puntorigenpuntorigen/avatar-skills/avatar-talking-video/SKILL.md

avatar-talking-video

Skill3 starsChanged 4 months agoMITView on GitHub

Generate a talking-head avatar video from a line of text. Stage 1 synthesizes the text in the avatar's cloned voice via the voice-clone skill (reusing the avatar's trained voice, or training one from a source recording if it has none). Stage 2 feeds a camera-angle image (from avatar-camera-angles) plus the generated mp3 to prunaai/p-video-avatar on Replicate at 720p (or 1080p) and saves the lip-synced MP4 under <avatar>/generated-videos/ with a manifest.json. Use when the user wants a talking avatar / talking-head video, a lip-synced clip of an avatar saying some text, to animate a camera-angle still into a speaking video, or mentions "video del avatar hablando", "avatar que hable", "talking head", "lip sync", or p-video-avatar.

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SKILL.md

Avatar Talking Video

Turn text → a lip-synced talking-head video of an avatar, in two stages:

Voice (TTS). Delegates to the voice-clone skill to speak the text in the avatar's cloned voice. It reuses the avatar's already-trained voice, or trains one from --source if the avatar has none.
Video (lip-sync). Sends a camera-angle image (image, from the avatar-camera-angles skill) plus the generated mp3 (audio) to prunaai/p-video-avatar on Replicate. When audio is supplied it drives the speech directly (the model's own voice settings are ignored), so lip-sync follows the cloned voice exactly.

Output lands in <avatar>/generated-videos/ with a manifest.json recording the text, voice, image, audio, and video params.

Requirements

pip3 install -r requirements.txt (Replicate client). The voice-clone skill must be installed (its TTS does stage 1); install its requirements too.
A Replicate API token, shared with the other Replicate skills (voice-clone, gpt-image-2, avatar-video-reel, …) and discovered automatically. To set/refresh: python3 scripts/setup_key.py YOUR_REPLICATE_API_TOKEN.

Inputs you need

An avatar folder (e.g. lolo/) — the one containing a videos/ dir. It is auto-inferred from --image/--audio, or pass --avatar-dir.
A camera-angle image — produce it first with avatar-camera-angles (a front-ish, clean portrait works best). Pass it with --image. If omitted, <avatar>/frames/frame_0001.png is used.
The text to say (positional or --text-file). The avatar must have a trained voice, or pass --source so stage 1 trains one first.

Usage

# Text -> cloned-voice audio -> talking-head video, from a camera angle
python3 scripts/generate_video.py "Hola, soy Lolo y te cuento algo." \
  --image lolo/angles/skill_test/lolo_push_in.png

# 1080p + happy delivery + a custom visual prompt
python3 scripts/generate_video.py "Big news today!" \
  --image lolo/angles/skill_test/lolo_push_in.png \
  --resolution 1080p --emotion happy \
  --video-prompt "The person is talking and smiling warmly."

# Reuse an existing mp3 (skip TTS) — just lip-sync it to the angle
python3 scripts/generate_video.py \
  --audio lolo/generated-audios/001_hola.mp3 \
  --image lolo/angles/skill_test/lolo_push_in.png

# Avatar has no voice yet: train it first from a clean voice clip
python3 scripts/generate_video.py "Hello there" \
  --image lolo/angles/skill_test/lolo_push_in.png \
  --source lolo/videos/2026-05-16_12-25-46_voice/voice_concat.mp3

Key options

Option	Default	Description
`text` / `--text-file`	—	What the avatar says (drives stage-1 TTS).
`--audio PATH`	—	Use this mp3/wav directly and skip TTS.
`--image PATH`	`<avatar>/frames/frame_0001.png`	Camera-angle / portrait image (`image` input).
`--avatar-dir`	auto	Avatar folder (else inferred from `--image`/`--audio`).
`--resolution`	`720p`	`720p` or `1080p` (1080p ≈ 2× the cost).
`--video-prompt`	`The person is talking.`	What the person is doing while speaking.
`--emotion`	`auto`	TTS delivery (forwarded to voice-clone).
`--language-boost`	`detect`	TTS language (auto-detected; forwarded).
`--voice-id` / `--name` / `--source`	—	Pick / train the voice (forwarded to voice-clone).
`--negative-prompt`	—	What to avoid (e.g. `subtitles, text, watermark`).
`--seed`	—	Reproducible generation.
`--disable-prompt-upsampling`	off	Use `--video-prompt` verbatim.

Output (in `<avatar>/generated-videos/`)

File	What it is
`<NNN>_<slug>.mp4`	The talking-head video (auto-numbered)
`manifest.json`	`items[]` mapping each video → `text`, `voice_id`, `image`, `audio`, `resolution`, `video_prompt`, and the rest of the params

Stage 1 also leaves the generated audio in <avatar>/generated-audios/ (the voice-clone skill's own output). Report the video path, the voice_id used, and the resolution when done.

Notes

audio overrides voice settings. Because we always pass audio, the model's voice / voice_script / voice_language inputs are intentionally unused — lip-sync follows the cloned-voice mp3.
Cost is per second of output: 720p ≈ $0.025/s, 1080p ≈ $0.045/s.
Image quality matters. A clean, front-ish angle preserves identity best; heavy angles or occlusion hurt lip-sync and likeness.
Per-shot reels: generate several angles with avatar-camera-angles, run this skill once per angle with the same text/voice, then stitch the clips.

Related skills

voice-clone — stage-1 TTS / voice training.
avatar-camera-angles — produce the image input.
avatar-frames — extract a clean reference frame.

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