Babysitter bentoml-model-packager

BentoML skill for model packaging, serving, and containerization.

install

source · Clone the upstream repo

git clone https://github.com/a5c-ai/babysitter

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/a5c-ai/babysitter "$T" && mkdir -p ~/.claude/skills && cp -r "$T/library/specializations/data-science-ml/skills/bentoml-model-packager" ~/.claude/skills/a5c-ai-babysitter-bentoml-model-packager && rm -rf "$T"

manifest: library/specializations/data-science-ml/skills/bentoml-model-packager/SKILL.md

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

{
  "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" },
            "maxLatencyMs": { "type": "integer" }
          }
        }
      }
    },
    "buildConfig": {
      "type": "object",
      "properties": {
        "bentoName": { "type": "string" },
        "version": { "type": "string" },
        "includeFiles": { "type": "array", "items": { "type": "string" } },
        "pythonRequirements": { "type": "string" }
      }
    },
    "containerConfig": {
      "type": "object",
      "properties": {
        "imageName": { "type": "string" },
        "registry": { "type": "string" },
        "dockerOptions": { "type": "object" }
      }
    }
  }
}

Output Schema

{
  "type": "object",
  "required": ["status", "action"],
  "properties": {
    "status": {
      "type": "string",
      "enum": ["success", "error"]
    },
    "action": {
      "type": "string"
    },
    "modelTag": {
      "type": "string"
    },
    "bentoTag": {
      "type": "string"
    },
    "imageTag": {
      "type": "string"
    },
    "endpoint": {
      "type": "string"
    },
    "kubernetesYaml": {
      "type": "string"
    }
  }
}

Usage Example

{
  kind: 'skill',
  title: 'Package and containerize model',
  skill: {
    name: 'bentoml-model-packager',
    context: {
      action: 'containerize',
      modelConfig: {
        name: 'fraud_classifier',
        framework: 'sklearn',
        modelPath: 'models/fraud_model.pkl'
      },
      buildConfig: {
        bentoName: 'fraud-service',
        version: '1.0.0',
        pythonRequirements: 'requirements.txt'
      },
      containerConfig: {
        imageName: 'fraud-service',
        registry: 'gcr.io/my-project'
      }
    }
  }
}