AI导哈

后端与数据库

databricks-model-serving

databricks/data…t-skills

Databricks Model Serving endpoint lifecycle and ops. Use when asked to: CRUD serving endpoints (CLI or MLflow Deployments client); configure traffic routing for A/B / canary deploys and zero-downtime version swaps; retrieve OpenAPI schemas; inspect logs, metrics, or permissions; manage legacy AI Gateway rate limits (not Unity Gateway); discover Foundation Model API endpoints at runtime; integrate endpoints into Databricks Apps; or stream from off-platform clients (Vercel AI SDK v6, standalone Node.js). NOT for: Unity Gateway CRUD and management (databricks-unity-gateway), training, MLflow autologging, UC registration, custom PyFunc/ResponsesAgent authoring (databricks-ml-training); no-code document / data agents incl. legacy Knowledge Assistants & Supervisor Agents (databricks-genie-agents); MLflow evaluation (databricks-mlflow-evaluation).

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安装命令

npx skills add https://github.com/databricks/databricks-agent-skills --skill databricks-model-serving

SKILL.md

Model Serving Endpoints

FIRST: Use the parent databricks-core skill for CLI basics, authentication, and profile selection.

Gateway boundary: This skill owns legacy AI Gateway configuration attached to a Model Serving endpoint, such as serving-endpoints put-ai-gateway. An explicit Unity Gateway / Unity AI Gateway request or any databricks ai-gateway model service, MCP service, or model provider service belongs to databricks-unity-gateway.

Model Serving provides managed endpoints for serving LLMs, custom ML models, and external models as scalable REST APIs. Endpoints are identified by name (unique per workspace).

Endpoint Types

Type When to Use Key Detail
Pay-per-token Foundation Model APIs (Llama, GPT-5, Claude, Gemini, etc.) Uses system.ai.* catalog models, pre-provisioned in every workspace. Discover at runtime — see Foundation Model API endpoints below.
Provisioned throughput Dedicated GPU capacity Guaranteed throughput, higher cost
Custom model Your own MLflow models or containers Deploy any model with an MLflow signature

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