OpenAI-Compatible Chat Endpoint Integration | Kamiwaza Docs

Documentation for Kamiwaza 1.0.0

This is documentation for Kamiwaza 1.0.0, which is no longer actively maintained. For the current GA release, see 1.0.1.

Overview

Kamiwaza can register any external endpoint that speaks the OpenAI /v1/chat/completions wire format and proxy it through the same deployment, audit, and access-control surfaces as locally hosted models. This includes OpenAI directly, Microsoft Azure's OpenAI Service and AI Foundry, customer-hosted LiteLLM proxies, self-hosted vLLM or Ollama, and any other provider whose chat API matches the OpenAI shape.

Once registered, the endpoint deploys through the normal model lifecycle and exposes a Kamiwaza /v1/chat/completions route that applications can call without knowing which provider sits behind it.

Prerequisites

Before registering an OpenAI-compatible endpoint, make sure:

You have a provider API key (OpenAI key, Azure resource key, Azure AI Foundry project key, LiteLLM master key, etc.).
The model you intend to register is enabled on the account the API key belongs to. For Azure, the deployment exists in the project the URL points at.
Outbound HTTPS from the Kamiwaza control plane to the provider hostname is permitted.

Quick Start (UI)

Registration is a three-step wizard: pick the provider, configure the endpoint, then pick which discovered models to register.

In Kamiwaza, go to Models, click Add Model, then click Add external inference endpoint in the dialog header.
Source — under Where is your model hosted?, choose one of:
- OpenAI — for OpenAI directly.
- Azure — for Azure OpenAI Service or Azure AI Foundry.
- Other (OpenAI-compatible) — for LiteLLM proxies, vLLM, Ollama, or any other host whose chat API matches the OpenAI shape.

Click Next.

Setup — configure the endpoint:
- Inference endpoint URL— The provider's API root.
- Credentials — If a credential is already stored for this endpoint, Kamiwaza offers Use existing credential with a Use a different credential link to override. Otherwise paste the provider API key.

Click Connect. Kamiwaza validates the URL, authenticates with the credential, and discovers the models the endpoint exposes.

Review — Kamiwaza shows the list of models discovered on the endpoint. Tick the checkbox for each model you want to register. Expand a row to customize the display name, default parameters, or other per-model settings. Click Register N models when done.
From the Models list, deploy each newly registered model.

Test each deployment from the Models list to confirm Kamiwaza can reach the provider with the credentials you supplied before applications start calling it.

Provider examples

The wizard is the same for every provider; only the values change.

OpenAI directly

Field	Value
Source	OpenAI
Inference endpoint URL	`https://api.openai.com/v1`
Credential	OpenAI API key (`sk-…`)
Underlying model (Review step)	`gpt-5`, `gpt-4o`, `gpt-5-chat-latest`, etc.

Restricted OpenAI keys default to chat-only. If you also intend to register a transcription endpoint with the same key, widen the key's scope to include Audio first.

Azure OpenAI Service

Field	Value
Source	Azure
Inference endpoint URL	`https://<your-resource>.openai.azure.com`
Credential	Azure OpenAI resource key
Underlying model (Review step)	The Azure deployment name (e.g. `gpt-4o`)

Kamiwaza auto-detects the *.openai.azure.com host.

Azure AI Foundry

Field	Value
Source	Azure
Inference endpoint URL	`https://<your-project>.services.ai.azure.com/models`
Credential	Azure AI Foundry project key
Underlying model (Review step)	The Foundry deployment name (e.g. `Mistral-Large-3`)

Customer-hosted LiteLLM proxy

Field	Value
Source	Other (OpenAI-compatible)
Inference endpoint URL	Your published proxy URL (e.g. `https://litellm.example.com`)
Credential	The proxy's master key (or a virtual key)
Underlying model (Review step)	The model alias as configured in your LiteLLM config

Self-hosted vLLM, Ollama, or other OpenAI-compatible service

Use Other (OpenAI-compatible), paste your internal hostname, and supply whatever bearer token the service requires (or any non-empty placeholder if it's open).

Credentials

Credentials registered through the OpenAI-compatible form are encrypted on save and stored in the Kamiwaza secret catalog, keyed by base URL. For most providers the credential is a single API key string. Kamiwaza handles wrapping it in the right header based on the detected provider.

API Usage

Once deployed, the endpoint is callable via the standard Kamiwaza runtime route:

curl -X POST "https://<your-domain>/runtime/models/<deployment-id>/v1/chat/completions" \
  -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "messages": [{"role": "user", "content": "Hello"}],
    "max_tokens": 50
  }'

Operational notes

Inference errors from the upstream provider are surfaced through the Kamiwaza response body.
Multiple registered models that share a base URL share one credential in the catalog.