VEED UGC

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name: veed-ugc description: Generate UGC-style promotional videos with AI lip-sync. Takes an image (person with product from Morpheus/Ad-Ready) and a script (pure dialogue), creates a video of the person speaking. Uses ElevenLabs for voice synthesis.

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Veed-UGC

Generate UGC (User Generated Content) style promotional videos with AI lip-sync using ComfyDeploy's Veed-UGC workflow.

Overview

Veed-UGC transforms static images into dynamic promotional videos: 1. Takes a photo of a person with a product (from Morpheus or Ad-Ready) 2. Receives a script (pure dialogue text) 3. Creates a lip-synced video of the person speaking the script

Perfect for creating authentic-feeling promotional content at scale.

API Details

Endpoint: https://api.comfydeploy.com/api/run/deployment/queue Deployment ID: 627c8fb5-1285-4074-a17c-ae54f8a5b5c6

Required Inputs

| Input | Description | Example | |-------|-------------|---------| | image | URL of person+product image | Output from Morpheus/Ad-Ready | | script | Pure dialogue text | "Hola che! Cómo anda todo por allá?" | | voice_id | ElevenLabs voice ID | Default: PBi4M0xL4G7oVYxKgqww |

⚠️ CRITICAL: Script Format

The script input must be PURE DIALOGUE ONLY:

✅ CORRECT:

Hola che! Cómo anda todo por allá? Mirá esto que acabo de probar, una locura total.

❌ WRONG - No annotations:

[Entusiasta] Hola che! (pausa) Cómo anda?

❌ WRONG - No tone directions:

Tono argentino informal: Hola che!

❌ WRONG - No stage directions:

*sonríe* Hola che! *levanta el producto*

❌ WRONG - No titles/labels:

ESCENA 1:
Hola che!

Just write exactly what the person should say. Nothing else.

Voice IDs (ElevenLabs)

| Voice | ID | Description | |-------|-----|-------------| | Default | PBi4M0xL4G7oVYxKgqww | Main voice |

*More voices can be added from ElevenLabs*

Usage

uv run ~/.clawdbot/skills/veed-ugc/scripts/generate.py \
  --image "https://example.com/person-with-product.png" \
  --script "Hola! Les quiero mostrar este producto increíble que acabo de probar." \
  --output "ugc-video.mp4"

With local image file:

uv run ~/.clawdbot/skills/veed-ugc/scripts/generate.py \
  --image "./morpheus-output.png" \
  --script "Mirá, yo antes no usaba esto pero ahora no puedo vivir sin él." \
  --voice-id "PBi4M0xL4G7oVYxKgqww" \
  --output "promo-video.mp4"

Direct API Call

const response = await fetch("https://api.comfydeploy.com/api/run/deployment/queue", {
  method: "POST",
  headers: {
    "Content-Type": "application/json",
    "Authorization": "Bearer YOUR_API_KEY"
  },
  body: JSON.stringify({
    "deployment_id": "627c8fb5-1285-4074-a17c-ae54f8a5b5c6",
    "inputs": {
      "image": "/* put your image url here */",
      "voice_id": "PBi4M0xL4G7oVYxKgqww",
      "script": "Hola che! Cómo anda todo por allá?"
    }
  })
});

Workflow Integration

Typical Pipeline

1. Generate image with Morpheus/Ad-Ready

   uv run morpheus... --output product-shot.png
   

2. Write the script (pure dialogue)

3. Create UGC video from the image

   uv run veed-ugc... --image product-shot.png --script "..." --output promo.mp4
   

Output

The workflow outputs an MP4 video file with:

The original image animated with lip-sync

AI-generated voiceover from the script

Natural head movements and expressions

Notes

Image should clearly show a person's face (frontal or 3/4 view works best)

Script is spoken exactly as written - no interpretation

Video length depends on script length

Processing time: ~2-5 minutes depending on script length

uv run ~/.clawdbot/skills/veed-ugc/scripts/generate.py \
  --image "https://example.com/person-with-product.png" \
  --script "Hola! Les quiero mostrar este producto increíble que acabo de probar." \
  --output "ugc-video.mp4"

With local image file:

uv run ~/.clawdbot/skills/veed-ugc/scripts/generate.py \
  --image "./morpheus-output.png" \
  --script "Mirá, yo antes no usaba esto pero ahora no puedo vivir sin él." \
  --voice-id "PBi4M0xL4G7oVYxKgqww" \
  --output "promo-video.mp4"

Image should clearly show a person's face (frontal or 3/4 view works best)

Script is spoken exactly as written - no interpretation

Video length depends on script length

Processing time: ~2-5 minutes depending on script length