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Community built data connectors and processors for

The vision for data-components-contrib is a community-driven library of components for streaming and processing time series data for use in the runtime. provides a general interface that anyone can implement to create data connectors and data processors. This enables both authors and consumers of pods, to use the same data sources for training and inferencing ML models. Join us in helping make AI easy for developers.

See on how you can contribute a component.

Data Component Concepts


A dataspace is a specification on how the runtime and AI engine loads, processes and interacts with data from a single source. A dataspace may contain a single data connector and data processor. There may be multiple dataspace definitions within a pod. The fields specified in the union of dataspaces are used as inputs to the neural networks that trains.

Data Connector

A data connector is a reuseable component that contains logic to fetch or ingest data from an external source.

Learn more at Data Connectors

Data Processor

A data processor is a reusable component, composable with a data connector that contains logic to process raw connector data into observations and state can use.

Learn more at Data Processors


Community built data connectors and processors for







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