields4resume):
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resume[n] = resume[n][0]
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if n.find("_tks") > 0:
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resume[n] = rag_tokenizer.fine_grained_tokenize(resume[n])
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doc[n] = resume[n]
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logging.debug("chunked resume to " + str(doc))
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KnowledgebaseService.update_parser_config(
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kwargs["kb_id"], {"field_map": field_map})
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return [doc]
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if __name__ == "__main__":
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import sys
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def dummy(a, b):
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pass
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chunk(sys.argv[1], callback=dummy)
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