Skip to main content

Documentation Index

Fetch the complete documentation index at: https://docs.openclaw.ai/llms.txt

Use this file to discover all available pages before exploring further.

openclaw infer is the canonical headless surface for provider-backed inference workflows. It intentionally exposes capability families, not raw gateway RPC names and not raw agent tool ids.

​
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 should:
  • map common user intents to the correct infer subcommand
  • include a few canonical infer examples for the workflows it covers
  • prefer openclaw infer ... in examples and suggestions
  • avoid re-documenting the entire infer surface inside the skill body
Typical infer-focused skill coverage:
  • openclaw infer model run
  • openclaw infer image generate
  • openclaw infer audio transcribe
  • openclaw infer tts convert
  • openclaw infer web search
  • openclaw infer embedding create

​
Why use infer

openclaw infer provides one consistent CLI for provider-backed inference tasks inside OpenClaw. Benefits:
  • Use the providers and models already configured in OpenClaw instead of wiring up one-off wrappers for each backend.
  • Keep model, image, audio transcription, TTS, video, web, and embedding workflows under one command tree.
  • Use a stable --json output shape for scripts, automation, and agent-driven workflows.
  • Prefer a first-party OpenClaw surface when the task is fundamentally “run inference.”
  • Use the normal local path without requiring the gateway for most infer commands.
For end-to-end provider checks, prefer openclaw infer ... once lower-level provider tests are green. It exercises the shipped CLI, config loading, default-agent resolution, bundled plugin activation, and the shared capability runtime before the provider request is made.

​
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
    status
    enable
    disable
    set-provider

  video
    generate
    describe
    providers

  web
    search
    fetch
    providers

  embedding
    create
    providers

​
Common tasks

This table maps common inference tasks to the corresponding infer command.
TaskCommandNotes
Run a text/model promptopenclaw infer model run --prompt "..." --jsonUses the normal local path by default
Run a model prompt on imagesopenclaw infer model run --prompt "Describe this" --file ./image.png --model provider/modelRepeat --file for multiple image inputs
Generate an imageopenclaw infer image generate --prompt "..." --jsonUse image edit when starting from an existing file
Describe an image fileopenclaw infer image describe --file ./image.png --prompt "..." --json--model must be an image-capable <provider/model>
Transcribe audioopenclaw infer audio transcribe --file ./memo.m4a --json--model must be <provider/model>
Synthesize speechopenclaw infer tts convert --text "..." --output ./speech.mp3 --jsontts status is gateway-oriented
Generate a videoopenclaw infer video generate --prompt "..." --jsonSupports provider hints such as --resolution
Describe a video fileopenclaw infer video describe --file ./clip.mp4 --json--model must be <provider/model>
Search the webopenclaw infer web search --query "..." --json
Fetch a web pageopenclaw infer web fetch --url https://example.com --json
Create embeddingsopenclaw infer embedding create --text "..." --json

​
Behavior

  • openclaw infer ... is the primary CLI surface for these workflows.
  • Use --json when the output will be consumed by another command or script.
  • Use --provider or --model provider/model when a specific backend is required.
  • For image describe, audio transcribe, and video describe, --model must use the form <provider/model>.
  • For image describe, an explicit --model runs that provider/model directly. The model must be image-capable in the model catalog or provider config. codex/<model> runs a bounded Codex app-server image-understanding turn; openai-codex/<model> uses the OpenAI Codex OAuth provider path.
  • Stateless execution commands default to local.
  • Gateway-managed state commands default to gateway.
  • The normal local path does not require 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 accepts image files, detects their MIME type, and sends them with the supplied prompt to the selected model. Repeat --file for multiple images.
  • model run --file rejects non-image inputs. Use infer audio transcribe for audio files and infer video describe for video files.
  • model run --gateway exercises Gateway routing, saved auth, provider selection, and the embedded runtime, but still runs as a raw model probe: it sends the supplied prompt and any image attachments without prior session transcript, bootstrap/AGENTS context, context-engine assembly, tools, or bundled MCP servers.
  • model run --gateway --model <provider/model> requires a trusted operator gateway credential because the request asks the Gateway to run a one-off provider/model override.

​
Model

Use model for provider-backed 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 providers --json
openclaw infer model inspect --name gpt-5.5 --json
Use full <provider/model> refs to smoke-test a specific provider without starting the Gateway or loading the full 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-small-latest --prompt "Reply with exactly: pong" --json
openclaw infer model run --local --model openai/gpt-4.1 --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 because, for non-Codex providers, it sends only the supplied prompt to the selected model.
  • openai-codex/* local probes are the narrow exception: OpenClaw adds a minimal system instruction so the Codex Responses transport can populate its required instructions field, without adding full agent context, tools, memory, or session transcript.
  • Local model run --file keeps that lean path and attaches image content directly to the single user message. Common image files such as PNG, JPEG, and WebP work when their MIME type is detected as image/*; unsupported or unrecognized files fail before the provider is called.
  • model run --file is best when you want to test the selected multimodal text model directly. Use infer image describe when you want OpenClaw’s image-understanding provider selection and default image-model routing.
  • 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 local providers or the Gateway are called.
  • Local model run exits non-zero when the provider returns no text output, so unreachable local providers and empty completions do not look like successful probes.
  • Use model run --gateway when you need to test Gateway routing, agent-runtime setup, or Gateway-managed provider state while keeping the model input raw. Use openclaw agent or chat surfaces when you want the full agent context, tools, memory, and session transcript.
  • model auth login, model auth logout, and model auth status manage saved provider auth state.

​
Image

Use image for 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 --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 ./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-4.1-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.
  • Use --size, --aspect-ratio, or --resolution with image edit for providers/models that support geometry hints on reference-image edits.
  • Use --output-format png --background transparent with --model openai/gpt-image-1.5 for transparent-background OpenAI PNG output; --openai-background remains available as an OpenAI-specific alias. Providers that do not declare background support report the hint as an ignored override.
  • Use image providers --json to verify which bundled image providers are discoverable, configured, selected, and which generation/edit capabilities each provider exposes.
  • Use image generate --model <provider/model> --json as the narrowest live CLI smoke for image generation changes. Example: 
    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 JSON 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 to give the vision model a task-specific instruction such as OCR, comparison, UI inspection, or concise captioning.
  • Use --timeout-ms with slow local vision models or cold Ollama starts.
  • For image describe, --model must be an image-capable <provider/model>.
  • 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

Use audio for file transcription. 
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
Notes:
  • audio transcribe is for file transcription, not realtime session management.
  • --model must be <provider/model>.

​
TTS

Use tts for speech synthesis and TTS provider 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 status --json
Notes:
  • tts status defaults to gateway because it reflects gateway-managed TTS state.
  • Use tts providers, tts voices, and tts set-provider to inspect and configure TTS behavior.

​
Video

Use video for 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-4.1-mini --json
Notes:
  • video generate accepts --size, --aspect-ratio, --resolution, --duration, --audio, --watermark, and --timeout-ms and forwards them to the video-generation runtime.
  • --model must be <provider/model> for video describe.

​
Web

Use web for search and fetch workflows. 
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
Notes:
  • Use web providers to inspect available, configured, and selected providers.

​
Embedding

Use embedding for 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": []
}
Top-level fields are stable:
  • ok
  • capability
  • transport
  • provider
  • model
  • attempts
  • outputs
  • 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

​
Notes

  • openclaw capability ... is an alias for openclaw infer ....