openclaw-openclaw/docs/cli/infer.md

summary, read_when, title

summary	read_when	title
Infer-first CLI for provider-backed model, image, audio, TTS, video, web, and embedding workflows	Adding or modifying `openclaw infer` commands Designing stable headless capability automation	Inference CLI

openclaw infer is the canonical headless surface for provider-backed inference. It exposes capability families (model, image, audio, tts, video, web, embedding), not raw gateway RPC names or agent tool ids. openclaw capability ... is an alias for the same command tree.

Reasons to prefer it over a one-off provider wrapper:

• Reuses providers and models already configured in OpenClaw.
• Stable --json envelope for scripts and agent-driven automation (see JSON output).
• Runs the normal local path without the gateway for most subcommands.
• For end-to-end provider checks, it exercises the shipped CLI, config loading, default-agent resolution, bundled plugin activation, and the shared capability runtime before the provider request goes out.

Turn infer into a skill

Copy and paste this to an agent:

Read https://docs.openclaw.ai/cli/infer, then create a skill that routes my common workflows to `openclaw infer`.
Focus on model runs, image generation, video generation, audio transcription, TTS, web search, and embeddings.

A good infer-based skill maps common user intents to the right subcommand, includes a few canonical examples per workflow, prefers openclaw infer ... over lower-level alternatives, and does not re-document the entire infer surface in the skill body.

Command tree

 openclaw infer
  list
  inspect

  model
    run
    list
    inspect
    providers
    auth login
    auth logout
    auth status

  image
    generate
    edit
    describe
    describe-many
    providers

  audio
    transcribe
    providers

  tts
    convert
    voices
    providers
    personas
    status
    enable
    disable
    set-provider
    set-persona

  video
    generate
    describe
    providers

  web
    search
    fetch
    providers

  embedding
    create
    providers

infer list / infer inspect --name <capability> show this tree as data (capability id, transports, description).

Common tasks

Task	Command	Notes
Run a text/model prompt	openclaw infer model run --prompt "..." --json	Local by default
Run a model prompt on images	openclaw infer model run --prompt "Describe this" --file ./image.png --model provider/model	Repeat --file for multiple images
Generate an image	openclaw infer image generate --prompt "..." --json	Use image edit when starting from an existing file
Describe an image file or URL	openclaw infer image describe --file ./image.png --prompt "..." --json	--model must be an image-capable <provider/model>
Transcribe audio	openclaw infer audio transcribe --file ./memo.m4a --json	--model must be <provider/model>
Synthesize speech	openclaw infer tts convert --text "..." --output ./speech.mp3 --json	tts status only runs through the gateway
Generate a video	openclaw infer video generate --prompt "..." --json	Supports provider hints such as --resolution
Describe a video file	openclaw infer video describe --file ./clip.mp4 --json	--model must be <provider/model>
Search the web	openclaw infer web search --query "..." --json
Fetch a web page	openclaw infer web fetch --url https://example.com --json
Create embeddings	openclaw infer embedding create --text "..." --json

Behavior

• Use --json when the output feeds another command or script; text output otherwise.
• Use --provider or --model provider/model to pin a specific backend.
• Use model run --thinking <level> for a one-shot thinking/reasoning override: off, minimal, low, medium, high, adaptive, xhigh, or max.
• For image describe, audio transcribe, and video describe, --model must use the form <provider/model>.
• For image describe, --file accepts local paths and HTTP(S) URLs; remote URLs go through the normal media-fetch SSRF policy.
• Stateless execution commands (model run, image *, audio *, video *, web *, embedding *) default to local. Gateway-managed state commands (tts status) default to gateway.
• The local path never requires the gateway to be running.
• Local model run is a lean one-shot provider completion: it resolves the configured agent model and auth but does not start a chat-agent turn, load tools, or open bundled MCP servers.
• model run --file attaches image files (auto-detected MIME type) to the prompt; repeat --file for multiple images. Non-image files are rejected — use infer audio transcribe or infer video describe instead.
• model run --gateway exercises Gateway routing, saved auth, provider selection, and the embedded runtime, but stays a raw model probe: no prior session transcript, bootstrap/AGENTS context, tools, or bundled MCP servers.
• model run --gateway --model <provider/model> requires a trusted-operator gateway credential, because it asks the Gateway to run a one-off provider/model override.

Model

Text inference and model/provider inspection.

openclaw infer model run --prompt "Reply with exactly: smoke-ok" --json
openclaw infer model run --prompt "Summarize this changelog entry" --model openai/gpt-5.4 --json
openclaw infer model run --prompt "Describe this image in one sentence" --file ./photo.jpg --model google/gemini-2.5-flash --json
openclaw infer model run --prompt "Use more reasoning here" --thinking high --json
openclaw infer model providers --json
openclaw infer model inspect --model gpt-5.5 --json

Use full <provider/model> refs with --local to smoke-test one provider without starting the Gateway or loading the agent tool surface:

openclaw infer model run --local --model anthropic/claude-sonnet-4-6 --prompt "Reply with exactly: pong" --json
openclaw infer model run --local --model cerebras/zai-glm-4.7 --prompt "Reply with exactly: pong" --json
openclaw infer model run --local --model google/gemini-2.5-flash --prompt "Reply with exactly: pong" --json
openclaw infer model run --local --model groq/llama-3.1-8b-instant --prompt "Reply with exactly: pong" --json
openclaw infer model run --local --model mistral/mistral-medium-3-5 --prompt "Reply with exactly: pong" --json
openclaw infer model run --local --model mistral/mistral-small-latest --prompt "Reply with exactly: pong" --json
openclaw infer model run --local --model openai/gpt-5.5 --prompt "Reply with exactly: pong" --json
openclaw infer model run --local --model ollama/qwen2.5vl:7b --prompt "Describe this image." --file ./photo.jpg --json

Notes:

• Local model run is the narrowest CLI smoke for provider/model/auth health: for non-ChatGPT-Codex providers it sends only the supplied prompt.
• Local model run --model <provider/model> can resolve exact bundled static-catalog rows (the same rows openclaw models list --all shows) before that provider is written to config. Provider auth is still required; missing credentials fail as auth errors, not Unknown model.
• For Mistral Medium 3.5 reasoning probes, leave temperature unset/default. Mistral rejects reasoning_effort="high" with temperature: 0; use default temperature or a non-zero value such as 0.7.
• OpenAI ChatGPT/Codex OAuth (openai-chatgpt-responses API) local probes add a minimal system instruction so the transport can populate its required instructions field — no full agent context, tools, memory, or session transcript.
• model run --file attaches image content directly to the single user message. Common formats (PNG, JPEG, WebP) work when MIME type is detected as image/*; unsupported or unrecognized files fail before the provider is called. Use infer image describe instead when you want OpenClaw's image-model routing and fallbacks rather than a direct multimodal-model probe.
• The selected model must support image input; text-only models may reject the request at the provider layer.
• model run --prompt must contain non-whitespace text; empty prompts are rejected before any provider or Gateway call.
• Local model run exits non-zero when the provider returns no text output, so unreachable providers and empty completions do not look like successful probes.
• Use model run --gateway to test Gateway routing or agent-runtime setup while keeping the model input raw. Use openclaw agent or a chat surface for full agent context, tools, memory, and session transcript.
• --thinking adaptive maps to the completion-runtime level medium; --thinking max maps to max for OpenAI models that support the native max effort, otherwise xhigh.
• model auth login, model auth logout, and model auth status manage saved provider auth state.

Image

Generation, edit, and description.

openclaw infer image generate --prompt "friendly lobster illustration" --json
openclaw infer image generate --prompt "cinematic product photo of headphones" --json
openclaw infer image generate --model openai/gpt-image-1.5 --output-format png --background transparent --prompt "simple red circle sticker on a transparent background" --json
openclaw infer image generate --model openai/gpt-image-2 --quality low --openai-moderation low --prompt "low-cost draft poster" --json
openclaw infer image generate --prompt "slow image backend" --timeout-ms 180000 --json
openclaw infer image edit --file ./logo.png --model openai/gpt-image-1.5 --output-format png --background transparent --prompt "keep the logo, remove the background" --json
openclaw infer image edit --file ./poster.png --prompt "make this a vertical story ad" --size 2160x3840 --aspect-ratio 9:16 --resolution 4K --json
openclaw infer image describe --file ./photo.jpg --json
openclaw infer image describe --file https://example.com/photo.png --json
openclaw infer image describe --file ./receipt.jpg --prompt "Extract the merchant, date, and total" --json
openclaw infer image describe-many --file ./before.png --file ./after.png --prompt "Compare the screenshots and list visible UI changes" --json
openclaw infer image describe --file ./ui-screenshot.png --model openai/gpt-5.4-mini --json
openclaw infer image describe --file ./photo.jpg --model ollama/qwen2.5vl:7b --prompt "Describe the image in one sentence" --timeout-ms 300000 --json

Notes:

• Use image edit when starting from existing input files; --size, --aspect-ratio, or --resolution add geometry hints on providers/models that support them.

• --output-format png --background transparent with --model openai/gpt-image-1.5 gives transparent-background OpenAI PNG output; --openai-background is an OpenAI-specific alias for the same hint. Providers that do not declare background support report it as an ignored override (see ignoredOverrides in the JSON envelope).

• --quality low|medium|high|auto works for providers that support image-quality hints, including OpenAI. OpenAI also accepts --openai-moderation low|auto.

• image providers --json lists which bundled image providers are discoverable, configured, selected, and which generation/edit capabilities each exposes.

• image generate --model <provider/model> --json is the narrowest live smoke for image-generation changes:

  openclaw infer image providers --json
  openclaw infer image generate \
    --model google/gemini-3.1-flash-image-preview \
    --prompt "Minimal flat test image: one blue square on a white background, no text." \
    --output ./openclaw-infer-image-smoke.png \
    --json
  

  The response reports ok, provider, model, attempts, and written output paths. When --output is set, the final extension may follow the provider's returned MIME type.

• For image describe and image describe-many, use --prompt for a task-specific instruction (OCR, comparison, UI inspection, concise captioning).

• Use --timeout-ms for slow local vision models or cold Ollama starts.

• For image describe, an explicit --model (must be an image-capable <provider/model>) runs first, then tries configured agents.defaults.imageModel.fallbacks if that call fails. Input-preparation errors (missing file, unsupported URL) fail before any fallback attempt, and the model must be image-capable in the model catalog or provider config.

• For local Ollama vision models, pull the model first and set OLLAMA_API_KEY to any placeholder value, for example ollama-local. See Ollama.

Audio

File transcription (not realtime session management).

openclaw infer audio transcribe --file ./memo.m4a --json
openclaw infer audio transcribe --file ./team-sync.m4a --language en --prompt "Focus on names and action items" --json
openclaw infer audio transcribe --file ./memo.m4a --model openai/whisper-1 --json

--model must be <provider/model>.

TTS

Speech synthesis and TTS provider/persona state.

openclaw infer tts convert --text "hello from openclaw" --output ./hello.mp3 --json
openclaw infer tts convert --text "Your build is complete" --output ./build-complete.mp3 --json
openclaw infer tts providers --json
openclaw infer tts personas --json
openclaw infer tts status --json

Notes:

• tts status only supports --gateway (it reflects gateway-managed TTS state).
• Use tts providers, tts voices, tts personas, tts set-provider, and tts set-persona to inspect and configure TTS behavior.

Video

Generation and description.

openclaw infer video generate --prompt "cinematic sunset over the ocean" --json
openclaw infer video generate --prompt "slow drone shot over a forest lake" --resolution 768P --duration 6 --json
openclaw infer video describe --file ./clip.mp4 --json
openclaw infer video describe --file ./clip.mp4 --model openai/gpt-5.4-mini --json

Notes:

• video generate accepts --size, --aspect-ratio, --resolution, --duration, --audio, --watermark, and --timeout-ms, forwarded to the video-generation runtime.
• --model must be <provider/model> for video describe.

Web

Search and fetch.

openclaw infer web search --query "OpenClaw docs" --json
openclaw infer web search --query "OpenClaw infer web providers" --json
openclaw infer web fetch --url https://docs.openclaw.ai/cli/infer --json
openclaw infer web providers --json

web providers lists available, configured, and selected providers for search and fetch.

Embedding

Vector creation and embedding-provider inspection.

openclaw infer embedding create --text "friendly lobster" --json
openclaw infer embedding create --text "customer support ticket: delayed shipment" --model openai/text-embedding-3-large --json
openclaw infer embedding providers --json

JSON output

Infer commands normalize JSON output under a shared envelope:

{
  "ok": true,
  "capability": "image.generate",
  "transport": "local",
  "provider": "openai",
  "model": "gpt-image-2",
  "attempts": [],
  "outputs": []
}

Stable top-level fields:

• ok
• capability
• transport
• provider
• model
• attempts
• inputs (image attachments sent with the request, when applicable)
• outputs
• ignoredOverrides (hint keys a provider does not support, when applicable)
• error

For generated media commands, outputs contains files written by OpenClaw. Use the path, mimeType, size, and any media-specific dimensions in that array for automation instead of parsing human-readable stdout.

Common pitfalls

# Bad
openclaw infer media image generate --prompt "friendly lobster"

# Good
openclaw infer image generate --prompt "friendly lobster"

# Bad
openclaw infer audio transcribe --file ./memo.m4a --model whisper-1 --json

# Good
openclaw infer audio transcribe --file ./memo.m4a --model openai/whisper-1 --json

Related

• CLI reference
• Models