ai-avatar-video

Создавайте AI-аватары и видео с говорящими головами через CLI inference.sh. Рекомендуется: P-Video-Avatar (самый быстрый, дешёвый, встроенный TTS). Также: OmniHuman, Fabric, PixVerse. Аудио: Inworld TTS-2 (100+ языков, управление эмоциями для персонажей), ElevenLabs, Kokoro. Возможности: аватары, управляемые аудио, текст-в-аватар, видео с синхронизацией губ, генерация говорящих голов, виртуальные ведущие, UGC-контент. Используйте для: AI-ведущие, обучающие видео, виртуальные инфлюенсеры, дубляж, маркетинговые видео, UGC-реклама, игровые аватары,...

npx skills add https://github.com/halt-catch-fire/skills --skill ai-avatar-video

Install the belt CLI skill: npx skills add belt-sh/cli

AI Avatar & Talking Head Videos

Create AI avatars and talking head videos via inference.sh CLI.

AI Avatar & Talking Head Videos

Quick Start

Requires inference.sh CLI (belt). Install instructions

belt login

# Recommended: P-Video-Avatar (fastest, cheapest, built-in TTS)
belt app run pruna/p-video-avatar --input '{
  "image": "https://portrait.jpg",
  "voice_script": "Hello, welcome to our product demo!",
  "voice": "Zephyr (Female)"
}'

Available Models

Start with P-Video-Avatar — it's 18x faster and 6x cheaper than alternatives, with built-in TTS, dynamic backgrounds, and 1080p support.

ModelApp IDBest ForBuilt-in TTS
P-Video-Avatarpruna/p-video-avatarBest overall: speed, cost, quality, controlYes (30 voices, 10 languages)
OmniHuman 1.5bytedance/omnihuman-1-5Multi-character, audio-drivenNo
Fabric 1.0falai/fabric-1-0Image talks with lipsyncYes
PixVerse Lipsyncfalai/pixverse-lipsyncHighly realistic lipsyncNo

Cost & Speed Comparison

ModelSpeed (per sec of video)Cost per second
P-Video-Avatar~1.83s/s$0.025
OmniHuman 1.5~28s/s (15x slower)$0.16 (6.4x more)
Fabric 1.0~34s/s (18x slower)$0.14 (5.6x more)

Examples

P-Video-Avatar (Recommended)

Generate avatar from portrait + text script with built-in TTS:

belt app run pruna/p-video-avatar --input '{
  "image": "https://portrait.jpg",
  "voice_script": "Welcome to our product walkthrough. Today I will show you three key features.",
  "voice": "Puck (Male)",
  "voice_language": "English (US)",
  "resolution": "720p"
}'

With custom style control:

belt app run pruna/p-video-avatar --input '{
  "image": "https://portrait.jpg",
  "voice_script": "This is exciting news!",
  "voice": "Aoede (Female)",
  "voice_prompt": "Enthusiastic and energetic tone",
  "video_prompt": "The person is presenting on stage with dramatic lighting",
  "resolution": "1080p"
}'

With audio file instead of TTS:

belt app run pruna/p-video-avatar --input '{
  "image": "https://portrait.jpg",
  "audio": "https://speech.mp3"
}'

Full Workflow: Generate Portrait + Avatar

Use Pruna P-Image to generate the portrait, then create the avatar:

# 1. Generate a portrait image
belt app run pruna/p-image --input '{
  "prompt": "professional headshot portrait of a young woman, neutral background, looking at camera, studio lighting, photorealistic",
  "aspect_ratio": "9:16"
}'

# 2. Create avatar video with built-in TTS
belt app run pruna/p-video-avatar --input '{
  "image": "<image-url-from-step-1>",
  "voice_script": "Hi there! Let me walk you through our latest features.",
  "voice": "Zephyr (Female)"
}'

OmniHuman 1.5 (Multi-Character)

belt app run bytedance/omnihuman-1-5 --input '{
  "image_url": "https://portrait.jpg",
  "audio_url": "https://speech.mp3"
}'

Supports specifying which character to drive in multi-person images.

Fabric 1.0 (Image Talks)

belt app run falai/fabric-1-0 --input '{
  "image_url": "https://face.jpg",
  "audio_url": "https://audio.mp3"
}'

PixVerse Lipsync

belt app run falai/pixverse-lipsync --input '{
  "image_url": "https://portrait.jpg",
  "audio_url": "https://speech.mp3"
}'

Full Workflow: TTS + Avatar (Non-TTS Models)

For models without built-in TTS (OmniHuman, PixVerse), generate speech first:

# 1. Generate speech — Inworld TTS-2 for expressive character voices
belt app run inworld/text-to-speech-2 --input '{
  "text": "[friendly] Welcome to our product demo! [excited] Let me show you three features that will change how you work.",
  "voice_id": "Sarah",
  "delivery_mode": "CREATIVE"
}' > speech.json

# 2. Create avatar video with the speech
belt app run bytedance/omnihuman-1-5 --input '{
  "image_url": "https://presenter-photo.jpg",
  "audio_url": "<audio-url-from-step-1>"
}'

Tip: For most use cases, P-Video-Avatar with built-in TTS is simpler — no separate audio step needed. Use this workflow only when you specifically need OmniHuman (multi-character) or PixVerse (realistic lipsync).

Full Workflow: Dub Video in Another Language

# 1. Transcribe original video
belt app run infsh/fast-whisper-large-v3 --input '{"audio_url": "https://video.mp4"}' > transcript.json

# 2. Translate text (manually or with an LLM)

# 3. Generate speech in new language
belt app run infsh/kokoro-tts --input '{"text": "<translated-text>"}' > new_speech.json

# 4. Lipsync the original video with new audio
belt app run infsh/latentsync-1-6 --input '{
  "video_url": "https://original-video.mp4",
  "audio_url": "<new-audio-url>"
}'

Avatar UGC Generation

Create UGC-style content with P-Video-Avatar — built-in TTS, no separate audio step needed:

# 1. Generate a relatable UGC-style portrait
belt app run pruna/p-image --input '{
  "prompt": "casual selfie-style photo of a young woman in a cozy room, natural lighting, looking at camera, warm smile, authentic feel",
  "aspect_ratio": "9:16"
}'

# 2. Create UGC avatar video with built-in TTS
belt app run pruna/p-video-avatar --input '{
  "image": "<image-url-from-step-1>",
  "voice_script": "Okay so I just tried this product and honestly? It is a game changer. I was not expecting to love it this much but here we are!",
  "voice": "Zephyr (Female)",
  "voice_prompt": "Excited, casual, authentic tone like talking to a friend",
  "video_prompt": "The person is talking casually to camera in their room, natural gestures",
  "resolution": "1080p"
}'

Why P-Video-Avatar for UGC

  • All-in-one — built-in TTS means no separate audio generation step
  • 30 voices, 10 languages — match your target audience
  • Voice + video prompts — control tone, emotion, body language, and background independently
  • 18x faster, 6x cheaper — produce UGC at scale vs. Fabric/OmniHuman/HeyGen
  • 1080p support — platform-ready vertical video from a single portrait image

Batch UGC: Same Product, Multiple Presenters

# Generate 3 different presenters
for voice in "Zephyr (Female)" "Puck (Male)" "Aoede (Female)"; do
  belt app run pruna/p-video-avatar --input "{
    \"image\": \"https://portrait.jpg\",
    \"voice_script\": \"This changed my morning routine completely. Five minutes and I am done.\",
    \"voice\": \"$voice\",
    \"voice_prompt\": \"Casual, authentic, like a real testimonial\",
    \"video_prompt\": \"Person talking to camera in a bright kitchen\",
    \"resolution\": \"1080p\"
  }"
done

Use Cases

  • UGC & Marketing: Product demos, UGC-style ads with AI presenters
  • Education: Course videos, explainers
  • Localization: Dub content across 10 languages from one image
  • Social Media: Consistent virtual influencer content
  • Corporate: Training videos, announcements
  • Gaming: Character avatars, NPC dialogue

Tips

  • Use high-quality portrait photos (front-facing, good lighting)
  • Audio should be clear with minimal background noise
  • P-Video-Avatar supports built-in TTS — no need for a separate speech generation step
  • P-Video-Avatar output aspect ratio matches the input image
  • Generate portraits with pruna/p-image using 9:16 aspect ratio for vertical videos
  • OmniHuman 1.5 supports multiple people in one image
  • LatentSync is best for syncing existing videos to new audio

Related Skills

# Dedicated P-Video-Avatar skill
npx skills add inference-sh/skills@p-video-avatar

# Full platform skill (all apps)
npx skills add inference-sh/skills@infsh-cli

# Text-to-speech (generate audio for non-TTS avatar models)
npx skills add inference-sh/skills@text-to-speech

# Speech-to-text (transcribe for dubbing)
npx skills add inference-sh/skills@speech-to-text

# Video generation
npx skills add inference-sh/skills@ai-video-generation

# Image generation (create avatar images)
npx skills add inference-sh/skills@ai-image-generation

Browse all video apps: belt app list --category video

Documentation

Больше skills от halt-catch-fire

ai-image-generation
halt-catch-fire
We need to translate the given text from English to Russian. The text describes an agent skill for AI image generation. We must preserve the name "ai-image-generation" but it's not in the text, so we don't include it. We preserve product names, protocol names, URLs, numbers, technical terms. No extra commentary. Translate the entire <text> content. The text: "Generate AI images with GPT-Image-2, FLUX, Gemini, Grok, Seedream, Reve and 50+ models via inference.sh CLI. Models: GPT-Image-2, FLUX Dev LoRA, FLUX.2 Klein LoRA, Gemini 3 Pro Image, Grok Imagine, Seedream 4.5, Reve, ImagineArt. Capabilities: text-to-image, image-to-image, inpainting, LoRA, image editing, upscaling, text rendering. Use for: AI art, product mockups, concept art, social media graphics, marketing visuals, illustrations. Triggers: flux, image generation, ai image, text to..." Translate
creativemediaimage
ai-video-generation
halt-catch-fire
Генерируйте AI-видео с помощью Google Veo, Seedance 2.0, HappyHorse, Wan, Grok и 40+ моделей через CLI inference.sh. Модели: Veo 3.1, Veo 3, Seedance 2.0, HappyHorse 1.0, Wan 2.5, Grok Imagine Video, OmniHuman, Fabric, HunyuanVideo. Возможности: текст-в-видео, изображение-в-видео, референс-в-видео, редактирование видео, липсинк, анимация аватаров, апскейлинг видео, звук фоли. Используйте для: видео для соцсетей, маркетинговый контент, объясняющие видео, демонстрации продуктов, AI-аватары. Триггеры: генерация видео, ai video,...
creativevideomedia
twitter-automation
halt-catch-fire
Автоматизация Twitter/X с публикацией, вовлечением и управлением пользователями через CLI inference.sh. Приложения: x/post-tweet, x/post-create (с медиа), x/post-like, x/post-retweet, x/dm-send, x/user-follow. Возможности: публикация твитов, планирование контента, лайки, ретвиты, отправка личных сообщений, подписка на пользователей, получение профилей. Используется для: автоматизации социальных сетей, планирования контента, ботов вовлечения, роста аудитории, X API. Триггеры: twitter api, x api, tweet automation, post to twitter, twitter bot, social media automation, x...
marketingapicommunication
agent-browser
halt-catch-fire
Автоматизация браузера для AI-агентов через inference.sh. Навигация по веб-страницам, взаимодействие с элементами с помощью @e refs, создание скриншотов, запись видео. Возможности: веб-скрапинг, заполнение форм, клики, ввод текста, перетаскивание, загрузка файлов, выполнение JavaScript. Используется для: веб-автоматизации, извлечения данных, тестирования, просмотра страниц агентом, исследований. Триггеры: браузер, веб-автоматизация, скрапинг, навигация, клик, заполнение формы, скриншот, просмотр веб-страниц, playwright, headless-браузер, веб-агент, серфинг в интернете, запись видео
browser-automationweb-scrapingtesting
web-search
halt-catch-fire
Веб-поиск и извлечение контента с помощью Tavily и Exa через CLI inference.sh. Приложения: Tavily Search, Tavily Extract, Exa Search, Exa Answer, Exa Extract. Возможности: поиск на основе ИИ, извлечение контента, прямые ответы, исследования. Используется для: исследований, RAG-пайплайнов, проверки фактов, агрегации контента, агентов. Триггеры: веб-поиск, tavily, exa, search api, извлечение контента, исследования, интернет-поиск, ИИ-поиск, поисковый ассистент, веб-скрапинг, rag, альтернатива perplexity
researchweb-scrapingapi
infsh-cli
halt-catch-fire
Запускайте 250+ AI-приложений через CLI inference.sh — генерация изображений, создание видео, LLM, поиск, 3D, автоматизация Twitter. Модели: FLUX, Veo, Gemini, Grok, Claude, Seedance, OmniHuman, Tavily, Exa, OpenRouter и многие другие. Используйте при запуске AI-приложений, генерации изображений/видео, вызове LLM, веб-поиске или автоматизации Twitter. Триггеры: inference.sh, infsh, ai model, run ai, serverless ai, ai api, flux, veo, claude api, image generation, video generation, openrouter, tavily, exa search, twitter api, grok
developmentapicreative
landing-page-design
halt-catch-fire
We need to translate the given text from English to Russian, preserving the name "landing-page-design" as it appears in the source? The instruction says: "Do not include the name unless it appears in the source text." The name "landing-page-design" is not in the <text> block. The <text> block contains the description. So we only translate the text inside <text>. Also preserve product names, protocol names, URLs, numbers, technical terms. No extra commentary. The text: "Landing page conversion optimization with layout rules, hero section design, and CTA psychology. Covers above-the-fold formula, social proof placement, mobile design, and F-pattern reading. Use for: startup landing pages, product pages, SaaS marketing, conversion optimization. Triggers: landing page, hero section, above the fold, conversion optimization, landing page design, cta button, hero image, landing page layout, saas landing page, product page design, conversion rate, landing page..." Translate to Russian. Keep technical terms like "CTA", "above-the-fold
product-photography
halt-catch-fire
AI-продуктовая фотография со студийным освещением, лайфстайл-снимками и конвенциями пакадшотов. Охватывает ракурсы, фоны, типы теней, герой-снимки и требования к изображениям для электронной коммерции. Используйте для: фото продуктов, изображений для электронной коммерции, листингов Amazon, пакадшотов, лайфстайл-фотографии. Триггеры: продуктовая фотография, фото продукта, пакадшот, фотография для электронной коммерции, снимок продукта, изображение продукта, студийная фотография, лайфстайл-продукт, фото продукта для Amazon, изображение для листинга продукта, герой-снимок, мокап продукта,...
creativeecommerceimage