Prehnite

Local-first, quality-gated visual asset production. No mandatory SaaS or platform fees.

Source and project README · Roadmap · Changelog · Issues

Prehnite is an MIT-licensed Python CLI and optional MCP integration for batch image generation, masks/cutouts, technical validation, targeted repair, stateful replay, quality evidence, and reproducible export. It orchestrates image models; it does not include model weights, a photorealistic image generator, or a subscription service.

Quick start: no-cost local test

Requires Python 3.11 or later.

python -m pip install prehnite
prehnite init --destination my-first-batch
prehnite doctor
prehnite --help

The init command creates local starter configuration, but does not run model inference or incur fees. For a sample batch, follow the source repository's two-minute demo.

For a sample zero-cost batch, follow the up-to-date project README and onboarding guide.

What is actually implemented

• CLI, strict manifest/profile validation, stage journal, bounded attempts and safe archive/export paths.
• Offline synthetic demo flow, reports and reproducible zero-cost validation.
• Experimental local ComfyUI adapter and opt-in prehnite-micro recipe binding with immutable batch identity. You must separately install ComfyUI and supply licensed checkpoints and compatible graphs. No real GPU model/cutout quality or 4K VRAM tier is certified.
• Optional paid inference connectors require explicit operator-selected profiles, permissions and budgets. Installing Prehnite does not authorize any cloud uploads or paid API calls.
• prehnite-macro is currently a read-only workflow blueprint, not an installed or benchmarked high-quality image pipeline.

See the implementation/evidence roadmap, recipe contract and public release history.

Release quality and licensing

The initial 0.1.0 alpha is an early developer preview, not production certified. Passing synthetic CI does not prove realistic image quality, legal rights to separate checkpoints, accepted cutout accuracy, stable public APIs or physical GPU suitability.

Prehnite code: MIT. Checkpoint weights, providers and third-party assets are governed by their own licenses and usage terms. The package contains no bundled checkpoint/model weights.