Field name "json" shadows a BaseModel attribute; use a different field name with "alias='json'"

Hello here , I have a python code using step functions sdk that was created a while ago using version 2.3.0 , suddenly without making any changes to the used code itself but maybe because i have added other dependencies to the project that uses pydantic classes ( though it wasn't added to the code that uses sfn sdk but rather same poetry environment ) I started receiving this weird error `NameError: Field name "json" shadows a BaseModel attribute; use a different field name with "alias='json'".

The error already happens with the imports
`

### Reproduction Steps

```
import json
from typing import Union, List, Tuple, Any, Iterable

from stepfunctions.workflow import Workflow
from stepfunctions.steps import Chain
from stepfunctions.steps.states import State

def generate_asl_json_file_for_workflow(
workflow: Workflow, output_file_path: str
) -> str:
workflow_json = json.loads(workflow.definition.to_json())

# Serializing json
pretty_workflow_json = json.dumps(workflow_json, indent=4)

# Writing to sample.json
with open(f"{output_file_path}.asl.json", "w") as outfile:
outfile.write(pretty_workflow_json)

return pretty_workflow_json
```

### What did you expect to happen?

Creating and generating step functions workflows after creating it using sfn python sdk

### What actually happened?

What happens is that i receive this log error :

```
Traceback (most recent call last) ──────────────────────╮
│ /Users/zied/PycharmProjects/ada-datasets-creation-service/ada_datasets_pipel │
│ ine/src/step_functions_scripts/main.py:2 in │
│ │
│ 1 from ada_datasets_pipeline.src.step_functions_scripts.parameters import │
│ ❱ 2 from ada_datasets_pipeline.src.step_functions_scripts.src.create_ada_da │
│ 3 │ generate_ada_pipeline_state_machine, │
│ 4 ) │
│ 5 │
│ │
│ /Users/zied/PycharmProjects/ada-datasets-creation-service/ada_datasets_pipel │
│ ine/src/step_functions_scripts/src/create_ada_dataset.py:1 in │
│ │
│ ❱ 1 from ada_datasets_pipeline.src.step_functions_scripts.src.utils import │
│ 2 │ states_format, │
│ 3 │ generate_asl_json_file_for_workflow, │
│ 4 │ chain_events_list, │
│ │
│ /Users/zied/PycharmProjects/ada-datasets-creation-service/ada_datasets_pipel │
│ ine/src/step_functions_scripts/src/utils.py:4 in │
│ │
│ 1 import json │
│ 2 from typing import Union, List, Tuple, Any, Iterable │
│ 3 │
│ ❱ 4 from stepfunctions.workflow import Workflow │
│ 5 from stepfunctions.steps import Chain │
│ 6 from stepfunctions.steps.states import State │
│ 7 │
│ │
│ /Users/zied/Library/Caches/pypoetry/virtualenvs/ada-datasets-pipeline-gB2QjA │
│ dD-py3.10/lib/python3.10/site-packages/stepfunctions/__init__.py:25 in │
│ │
│ │
│ 22 # disable logging.warning() from import packages │
│ 23 logging.getLogger().setLevel(logging.ERROR) │
│ 24 │
│ ❱ 25 from stepfunctions import steps │
│ 26 from stepfunctions import workflow │
│ 27 from stepfunctions import template │
│ 28 from stepfunctions.workflow.utils import CustomColorFormatter │
│ │
│ /Users/zied/Library/Caches/pypoetry/virtualenvs/ada-datasets-pipeline-gB2QjA │
│ dD-py3.10/lib/python3.10/site-packages/stepfunctions/steps/__init__.py:19 in │
│ │
│ │
│ 16 │
│ 17 from stepfunctions.steps.states import Pass, Succeed, Fail, Wait, Choic │
│ 18 from stepfunctions.steps.states import Graph, FrozenGraph │
│ ❱ 19 from stepfunctions.steps.sagemaker import TrainingStep, TransformStep, │
│ 20 from stepfunctions.steps.compute import LambdaStep, BatchSubmitJobStep, │
│ 21 from stepfunctions.steps.service import DynamoDBGetItemStep, DynamoDBPu │
│ 22 │
│ │
│ /Users/zied/Library/Caches/pypoetry/virtualenvs/ada-datasets-pipeline-gB2QjA │
│ dD-py3.10/lib/python3.10/site-packages/stepfunctions/steps/sagemaker.py:25 │
│ in │
│ │
│ 22 from stepfunctions.steps.utils import merge_dicts, tags_dict_to_kv_lis │
│ 23 from stepfunctions.steps.integration_resources import IntegrationPatte │
│ 24 │
│ ❱ 25 from sagemaker.workflow.airflow import training_config, transform_conf │
│ 26 from sagemaker.model import Model, FrameworkModel │
│ 27 from sagemaker.model_monitor import DataCaptureConfig │
│ 28 │
│ │
│ /Users/zied/Library/Caches/pypoetry/virtualenvs/ada-datasets-pipeline-gB2QjA │
│ dD-py3.10/lib/python3.10/site-packages/sagemaker/__init__.py:18 in │
│ │
│ 15 │
│ 16 import importlib_metadata │
│ 17 │
│ ❱ 18 from sagemaker import estimator, parameter, tuner # noqa: F401 │
│ 19 from sagemaker.amazon.kmeans import KMeans, KMeansModel, KMeansPredicto │
│ 20 from sagemaker.amazon.pca import PCA, PCAModel, PCAPredictor # noqa: F │
│ 21 from sagemaker.amazon.lda import LDA, LDAModel, LDAPredictor # noqa: F │
│ │
│ /Users/zied/Library/Caches/pypoetry/virtualenvs/ada-datasets-pipeline-gB2QjA │
│ dD-py3.10/lib/python3.10/site-packages/sagemaker/estimator.py:30 in │
│ │
│ 27 from six.moves.urllib.parse import urlparse │
│ 28 │
│ 29 import sagemaker │
│ ❱ 30 from sagemaker import git_utils, image_uris, vpc_utils, s3 │
│ 31 from sagemaker.analytics import TrainingJobAnalytics │
│ 32 from sagemaker.config import ( │
│ 33 │ ESTIMATOR_DEBUG_HOOK_CONFIG_PATH, │
│ │
│ /Users/zied/Library/Caches/pypoetry/virtualenvs/ada-datasets-pipeline-gB2QjA │
│ dD-py3.10/lib/python3.10/site-packages/sagemaker/image_uris.py:24 in │
│ │
│ │
│ 21 from packaging.version import Version │
│ 22 │
│ 23 from sagemaker import utils │
│ ❱ 24 from sagemaker.jumpstart.constants import DEFAULT_JUMPSTART_SAGEMAKER_ │
│ 25 from sagemaker.jumpstart.enums import JumpStartModelType │
│ 26 from sagemaker.jumpstart.utils import is_jumpstart_model_input │
│ 27 from sagemaker.spark import defaults │
│ │
│ /Users/zied/Library/Caches/pypoetry/virtualenvs/ada-datasets-pipeline-gB2QjA │
│ dD-py3.10/lib/python3.10/site-packages/sagemaker/jumpstart/constants.py:27 │
│ in │
│ │
│ 24 │ MIMEType, │
│ 25 │ JumpStartModelType, │
│ 26 ) │
│ ❱ 27 from sagemaker.jumpstart.types import JumpStartLaunchedRegionInfo, Jum │
│ 28 from sagemaker.base_serializers import ( │
│ 29 │ BaseSerializer, │
│ 30 │ CSVSerializer, │
│ │
│ /Users/zied/Library/Caches/pypoetry/virtualenvs/ada-datasets-pipeline-gB2QjA │
│ dD-py3.10/lib/python3.10/site-packages/sagemaker/jumpstart/types.py:20 in │
│ │
│ │
│ 17 from copy import deepcopy │
│ 18 from enum import Enum │
│ 19 from typing import Any, Dict, List, Optional, Set, Union │
│ ❱ 20 from sagemaker_core.shapes import ModelAccessConfig as CoreModelAcces │
│ 21 from sagemaker.model_card.model_card import ModelCard, ModelPackageMo │
│ 22 from sagemaker.utils import ( │
│ 23 │ S3_PREFIX, │
│ │
│ /Users/zied/Library/Caches/pypoetry/virtualenvs/ada-datasets-pipeline-gB2QjA │
│ dD-py3.10/lib/python3.10/site-packages/sagemaker_core/shapes/__init__.py:1 │
│ in │
│ │
│ ❱ 1 from ..main.shapes import * │
│ 2 │
│ │
│ /Users/zied/Library/Caches/pypoetry/virtualenvs/ada-datasets-pipeline-gB2QjA │
│ dD-py3.10/lib/python3.10/site-packages/sagemaker_core/main/shapes.py:2509 in │
│ │
│ │
│ 2506 │ """ │
│ 2507 │
│ 2508 │
│ ❱ 2509 class MonitoringDatasetFormat(Base): │
│ 2510 │ """ │
│ 2511 │ MonitoringDatasetFormat │
│ 2512 │ Represents the dataset format used when running a monitoring j │
│ │
│ in pydantic.main.ModelMetaclass.__new__:186 │
│ │
│ in pydantic.utils.validate_field_name:168 │
╰──────────────────────────────────────────────────────────────────────────────╯
NameError: Field name "json" shadows a BaseModel attribute; use a different
field name with "alias='json'".
```

### Environment

- **AWS Step Functions Data Science Python SDK version : 2.3.0
- **Python Version: Python 3.10.15

This is :bug: Bug Report

Commencez par reproduire l’échec de l’importation dans l’environnement Python 3.10 indiqué, en commençant par stepfunctions/__init__.py et en examinant stepfunctions/steps/sagemaker.py. Suivez la chaîne d’importation des dépendances impliquant sagemaker et l’erreur Pydantic, puis vérifiez que le SDK s’importe et que l’exemple de workflow s’exécute sans le traceback.

Rédigé par le modèle d'indexation à partir du texte de l'issue.