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The configuration parameters can be specified either on the command line or in a properties file. The properties file makes it simpler to maintain and share settings across instances, for example, if running in a cluster.

Create the properties file

To create the properties file, use the following command:

java -Dcreateproperties=true -jar ai.h2o.mojos.jar >

This command generates a properties file with the defaults that can be changed for the environment. To use this file at runtime, use the following command line argument:

If no propertiesfilename is set, the default properties file is used. If no properties file exists, then the program defaults are used.

Create Autogen

The server can be executed to generate notebooks and terminate, rather than executed as an endpoint. This is used as an easy way to create templates.

createautogenName of model to use for notebook generation
createnotebookSQLType of notebook
notebookfilenameModelname+typeProvides a way to generate the output file name

The current directory is used as the location of the model unless the command line parameter ModelDirectory is included on the command line.


The properties file enables specific settings to be set for the environment.

ModelDirectoryThis is the location of the Driverless AI models (.mojo) and the H2O-3 models (.zip). In Windows environments, use a double backslash (\\) for the path.
ModelDirectory = /
ModelnameThe default model name to use if no model name is passed with a scoring request.
modelname = pipeline.mojo
SecureEndPointsDefines the start of a uri for which authentication will be required.
SecureEndPoints = /modelsecure**
SecureEndPointsAllowedIPThis is an IP address for which requests are always allowed regardless of the SecureEndPoints setting. This is useful for specific management requests from a defined IP. The default is for any request to be accepted.
SecureEndPointsAllowedIP =
RestuserThis is the default username for operations that require standard user access.
restuser = h2o
RestpassThis is the encrypted password for the restuser.
restpass = aDJvMTIz
AdminuserThe username required for administrative requests to the server.
adminuser = h2oadmin
adminpassThis is the encrypted password for the admin user.
adminpass = aDJvMTIz
ScorerHostIPIf this instance should forward recipes to a specific host, this is the forwarding destination.
ScorerHostIP =
ScorerHostPortUsed in conjunction with the ScorerHostIP for supporting recipes.
ScorerHostPort = 9191
ScorerRecycleIf ScorerPool is set to zero (default) and ScorerRecycle is true (default) then a single Python model is executed, and dynamically started and stopped as needed.
ScorerRecycle = true
ScorerPoolThis is the number of Python HTTP Servers that are running in this instance. This is also the port index of the ScorerHostPort that is used for connections. This allows multiple models to be started at the same time, with 0 being the default value. Usually, using a single instance with ScorerRecycle set to true is more maintainable except in concurrent request to different models.
ScorerPool = 0
ScorelogIf enabled (true), then when a prediction is made, the model name, UUID, input variables and predictions are written to standard out as part of an audit trail.
scorelog = true
ModelmonitorIf enabled (true), then when a prediction is made, a specially formatted line is written to the standard out file, which is then used by the Model Monitoring component.
modelmonitor = true
ExtendedoutputIf enabled (true), then all the predictions are returned, otherwise only the first result is returned.
extendedoutput = true
ExplainabilityIf enabled, then the prediction will also return klime reason codes if the model supports returning them.
explainability = false
ExplainabilityShapleyIf set to true and if the model supports this function, then the shapley reason codes are returned with the prediction.
explainabilityShapley = false
ExplainabilityShapContribIf set to true and if the model supports this function, then the shapley reason codes are returned with the prediction for Driverless AI models.
explainabilityShapContrib = false
ExplainabilityUsesFloatsSome older models use floats for numeric features.
explainabilityUsesFloats = true
DetectShiftThis enables checking if the input row is different from the training. This requires the Experiment summary to be available on the REST endpoint.
DetectShift = false
DetectShiftToleranceAcceptable difference as a percentage. Only valid if DetectShift is enabled.
DetectShiftTolerance = 0.0f
DetectShiftEnforceIf DetectShift is enabled and the input row is equal or larger than the DetectShiftTolerance value, then a blank response is sent and not the prediction.
DetectShiftEnforce = false
CachefeaturesIf the model is already loaded, you can use the model's features. This saves processing time at the expense of memory to hold the list of features.
cachefeatures = true
UnloadModelsIf memory is required to load a new model, but memory is limited, and if the parameter unload is set to true, then the model with the lowest use count will be unloaded.
UnloadModels = true
RetryOnUnloadIf enabled, this option will cause the request that initiated the unloading of models to be retried. Three attempts will be made, after which an exception (HTTP 500) error will be returned to the caller.
RetryOnUnload = true
PreloadModelsThis is a comma-separated list of models that will be loaded at start up. Otherwise the models are loaded on demand.
InputSeperatorIf specified, this will be used as a feature separator. This is usually not set.
InputSeperator = ,
SecureModelThe REST server can monitor for attacks on the model. For example, probing.
SecureModel = false
SecureModelLoggingIf set to true, the request will be logged to standard out.
SecureModelLogging = false
SecureModelFeatureChangeDistanceMinimum value distance between feature request inputs.
SecureModelFeatureChangeDistance = 1000
SecureModelFeatureChangeNumberMinimum number of features that should change per request.
SecureModelFeatureChangeNumber = 2
SecureModelFeatureChangePercentMinimum feature change for this request.
SecureModelFeatureChangePercent = 8
SecureModelNumberOfReqestsNumber of requests from a single source IP.
SecureModelNumberOfReqests = 50
SecureModelActionIf true, a blank result will be returned if suspicious requests are received.
SecureModelAction = false
SecureModelTrackingAgeMSHow long to remember requests from the same source IP. Default is 1 hour.
SecureModelTrackingAgeMS = 3600000
SecureModelTrackingSizeMaximum number of source locations to remember.
SecureModelTrackingSize = 1000
SecureModelMSBetweenReqestsMinimum time between requests in milliseconds from the same source.
SecureModelMSBetweenReqests = 4000
setConvertInvalidNumbersToNaSpecific setting for H2O-3 models.
setConvertInvalidNumbersToNa = false
setConvertUnknownCategoricalLevelsToNaSpecific setting for H2O-3 models.
setConvertUnknownCategoricalLevelsToNa = false
IgnoreEmptyStringsFor both Driverless AI and H2O-3 models, if the input is parsed but contains an empty string, this specifies whether the model should receive an empty string.
IgnoreEmptyStrings = false
ResultLengthTruncates the returned prediction to the specified number digits. Using zero (0) disables the truncation.
resultLength = 0
IncludeUUIDWhen writing scoring details to standard out, this specifies whether to include the models UUID.
includeUUID = true
numberWorkersA Snowflake specific setting that controls the number of threads used for scoring.
numberWorkers = 10
SnowflakeAllowedFunctionsA Snowflake specific setting that ensures only the requests from this function will be accepted.
SnowflakeAllowedFunctions = H2O.*
EnableModelBuildA Snowflake specific setting that enables model building for this instance.
EnableModelBuild = True
SecureModelAllowedAgentA Snowflake specific setting that will only accept requests from these specific source locations.
SecureModelAllowedAgent = .*snowflake.*
SF_functionA Snowflake specific setting that defines the template for returning populated SQL function create call.

sf_function =H2OPredicit

RemoveQuotesIf the input features are in quotes, this specifies whether the quotes should be removed before scoring.
RemoveQuotes = True
AutoGenSpecifies if auto generation of scoring code templates is enabled. Setting Autogen to false also disables OpenAPI generation via http://hostname:port/v3/api-docs/

Autogen = True
AutogenHostThe endpoint used to generate the code. This has a separate interface for isolation.
AutogenHost =
AutogenTypeThis setting is used to allow or restrict what templates are available. For example, maybe only Snowflake templates should be available.
AutogenHost = <valid regex expression>

.* : This is the default and lists all templates
.*Snowflake.* : Returns only Snowflake templates
((?!PowerBI).)*$ : Do not return templates for PowerBI

Call curl -u h2o:h2o123 -s to get all the available template types.
TempWorkingDirThis setting is used to define the location that eScorer will use for operations where temporary files are required to be written and accessed. Note that this setting ends with a /. For eample, /opt/H2O/temp/. If the default value is not set and /opt/H2O/temp/ does not exist, then the JVM runtime setting is used.

TempWorkingDir=<valid directory location>