Function load_model

webui/app.py:627–663

Load Kronos model

()

@app.route('/api/load-model', methods=['POST'])
def load_model():
    """Load Kronos model"""
    global tokenizer, model, predictor
    
    try:
        if not MODEL_AVAILABLE:
            return jsonify({'error': 'Kronos model library not available'}), 400
        
        data = request.get_json()
        model_key = data.get('model_key', 'kronos-small')
        device = data.get('device', 'cpu')
        
        if model_key not in AVAILABLE_MODELS:
            return jsonify({'error': f'Unsupported model: {model_key}'}), 400
        
        model_config = AVAILABLE_MODELS[model_key]
        
        # Load tokenizer and model
        tokenizer = KronosTokenizer.from_pretrained(model_config['tokenizer_id'])
        model = Kronos.from_pretrained(model_config['model_id'])
        
        # Create predictor
        predictor = KronosPredictor(model, tokenizer, device=device, max_context=model_config['context_length'])
        
        return jsonify({
            'success': True,
            'message': f'Model loaded successfully: {model_config["name"]} ({model_config["params"]}) on {device}',
            'model_info': {
                'name': model_config['name'],
                'params': model_config['params'],
                'context_length': model_config['context_length'],
                'description': model_config['description']
            }
        })
        
    except Exception as e:
        return jsonify({'error': f'Model loading failed: {str(e)}'}), 500

@app.route('/api/available-models')
def get_available_models():