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serving-and-cli

serving-and-cli

Launch and operate Xinference services and model lifecycles through public CLI surfaces with safe command templates, placement notes, and troubleshooting handoffs.

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentation de la Skill

GitHub

name: serving-and-cli description: "Launch and operate Xinference services and model lifecycles through public CLI surfaces with safe command templates, placement notes, and troubleshooting handoffs." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Serving and CLI

Use this sub-skill when you need to start a local service, stand up a supervisor/worker cluster, or build safe command lines for model launch and lifecycle management.

Covers

  • Local cluster startup with xinference-local.
  • Distributed startup with xinference-supervisor and xinference-worker.
  • Top-level xinference service commands for:
    • launch
    • list
    • terminate
    • register
    • unregister
    • registrations
    • cached
    • remove-cache
    • engine
    • cal-model-mem
    • vllm-models
    • stop-cluster
    • login
  • Placement and launch flags such as:
    • --endpoint / -e
    • --model-name, --model-uid, --model-type
    • --n-worker, --n-gpu, --replica
    • --worker-ip, --gpu-idx
    • --enable-virtual-env, --disable-virtual-env
    • --virtual-env-package, --env
    • --api-key placeholders

Does not cover

  • Python client calls or HTTP/OpenAI request bodies -> client-and-api
  • Backend or model-family selection, optional engine installs, or model schema design -> models-and-backends
  • Auth database, metrics policy, environment policy, or deployment hardening -> operations-and-security

Working pattern

  1. Read references/cli-reference.md for exact command shapes.
  2. Use scripts/render_xinference_commands.py to generate copy-paste-safe templates.
  3. Read references/serving-workflows.md for local, distributed, launch, and shutdown flows.
  4. Read references/distributed-deployment.md for host/port and worker placement rules.
  5. Read references/troubleshooting.md when a command fails, blocks, or returns a validation error.

Safety rules

  • Treat bundled command text as templates, not runnable automation.
  • Real launches may download models and per-model dependencies.
  • launch requires --model-engine for LLMs.
  • Distributed placement must use full registered worker IP:port values.
  • --gpu-idx is a comma-separated list of integers.
  • Pass engine-specific extras as --key value pairs after the standard launch flags.
  • Use --enable-virtual-env or --disable-virtual-env, never both.

Bundled references

Skills enregistrées