B2BMGMT_Candle-Moondream-2 / moondreamWorker.js
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import init, { Model } from "./build/m.js";
async function fetchArrayBuffer(url, cacheModel = true) {
if (!cacheModel)
return new Uint8Array(await (await fetch(url)).arrayBuffer());
const cacheName = "moondream-candle-cache";
const cache = await caches.open(cacheName);
const cachedResponse = await cache.match(url);
if (cachedResponse) {
const data = await cachedResponse.arrayBuffer();
return new Uint8Array(data);
}
const res = await fetch(url, { cache: "force-cache" });
cache.put(url, res.clone());
return new Uint8Array(await res.arrayBuffer());
}
async function concatenateArrayBuffers(urls) {
const arrayBuffers = await Promise.all(
urls.map((url) => fetchArrayBuffer(url))
);
let totalLength = arrayBuffers.reduce(
(acc, arrayBuffer) => acc + arrayBuffer.byteLength,
0
);
let concatenatedBuffer = new Uint8Array(totalLength);
let offset = 0;
arrayBuffers.forEach((buffer) => {
concatenatedBuffer.set(new Uint8Array(buffer), offset);
offset += buffer.byteLength;
});
return concatenatedBuffer;
}
class Moondream {
static imageArrayHash = {};
static instance = {};
static currentModelID = null;
static async getInstance(weightsURL, modelID, tokenizerURL, quantized) {
// load individual modelID only once
if (!this.instance[modelID]) {
await init();
self.postMessage({ status: "loading", message: "Loading Model" });
const [weightsArrayU8, tokenizerArrayU8] = await Promise.all([
weightsURL instanceof Array
? concatenateArrayBuffers(weightsURL)
: fetchArrayBuffer(weightsURL),
fetchArrayBuffer(tokenizerURL),
]);
this.instance[modelID] = new Model(
weightsArrayU8,
tokenizerArrayU8,
quantized
);
}
this.currentModelID = modelID;
return this.instance[modelID];
}
// Remove the modelID parameter from setImageEmbeddings
static setImageEmbeddings(imageArrayU8) {
// check if image embeddings are already set for this image and model
const imageArrayHash = this.getSimpleHash(imageArrayU8);
if (
this.imageArrayHash[this.currentModelID] === imageArrayHash &&
this.instance[this.currentModelID]
) {
self.postMessage({
status: "embedding",
message: "Embeddings Already Set",
});
return;
}
this.imageArrayHash[this.currentModelID] = imageArrayHash;
this.instance[this.currentModelID].set_image_embeddings(imageArrayU8);
self.postMessage({ status: "embedding", message: "Embeddings Set" });
}
static getSimpleHash(imageArrayU8) {
// get simple hash of imageArrayU8
let imageArrayHash = 0;
for (let i = 0; i < imageArrayU8.length; i += 100) {
imageArrayHash ^= imageArrayU8[i];
}
return imageArrayHash.toString(16);
}
}
let controller = null;
self.addEventListener("message", (event) => {
if (event.data.command === "start") {
controller = new AbortController();
generate(event.data);
} else if (event.data.command === "abort") {
controller.abort();
}
});
async function generate(data) {
const {
weightsURL,
modelID,
tokenizerURL,
quantized,
imageURL,
prompt,
seed,
temp,
top_p,
repeatPenalty,
maxSeqLen,
verbose_prompt,
} = data;
try {
self.postMessage({ status: "loading", message: "Starting Moondream" });
const model = await Moondream.getInstance(
weightsURL,
modelID,
tokenizerURL,
quantized
);
self.postMessage({ status: "loading", message: "Initializing model" });
self.postMessage({ status: "loading", message: "Loading Image" });
const imageArrayU8 = await fetchArrayBuffer(imageURL, false);
self.postMessage({ status: "embedding", message: "Creating Embeddings" });
Moondream.setImageEmbeddings(imageArrayU8);
self.postMessage({
status: "complete-embedding",
message: "Embeddings Complete",
});
const { token, token_id } = model.init_with_image_prompt({
prompt,
seed: BigInt(seed),
temp: parseFloat(temp),
top_p: parseFloat(top_p),
repeat_penalty: parseFloat(repeatPenalty),
repeat_last_n: 64,
verbose_prompt,
});
const seq_len = 2048;
let sentence = token;
let maxTokens = maxSeqLen ? maxSeqLen : seq_len - prompt.length - 1;
let startTime = performance.now();
let tokensCount = 0;
while (tokensCount < maxTokens) {
await new Promise(async (resolve) => {
if (controller && controller.signal.aborted) {
console.log("Aborted");
self.postMessage({
status: "aborted",
message: "Aborted",
output: prompt + sentence,
});
return;
}
const { token, token_id } = await model.next_token();
if (token_id === 50256) {
// <|endoftext|>
self.postMessage({
status: "complete",
message: "complete",
output: prompt + sentence,
});
return;
}
const tokensSec =
((tokensCount + 1) / (performance.now() - startTime)) * 1000;
sentence += token;
self.postMessage({
status: "generating",
message: "Generating token",
token: token,
sentence: sentence,
totalTime: performance.now() - startTime,
tokensSec,
prompt: prompt,
});
setTimeout(resolve, 0);
});
tokensCount++;
}
self.postMessage({
status: "complete",
message: "complete",
output: prompt + sentence,
});
} catch (e) {
self.postMessage({ error: e });
}
}