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ai-cli

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Generate text, images, video, and audio from the terminal using AI models.

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Source SKILL.md: https://github.com/vercel-labs/ai-cli/blob/HEAD/skills/ai-cli/SKILL.md

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ai-cli

Generate text, images, video, and audio from the terminal using AI models.

When to Use

Use when you need to:

  • Generate images from text prompts or existing images
  • Generate video from text prompts or images
  • Generate text (summaries, explanations, code reviews) from prompts or piped content
  • Generate speech from text or transcribe audio files and streams
  • Compare outputs across multiple models side-by-side
  • Build composable media pipelines by chaining commands via stdin/stdout

Prerequisites

Requires AI_GATEWAY_API_KEY or a provider-specific key (e.g. OPENAI_API_KEY) in the environment.

Commands

ai text "explain this code"              # generate text
ai image "a sunset over mountains"       # generate an image
ai video "a spinning triangle"           # generate a video
ai audio speak "hello"                   # generate speech
ai audio transcribe recording.mp3        # transcribe audio
ai models --type audio                   # list speech and transcription models

Key Flags

-m, --model <id>       Model ID (provider/name or short name), comma-separated for multi-model
-o, --output <path>    Output file or directory
-n, --count <n>        Number of generations per model
-q, --quiet            Suppress progress output
--json                 Output structured metadata as JSON (paths, timing, success/failure)

Piping Patterns

Chain commands for agent workflows:

# Pipe content in for summarization
cat file.txt | ai text "summarize this"
git diff | ai text "write a commit message"

# Image-to-video pipeline
ai image "a dragon" | ai video "animate this"

# Image editing via stdin
cat photo.png | ai image "make it a watercolor"

# Audio workflows
echo "Ship the changelog" | ai audio speak -o changelog.mp3
cat recording.mp3 | ai audio transcribe -o transcript.txt

Structured Output

Use --json to get machine-readable results:

ai image "a sunset" --json

Returns:

{
  "elapsed_ms": 3420,
  "count": 1,
  "results": [
    {
      "index": 1,
      "model": "openai/gpt-image-2",
      "elapsed_ms": 3420,
      "success": true,
      "file": "/path/to/resp_abc123.png"
    }
  ]
}

Multi-Model Comparison

ai image "a sunset" -m "openai/gpt-image-1,bfl/flux-2-pro,xai/grok-imagine-image"

Output Behavior

  • Interactive (TTY): saves to file, prints path to stderr
  • Piped (non-TTY): writes raw content to stdout for chaining
  • -o <dir>: saves inside directory with auto-generated names

When the CLI chooses a filename, it uses a response ID when available and falls back to a random 8-character ID, such as resp_abc123.png or 7f3a9c1d.mp3.

Important for agents: Always use -o to save to a file when generating images, video, or speech audio. Without -o in a non-TTY context, raw binary data is written to stdout, which wastes context and is not useful for agents. Use -o output.png, -o speech.mp3, or an output directory and read the file path from --json output instead.

Timeouts

  • text: 120 seconds
  • image: 300 seconds
  • video: 300 seconds
  • audio speak: 120 seconds
  • audio transcribe: 120 seconds

Exit Codes

  • 0 — success
  • 1 — all generations failed
  • 2 — partial failure (some succeeded)