feat: Add comprehensive website to API example with frontend

This commit adds a complete, web scraping API example that demonstrates how to get structured data from any website and use it like an API using the crawl4ai library with a minimalist frontend interface.

Core Functionality
- AI-powered web scraping with plain English queries
- Dual scraping approaches: Schema-based (faster) and LLM-based (flexible)
- Intelligent schema caching for improved performance
- Custom LLM model support with API key management
- Automatic duplicate request prevention

Modern Frontend Interface
- Minimalist black-and-white design inspired by modern web apps
- Responsive layout with smooth animations and transitions
- Three main pages: Scrape Data, Models Management, API Request History
- Real-time results display with JSON formatting
- Copy-to-clipboard functionality for extracted data
- Toast notifications for user feedback
- Auto-scroll to results when scraping starts

Model Management System
- Web-based model configuration interface
- Support for any LLM provider (OpenAI, Gemini, Anthropic, etc.)
- Simplified configuration requiring only provider and API token
- Add, list, and delete model configurations
- Secure storage of API keys in local JSON files

API Request History
- Automatic saving of all API requests and responses
- Display of request history with URL, query, and cURL commands
- Duplicate prevention (same URL + query combinations)
- Request deletion functionality
- Clean, simplified display focusing on essential information

Technical Implementation

Backend (FastAPI)
- RESTful API with comprehensive endpoints
- Pydantic models for request/response validation
- Async web scraping with crawl4ai library
- Error handling with detailed error messages
- File-based storage for models and request history

Frontend (Vanilla JS/CSS/HTML)
- No framework dependencies - pure HTML, CSS, JavaScript
- Modern CSS Grid and Flexbox layouts
- Custom dropdown styling with SVG arrows
- Responsive design for mobile and desktop
- Smooth scrolling and animations

Core Library Integration
- WebScraperAgent class for orchestration
- ModelConfig class for LLM configuration management
- Schema generation and caching system
- LLM extraction strategy support
- Browser configuration with headless mode

docs/examples/website-to-api/test_api.py

@@ -0,0 +1,28 @@
+import asyncio
+from web_scraper_lib import scrape_website
+import os
+
+async def test_library():
+    """Test the mini library directly."""
+    print("=== Testing Mini Library ===")
+    
+    # Test 1: Scrape with a custom model
+    url = "https://marketplace.mainstreet.co.in/collections/adidas-yeezy/products/adidas-yeezy-boost-350-v2-yecheil-non-reflective"
+    query = "Extract the following data: Product name, Product price, Product description, Product size. DO NOT EXTRACT ANYTHING ELSE."
+    if os.path.exists("models"):
+        model_name = os.listdir("models")[0].split(".")[0]
+    else:
+        raise Exception("No models found in models directory")
+
+    print(f"Scraping: {url}")
+    print(f"Query: {query}")
+    
+    try:
+        result = await scrape_website(url, query, model_name)
+        print("✅ Library test successful!")
+        print(f"Extracted data: {result['extracted_data']}")
+    except Exception as e:
+        print(f"❌ Library test failed: {e}")
+
+if __name__ == "__main__":
+    asyncio.run(test_library())