lenscore-accessibility
v0.1.0
Published
Open-source accessibility testing and web crawling platform
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LensCore
LensCore is an open-source accessibility testing and web crawling platform built with a containerized, API-driven architecture. It provides comprehensive web accessibility analysis using axe-core integration and flexible storage options for screenshots and reports.
🚀 Features
- 🌐 Web Crawling: Intelligent website crawling with configurable depth and rules
- ♿ Accessibility Testing: WCAG compliance testing powered by axe-core
- 🤖 AI-Powered Analysis: Plain language explanations and tech-stack specific remediation
- 🧠 Intelligent Caching: Smart caching system to minimize AI API costs and improve performance
- 📸 Screenshot Capture: Automatic screenshot capture for violations and pages
- 💾 Flexible Storage: Support for local, AWS S3, and Google Cloud Storage
- 🔌 RESTful APIs: Clean API endpoints for crawl, test, and combined operations
- 🐳 Docker Ready: Fully containerized with Docker Compose support
- ⚡ High Performance: Concurrent processing with configurable limits
- 🛡️ Production Ready: Built-in health checks, logging, and error handling
📋 Table of Contents
⚡ Quick Start
Prerequisites
- Node.js 20+ (for local development)
- Docker & Docker Compose (for containerized deployment)
- Git (for cloning the repository)
Using Docker (Recommended)
Clone the repository:
git clone <repository-url> cd LensCoreSet up environment:
cp env.example .envStart the service (with Makefile):
make build-dockerVerify installation:
curl http://localhost:3001/api/healthStop services:
make down
Docker with Redis (Production)
For production deployments with Redis caching:
Set up environment:
cp env.example .env # Edit .env and set CACHE_TYPE=redisStart with Redis:
docker-compose up -d --buildVerify Redis connection:
curl http://localhost:3001/api/cache/stats
Using Node.js
Install dependencies:
make installSet up environment:
cp env.example .envStart development server:
make dev
Makefile Commands
Common tasks:
make install # Install dependencies
make dev # Run development server
make build # Build for production
make start # Run production server
make test # Run all tests
make lint # Run ESLint
make format # Format code with Prettier
make typecheck # TypeScript type checking
make build-docker # Build Docker image
make up # Start services with Docker Compose
make down # Stop services with Docker Compose
make logs # Tail Docker Compose logs
make env # Print key env variables from .env⚙️ Configuration
Environment Variables
LensCore uses environment variables for configuration. Copy env.example to .env and customize as needed:
Core Application Settings
NODE_ENV=development
PORT=3001
LOG_LEVEL=infoStorage Configuration
Local Storage (Default):
STORAGE_TYPE=local
STORAGE_PATH=./storageAWS S3:
STORAGE_TYPE=s3
AWS_ACCESS_KEY_ID=your_aws_access_key
AWS_SECRET_ACCESS_KEY=your_aws_secret_key
AWS_REGION=us-east-1
AWS_S3_BUCKET=your-s3-bucket-nameGoogle Cloud Storage:
STORAGE_TYPE=gcs
GCS_PROJECT_ID=your-gcs-project-id
GCS_KEY_FILE_PATH=./path/to/service-account-key.json
GCS_BUCKET_NAME=your-gcs-bucket-nameCrawling Configuration
CRAWL_TIMEOUT=10000
CRAWL_CONCURRENCY=5
CRAWL_MAX_URLS=25
CRAWL_WAIT_UNTIL=domcontentloadedAccessibility Testing Configuration
AXE_TIMEOUT=10000
AXE_CONCURRENCY=5AI Processing Configuration (Optional)
OPENAI_API_KEY=your-openai-api-key
OPENAI_MODEL=gpt-3.5-turbo
OPENAI_MAX_TOKENS=1000
OPENAI_TEMPERATURE=0.7
OPENAI_TIMEOUT=30000
OPENAI_RETRY_ATTEMPTS=3
OPENAI_RETRY_DELAY=1000Cache Configuration (Optional)
CACHE_TYPE=memory # memory, filesystem, redis
CACHE_TTL=3600 # 1 hour in seconds
CACHE_MAX_SIZE=1000 # For memory cache
CACHE_PATH=./cache # For filesystem cache
REDIS_HOST=localhost # Redis host
REDIS_PORT=6379 # Redis port
REDIS_PASSWORD= # Redis password (optional)
REDIS_DB=0 # Redis database📚 API Documentation
Base URL
http://localhost:3001/apiResponse Format
All API responses follow a consistent JSON format with appropriate HTTP status codes.
Check the health status of all services.
Endpoint: GET /api/health
Example:
curl http://localhost:3001/api/healthResponse:
{
"status": "healthy",
"timestamp": "2024-01-01T00:00:00.000Z",
"services": {
"crawling": "up",
"accessibility": "up",
"storage": "up"
}
}Crawl a website and discover all linked pages.
Endpoint: POST /api/crawl
Request Body:
{
"url": "https://example.com",
"max_depth": 2,
"maxUrls": 10,
"timeout": 10000,
"concurrency": 3,
"waitUntil": "domcontentloaded",
"rules": {
"include_subdomains": true,
"follow_external": false,
"exclude_paths": ["/admin", "/private"],
"include_paths": ["/public", "/docs"],
"respect_robots": true
},
"enableAI": true,
"projectContext": {
"framework": "React",
"cssFramework": "Tailwind CSS",
"language": "TypeScript",
"buildTool": "Vite"
}
}Parameters:
url(required): Target website URLmax_depth(optional): Maximum crawling depth (1-5, default: 2)maxUrls(optional): Maximum number of URLs to crawl (default: 25)timeout(optional): Request timeout in milliseconds (default: 10000)concurrency(optional): Number of concurrent requests (default: 5)waitUntil(optional): Page load condition (default: "domcontentloaded")rules(optional): Crawling rules configurationenableAI(optional): Enable AI processing for accessibility issues (default: false)projectContext(optional): Structured project context for more precise AI analysis
Crawling Rules:
include_subdomains(optional): Include subdomains in crawling (default: false)follow_external(optional): Follow external links (default: false)exclude_paths(optional): Array of paths to exclude from crawlinginclude_paths(optional): Array of paths to include (if specified, only these paths will be crawled)respect_robots(optional): Respect robots.txt (default: true)
Project Context Structure:
{
"framework": "React",
"cssFramework": "Tailwind CSS",
"language": "TypeScript",
"buildTool": "Vite",
"additionalContext": "Custom context"
}Example:
curl -X POST http://localhost:3001/api/crawl \
-H "Content-Type: application/json" \
-d '{
"url": "https://example.com",
"max_depth": 2,
"maxUrls": 10,
"timeout": 10000,
"concurrency": 3,
"rules": {
"include_subdomains": true,
"follow_external": false,
"exclude_paths": ["/admin", "/private"]
},
"enableAI": true,
"projectContext": {
"framework": "React",
"cssFramework": "Tailwind CSS",
"language": "TypeScript",
"additionalContext": "Need to detail explanation"
}
}'Response:
{
"pages": [
{
"url": "https://example.com",
"title": "Example Domain",
"description": "This domain is for use in illustrative examples",
"statusCode": 200,
"timestamp": "2024-01-01T00:00:00.000Z"
},
{
"url": "https://example.com/about",
"title": "About Us",
"description": "Learn more about our company",
"statusCode": 200,
"timestamp": "2024-01-01T00:00:01.000Z"
}
],
"totalPages": 2,
"crawlTime": 2500,
"metadata": {
"crawledAt": "2024-01-01T00:00:02.000Z",
"maxDepth": 2,
"rules": {
"include_subdomains": true,
"follow_external": false,
"exclude_paths": ["/admin", "/private"]
},
"totalPages": 2,
"crawlTime": 2500,
"aiEnabled": true,
"cacheHits": 0,
"cacheMisses": 0,
"processingTime": 150
}
}Run accessibility tests on a single page using axe-core.
Endpoint: POST /api/test
Request Body:
{
"url": "https://example.com",
"includeScreenshot": true,
"timeout": 10000,
"rules": ["color-contrast", "image-alt"],
"tags": ["wcag2aa", "wcag143"],
"enableAI": true,
"projectContext": {
"framework": "Vue.js",
"cssFramework": "Bootstrap",
"language": "JavaScript"
}
}Parameters:
url(required): Target page URLincludeScreenshot(optional): Capture screenshot (default: false)timeout(optional): Test timeout in milliseconds (default: 10000)rules(optional): Specific axe-core rules to testtags(optional): WCAG tags to include in testingenableAI(optional): Enable AI processing for accessibility issues (default: false)projectContext(optional): Structured project context for more precise AI analysis
Project Context Structure:
{
"framework": "React",
"cssFramework": "Tailwind CSS",
"language": "TypeScript",
"buildTool": "Vite",
"additionalContext": "Custom context"
}Example:
curl -X POST http://localhost:3001/api/test \
-H "Content-Type: application/json" \
-d '{
"url": "https://example.com",
"includeScreenshot": true,
"timeout": 10000,
"enableAI": true,
"projectContext": {
"framework": "Next.js",
"cssFramework": "Tailwind CSS",
"language": "TypeScript"
}
}'Response:
{
"url": "https://example.com",
"score": 85,
"violations": [
{
"id": "color-contrast",
"impact": "serious",
"description": "Ensures the contrast between foreground and background colors meets WCAG 2 AA contrast ratio thresholds",
"help": "Elements must have sufficient color contrast",
"helpUrl": "https://dequeuniversity.com/rules/axe/4.8/color-contrast",
"tags": ["cat.color", "wcag2aa", "wcag143"],
"nodes": [
{
"target": ["h1"],
"html": "<h1>Example Domain</h1>",
"failureSummary": "Fix any of the following:\n Element has insufficient color contrast of 2.52 (foreground color: #000000, background color: #ffffff, font size: 32px, font weight: normal). Expected contrast ratio of at least 3:1"
}
],
"aiExplanation": "This accessibility issue occurs when text doesn't have enough contrast against its background...",
"aiRemediation": "To fix this issue:\n1. Increase color contrast ratio...\n2. Use CSS: color: #000; background: #fff;",
"userStory": "Users with screen readers have difficulty navigating because there is no clear main landmark. Users who use keyboard navigation cannot jump to the main content quickly. Users with cognitive disabilities may be confused by unclear page structure."
}
],
"passes": [],
"incomplete": [],
"inapplicable": [],
"screenshot": "https://storage.example.com/screenshots/uuid.png",
"timestamp": "2024-01-01T00:00:00.000Z",
"aiEnabled": true,
"aiError": null
}Run accessibility tests on multiple pages simultaneously.
Endpoint: POST /api/test-multiple
Request Body:
[
{
"url": "https://example.com",
"includeScreenshot": true,
"timeout": 10000
},
{
"url": "https://example.com/about",
"includeScreenshot": true,
"timeout": 10000
}
]Example:
curl -X POST http://localhost:3001/api/test-multiple \
-H "Content-Type: application/json" \
-d '[
{
"url": "https://example.com",
"includeScreenshot": true
},
{
"url": "https://example.com/about",
"includeScreenshot": true
}
]'Response:
{
"results": [
{
"url": "https://example.com",
"score": 85,
"violations": [...],
"passes": [],
"incomplete": [],
"inapplicable": [],
"screenshot": "https://storage.example.com/screenshots/uuid1.png",
"timestamp": "2024-01-01T00:00:00.000Z"
},
{
"url": "https://example.com/about",
"score": 92,
"violations": [...],
"passes": [],
"incomplete": [],
"inapplicable": [],
"screenshot": "https://storage.example.com/screenshots/uuid2.png",
"timestamp": "2024-01-01T00:00:00.000Z"
}
],
"totalPages": 2,
"testTime": 3000
}Crawl a website and run accessibility tests on all discovered pages.
Endpoint: POST /api/combined
Request Body:
{
"url": "https://example.com",
"crawlOptions": {
"maxUrls": 5,
"concurrency": 2,
"timeout": 10000
},
"testOptions": {
"includeScreenshot": true,
"timeout": 15000,
"rules": ["color-contrast"]
},
"enableAI": true,
"projectContext": {
"framework": "Angular",
"cssFramework": "Material UI",
"language": "TypeScript"
}
}Parameters:
url(required): Target website URLcrawlOptions(optional): Crawling configuration (see crawl API)testOptions(optional): Testing configuration (see test API)enableAI(optional): Enable AI processing for accessibility issues (default: false)projectContext(optional): Structured project context for more precise AI analysis
Project Context Structure:
{
"framework": "React",
"cssFramework": "Tailwind CSS",
"language": "TypeScript",
"buildTool": "Vite",
"additionalContext": "Custom context"
}Example:
curl -X POST http://localhost:3001/api/combined \
-H "Content-Type: application/json" \
-d '{
"url": "https://example.com",
"crawlOptions": {
"maxUrls": 5,
"concurrency": 2
},
"testOptions": {
"includeScreenshot": true,
"timeout": 15000
},
"enableAI": true,
"projectContext": {
"framework": "React",
"cssFramework": "Tailwind CSS",
"language": "TypeScript"
}
}'Response:
{
"crawl": {
"pages": [
{
"url": "https://example.com",
"title": "Example Domain",
"description": "This domain is for use in illustrative examples",
"statusCode": 200,
"timestamp": "2024-01-01T00:00:00.000Z"
}
],
"totalPages": 1,
"crawlTime": 3000
},
"accessibility": {
"results": [
{
"url": "https://example.com",
"score": 85,
"violations": [
{
"id": "color-contrast",
"impact": "serious",
"description": "Elements must have sufficient color contrast",
"help": "Ensure all text elements have sufficient color contrast",
"helpUrl": "https://dequeuniversity.com/rules/axe/4.8/color-contrast",
"nodes": [...],
"aiExplanation": "This accessibility issue occurs when text doesn't have enough contrast...",
"aiRemediation": "To fix this issue:\n1. Increase color contrast ratio...\n2. Use CSS: color: #000; background: #fff;"
}
],
"passes": [],
"incomplete": [],
"inapplicable": [],
"screenshot": "https://storage.example.com/screenshots/uuid.png",
"timestamp": "2024-01-01T00:00:00.000Z",
"aiEnabled": true,
"aiError": null
}
],
"totalPages": 1,
"testTime": 15000
},
"totalTime": 18000
}Manage the intelligent caching system for AI responses.
Endpoint: GET /api/cache/stats
Example:
curl http://localhost:3001/api/cache/statsResponse:
{
"status": "success",
"data": {
"hits": 15,
"misses": 8,
"size": 12,
"hitRate": 0.65
}
}Endpoint: DELETE /api/cache/clear
Example:
curl -X DELETE http://localhost:3001/api/cache/clearResponse:
{
"status": "success",
"message": "Cache cleared successfully"
}🤖 AI Integration
LensCore includes optional AI-powered analysis for accessibility issues, providing plain language explanations and tech-stack specific remediation steps.
Features
- Plain Language Explanations: Convert technical accessibility issues into easy-to-understand explanations
- Tech-Stack Specific Remediation: Get specific, actionable steps tailored to your technology stack
- Dynamic Prompt Engineering: Intelligent prompt generation based on project context
- Structured Response Parsing: Consistent JSON response format with fallback handling
- Optional Processing: AI processing is opt-in and doesn't affect existing functionality
- Cost Effective: Only processes AI when explicitly requested
Usage
Project Context (Recommended):
{
"enableAI": true,
"projectContext": {
"framework": "React",
"cssFramework": "Tailwind CSS",
"language": "TypeScript",
"buildTool": "Vite"
}
}Backward Compatibility (Tech Stack String):
{
"enableAI": true,
"projectContext": {
"additionalContext": "React, TypeScript, Tailwind CSS"
}
}Response Fields
When AI is enabled, responses include additional fields:
aiExplanation: Plain language explanation of the accessibility issueaiRemediation: Specific steps to fix the issue with code examplesuserStory: Human-readable impact explanation for the accessibility issueaiEnabled: Boolean indicating if AI processing was successfulaiError: Error message if AI processing failed
Configuration
Set your OpenAI API key in environment variables:
OPENAI_API_KEY=your-openai-api-keyAI Prompt Engineering
LensCore uses advanced prompt engineering to generate context-aware responses:
Automatic Tech Stack Detection:
- Framework: React, Vue.js, Angular, Svelte, Next.js, Nuxt.js
- CSS Framework: Tailwind CSS, Bootstrap, Material UI, Chakra UI
- Language: TypeScript, JavaScript
- Build Tools: Webpack, Vite, Rollup, Parcel
Response Format:
{
"rule_id": "color-contrast",
"plain_explanation": "This text has insufficient contrast for users with visual impairments.",
"remediation": "Use Tailwind CSS classes like text-gray-800 or text-gray-900 for better contrast."
}Fallback Handling:
- Automatic fallback responses if AI fails
- Graceful degradation without breaking the API
- Consistent response structure
Examples
Test with AI (Project Context):
curl -X POST http://localhost:3001/api/test \
-H "Content-Type: application/json" \
-d '{
"url": "https://example.com",
"enableAI": true,
"projectContext": {
"framework": "Vue.js",
"cssFramework": "Bootstrap",
"language": "JavaScript"
}
}'Test with AI (Backward Compatibility):
curl -X POST http://localhost:3001/api/test \
-H "Content-Type: application/json" \
-d '{
"url": "https://example.com",
"enableAI": true,
"projectContext": {
"additionalContext": "Vue.js, JavaScript, Bootstrap"
}
}'Combined with AI:
curl -X POST http://localhost:3001/api/combined \
-H "Content-Type: application/json" \
-d '{
"url": "https://example.com",
"enableAI": true,
"projectContext": {
"framework": "Next.js",
"cssFramework": "Tailwind CSS",
"language": "TypeScript"
}
}'📄 License
This project is licensed under the MIT License - see the LICENSE file for details.
🙏 Acknowledgments
- axe-core for accessibility testing
- Puppeteer for web automation
- Express.js for the web framework
- OpenAI for AI-powered accessibility analysis
- Docker for containerization
Made with ❤️ by the AccessTime team
