Manage Hopsworks Feature Store resources via the hops CLI with JSON output.
npx skills add https://github.com/logicalclocks/hopsworks-cli --skill hops-logicalclocks
Please help me install this Agent Skill. Skill: hops Source: https://github.com/logicalclocks/hopsworks-cli/tree/main/cmd/templates Command: npx skills add https://github.com/logicalclocks/hopsworks-cli --skill hops-logicalclocks
This Skill eliminates the tedious, error-prone manual work of managing Hopsworks Feature Store resources, including feature groups, feature views, training datasets, models, deployments, and external data connectors, saving data and ML teams hours of repetitive administrative and operational effort.
Use the hops skill to list all feature groups in your current Hopsworks project and display the full schema and statistics for the customer_transactions feature group.
High-intent search queries and answers about installing and using this skill.
You can manage Hopsworks Feature Store resources from the command line by using the hops CLI to automate the creation and listing of feature groups, feature views, and training datasets. This reduces manual operational overhead for ML teams.
Yes, you can connect external data sources like Snowflake, S3, and BigQuery to create external feature groups without manual data movement. This allows you to integrate external databases directly into your feature engineering workflows.
Automate ML pipeline orchestration and model deployment in Hopsworks by registering models, creating deployments, and running scheduled jobs via the hops CLI. This streamlines end-to-end machine learning operations for online serving.
Yes, you need to configure environment variables for authentication when using the hops CLI for programmatic access to Hopsworks. The CLI supports JSON output for parsing, ensuring secure and automated environment configuration.
The best way to build a training dataset from an external feature group is to use the hops CLI to build a feature view with joins and transformations. You can then compute the training dataset and register the trained model for deployment.
Managing feature groups via the hops CLI is limited to Hopsworks environments and requires proper environment variable configuration for authentication. It applies to feature engineering workflows and model serving operations within that specific ecosystem.
logicalclocksAutomate data discovery across Hopsworks feature groups, data sources, and files.
jshsakuraAlign preprocessing, feature generation, model artifacts, and serving integration for training-serving parity.
logicalclocksAutomate external data source ingestion and mounting into Hopsworks.
logicalclocksMonitor Hopsworks feature stores for drift and data quality issues.
