Make sure to complete the prerequisites before getting started with registering models to Vectice.
The Vectice API enables you to register all models used during development to the Vectice UI. To register your model's data and metadata, use the following Model method to declare your model.
model =Model(name, library, technique, metrics, predictor, attachments)
Once your model is declared, sync the model and its metadata to vectice by assigning the model to your project's phase iteration as follows:
my_iteration.step_register_model = model
Example
Below is a full example showcasing the concepts mentioned above.
import vecticefrom vectice import Model, Metricfrom sklearn import ...# Connect to Vecticeconnection = vectice.connect(config="vectice_config.json")# Retrieve the project phase to begin the model development phase = connection.phase("PHA-XXX")# Initialize iterationmy_iteration = phase.iteration()# Model metrics and metadatamodel_name ="My model"model_library ="sklearn"model_technique ="clustering"model_metrics = [Metric("RMSE", 153),Metric("Clusters number", 5)]model_predictor = my_sklearn_predictormodel_attachments = ["attachment1.png","attachment2.png" ]# Declaring your model and its metadatamodel = Model(name=model_name, library=model_library, technique=model_technique, metrics=model_metrics, predictor=model_predictor, attachments=model_attachments)
# Connecting your model to an iteration will automatically sync the information to Vectice UImy_iteration.step_register_model = model
For an in-depth example, view the code example found in the Iterative Development guide.