refactor: no need to inherit in python3 clean the code (#5659)

### What problem does this PR solve?

As title

### Type of change


- [x] Refactoring

Signed-off-by: yihong0618 <zouzou0208@gmail.com>

api/db/services/llm_service.py

         return list(objs)
 
 
-class LLMBundle(object):
+class LLMBundle:
     def __init__(self, tenant_id, llm_type, llm_name=None, lang="Chinese"):
         self.tenant_id = tenant_id
         self.llm_type = llm_type

deepdoc/parser/pdf_parser.py

         return poss
 
 
-class PlainParser(object):
+class PlainParser:
     def __call__(self, filename, from_page=0, to_page=100000, **kwargs):
         self.outlines = []
         lines = []

deepdoc/parser/ppt_parser.py

 from pptx import Presentation
 
 
-class RAGFlowPptParser(object):
+class RAGFlowPptParser:
     def __init__(self):
         super().__init__()
 

deepdoc/vision/ocr.py

     return loaded_model
 
 
-class TextRecognizer(object):
+class TextRecognizer:
     def __init__(self, model_dir):
         self.rec_image_shape = [int(v) for v in "3, 48, 320".split(",")]
         self.rec_batch_num = 16
         return rec_res, time.time() - st
 
 
-class TextDetector(object):
+class TextDetector:
     def __init__(self, model_dir):
         pre_process_list = [{
             'DetResizeForTest': {
         return dt_boxes, time.time() - st
 
 
-class OCR(object):
+class OCR:
     def __init__(self, model_dir=None):
         """
         If you have trouble downloading HuggingFace models, -_^ this might help!!

deepdoc/vision/operators.py

 from PIL import Image
 
 
-class DecodeImage(object):
+class DecodeImage:
     """ decode image """
 
     def __init__(self,
         return data
 
 
-class StandardizeImage(object):
+class StandardizeImag:
     """normalize image
     Args:
         mean (list): im - mean
         return im, im_info
 
 
-class NormalizeImage(object):
+class NormalizeImage:
     """ normalize image such as subtract mean, divide std
     """
 
         return data
 
 
-class ToCHWImage(object):
+class ToCHWImage:
     """ convert hwc image to chw image
     """
 
         return data
 
 
-class KeepKeys(object):
+class KeepKeys:
     def __init__(self, keep_keys, **kwargs):
         self.keep_keys = keep_keys
 
         return data_list
 
 
-class Pad(object):
+class Pad:
     def __init__(self, size=None, size_div=32, **kwargs):
         if size is not None and not isinstance(size, (int, list, tuple)):
             raise TypeError("Type of target_size is invalid. Now is {}".format(
         return data
 
 
-class LinearResize(object):
+class LinearResize:
     """resize image by target_size and max_size
     Args:
         target_size (int): the target size of image
         return im_scale_y, im_scale_x
 
 
-class Resize(object):
+class Resize:
     def __init__(self, size=(640, 640), **kwargs):
         self.size = size
 
         return data
 
 
-class DetResizeForTest(object):
+class DetResizeForTest:
     def __init__(self, **kwargs):
         super(DetResizeForTest, self).__init__()
         self.resize_type = 0
         return img, [ratio_h, ratio_w]
 
 
-class E2EResizeForTest(object):
+class E2EResizeForTest:
     def __init__(self, **kwargs):
         super(E2EResizeForTest, self).__init__()
         self.max_side_len = kwargs['max_side_len']
         return im, (ratio_h, ratio_w)
 
 
-class KieResize(object):
+class KieResize:
     def __init__(self, **kwargs):
         super(KieResize, self).__init__()
         self.max_side, self.min_side = kwargs['img_scale'][0], kwargs[
         return points
 
 
-class SRResize(object):
+class SRResize:
     def __init__(self,
                  imgH=32,
                  imgW=128,
         return data
 
 
-class ResizeNormalize(object):
+class ResizeNormalize:
     def __init__(self, size, interpolation=Image.BICUBIC):
         self.size = size
         self.interpolation = interpolation
         return img_numpy
 
 
-class GrayImageChannelFormat(object):
+class GrayImageChannelFormat:
     """
     format gray scale image's channel: (3,h,w) -> (1,h,w)
     Args:
         return data
 
 
-class Permute(object):
+class Permute:
     """permute image
     Args:
         to_bgr (bool): whether convert RGB to BGR
         return im, im_info
 
 
-class PadStride(object):
+class PadStride:
     """ padding image for model with FPN, instead PadBatch(pad_to_stride) in original config
     Args:
         stride (bool): model with FPN need image shape % stride == 0

deepdoc/vision/postprocess.py

     return module_class(**config)
 
 
-class DBPostProcess(object):
+class DBPostProcess:
     """
     The post process for Differentiable Binarization (DB).
     """
         return boxes_batch
 
 
-class BaseRecLabelDecode(object):
+class BaseRecLabelDecode:
     """ Convert between text-label and text-index """
 
     def __init__(self, character_dict_path=None, use_space_char=False):

deepdoc/vision/recognizer.py

 from . import operators
 from .ocr import load_model
 
-class Recognizer(object):
+class Recognizer:
     def __init__(self, label_list, task_name, model_dir=None):
         """
         If you have trouble downloading HuggingFace models, -_^ this might help!!

rag/utils/azure_sas_conn.py

 
 
 @singleton
-class RAGFlowAzureSasBlob(object):
+class RAGFlowAzureSasBlob:
     def __init__(self):
         self.conn = None
         self.container_url = os.getenv('CONTAINER_URL', settings.AZURE["container_url"])

rag/utils/azure_spn_conn.py

 
 
 @singleton
-class RAGFlowAzureSpnBlob(object):
+class RAGFlowAzureSpnBlob:
     def __init__(self):
         self.conn = None
         self.account_url = os.getenv('ACCOUNT_URL', settings.AZURE["account_url"])

rag/utils/minio_conn.py

 
 
 @singleton
-class RAGFlowMinio(object):
+class RAGFlowMinio:
     def __init__(self):
         self.conn = None
         self.__open__()

rag/utils/oss_conn.py

 
 
 @singleton
-class RAGFlowOSS(object):
+class RAGFlowOSS:
     def __init__(self):
         self.conn = None
         self.oss_config = settings.OSS

rag/utils/s3_conn.py

 from rag import settings
 
 @singleton
-class RAGFlowS3(object):
+class RAGFlowS3:
     def __init__(self):
         self.conn = None
         self.s3_config = settings.S3

sdk/python/ragflow_sdk/modules/base.py

 #  limitations under the License.
 #
 
-class Base(object):
+class Base:
     def __init__(self, rag, res_dict):
         self.rag = rag
         for k, v in res_dict.items():