feat: Enhance image processing in data-fetching and update SEO meta tags for product images; add Telegram assistant link in ChatAssistant component with localization support
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sebseb7
@@ -186,80 +186,98 @@ const saveProductImages = async (socket, products, categoryName, outputDir) => {
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.filter((id) => id);
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if (imageIds.length > 0) {
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// Process first image for each product
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// Process first image for each product — store AVIF + JPEG (e.g. for Twitter / social)
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const bildId = parseInt(imageIds[0]);
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const estimatedFilename = `prod${bildId}.avif`; // We'll generate a filename based on the ID
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const avifFilename = `prod${bildId}.avif`;
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const jpegFilename = `prod${bildId}.jpg`;
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const avifPath = path.join(assetsPath, avifFilename);
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const jpegPath = path.join(assetsPath, jpegFilename);
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const imagePath = path.join(assetsPath, estimatedFilename);
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// Skip if image already exists
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if (fs.existsSync(imagePath)) {
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if (fs.existsSync(avifPath) && fs.existsSync(jpegPath)) {
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imagesSkipped++;
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continue;
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}
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const writeAvifAndJpegFromBuffer = async (buf) => {
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if (!fs.existsSync(avifPath)) {
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await sharp(buf).avif().toFile(avifPath);
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}
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if (!fs.existsSync(jpegPath)) {
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await sharp(buf)
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.jpeg({ quality: 85, mozjpeg: true })
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.toFile(jpegPath);
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}
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};
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try {
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const imageBuffer = await fetchProductImage(socket, bildId);
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// If overlay exists, apply it to the image
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if (false && fs.existsSync(overlayPath)) {
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try {
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// Get image dimensions to center the overlay
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const baseImage = sharp(Buffer.from(imageBuffer));
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const baseMetadata = await baseImage.metadata();
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const overlaySize = Math.min(baseMetadata.width, baseMetadata.height) * 0.4;
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// Resize overlay to 20% of base image size and get its buffer
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const resizedOverlayBuffer = await sharp(overlayPath)
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.resize({
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width: Math.round(overlaySize),
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height: Math.round(overlaySize),
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fit: 'contain', // Keep full overlay visible
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background: { r: 0, g: 0, b: 0, alpha: 0 } // Transparent background instead of black bars
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})
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.toBuffer();
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// Calculate center position for the resized overlay
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const centerX = Math.floor((baseMetadata.width - overlaySize) / 2);
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const centerY = Math.floor((baseMetadata.height - overlaySize) / 2);
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const processedImageBuffer = await baseImage
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.composite([
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{
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input: resizedOverlayBuffer,
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top: centerY,
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left: centerX,
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blend: "multiply", // Darkens the image, visible on all backgrounds
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opacity: 0.3,
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},
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])
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.avif() // Ensure output is AVIF
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.toBuffer();
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fs.writeFileSync(imagePath, processedImageBuffer);
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console.log(
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` ✅ Applied centered inverted sh.avif overlay to ${estimatedFilename}`
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);
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} catch (overlayError) {
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console.log(
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` ⚠️ Failed to apply overlay to ${estimatedFilename}: ${overlayError.message}`
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);
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// Fallback: save without overlay
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fs.writeFileSync(imagePath, Buffer.from(imageBuffer));
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}
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if (fs.existsSync(avifPath) && !fs.existsSync(jpegPath)) {
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await sharp(avifPath)
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.jpeg({ quality: 85, mozjpeg: true })
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.toFile(jpegPath);
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} else if (!fs.existsSync(avifPath) && fs.existsSync(jpegPath)) {
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await sharp(jpegPath).avif().toFile(avifPath);
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} else {
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// Save without overlay if overlay file doesn't exist
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fs.writeFileSync(imagePath, Buffer.from(imageBuffer));
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const imageBuffer = await fetchProductImage(socket, bildId);
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const buf = Buffer.from(imageBuffer);
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// If overlay exists, apply it to the image
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if (false && fs.existsSync(overlayPath)) {
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try {
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const baseImage = sharp(buf);
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const baseMetadata = await baseImage.metadata();
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const overlaySize =
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Math.min(baseMetadata.width, baseMetadata.height) * 0.4;
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const resizedOverlayBuffer = await sharp(overlayPath)
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.resize({
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width: Math.round(overlaySize),
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height: Math.round(overlaySize),
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fit: "contain",
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background: { r: 0, g: 0, b: 0, alpha: 0 },
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})
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.toBuffer();
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const centerX = Math.floor(
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(baseMetadata.width - overlaySize) / 2
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);
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const centerY = Math.floor(
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(baseMetadata.height - overlaySize) / 2
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);
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const processedImageBuffer = await baseImage
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.composite([
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{
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input: resizedOverlayBuffer,
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top: centerY,
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left: centerX,
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blend: "multiply",
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opacity: 0.3,
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},
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])
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.toBuffer();
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await writeAvifAndJpegFromBuffer(processedImageBuffer);
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console.log(
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` ✅ Applied overlay → ${avifFilename} + ${jpegFilename}`
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);
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} catch (overlayError) {
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console.log(
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` ⚠️ Failed to apply overlay to prod${bildId}: ${overlayError.message}`
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);
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await writeAvifAndJpegFromBuffer(buf);
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}
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} else {
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await writeAvifAndJpegFromBuffer(buf);
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}
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}
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imagesSaved++;
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// Small delay to avoid overwhelming server
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await new Promise((resolve) => setTimeout(resolve, 50));
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} catch (error) {
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console.log(
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` ⚠️ Failed to fetch image ${estimatedFilename} (ID: ${bildId}): ${error.message}`
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` ⚠️ Failed to fetch/save prod${bildId} (${avifFilename} / ${jpegFilename}): ${error.message}`
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);
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}
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}
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@@ -1,13 +1,18 @@
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const generateProductMetaTags = (product, baseUrl, config) => {
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const productUrl = `${baseUrl}/Artikel/${product.seoName}`;
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const imageUrl =
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product.pictureList && product.pictureList.trim()
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? `${baseUrl}/assets/images/prod${product.pictureList
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.split(",")[0]
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.trim()}.avif`
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: `${baseUrl}/assets/images/nopicture.jpg`;
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const pictureFirstId =
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product.pictureList && product.pictureList.trim()
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? product.pictureList.split(",")[0].trim()
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: null;
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const imageUrl = pictureFirstId
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? `${baseUrl}/assets/images/prod${pictureFirstId}.avif`
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: `${baseUrl}/assets/images/nopicture.jpg`;
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const twitterImageUrl = pictureFirstId
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? `${baseUrl}/assets/images/prod${pictureFirstId}.jpg`
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: `${baseUrl}/assets/images/nopicture.jpg`;
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// Clean description for meta (remove HTML tags and limit length)
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const cleanDescription = product.kurzBeschreibung
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@@ -32,7 +37,7 @@ const generateProductMetaTags = (product, baseUrl, config) => {
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<!-- Open Graph Meta Tags -->
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<meta property="og:title" content="${product.name}">
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<meta property="og:description" content="${cleanDescription}">
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<meta property="og:image" content="${imageUrl}">
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<meta property="og:image" content="${twitterImageUrl}">
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<meta property="og:url" content="${productUrl}">
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<meta property="og:type" content="product">
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<meta property="og:site_name" content="${config.siteName}">
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@@ -49,7 +54,7 @@ const generateProductMetaTags = (product, baseUrl, config) => {
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<meta name="twitter:card" content="summary_large_image">
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<meta name="twitter:title" content="${product.name}">
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<meta name="twitter:description" content="${cleanDescription}">
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<meta name="twitter:image" content="${imageUrl}">
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<meta name="twitter:image" content="${twitterImageUrl}">
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<!-- Additional Meta Tags -->
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<meta name="robots" content="index, follow">
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@@ -64,12 +69,13 @@ const generateProductMetaTags = (product, baseUrl, config) => {
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const generateProductJsonLd = (product, baseUrl, config, categoryInfo = null) => {
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const productUrl = `${baseUrl}/Artikel/${product.seoName}`;
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const imageUrl =
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const pictureFirstId =
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product.pictureList && product.pictureList.trim()
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? `${baseUrl}/assets/images/prod${product.pictureList
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.split(",")[0]
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.trim()}.avif`
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: `${baseUrl}/assets/images/nopicture.jpg`;
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? product.pictureList.split(",")[0].trim()
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: null;
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const imageUrl = pictureFirstId
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? `${baseUrl}/assets/images/prod${pictureFirstId}.avif`
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: `${baseUrl}/assets/images/nopicture.jpg`;
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// Clean description for JSON-LD (remove HTML tags)
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const cleanDescription = product.description
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