A Claude Code plugin that makes narrated explainer videos on your own GPU

Narrated explainer videos made on your own GPU, with Claude Code directing.

Quick start · What you get · Why local · How it works · Setup · Português

Script, voice, music, animated scenes, assembly, sped-up version and cover, all on your machine. Voice on OmniVoice, music on MusicGen, scenes in HTML/SVG/GSAP rendered by HyperFrames, cover on SDXL via ComfyUI. No voice, music or video API to pay for.

Made with this: Your mind under terms of use, 13 minutes on neurotechnology (assignment for Computers and Society, UFES). It was made in Brazilian Portuguese and then dubbed into English with this pipeline. Full code in examples/your-mind/.

Click the player to watch in 1080p (716 MB), or the light 26 MB copy. Description and chapters in the release; the original Portuguese cut has its own.

Install the skills as a Claude Code plugin:

claude plugin marketplace add lewislf/claude-code-video-studio
claude plugin install video-studio@claude-code-video-studio

Then ask in plain words. Some prompts that work:

• "make a narrated video about why the sky is blue, 3 minutes"
• "redo scene 12, the diagram is too small"
• "swap the voice for a British one"
• "make the final version at 1.35x and send it to my phone"
• "write the YouTube description with chapters" / "make a cover"

The narrated-video skill knows the steps; scenes go to subagents with the studio/AGENT.md briefing; the ai-cover skill makes the thumbnail. The machine still needs the setup below.

• one MP4 per video, with the narration over a low music bed and a thin progress bar;
• a sped-up cut (1.35x by default) and a light phone copy;
• the voice cloned from a reference clip, in any language OmniVoice speaks, with 3 takes per sentence and whisper picking the clearest one;
• scenes timed to the word: an animation fires on the instant the voice says it;
• patching: redo one scene (patch.py ) or the whole audio (swap_audio.py ) without rebuilding the rest;
• dubbing: a new language over the same timeline, with .srt subtitles (examples/your-mind/dub.py , how the example became English);
• YouTube title, description and chapters, and a 1280x720 cover.

Similar projects, by what their READMEs say (November 2026):

The script still comes from Claude Code, so you need a Claude plan. Everything after it runs on your GPU.

A video is a folder with a script.py. The script is the single source: the voice, the timing of each scene and the assembly all come from it.

SCENES = [
  ("sky", "The sky", [
    ("Look up on a clear day. The sky is blue.", 0.5, {"a": "sky"}),
    ("But sunlight is white.", 1.4, {"a": "prism"}),
  ]),
]

Each segment (spoken text, , visual) becomes a clip with the exact duration of the speech. Scenes are Python functions that return HTML; word("sky", 0, "blue") gives the instant the voice says "blue", and the animation fires there.

script.py ──> tts.py ──> assets/voice/*.wav + durations.json ──> transcribe.py ──> words/*.json
                                   │                                                  │
                                   └──────────> scenes/<group>/build_*.py <───────────┘
                                                        │  scenes.py render
music.py ──> assets/music.mp3 ──> assemble.py <── assets/clips/*.mp4
                                        │
             progress_bar.sh ──> deliver.sh ──> renders/v1-bar-1.35x.mp4 (+ mobile)

The narration language is LANG in script.py (ISO code, default "en"). Any language OmniVoice supports works; the example video is pt-BR. The voice is cloned from a reference clip, and the clip's accent carries over, so the reference has to be in the narration's language. studio/voices/ has eight English references made with OmniVoice voice design (deep male US and UK, older male US, low female US, two takes each) and one Portuguese (deep_narrator). Without VOICE, English uses en_deep_us_b and other languages use deep_narrator; set VOICE = "en_deep_uk_a" to pick another, or point it at your own clip.

The same pipeline without the skills:

cp -r template ~/videos/my-video && cd ~/videos/my-video
ST=~/claude-code-video-studio/studio; PY=~/.venvs/studio/bin/python   # the env from Setup

$PY $ST/tts.py generate && $PY $ST/tts.py pick          # voice, 3 takes per sentence, keeps the one whisper understands best
python3 $ST/transcribe.py                               # timing of each word
$PY $ST/music.py                                        # music
python3 $ST/scenes.py render g1                         # scenes of group g1 -> clips
python3 $ST/assemble.py                                 # renders/v1.mp4
$ST/progress_bar.sh v1 v1-bar && $ST/deliver.sh v1-bar  # progress bar and 1.35x version

NVIDIA GPU (tested on an 8 GB RTX 5070), Linux with systemd-run (the scripts set memory caps), ffmpeg, Node 22+ (for npx hyperframes@0.8.185). The voice, word timing and music share one Python 3.11 environment:

python3.11 -m venv ~/.venvs/studio
~/.venvs/studio/bin/pip install torch torchaudio torchvision --index-url https://download.pytorch.org/whl/cu128
~/.venvs/studio/bin/pip install "omnivoice @ git+https://github.com/debpalash/VoiceStudio@73b83768bdc02dd7068c5c2fefcfa0530fa622e4" \
  faster-whisper transformers accelerate soundfile librosa

The environment takes about 9 GB. Tested from scratch with torch 2.11 (cu128), VoiceStudio at the pinned commit, faster-whisper 1.2.1 and transformers 5.22; the template video renders end to end. Install torchvision from the PyTorch index together with torch: the copy pip pulls in for omnivoice does not match the cu128 build and breaks the import. The OmniVoice and MusicGen weights download from Hugging Face on the first run. The cover needs ComfyUI with SDXL base (see skills/ai-cover/SKILL.md). taskline, if installed, shows progress.

Everything runs on your machine. The plugin sends no data anywhere: no telemetry, no API calls of its own. It downloads:

• the OmniVoice, whisper and MusicGen weights from Hugging Face, on the first run of each step;
• hyperframes@0.8.185 from npm throughnpx , to render the scenes and time the words (it uses a local headless Chrome);
• GSAP 3.14.2 from cdn.jsdelivr.net and the fonts from fonts.googleapis.com, loaded by the scene pages while they render;
• the Python packages in Setup , when you install them.

The skills run the scripts in studio/ with python3, ffmpeg and systemd-run, inside the video's own folder, and the ai-cover skill talks to a ComfyUI server on 127.0.0.1.

The code here is MIT, but the models have their own terms, and they decide what you can do with the video:

• MusicGen weights (facebook/musicgen-small ): CC-BY-NC 4.0,non-commercial . On a monetized channel, swap the music for a track you have rights to.
• OmniVoice: the omnivoice package (VoiceStudio) is AGPL-3.0; thek2-fsa/OmniVoice weights follow their model card.
• SDXL base: CreativeML Open RAIL++-M.

Voice and music are AI-generated; say so in the video description.

Made by lewislf and FeLiPeOLi7.

Code under MIT. The film and trailer clips cited in examples/your-mind/film/assets/CREDITS.md belong to their owners and are not in the repo. The fly photo is by Alexis (iNaturalist), CC BY 4.0.