Hello, I'm in the process of learning BentoML, getting familiar with it, so I'm trying to follow a project, but since it's a year old, when I run the command:

bentoml serve bentoml_app_pandas.py:service --reload

, I encounter the following error: "`[ERROR] [api_server:11] The "bentoml.sklearn.load_runner" method is deprecated. "load_runner" arguments will be ignored. Use "bentoml.sklearn.get("pca:latest").to_runner()`" instead." So, I've updated my code:

import bentoml

import pandas as pd

from <http://bentoml.io|bentoml.io> import NumpyNdarray, PandasDataFrame

import numpy as np

# Load transformers and model

# scaler = bentoml.sklearn.load_runner("scaler:latest", function_name="transform")

scaler = bentoml.sklearn.get("scaler:latest").to_runner()

# pca = bentoml.sklearn.load_runner("pca:latest", function_name="transform")

pca = bentoml.sklearn.get("pca:latest").to_runner()

# model = bentoml.sklearn.load_runner("customer_segmentation_kmeans:latest")

model = bentoml.sklearn.get("customer_segmentation_kmeans:latest").to_runner()

service = bentoml.Service("customer_segmentation_kmeans", runners=[scaler, pca, model])

@service.api(input=PandasDataFrame(), output=NumpyNdarray())

def predict(df: pd.DataFrame) -> np.array:

# Process data

scaled_df  = pd.DataFrame([scaler.run(df)], columns=df.columns)

processed_df = pd.DataFrame([pca.run(scaled_df)], columns=['col1', 'col2', 'col3'])

# Predict data

result = model.run(processed_df)

return np.array(result)

But I'm getting the error: (I don't use 'predict' in my code)

AttributeError: 'StandardScaler' object has no attribute 'predict'

2024-04-11T14:38:02+0200 [ERROR] [api_server:customer_segmentation_kmeans:2] Exception on /predict [POST] (trace=b038efd3e586ab0e884ec2f092b2bab3,span=1e547feb6f675e0b,sampled=0,service.name=customer_segmentation_kmeans)

Traceback (most recent call last):

File "C:\Users\hguilbot\Documents\BentoML_Project\bentomlenv\lib\site-packages\bentoml\_internal\server\http_app.py", line 344, in api_func

output = await run_in_threadpool(api.func, *args)

File "C:\Users\hguilbot\Documents\BentoML_Project\bentomlenv\lib\site-packages\starlette\concurrency.py", line 42, in run_in_threadpool

return await <http://anyio.to|anyio.to>_thread.run_sync(func, *args)

File "C:\Users\hguilbot\Documents\BentoML_Project\bentomlenv\lib\site-packages\anyio\to_thread.py", line 49, in run_sync

return await get_async_backend().run_sync_in_worker_thread(

File "C:\Users\hguilbot\Documents\BentoML_Project\bentomlenv\lib\site-packages\anyio\_backends\_asyncio.py", line 2103, in run_sync_in_worker_thread

return await future

File "C:\Users\hguilbot\Documents\BentoML_Project\bentomlenv\lib\site-packages\anyio\_backends\_asyncio.py", line 823, in run

result = context.run(func, *args)

File "C:\Users\hguilbot\Documents\BentoML_Project\src\bentoml_app_pandas.py", line 18, in predict

scaled_df  = pd.DataFrame([scaler.run(df)], columns=df.columns)

File "C:\Users\hguilbot\Documents\BentoML_Project\bentomlenv\lib\site-packages\bentoml\_internal\runner\runner.py", line 53, in run

return self.runner._runner_handle.run_method(self, *args, **kwargs)

File "C:\Users\hguilbot\Documents\BentoML_Project\bentomlenv\lib\site-packages\bentoml\_internal\runner\runner_handle\remote.py", line 346, in run_method

anyio.from_thread.run(

File "C:\Users\hguilbot\Documents\BentoML_Project\bentomlenv\lib\site-packages\anyio\from_thread.py", line 48, in run

return async_backend.run_async_from_thread(func, args, token=token)

File "C:\Users\hguilbot\Documents\BentoML_Project\bentomlenv\lib\site-packages\anyio\_backends\_asyncio.py", line 2143, in run_async_from_thread

return f.result()

File "C:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.9_3.9.3568.0_x64__qbz5n2kfra8p0\lib\concurrent\futures\_base.py", line 446, in result

return self.__get_result()

File "C:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.9_3.9.3568.0_x64__qbz5n2kfra8p0\lib\concurrent\futures\_base.py", line 391, in __get_result

raise self._exception

File "C:\Users\hguilbot\Documents\BentoML_Project\bentomlenv\lib\site-packages\anyio\_backends\_asyncio.py", line 2130, in task_wrapper

return await func(*args)

File "C:\Users\hguilbot\Documents\BentoML_Project\bentomlenv\lib\site-packages\bentoml\_internal\runner\runner_handle\remote.py", line 242, in async_run_method

raise RemoteException(

bentoml.exceptions.RemoteException: An unexpected exception occurred in remote runner scaler: [500] Internal Server Error

2024-04-11T14:38:02+0200 [INFO] [api_server:customer_segmentation_kmeans:2] 127.0.0.1:63611 (scheme=http,method=POST,path=/predict,type=application/json,length=185) (status=500,type=application/json,length=2) 132.446ms (trace=b038efd3e586ab0e884ec2f092b2bab3,span=1e547feb6f675e0b,sampled=0,service.name=customer_segmentation_kmeans)

I'm not sure what to do next. Do you have any ideas? ( I use "bentoml, version 1.2.10",so I think the reason is that I'm using a syntax that works in version 1.1 but I'm using 1.2, so if that's the case, do you have any idea how to help me? Thanks you