/v1/chat/completions or /v1/responses
as usual.
The pages in this section exist for providers whose setup is not purely
“set an API key”: auth flows that pull from cloud credentials, deployment-based
URLs, region/project requirements, dual native + OpenAI-compatible API
surfaces, or other quirks worth documenting. If a provider isn’t listed
separately, its default configuration is enough.
Supported providers
See the README provider table
for per-provider feature support (chat, Responses, embeddings, files, batches,
passthrough).
Why some providers have dedicated pages
These are the providers most users hit friction on:- Google Vertex AI — needs a GCP project, region, and either Application Default Credentials or a service-account JSON key. Multi-region or multi-account setups use suffixed env vars.
- Amazon Bedrock — no API key of its own; authenticates through the AWS credential chain (env, profile, IAM Identity Center, instance/container roles). Requires explicit model access in the Bedrock console.
- Azure OpenAI — deployment-scoped base URLs, the
api-versionquery parameter, and theapi-keyheader instead ofAuthorization: Bearer. - Oracle GenAI — requires an OCI IAM policy for
generativeaiapikeyand a region-specific OpenAI-compatible endpoint URL. - Google Gemini (AI Studio) — two routing modes (native
generateContentvs OpenAI-compatible) with different image-input behavior. - DeepSeek — reasoning effort mapping quirks for DeepSeek V4.
- Ollama / vLLM — local-model hosting with optional multi-instance setup through suffixed env vars and provider-qualified model IDs.