fix: multiple improvements to TTS modal and language switching
- Fix TTS speed control: change default to 0.9, step by 0.05, max 2.0 - Apply playbackRate to audio element so speed actually works - Add refreshModalUI() function to update UI when language changes - Re-add upstream tokenizer API with simplified token counting - Format token counts with commas (e.g., 8,432 tokens) - Add getTokenCount() for simple integer token counts - Language switching now refreshes modal UI without hard refresh
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5 changed files with 137 additions and 11 deletions
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@ -301,6 +301,87 @@ export class SimpleBPETokenizer {
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// Export singleton instance
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export const tokenizer = new SimpleBPETokenizer();
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// Use upstream tokenizer API for accurate token counting
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export async function countTokensWithUpstream(text, model) {
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const { API_KEY } = await import("./config.js");
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const { getSelectedModel, getSelectedModelEndpoint } = await import("./models.js");
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try {
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const response = await fetch(`${getSelectedModelEndpoint()}/tokenize`, {
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method: "POST",
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headers: {
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"Content-Type": "application/json",
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Authorization: `Bearer ${API_KEY}`,
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},
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body: JSON.stringify({
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model: model || getSelectedModel(),
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prompt: text,
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add_special_tokens: true,
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}),
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});
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if (!response.ok) {
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console.warn(`Upstream tokenizer failed (${response.status}), falling back to JS tokenizer`);
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return tokenizer.count(text);
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}
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const tokens = await response.json();
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// Simply count the length of the token array
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const tokenCount = tokens.length;
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console.log(`Upstream tokenizer: ${tokenCount.toLocaleString()} tokens for ${text.length.toLocaleString()} chars`);
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// Return in same format as JS tokenizer for compatibility
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return {
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totalTokens: tokenCount,
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regularTokens: tokenCount,
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specialTokens: 0,
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breakdown: {
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words: Math.ceil(tokenCount * 0.7),
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numbers: Math.ceil(tokenCount * 0.1),
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punctuation: Math.ceil(tokenCount * 0.1),
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whitespace: Math.ceil(tokenCount * 0.1),
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},
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textLength: text.length,
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};
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} catch (error) {
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console.warn("Error with upstream tokenizer, falling back to JS tokenizer:", error);
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return tokenizer.count(text);
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}
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}
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// Get just the token count as a number from upstream
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export async function getTokenCount(text, model) {
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const { API_KEY } = await import("./config.js");
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const { getSelectedModel, getSelectedModelEndpoint } = await import("./models.js");
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try {
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const response = await fetch(`${getSelectedModelEndpoint()}/tokenize`, {
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method: "POST",
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headers: {
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"Content-Type": "application/json",
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Authorization: `Bearer ${API_KEY}`,
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},
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body: JSON.stringify({
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model: model || getSelectedModel(),
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prompt: text,
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add_special_tokens: true,
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}),
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});
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if (!response.ok) {
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throw new Error(`Tokenizer API error: ${response.status}`);
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}
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const tokens = await response.json();
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return tokens.length;
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} catch (error) {
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console.warn("Upstream tokenizer error:", error);
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// Fallback to JS estimate
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return tokenizer.count(text).totalTokens;
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}
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}
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// Convenience functions
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export function countTokens(text) {
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return tokenizer.count(text);
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@ -310,3 +391,8 @@ export function estimateTokens(text) {
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const result = tokenizer.count(text);
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return result.totalTokens;
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}
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// Format token count as a string with commas (e.g., "8,432 tokens")
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export function formatTokenCount(count) {
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return `${count.toLocaleString()} tokens`;
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}
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@ -284,13 +284,14 @@ export function openTranslateModal() {
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translateButton.disabled = true;
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resultContainer.style.display = "none";
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// Get token count and estimated time for progress
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const { countTokens } = await import("./token_estimator.js");
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// Get token count and estimated time for progress using upstream tokenizer
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const { countTokensWithUpstream } = await import("./token_estimator.js");
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const { estimateProcessingTime } = await import("./translation.js");
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const { getSelectedModel } = await import("./models.js");
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const textToAnalyze = isPageMode
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? document.documentElement.outerHTML
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: textArea.value.trim();
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const tokenInfo = countTokens(textToAnalyze);
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const tokenInfo = await countTokensWithUpstream(textToAnalyze, getSelectedModel());
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const estimatedSeconds = estimateProcessingTime(tokenInfo.totalTokens);
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// Create progress indicator
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@ -1,6 +1,6 @@
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import { API_KEY } from "./config.js";
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import { getSelectedModel, getSelectedModelEndpoint } from "./models.js";
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import { countTokens } from "./token_estimator.js";
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import { countTokens, countTokensWithUpstream } from "./token_estimator.js";
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// Languages supported by Hermes 3 model (in English for reference)
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export const SUPPORTED_LANGUAGES = {
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@ -237,8 +237,8 @@ export async function translateText(text, targetLanguage) {
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const { fetchModelsFromEndpoints } = await import("./models.js");
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await fetchModelsFromEndpoints();
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// Get accurate token count and timing estimate
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const tokenInfo = countTokens(text);
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// Get accurate token count and timing estimate using upstream tokenizer
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const tokenInfo = await countTokensWithUpstream(text, getSelectedModel());
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const estimatedSeconds = estimateProcessingTime(tokenInfo.totalTokens);
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console.log("=== TRANSLATION ANALYSIS ===");
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@ -191,16 +191,16 @@ export function openTTSModal() {
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const speedLabel = document.createElement("label");
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const speedValue = document.createElement("span");
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speedValue.textContent = "1.0";
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speedValue.textContent = "0.9";
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speedLabel.textContent = `${getUIText("speedLabel")} ${speedValue.textContent}`;
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speedLabel.setAttribute("data-i18n", "speedLabel");
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const speedSlider = document.createElement("input");
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speedSlider.type = "range";
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speedSlider.min = "0.25";
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speedSlider.max = "4.0";
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speedSlider.step = "0.25";
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speedSlider.value = "1.0";
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speedSlider.max = "2.0";
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speedSlider.step = "0.05";
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speedSlider.value = "0.9";
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speedSlider.oninput = () => {
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speedValue.textContent = speedSlider.value;
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speedLabel.textContent = `${getUIText("speedLabel")} ${speedSlider.value}`;
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@ -286,6 +286,7 @@ export function openTTSModal() {
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// Create hidden audio element (no controls)
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const audio = new Audio(result.blobUrl);
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audio.preload = "auto";
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audio.playbackRate = speed; // Apply the speed setting!
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// Create custom control container
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const controlsContainer = document.createElement("div");
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@ -121,7 +121,42 @@ function addCodeBlockCopyButtons(element) {
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pre.appendChild(copyBtn);
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}
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});
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}async function openUncloseaiEmbeddedModalNew() {
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}
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// Function to refresh modal UI when language changes
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function refreshModalUI() {
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// Refresh all elements with data-i18n attributes in the modal
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const modal = document.getElementById("uncloseai-embedded-modal");
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if (!modal) return;
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const elementsWithI18n = modal.querySelectorAll("[data-i18n]");
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elementsWithI18n.forEach((element) => {
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const key = element.getAttribute("data-i18n");
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const translatedText = getUIText(key);
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if (element.tagName === "INPUT" && element.type === "text") {
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element.placeholder = translatedText;
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} else if (element.tagName === "BUTTON" || element.tagName === "LABEL") {
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// Preserve any icons/emojis at the start
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const currentText = element.textContent;
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const iconMatch = currentText.match(/^[^\w\s]+\s*/);
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const icon = iconMatch ? iconMatch[0] : '';
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element.textContent = icon + translatedText;
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} else {
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element.textContent = translatedText;
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}
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});
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// Update any specific elements that need special handling
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const titleElement = modal.querySelector("h1");
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if (titleElement) {
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titleElement.innerHTML = `<span style="font-family: 'ChunkFiveRegular', monospace;">uncloseai.</span> ${getUIText("hermesTitle")}`;
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}
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console.log("Modal UI language refreshed");
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}
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async function openUncloseaiEmbeddedModalNew() {
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// Ensure ChunkFive font is loaded
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initializeChunkFiveFont();
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@ -495,6 +530,9 @@ function addCodeBlockCopyButtons(element) {
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// Show confirmation
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const selectedOption = languageSelect.options[languageSelect.selectedIndex];
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console.log(`Language changed to: ${selectedOption.textContent}`);
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// Refresh all UI text in the modal
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refreshModalUI();
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// Notify user to refresh for full effect
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setTimeout(() => {
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