You're viewing version 2.17 of the OpenSearch documentation. This version is no longer maintained. For the latest version, see the current documentation. For information about OpenSearch version maintenance, see Release Schedule and Maintenance Policy.

Machine learning

The ML Commons plugin provides machine learning (ML) features in OpenSearch.

Integrating ML models

For ML-model-powered search, you can use a pretrained model provided by OpenSearch, upload your own model to the OpenSearch cluster, or connect to a foundation model hosted on an external platform. In OpenSearch version 2.9 and later, you can integrate local and external models simultaneously within a single cluster.

For more information, see Integrating ML models.

Managing ML models in OpenSearch Dashboards

Administrators of ML clusters can use OpenSearch Dashboards to review and manage the status of ML models running inside a cluster. For more information, see Managing ML models in OpenSearch Dashboards.

Support for algorithms

ML Commons supports various algorithms to help train ML models and make predictions or test data-driven predictions without a model. For more information, see Supported algorithms.

ML Commons API

ML Commons provides its own set of REST APIs. For more information, see ML Commons API.

ML-powered search

For information about available ML-powered search types, see ML-powered search.

Tutorials

Using the OpenSearch ML framework, you can build various applications, from implementing conversational search to building your own chatbot. For more information, see Tutorials.