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models-providers

models-providers

Configure OpenAI Agents Python model settings, OpenAI providers, Responses websocket transport, third-party adapters, retries, and multi-provider routing.

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Documentación de la Skill

GitHub

name: models-providers description: "Configure OpenAI Agents Python model settings, OpenAI providers, Responses websocket transport, third-party adapters, retries, and multi-provider routing." disable-model-invocation: true metadata: disco-role: operating license: MIT

Models & Providers

Use this sub-skill when configuring model selection, provider routing, OpenAI Responses vs Chat Completions, Responses websocket transport, ModelSettings, model retries, LiteLLM, any-llm, or OpenAI-compatible endpoints.

Read First

  • Start with references/provider-reference.md for the model/provider classes, settings fields, environment variables, transport choices, and optional extras.
  • Use references/workflows.md for copyable setup patterns: default OpenAI, websocket reuse, custom OpenAI-compatible endpoints, MultiProvider prefix modes, LiteLLM/any-llm, retries, and feature validation.
  • Use references/troubleshooting.md for API key errors, wrong API path, websocket keepalive/message-size issues, Chat Completions feature gaps, namespaced model IDs, missing optional extras, and reasoning-content replay.
  • Run scripts/inspect_model_provider.py for a local no-API-call import/configuration check that masks secret values and reports optional adapter availability.

Routing Boundaries

  • Stay here for ModelSettings, OpenAIProvider, OpenAIResponsesModel, OpenAIChatCompletionsModel, responses_websocket_session(), MultiProvider, LiteLLM, any-llm, model retries, feature validation, and reasoning-content model adapter caveats.
  • Route realtime model sessions, RealtimeAgent, RealtimeRunner, audio, and voice optional extras to ../realtime-voice/SKILL.md.
  • Route runner loop behavior, handoffs, sessions, RunState, guardrails, tool execution, and turn limits to ../core-runtime/SKILL.md.
  • Route tracing processors, trace export keys, trace metadata, and sensitive trace payload controls to ../tracing-observability/SKILL.md.

Fast Decisions

  • Prefer the default OpenAI Responses path for OpenAI models and Responses-only tools.
  • Use Chat Completions only for providers/endpoints that do not support Responses, and enable strict feature validation while migrating.
  • Use responses_websocket_session() for multi-turn Responses websocket workflows that should reuse one websocket-capable provider/run config.
  • Use MultiProvider(openai_prefix_mode="model_id", unknown_prefix_mode="model_id") when an OpenAI-compatible endpoint expects literal namespaced model IDs.
  • Use LiteLLM or any-llm only when their adapter coverage/routing is needed; validate the exact upstream provider feature set before relying on structured outputs, tools, usage, or Responses-only behavior.
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