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client-and-api

client-and-api

Use Xinference sync and async Python clients, model handles, and HTTP/OpenAI-compatible APIs safely.

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentation de la Skill

GitHub

name: client-and-api description: "Use Xinference sync and async Python clients, model handles, and HTTP/OpenAI-compatible APIs safely." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Client and API

Use this sub-skill when a task is about calling a running Xinference service from Python, cURL, the OpenAI SDK, or another HTTP client. It assumes the target model has already been launched and identified by a model UID.

Use this for

  • Client, AsyncClient, RESTfulClient, and AsyncRESTfulClient usage.
  • launch_model, register_model, list_models, get_model, and terminate_model client signatures.
  • Model handles for chat, text generation, embeddings, rerank, images, audio, video, and flexible model requests.
  • Service-root versus /v1 OpenAI-compatible base URL selection.
  • Streaming response iterators and async iterator handoffs.
  • API key headers and endpoint placeholders in examples.
  • Request-shape validation, including strict system-message ordering and integer-like replica validation.

Route away when needed

  • Service startup, model lifecycle CLI commands, and supervisor/worker cluster orchestration: serving-and-cli.
  • Model family, engine, format, quantization, optional extras, LoRA, or custom model JSON decisions: models-and-backends.
  • Auth database bootstrap, OIDC, admin policy, audit logs, metrics, Web UI, or deployment hardening: operations-and-security.

Working pattern

  1. Confirm the service endpoint root, for example http://<host>:9997.
  2. Confirm the model UID returned by launch/list operations.
  3. Pick the API surface:
    • Xinference Python client: endpoint root.
    • OpenAI-compatible SDK/cURL: endpoint root plus /v1.
    • Direct HTTP family endpoints: use the family-specific reference.
  4. Add Authorization: Bearer <token-or-api-key> only when auth is enabled.
  5. Keep examples placeholder-only until the user supplies a real endpoint, model UID, and API key policy.
  6. If a request fails, classify the failure as endpoint/base-url, auth, model-UID, request-shape, streaming, or backend/model-readiness before changing code.

Core rules

  • A launched model UID is required for every request family.
  • The OpenAI-compatible base URL should end in /v1; the Xinference Client constructor uses the service root.
  • RESTfulClient is a compatibility alias for Client; AsyncRESTfulClient is an alias for AsyncClient.
  • In this inspected build, the sync Client.launch_model exposes virtual-env launch knobs that the async launch signature does not mirror exactly. Check references/api-reference.md before assuming parity.
  • Treat rerank as a Xinference HTTP/client workflow, not a universal OpenAI SDK helper.
  • Do not make live network calls from bundled helper scripts; they render snippets only.

References

  • API reference for verified signatures and model handle method notes.
  • OpenAI-compatible API for /v1 base URL shape and request-family templates.
  • Client workflows for sync/async launch, list/get, model handle, streaming, and registration flows.
  • Troubleshooting for 401/403, 404, strict message order, replica, streaming, and OCR response issues.

Snippet helper

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