h2o_sonar package

Subpackages

Submodules

h2o_sonar.config module

class h2o_sonar.config.ConfigItemType(value)

Bases: Enum

Configuration item types.

CONNECTION = 1

LICENSE = 2

class h2o_sonar.config.ConfigKeys

Bases: object

KEY_DESCRIPTION = 'description'

KEY_ENCRYPTED = 'encrypted'

KEY_NAME = 'name'

Bases: ConfigKeys

A generic purpose connection configuration which can be used to connect to various H2O.ai and 3rd party products and services.

Overview of the fields which are important for the H2O.ai authentication methods:

Username/password authentication method requires (Keycloak): - authentication server URL: auth_server_url - client ID: client_id - client secret: token + token_use_type==SECRET - username and password (on getting the access token)

Refresh token authentication method requires (Keycloak): - authentication server URL: auth_server_url - client ID: client_id - refresh token: token + token_use_type==REFRESH_TOKEN - realm: realm_name

H2O token provider authentication method requires: - environment URL: environment_url - refresh token: token + token_use_type==REFRESH_TOKEN

ENCRYPTED_FIELDS = ['token', 'password']

KEY_AUTH_SERVER_URL = 'auth_server_url'

KEY_CLIENT_ID = 'client_id'

KEY_ENV_URL = 'environment_url'

KEY_EXTRA_PARAMS = 'extra_params'

KEY_KEY = 'key'

KEY_PASSWORD = 'password'

KEY_REALM_NAME = 'realm_name'

KEY_SERVER_ID = 'server_id'

KEY_SERVER_URL = 'server_url'

KEY_TOKEN = 'token'

KEY_TOKEN_USE_TYPE = 'token_use_type'

KEY_TYPE = 'connection_type'

KEY_USERNAME = 'username'

static from_dict(config_dict: dict, decrypt: bool = True, encryption_key: str = '') → ConnectionConfig

Create the connection configuration from dictionary.

JSon example w/ unencrypted fields:

{
    "key": "096ca3c2-4715-11ee-9e2f-10828613f8ad",
    "connection_type": "ML_API",
    "name": "My connection name",
    "description": "My connection description.",
    "server_url": "http://localhost:8080",
    "server_id": "my-model-validation-dai",
    "auth_server_url": "http://localhost:8080/auth",
    "environment_url": "https://cloud.h2o.ai/",
    "realm_name": "my_realm",
    "client_id": "my_client_id",
    "token": "",
    "token_use_type": "",
    "username": "sonaruser",
    "password": "s3cr3tpa33word"
}

JSon example w/ encrypted fields:

{
    "key": "096ca3c2-4715-11ee-9e2f-10828613f8ad",
    "connection_type": "ML_API",
    "name": "My connection name",
    "description": "My connection description.",
    "server_url": "http://localhost:8080",
    "server_id": "my-model-validation-dai",
    "auth_server_url": "http://localhost:8080/auth",
    "environment_url": "https://cloud.h2o.ai/",
    "realm_name": "my_realm",
    "client_id": "my_client_id",
    "token": {
        "encrypted": "gAAAAABkTfy18iis3ya8nitGi...URMxE14aJJk="
    },
    "token_use_type": "REFRESH_TOKEN",
    "username": "sonaruser",
    "password": {
        "encrypted": "py18iis3ya8nitG="
    }
}

to_dict(encrypt: bool = True, encryption_key: str = '') → dict

class h2o_sonar.config.ConnectionConfigType(value)

Bases: Enum

Predefined connection types.

AMAZON_BEDROCK = 14

ANTHROPIC_CHAT = 12

AZURE_OPENAI_CHAT = 11

DRIVERLESS_AI = 1

DRIVERLESS_AI_AIEM = 3

DRIVERLESS_AI_STEAM = 2

H2O_3 = 4

H2O_GPT = 5

H2O_GPT_E = 6

H2O_LLM_OPS = 7

HF_SPACES = 13

OLLAMA = 8

OPENAI_CHAT = 10

OPENAI_RAG = 9

class h2o_sonar.config.EvaluationJudgeConfig(name: str, description: str, judge_type: str, connection: ConnectionConfig, llm_model_name: str = '', collection_id: str = '', key: str = '')

Bases: object

Evaluation judge configuration.

KEY_COLLECTION_ID = 'collection_id'

KEY_CONNECTION = 'connection'

KEY_DESCRIPTION = 'description'

KEY_JUDGE_TYPE = 'judge_type'

KEY_KEY = 'key'

KEY_LLM_MODEL_NAME = 'llm_model_name'

KEY_NAME = 'name'

static from_dict(config_dict: dict) → EvaluationJudgeConfig

to_dict() → dict

class h2o_sonar.config.EvaluationJudgeType(value)

Bases: Enum

anthropic_llm = 8

azure_openai_llm = 7

custom = 10

h2ogpt = 1

h2ogpte = 2

h2ogpte_llm = 3

h2ollmops = 4

ollama = 9

openai_llm = 6

openai_rag = 5

class h2o_sonar.config.H2o3Config

Bases: object

H2O-3 configuration keys used by H2O Sonar.

DEFAULT_AUTO_CLEANUP = True

DEFAULT_AUTO_START = True

DEFAULT_AUTO_STOP = False

DEFAULT_HOST = 'localhost'

DEFAULT_MAX_MEM_SIZE = '4G'

DEFAULT_MIN_MEM_SIZE = '2G'

DEFAULT_PORT = 12349

KEYS = ['h2o_min_mem_size', 'h2o_max_mem_size', 'h2o_host', 'h2o_port', 'h2o_auto_start', 'h2o_auto_cleanup', 'h2o_auto_stop']

KEY_AUTO_CLEANUP = 'h2o_auto_cleanup'

KEY_AUTO_START = 'h2o_auto_start'

KEY_AUTO_STOP = 'h2o_auto_stop'

KEY_HOST = 'h2o_host'

KEY_MAX_MEM_SIZE = 'h2o_max_mem_size'

KEY_MIN_MEM_SIZE = 'h2o_min_mem_size'

KEY_PORT = 'h2o_port'

class h2o_sonar.config.H2oSonarConfig(connections: list[ConnectionConfig] | None = None, licenses: list[LicenseConfig] | None = None, evaluation_judges: list[EvaluationJudgeConfig] | None = None, ignore_env: bool | None = False)

Bases: object

H2O Sonar configuration with global configuration items which impact H2O Sonar behavior, methods and explainers.

Configuration priority from lowest to highest:

default value
configuration file
environment variable
command line argument
configuration item

CFG_BRANDING = <h2o_sonar.lib.api.commons.Param object>

CFG_CREATE_HTML_REPRESENTATIONS = <h2o_sonar.lib.api.commons.Param object>

CFG_CUSTOM_EXPLAINERS = <h2o_sonar.lib.api.commons.Param object>

CFG_DEVICE = <h2o_sonar.lib.api.commons.Param object>

CFG_DO_SAMPLE = <h2o_sonar.lib.api.commons.Param object>

CFG_ENABLE_DATASET_DOWNLOADING = <h2o_sonar.lib.api.commons.Param object>

CFG_ENABLE_SLOW_PERTURBATORS = <h2o_sonar.lib.api.commons.Param object>

CFG_FORCE_EVAL_JUDGE = <h2o_sonar.lib.api.commons.Param object>

CFG_H2O_AUTO_CLEANUP = <h2o_sonar.lib.api.commons.Param object>

CFG_H2O_AUTO_START = <h2o_sonar.lib.api.commons.Param object>

CFG_H2O_AUTO_STOP = <h2o_sonar.lib.api.commons.Param object>

CFG_H2O_HOST = <h2o_sonar.lib.api.commons.Param object>

CFG_H2O_MAX_MEM_SIZE = <h2o_sonar.lib.api.commons.Param object>

CFG_H2O_MIN_MEM_SIZE = <h2o_sonar.lib.api.commons.Param object>

CFG_H2O_PORT = <h2o_sonar.lib.api.commons.Param object>

CFG_HTTP_SSL_CERT_VERIFY = <h2o_sonar.lib.api.commons.Param object>

CFG_LOOK_AND_FEEL = <h2o_sonar.lib.api.commons.Param object>

CFG_MODEL_CACHE_DIR = <h2o_sonar.lib.api.commons.Param object>

CFG_MP_START_METHOD = <h2o_sonar.lib.api.commons.Param object>

CFG_NUM_QUANTILES = <h2o_sonar.lib.api.commons.Param object>

CFG_PER_EXPLAINER_LOGGER = <h2o_sonar.lib.api.commons.Param object>

CFG_SAMPLE_SIZE = <h2o_sonar.lib.api.commons.Param object>

ENV_VAR_CFG_PREFIX = 'H2O_SONAR_CFG_'

KEY_BRANDING = 'branding'

KEY_CONNECTIONS = 'connections'

KEY_CREATE_HTML_REPRESENTATIONS = 'create_html_representations'

KEY_CUSTOM_EXPLAINERS = 'custom_explainers'

KEY_DEVICE = 'device'

KEY_ENABLE_SLOW_PERTURBATORS = 'enable_slow_perturbators'

KEY_EVALUATION_JUDGES = 'evaluation_judges'

KEY_FORCE_EVAL_JUDGE = 'force_eval_judge'

KEY_HTTP_SSL_CERT_VERIFY = 'http_ssl_cert_verify'

KEY_LICENSES = 'licenses'

KEY_LOOK_AND_FEEL = 'look_and_feel'

KEY_MODEL_CACHE_DIR = 'model_cache_dir'

KEY_PER_EXPLAINER_LOGGER = 'per_explainer_logger'

MP_START_METHOD_FORK = 'fork'

MP_START_METHOD_FORKSERVER = 'forkserver'

MP_START_METHOD_SPAWN = 'spawn'

VALUE_AUTO = ''

VALUE_CPU = 'cpu'

VALUE_CUDA = 'cuda'

VALUE_GPU = 'gpu'

VALUE_MPS = 'mps'

VALUE_NPU = 'npu'

VALUE_STR_FALSE = 'false'

VALUE_STR_TRUE = 'true'

add_connection(connection_config: ConnectionConfig)

add_evaluation_judge(evaluation_judge_config: EvaluationJudgeConfig)

add_license(license_config: LicenseConfig)

copy()

custom_explainers: list[str]

describe_config_item(config_item_name: str) → Param | None

describe_config_items() → dict[str, Param]

env_and_override(): Get configuration from environment variables following the naming convention and override this instance configuration.

from_toml()

get_connection(connection_key: str, connection_type: str = '') → ConnectionConfig | None

get_evaluation_judge(judge_key: str = '') → EvaluationJudgeConfig | None

get_license(license_key: str) → LicenseConfig | None

h2o_auto_cleanup: bool

h2o_auto_start: bool

h2o_auto_stop: bool

h2o_host: str

h2o_port: int

property http_ssl_cert_verify

static load(config_path: str, encryption_key: str = '') → dict | None

Load JSon/TOML file with configuration items specified in the configuration file.

Parameters:

config_pathstr: Path to the configuration file.
encryption_keystr: Optional encryption key to decrypt/encrypt sensitive data. If not specified, then shell environment variable H2O_SONAR_ENCRYPTION_KEY will be used.

Returns:

dict: Dictionary with the configuration if file can be found and parsed, None otherwise.

load_and_override(config_path: str, encryption_key: str = '')

Load JSon/TOML file and override this instance configuration items with configuration items specified in the configuration file.

Parameters:

config_pathstr: Path to the configuration file.
encryption_keystr: Optional encryption key to decrypt encrypted fields in the configuration file. If not specified, then shell environment variable H2O_SONAR_ENCRYPTION_KEY will be used.

mli_nlp_append_to_english_stop_words: bool

mli_nlp_max_df: float

mli_nlp_max_ngram: int

mli_nlp_min_df: float

mli_nlp_min_ngram: int

mli_nlp_min_token_mode: str

mli_nlp_stop_words: str

mli_nlp_surrogate_tokenizer: str

mli_nlp_surrogate_tokens: int

mli_nlp_tokenizer: str

mli_nlp_use_stop_words: bool

mli_num_quantiles: int

mli_sample: bool

mli_sample_size: int

resolve_gpu_cpu_device(result_format: str = 'torch')

Resolve a GPU/CPU device for the evaluation.

Parameters:

result_formatstr: Result format - one of “str” or “torch”.

Returns:

str | torch.device | None: Device string, torch device object, or None if unable to resolve.

save(config_path: str, config_data: dict | None = None, encrypt: bool = True, encryption_key: str = '')

Save configuration to JSon file.

Parameters:

config_pathstr: Path to the configuration file.
config_datadict: Optional dictionary with configuration data
encryptbool: Whether to encrypt sensitive data.
encryption_keystr: Optional encryption key to encrypt sensitive data. If not specified, then shell environment variable H2O_SONAR_ENCRYPTION_KEY will be used.

to_dict(encrypt: bool = True, encryption_key: str = '') → dict

to_toml()

class h2o_sonar.config.LicenseConfig(product: str, name: str, description: str, license: str = '', license_file: str = '', key: str = '')

Bases: ConfigKeys

A product license configuration.

ENCRYPTED_FIELDS = ['license']

KEY_KEY = 'key'

KEY_LICENSE = 'license'

KEY_LICENSE_FILE = 'license_file'

KEY_PRODUCT = 'product'

static from_dict(config_dict: dict, decrypt: bool = True, encryption_key: str = '') → LicenseConfig

to_dict(encrypt: bool = True, encryption_key: str = '') → dict

class h2o_sonar.config.ProductLicenseConfig(value)

Bases: Enum

Predefined license types.

DRIVERLESS_AI = 1

class h2o_sonar.config.TokenUseType(value)

Bases: Enum

Predefined token use types.

ACCESS_TOKEN = 2

API_KEY = 1

REFRESH_TOKEN = 3

SECRET = 4

h2o_sonar.errors module

exception h2o_sonar.errors.DatasetTooBigError(message, suggestion=None)

Bases: MliError

The dataset is too big to be processed by H2O Sonar.

exception h2o_sonar.errors.ExplainerCompatibilityError(message, suggestion=None)

Bases: MliError

Explainer not compatible error.

exception h2o_sonar.errors.InvalidArgumentError(message, suggestion=None)

Bases: MliError

Invalid (CLI) argument error.

exception h2o_sonar.errors.InvalidArgumentValueError(message, suggestion=None)

Bases: MliError

Invalid (CLI) argument value error.

exception h2o_sonar.errors.InvalidDataError(message, suggestion=None)

Bases: MliError

Invalid data error.

exception h2o_sonar.errors.MliError(message, suggestion=None)

Bases: Exception

MLI error.

exception h2o_sonar.errors.MliJsonDeserializationError(message, suggestion=None)

Bases: MliError

MLI JSon deserialization error.

exception h2o_sonar.errors.MliJsonSerializationError(message, suggestion=None)

Bases: MliError

MLI JSon serialization error.

exception h2o_sonar.errors.MliNotFoundError(message, suggestion=None)

Bases: MliError

Entity not found error.

exception h2o_sonar.errors.MliPredictMethodError(message, suggestion=None)

Bases: MliError

Predict method failure.

exception h2o_sonar.errors.MliTypeError(message, suggestion=None)

Bases: MliError

Wrong type error.

exception h2o_sonar.errors.MliUnsupportedDataFormatError(message, suggestion=None)

Bases: MliUnsupportedError

Unsupported data type error.

exception h2o_sonar.errors.MliUnsupportedError(message, suggestion=None): Bases: MliError

exception h2o_sonar.errors.MliUnsupportedOperationError(message, suggestion=None)

Bases: MliUnsupportedError

Unsupported operation.

exception h2o_sonar.errors.RenderingError(message, suggestion=None)

Bases: MliError

Chart or image rendering error.

exception h2o_sonar.errors.UnknownExplainerError(explainer_id: str)

Bases: MliError

Explainer not known to explainer container error.

h2o_sonar.h2o_sonar_cli module

h2o_sonar.h2o_sonar_cli.main() → int: H2O Sonar Python library for Responsible AI command line interface (CLI). See argparse configuration for more details.

h2o_sonar.interpret module

h2o_sonar.interpret.add_config_item(config_type: str, config_value: dict | str, h2o_sonar_config_path: Path | str | None = None, encryption_key: str = '')

Add configuration item.

Parameters:

config_typestr: Configuration item type - see config.ConfigItemType for options.
config_valuedict | str: Configuration item value represented either as dictionary or as string with JSon serialization of the configuration item. It is expected that the config item is NOT encrypted.
h2o_sonar_config_pathpathlib.Path | str | None: Path to the H2O Sonar configuration file. If None, then in-memory (current) configuration singleton is modified.
encryption_keystr: Encryption key to be used for encrypting sensitive data written in the configuration. If None, shell environment variable H2O_SONAR_ENCRYPTION_KEY with the encryption key must be set.

h2o_sonar.interpret.describe_explainer(explainer: type[Explainer] | str, portable: bool = False) → dict

Get explainer description.

Parameters:

explainerType[e8s.Explainer] | str: Explainer to describe.
portablebool: If True, then floats (infinity, NaN) and tuples are converted to be portable - from strings to max/min values of respective types.

Returns:

dict: Dictionary with explainer name and parameters.

h2o_sonar.interpret.do_gc()

Free system resources:

shutdowns process pool(s)
runs garbage collector
clears temporary files

h2o_sonar.interpret.get_config(h2o_sonar_config_path: Path | str | None = None, encryption_key: str = '') → dict

Get configuration item.

Parameters:

h2o_sonar_config_pathpathlib.Path | str | None: Path to the H2O Sonar configuration file. If None, then in-memory ( current) configuration singleton will be returned.
encryption_keystr | None: Encryption key to be used for decryption of the sensitive data in the configuration. If not set, then the encryption key from shell environment variable H2O_SONAR_ENCRYPTION_KEY will be used. If encryption key is not provided, then sensitive data will be returned encrypted.

List explainers by supported experiment types, scores, keywords and other criteria. Parameters are used with AND logical operator.

Parameters:

experiment_typeslist[str] | None: Filter explainers by supported experiment types - regression, binomial or multinomial.
explanation_scopeslist[str] | None: Filter explainers by supported explanation scopes - local or global.
model_metamodels.ExplainableModelMeta | None: Filter explainers by model metadata.
keywordslist[str] | None: Filter explainers by keywords.
explainer_filterlist[commons.FilterEntry] | None: Filter explainers by generic filter (forward compatible filtering). See FilterEntry for supported search types.
containerstr | explainer_container.ExplainerContainer | None: Optional explainer container name or instance to be used to run the interpretation.
args_as_json_locationpathlib.Path | str | None: Load all positional arguments and keyword arguments from JSon file. This is useful when input is generated, persisted, repeated and used from CLI (which doesn’t support all the options). IMPORTANT: if this argument is specified, then all other function parameters are ignored.
portablebool: If True, then floats (infinity, NaN) and tuples are converted to be portable - from strings to max/min values of respective types.
extra_paramsdict | None: Extra parameters.

Returns:

list[explainers.ExplainerDescriptor]: Explainers compliant with provided filters.

h2o_sonar.interpret.list_interpretations(results_location: str | Path | dict, persistence_type: PersistenceType = PersistenceType.file_system, container: str | ExplainerContainer | None = None, log_level: int = 30, extra_params: dict | None = None) → list[str]

List interpretations in given results location.

Parameters:

results_locationstr | pathlib.Path | dict: Location used e.g. by run_interpretation() to store interpretations results - filesystem (path as string or Path), memory (dictionary) or DB. If None, then results are loaded from the current directory.
persistence_typepersist.PersistenceType: Optional choice of the persistence type: file-system (default), in-memory or database. This option does not override persistence type in case that container is provided.
containerstr | explainer_container.ExplainerContainer | None: Optional explainer container name (str) or container instance to be used to run the interpretation.
log_levelint: Optional container and explainers log level.
extra_paramsdict | None: Extra parameters.

Returns:

list[str]: Interpretation keys in given results location.

h2o_sonar.interpret.register_explainer(explainer_class: type[Explainer], explainer_id: str = '', container: str | ExplainerContainer | None = None, extra_params: dict | None = None) → str

Register explainer.

Parameters:

explainer_classType[explainers.Explainer]: Explainer class.
explainer_idstr: Optional custom explainer ID to be used for explainer identification.
containerstr | explainer_container.ExplainerContainer | None: Optional explainer container name or instance to be used to run the interpretation.
extra_paramsdict | None: Extra parameters.

Returns:

str: Explainer ID.

h2o_sonar.interpret.resolve_container(container: str | ExplainerContainer | None = None, results_location: str | Any = '', persistence_api: PersistenceApi | None = None, persistence_type: PersistenceType | None = PersistenceType.file_system, do_setup: bool = True, logger: SonarLogger | None = None, log_level: int | None = None) → ExplainerContainer

Get explainer container instance to configure, register explainers and tune it.

Parameters:

containerstr | explainer_container.ExplainerContainer | None: Optional explainer container name (str) or container instance to be used to run the interpretation.
results_locationpathlib.Path | str | dict | Any | None: Where to store interpretation results - filesystem (path as string or Path), memory (dictionary) or DB. If None, then results are stored to the current directory.
persistence_apipersist.PersistenceApi | None: Instance of the persistence API allowing to create various persistence types (like file-system or DB)
persistence_typepersist.PersistenceType | None: Optional choice of the persistence type: file-system (default), in-memory or database. This option does not override persistence type in case that container is provided.
do_setupbool: Ensure explainer container set up.
loggerloggers.SonarLogger | None: Optional custom logger.
log_levelint: Optional container and explainers log level.

Returns:

explainer_container.ExplainerContainer: Explainer container instance.

Run interpretation.

Parameters:

dataset: Dataset source: explainable dataset instance, datatable frame, string (expect path to CSV, .jay or any other file type supported by datatable), dictionary (used to construct frame).
model: Path to model (str, Path), explainable model (ExplainableModel) or an instance of 3rd party model (like Scikit) to interpret.
models: Paths to models (str, Path), explainable models (ExplainableModel) or an instances of 3rd party models (like Scikit) to interpret.
target_colstr: Target column name - must be valid dataset column name.
explainerslist[str | commons.ExplainerToRun] | None: Explainer IDs to run within the interpretation or ExplainerToRun instances with explainer parameters. In case of None or empty list are run all default compatible explainers.
explainer_keywords: list[str] | None: Run compatible explainers which have given keyword (AND). This setting is used only in case that explainers parameter is empty list (or None).
validset: Optional path to validation dataset (str, Path) or datatable Frame instance.
testset: Optional path to test dataset (str, Path) or datatable Frame instance.
use_raw_featuresbool: True to use original features (default), False to force the use of transformed features in surrogate models.
used_featureslist | None: Optional parameter specifying features (dataset columns) used by the model. This parameter is used in case that an instance of the model (not ExplainableModel) is provided by the user - therefore ExplainableModel’s metadata are not available.
weight_colstr: Name of the weight column to be used by explainers.
prediction_colstr: Name of the predictions column - in case of 3rd party model (standalone MLI).
drop_colslist | None: List of the columns to drop from the interpretation i.e. columns names which should not be explained.
sample_num_rowsint | None: If None, then automatically sample based on the dataset and RAM size. If > 0, then do sample the dataset to sample_num_rows number of rows. If == 0, then do NOT sample.
samplerDatasetSampler | None: Sampling method (implementation) to be used - see h2o_sonar.utils.sampling module (documentation) for available sampling methods. Use a sampler instance to use the specific sampling method.
containerstr | explainer_container.ExplainerContainer | None: Optional explainer container name (str) or container instance to be used to run the interpretation.
results_locationpathlib.Path | str | dict | Any | None: Where to store interpretation results - filesystem (path as string or Path), memory (dictionary) or DB. If None, then results are stored to the current directory.
results_formatslist[str] | None: Optional list of the result formats (MIME types) to be generated. If None, then report in HTML and JSon is created. Supported formats: MIME_PDF, MIME_HTML and MIME_JSON.
persistence_typepersist.PersistenceType: Optional choice of the persistence type: file-system (default), in-memory or database. This option does not override persistence type in case that container is provided.
run_asynchronouslybool: True to run the interpretation asynchronously - the interpretation is run synchronously by default (False).
run_explainers_in_parallelbool: True to run explainers in parallel - explainers are run sequentially by default.
progress_callbackprogress.AbstractProgressCallbackContext | None: Optional progress callback context which is stacked atop default logging callback in h2o_sonar.lib.api.interpretations::Interpretation constructor.
loggerloggers.SonarLogger | None: Optional custom logger which implements loggers.SonarLogger interface. If logger is provided, then log_level is ignored.
log_levelint: Optional container and explainers log level. If logger is provided, then log_level is ignored.
args_as_json_locationpathlib.Path | str | None: Load all positional arguments and keyword arguments from JSon file. This is useful when input is generated, persisted, repeated and used from CLI (which doesn’t support all the options). IMPORTANT: if this argument is specified, then all other function parameters are ignored.
upload_tostr | config.ConnectionConfig | None: Upload the interpretation report to the H2O GPT Enterprise in order to talk to the report.
keystr: Custom interpretation key which must be valid UUID4 string.
extra_paramsdict | None: Extra parameters.

Returns:

interpretations.Interpretation: Interpretations instance with the explainer results (references).

h2o_sonar.interpret.unregister_explainer(explainer_id: str, container: str | ExplainerContainer | None = None, extra_params: dict | None = None) → str

Unregister explainer.

Parameters:

explainer_idstr: Custom explainer to be unregistered.
containerstr | explainer_container.ExplainerContainer | None: Optional explainer container name or instance to be used to run the interpretation.
extra_paramsdict | None: Extra parameters.

Returns:

str: ID of the unregistered explainer or "" no explainer was unregistered.

Upload interpretation to an LLM like h2oGPTE in order to talk to the interpretation report.

Returns:

Tuple[str, str]: h2oGPT Enterprise collection ID and URL.

h2o_sonar.loggers module

class h2o_sonar.loggers.SonarFileLogger(logger_name: str, log_file: str, log_level=30)

Bases: SonarLogger

File logger saves log messages to log files.

FORMATTER = <logging.Formatter object>

data(data, *args, **kwargs)

debug(msg, *args, **kwargs)

error(msg, *args, **kwargs)

info(msg, *args, **kwargs)

warning(msg, *args, **kwargs)

class h2o_sonar.loggers.SonarLogger

Bases: ABC

Abstract logger base class to be extended by runtime specific logging implementations.

FILE_NAME_H2O_SONAR_LOG = 'h2o-sonar.log'

data(data, *args, **kwargs)

debug(msg, *args, **kwargs)

error(msg, *args, **kwargs)

info(msg, *args, **kwargs)

warning(msg, *args, **kwargs)

class h2o_sonar.loggers.SonarPrintLogger

Bases: SonarLogger

Print logger prints log messages using print() method.

data(data, *args, **kwargs)

debug(msg, *args, **kwargs)

error(msg, *args, **kwargs)

info(msg, *args, **kwargs)

warning(msg, *args, **kwargs)

h2o_sonar.loggers.debug(msg, *args, **kwargs)

h2o_sonar.loggers.error(msg, *args, **kwargs)

h2o_sonar.loggers.fatal(msg, *args, **kwargs)

h2o_sonar.loggers.get_level()

h2o_sonar.loggers.info(msg, *args, **kwargs)

h2o_sonar.loggers.log(level, msg, *args, **kwargs)

h2o_sonar.loggers.setLevel(level=0)

h2o_sonar.loggers.warn(msg, *args, **kwargs)

h2o_sonar.loggers.warning(msg, *args, **kwargs)

h2o_sonar package

Subpackages

Submodules

h2o_sonar.config module

h2o_sonar.errors module

h2o_sonar.h2o_sonar_cli module

h2o_sonar.interpret module

h2o_sonar.loggers module

h2o_sonar.version module

Module contents