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Working with Models

Models represent AI/ML models that are part of your use cases in Credo AI.

Overview​

Models in Credo AI represent the machine learning models you're building, training, or deploying. Each model can be associated with one or more use cases.

Listing Models​

from credoai import CredoAI

client = CredoAI()

response = client.models.list(page_limit=50)
for model in response.items:
    print(f"{model.name} (ID: {model.id})")

Creating a Model​

from credoai import CredoAI, ModelCreate

client = CredoAI()

model = client.models.create(
    data=ModelCreate(
        name="Churn Predictor v2",
        summary="XGBoost model for customer churn prediction",
    )
)
print(f"Created: {model.id}")

Getting a Model​

model = client.models.get(model_id="model_xyz789")
print(f"Name: {model.name}")

Updating a Model​

from credoai import ModelUpdate

updated = client.models.update(
    model_id="model_xyz789",
    data=ModelUpdate(summary="Updated summary"),
)

Deleting a Model​

client.models.delete(model_id="model_xyz789")

Managing Relationships​

Models can be linked to use cases and vendors:

from credoai import RelationshipAdd

# Add a model to a use case
client.use_case_models.add(
    use_case_id="uc_abc123",
    data=RelationshipAdd(id="model_xyz789"),
)

# List use cases for a model
use_cases = client.use_case_models.list(use_case_id="uc_abc123")

# Add a vendor to a model
client.model_vendors.add(
    model_id="model_xyz789",
    data=RelationshipAdd(id="vendor_def456"),
)

Next Steps​