nanoframes

SVG-first, browserless, deterministic frame rendering on ThorVG.

nanoframes is an offline counterpart to hyperframes: the same idea — write a frame, render a video, built for agents — but without a browser. Compositions are authored as SVG documents plus a small declarative animation timeline, and every frame is rasterized deterministically by ThorVG (thorvg-python) to PNG, then muxed to MP4 with FFmpeg.

Because nothing depends on a browser, an AI agent can render a frame or a whole clip locally in milliseconds and iterate fast: check → preview → render.

Status

v1 complete. Full offline pipeline works end-to-end: init → check → render/preview → video. SVG compositions + declarative keyframe timeline are rendered deterministically by ThorVG; MP4 export via ffmpeg; visual snapshots guard regressions. Text auto-layout (measured chips, wrap, curve, fit) + a bundled monospace CJK font (Sarasa Mono SC, ligatures stripped) for solid Chinese.

Layout

docs/             architecture + composition contract
examples/         `.nf.svg` compositions
skills/nanoframes/ SKILL.md — the agent production loop
nanoframes/       package (model, parser, timeline, bake, render, lint, cli, video)
tests/            unit + render + snapshot + CLI tests

Docs

• Architecture — why SVG + ThorVG, the pipeline, scope decisions.
• Composition — the .nf.svg contract (timing attributes + animation timeline).
• Text capabilities — measured chips/wrap/curve/fit, bundled CJK font, text_handler escape hatch.

docs/ and skills/ also ship inside the pip wheel (nanoframes/docs, nanoframes/skills); running nanoframes with no arguments prints where the docs and the agent skill live — repo checkout or installed package alike.