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// This demo requires importScripts, so we use a local, pre-built JavaScript bundle.
importScripts('/mediapipe_genai_bundle.js'); // from npm @mediapipe/tasks-genai@0.10.24
const { FilesetResolver, LlmInference } = self.BundledCode;
let llmInference;
let modelPath = './myemoji-gemma-3-270m-it.task'; // UPDATE TO MATCH YOUR MODEL FILE
// Listen for messages from the main thread
self.onmessage = async (event) => {
const { type, data } = event.data;
console.log("[Worker] Received message:", { type, data });
switch (type) {
case "load":
try {
console.log("[Worker] Loading model...");
// Load the model in the worker thread
const genai = await FilesetResolver.forGenAiTasks('https://cdn.jsdelivr.net/npm/@mediapipe/tasks-genai@latest/wasm');
llmInference = await LlmInference.createFromOptions(genai, {
baseOptions: {
modelAssetPath: modelPath
},
maxTokens: 32,
temperature: .8,
forceF32: true,
});
console.log("[Worker] Model loaded successfully.");
self.postMessage({ type: "loaded" });
} catch (error) {
console.error("[Worker] Error loading model:", error);
self.postMessage({ type: "error", data: error.message });
}
break;
case "generate":
if (!llmInference) {
console.error("[Worker] Generation failed: model not loaded yet.");
self.postMessage({ type: "error", data: "Model not loaded yet." });
return;
}
try {
const generatedResponses = new Set();
const prompt = `<start_of_turn>user\nTranslate this text to emoji: ${data.prompt}<end_of_turn>\n<start_of_turn>model\n`;
// Request 3 unique, clean responses from the model
for (let i = 0; i < 3; i++) {
const modifiedPrompt = prompt + ' '.repeat(i);
const rawResponse = await llmInference.generateResponse(modifiedPrompt);
const cleanResponse = rawResponse.replace(/[^\p{Emoji}\s\u200D]/gu, '').trim();
if (cleanResponse) {
generatedResponses.add(cleanResponse);
}
}
generatedResponses.forEach(response => {
self.postMessage({ type: "result", data: response + '\n' });
});
self.postMessage({ type: "complete" });
} catch (error) {
console.error("[Worker] Error during generation:", error);
self.postMessage({ type: "error", data: error.message });
}
break;
}
};
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