bentoml-model-packager

# bentoml-model-packager ## Overview BentoML skill for model packaging, serving, and containerization with support for multiple ML frameworks. ## Capabilities - Bento creation and versioning - Multi-framework model support (sklearn, PyTorch, TensorFlow, etc.) - API endpoint definition with validation - Docker containerization - Kubernetes deployment YAML generation - Adaptive batching configuration - Model signatures and runners - Service composition ## Target Processes - Model Deployment Pipeline with Canary Release - Model Training Pipeline - ML System Integration Testing ## Tools and Libraries - BentoML - Docker - Kubernetes ## Input Schema ```json { "type": "object", "required": ["action"], "properties": { "action": { "type": "string", "enum": ["save", "build", "serve", "containerize", "push", "list"], "description": "BentoML action to perform" }, "modelConfig": { "type": "object", "properties": { "name": { "type": "string" }, "framework": { "type": "string" }, "modelPath": { "type": "string" }, "signatures": { "type": "object" } } }, "serviceConfig": { "type": "object", "properties": { "servicePath": { "type": "string" }, "port": { "type": "integer" }, "workers": { "type": "integer" }, "batchConfig": { "type": "object", "properties": { "maxBatchSize": { "type": "integer" }, "maxLate...