Community built data connectors and processors for Spice.ai
The vision for data-components-contrib is a community-driven library of components for streaming and processing time series data for use in the Spice.ai runtime. Spice.ai provides a general interface that anyone can implement to create data connectors and data processors. This enables both authors and consumers of Spice.ai pods, to use the same data sources for training and inferencing ML models. Join us in helping make AI easy for developers.
See CONTRIBUTING.md on how you can contribute a component.
A dataspace is a specification on how the Spice.ai 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 Spice.ai trains.
A data connector is a reuseable component that contains logic to fetch or ingest data from an external source.
Learn more at Data Connectors
A data processor is a reusable component, composable with a data connector that contains logic to process raw connector data into observations and state Spice.ai can use.
Learn more at Data Processors
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent