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import os
document.getElementById('avgResponseTime').textContent = data.avg_request_time_ms.toFixed(0) + 'ms';
document.getElementById('concurrentRequests').textContent = data.concurrent_requests;
document.getElementById('requestsPerMinute').textContent = data.requests_per_minute;
document.getElementById('todayRequests').textContent = data.today_requests;
}
} catch (error) {
console.error('Error updating metrics:', error);
}
}
function showLoading(show) {
if (show) {
loadingModal.classList.remove('hidden');
} else {
loadingModal.classList.add('hidden');
}
}
function showNotification(message, type = 'info') {
const notification = document.createElement('div');
notification.className = `fixed top-4 right-4 p-4 rounded-lg shadow-lg z-50 ${
type === 'error' ? 'bg-red-500' : 'bg-indigo-500'
} text-white`;
notification.innerHTML = `
<div class="flex items-center">
<i class="fas ${type === 'error' ? 'fa-exclamation-circle' : 'fa-info-circle'} mr-2"></i>
<span>${message}</span>
</div>
`;
document.body.appendChild(notification);
setTimeout(() => {
notification.style.opacity = '0';
notification.style.transition = 'opacity 0.5s';
setTimeout(() => {
document.body.removeChild(notification);
}, 500);
}, 3000);
}
document.addEventListener('DOMContentLoaded', () => {
addMixedItem();
updateMetrics();
setInterval(updateMetrics, 30000);
});
</script>
</body>
</html>""")
print("Initializing models...")
with torch.inference_mode():
_ = model.generate(
**tokenizer(["Hello"], return_tensors="pt").to(model.device),
max_new_tokens=1, do_sample=False, use_cache=True
)
print("🚀 Starting AI Content Moderator API...")
if __name__ == "__main__":
uvicorn.run(app, host="0.0.0.0", port=7860) |