---

name: recipe-image-processor description: Process recipe photos into structured recipe data using GPT-4 vision. Use when asked to extract recipes from images, convert recipe photos to JSON, process HelloFresh/meal-kit recipe cards, or batch process multiple recipe images. Handles image preprocessing (resize, rotate), recipe extraction via AI vision, step image linking, and cooking process generation.

Recipe Image Processor

Extract structured recipe data from recipe card photos using GPT vision API.

Prerequisites

• Bun runtime: curl -fsSL https://bun.sh/install | bash
• ImageMagick: brew install imagemagick
• OpenAI API key: Set OPENAI_API_KEY environment variable

Workflow

Step 1: Preprocess Photos

Large photos (>2MB) should be resized before sending to GPT vision. Recipe card photos often need rotation.

Copy# Resize and rotate single photo
magick "input.jpg" -rotate -90 -resize '2000x2000>' -quality 85 "processed.jpg"

# Batch preprocess all photos in a directory
for f in photos/*.jpg; do
  basename=$(basename "$f")
  magick "$f" -rotate -90 -resize '2000x2000>' -quality 85 "photos/processed/$basename"
done

Common transformations:

• -rotate -90: Rotate 90° counter-clockwise (for portrait photos taken in landscape)
• -resize '2000x2000>': Shrink to max 2000px, maintaining aspect ratio
• -quality 85: Compress to reduce file size while maintaining readability

Step 2: Extract Recipe from Image

Run the image-to-recipe script to extract structured recipe data using GPT-4 vision:

Copybun run image-to-recipe <image-path> [custom-slug]

The script:

1. Reads and optionally resizes the image
2. Sends to GPT-4.1-mini with structured JSON schema
3. Validates against Zod recipe schema
4. Saves to recipes.json and generates initial processes.json

Example:

Copybun run image-to-recipe photos/processed/my-recipe.jpg
bun run image-to-recipe photos/processed/my-recipe.jpg custom-slug-name

Step 3: Link Step Images (if available)

If step images exist (extracted from the same photo), add image field to each recipe step.

Image path format: /chickadee/assets/images/steps/{photo-prefix}-pic-{1-6}.jpg

Mapping pattern (6 steps max with images):

• Step 1 → -pic-1.jpg
• Step 2 → -pic-2.jpg
• ...
• Step 6 → -pic-6.jpg

Edit recipes.json to add image paths:

Copy{
  "steps": [
    {
      "id": "chop-vegetables",
      "instruction": "Chop the vegetables",
      "durationMinutes": 5,
      "image": "/chickadee/assets/images/steps/PXL_20251228_145906937.MP-pic-1.jpg"
    }
  ]
}

Step 4: Regenerate Cooking Process

After modifying recipes.json (especially adding images), regenerate the process:

Copybun run generate <recipe-slug>

This updates processes.json with image paths in the timeline.

Step 5: Validate

Run validation to ensure all recipes and processes are valid:

Copybun run validate

Batch Processing Multiple Photos

For processing many recipe photos:

Copy# 1. Preprocess all photos
mkdir -p photos/processed
for f in photos/*.jpg; do
  basename=$(basename "$f")
  magick "$f" -rotate -90 -resize '2000x2000>' -quality 85 "photos/processed/$basename"
done

# 2. Extract recipes one by one
for f in photos/processed/*.jpg; do
  bun run image-to-recipe "$f"
done

# 3. Link step images (see Step 3 above)

# 4. Regenerate all processes
for slug in $(jq -r 'keys[]' src/_data/recipes.json); do
  bun run generate "$slug"
done

# 5. Validate all
bun run validate

Extracting Step Images from Recipe Cards

If recipe cards contain embedded step images (e.g., HelloFresh cards with 6 cooking step photos), use the extract-food-pictures script:

Copy# Single image
bun scripts/extract-food-pictures.js <image-path>

# All images in photos directory
bun scripts/extract-food-pictures.js --all

This extracts 6 cropped step images per recipe card, saved to src/assets/images/steps/.

Recipe JSON Schema

Extracted recipes follow this structure:

Copy{
  "slug": "kebab-case-name",
  "title": "Recipe Title",
  "description": "Brief description",
  "difficulty": "easy|medium|hard",
  "totalTimeMinutes": 30,
  "servings": { "min": 2, "max": 6, "default": 4 },
  "ingredients": [
    {
      "name": "Ingredient Name",
      "unit": "g|ml|pieces|etc",
      "quantitiesByServings": { "2": 100, "3": 150, "4": 200, "5": 250, "6": 300 },
      "notes": "optional notes"
    }
  ],
  "steps": [
    {
      "id": "step-id-kebab-case",
      "instruction": "Do the thing",
      "durationMinutes": 5,
      "ingredients": ["ingredient-name"],
      "notes": "optional",
      "image": "/path/to/step-image.jpg"
    }
  ],
  "tags": ["vegetarian", "quick", "etc"]
}

Troubleshooting

command not found: bun: Use full path /Users/<user>/.bun/bin/bun or add to PATH

command not found: magick: Install ImageMagick with brew install imagemagick

Recipe validation fails: Check error messages from bun run validate - common issues:

• Missing required fields (quantitiesByServings needs 2-6)
• Invalid step IDs (must be kebab-case)
• Invalid difficulty (must be easy/medium/hard)

GPT extraction incomplete: Try reducing image size further or improving image quality/lighting