ML Hub: Deployed Successful but not shown in ML Tag

Hi ​@Thanawath.Ruangsamuth

Once you have successfully deployed the model, you should set up your Machine Learning Model tag through the Tag Builder as a next step, as described here: https://userguide.trendminer.com/en/tag-builder--machine-learning-model-tag.html

Let me know if that solves your question…

Kind regards,
Jef

Thanks for the reply. It not shown any pmml model to chose for Builder. IDK why but it shown success in my code without errors.
 

Hi ​@Thanawath.Ruangsamuth,

Could you please run the code snippet bellow in an MLHub Notebook this should list all available PMML models that you have.

This way I can confirm the publishing was correct.

Kind regards,

Frederik

from trendminer.trendminer_client import TrendMinerClient
from trendminer.ml.models import ZementisModels

import os

token = os.environ["KERNEL_USER_TOKEN"]

# Create TrendMiner API object
client = TrendMinerClient(token)

models = ZementisModels(client)
all_models = models.list_models()
print(all_models)

from trendminer.trendminer_client import TrendMinerClient
from trendminer.ml.models import ZementisModels

import os

token = os.environ["KERNEL_USER_TOKEN"]

# Create TrendMiner API object
client = TrendMinerClient(token)

models = ZementisModels(client)
all_models = models.list_models()
print(all_models)

Here’s the output 

[]Please see my deployed code below.

# ==========================================================
# 3. SECURE PMML EXPORT
# ==========================================================
from datetime import datetime
from nyoka import skl_to_pmml
from trendminer.ml.models import ZementisModels

timestamp = datetime.now().strftime('%Y%m%d_%H%M')
model_name = f"PDP_10Min_Forecast_{timestamp}"
pmml_path = "pdp_10min_forecast.pmml"

# Export trained pipeline to PMML
skl_to_pmml(
    pipeline,     # your trained Pipeline
    feature_cols,         # list of feature column names
    'Future_PDP',         # target column name
    pmml_path,
    model_name=model_name
)

print("PMML exported successfully:", pmml_path)


# ==========================================================
# 4. DEPLOYMENT WITH ERROR HANDLING
# ==========================================================
try:
    z_models = ZementisModels(client)

    with open(pmml_path, "r") as f:
        pmml_content = f.read()

    model_id = z_models.deploy_model(pmml_content)

    print(f"\n✅ SUCCESS! Model Deployed.")
    print(f"Model ID: {model_id}")

except Exception as e:
    print(f"\n❌ Deployment failed.")
    print(f"Technical detail: {e}")

Hi @Thanawath.Ruangsamuth,

If I understand correctly, you were able to deploy your model successfully and your code outputs the model_id.

If the model_id is printed, the all_models list should also contain the models.

Could you please confirm whether the model_id is being printed?

Kind regards,

Frederik