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* Prepare infra * Store experiment information in MySQL & MinIO * Use CreateMlModelEntityRequest instead of MlModel for PUT operations * Update MlFlow infra * Prepare MlFlow source * Prepare Mlflow workflow * Simplify test and prepare README * Revert compose * Fix compose * Prepare warnings and fix features * Use non-default port for integration test * Use mlflow-skinny for the client application
21 lines
429 B
JSON
21 lines
429 B
JSON
{
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"source": {
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"type": "mlflow",
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"config": {
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"tracking_uri": "http://localhost:5000",
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"registry_uri": "mysql+pymysql://mlflow:password@localhost:3307/experiments"
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}
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},
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"sink": {
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"type": "metadata-rest",
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"config": {}
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},
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"metadata_server": {
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"type": "metadata-server",
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"config": {
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"api_endpoint": "http://localhost:8585/api",
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"auth_provider_type": "no-auth"
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}
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}
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}
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