hana_ai.tools

hana.ai tools is a set of tools that can be used to perform various tasks like forecasting, time series analysis, etc.

agent_as_a_tool

agent_as_a_tool.AgentAsATool(agent, name, ...)

Agent as a tool.

code_template_tools

code_template_tools.GetCodeTemplateFromVectorDB(*)

Get code template from vector database.

hana_ml_tools

hana_ml_tools.additive_model_forecast_tools.AdditiveModelForecastFitAndSave(...)

This tool is used to fit and predict the additive model forecast.

hana_ml_tools.additive_model_forecast_tools.AdditiveModelForecastLoadModelAndPredict(...)

This tool is used to load the additive model forecast from model storage and predict.

hana_ml_tools.additive_model_forecast_tools.MassiveAdditiveModelForecastFitAndSave(...)

This tool fits a grouped additive model forecast and saves it in model storage.

hana_ml_tools.additive_model_forecast_tools.MassiveAdditiveModelForecastLoadModelAndPredict(...)

This tool loads a grouped additive model forecast from model storage and predicts.

hana_ml_tools.automatic_timeseries_tools.AutomaticTimeSeriesFitAndSave(...)

This tool fits a time series model and saves it in the model storage.

hana_ml_tools.automatic_timeseries_tools.AutomaticTimeSeriesLoadModelAndPredict(...)

This tool load model from model storage and do the prediction.

hana_ml_tools.automatic_timeseries_tools.AutomaticTimeSeriesLoadModelAndScore(...)

This tool load model from model storage and do the scoring.

hana_ml_tools.cap_artifacts_tools.CAPArtifactsTool(...)

This tool generates CAP artifacts for a given model.

hana_ml_tools.config_dict_validator_tools.GetPALPipelineInfo(...)

Query _SYS_AFL.PAL_PIPELINE_INFO for the catalogue of operators supported by the current HANA instance.

hana_ml_tools.config_dict_validator_tools.GetAutoMLConfigDict(...)

Return the resolved config_dict for a given AutoML pipeline type.

hana_ml_tools.config_dict_validator_tools.ModifyAutoMLConfigDict(...)

Verify (and, if needed, amend) an AutoML config_dict via _SYS_AFL.PAL_AUTOML_CONFIG.

hana_ml_tools.dataset_prep_tools.ImportCSVToTableTool(...)

Import a local CSV file into a HANA table.

hana_ml_tools.dataset_prep_tools.SplitTableForForecastingTool(...)

Split a source HANA table into time-ordered train/test/validation tables for forecasting.

hana_ml_tools.fetch_tools.FetchDataTool(...)

This tool fetches data from a given table.

hana_ml_tools.hdi_artifacts_tools.HDIArtifactsTool(...)

This tool generates HDI artifacts for a given model.

hana_ml_tools.intermittent_forecast_tools.IntermittentForecast(...)

This tool generates forecast for the intermittent demand dataset.

hana_ml_tools.model_storage_tools.ListModels(...)

Tool to list all models in the model storage.

hana_ml_tools.model_storage_tools.DeleteModels(*, ...)

Tool to delete a model from the model storage.

hana_ml_tools.model_storage_tools.DisplayConfigDict(...)

Tool to display the config_dict used at training time for a stored AutoML model.

hana_ml_tools.select_statement_to_table_tools.SelectStatementToTableTool(...)

This tool stores SelectStatement data into a HANA table.

hana_ml_tools.ts_accuracy_measure_tools.AccuracyMeasure(...)

This tool calculates the accuracy measure for the time series forecast.

hana_ml_tools.ts_check_tools.TimeSeriesCheck(...)

This tool calls stationarity test, intermittent check, trend test and seasonality test for the given time series data.

hana_ml_tools.ts_check_tools.StationarityTest(...)

This tool calls stationarity test for the given time series data.

hana_ml_tools.ts_check_tools.TrendTest(...)

This tool calls trend test for the given time series data.

hana_ml_tools.ts_check_tools.SeasonalityTest(...)

This tool calls seasonality test for the given time series data.

hana_ml_tools.ts_check_tools.WhiteNoiseTest(...)

This tool calls white noise test for the given time series data.

hana_ml_tools.ts_make_predict_table.TSMakeFutureTableTool(...)

This tool creates a predict table for time series forecasting in HANA.

hana_ml_tools.ts_outlier_detection_tools.TSOutlierDetection(...)

This tool detects outliers in time series data.

hana_ml_tools.ts_visualizer_tools.TimeSeriesDatasetReport(...)

This tool generates a report for a time series dataset.

hana_ml_tools.ts_visualizer_tools.ForecastLinePlot(...)

This tool generates a line plot for the forecasted result.

graph_tools

Knowledge-graph-backed retrieval tools exposed on the MCP server. ObjectDiscoveryTool calls the HANA AI Core object-discovery procedure (default AI_OBJECT_RETRIEVAL) to surface schemas, tables, columns, and their relationships as narrative context. DataRetrievalTool calls the paired data-retrieval procedure to fetch rows or aggregations for a natural-language question. Both tools share the hana_ai.retrieval clients and expect a HANA remote source connected to AI Core.

hana_ml_tools.graph_tools.ObjectDiscoveryTool(...)

Tool for discovering HANA objects via knowledge graph.

hana_ml_tools.graph_tools.DataRetrievalTool(...)

Tool for interacting with Data Retrieval.

df_tools

df_tools.automatic_timeseries_tools.AutomaticTimeSeriesFitAndSave(...)

This tool fits a time series model and saves it in the model storage.

df_tools.automatic_timeseries_tools.AutomaticTimeSeriesLoadModelAndPredict(...)

This tool load model from model storage and do the prediction.

df_tools.automatic_timeseries_tools.AutomaticTimeSeriesLoadModelAndScore(...)

This tool load model from model storage and do the scoring.

df_tools.fetch_tools.FetchDataTool(...[, ...])

This tool fetches data from a given table.

df_tools.ts_outlier_detection_tools.TSOutlierDetection(...)

This tool detects outliers in time series data.

df_tools.ts_visualizer_tools.TimeSeriesDatasetReport(...)

This tool generates a report for a time series.

hana_ml_toolkit

toolkit.HANAMLToolkit(connection_context[, ...])

Toolkit for interacting with HANA SQL.