feast-feature-store

# feast-feature-store ## Overview Feature store management skill using Feast for online/offline feature serving, feature registration, and ensuring training-serving consistency in ML systems. ## Capabilities - Feature definition and registration - Online feature serving setup - Offline feature retrieval for training - Point-in-time correctness validation - Feature freshness monitoring - Entity management - Feature view creation and management - Materialization scheduling ## Target Processes - Feature Store Implementation and Management - Feature Engineering Design and Implementation - Model Training Pipeline ## Tools and Libraries - Feast - Redis (online store) - PostgreSQL/BigQuery/Snowflake (offline store) - Parquet files ## Input Schema ```json { "type": "object", "required": ["action"], "properties": { "action": { "type": "string", "enum": ["apply", "materialize", "get-online", "get-historical", "list", "teardown"], "description": "Feast action to perform" }, "featureRepo": { "type": "string", "description": "Path to feature repository" }, "features": { "type": "array", "items": { "type": "string" }, "description": "Feature references (feature_view:feature_name)" }, "entityDf": { "type": "string", "description": "Path to entity DataFrame for historical retrieval" }, "materializationWindow": { "type": "object", "properties": { "startDate": { "...