WaveSpeed CLI

SkillMedia

Generate, edit, animate, upscale, or transform AI media using the WaveSpeed CLI from Codex. Use when the user asks to create image, video, audio, 3D, TTS, marketing creatives, or to inspect/run WaveSpeed models.

Use WaveSpeed CLI in Claude, ChatGPT or Ahel Desktop

Free. Sign in, add WaveSpeed CLI and connect your AI. About a minute.

Also: Claude Code · Cursor · Codex

Then ask your AI: use the WaveSpeed CLI skill

Details

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

WaveSpeed CLIStart free

What this skill tells your AI

The instructions your AI receives, as published by hashgraph-online/awesome-codex-plugins in plugins/WaveSpeedAI/codex-plugin-wavespeed-cli/skills/wavespeed-cli/SKILL.md and read by ahel’s review.

Use the wavespeed CLI to run WaveSpeed image, video, audio, and 3D models. Every generation uses the same flow: search the live catalog, inspect the model schema, then run the model with explicit inputs.

This plugin also starts the WaveSpeed MCP server. Its tools map one-to-one onto the CLI commands below: search_models = wavespeed models, get_model_schema = wavespeed schema, get_price = wavespeed price, upload_file = wavespeed upload, run_model = wavespeed run, get_prediction = wavespeed show, get_balance = wavespeed balance. Prefer the MCP tools for single generations; use the CLI when it is installed and the user wants batch or scripted runs. Both share the same login.

Before Running

Check whether the CLI is available:

wavespeed --version

If it is missing, run this plugin helper:

./plugins/wavespeed-cli/scripts/install-wavespeed-cli.sh

Check auth before generation:

wavespeed status

If the user is not signed in, ask them to run wavespeed login. Do not ask the user to paste an API key into chat. For CI or one-off shells, WAVESPEED_API_KEY may be set in the environment.

Standard Flow

# 1. Search the live catalog.
wavespeed models "nano banana"
wavespeed models --type image-to-video
wavespeed models --type text-to-video
wavespeed models --type text-to-audio
wavespeed models --type text-to-3d

# 2. Inspect dynamic inputs for the selected model.
wavespeed run google/nano-banana-2/text-to-image -h

# 3. Run with --json so Codex can parse outputs.
wavespeed run google/nano-banana-2/text-to-image \
  -p "a cyberpunk skyline at golden hour" \
  -i aspect_ratio="16:9" \
  -i resolution="2k" \
  --json

wavespeed run --json returns machine-readable fields such as model, prompt, outputs, saved, elapsed_ms, and raw. Use output URLs directly when the user wants links. Add --download when the user wants local files.

Recommended Starting Models

Use caseModel
Text to imagegoogle/nano-banana-2/text-to-image
Image editgoogle/nano-banana-2/edit
Text to videowavespeed-ai/minimax-h3/text-to-video (cheap open-weights default; bytedance/seedance-2.5/text-to-video for the highest quality)
Image to videowavespeed-ai/minimax-h3/image-to-video (bytedance/seedance-2.5/image-to-video for the highest quality)

These are defaults, not a fixed list. Browse alternatives with wavespeed models <query> and inspect each selected model before running it.

Files

Local file paths are not automatically uploaded. Upload files first, then pass returned URLs into generation commands.

wavespeed upload ./input.jpg --json
wavespeed run google/nano-banana-2/edit \
  -p "replace the background with a sunlit kitchen" \
  -i images='["https://..."]' \
  --json

Save generated outputs locally:

wavespeed run google/nano-banana-2/text-to-image \
  -p "minimal product photo on a glass table" \
  --download "./wavespeed-output/{index}.{ext}" \
  --json

Project Config

wavespeed init creates wavespeed.json with shared defaults and aliases.

  • defaultModel lets wavespeed run -p "..." omit the model argument.
  • aliases bundle a model with default inputs.
  • wavespeed aliases lists configured aliases.
  • CLI flags override alias defaults.

The CLI never rewrites the user's prompt or inputs.

Pitfalls

  • Do not invent model IDs. Confirm with wavespeed models or wavespeed schema <model>.
  • Prefer --json for runs, uploads, and any command that will be parsed.
  • Use structured inputs via -i key=value; inspect model help for exact names and accepted values.
  • Some models require uploaded asset URLs, not local paths.

Signals

GitHub stars
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Forks
316
Last commit
Oct 2026
Advanced
Item type
skill
Key
wavespeed-cli
Source
github.com/hashgraph-online/awesome-codex-plugins