config.js

/**
 * Configuration for LFM2-VL-450M Demo
 * WebGPU inference with ONNX models from HuggingFace Hub
 */

const HF_BASE = 'https://huggingface.co/onnx-community/LFM2-VL-450M-ONNX/resolve/main';

// Model configurations
export const MODELS = {
  'LFM2-VL-450M-FP16': {
    id: 'LFM2-VL-450M-FP16',
    path: HF_BASE,
    label: 'FP16 (Half Precision)',
    size: '~1.05 GB',
    quantization: { decoder: 'fp16', visionEncoder: 'fp16' }
  },
  'LFM2-VL-450M-FP32': {
    id: 'LFM2-VL-450M-FP32',
    path: HF_BASE,
    label: 'FP32 (Full Precision)',
    size: '~2.1 GB',
    quantization: { decoder: null, visionEncoder: null }
  }
};

// Default settings
export const DEFAULT_CONFIG = {
  defaultModel: 'LFM2-VL-450M-FP16',
  maxNewTokens: 512,
  temperature: 0.0
};

// Get config with optional env overrides
export function getConfig() {
  const config = { ...DEFAULT_CONFIG };

  if (typeof import.meta !== 'undefined' && import.meta.env) {
    if (import.meta.env.VITE_DEFAULT_MODEL) {
      config.defaultModel = import.meta.env.VITE_DEFAULT_MODEL;
    }
  }

  return config;
}

// Get model configuration by ID
export function getModelConfig(modelId) {
  return MODELS[modelId];
}

// Get all available models
export function getAvailableModels() {
  return Object.values(MODELS);
}