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ad-ready

Generate professional advertising images from product URLs using the Ad-Ready pipeline on ComfyDeploy. Use when the user wants to create ads for any product by providing a URL, optionally with a brand profile (70+ brands) and funnel stage targeting. Supports model/talent integration, brand-aware creative direction, and multi-format output. Differs from Morpheus (manual fashion photography) — Ad-Ready is URL-driven, brand-intelligent, and funnel-stage aware.

personAuthor: jakexiaohubgithub
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Ad-Ready: AI Advertising Image Generator

Generate professional advertising images from product URLs using a 4-phase AI pipeline on ComfyDeploy.

⚠️ CRITICAL: Required Inputs Checklist

Before running ANY ad generation, the agent MUST ensure ALL of these are provided:

| Input | Required? | How to Get It | |-------|-----------|---------------| | --product-url | ✅ ALWAYS | User provides the product page URL | | --product-image | ✅ ALWAYS | Download from the product page, or user provides | | --logo | ✅ ALWAYS | Download from brand website or search online. MUST be an image file | | --reference | ✅ RECOMMENDED | An existing ad whose style we want to clone. Search online or use previously generated images | | --brand-profile | ✅ NEVER EMPTY | Pick from catalog or run brand-analyzer first. NEVER leave as "No Brand" if a brand is known | | --prompt-profile | ✅ ALWAYS | Choose based on campaign objective | | --aspect-ratio | Default: 4:5 | Change if needed for platform | | --model | Optional | Model/talent face from catalog or user-provided |

🚨 NEVER Skip These Steps:

  1. Product image — Download the main product photo from the product URL. The scraper is fragile; always provide a product image explicitly.
  2. Brand logo — Download the logo from the brand's official website or search for "{brand name} logo" online. Must be a clean logo image (PNG preferred).
  3. Brand profile — If the brand doesn't exist in the catalog, run brand-analyzer skill FIRST to generate one. Never submit with "No Brand" when a brand is known.
  4. Reference image — Search for an existing ad or visual with a style that matches what we're generating. Can be from previously generated images, the brand's campaigns, or found online. This dramatically improves output quality.

Auto-Preparation Workflow

When the user asks to generate an ad, follow this workflow:

1. User provides: product URL + brand name + objective

2. CHECK brand profile exists:
   → ls ~/clawd/ad-ready/configs/Brands/ | grep -i "{brand}"
   → If not found: run brand-analyzer skill first
   
3. DOWNLOAD product image:
   → Visit the product URL in browser or fetch the page
   → Find and download the main product image
   → Save to /tmp/ad-ready-product.jpg

4. DOWNLOAD brand logo:
   → Search "{brand name} logo PNG" or fetch from brand website
   → Download clean logo image
   → Save to /tmp/ad-ready-logo.png

5. FIND reference image:
   → Search for "{brand name} advertisement" or similar
   → Or use a previously generated ad that has the right style
   → Save to /tmp/ad-ready-reference.jpg

6. SELECT prompt profile based on objective:
   → Awareness: brand discovery, first impressions
   → Interest: engagement, curiosity
   → Consideration: comparison, features
   → Evaluation: deep dive, decision support
   → Conversion: purchase intent, CTAs (most common)
   → Retention: re-engagement
   → Loyalty: brand advocates
   → Advocacy: referral, community

7. RUN the generation with ALL inputs filled

Usage

Full command (recommended):

COMFY_DEPLOY_API_KEY="$KEY" uv run ~/.clawdbot/skills/ad-ready/scripts/generate.py \
  --product-url "https://shop.example.com/product" \
  --product-image "/tmp/product-photo.jpg" \
  --logo "/tmp/brand-logo.png" \
  --reference "/tmp/reference-ad.jpg" \
  --model "models-catalog/catalog/images/model_15.jpg" \
  --brand-profile "Nike" \
  --prompt-profile "Master_prompt_05_Conversion" \
  --aspect-ratio "4:5" \
  --output "ad-output.png"

Auto-fetch mode (downloads product image and logo automatically):

COMFY_DEPLOY_API_KEY="$KEY" uv run ~/.clawdbot/skills/ad-ready/scripts/generate.py \
  --product-url "https://shop.example.com/product" \
  --brand-profile "Nike" \
  --prompt-profile "Master_prompt_05_Conversion" \
  --auto-fetch \
  --output "ad-output.png"

The --auto-fetch flag will:

  • Download the main product image from the product URL
  • Search and download the brand logo
  • Both get uploaded to ComfyDeploy automatically

API Details

Endpoint: https://api.comfydeploy.com/api/run/deployment/queue Deployment ID: e37318e6-ef21-4aab-bc90-8fb29624cd15

ComfyDeploy Input Variables

These are the exact variable names the ComfyDeploy deployment expects:

| Variable | Type | Description | |----------|------|-------------| | product_url | string | Product page URL to scrape | | producto | image URL | Product image (uploaded to ComfyDeploy) | | model | image URL | Model/talent face reference | | referencia | image URL | Style reference ad image | | marca | image URL | Brand logo image | | brand_profile | enum | Brand name from catalog | | prompt_profile | enum | Funnel stage prompt | | aspect_ratio | enum | Output format |

4-Phase Pipeline (How It Works Internally)

Phase 1: Product Scraping

  • Gemini Flash visits the product URL
  • Extracts: title, description, features, price, images
  • ⚠️ Image scraping is the most fragile part — always provide product images manually

Phase 2: Campaign Brief Generation (CRITICAL)

  • Uses Brand Identity JSON + Product Data → 10-point brief
  • Everything downstream depends on brief quality
  • Brief covers: strategic objective, central message, visual tone, product role, photographer, art direction, environment, textures, signature

Phase 3: Blueprint Generation

  • Master Prompt (per funnel stage) + Brief + Product JSON + Keyword Bank + Format
  • Gemini Flash generates complete Blueprint JSON
  • Covers: scene, production, graphic design, lighting, composition, materials, CTA

Phase 4: Image Generation

  • Nano Banana Pro (Imagen 3.0) generates the final image
  • Uses Blueprint JSON + all reference images (product, talent, logo, style ref)

Supporting Reference Nodes

  • pose_ref → enforce a specific pose (replicated exactly)
  • photo_style_ref → replicate photographic style (⚠️ can be too literal, being optimized)
  • location_ref → replicate location and color palette

Brand Profiles

Existing catalog (70+ brands):

ls ~/clawd/ad-ready/configs/Brands/*.json | sed 's/.*\///' | sed 's/\.json//'

Creating new brand profiles:

Use the brand-analyzer skill:

GEMINI_API_KEY="$KEY" uv run ~/.clawdbot/skills/brand-analyzer/scripts/analyze.py \
  --brand "Brand Name" --auto-save

This generates a full Brand Identity JSON and saves it to the catalog automatically.

Prompt Profiles (Funnel Stages)

| Profile | Stage | Best For | |---------|-------|----------| | Master_prompt_01_Awareness | Awareness | Brand discovery, first impressions | | Master_prompt_02_Interest | Interest | Engagement, curiosity | | Master_prompt_03_Consideration | Consideration | Comparison, features | | Master_prompt_04_Evaluation | Evaluation | Deep dive, decision support | | Master_prompt_05_Conversion | Conversion | Purchase intent, CTAs | | Master_prompt_06_Retention | Retention | Re-engagement, loyalty | | Master_prompt_07_Loyalty | Loyalty | Brand advocates | | Master_prompt_08_Advocacy | Advocacy | Referral, community |

How to choose:

  • Most ads → Conversion (purchase intent)
  • New product launches → Awareness
  • Retargeting → Consideration or Evaluation
  • Existing customers → Retention or Loyalty

Aspect Ratios

| Ratio | Use Case | |-------|----------| | 4:5 | Default. Instagram feed, Facebook | | 9:16 | Stories, Reels, TikTok | | 1:1 | Square posts | | 16:9 | YouTube, landscape banners | | 5:4 | Alternative landscape |

Model Catalog

Models for talent/face reference: ~/clawd/models-catalog/catalog/

Priority: User-provided model > Catalog selection > No model (product-only ad)

Known Limitations

  1. Product image scraping is fragile — always provide product images manually when possible
  2. photo_style_ref can be too literal — the style reference may be replicated too closely
  3. Some websites block scraping — Armani works well, others may return incorrect data
  4. Auto 4-Format is alpha — bugs and edge cases exist
  5. Gemini hallucinations — occasional issues in complex reasoning steps

Ad-Ready vs Morpheus

| Feature | Ad-Ready | Morpheus | |---------|----------|----------| | Input | Product URL (auto-scrapes) | Manual product image | | Brand intelligence | 70+ brand profiles | None | | Funnel targeting | 8 funnel stages | None | | Creative direction | Auto-generated from brief | Pack-based (camera, lens, etc.) | | Best for | Product advertising campaigns | Fashion/lifestyle editorial photography | | Control level | High-level (objective-driven) | Granular (every visual parameter) |

Source Repository

  • GitHub: https://github.com/PauldeLavallaz/ads_SV
  • Local clone: ~/clawd/ad-ready/
  • Patreon docs: https://www.patreon.com/posts/from-product-to-149933468

API Key

Uses ComfyDeploy API key. Set via COMFY_DEPLOY_API_KEY environment variable.