Worker ES module: importScripts → import (wasm-pack --target web)

wasm-pack --target web generoi ES module -syntaksia (export).
Worker käyttää nyt type:'module' ja import-lauseita importScripts:n sijaan.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

network-poc/hub/src/main.rs

@@ -1080,7 +1080,7 @@ async fn api_chat_completions(
         }
     }
 
-    let timeout = tokio::time::timeout(std::time::Duration::from_secs(120), async move {
+    let timeout = tokio::time::timeout(std::time::Duration::from_secs(600), async move {
         loop {
             let msg_str = match rx.recv().await {
                 Ok(msg) => msg,

network-poc/node/src/lib.rs

@@ -38,17 +38,50 @@ pub fn set_gpu_load(load: u32) {
     console_log!("[Wasm] GPU Kuormitusraja vaihdettu -> {}%", load);
 }
 
-// Asynkroninen odotus WebAssemblylle
-async fn sleep_ms(ms: i32) {
+// Worker-yhteensopiva setTimeout — toimii sekä Window- että Worker-kontekstissa
+#[wasm_bindgen]
+extern "C" {
+    #[wasm_bindgen(js_name = setTimeout)]
+    fn set_timeout(closure: &js_sys::Function, ms: i32);
+}
+
+// Asynkroninen odotus WebAssemblylle (Window + Worker)
+pub async fn sleep_ms(ms: i32) {
     let promise = js_sys::Promise::new(&mut |resolve, _| {
-        web_sys::window()
-            .unwrap()
-            .set_timeout_with_callback_and_timeout_and_arguments_0(&resolve, ms)
-            .unwrap();
+        set_timeout(&resolve, ms);
     });
     let _ = wasm_bindgen_futures::JsFuture::from(promise).await;
 }
 
+// Worker-yhteensopiva Performance — käyttää globalThis.performance
+pub fn perf_now() -> f64 {
+    js_sys::Reflect::get(&js_sys::global(), &"performance".into())
+        .ok()
+        .and_then(|p| js_sys::Reflect::get(&p, &"now".into()).ok())
+        .and_then(|f| f.dyn_into::<js_sys::Function>().ok())
+        .and_then(|f| {
+            let perf = js_sys::Reflect::get(&js_sys::global(), &"performance".into()).unwrap();
+            f.call0(&perf).ok()
+        })
+        .and_then(|v| v.as_f64())
+        .unwrap_or(0.0)
+}
+
+// Worker-yhteensopiva fetch — käyttää globalThis.fetch
+pub async fn worker_fetch(url: &str) -> Result<web_sys::Response, String> {
+    let promise = js_sys::Reflect::get(&js_sys::global(), &"fetch".into())
+        .map_err(|_| "fetch ei saatavilla".to_string())?
+        .dyn_into::<js_sys::Function>()
+        .map_err(|_| "fetch ei funktio".to_string())?
+        .call1(&JsValue::NULL, &url.into())
+        .map_err(|e| format!("fetch: {:?}", e))?;
+    let resp = wasm_bindgen_futures::JsFuture::from(js_sys::Promise::from(promise))
+        .await
+        .map_err(|e| format!("fetch await: {:?}", e))?;
+    resp.dyn_into::<web_sys::Response>()
+        .map_err(|_| "ei Response".to_string())
+}
+
 // Geneerinen tensorilaskenta — toimii millä tahansa Burn-backendillä
 fn run_matmul<B: burn::tensor::backend::Backend>(size: usize) -> String {
     let device = Default::default();
@@ -123,10 +156,9 @@ async fn run_single_tokenize(text: String, ws: Rc<RefCell<WebSocket>>) {
     let Some(bytes) = cached_tok else { return; };
     let Ok(tokenizer) = tokenizers::Tokenizer::from_bytes(&bytes) else { return; };
 
-    let perf = web_sys::window().unwrap().performance().unwrap();
-    let start = perf.now();
+    let start = perf_now();
     let result = tokenize_text(&tokenizer, &text);
-    let duration_ms = perf.now() - start;
+    let duration_ms = perf_now() - start;
 
     let token_count = result["token_count"].as_u64().unwrap_or(0);
     let cpt = result["chars_per_token"].as_f64().unwrap_or(0.0);
@@ -157,11 +189,10 @@ async fn run_pair_comparison(en_text: String, fi_text: String, ws: Rc<RefCell<We
         return;
     };
 
-    let perf = web_sys::window().unwrap().performance().unwrap();
-    let start_time = perf.now();
+    let start_time = perf_now();
     let en_result = tokenize_text(&tokenizer, &en_text);
     let fi_result = tokenize_text(&tokenizer, &fi_text);
-    let duration_ms = perf.now() - start_time; // millisekunteja desimaalitarkkuudella
+    let duration_ms = perf_now() - start_time;
 
     let en_cpt = en_result["chars_per_token"].as_f64().unwrap_or(0.0);
     let fi_cpt = fi_result["chars_per_token"].as_f64().unwrap_or(0.0);

network-poc/node/src/qwen.rs

@@ -24,10 +24,7 @@ async fn ensure_cached(key: &str, url: &str, ws: &Rc<RefCell<WebSocket>>) -> Res
 
     console_log!("[Qwen] Ladataan {}...", key);
 
-    let window = web_sys::window().unwrap();
-    let resp_val = wasm_bindgen_futures::JsFuture::from(window.fetch_with_str(url))
-        .await.map_err(|e| format!("Fetch epäonnistui: {:?}", e))?;
-    let resp: web_sys::Response = resp_val.dyn_into().map_err(|_| "Ei Response".to_string())?;
+    let resp = crate::worker_fetch(url).await?;
     if !resp.ok() { return Err(format!("HTTP {}", resp.status())); }
 
     let total_size: usize = resp.headers()
@@ -71,7 +68,7 @@ async fn ensure_cached(key: &str, url: &str, ws: &Rc<RefCell<WebSocket>>) -> Res
 }
 
 pub async fn run_qwen_inference(prompt: String, ws: Rc<RefCell<WebSocket>>) {
-    let perf = web_sys::window().unwrap().performance().unwrap();
+    // performance via crate::perf_now()
 
     let tok_bytes = match ensure_cached("qwen05b-tokenizer.json", TOKENIZER_URL, &ws).await {
         Ok(b) => b,
@@ -88,7 +85,7 @@ pub async fn run_qwen_inference(prompt: String, ws: Rc<RefCell<WebSocket>>) {
     };
 
     console_log!("[Qwen] Rakennetaan mallia...");
-    let start_load = perf.now();
+    let start_load = crate::perf_now();
     let device = Device::Cpu;
     let dtype = DType::F32;
 
@@ -120,7 +117,7 @@ pub async fn run_qwen_inference(prompt: String, ws: Rc<RefCell<WebSocket>>) {
         Err(e) => { console_log!("[Qwen] Mallin lataus: {}", e); return; }
     };
 
-    let load_time = perf.now() - start_load;
+    let load_time = crate::perf_now() - start_load;
     console_log!("[Qwen] Malli ladattu ({:.0}ms). Generoidaan...", load_time);
 
     let encoding = match tokenizer.encode(prompt.as_str(), true) {
@@ -131,7 +128,7 @@ pub async fn run_qwen_inference(prompt: String, ws: Rc<RefCell<WebSocket>>) {
     let input_len = input_ids.len();
     console_log!("[Qwen] Syöte: {} tokenia", input_len);
 
-    let start_gen = perf.now();
+    let start_gen = crate::perf_now();
     let max_new_tokens = 32;
     let mut generated_text = String::new();
     let mut tokens_generated: usize = 0;
@@ -202,7 +199,7 @@ pub async fn run_qwen_inference(prompt: String, ws: Rc<RefCell<WebSocket>>) {
         crate::sleep_ms(0).await;
     }
 
-    let gen_time = perf.now() - start_gen;
+    let gen_time = crate::perf_now() - start_gen;
     let tokens_per_sec = if gen_time > 0.0 { (tokens_generated as f64 / gen_time) * 1000.0 } else { 0.0 };
     console_log!("[Qwen] {} tokenia | {:.0}ms | {:.1} tok/s", tokens_generated, gen_time, tokens_per_sec);
 

network-poc/node/src/qwen_coder.rs

@@ -140,10 +140,7 @@ async fn ensure_cached(key: &str, url: &str, ws: &Rc<RefCell<WebSocket>>) -> Res
 
     console_log!("[Coder] Ladataan {}...", key);
 
-    let window = web_sys::window().unwrap();
-    let resp_val = wasm_bindgen_futures::JsFuture::from(window.fetch_with_str(url))
-        .await.map_err(|e| format!("Fetch: {:?}", e))?;
-    let resp: web_sys::Response = resp_val.dyn_into().map_err(|_| "Ei Response".to_string())?;
+    let resp = crate::worker_fetch(url).await?;
     if !resp.ok() { return Err(format!("HTTP {}", resp.status())); }
 
     let total_size: usize = resp.headers()
@@ -251,17 +248,16 @@ async fn get_or_build_model(use_3b: bool, ws: &Rc<RefCell<WebSocket>>) -> Result
 
 /// use_3b: false = 0.5B (nopea), true = 3B (laadukas)
 pub async fn run_coder_inference(prompt: String, ws: Rc<RefCell<WebSocket>>, use_3b: bool, task_id: Option<String>) {
-    let perf = web_sys::window().unwrap().performance().unwrap();
     let size_label = if use_3b { "3B" } else { "0.5B" };
 
-    let start_load = perf.now();
+    let start_load = crate::perf_now();
 
     if let Err(e) = get_or_build_model(use_3b, &ws).await {
         console_log!("[Coder] Mallin lataus: {}", e);
         return;
     }
 
-    let load_time = perf.now() - start_load;
+    let load_time = crate::perf_now() - start_load;
     if load_time > 100.0 {
         console_log!("[Coder] Malli ladattu ({:.0}ms). Generoidaan...", load_time);
     }
@@ -297,7 +293,7 @@ pub async fn run_coder_inference(prompt: String, ws: Rc<RefCell<WebSocket>>, use
         console_log!("[Coder] Syöte: {} tokenia", input_len);
 
         let device = Device::Cpu;
-        let start_gen = perf.now();
+        let start_gen = crate::perf_now();
         let eos_token = 151645u32;
         let temperature: f32 = 0.7;
         let top_k: usize = 40;
@@ -373,7 +369,7 @@ pub async fn run_coder_inference(prompt: String, ws: Rc<RefCell<WebSocket>>, use
             tokens_generated += 1;
         }
 
-        let gen_time = perf.now() - start_gen;
+        let gen_time = crate::perf_now() - start_gen;
 
         // Siivotaan vastaus: poista markdown-koodiblokit ja johdantotekstit
         let cleaned = strip_markdown_wrapper(&generated_text);

network-poc/node/src/smollm.rs

@@ -28,10 +28,7 @@ async fn ensure_cached(key: &str, url: &str, ws: &Rc<RefCell<WebSocket>>) -> Res
     send_progress(ws, key, 0, 0, 0);
 
     // Fetch API:lla saadaan Content-Length ja streaming-luku
-    let window = web_sys::window().unwrap();
-    let resp_val = wasm_bindgen_futures::JsFuture::from(window.fetch_with_str(url))
-        .await.map_err(|e| format!("Fetch epäonnistui: {:?}", e))?;
-    let resp: web_sys::Response = resp_val.dyn_into().map_err(|_| "Ei Response-objekti".to_string())?;
+    let resp = crate::worker_fetch(url).await?;
 
     if !resp.ok() {
         return Err(format!("HTTP {}", resp.status()));
@@ -99,7 +96,7 @@ fn send_progress(ws: &Rc<RefCell<WebSocket>>, file: &str, pct: u32, loaded: usiz
 
 /// Lataa malli ja tokenizer, suorita inferenssi ja streamaa tokenit hubille
 pub async fn run_smollm_inference(prompt: String, ws: Rc<RefCell<WebSocket>>) {
-    let perf = web_sys::window().unwrap().performance().unwrap();
+    // performance via crate::perf_now()
 
     // 1. Lataa tokenizer
     let tok_bytes = match ensure_cached("smollm-tokenizer.json", TOKENIZER_URL, &ws).await {
@@ -122,7 +119,7 @@ pub async fn run_smollm_inference(prompt: String, ws: Rc<RefCell<WebSocket>>) {
     // Burn 0.21-pre.2 cubecl-runtime ei käänny Wasmille (println! puuttuu)
     // → NdArray kunnes Burn 0.21 stable + Wasm-tuki
     console_log!("[SmolLM] Burn NdArray (CPU) inferenssi...");
-    run_burn_inference::<burn::backend::NdArray>(prompt, model_bytes, tokenizer, ws, perf.clone()).await;
+    run_burn_inference::<burn::backend::NdArray>(prompt, model_bytes, tokenizer, ws).await;
 }
 
 async fn run_burn_inference<B: burn::tensor::backend::Backend>(
@@ -130,9 +127,8 @@ async fn run_burn_inference<B: burn::tensor::backend::Backend>(
     model_bytes: Vec<u8>,
     tokenizer: tokenizers::Tokenizer,
     ws: Rc<RefCell<WebSocket>>,
-    perf: web_sys::Performance, // Korjattu Wasm-performanssi välitettäväksi
 ) {
-    let start_load = perf.now();
+    let start_load = crate::perf_now();
 
     let device = Default::default();
     let config = crate::burn_smollm::config::SmolLMConfig::default();
@@ -143,7 +139,7 @@ async fn run_burn_inference<B: burn::tensor::backend::Backend>(
         Err(e) => { console_log!("[SmolLM] Lataus epäonnistui: {}", e); return; }
     };
 
-    let load_time = perf.now() - start_load;
+    let load_time = crate::perf_now() - start_load;
     console_log!("[SmolLM] Burn-malli ladattu ({:.0}ms). Generoidaan...", load_time);
 
     let formatted_prompt = format!("<|im_start|>user\n{}<|im_end|>\n<|im_start|>assistant\n", prompt);
@@ -156,7 +152,7 @@ async fn run_burn_inference<B: burn::tensor::backend::Backend>(
     let input_len = input_ids.len();
     console_log!("[SmolLM] Syöte: {} tokenia", input_len);
 
-    let start_gen = perf.now();
+    let start_gen = crate::perf_now();
     let max_new_tokens = 32;
     let mut generated_text = String::new();
     let mut tokens_generated: usize = 0;
@@ -219,7 +215,7 @@ async fn run_burn_inference<B: burn::tensor::backend::Backend>(
         tokens_generated += 1;
     }
 
-    let gen_time = perf.now() - start_gen;
+    let gen_time = crate::perf_now() - start_gen;
     let tokens_per_sec = if gen_time > 0.0 { (tokens_generated as f64 / gen_time) * 1000.0 } else { 0.0 };
 
     let done = serde_json::json!({

network-poc/static/index.html

@@ -1773,9 +1773,11 @@
             const statusDiv = document.createElement('div');
             statusDiv.className = 'terminal-line';
             statusDiv.id = 'status-' + taskId;
-            statusDiv.innerHTML = `  <span style="color:#8b949e">→ <span style="color:#58a6ff">${model}</span> käsittelee...</span>`;
+            statusDiv.innerHTML = `  <span style="color:#8b949e">→ <span style="color:#58a6ff">${model}</span> käsittelee... <span style="color:#d29922">(selain voi hidastua)</span></span>`;
             termPanel.appendChild(statusDiv);
             termPanel.scrollTop = termPanel.scrollHeight;
+            // Yield jotta status-rivi ehditään piirtää ennen mahdollista blokkia
+            await new Promise(r => setTimeout(r, 50));
 
             try {
                 const agent = Object.values(agentPrompts).find(a => a.model === model);
@@ -3231,7 +3233,9 @@ Write the corrected code.`;
         const _prevConsoleLog = console.log;
         console.log = function(...args) { _prevConsoleLog.apply(console, args); codeLogListener(...args); };
 
-        // Käynnistä Coder-node automaattisesti ensimmäisellä kerralla
+        // Web Worker -pohjainen laskentasolmu — UI ei jäädy inferenssin aikana
+        let coderWorker = null;
+
         async function ensureCoderNode() {
             if (coderJoined) return;
             coderJoined = true;
@@ -3241,10 +3245,21 @@ Write the corrected code.`;
             setStep('step-wasm', 'active');
 
             try {
-                if (!wasmInitialized) {
-                    await init();
-                    wasmInitialized = true;
-                }
+                // Käynnistetään WASM Web Workerissa
+                coderWorker = new Worker('./worker.js', { type: 'module' });
+
+                // Workerin console.log-viestit → pääsäikeen kuuntelija
+                // Worker ei voi kutsua console.log näkyvästi, joten WASM:n console_log
+                // ei näy automaattisesti. Workerissa console.log menee Workerin konsoliin.
+
+                await new Promise((resolve, reject) => {
+                    coderWorker.onmessage = (e) => {
+                        if (e.data.type === 'ready') resolve();
+                        else if (e.data.type === 'error') reject(new Error(e.data.message));
+                    };
+                    coderWorker.postMessage({ type: 'init' });
+                });
+
                 setStep('step-wasm', 'done');
                 setStep('step-tokenizer', 'active');
 
@@ -3258,30 +3273,23 @@ Write the corrected code.`;
                     selected_task: coderSize === '3b' ? 'qwen-coder-3b' : 'qwen-coder-05b'
                 };
                 const taskId = coderSize === '3b' ? 5 : 4;
-                // Tunnistetaan WebGPU myös koodilaboratorion puolella
-                let coderHasWebGPU = false;
-                if (navigator.gpu) {
-                    try {
-                        const adapter = await navigator.gpu.requestAdapter();
-                        if (adapter) {
-                            try {
-                                const testDevice = await adapter.requestDevice({ requiredLimits: { maxInterStageShaderComponents: 60 } });
-                                coderHasWebGPU = true;
-                                testDevice.destroy();
-                            } catch(e) {
-                                coderHasWebGPU = false;
-                            }
-                        }
-                    } catch(e) {}
-                }
-                await start_agent_node(wsUrl, coderHasWebGPU, JSON.stringify(deviceInfo), taskId);
+
+                // Käynnistetään node Workerissa
+                coderWorker.onmessage = (e) => {
+                    if (e.data.type === 'started') {
                         document.getElementById('coder-status').textContent = 'Connected';
                         document.getElementById('coder-status').style.color = '#d29922';
                         coderWsReady = true;
+                    } else if (e.data.type === 'error') {
+                        console.log('[Worker] Virhe: ' + e.data.message);
+                    }
+                };
+                coderWorker.postMessage({
+                    type: 'start',
+                    data: { hubUrl: wsUrl, hasWebGPU: false, deviceInfo: JSON.stringify(deviceInfo), taskId }
+                });
 
-                // Proaktiivinen mallin esilataus: lähetetään tyhjä warmup-prompt
-                // joka triggeröi get_or_build_model:n ilman varsinaista generointia.
-                // Pipeline-tilakone seuraa logeja ja merkkaa vaiheet valmiiksi.
+                // Warmup
                 setTimeout(() => {
                     if (uiSocket && uiSocket.readyState === 1) {
                         uiSocket.send(JSON.stringify({
@@ -3295,7 +3303,7 @@ Write the corrected code.`;
                 if (pendingCodePrompt) {
                     setTimeout(() => {
                         sendCodeToHub(pendingCodePrompt);
-                    }, 2000); // Hieman pidempi odotus jotta warmup ehtii ensin
+                    }, 2000);
                     pendingCodePrompt = null;
                 }
             } catch(e) {
@@ -3306,11 +3314,7 @@ Write the corrected code.`;
             }
         }
 
-        // Automaattinen uudelleenkäynnistys: jos malli oli ladattu ennen refreshiä, ladataan se uudelleen cachesta
-        if (localStorage.getItem('kpn-coder-loaded') === 'true') {
-            // Pieni viive jotta UI ehtii piirtyä
-            setTimeout(() => ensureCoderNode(), 500);
-        }
+        // Mallia EI ladata automaattisesti — käyttäjä käynnistää itse: kpn load
 
         // Laskentasolmun käynnistys/pysäytys -nappi
         let computeAbortController = null;

network-poc/static/worker.js

@@ -0,0 +1,31 @@
+// Kipinä WASM Worker (ES module) — ajaa kielimallin inferenssin erillisessä säikeessä
+import init, { start_agent_node, set_gpu_load, set_auto_tasks } from './pkg/node.js';
+
+let wasmReady = false;
+
+self.onmessage = async (e) => {
+    const { type, data } = e.data;
+
+    if (type === 'init') {
+        try {
+            await init();
+            wasmReady = true;
+            self.postMessage({ type: 'ready' });
+        } catch (err) {
+            self.postMessage({ type: 'error', message: 'WASM init: ' + err.message });
+        }
+    } else if (type === 'start') {
+        if (!wasmReady) return;
+        const { hubUrl, hasWebGPU, deviceInfo, taskId } = data;
+        try {
+            await start_agent_node(hubUrl, hasWebGPU, deviceInfo, taskId);
+            self.postMessage({ type: 'started' });
+        } catch (err) {
+            self.postMessage({ type: 'error', message: 'Node: ' + err.message });
+        }
+    } else if (type === 'set_gpu_load') {
+        if (wasmReady) set_gpu_load(data.load);
+    } else if (type === 'set_auto_tasks') {
+        if (wasmReady) set_auto_tasks(data.enabled);
+    }
+};