Files
crawl4ai/docs/examples/website-to-api/static/script.js
Soham Kukreti b1dff5a4d3 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
2025-08-24 18:52:37 +05:30

401 lines
13 KiB
JavaScript

// API Configuration
const API_BASE_URL = 'http://localhost:8000';
// DOM Elements
const navLinks = document.querySelectorAll('.nav-link');
const pages = document.querySelectorAll('.page');
const scrapeForm = document.getElementById('scrape-form');
const modelForm = document.getElementById('model-form');
const modelSelect = document.getElementById('model-select');
const modelsList = document.getElementById('models-list');
const resultsSection = document.getElementById('results-section');
const loadingSection = document.getElementById('loading');
const copyJsonBtn = document.getElementById('copy-json');
// Navigation
navLinks.forEach(link => {
link.addEventListener('click', (e) => {
e.preventDefault();
const targetPage = link.dataset.page;
// Update active nav link
navLinks.forEach(l => l.classList.remove('active'));
link.classList.add('active');
// Show target page
pages.forEach(page => page.classList.remove('active'));
document.getElementById(`${targetPage}-page`).classList.add('active');
// Load data for the page
if (targetPage === 'models') {
loadModels();
} else if (targetPage === 'requests') {
loadSavedRequests();
}
});
});
// Scrape Form Handler
document.getElementById('extract-btn').addEventListener('click', async (e) => {
e.preventDefault();
// Scroll to results section immediately when button is clicked
document.getElementById('results-section').scrollIntoView({
behavior: 'smooth',
block: 'start'
});
const url = document.getElementById('url').value;
const query = document.getElementById('query').value;
const headless = true; // Always use headless mode
const model_name = document.getElementById('model-select').value || null;
const scraping_approach = document.getElementById('scraping-approach').value;
if (!url || !query) {
showToast('Please fill in both URL and query fields', 'error');
return;
}
if (!model_name) {
showToast('Please select a model from the dropdown or add one from the Models page', 'error');
return;
}
const data = {
url: url,
query: query,
headless: headless,
model_name: model_name
};
// Show loading state
showLoading(true);
hideResults();
try {
// Choose endpoint based on scraping approach
const endpoint = scraping_approach === 'llm' ? '/scrape-with-llm' : '/scrape';
const response = await fetch(`${API_BASE_URL}${endpoint}`, {
method: 'POST',
headers: {
'Content-Type': 'application/json'
},
body: JSON.stringify(data)
});
const result = await response.json();
if (response.ok) {
displayResults(result);
showToast(`Data extracted successfully using ${scraping_approach === 'llm' ? 'LLM-based' : 'Schema-based'} approach!`, 'success');
} else {
throw new Error(result.detail || 'Failed to extract data');
}
} catch (error) {
console.error('Scraping error:', error);
showToast(`Error: ${error.message}`, 'error');
} finally {
showLoading(false);
}
});
// Model Form Handler
modelForm.addEventListener('submit', async (e) => {
e.preventDefault();
const formData = new FormData(modelForm);
const data = {
model_name: formData.get('model_name'),
provider: formData.get('provider'),
api_token: formData.get('api_token')
};
try {
const response = await fetch(`${API_BASE_URL}/models`, {
method: 'POST',
headers: {
'Content-Type': 'application/json'
},
body: JSON.stringify(data)
});
const result = await response.json();
if (response.ok) {
showToast('Model saved successfully!', 'success');
modelForm.reset();
loadModels();
loadModelSelect();
} else {
throw new Error(result.detail || 'Failed to save model');
}
} catch (error) {
console.error('Model save error:', error);
showToast(`Error: ${error.message}`, 'error');
}
});
// Copy JSON Button
copyJsonBtn.addEventListener('click', () => {
const actualJsonOutput = document.getElementById('actual-json-output');
const textToCopy = actualJsonOutput.textContent;
navigator.clipboard.writeText(textToCopy).then(() => {
showToast('JSON copied to clipboard!', 'success');
}).catch(() => {
showToast('Failed to copy JSON', 'error');
});
});
// Load Models
async function loadModels() {
try {
const response = await fetch(`${API_BASE_URL}/models`);
const result = await response.json();
if (response.ok) {
displayModels(result.models);
} else {
throw new Error(result.detail || 'Failed to load models');
}
} catch (error) {
console.error('Load models error:', error);
showToast(`Error: ${error.message}`, 'error');
}
}
// Display Models
function displayModels(models) {
if (models.length === 0) {
modelsList.innerHTML = '<p style="text-align: center; color: #7f8c8d; padding: 2rem;">No models saved yet. Add your first model above!</p>';
return;
}
modelsList.innerHTML = models.map(model => `
<div class="model-card">
<div class="model-info">
<div class="model-name">${model}</div>
<div class="model-provider">Model Configuration</div>
</div>
<div class="model-actions">
<button class="btn btn-danger" onclick="deleteModel('${model}')">
<i class="fas fa-trash"></i>
Delete
</button>
</div>
</div>
`).join('');
}
// Delete Model
async function deleteModel(modelName) {
if (!confirm(`Are you sure you want to delete the model "${modelName}"?`)) {
return;
}
try {
const response = await fetch(`${API_BASE_URL}/models/${modelName}`, {
method: 'DELETE'
});
const result = await response.json();
if (response.ok) {
showToast('Model deleted successfully!', 'success');
loadModels();
loadModelSelect();
} else {
throw new Error(result.detail || 'Failed to delete model');
}
} catch (error) {
console.error('Delete model error:', error);
showToast(`Error: ${error.message}`, 'error');
}
}
// Load Model Select Options
async function loadModelSelect() {
try {
const response = await fetch(`${API_BASE_URL}/models`);
const result = await response.json();
if (response.ok) {
// Clear existing options
modelSelect.innerHTML = '<option value="">Select a Model</option>';
// Add model options
result.models.forEach(model => {
const option = document.createElement('option');
option.value = model;
option.textContent = model;
modelSelect.appendChild(option);
});
}
} catch (error) {
console.error('Load model select error:', error);
}
}
// Display Results
function displayResults(result) {
// Update result info
document.getElementById('result-url').textContent = result.url;
document.getElementById('result-query').textContent = result.query;
document.getElementById('result-model').textContent = result.model_name || 'Default Model';
// Display JSON in the actual results section
const actualJsonOutput = document.getElementById('actual-json-output');
actualJsonOutput.textContent = JSON.stringify(result.extracted_data, null, 2);
// Don't update the sample JSON in the workflow demo - keep it as example
// Update the cURL example based on the approach used
const scraping_approach = document.getElementById('scraping-approach').value;
const endpoint = scraping_approach === 'llm' ? '/scrape-with-llm' : '/scrape';
const curlExample = document.getElementById('curl-example');
curlExample.textContent = `curl -X POST http://localhost:8000${endpoint} -H "Content-Type: application/json" -d '{"url": "${result.url}", "query": "${result.query}"}'`;
// Show results section
resultsSection.style.display = 'block';
resultsSection.scrollIntoView({ behavior: 'smooth' });
}
// Show/Hide Loading
function showLoading(show) {
loadingSection.style.display = show ? 'block' : 'none';
}
// Hide Results
function hideResults() {
resultsSection.style.display = 'none';
}
// Toast Notifications
function showToast(message, type = 'info') {
const toastContainer = document.getElementById('toast-container');
const toast = document.createElement('div');
toast.className = `toast ${type}`;
const icon = type === 'success' ? 'fas fa-check-circle' :
type === 'error' ? 'fas fa-exclamation-circle' :
'fas fa-info-circle';
toast.innerHTML = `
<i class="${icon}"></i>
<span>${message}</span>
`;
toastContainer.appendChild(toast);
// Auto remove after 5 seconds
setTimeout(() => {
toast.remove();
}, 5000);
}
// Load Saved Requests
async function loadSavedRequests() {
try {
const response = await fetch(`${API_BASE_URL}/saved-requests`);
const result = await response.json();
if (response.ok) {
displaySavedRequests(result.requests);
} else {
throw new Error(result.detail || 'Failed to load saved requests');
}
} catch (error) {
console.error('Load saved requests error:', error);
showToast(`Error: ${error.message}`, 'error');
}
}
// Display Saved Requests
function displaySavedRequests(requests) {
const requestsList = document.getElementById('requests-list');
if (requests.length === 0) {
requestsList.innerHTML = '<p style="text-align: center; color: #CCCCCC; padding: 2rem;">No saved API requests yet. Make your first request from the Scrape page!</p>';
return;
}
requestsList.innerHTML = requests.map(request => {
const url = request.body.url;
const query = request.body.query;
const model = request.body.model_name || 'Default Model';
const endpoint = request.endpoint;
// Create curl command
const curlCommand = `curl -X POST http://localhost:8000${endpoint} \\
-H "Content-Type: application/json" \\
-d '{
"url": "${url}",
"query": "${query}",
"model_name": "${model}"
}'`;
return `
<div class="request-card">
<div class="request-header">
<div class="request-info">
<div class="request-url">${url}</div>
<div class="request-query">${query}</div>
</div>
<div class="request-actions">
<button class="btn-danger" onclick="deleteSavedRequest('${request.id}')">
<i class="fas fa-trash"></i>
Delete
</button>
</div>
</div>
<div class="request-curl">
<h4>cURL Command:</h4>
<pre>${curlCommand}</pre>
</div>
</div>
`;
}).join('');
}
// Delete Saved Request
async function deleteSavedRequest(requestId) {
if (!confirm('Are you sure you want to delete this saved request?')) {
return;
}
try {
const response = await fetch(`${API_BASE_URL}/saved-requests/${requestId}`, {
method: 'DELETE'
});
const result = await response.json();
if (response.ok) {
showToast('Saved request deleted successfully!', 'success');
loadSavedRequests();
} else {
throw new Error(result.detail || 'Failed to delete saved request');
}
} catch (error) {
console.error('Delete saved request error:', error);
showToast(`Error: ${error.message}`, 'error');
}
}
// Initialize
document.addEventListener('DOMContentLoaded', () => {
loadModelSelect();
// Check if API is available
fetch(`${API_BASE_URL}/health`)
.then(response => {
if (!response.ok) {
showToast('Warning: API server might not be running', 'error');
}
})
.catch(() => {
showToast('Warning: Cannot connect to API server. Make sure it\'s running on localhost:8000', 'error');
});
});