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name: cli-and-serving description: "Operate DiscoArt command-line, YAML execution, Jina serving, endpoint polling/control, and Docker/Jupyter runtime planning." disable-model-invocation: true metadata: disco-role: operating license: NOASSERTION

CLI and Serving

Use this sub-skill when the task asks to use python -m discoart, export or run a YAML file from the command line, launch or tune DiscoArt as a Jina service, call /create//result//skip//stop, or plan Docker/Jupyter GPU execution.

Route first

• CLI command syntax, stdin/file behavior, service flow YAML, endpoint calls, Jina Client/curl shapes, Docker/Jupyter notes: read CLI and serving reference.
• YAML/stdin mistakes, blocked servers, polling mismatches, Jina issues, GPU/OOM, floating requests, and port/protocol confusion: read Troubleshooting.
• Python create(**kwargs) parameter meanings, outputs, DocumentArray post-processing, generation runtime, and model/cache behavior belong to ../artwork-generation/SKILL.md.
• Prompt schema, YAML parameter semantics, schedules, default config editing, and config validation belong to ../configuration-and-prompts/SKILL.md.
• Maintainer release automation, CI scripts, shell release helpers, and packaging publication are out of scope.

Quick workflow

1. Decide whether the request is a local CLI run, a persistent service run, or a Docker/Jupyter runtime plan. Do not start image generation or a long-lived server unless the user explicitly asks and the GPU/cache/time budget is clear.
2. For local CLI config export, use python -m discoart config [EXPORT_YAML_FILE]. With no output path, the default YAML is printed to stdout.
3. For local CLI generation, use python -m discoart create [YAML_CONFIG_FILE]. With no file path, create reads YAML from stdin; avoid leaving it waiting on an interactive terminal by accident.
4. For serving, generate or edit a Jina Flow YAML, then run python -m discoart serve [FLOW_YAML_FILE]. The command loads the flow and blocks the terminal until interrupted.
5. For HTTP clients, post JSON to the Jina gateway /post route with execEndpoint. Use a stable name_docarray in /create if the workflow needs /result polling.
6. For gRPC or non-HTTP gateways, use jina.Client(...).post(endpoint, parameters=...); the service endpoints remain /create, /result, /skip, and /stop.
7. For Docker, preserve bind mounts for working output and model cache, pass GPU access explicitly, and carry required environment variables such as DISCOART_OUTPUT_DIR, DISCOART_CACHE_DIR, DISCOART_DEFAULT_PARAMETERS_YAML, and WANDB_MODE into the container.
8. Verify safely with parser/config/help smoke tests and the bundled helper's --help; do not run full generation, Docker, or persistent service checks by default.

Fast validation anchors

• Root parser usage is python -m discoart [-h] [-v] {create,config,serve} ....
• config accepts optional EXPORT_YAML_FILE and defaults to stdout.
• create accepts optional YAML_CONFIG_FILE and defaults to stdin.
• serve accepts optional FLOW_YAML_FILE and defaults to DiscoArt's packaged Jina flow.
• Service executor endpoints are /create, /skip, and /stop; result polling endpoint is /result.
• The default flow uses HTTP port 51001, monitoring port 51002, DiscoArtExecutor, ResultPoller, replicas: 1, and floating: false.
• The bundled helper at scripts/service_config_helper.py prints flow YAML only; it never launches a server, downloads models, opens ports, or writes files by default.