feat(denoise): add self-hosted DeepFilterNet 3 ML noise-suppression model

Integrate DeepFilterNet 3 (deepfilternet3-noise-filter@1.2.1) as a new
client-side denoise model id 'deepfilternet', mirroring the DTLN pattern.

The npm package ships only an ESM whose AudioWorklet processor + wasm-bindgen
glue are inlined as a string (loaded via a Blob URL — no CDN for the worklet).
Its only runtime fetches are a single-threaded df_bg.wasm and an ONNX model
tarball, which previously loaded from an external CDN. We now VENDOR both
(build/denoise-vendor/deepfilternet/v2/...) and self-host them under
denoise/deepfilternet/, overriding the package's cdnUrl so nothing hits the
upstream CDN — keeping it self-hosted / Tauri-CSP safe.

The wasm is single-threaded (no SharedArrayBuffer / atomics / imported shared
memory), so it needs no COOP/COEP cross-origin isolation and runs fine in EC's
non-isolated iframe. Runs at 48 kHz fullband. Any init/runtime failure falls
back to the raw mic, like the other models.

- vite.config.js: copy ESM + vendored wasm/model into the EC denoise dir with a
  required-asset guard that aborts the build if any entry is missing.
- build/lotus-denoise.js: 'deepfilternet' branch — dynamic-import the ESM, build
  a DeepFilterNet3Core pointed at the self-hosted base, await init, return the
  worklet node; 48 kHz; raw-mic fail-safe preserved.
- denoisePipeline.ts: 'deepfilternet' branch for the in-app tester + sampleRate.
- settings.ts: add 'deepfilternet' to DenoiseModelId + getSettings whitelist.
- lotusDenoiseUtils.ts: add the comparison-chart row.
- General.tsx: add the "DeepFilterNet 3 (beta)" dropdown option.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

src/app/utils/denoisePipeline.ts

@@ -14,10 +14,10 @@ import { DenoiseModelId } from '../state/settings';
 const BASE = `${import.meta.env.BASE_URL.replace(/\/+$/, '')}/public/element-call/denoise/`;
 
 /**
- * Required AudioContext sample rate per model. RNNoise/Speex (sapphi) assume
- * 48 kHz. DTLN (@workadventure) targets 16 kHz and does NOT resample internally
- * — running it at 48 kHz produces robotic/choppy/quiet output, so its whole
- * graph must run in a 16 kHz context.
+ * Required AudioContext sample rate per model. RNNoise/Speex (sapphi) and
+ * DeepFilterNet 3 are 48 kHz. DTLN (@workadventure) targets 16 kHz and does NOT
+ * resample internally — running it at 48 kHz produces robotic/choppy/quiet
+ * output, so its whole graph must run in a 16 kHz context.
  */
 export const sampleRateFor = (model: DenoiseModelId): number => (model === 'dtln' ? 16000 : 48000);
 
@@ -75,6 +75,32 @@ export async function buildModelNode(
     const handle = await mod.createNoiseSuppressionAudioWorklet(ctx, { bypassUntilReady: true });
     return { node: handle.node, dispose: () => handle.dispose() };
   }
+  if (model === 'deepfilternet') {
+    // deepfilternet3-noise-filter ESM: inlines its worklet/wasm-bindgen glue and
+    // fetches only df_bg.wasm + the ONNX model, which we self-host under
+    // deepfilternet/v2/... Override its cdnUrl to our absolute base so nothing
+    // hits the upstream CDN. DeepFilterNet3Core builds the worklet node directly.
+    const dfnBase = new URL(`${BASE}deepfilternet`, window.location.href).href;
+    // eslint-disable-next-line @typescript-eslint/no-explicit-any
+    const mod: any = await import(/* @vite-ignore */ `${BASE}deepfilternet/index.esm.js`);
+    const core = new mod.DeepFilterNet3Core({
+      sampleRate: sampleRateFor(model),
+      noiseReductionLevel: 80,
+      assetConfig: { cdnUrl: dfnBase },
+    });
+    await core.initialize();
+    const node: AudioWorkletNode = await core.createAudioWorkletNode(ctx);
+    return {
+      node,
+      dispose: () => {
+        try {
+          core.destroy();
+        } catch {
+          /* noop */
+        }
+      },
+    };
+  }
   const cfg = SAPPHI[model];
   const [, wasmBinary] = await Promise.all([addModuleOnce(ctx, cfg.script), fetchWasm(cfg.wasm)]);
   const node = new AudioWorkletNode(ctx, cfg.proc, {