mirror of
https://github.com/infiniflow/ragflow.git
synced 2025-12-08 20:42:30 +08:00
Rework logging (#3358)
Unified all log files into one. ### What problem does this PR solve? Unified all log files into one. ### Type of change - [x] Refactoring
This commit is contained in:
Zhichang Yu
@ -19,13 +19,14 @@ from io import BytesIO
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import re
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import pdfplumber
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import logging
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from PIL import Image, ImageDraw
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from PIL import Image
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import numpy as np
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from timeit import default_timer as timer
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from pypdf import PdfReader as pdf2_read
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from api.settings import LIGHTEN
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from api.utils.file_utils import get_project_base_directory
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from api.utils.log_utils import logger
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from deepdoc.vision import OCR, Recognizer, LayoutRecognizer, TableStructureRecognizer
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from rag.nlp import rag_tokenizer
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from copy import deepcopy
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@ -49,15 +50,15 @@ class RAGFlowPdfParser:
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import torch
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if torch.cuda.is_available():
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self.updown_cnt_mdl.set_param({"device": "cuda"})
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except Exception as e:
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logging.error(str(e))
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except Exception:
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logger.exception("RAGFlowPdfParser __init__")
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try:
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model_dir = os.path.join(
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get_project_base_directory(),
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"rag/res/deepdoc")
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self.updown_cnt_mdl.load_model(os.path.join(
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model_dir, "updown_concat_xgb.model"))
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except Exception as e:
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except Exception:
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model_dir = snapshot_download(
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repo_id="InfiniFlow/text_concat_xgb_v1.0",
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local_dir=os.path.join(get_project_base_directory(), "rag/res/deepdoc"),
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@ -187,7 +188,7 @@ class RAGFlowPdfParser:
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return True
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def _table_transformer_job(self, ZM):
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logging.info("Table processing...")
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logger.info("Table processing...")
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imgs, pos = [], []
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tbcnt = [0]
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MARGIN = 10
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@ -425,12 +426,12 @@ class RAGFlowPdfParser:
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detach_feats = [b["x1"] < b_["x0"],
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b["x0"] > b_["x1"]]
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if (any(feats) and not any(concatting_feats)) or any(detach_feats):
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print(
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logger.info("{} {} {} {}".format(
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b["text"],
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b_["text"],
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any(feats),
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any(concatting_feats),
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any(detach_feats))
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))
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i += 1
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continue
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# merge up and down
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@ -726,14 +727,14 @@ class RAGFlowPdfParser:
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# continue
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if tv < fv and tk:
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tables[tk].insert(0, c)
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logging.debug(
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logger.debug(
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"TABLE:" +
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self.boxes[i]["text"] +
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"; Cap: " +
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tk)
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elif fk:
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figures[fk].insert(0, c)
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logging.debug(
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logger.debug(
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"FIGURE:" +
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self.boxes[i]["text"] +
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"; Cap: " +
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@ -760,7 +761,7 @@ class RAGFlowPdfParser:
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if ii is not None:
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b = louts[ii]
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else:
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logging.warn(
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logger.warn(
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f"Missing layout match: {pn + 1},%s" %
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(bxs[0].get(
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"layoutno", "")))
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@ -918,8 +919,8 @@ class RAGFlowPdfParser:
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if usefull(boxes[0]):
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dfs(boxes[0], 0)
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else:
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logging.debug("WASTE: " + boxes[0]["text"])
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except Exception as e:
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logger.debug("WASTE: " + boxes[0]["text"])
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except Exception:
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pass
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boxes.pop(0)
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mw = np.mean(widths)
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@ -927,7 +928,7 @@ class RAGFlowPdfParser:
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res.append(
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"\n".join([c["text"] + self._line_tag(c, ZM) for c in lines]))
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else:
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logging.debug("REMOVED: " +
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logger.debug("REMOVED: " +
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"<<".join([c["text"] for c in lines]))
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return "\n\n".join(res)
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@ -938,8 +939,8 @@ class RAGFlowPdfParser:
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pdf = pdfplumber.open(
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fnm) if not binary else pdfplumber.open(BytesIO(binary))
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return len(pdf.pages)
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except Exception as e:
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logging.error(str(e))
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except Exception:
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logger.exception("total_page_number")
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def __images__(self, fnm, zoomin=3, page_from=0,
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page_to=299, callback=None):
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@ -962,8 +963,8 @@ class RAGFlowPdfParser:
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self.page_chars = [[{**c, 'top': c['top'], 'bottom': c['bottom']} for c in page.dedupe_chars().chars if self._has_color(c)] for page in
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self.pdf.pages[page_from:page_to]]
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self.total_page = len(self.pdf.pages)
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except Exception as e:
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logging.error(str(e))
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except Exception:
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logger.exception("RAGFlowPdfParser __images__")
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self.outlines = []
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try:
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@ -979,11 +980,11 @@ class RAGFlowPdfParser:
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dfs(outlines, 0)
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except Exception as e:
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logging.warning(f"Outlines exception: {e}")
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logger.warning(f"Outlines exception: {e}")
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if not self.outlines:
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logging.warning(f"Miss outlines")
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logger.warning("Miss outlines")
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logging.info("Images converted.")
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logger.info("Images converted.")
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self.is_english = [re.search(r"[a-zA-Z0-9,/¸;:'\[\]\(\)!@#$%^&*\"?<>._-]{30,}", "".join(
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random.choices([c["text"] for c in self.page_chars[i]], k=min(100, len(self.page_chars[i]))))) for i in
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range(len(self.page_chars))]
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@ -1023,7 +1024,7 @@ class RAGFlowPdfParser:
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self.is_english = re.search(r"[\na-zA-Z0-9,/¸;:'\[\]\(\)!@#$%^&*\"?<>._-]{30,}",
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"".join([b["text"] for b in random.choices(bxes, k=min(30, len(bxes)))]))
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logging.info("Is it English:", self.is_english)
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logger.info("Is it English:", self.is_english)
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self.page_cum_height = np.cumsum(self.page_cum_height)
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assert len(self.page_cum_height) == len(self.page_images) + 1
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@ -1162,10 +1163,10 @@ class PlainParser(object):
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dfs(a, depth + 1)
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dfs(outlines, 0)
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except Exception as e:
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logging.warning(f"Outlines exception: {e}")
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except Exception:
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logger.exception("Outlines exception")
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if not self.outlines:
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logging.warning(f"Miss outlines")
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logger.warning("Miss outlines")
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return [(l, "") for l in lines], []
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@ -11,10 +11,15 @@
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# limitations under the License.
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#
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import re,json,os
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import re
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import json
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import os
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import pandas as pd
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from rag.nlp import rag_tokenizer
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from . import regions
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from api.utils.log_utils import logger
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current_file_path = os.path.dirname(os.path.abspath(__file__))
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GOODS = pd.read_csv(os.path.join(current_file_path, "res/corp_baike_len.csv"), sep="\t", header=0).fillna(0)
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GOODS["cid"] = GOODS["cid"].astype(str)
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@ -27,7 +32,7 @@ def baike(cid, default_v=0):
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global GOODS
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try:
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return GOODS.loc[str(cid), "len"]
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except Exception as e:
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except Exception:
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pass
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return default_v
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@ -65,7 +70,8 @@ def rmNoise(n):
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GOOD_CORP = set([corpNorm(rmNoise(c), False) for c in GOOD_CORP])
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for c,v in CORP_TAG.items():
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cc = corpNorm(rmNoise(c), False)
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if not cc: print (c)
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if not cc:
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logger.info(c)
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CORP_TAG = {corpNorm(rmNoise(c), False):v for c,v in CORP_TAG.items()}
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def is_good(nm):
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@ -11,13 +11,19 @@
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# limitations under the License.
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#
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import re, copy, time, datetime, demjson3, \
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traceback, signal
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import re
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import copy
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import time
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import datetime
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import demjson3
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import traceback
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import signal
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import numpy as np
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from deepdoc.parser.resume.entities import degrees, schools, corporations
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from rag.nlp import rag_tokenizer, surname
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from xpinyin import Pinyin
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from contextlib import contextmanager
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from api.utils.log_utils import logger
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class TimeoutException(Exception): pass
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@ -79,7 +85,7 @@ def forEdu(cv):
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y, m, d = getYMD(dt)
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st_dt.append(str(y))
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e["start_dt_kwd"] = str(y)
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except Exception as e:
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except Exception:
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pass
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r = schools.select(n.get("school_name", ""))
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@ -158,7 +164,7 @@ def forEdu(cv):
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y, m, d = getYMD(edu_end_dt)
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cv["work_exp_flt"] = min(int(str(datetime.date.today())[0:4]) - int(y), cv.get("work_exp_flt", 1000))
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except Exception as e:
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print("EXCEPTION: ", e, edu_end_dt, cv.get("work_exp_flt"))
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logger.exception("forEdu {} {} {}".format(e, edu_end_dt, cv.get("work_exp_flt")))
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if sch:
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cv["school_name_kwd"] = sch
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if (len(cv.get("degree_kwd", [])) >= 1 and "本科" in cv["degree_kwd"]) \
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@ -233,7 +239,7 @@ def forWork(cv):
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if type(n) == type(""):
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try:
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n = json_loads(n)
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except Exception as e:
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except Exception:
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continue
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if n.get("start_time") and (not work_st_tm or n["start_time"] < work_st_tm): work_st_tm = n["start_time"]
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@ -269,8 +275,8 @@ def forWork(cv):
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try:
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duas.append((datetime.datetime.strptime(ed, "%Y-%m-%d") - datetime.datetime.strptime(st, "%Y-%m-%d")).days)
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except Exception as e:
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print("kkkkkkkkkkkkkkkkkkkk", n.get("start_time"), n.get("end_time"))
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except Exception:
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logger.exception("forWork {} {}".format(n.get("start_time"), n.get("end_time")))
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if n.get("scale"):
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r = re.search(r"^([0-9]+)", str(n["scale"]))
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@ -327,7 +333,7 @@ def forWork(cv):
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y, m, d = getYMD(work_st_tm)
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cv["work_exp_flt"] = min(int(str(datetime.date.today())[0:4]) - int(y), cv.get("work_exp_flt", 1000))
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except Exception as e:
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print("EXCEPTION: ", e, work_st_tm, cv.get("work_exp_flt"))
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logger.exception("forWork {} {} {}".format(e, work_st_tm, cv.get("work_exp_flt")))
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cv["job_num_int"] = 0
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if duas:
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@ -457,8 +463,8 @@ def parse(cv):
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t = k[:-4]
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cv[f"{t}_kwd"] = nms
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cv[f"{t}_tks"] = rag_tokenizer.tokenize(" ".join(nms))
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except Exception as e:
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print("【EXCEPTION】:", str(traceback.format_exc()), cv[k])
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except Exception:
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logger.exception("parse {} {}".format(str(traceback.format_exc()), cv[k]))
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cv[k] = []
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# tokenize fields
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@ -524,7 +530,7 @@ def parse(cv):
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if not y: y = "2012"
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if not m: m = "01"
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if not d: d = "01"
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cv["updated_at_dt"] = f"%s-%02d-%02d 00:00:00" % (y, int(m), int(d))
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cv["updated_at_dt"] = "%s-%02d-%02d 00:00:00" % (y, int(m), int(d))
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# long text tokenize
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if cv.get("responsibilities"): cv["responsibilities_ltks"] = rag_tokenizer.tokenize(rmHtmlTag(cv["responsibilities"]))
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@ -556,10 +562,10 @@ def parse(cv):
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cv["work_exp_flt"] = (time.time() - int(int(cv["work_start_time"]) / 1000)) / 3600. / 24. / 365.
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elif re.match(r"[0-9]{4}[^0-9]", str(cv["work_start_time"])):
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y, m, d = getYMD(str(cv["work_start_time"]))
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cv["work_start_dt"] = f"%s-%02d-%02d 00:00:00" % (y, int(m), int(d))
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cv["work_start_dt"] = "%s-%02d-%02d 00:00:00" % (y, int(m), int(d))
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cv["work_exp_flt"] = int(str(datetime.date.today())[0:4]) - int(y)
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except Exception as e:
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print("【EXCEPTION】", e, "==>", cv.get("work_start_time"))
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logger.exception("parse {} ==> {}".format(e, cv.get("work_start_time")))
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if "work_exp_flt" not in cv and cv.get("work_experience", 0): cv["work_exp_flt"] = int(cv["work_experience"]) / 12.
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keys = list(cv.keys())
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@ -574,7 +580,7 @@ def parse(cv):
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cv["tob_resume_id"] = str(cv["tob_resume_id"])
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cv["id"] = cv["tob_resume_id"]
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print("CCCCCCCCCCCCCCC")
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logger.info("CCCCCCCCCCCCCCC")
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return dealWithInt64(cv)
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@ -589,4 +595,3 @@ def dealWithInt64(d):
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if isinstance(d, np.integer): d = int(d)
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return d
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@ -20,6 +20,7 @@ import cv2
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import numpy as np
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import math
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from PIL import Image
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from api.utils.log_utils import logger
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class DecodeImage(object):
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@ -402,7 +403,7 @@ class DetResizeForTest(object):
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return None, (None, None)
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img = cv2.resize(img, (int(resize_w), int(resize_h)))
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except BaseException:
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print(img.shape, resize_w, resize_h)
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logger.exception("{} {} {}".format(img.shape, resize_w, resize_h))
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sys.exit(0)
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ratio_h = resize_h / float(h)
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ratio_w = resize_w / float(w)
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@ -452,7 +453,6 @@ class E2EResizeForTest(object):
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return data
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def resize_image_for_totaltext(self, im, max_side_len=512):
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h, w, _ = im.shape
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resize_w = w
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resize_h = h
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@ -19,6 +19,7 @@ from huggingface_hub import snapshot_download
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from api.utils.file_utils import get_project_base_directory
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from .operators import *
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from api.utils.log_utils import logger
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class Recognizer(object):
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@ -439,7 +440,7 @@ class Recognizer(object):
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end_index = min((i + 1) * batch_size, len(imgs))
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batch_image_list = imgs[start_index:end_index]
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inputs = self.preprocess(batch_image_list)
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print("preprocess")
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logger.info("preprocess")
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for ins in inputs:
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bb = self.postprocess(self.ort_sess.run(None, {k:v for k,v in ins.items() if k in self.input_names})[0], ins, thr)
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res.append(bb)
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@ -14,6 +14,7 @@
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import os
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import PIL
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from PIL import ImageDraw
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from api.utils.log_utils import logger
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def save_results(image_list, results, labels, output_dir='output/', threshold=0.5):
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@ -24,7 +25,7 @@ def save_results(image_list, results, labels, output_dir='output/', threshold=0.
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out_path = os.path.join(output_dir, f"{idx}.jpg")
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im.save(out_path, quality=95)
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print("save result to: " + out_path)
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logger.info("save result to: " + out_path)
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def draw_box(im, result, lables, threshold=0.5):
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@ -10,7 +10,10 @@
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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 os, sys
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import os
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import sys
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from api.utils.log_utils import logger
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sys.path.insert(
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0,
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os.path.abspath(
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@ -56,7 +59,7 @@ def main(args):
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} for t in lyt]
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img = draw_box(images[i], lyt, labels, float(args.threshold))
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img.save(outputs[i], quality=95)
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print("save result to: " + outputs[i])
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logger.info("save result to: " + outputs[i])
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def get_table_html(img, tb_cpns, ocr):
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