James RussoandClaude Opus 4.7 5d264e146c docs(lambda): document webm support + simplify-review fixes (#953)
* docs(lambda): document webm support in distributed mode

PR 8.4 of the WebM distributed-rendering plan (v1.5 backlog #1; see
DISTRIBUTED-RENDERING-PLAN.md §7.2). User-facing docs catch up with the
shipped capability.

Updates docs/deploy/migrating-to-hyperframes-lambda.mdx:

- "Output format" row in the migration table now lists `webm` alongside
  mp4 / mov / png-sequence with a note that webm uses libvpx-vp9 +
  closed-GOP concat-copy. HDR mp4 remains the only refused format.

- "No webm distributed" caveat replaced with "webm uses closed-GOP VP9"
  explainer covering the encoder args (`-g <chunkSize>`,
  `-keyint_min <chunkSize>`, `-auto-alt-ref 0`, `-cpu-used 2`), why
  alt-ref disable is load-bearing, and that the output preserves alpha
  via yuva420p with Opus audio.

- Migration checklist no longer asks adopters to filter out webm
  compositions; only HDR-dependent renders need to stay on the previous
  framework.

aws-lambda.mdx doesn't currently call out webm as unsupported (only HDR
in the v1 surface list), so it gets no copy edits beyond the migration
guide.

The internal planning doc (DISTRIBUTED-RENDERING-PLAN.md §7.2, §8,
§12 — kept outside the repo) gets matching updates: format support
matrix flipped ✓, v1.5 backlog #1 marked shipped, HDR promoted to the
new top item, and the rev-12 → rev-13 status line.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* refactor: address simplify-review findings on webm stack

Folds in cleanups identified by a multi-agent code-review pass over the
4-PR webm-distributed stack:

- plan.ts: `resolveEncoderTriple()` webm case now calls
  `getEncoderPreset(quality, "webm")` for its preset string instead of
  hardcoding "good". The hardcode was wrong for `quality: "draft"`
  (`getEncoderPreset` returns "realtime" for that tier) — would have
  silently overridden the draft → realtime mapping for distributed webm
  renders.
- chunkEncoder.ts: trim the new VP9 closed-GOP comment block from ~18
  lines of WHY narration down to the 6 lines that actually explain why
  (alt-ref + cpu-used drift). Match the alpha branch's idempotent-push
  comment to the same standard.
- chunkEncoder.test.ts: drop the duplicate WHY comment that restated
  the implementation comment in plain words.
- webm-concat-copy.test.ts: rewrite the file-header docstring to
  describe the contract being tested instead of the PR-8.1-gating
  history; strip "PR 8.2 / Path A / Path B" references from error
  messages (they belong in PR bodies, not in test output). Consolidate
  the yuva420p alpha smoke into a single `it()` block (was a full
  4-test describe with duplicated setup) — the yuv420p block already
  covers the probe/decode/frame-count contract; the alpha smoke only
  needs to prove the alpha args don't break concat-copy.
- plan.test.ts: drop the "PR 8.1 proved the contract" comment.
- webm-vp9 fixture: drop the aspirational "Other webm-with-audio
  fixtures cover the mux path separately when added" sentence (no
  other fixtures exist). Regenerated the baseline via
  `docker:test:update webm-vp9` to reflect the updated comment.
- migrating-to-hyperframes-lambda.mdx: add a paragraph about
  distributed webm's perf cost — ~10-25% larger files at constant CRF
  due to forced keyframes, and slower per-chunk encode due to
  `-cpu-used 2` being more conservative than the libvpx default.

All unit tests + the webm-vp9 distributed-simulated regression still
pass after these changes.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* fix(cli): accept --format=webm in `hyperframes lambda render`

The CLI's `lambda render` subcommand's FORMATS allowlist and the
`RenderArgs.format` type still narrowed to `mp4 | mov | png-sequence`,
so even though the producer + aws-lambda packages now support webm
end-to-end, the CLI surface rejected it with `--format must be mp4|mov|
png-sequence`. Add webm to both spots and update the --help description.

Surfaced during real-AWS deploy prep — the local lambda-local /
distributed-simulated tests didn't go through the CLI so the gap went
unnoticed.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* fix(producer): font cache writes to /tmp on Lambda (read-only \$HOME)

The deterministic Google Fonts cache was rooted at
`\$HOME/.cache/hyperframes/fonts`, which fails on AWS Lambda — the
runtime's `\$HOME` resolves to a `/home/sbx_*` directory tree that's
read-only. `mkdirSync(..., { recursive: true })` can't create that
path and the plan stage trips with `ENOENT: no such file or directory,
mkdir '/home/sbx_user1051/.cache/hyperframes/fonts/space-mono'` on
every Lambda render that pulls a Google Font (i.e. every distributed
fixture using `@import url("https://fonts.googleapis.com/...")`).

Detect Lambda via `\$AWS_LAMBDA_FUNCTION_NAME` and route the cache to
`tmpdir()/hyperframes/fonts` in that case. Lambda's `/tmp` survives
across invocations on a warm container, so cache hit rate is the same
as non-Lambda runs. Also honor an explicit
`\$HYPERFRAMES_FONT_CACHE_DIR` override for adopters who want a
different location regardless of the runtime.

Surfaced while verifying webm distributed end-to-end on real AWS — the
same bug affects mp4 fixtures using Google Fonts; webm just happened to
be the one I tried first.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* refactor: extract DistributedFormat type + trim font-cache resolver

Second simplify-review pass on the webm stack flagged two cleanups:

1. **`DistributedFormat` type duplicated 10 times.** Every file in the
   distributed pipeline carried its own copy of
   `"mp4" | "mov" | "png-sequence" | "webm"` — adding a new format
   meant a 10-place edit with no compile-time guarantee they stayed in
   sync. Extract a single source of truth in
   `packages/producer/src/services/distributed/shared.ts`, re-export
   from `@hyperframes/producer/distributed` and
   `@hyperframes/aws-lambda/sdk`, and have all callers pull from
   there. The aws-lambda `ALLOWED_FORMATS` runtime tuple and the CLI's
   `FORMATS` tuple now both use `satisfies readonly DistributedFormat[]`
   so the compiler enforces the runtime allowlist stays in sync with
   the type.

2. **`deterministicFonts.ts` font-cache resolver was over-commented.**
   Trim the 7-line block to 4 lines (drop the aspirational
   "and other read-only-FS execution environments" — only Lambda is
   detected — and the warm-container `/tmp` persistence narration —
   anyone reading already knows Lambda /tmp semantics). Collapse the
   two-step `if (explicit && explicit.length > 0)` into a single
   nullish-coalesce expression now that the empty-string defensive
   check is gone (`process.env.X` is `string | undefined`, no third
   shape to guard against).

Out-of-scope skips (called out by the agents, deferred):
- In-process `RenderConfig.format` and the in-process CLI's
  `render.ts` format union still carry their own inline copies. The
  union happens to coincide today but they're separate concerns —
  leaving them alone limits this PR's blast radius.
- `fontCacheDir(slug)` / `resolveFontCacheRoot()` naming asymmetry
  flagged as taste; skipping.
- Pre-existing redundant `existsSync` before `mkdirSync({ recursive:
  true })` in `fontCacheDir` — out of scope.

All tests + typecheck still pass. Lambda render still works
end-to-end (no functional changes).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* docs(lambda): drop plan-doc reference from migration checklist

PR review feedback: source/docs should not mention the
distributed-rendering planning doc. Tighten the migration checklist
sentence to describe the webm path directly rather than referencing
the doc's version label.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* refactor(producer): split resolveEncoderTriple into mp4 + non-mp4 helpers

CI Fallow audit on PR #953 flagged `resolveEncoderTriple` at CRAP 31.6 —
the function interleaved (a) mp4 codec validation + dispatch, (b) the
non-mp4 codec-rejection throw, and (c) per-format dispatch. Splitting
into `resolveMp4EncoderTriple` + `resolveNonMp4EncoderTriple` drops the
top-level function's cyclomatic complexity below the threshold while
preserving every error message and code path. Behavior unchanged.

Also extracts an `EncoderTriple` type alias so the three functions
share the return shape declaratively rather than repeating it.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

---------

Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-19 04:11:26 -04:00
2026-05-18 20:07:08 +00:00
2026-03-21 22:43:56 -07:00

HyperFrames

npm version npm downloads License Node.js Discord

Write HTML. Render video. Built for agents.

HyperFrames demo — HTML code on the left transforms into a rendered video on the right

Hyperframes is an open-source video rendering framework that lets you create, preview, and render HTML-based video compositions — with first-class support for AI agents.

Quick Start

Install the HyperFrames skills, then describe the video you want:

npx skills add heygen-com/hyperframes

This teaches your agent (Claude Code, Cursor, Gemini CLI, Codex) how to write correct compositions, GSAP timelines, Tailwind v4 browser-runtime styles, and first-party adapter animations. In Claude Code, the skills register as slash commands — invoke /hyperframes to author compositions, /hyperframes-cli for the dev-loop commands (init, lint, preview, render), /hyperframes-media for asset preprocessing (TTS, transcription, background removal), /tailwind for init --tailwind projects, /gsap for timeline animation help, or the adapter skills (/animejs, /css-animations, /lottie, /three, /waapi) when a composition uses those runtimes.

For Claude Design, open docs/guides/claude-design-hyperframes.md on GitHub and click the download button (↓) to save it, then attach the file to your Claude Design chat. It produces a valid first draft; refine in any AI coding agent. See the Claude Design guide.

For Codex specifically, the same skills are also exposed as an OpenAI Codex plugin — sparse-install just the plugin surface:

codex plugin marketplace add heygen-com/hyperframes --sparse .codex-plugin --sparse skills --sparse assets

For Claude Code, the repo also ships a Claude Code plugin manifest: test it locally with claude --plugin-dir .. The manifest intentionally omits skills because Claude Code auto-discovers the root skills/ directory by convention, and for marketplace submission use the title HyperFrames by HeyGen plus the black/white icon assets at assets/claude-code-icon-dark.svg and assets/claude-code-icon-light.svg for the two theme slots. For Cursor, the same skills are packaged as a Cursor plugin — install from the Cursor Marketplace, or sideload by cloning this repo and pointing Settings → Plugins → Load unpacked at the repo root.

Try it: example prompts

Copy any of these into your agent to get started. The /hyperframes prefix loads the skill context explicitly so you get correct output the first time.

Cold start — describe what you want:

Using /hyperframes, create a 10-second product intro with a fade-in title, a background video, and background music.

Warm start — turn existing context into a video:

Take a look at this GitHub repo https://github.com/heygen-com/hyperframes and explain its uses and architecture to me using /hyperframes.

Summarize the attached PDF into a 45-second pitch video using /hyperframes.

Turn this CSV into an animated bar chart race using /hyperframes.

Format-specific:

Make a 9:16 TikTok-style hook video about [topic] using /hyperframes, with bouncy captions synced to a TTS narration.

Iterate — talk to the agent like a video editor:

Make the title 2x bigger, swap to dark mode, and add a fade-out at the end.

Add a lower third at 0:03 with my name and title.

The agent handles scaffolding, animation, and rendering. See the prompting guide for more patterns.

Option 2: Start a project manually

npx hyperframes init my-video
cd my-video
npx hyperframes preview      # preview in browser (live reload)
npx hyperframes render       # render to MP4

hyperframes init installs skills automatically, so you can hand off to your AI agent at any point.

Requirements: Node.js >= 22, FFmpeg

Why Hyperframes?

  • HTML-native — compositions are HTML files with data attributes. No React, no proprietary DSL.
  • AI-first — agents already speak HTML. The CLI is non-interactive by default, designed for agent-driven workflows.
  • Deterministic rendering — same input = identical output. Built for automated pipelines.
  • Frame Adapter pattern — bring your own animation runtime (GSAP, Lottie, CSS, Three.js).

Hyperframes vs Remotion

Hyperframes is inspired by Remotion — we used Remotion at HeyGen in production, learned a ton from it, and kept attribution comments in the source for the patterns it pioneered (Chrome launch flags, image2pipe → FFmpeg streaming, frame buffering). Both tools drive headless Chrome and both are deterministic. They differ on one decision: what the primary author writes. Remotion's bet is React components; Hyperframes' bet is HTML.

Hyperframes Remotion
Authoring HTML + CSS + GSAP React components (TSX)
Build step None; index.html plays as-is Required (bundler)
Library-clock animations (GSAP, Anime.js, Motion One) Seekable, frame-accurate Plays at wall-clock during render
Arbitrary HTML / CSS passthrough Paste and animate Rewrite as JSX
Distributed rendering Single-machine today Lambda, production-ready

Licensing: fully open source vs source-available

Hyperframes is completely open source under Apache 2.0 — an OSI-approved license. Use it commercially at any scale, with no per-render fees, no seat caps, no company-size thresholds.

Remotion is source-available, not open source. The code is on GitHub under a custom Remotion License that requires a paid company license above small-team thresholds. It's a great product with a real team behind it — but if open-source licensing matters to you (OSI compliance, redistribution rights, no per-use fees), that's a first-order decision point.

Full write-up with benchmarks, an honest list of where each tool wins, and a GSAP side-by-side: Hyperframes vs Remotion guide.

How It Works

Define your video as HTML with data attributes:

<div id="stage" data-composition-id="my-video" data-start="0" data-width="1920" data-height="1080">
  <video
    id="clip-1"
    data-start="0"
    data-duration="5"
    data-track-index="0"
    src="intro.mp4"
    muted
    playsinline
  ></video>
  <img
    id="overlay"
    class="clip"
    data-start="2"
    data-duration="3"
    data-track-index="1"
    src="logo.png"
  />
  <audio
    id="bg-music"
    data-start="0"
    data-duration="9"
    data-track-index="2"
    data-volume="0.5"
    src="music.wav"
  ></audio>
</div>

Preview instantly in the browser. Render to MP4 locally or in Docker.

Catalog

50+ ready-to-use blocks and components — social overlays, shader transitions, data visualizations, and cinematic effects:

npx hyperframes add flash-through-white   # shader transition
npx hyperframes add instagram-follow      # social overlay
npx hyperframes add data-chart            # animated chart

Browse the full catalog at hyperframes.heygen.com/catalog.

Documentation

Full documentation at hyperframes.heygen.com/introduction — Quickstart | Guides | API Reference | Catalog

Packages

Package Description
hyperframes CLI — create, preview, lint, and render compositions
@hyperframes/core Types, parsers, generators, linter, runtime, frame adapters
@hyperframes/engine Seekable page-to-video capture engine (Puppeteer + FFmpeg)
@hyperframes/producer Full rendering pipeline (capture + encode + audio mix)
@hyperframes/studio Browser-based composition editor UI
@hyperframes/player Embeddable <hyperframes-player> web component
@hyperframes/shader-transitions WebGL shader transitions for compositions

Skills

HyperFrames ships skills that teach AI agents framework-specific patterns that generic docs don't cover.

npx skills add heygen-com/hyperframes
Skill What it teaches
hyperframes HTML composition authoring, captions, TTS, audio-reactive animation, transitions
hyperframes-cli Dev-loop CLI: init, lint, inspect, preview, render, doctor
hyperframes-media Asset preprocessing: tts (Kokoro), transcribe (Whisper), remove-background (u2net) — voice/model/codec selection
hyperframes-registry Block and component installation via hyperframes add
website-to-hyperframes Capture a URL and turn it into a video — full website-to-video pipeline
remotion-to-hyperframes Translate a Remotion (React) composition into a HyperFrames HTML composition
gsap GSAP timelines for HyperFrames: paused registration, deterministic seeking, easing, sequencing, performance
animejs Anime.js animations and timelines registered on window.__hfAnime for deterministic HyperFrames seeking
css-animations CSS keyframe animation patterns that HyperFrames can discover, pause, and seek
lottie lottie-web and dotLottie players registered on window.__hfLottie with local assets and paused playback
three Three.js scenes that render from HyperFrames hf-seek events and window.__hfThreeTime instead of wall-clock time
waapi Web Animations API element.animate() patterns seeked through document.getAnimations()

Contributing

See CONTRIBUTING.md for guidelines.

Cloning the repo

The repo uses Git LFS for golden regression-test baselines under packages/producer/tests/**/output.mp4 (~240 MB of .mp4 files). If you're cloning the full repo for development, install Git LFS first:

# macOS
brew install git-lfs

# Ubuntu/Debian
sudo apt install git-lfs

# Windows
winget install GitHub.GitLFS
# (or install Git for Windows, which bundles Git LFS as an optional component)

# Then (once, per machine)
git lfs install

If you hit git-lfs filter-process: command not found during git clone or npx skills add heygen-com/hyperframes, install Git LFS and retry. You can also skip LFS content if you only need the source files:

GIT_LFS_SKIP_SMUDGE=1 git clone https://github.com/heygen-com/hyperframes.git

License

Apache 2.0

S
Description
Write HTML. Render video. Built for agents.
Readme
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