--- summary: "Run OpenClaw through inferrs (OpenAI-compatible local server)" read_when: - You want to run OpenClaw against a local inferrs server - You are serving Gemma or another model through inferrs - You need the exact OpenClaw compat flags for inferrs title: "Inferrs" --- [inferrs](https://github.com/ericcurtin/inferrs) serves local models behind an OpenAI-compatible `/v1` API. OpenClaw talks to it through the generic `openai-completions` adapter. | Property | Value | | ------------------ | -------------------------------------------------------------------- | | Provider id | `inferrs` (custom; configure under `models.providers.inferrs`) | | Plugin | none — not a bundled OpenClaw provider plugin | | Auth env var | none required; any value works if your inferrs server has no auth | | API | OpenAI-compatible (`openai-completions`) | | Suggested base URL | `http://127.0.0.1:8080/v1` (or wherever your inferrs server listens) | `inferrs` is a custom self-hosted OpenAI-compatible backend, not a dedicated OpenClaw provider plugin: you configure it under `models.providers.inferrs` instead of picking an onboarding auth choice. For a bundled plugin with auto-discovery, see [SGLang](/providers/sglang) or [vLLM](/providers/vllm). ## Getting started ```bash inferrs serve google/gemma-4-E2B-it \ --host 127.0.0.1 \ --port 8080 \ --device metal ``` ```bash curl http://127.0.0.1:8080/health curl http://127.0.0.1:8080/v1/models ``` Add an explicit provider entry and point your default model at it. See the config example below. ## Full config example Gemma 4 on a local `inferrs` server: ```json5 { agents: { defaults: { model: { primary: "inferrs/google/gemma-4-E2B-it" }, models: { "inferrs/google/gemma-4-E2B-it": { alias: "Gemma 4 (inferrs)", }, }, }, }, models: { mode: "merge", providers: { inferrs: { baseUrl: "http://127.0.0.1:8080/v1", apiKey: "inferrs-local", api: "openai-completions", models: [ { id: "google/gemma-4-E2B-it", name: "Gemma 4 E2B (inferrs)", reasoning: false, input: ["text"], cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 }, contextWindow: 131072, maxTokens: 4096, compat: { requiresStringContent: true, }, }, ], }, }, }, } ``` ## On-demand startup OpenClaw can start `inferrs` itself only when an `inferrs/...` model is selected. Add `localService` to the same provider entry: ```json5 { models: { providers: { inferrs: { baseUrl: "http://127.0.0.1:8080/v1", apiKey: "inferrs-local", api: "openai-completions", timeoutSeconds: 300, localService: { command: "/opt/homebrew/bin/inferrs", args: [ "serve", "google/gemma-4-E2B-it", "--host", "127.0.0.1", "--port", "8080", "--device", "metal", ], healthUrl: "http://127.0.0.1:8080/v1/models", readyTimeoutMs: 180000, idleStopMs: 0, }, models: [ { id: "google/gemma-4-E2B-it", name: "Gemma 4 E2B (inferrs)", reasoning: false, input: ["text"], cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 }, contextWindow: 131072, maxTokens: 4096, compat: { requiresStringContent: true, }, }, ], }, }, }, } ``` `command` must be an absolute path. Run `which inferrs` on the Gateway host and use that path. Full field reference: [Local model services](/gateway/local-model-services). ## Advanced configuration Some `inferrs` Chat Completions routes accept only string `messages[].content`, not structured content-part arrays. If OpenClaw runs fail with: ```text messages[1].content: invalid type: sequence, expected a string ``` set `compat.requiresStringContent: true` in the model entry. OpenClaw then flattens pure text content parts into plain strings before sending the request. Some `inferrs` + Gemma combinations accept small direct `/v1/chat/completions` requests but fail on full OpenClaw agent-runtime turns. Try disabling the tool schema surface first: ```json5 compat: { requiresStringContent: true, supportsTools: false } ``` That reduces prompt pressure on stricter local backends. If tiny direct requests still work but normal OpenClaw agent turns keep crashing inside `inferrs`, treat it as an upstream model/server limitation rather than an OpenClaw transport issue. Test both layers once configured: ```bash curl http://127.0.0.1:8080/v1/chat/completions \ -H 'content-type: application/json' \ -d '{"model":"google/gemma-4-E2B-it","messages":[{"role":"user","content":"What is 2 + 2?"}],"stream":false}' ``` ```bash openclaw infer model run \ --model inferrs/google/gemma-4-E2B-it \ --prompt "What is 2 + 2? Reply with one short sentence." \ --json ``` If the first command works but the second fails, see Troubleshooting below. Because `inferrs` uses the generic `openai-completions` adapter (not `openai-responses`), native-OpenAI-only request shaping never applies: no `service_tier`, no Responses `store`, no prompt-cache hints, and no OpenAI reasoning-compat payload shaping get sent. ## Troubleshooting `inferrs` is not running, not reachable, or not bound to the host/port you configured. Confirm the server is started and listening on that address. Set `compat.requiresStringContent: true` in the model entry (see above). Set `compat.supportsTools: false` to disable the tool schema surface (see the Gemma caveat above). If schema errors are gone but `inferrs` still crashes on larger agent turns, treat it as an upstream `inferrs` or model limitation. Reduce prompt pressure or switch backend/model. For general help, see [Troubleshooting](/help/troubleshooting) and [FAQ](/help/faq). ## Related Running OpenClaw against local model servers. Starting local model servers on demand for configured providers. Debugging local OpenAI-compatible backends that pass probes but fail agent runs. Overview of all providers, model refs, and failover behavior.