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การเข้าถึงหน้านี้ต้องได้รับการอนุญาต คุณสามารถลอง ลงชื่อเข้าใช้หรือเปลี่ยนไดเรกทอรีได้
การเข้าถึงหน้านี้ต้องได้รับการอนุญาต คุณสามารถลองเปลี่ยนไดเรกทอรีได้
The databricks-ai-runtime agent skill gives AI coding agents, such as Claude Code, Cursor, and Codex, instructions for working with AI Runtime through the databricks air Databricks CLI commands. With the skill installed, you can ask your agent to write a workload YAML, submit a GPU training run, and check its progress.
Requirements
- The Databricks CLI, authenticated to your workspace. The skill's examples use the flattened
code_sourceformat, which requires Databricks CLI version 1.20.0 or above. - A workspace with AI Runtime enabled. See Requirements.
Install the skill
Run the following command:
databricks aitools install --skills-only --skills databricks-ai-runtime
Follow the prompts to choose your AI agent and installation scope. For installation options, see aitools command group.
What the skill covers
| Capability | What the agent can do |
|---|---|
| Write workloads | Turn a request into a workload YAML with compute, environment, code source, and the launch command for your framework, such as torchrun, Accelerate, or DeepSpeed. |
| Configure runs | Set environment variables, secrets, hyperparameters, retries, and permissions. |
| Submit runs | Validate the config with --dry-run, then submit with databricks air run and an idempotency key. |
| Check and monitor runs | Get status with databricks air get and databricks air list, stream logs with databricks air logs, and point you to the MLflow run for metrics. |
| Cancel runs | Cancel one, several, or all of your active runs with databricks air cancel. |
| Debug failures | Pull logs from a failed run and surface the error. |
| Use custom Docker images | Build and push a custom image, then reference it in the workload. |