Listing models

This feature is in the beta tier. For more information on feature tiers, see API Tiers.

Information about models in the catalog can be retrieved using the gds.beta.model.list() procedure.

1. Syntax

List models from the catalog:

CALL gds.beta.model.list(modelName: String)
YIELD
    modelInfo: Map,
    trainConfig: Map,
    graphSchema: Map,
    loaded: Boolean,
    stored: Boolean,
    creationTime: DateTime,
    shared: Boolean

Table 1. Parameters
Name	Type	Default	Optional	Description
modelName	String	`n/a`	yes	The name of a model. If not specified, all models in the catalog are listed.

Table 2. Results
Name	Type	Description
modelInfo	Map	Detailed information about the trained model. Always includes the `modelName` and `modelType`, e.g., GraphSAGE. Dependent on the model type, there are additional fields.
trainConfig	Map	The configuration used for training the model.
graphSchema	Map	The schema of the graph on which the model was trained.
loaded	Boolean	True, if the model is loaded in the in-memory model catalog.
stored	Boolean	True, if the model is stored on disk.
creationTime	Datetime	Time when the model was created.
shared	Boolean	True, if the model is shared between users.

2. Examples

Once we have trained models in the catalog we can see information about either all of them or a single model using its name

2.1. Listing all models

Listing detailed information about all models:

CALL gds.beta.model.list()
YIELD modelInfo, loaded, shared, stored
RETURN modelInfo.modelName AS modelName, loaded, shared, stored

Table 3. Results
modelName	loaded	shared	stored
`"my-model"`	`true`	`false`	`false`

2.2. Listing a specific model

Listing detailed information about specific model:

CALL gds.beta.model.list('my-model')
YIELD modelInfo, loaded, shared, stored
RETURN modelInfo.modelName AS modelName, loaded, shared, stored

Table 4. Results
modelName	loaded	shared	stored
`"my-model"`	`true`	`false`	`false`

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