Gemini Visual - Front-End & Visual Development Assistant

Overview

A comprehensive toolkit leveraging Google Gemini's advanced visual reasoning capabilities for front-end development and design tasks. Gemini provides state-of-the-art multimodal understanding with spatial reasoning, document understanding, and high-resolution image processing.

When to Use

• UI/UX Analysis: Analyze screenshots for layout issues, visual hierarchy, and design patterns
• Accessibility Audits: Check contrast ratios, text readability, and WCAG compliance
• Design Comparison: Compare mockups, before/after screenshots, or different design variations
• Color Palette Extraction: Extract colors from images with HEX, RGB, and HSL values
• Screenshot to Code: Generate HTML/CSS from design screenshots
• UI Asset Generation: Create icons, backgrounds, gradients, and UI graphics
• Responsive Design Review: Analyze multi-device screenshots for consistency
• Visual Debugging: Identify rendering issues, broken layouts, or visual bugs
• Design from Brief: Generate designs, code, and components from text descriptions
• Interactive Design Sessions: Multi-turn conversations for iterative design refinement

Prerequisites

• Python 3.9+
• google-genai package
• GEMINI_API_KEY environment variable

Installation

pip install google-genai

Getting an API Key

1. Go to Google AI Studio
2. Sign in with your Google account
3. Click "Create API Key"
4. Copy the key and set it as an environment variable:

export GEMINI_API_KEY="your-api-key"

Add to your shell profile (~/.zshrc or ~/.bashrc) for persistence:

echo 'export GEMINI_API_KEY="your-api-key"' >> ~/.zshrc

Scripts Overview

Script	Purpose
analyze_ui.py	Analyze UI screenshots for issues, patterns, and suggestions
generate_ui_assets.py	Generate icons, backgrounds, and UI graphics
compare_designs.py	Compare two designs and highlight differences
extract_colors.py	Extract color palettes from images
screenshot_to_code.py	Convert screenshots to HTML/CSS code
design_from_brief.py	Generate designs and code from text briefs (no image required)

Available Models

Model	Best For	Notes
gemini-2.5-flash	Visual analysis, code generation, fast reasoning	Best cost/quality for analysis
gemini-2.5-pro	Complex visual reasoning, code generation	Highest quality analysis
gemini-2.5-flash-image-preview	Asset generation, image editing	Native image output
gemini-3.1-flash-image-preview	High-quality image generation, 4K output	Latest image generation model
gemini-3-pro-image-preview	Professional image generation	Previous-gen high quality

Note: For image analysis tasks (analyze_ui, compare_designs, screenshot_to_code, extract_colors), use the text+vision models (gemini-2.5-flash or gemini-2.5-pro). For image generation tasks (generate_ui_assets), use the image-output models.

Media Resolution Options

Control token usage and detail level with --resolution:

Resolution	Tokens/Image	Best For
low	70	Quick scans, thumbnails
medium	560	Standard screenshots, OCR
high	1120	Detailed UI analysis
ultra_high	2240+	Fine text, complex layouts

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Script Reference

1. analyze_ui.py - UI Analysis

Analyze UI screenshots for design issues, accessibility problems, and improvement suggestions.

python scripts/analyze_ui.py [options] IMAGE

Required:
  IMAGE                    Path to UI screenshot to analyze

Options:
  -m, --mode MODE          Analysis mode (default: comprehensive)
                           Modes: comprehensive, accessibility, layout, ux
  -r, --resolution RES     Media resolution (default: high)
  -o, --output FILE        Save analysis to file (JSON or text)
  -f, --format FORMAT      Output format: text, json, markdown (default: text)
  --thinking LEVEL         Thinking level: low, high (default: high)
  -v, --verbose            Show detailed progress

Examples:

# Comprehensive UI analysis
python scripts/analyze_ui.py screenshot.png

# Accessibility-focused analysis
python scripts/analyze_ui.py -m accessibility app_screen.png

# Layout analysis with JSON output
python scripts/analyze_ui.py -m layout -f json -o report.json mockup.png

# Quick UX review
python scripts/analyze_ui.py -m ux --thinking low mobile_app.png

Analysis Modes:

• comprehensive: Full analysis including layout, colors, typography, accessibility, and UX
• accessibility: WCAG compliance, contrast ratios, screen reader compatibility, touch targets
• layout: Visual hierarchy, spacing, alignment, responsive issues
• ux: User flow, affordances, cognitive load, interaction patterns

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2. generate_ui_assets.py - Asset Generation

Generate UI assets like icons, backgrounds, patterns, and graphics.

python scripts/generate_ui_assets.py [options]

Required:
  -p, --prompt TEXT        Description of asset to generate

Options:
  -t, --type TYPE          Asset type (default: icon)
                           Types: icon, background, pattern, illustration, badge
  -s, --style STYLE        Design style (default: modern)
                           Styles: modern, minimal, flat, gradient, glassmorphism,
                                   neumorphism, material, ios, outlined
  -c, --colors COLORS      Color palette (comma-separated HEX or names)
  -a, --aspect-ratio RATIO Aspect ratio (default: 1:1)
  --size SIZE              Resolution: 1K, 2K, 4K (default: 1K)
  -o, --output FILE        Output file path
  -r, --reference IMAGE    Reference image for style guidance
  -v, --verbose            Show detailed progress

Examples:

# Generate app icon
python scripts/generate_ui_assets.py -p "Weather app icon with sun and clouds" -t icon

# Create gradient background
python scripts/generate_ui_assets.py -p "Soft gradient for login screen" -t background \
  -c "#667eea,#764ba2" -a 9:16 -o login_bg.png

# Generate pattern for UI
python scripts/generate_ui_assets.py -p "Subtle geometric pattern for card backgrounds" \
  -t pattern -s minimal -o pattern.png

# Create illustration from reference
python scripts/generate_ui_assets.py -p "Onboarding illustration, person using phone" \
  -t illustration -r brand_style.png -o onboarding.png

# Generate badge/label
python scripts/generate_ui_assets.py -p "Premium badge with star" -t badge \
  -c "gold,white" -s gradient

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3. compare_designs.py - Design Comparison

Compare two design screenshots and analyze differences.

python scripts/compare_designs.py [options] IMAGE1 IMAGE2

Required:
  IMAGE1                   First design image (before/version A)
  IMAGE2                   Second design image (after/version B)

Options:
  -m, --mode MODE          Comparison mode (default: full)
                           Modes: full, visual, content, accessibility
  -f, --format FORMAT      Output format: text, json, markdown (default: text)
  -o, --output FILE        Save comparison to file
  -r, --resolution RES     Media resolution (default: high)
  -v, --verbose            Show detailed progress

Examples:

# Full design comparison
python scripts/compare_designs.py before.png after.png

# Visual-only comparison
python scripts/compare_designs.py -m visual old_design.png new_design.png

# Compare for accessibility changes
python scripts/compare_designs.py -m accessibility v1.png v2.png -o report.md

# A/B test comparison as JSON
python scripts/compare_designs.py -m full variant_a.png variant_b.png -f json

Comparison Modes:

• full: Comprehensive comparison of all visual and functional aspects
• visual: Focus on colors, typography, spacing, visual hierarchy
• content: Text changes, layout shifts, information architecture
• accessibility: Contrast, readability, touch targets, WCAG compliance changes

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4. extract_colors.py - Color Palette Extraction

Extract color palettes from images with multiple output formats.

python scripts/extract_colors.py [options] IMAGE

Required:
  IMAGE                    Image to extract colors from

Options:
  -n, --count COUNT        Number of colors to extract (default: 6)
  -f, --format FORMAT      Output format: text, json, css, tailwind, scss (default: text)
  -o, --output FILE        Save palette to file
  --named                  Include closest CSS color names
  --contrast               Calculate contrast ratios between colors
  -v, --verbose            Show detailed progress

Examples:

# Extract 6 main colors
python scripts/extract_colors.py screenshot.png

# Extract palette as CSS variables
python scripts/extract_colors.py -f css -o colors.css brand_image.png

# Get Tailwind config
python scripts/extract_colors.py -f tailwind -o tailwind.config.js design.png

# Detailed palette with contrast info
python scripts/extract_colors.py -n 8 --named --contrast hero_image.jpg

# SCSS variables output
python scripts/extract_colors.py -f scss -o _colors.scss mockup.png

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5. screenshot_to_code.py - Screenshot to Code

Convert UI screenshots to HTML/CSS code.

python scripts/screenshot_to_code.py [options] IMAGE

Required:
  IMAGE                    UI screenshot to convert

Options:
  -f, --framework FRAME    CSS framework (default: tailwind)
                           Frameworks: tailwind, css, bootstrap, vanilla
  -c, --components         Extract as reusable components
  --responsive             Generate responsive code
  -o, --output DIR         Output directory for files
  -r, --resolution RES     Media resolution (default: ultra_high)
  --thinking LEVEL         Thinking level: low, high (default: high)
  -v, --verbose            Show detailed progress

Examples:

# Convert to Tailwind HTML
python scripts/screenshot_to_code.py landing_page.png

# Generate vanilla CSS
python scripts/screenshot_to_code.py -f vanilla -o ./output mockup.png

# Create responsive Bootstrap components
python scripts/screenshot_to_code.py -f bootstrap -c --responsive card.png

# Full page conversion with components
python scripts/screenshot_to_code.py -f tailwind -c --responsive -o ./components page.png

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6. design_from_brief.py - Text-Based Design Assistant

Generate frontend designs, code, and components from text descriptions without needing visual input.

python scripts/design_from_brief.py [options]

Input (one required):
  -p, --prompt TEXT      Design brief or prompt text
  -b, --brief-file FILE  Read brief from a file
  --interactive          Start interactive design session

Options:
  -m, --mode MODE        Generation mode (default: code)
                         Modes: design, code, component, review, brainstorm
  -fw, --framework FW    Framework for code generation (default: tailwind)
                         Frameworks: tailwind, css, bootstrap, react, vue, svelte, vanilla
  -c, --context TEXT     Additional context (existing code, constraints)
  -f, --format FORMAT    Output format: text, json, markdown (default: text)
  -o, --output FILE      Save output to file
  -v, --verbose          Show detailed progress

Examples:

# Generate code from a brief
python scripts/design_from_brief.py -p "Create a pricing table with 3 tiers" -m code -fw tailwind

# Get design advice and guidance
python scripts/design_from_brief.py -p "Design a modern SaaS landing page" -m design

# Generate a React component
python scripts/design_from_brief.py -p "A toggle switch with smooth animation" -m component -fw react

# Review a design idea
python scripts/design_from_brief.py -p "Is a hamburger menu good for desktop navigation?" -m review

# Brainstorm creative ideas
python scripts/design_from_brief.py -p "Ideas for a fitness app dashboard" -m brainstorm

# Read brief from file
python scripts/design_from_brief.py -b project_brief.txt -m code -fw vue

# Interactive multi-turn session
python scripts/design_from_brief.py --interactive -m code -fw tailwind

Generation Modes:

• design: Get design guidance including colors, typography, layout, and UX recommendations
• code: Generate complete, production-ready frontend code
• component: Design and code reusable UI components with props and variants
• review: Get feedback and recommendations on design ideas or code
• brainstorm: Generate creative ideas and multiple design directions

Supported Frameworks:

Framework	Description
tailwind	Tailwind CSS utility classes
css	Custom CSS with variables and BEM
bootstrap	Bootstrap 5 components
react	React functional components with TypeScript
vue	Vue 3 Composition API with TypeScript
svelte	Svelte components
vanilla	Plain HTML/CSS/JavaScript

Interactive Session Commands:

When using --interactive, you can use these commands:

Command	Description
/mode <mode>	Change generation mode
/framework <fw>	Change framework
/save <file>	Save last response to file
/clear	Clear conversation history
/quit	Exit session

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Use Cases

Front-End Development Workflow

# 1. Analyze a design mockup
python scripts/analyze_ui.py mockup.png -f markdown -o analysis.md

# 2. Extract brand colors
python scripts/extract_colors.py mockup.png -f tailwind -o colors.js

# 3. Generate code from screenshot
python scripts/screenshot_to_code.py mockup.png -f tailwind -c -o ./src

# 4. Generate placeholder icons
python scripts/generate_ui_assets.py -p "Settings gear icon" -t icon -s outlined

Design Review Process

# Compare design iterations
python scripts/compare_designs.py v1.png v2.png -f markdown -o review.md

# Check accessibility
python scripts/analyze_ui.py final_design.png -m accessibility -o a11y_report.json

Asset Production Pipeline

# Generate icon set
for icon in "home" "search" "profile" "settings"; do
  python scripts/generate_ui_assets.py -p "${icon} icon" -t icon -s outlined -o icons/${icon}.png
done

# Generate backgrounds for different screens
python scripts/generate_ui_assets.py -p "Auth screen gradient" -t background -a 9:16 -o bg_auth.png
python scripts/generate_ui_assets.py -p "Dashboard header" -t background -a 21:9 -o bg_header.png

Design from Text Brief

# Start with design exploration
python scripts/design_from_brief.py -p "E-commerce product page for sneakers" -m design -o design_spec.md

# Generate the code
python scripts/design_from_brief.py -p "E-commerce product page with image gallery,
size selector, add to cart button, and reviews section" -m code -fw react -o product_page.tsx

# Create reusable components
python scripts/design_from_brief.py -p "Star rating component, 1-5 stars,
supports half stars, shows count" -m component -fw react

# Interactive refinement session
python scripts/design_from_brief.py --interactive -m code -fw tailwind
# Then iterate: "Add a sticky header", "Make the CTA more prominent", etc.

Full Project Workflow (No Images Needed)

# 1. Brainstorm ideas
python scripts/design_from_brief.py -p "Modern dashboard for analytics SaaS" -m brainstorm

# 2. Get detailed design spec
python scripts/design_from_brief.py -p "Analytics dashboard with sidebar nav,
KPI cards, charts, and data tables" -m design -f markdown -o design.md

# 3. Generate components
python scripts/design_from_brief.py -p "KPI card showing metric, trend, and sparkline" \
  -m component -fw react -o components/KPICard.tsx

python scripts/design_from_brief.py -p "Data table with sorting, filtering, pagination" \
  -m component -fw react -o components/DataTable.tsx

# 4. Generate full page layout
python scripts/design_from_brief.py -p "Dashboard layout combining sidebar, header,
and main content area with the KPI cards and data table" -m code -fw react

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API Capabilities Summary

Gemini 3 Visual Features

• Spatial Reasoning: Understands element positioning, alignment, and relationships
• Document Understanding: OCR, text extraction, layout parsing
• High Resolution: Up to ultra-high resolution for fine details and small text
• Multi-Image Input: Compare up to 3,600 images per request
• Thought Signatures: Maintains reasoning context for multi-turn editing

Image Support

• Input Formats: PNG, JPEG, WebP, HEIC, HEIF
• Max File Size: 20MB inline, larger via File API
• Output Formats: PNG (generated images)
• Resolutions: 1K, 2K, 4K (generation), configurable input resolution

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Troubleshooting

"GEMINI_API_KEY environment variable not set"

Set your API key:

export GEMINI_API_KEY="your-api-key"

"Rate limit exceeded"

Wait a few minutes and retry. For batch operations, add delays between requests.

Low quality analysis

Use higher resolution:

python scripts/analyze_ui.py -r ultra_high screenshot.png

Missing fine details

For detailed UI analysis, use ultra_high resolution:

python scripts/analyze_ui.py -r ultra_high -m comprehensive app.png

Code generation issues

Use high thinking level and ultra_high resolution:

python scripts/screenshot_to_code.py --thinking high -r ultra_high mockup.png

Asset generation blocked by content moderation

If you see "No image content returned. The request may have been blocked by content moderation", try:

• Simplifying or rephrasing your prompt
• Removing specific brand names or copyrighted references
• Using more generic descriptions

This is a safety filter from the Gemini API and not all prompts will be accepted.

Resolution affects token usage

The --resolution parameter controls how many tokens are used for image processing:

• low: ~70 tokens/image - Quick scans, thumbnails
• medium: ~560 tokens/image - Standard screenshots, OCR
• high: ~1120 tokens/image - Detailed UI analysis (default)

Higher resolution provides better accuracy but uses more tokens.

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Best Practices

1. Use appropriate resolution: Higher resolution = more tokens but better accuracy
2. Match model to task: Use gemini-3-pro-preview for analysis, gemini-3-pro-image-preview for generation
3. Provide context: Add relevant details to prompts for better results
4. Iterate on assets: Use multi-turn conversations for refinement
5. Combine scripts: Use extraction + generation for consistent design systems
6. Save outputs: Use -o flag to save reports for documentation
7. Batch similar tasks: Process multiple similar items together for efficiency

Sources

• Gemini Models Reference
• Image Understanding
• Image Generation
• Google AI Studio