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Skip downloading transformer models if they already exist. #64

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26 changes: 26 additions & 0 deletions resources/shared/download-cache.mjs
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Original file line number Diff line number Diff line change
@@ -0,0 +1,26 @@
import fs from 'fs';

export default class DownloadCache {
cached = {};

constructor(filename, force) {
if (force) {
return;
}
this.filename = filename;
if (fs.existsSync(filename)) {
try {
this.cached = JSON.parse(fs.readFileSync(filename, 'utf8'));
} catch (err) {
console.warn(`Warning: Could not read cache file ${filename}:`, err.message);
}
}
}
has(key) {
return !!this.cached[key];
}
put(key) {
this.cached[key] = true;
fs.writeFileSync(this.filename, JSON.stringify(this.cached, null, 2));
}
}
82 changes: 62 additions & 20 deletions resources/transformers-js/src/download-models.mjs
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Original file line number Diff line number Diff line change
Expand Up @@ -3,6 +3,7 @@ import { KokoroTTS } from "kokoro-js";
import fs from 'fs';
import path from 'path';
import fetch from 'node-fetch';
import DownloadCache from '../../shared/download-cache.mjs';

const MODEL_DIR = './models';
env.localModelPath = MODEL_DIR;
Expand Down Expand Up @@ -48,6 +49,30 @@ const KOKORO_FILES = [
'tokenizer_config.json',
];

const MARGO_MODELS_TO_DOWNLOAD = [
{
class: 'SiglipVisionModel',
dtype: 'bnb4',
},
{
class: 'AutoImageProcessor',
},
{
class: 'SiglipTextModel',
dtype: 'bnb4',
},
{
class: 'AutoTokenizer',
dtype: 'bnb4',
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@rmahdav rmahdav Jan 23, 2026

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nit: I don't think AutoTokenizer has dtype.

}
];
const MARGO_NAME_TO_CLASS = {
'SiglipVisionModel': SiglipVisionModel,
'AutoImageProcessor': AutoImageProcessor,
'SiglipTextModel': SiglipTextModel,
'AutoTokenizer': AutoTokenizer,
};

function getHuggingFaceUrl(repo, filename, branch = 'main') {
if(filename.endsWith('.onnx')) {
return `https://huggingface.co/${repo}/resolve/${branch}/onnx/${filename}`;
Expand All @@ -56,6 +81,8 @@ function getHuggingFaceUrl(repo, filename, branch = 'main') {
}

async function downloadModels() {
const CACHE_FILE = path.join(MODEL_DIR, 'cache.json');
const cache = new DownloadCache(CACHE_FILE, process.argv.includes('--force'));
if (!fs.existsSync(MODEL_DIR)) {
console.log(`Creating directory: ${MODEL_DIR}`);
fs.mkdirSync(MODEL_DIR, { recursive: true });
Expand All @@ -71,6 +98,12 @@ async function downloadModels() {
for (const modelInfo of MODELS_TO_DOWNLOAD) {
const { id: modelId, task: modelTask, dtype: modelDType } = modelInfo;

const cacheKey = `${modelId}-${modelTask}-${modelDType}`;
if (cache.has(cacheKey)) {
console.log(`Model ${modelId} (${modelTask}, dtype: ${modelDType}) already cached. Skipping.`);
continue;
}

console.log(`Downloading files for ${modelId} (${modelTask}, dtype: ${modelDType})...`);

await pipeline(
Expand All @@ -82,34 +115,41 @@ async function downloadModels() {
});

console.log(`Successfully downloaded and cached ${modelId}`);
cache.put(cacheKey);
}

// Download Marqo/marqo-fashionSigLIP model
console.log(`Downloading files for Marqo/marqo-fashionSigLIP (zero-shot-image-classification, dtype: bnb4)...`);
await SiglipVisionModel.from_pretrained("Marqo/marqo-fashionSigLIP" ,{
cache_dir: env.localModelPath,
dtype: 'bnb4'
});
await AutoImageProcessor.from_pretrained("Marqo/marqo-fashionSigLIP", {
cache_dir: env.localModelPath,
});
await SiglipTextModel.from_pretrained("Marqo/marqo-fashionSigLIP", {
cache_dir: env.localModelPath,
dtype: 'bnb4'
});
await AutoTokenizer.from_pretrained("Marqo/marqo-fashionSigLIP", {
cache_dir: env.localModelPath,
});
console.log(`Successfully downloaded and cached Marqo/marqo-fashionSigLIP`);
console.log(`Checking Marqo/marqo-fashionSigLIP models...`);
for (const modelInfo of MARGO_MODELS_TO_DOWNLOAD) {
const cacheKey = `${modelInfo.class}-${modelInfo.dtype}`;
if (cache.has(cacheKey)) {
console.log(`Model ${modelInfo.class} (dtype: ${modelInfo.dtype}) already cached. Skipping.`);
continue;
}

console.log(`Downloading Marqo/marqo-fashionSigLIP (${modelInfo.class}${modelInfo.dtype ? `, dtype: ${modelInfo.dtype}` : ''})...`);
await MARGO_NAME_TO_CLASS[modelInfo.class].from_pretrained("Marqo/marqo-fashionSigLIP", {
cache_dir: env.localModelPath,
dtype: modelInfo.dtype
});

cache.put(cacheKey);
}
console.log(`Successfully checked Marqo/marqo-fashionSigLIP`);

// Download onnx-community/Kokoro-82M-v1.0-ONNX model
console.log(`Starting manual download for ${KOKORO_REPO}...`);
console.log(`Starting manual download check for ${KOKORO_REPO}...`);
const kokoroModelPath = path.join(MODEL_DIR, KOKORO_REPO);
if (!fs.existsSync(kokoroModelPath)) {
fs.mkdirSync(kokoroModelPath, { recursive: true });
}

for (const filename of KOKORO_FILES) {
const cacheKey = `${KOKORO_REPO}-${filename}`;
if (cache.has(cacheKey)) {
console.log(` ${filename} already exists, skipping.`);
continue;
}
const isOnnxFile = filename.endsWith('.onnx') || filename.endsWith('.onnx_data');
const modelUrl = getHuggingFaceUrl(KOKORO_REPO, filename);
let outputPath;
Expand All @@ -136,11 +176,13 @@ async function downloadModels() {
response.body.on('error', reject);
fileStream.on('finish', resolve);
});

cache.put(cacheKey);
} catch (err) {
console.error(` Failed to download ${filename}:`, err.message);
}
}
console.log(`Successfully downloaded all files for ${KOKORO_REPO}`);
console.log(`Successfully checked all files for ${KOKORO_REPO}`);

} catch (err) {
console.error("Model download failed:", err);
Expand All @@ -151,6 +193,6 @@ async function downloadModels() {
}

downloadModels().catch(err => {
console.error("Download process terminated.");
console.error("Download process terminated.", err);
process.exit(1);
});
});