openclaw/docs/providers/sglang.md

summary, read_when, title

summary	read_when	title
Run OpenClaw with SGLang (OpenAI-compatible self-hosted server)	You want to run OpenClaw against a local SGLang server You want OpenAI-compatible /v1 endpoints with your own models	SGLang

SGLang serves open-weight models via an OpenAI-compatible HTTP API. OpenClaw connects to SGLang using the openai-completions provider family with auto-discovery of available models.

Property	Value
Provider id	sglang
Plugin	bundled, enabledByDefault: true
Auth env var	SGLANG_API_KEY (any non-empty value if server has no auth)
Onboarding flag	--auth-choice sglang
API	OpenAI-compatible (openai-completions)
Default base URL	http://127.0.0.1:30000/v1
Default model placeholder	sglang/Qwen/Qwen3-8B
Streaming usage	Yes (supportsStreamingUsage: true)
Pricing	Marked external-free (modelPricing.external: false)

OpenClaw also auto-discovers available models from SGLang when you opt in with SGLANG_API_KEY and you do not define an explicit models.providers.sglang entry — see Model discovery (implicit provider) below.

Getting started

Launch SGLang with an OpenAI-compatible server. Your base URL should expose `/v1` endpoints (for example `/v1/models`, `/v1/chat/completions`). SGLang commonly runs on:

- `http://127.0.0.1:30000/v1`

Any value works if no auth is configured on your server:

```bash
export SGLANG_API_KEY="sglang-local"
```

```bash openclaw onboard ```

Or configure the model manually:

```json5
{
  agents: {
    defaults: {
      model: { primary: "sglang/your-model-id" },
    },
  },
}
```

Model discovery (implicit provider)

When SGLANG_API_KEY is set (or an auth profile exists) and you do not define models.providers.sglang, OpenClaw will query:

• GET http://127.0.0.1:30000/v1/models

and convert the returned IDs into model entries.

If you set `models.providers.sglang` explicitly, auto-discovery is skipped and you must define models manually.

Explicit configuration (manual models)

Use explicit config when:

• SGLang runs on a different host/port.
• You want to pin contextWindow/maxTokens values.
• Your server requires a real API key (or you want to control headers).

{
  models: {
    providers: {
      sglang: {
        baseUrl: "http://127.0.0.1:30000/v1",
        apiKey: "${SGLANG_API_KEY}",
        api: "openai-completions",
        models: [
          {
            id: "your-model-id",
            name: "Local SGLang Model",
            reasoning: false,
            input: ["text"],
            cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
            contextWindow: 128000,
            maxTokens: 8192,
          },
        ],
      },
    },
  },
}

Advanced configuration

SGLang is treated as a proxy-style OpenAI-compatible `/v1` backend, not a native OpenAI endpoint.

| Behavior | SGLang |
|----------|--------|
| OpenAI-only request shaping | Not applied |
| `service_tier`, Responses `store`, prompt-cache hints | Not sent |
| Reasoning-compat payload shaping | Not applied |
| Hidden attribution headers (`originator`, `version`, `User-Agent`) | Not injected on custom SGLang base URLs |

**Server not reachable**

Verify the server is running and responding:

```bash
curl http://127.0.0.1:30000/v1/models
```

**Auth errors**

If requests fail with auth errors, set a real `SGLANG_API_KEY` that matches
your server configuration, or configure the provider explicitly under
`models.providers.sglang`.

<Tip>
If you run SGLang without authentication, any non-empty value for
`SGLANG_API_KEY` is sufficient to opt in to model discovery.
</Tip>

Related

Choosing providers, model refs, and failover behavior. Full config schema including provider entries.