generating-mock-images

name	generating-mock-images
description	Generates mock flower and plant images for an e-commerce website, presenting them for user review. Use when generating mock product images for flower and plant stores or managing generated mock image assets.

Generating Mock Images for Flower & Plant E-Commerce

Generates high-quality mock product photography for flower and plant e-commerce stores, displays the resulting image in chat for review, and handles user feedback (regenerate, delete, or save to workspace).

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Workflow Steps

1. Synthesize Prompt & Call generate_image

CRITICAL TOOL RULE: You MUST execute the native generate_image tool to generate studio product images. Do NOT write Python scripts (e.g. PIL, matplotlib, byte packing), HTML/Canvas, SVG, or code to render images.

Default Pre-baked Subject Options:

• Option A (Houseplants): "Lush potted plant with healthy leaves in a minimalist ceramic pot"
• Option B (Floral Arrangements): "Elegant floral arrangement of fresh seasonal blooms in a clear glass vase filled with crystal-clear water"

Prompt Synthesis Strategy: When composing the Prompt argument for generate_image, integrate the scene, camera, and lighting parameters:

"Professional studio product photograph of [SUBJECT]. [SCENE: smooth matte light gray surface, seamless background curve with soft infinite horizon, visible water line in vase]. [CAMERA: macro lens photography, sharp focus from front to back, f/11 aperture, crisp details, zero digital noise]. [LIGHTING: three-point soft-diffuse lighting, 48-inch octagonal softbox key light at 45 degrees, gentle fill light, backlit soft ambient glow, no harsh glare or unwanted reflections, premium e-commerce product catalog style]."

Invoke generate_image tool:

• Prompt: Synthesized prompt combining Subject + Scene + Camera + Lighting specs.
• ImageName: mock_flower_plant (or uniquely named based on selection).
• AspectRatio: Default to "1:1". If the user explicitly specifies a different aspect ratio in their prompt or request (e.g., "16:9", "3:2", "4:3", "9:16"), use that specified aspect ratio instead.

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2. Display Image in Chat

Upon receiving the output path from generate_image, render the image directly in the chat response using standard markdown image syntax:

![Mock Flower/Plant Product](file://<GENERATED_IMAGE_PATH>)

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3. Prompt User for Action (ask_question)

Invoke ask_question tool to ask the user how to handle the generated asset:

• Question: "What would you like to do with this generated mock image?"
• Options:
  • "Keep"
  • "Regenerate"
  • "Exit"

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4. Process User Choice

Action: Keep (<workspace>/public/images/)

• Ensure the destination directory exists at <workspace>/public/images/.
• Copy image file from <GENERATED_IMAGE_PATH> to <workspace>/public/images/<image_filename>.
• Display a confirmation message.

Action: Regenerate Image

• Re-run Step 1.
• Render the updated image in chat (Step 2).
• Re-prompt the user with ask_question (Step 3).

Action: Exit

• Exit workflow without saving to workspace