---
title: "Adding a custom LLM provider"
description: "Create a custom provider definition in OpenWork Cloud and import it into the desktop app"
---
Use this when the provider is not in the catalog. The Cloud dashboard stores the shared credential once and then lets desktop workspaces import it.
## Create the custom provider
1. Open `LLM Providers`.
2. Click `Add Provider`.
3. Switch to `Custom provider`.
4. Give it a `Name` (the `Provider ID` fills in automatically).
5. Enter the `Base URL` of the OpenAI-compatible endpoint (for Azure AI Foundry this looks like `https://my-resource.openai.azure.com/openai/v1`).
6. List the `Model IDs` the endpoint serves — on Azure AI Foundry these are your deployment names.
7. Paste the shared `API key / credential`.
8. Choose `People access` and/or `Team access`.
9. Click `Create Provider`.
That's it — no JSON required for OpenAI-compatible endpoints.
### Advanced: raw JSON config
If the provider needs more than the form covers (a different AI SDK package, per-model limits or modalities, custom options), click `Advanced: edit as JSON` and provide a models.dev-style definition. The JSON must include `id`, `name`, `npm`, `env`, and `models`; `api` is optional, but most OpenAI-compatible providers use it. The editor requires valid JSON, at least one environment variable, and at least one model.
```json
{
"id": "custom-provider",
"name": "Custom Provider",
"npm": "@ai-sdk/openai-compatible",
"env": [
"CUSTOM_PROVIDER_API_KEY"
],
"doc": "https://example.com/docs/models",
"api": "https://api.example.com/v1",
"models": [
{
"id": "custom-provider/example-model",
"name": "Example Model",
"attachment": false,
"reasoning": false,
"tool_call": true,
"structured_output": true,
"temperature": true,
"release_date": "2026-01-01",
"last_updated": "2026-01-01",
"open_weights": false,
"limit": {
"context": 128000,
"input": 128000,
"output": 8192
},
"modalities": {
"input": [
"text"
],
"output": [
"text"
]
}
}
]
}
```
## Import it into the desktop app
1. Open `Settings > Cloud Providers`.
2. Choose the correct `Active org`.
3. Under `Cloud providers`, click `Import`.
4. Reload the workspace when OpenWork asks.
### Functional example: an LLM gateway (Infron)
An LLM gateway is one OpenAI-compatible endpoint that fans out to many model providers. If you want to run the routing yourself, [LiteLLM](https://infron.ai/docs/frameworks-and-integrations/litellm) is a good starting point. [Infron](https://infron.ai) is the hosted option: one API key gets you every model in its [marketplace](https://infron.ai/models) with automatic provider fallbacks and a single invoice, so adding a new LLM to OpenWork is just another entry under `models`.
Grab a key from the [API Keys dashboard](https://infron.ai/dashboard/apiKeys). If you don't have an account yet, sign up at [infron.ai/login](https://infron.ai/login) and their [quickstart](https://infron.ai/docs/overview/quickstart/text) walks you through your first request.
Paste the key into `API key / credential` and use this JSON:
```json
{
"id": "infron",
"name": "Infron",
"npm": "@ai-sdk/openai-compatible",
"env": [
"INFRON_API_KEY"
],
"doc": "https://infron.ai/docs/frameworks-and-integrations/openwork",
"api": "https://llm.onerouter.pro/v1",
"models": [
{
"id": "deepseek/deepseek-v3.2",
"name": "DeepSeek V3.2",
"attachment": false,
"reasoning": true,
"tool_call": true,
"structured_output": true,
"temperature": true,
"release_date": "2025-09-29",
"last_updated": "2025-09-29",
"open_weights": true,
"limit": {
"context": 128000,
"input": 128000,
"output": 8192
},
"modalities": {
"input": ["text"],
"output": ["text"]
}
}
]
}
```
Once imported, Infron models show up in the Chat model picker alongside everything else:
Pick the model and it's live in the session footer:
Add more entries under `models` to expose other routes the gateway supports (e.g. `openai/gpt-5.4`, `google/gemini-2.5-flash`).
## When to use a cloud provider
Use a Cloud provider when the setup is meant to be shared across an org or team. For solo use, configuring it directly in the desktop app is simpler.