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bentoml

Use BentoML to author model-serving Services, build and containerize Bentos, run HTTP/gRPC servers and clients, manage models, operate the CLI and BentoCloud, and configure observability or production runtime behavior. Use when tasks mention BentoML, bentoml service.py, bentofile.yaml, Bento build/serve/deploy, BentoCloud, or BentoML model stores.

インストール方法を見る

含まれるファイル(40)

  • SKILL.md5.7 KB
  • references/repo-provenance.md1.9 KB
  • references/repo-routing-metadata.json413 B
  • references/troubleshooting.md4.0 KB
  • sub-skills/cli-and-cloud/references/bentocloud-workflows.md6.3 KB
  • sub-skills/cli-and-cloud/references/cli-catalog.md6.8 KB
  • sub-skills/cli-and-cloud/references/troubleshooting.md4.5 KB
  • sub-skills/cli-and-cloud/scripts/deployment_config_lint.py6.9 KB
  • sub-skills/cli-and-cloud/scripts/inspect_bentoml_cli.py2.5 KB
  • sub-skills/cli-and-cloud/SKILL.md4.3 KB
  • sub-skills/model-management/references/frameworks.md6.2 KB
  • sub-skills/model-management/references/model-store.md4.3 KB
  • sub-skills/model-management/references/troubleshooting.md4.9 KB
  • sub-skills/model-management/scripts/check_framework_extra.py5.3 KB
  • sub-skills/model-management/scripts/inspect_model_store.py4.3 KB
  • sub-skills/model-management/SKILL.md4.8 KB
  • sub-skills/observability-and-operations/references/configuration.md8.2 KB
  • sub-skills/observability-and-operations/references/observability.md8.2 KB
  • sub-skills/observability-and-operations/references/troubleshooting.md8.4 KB
  • sub-skills/observability-and-operations/scripts/check_observability_config.py13.1 KB
  • sub-skills/observability-and-operations/scripts/resource_plan_template.py9.0 KB
  • sub-skills/observability-and-operations/SKILL.md3.4 KB
  • sub-skills/packaging-and-containerization/references/bentofile-reference.md4.8 KB
  • sub-skills/packaging-and-containerization/references/troubleshooting.md4.1 KB
  • sub-skills/packaging-and-containerization/references/workflows.md3.3 KB
  • sub-skills/packaging-and-containerization/scripts/create_minimal_bentofile.py6.5 KB
  • sub-skills/packaging-and-containerization/scripts/validate_bentofile.py16.0 KB
  • sub-skills/packaging-and-containerization/SKILL.md4.6 KB
  • sub-skills/service-authoring/references/api-reference.md6.1 KB
  • sub-skills/service-authoring/references/troubleshooting.md5.4 KB
  • sub-skills/service-authoring/references/workflows.md4.5 KB
  • sub-skills/service-authoring/scripts/create_minimal_service.py3.8 KB
  • sub-skills/service-authoring/scripts/validate_service_target.py5.7 KB
  • sub-skills/service-authoring/SKILL.md5.8 KB
  • sub-skills/serving-and-clients/references/cli-reference.md4.0 KB
  • sub-skills/serving-and-clients/references/client-reference.md4.0 KB
  • sub-skills/serving-and-clients/references/troubleshooting.md4.0 KB
  • sub-skills/serving-and-clients/scripts/inspect_service_client.py4.4 KB
  • sub-skills/serving-and-clients/scripts/serve_command_builder.py3.4 KB
  • sub-skills/serving-and-clients/SKILL.md7.4 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

BentoML

Use this repo skill for BentoML, a Python framework for building, serving, packaging, and deploying AI/model inference APIs. This root skill is a router: read the focused sub-skill that matches the user’s task, then use its bundled references and scripts.

First Checks

  • Install: pip install -U bentoml; optional extras include bentoml[grpc], bentoml[io], bentoml[tracing-otlp], bentoml[monitor-otlp], and framework-specific packages needed by the user’s model.
  • Import check: python -c "import bentoml; print(bentoml.__version__)".
  • CLI check: bentoml --help and bentoml env.
  • Provenance check: read references/repo-provenance.md before deciding whether this skill is stale for a current checkout.
  • Troubleshooting: read references/troubleshooting.md for cross-cutting install/import, CLI, environment, optional dependency, and cloud safety issues.

Route The Task

User taskUse this sub-skillTypical triggers
Write or debug service.py, APIs, tasks, batching, lifecycle hooks, ASGI/Gradio/WebSocket/streaming, IO specs, runtime image hintssub-skills/service-authoring/SKILL.md@bentoml.service, @bentoml.api, @bentoml.task, bentoml.importing, service import target, API schema
Build a Bento, author bentofile.yaml, include/exclude files, configure build dependencies/images, local Bento store, Docker/containerizesub-skills/packaging-and-containerization/SKILL.mdbentoml build, bentofile.yaml, bentoml.build, containerize, .bentoignore, build context
Run a local server or call endpoints using Python clients, curl/OpenAPI, HTTP/gRPC, streaming, WebSocket, server flagssub-skills/serving-and-clients/SKILL.mdbentoml serve, bentoml.serve, SyncHTTPClient, AsyncHTTPClient, port, host, reload, gRPC
Save/load/list/import/export models and choose framework helpers or optional dependenciessub-skills/model-management/SKILL.mdbentoml.models, model tags, Model Store, sklearn/pytorch/transformers/mlflow/xgboost helpers, missing model
Use CLI command families or BentoCloud login/deploy/deployment/secret/api-token/codespace/push/pull workflowssub-skills/cli-and-cloud/SKILL.mdbentoml deploy, bentoml deployment, bentoml cloud, secrets, tokens, context, cluster, BentoCloud
Configure logging, metrics, tracing, monitoring, resources, scaling, gateways, testing, config files, production diagnosticssub-skills/observability-and-operations/SKILL.mdmetrics missing, tracing, config YAML, GPU resources, workers, autoscaling, gateways, production readiness

Common End-To-End Flow

  1. Author a Service with sub-skills/service-authoring/SKILL.md; validate the import target before serving.
  2. Serve locally and call endpoints with sub-skills/serving-and-clients/SKILL.md; keep server/client debugging separate from service authoring.
  3. Package with sub-skills/packaging-and-containerization/SKILL.md; validate bentofile.yaml or bentoml.build(...) options before expensive builds.
  4. Use sub-skills/model-management/SKILL.md when the workflow needs saved model tags, framework helpers, or model inclusion in a Bento.
  5. Deploy or manage cloud resources with sub-skills/cli-and-cloud/SKILL.md; treat credentialed and destructive operations as explicit user-run or user-approved actions.
  6. Add telemetry, resources, scaling, config, and production validation with sub-skills/observability-and-operations/SKILL.md.

Safe Bundled Helpers

  • sub-skills/service-authoring/scripts/create_minimal_service.py generates a starter service file.
  • sub-skills/service-authoring/scripts/validate_service_target.py imports and inspects a service target without serving it.
  • sub-skills/packaging-and-containerization/scripts/validate_bentofile.py statically checks a bentofile.yaml.
  • sub-skills/serving-and-clients/scripts/serve_command_builder.py constructs dry-run bentoml serve commands.
  • sub-skills/model-management/scripts/check_framework_extra.py checks optional framework imports.
  • sub-skills/cli-and-cloud/scripts/inspect_bentoml_cli.py renders safe CLI help without contacting BentoCloud.
  • sub-skills/observability-and-operations/scripts/check_observability_config.py checks local config shapes without external collectors.

Side-Effect Boundaries

  • Safe by default: import checks, CLI help, static YAML/config validation, command construction, and read-only local store inspection.
  • Potentially mutating: bentoml build, model save/delete/import/export, local store changes, config writes, and server startup.
  • External or credentialed: bentoml deploy, cloud, deployment, secret, api-token, push, pull, Docker/container builds, OTLP/exporter endpoints, and cloud scaling changes.
  • Expensive or environment-specific: framework model downloads, GPU workloads, large image builds, long-running servers, and integration tests requiring Docker/cloud credentials.

Version Notes

This skill was generated from BentoML source commit 73c4dbead99be6515fa25fcd91e348ac30f5c22e on branch main and installed package version 0.0.0.post1+g73c4dbead. If the current checkout, package version, CLI flags, or public SDK signatures differ, run a DisCo refresh before relying on detailed guidance.

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

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