This project is an OpenSearch plugin that enables builders to innovate AI apps on OpenSearch.

The current process of using ML offerings in OpenSearch, such as Semantic Search, requires users to handle complex setup and pre-processing tasks, and send verbose user queries, both of which can be time-consuming and error-prone.

The directional idea is to provide OpenSearch users with use case templates, which provide a compact description (e.g., JSON document). These templates would describe configurations for automated workflows such as Retrieval Augment Generation (RAG), AI connectors and other components that prime OpenSearch as a backend to leverage generative models—once primed, builders can query OpenSearch directly without building middleware logic to stitch together data flows and ML models.

See the RFC on the OpenSearch project for initial design discussions.

See CONTRIBUTING for more information.

This project is licensed under the Apache-2.0 License.