domains / families / general / routerbase-model-gateway

routerbase-model-gateway

combined

Integrate and route AI model requests through RouterBase. Use when migrating OpenAI-compatible clients, choosing model IDs, configuring fallbacks, or building chat, image, video, audio, speech, and embedding workflows. Integrate RouterBase as an OpenAI-compatible model gateway for routing GPT, Claude, Gemini, media, audio, and embedding requests.

When to use

• The user wants to migrate an OpenAI SDK or OpenAI-compatible integration to RouterBase.
• The user needs a model routing plan across cost, latency, quality, context length, streaming, tool calling, JSON mode, or vision requirements.
• The user is adding chat, image, video, audio, speech, or embedding calls to an application.
• The user is debugging RouterBase auth, endpoint, model ID, streaming, media, or payload issues.
• The user needs documentation or a smoke-test checklist for a RouterBase integration.
• Use when migrating an OpenAI-compatible client to RouterBase by changing the base URL and model ID.
• Use when selecting primary and fallback models for chat, reasoning, vision, media generation, audio, or embeddings.
• Use when debugging RouterBase request setup, headers, environment variables, streaming, tool calls, JSON mode, or multimodal payloads.

When not to use

• This skill does not replace RouterBase account configuration, live model catalog checks, or production observability.
• Some model features are provider-specific and must be tested with the exact selected model.
• High-stakes outputs still require human review and domain-specific evaluation.

Skill page

Conflict

Both copies describe the same RouterBase OpenAI-compatible gateway integration, but each contains material steps the other lacks. The davepoon copy provides a detailed debug checklist, a specific output contract, and guardrails for high-impact use cases. The sickn33 copy provides a structured four-step workflow (classify workload, configure client, validate model IDs via live catalog, design fallbacks), a live catalog curl command, and a retryable-error classification pattern. Crowning one would hide the other's unique validation and debugging procedures.