Prodigy
ML platformprodigy
Scriptable annotation tool from Explosion that runs locally on a lifetime licence.
- Provider
- default
- Kind
- ML platform
- Category
- Compute
- Official docs
- https://prodi.gy/docs/install
| property | type | values | required | kind default | this component |
|---|---|---|---|---|---|
| computeInstances | integer | — | no | — | inherited |
| database | enum | sqlite | mysql | postgresql | no | sqlite | inherited |
| experimentTracking | boolean | — | no | true | ▸ false |
| gpuEnabled | boolean | — | no | — | inherited |
| managed | boolean | — | no | false | ▸ false |
| modelRegistry | boolean | — | no | true | ▸ false |
| port | integer | — | no | 8080 | inherited |
| publicAccess | boolean | — | no | — | ▸ false |
Every rule whose selector covers this component's kind or its category. Whether a rule fires depends on the design: its properties, its edges and its groups.
stateful-node-without-zone-redundancy
A stateful compute node pinned to exactly one availability zone disappears with that zone, and its state goes with it. Nodes inside a cell are exempt, because there the cell is deliberately single-zone and redundancy comes from the other cells.
- — all of these hold:
- — the node's `stateless` is false
- — the node sits inside exactly 1 availability-zone group
- — this does not hold:
- — the node sits inside at least one cell group
nodes:
- { id: "prodigy", component: "prodigy" }Platform for AIalibaba-paiAWS Clean Rooms MLaws-clean-rooms-mlAmazon SageMaker AIaws-sagemakerAmazon SageMaker Canvasaws-sagemaker-canvasAmazon SageMaker Feature Storeaws-sagemaker-feature-storeManaged MLflow on Amazon SageMaker AIaws-sagemaker-mlflowAmazon SageMaker Unified Studioaws-sagemaker-unified-studioMicrosoft Foundryazure-ai-foundryAzure Machine Learningazure-machine-learningAbacus.AIabacus-aiAlteryxalteryxArgillaargillaC3 AI Platformc3-aiClearMLclearmlCometcomet-mlCVATcvatDataikudataikuDataRobotdatarobotDatasaurdatasaurDetermined AIdeterminedDomino Data Labdomino-data-labDVCdvcEncordencordFeastfeastFlyteflyteH2O.aih2oKilikiliKNIMEknimeKubeflowkubeflowLabel Studiolabel-studioLabelboxlabelboxMetaflowmetaflowGeneric ML platformml-platformMLflowmlflowneptune.aineptune-aiNVIDIA DGX Cloudnvidia-dgx-cloudPachydermpachydermPolyaxonpolyaxonRapidMiner AI HubrapidminerRoboflowroboflow
and 21 more → ML platform page# yaml-language-server: $schema=../../schema/component.schema.json # Prodigy: Explosion's scriptable annotation tool, bought once on a lifetime licence and run locally. Per # "Installation", the web server starts on localhost port 8080 (prodigy.json or PRODIGY_HOST/PRODIGY_PORT change it) and # annotations go to SQLite by default, with MySQL or PostgreSQL as alternatives. schemaVersion: "1" type: "component" id: "prodigy" kind: "ml-platform" provider: "default" docs: "https://prodi.gy/docs/install" defaults: managed: false experimentTracking: false modelRegistry: false publicAccess: false properties: port: type: "integer" default: 8080 database: type: "enum" values: ["sqlite", "mysql", "postgresql"] default: "sqlite"