Limn

Turn rough ideas into production-ready image prompts for any T2I model, with one command.

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Limn translates plain ideas into model-optimized prompts for text-to-image generation. Pick a target model, describe what you want, and Limn rewrites your concept using that model's preferred syntax — tag‑based for SDXL, natural prose for FLUX, cinematic language for Wan‑Image, and more.

Built for developers, designers, and anyone who needs production-quality image prompts without studying each model's prompting quirks.

Features

• One prompt, any model — FLUX, SDXL, Nano Banana Pro, Seedream‑4, Z‑Image Turbo, Chroma, Qwen Image, and Wan‑Image. Limn rewrites your idea for whichever syntax that model expects.
• Transform or generate — Optimize prompts only, or go all the way with Replicate-backed image generation. Get back a WebP file with full cost and timing analytics.
• Per-model prompt intelligence — Every model profile encodes real prompting rules: tag‑based for SDXL, prose for FLUX, reasoning‑first structure for Nano Banana Pro. No guesswork.
• Cost analytics built-in — Token counts, generation time, and OpenRouter plus Replicate costs displayed after every run. JSON output captures every number for automation.
• Smart API key management — Keys resolve from environment variables or OS keychain. No plaintext dotfiles. Secret values are redacted by default.
• Programmatic API — Call limn(), limnGenerate(), or instantiate the Limn class with keys passed directly. TypeScript‑first with full type coverage.
• Inline image preview — Terminals that support it render the generated image inside the console after generation.
• Model catalog API — getSupportedModelCatalog() exposes all model metadata. Drive downstream selectors and validators from Limn's canonical model definitions.

Quick Start

Install and generate your first image:

npm i -g @telepat/limn
limn settings set openrouterApiKey sk-or-...
limn settings set replicateApiKey r8_...
limn -m flux "a cat in space" --generate

Expected outcome:

• Limn transforms your prompt into FLUX-optimized syntax via OpenRouter.
• Replicate generates and saves a timestamped .webp to the current directory.
• Cost and timing analytics are displayed after every run.

Requirements

• Node.js 20+
• npm
• OpenRouter API key
• Replicate API token (for generation)

How It Works

Limn loads a per-model profile that encodes the preferred prompt syntax for that T2I model. It sends your raw prompt — plus the profile's system instructions — to an LLM via OpenRouter. The LLM returns a model-optimized prompt. Optionally, Limn sends that prompt to Replicate for image generation.

Core commands:

# Transform only
limn -m sdxl "a cat in space"

# Transform and generate
limn -m flux "a cat in space" --generate

# JSON output
limn -m flux "a cat in space" --generate --json

# Custom aspect ratio
limn -m flux "a cat in space" --generate --aspect-ratio 16:9

# Override Replicate model
limn -m flux "a cat in space" --generate --replicate-model black-forest-labs/flux-2-pro

# List model options (including supported aspect ratios)
limn -m seedream-4 "a cat in space" --list-options

Aspect Ratio Support

All models support 1:1, 16:9, and 9:16 universally. Each model also supports additional ratios depending on its capabilities — Limn validates the chosen ratio before sending it to Replicate, so you get a clear error immediately if the ratio is unsupported by that model.

Use --list-options on any model to see its full set of supported aspect ratios.

Per-model prompting strategies are documented in the Prompting Guide.

Using With AI Agents

Limn is designed for agentic and automated workflows:

• Machine-readable output — --json returns structured JSON for both transform-only and generate runs. Every field is typed and predictable.
• Programmatic API — The library exports limn() and limnGenerate() for functional use, plus the Limn class for object‑oriented workflows with injected API keys. No interactive prompts required.
• CI‑ready — Pass keys via OPENROUTER_API_KEY and REPLICATE_API_TOKEN environment variables, or through the Limn constructor. No keychain or interactive settings command needed.
• Model catalog API — getSupportedModelCatalog() exposes canonical model metadata for downstream tooling and runtime validation.

Security and Trust

• API keys are stored in the OS keychain by default via limn settings.
• In CI or containerized environments, use OPENROUTER_API_KEY and REPLICATE_API_TOKEN environment variables.
• Set LIMN_DISABLE_KEYTAR=true when keychain access is unavailable.
• limn settings list redacts secret values as ***configured***.
• Generated images are model-produced output. Review images before publishing.

To report a security issue, see the security policy or open a private report through the repository security flow.

Documentation and Support

• Repository
• Prompting Guide
• npm package
• Issues

Contributing

Contributions are welcome. Open an issue or pull request on GitHub.

License

MIT. See LICENSE.