147d077aa7 feat(inference): unify and optimize WebGPU inference pipeline (#1622)
## Problem

The WebGPU inference pipeline had several structural issues:

1. **No unified protocol** — Kokoro TTS, Whisper ASR, and Background
Removal workers each used their own ad-hoc message formats. Adding a new
model meant reinventing worker communication from scratch.
2. **Infrastructure existed but was disconnected** —
`GPUResourceCoordinator`, `LoadQueue`, `InferenceWorkerManager`, and
`protocol.ts` were all implemented but had zero consumers. The adapters
duplicated the same lifecycle/timeout/mutex patterns independently.
3. **Performance gaps** — Kokoro only offered fp32 on WebGPU (no fp16),
Whisper warm-up compiled shaders for 187.5s of dummy audio, audio
transfer went through unnecessary WAV blob encode/decode, and
`listVoices` reloaded the model every time.
4. **Silent failures** — Whisper worker's `generate()` had no try-catch;
errors were swallowed and the main thread waited until timeout.
5. **No graceful degradation** — Whisper and Background Removal workers
hardcoded `device: 'webgpu'` with no WASM fallback.
6. **No observability** — Only Kokoro had performance tracing. No
adapter reported status to `useInferenceStatus`. No cache management UI
existed.
7. **Dead code accumulation** — Old `KokoroWorkerManager` (232 lines),
legacy Whisper message types, and scattered duplicate constants.

## Changes

### Phase 0 — Critical Performance & Bugs
- Add `fp16-webgpu` dtype for Kokoro TTS (~2x inference speed on
supported GPUs)
- Fix Whisper warm-up tensor from `[1, 128, 3000]` → `[1, 128, 1]`
(minimal shader compilation)
- Fix Whisper worker silent error bug (add try-catch to `generate()` and
`load()`)

### Phase 1 — Data Transfer & Caching
- Switch Kokoro audio to Float32Array transferable (skip WAV blob encode
in worker, lightweight WAV encode on main thread)
- Cache `listVoices` results (skip redundant model reload when adapter
state is `ready`)
- Normalize progress reporting to 0-100 across all adapters,
differentiate `warmup` phase

### Phase 2 — Protocol Unification & Infrastructure
- Migrate all 3 workers + 3 adapters to unified `protocol.ts` message
types (`load-model`, `run-inference`, `model-ready`, `inference-result`,
`progress`, `error`)
- Wire `GPUResourceCoordinator` into all adapters (VRAM allocation
tracking, LRU ordering, memory pressure events)
- Wire `LoadQueue` into all adapters (priority-based sequential model
loading: TTS=10 > ASR=5 > BG_REMOVAL=1)
- Add `coordinator.ts` global singleton for GPU coordinator + load queue
- Add WebGPU detection + WASM fallback in Whisper and Background Removal
workers

### Phase 3 — Error Recovery & Observability
- Add restart logic with exponential backoff to Whisper adapter
(matching Kokoro's existing pattern)
- Integrate `classifyError()` (OOM / DEVICE_LOST / TIMEOUT
classification) in Whisper adapter
- Extend `defaultPerfTracer` to Whisper `transcribe()` and Background
Removal `processImage()`
- Wire `useInferenceStatus` into all 3 adapters (downloading → ready →
terminated lifecycle)

### Phase 4 — Tests
- Add unit tests for `AsyncMutex` (4 tests), `LoadQueue` (4 tests),
`GPUResourceCoordinator` (7 tests) — all 15 passing

### Phase 5 — Cleanup & Features
- Delete old `KokoroWorkerManager` (232 lines, zero consumers)
- Delete orphaned `libs/workers/types.ts` (old Whisper message types)
- Clean up `workers/kokoro/types.ts` (remove legacy message types, keep
domain types)
- Create centralized `constants.ts` (MODEL_IDS, MODEL_NAMES, TIMEOUTS,
MAX_RESTARTS)
- Remove hardcoded WebGPU check from background-removal devtools pages
(worker auto-detects)
- Add `useModelPreload` composable for generic idle-time preloading
- Add `useInferencePreload` composable that reads provider config and
preloads configured local models
- Wire preloading into both `stage-web` and `stage-tamagotchi` App.vue
(Kokoro TTS preloads 3s after init)
- Add `ModelCacheManager.vue` settings component (cache size display,
per-model status, clear cache)
- Document GPU Device isolation architecture in protocol.ts

## After This PR

- All inference workers speak the same protocol → adding a new model
adapter is straightforward
- GPU memory is tracked across all models with automatic pressure
warnings at 80%/95% of VRAM budget
- Models load sequentially via priority queue → no bandwidth/VRAM
contention
- Workers auto-detect WebGPU and fall back to WASM → works on browsers
without WebGPU
- Kokoro TTS preloads during idle time → "instant" first use for
configured users
- All adapters auto-restart on worker crashes (max 3 attempts,
exponential backoff)
- 15 unit tests cover core infrastructure (mutex, queue, coordinator)
- Zero dead code remains in the inference pipeline

## Test Plan

- [x] `pnpm exec vitest run packages/stage-ui/src/libs/inference/` — 15
tests pass
- [x] `pnpm -F @proj-airi/stage-ui exec tsc --noEmit` — no TypeScript
errors
- [x] `pnpm lint:fix` — no lint errors in changed files
- [ ] Manual: verify Kokoro TTS works with fp16-webgpu on a supported
browser
- [ ] Manual: verify Whisper ASR loads and transcribes correctly
- [ ] Manual: verify Background Removal works in devtools page
- [ ] Manual: verify preloading triggers in console (`[Preload] Loading
kokoro-...`)

---------

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>
2026-04-13 23:19:27 +08:00
2025-08-21 22:14:16 +08:00
2026-04-11 04:00:49 +08:00
2026-04-12 20:19:25 +00:00
2026-04-11 04:00:49 +08:00
2026-04-11 04:00:49 +08:00
2025-11-30 20:27:08 +08:00
2024-12-03 16:25:03 +08:00
2026-04-11 04:00:49 +08:00
2026-04-02 04:24:04 +08:00

Project AIRI

Re-creating Neuro-sama, a soul container of AI waifu / virtual characters to bring them into our world.

[Join Discord Server] [Try it] [简体中文] [日本語] [Русский] [Tiếng Việt] [Français] [한국어]

AIRI - A container of cyber living souls, re-creation of Neuro-sama | Product Hunt moeru-ai%2Fairi | Trendshift

Heavily inspired by Neuro-sama

Tip

On Windows, you can also install AIRI with Scoop:

scoop bucket add airi https://github.com/moeru-ai/airi
scoop install airi/airi

Warning

Attention: We do not have any officially minted cryptocurrency or token associated with this project. Please check the information and proceed with caution.

Note

We've got a whole dedicated organization @proj-airi for all the sub-projects born from Project AIRI. Check it out!

RAG, memory system, embedded database, icons, Live2D utilities, and more!

Tip

We have a translation project on Crowdin. If you find any inaccurate translations, feel free to contribute improvements there. Crowdin | Agile localization for tech companies

Have you dreamed about having a cyber living being (cyber waifu, digital pet) or digital companion that could play with and talk to you?

With the power of modern large language models like ChatGPT and famous Claude, asking a virtual being to roleplay and chat with us is already easy enough for everyone. Platforms like Character.ai (a.k.a. c.ai) and JanitorAI as well as local playgrounds like SillyTavern are already good-enough solutions for a chat based or visual adventure game like experience.

But, what about the abilities to play games? And see what you are coding at? Chatting while playing games, watching videos, and is capable of doing many other things.

Perhaps you know Neuro-sama already. She is currently the best virtual streamer capable of playing games, chatting, and interacting with you and the participants. Some also call this kind of being "digital human." Sadly, as it's not open sourced, you cannot interact with her after her live streams go offline.

Therefore, this project, AIRI, offers another possibility here: let you own your digital life, cyber living, easily, anywhere, anytime.

DevLogs We Posted & Recent Updates

What's So Special About This Project?

Unlike the other AI driven VTuber open source projects, アイリ was built with support of many Web technologies such as WebGPU, WebAudio, Web Workers, WebAssembly, WebSocket, etc. from the first day.

Tip

Worrying about the performance drop since we are using Web related technologies?

Don't worry, while Web browser version is meant to give an insight about how much we can push and do inside browsers, and webviews, we will never fully rely on this, the desktop version of AIRI is capable of using native NVIDIA CUDA and Apple Metal by default (thanks to HuggingFace & beloved candle project), without any complex dependency managements, considering the tradeoff, it was partially powered by Web technologies for graphics, layouts, animations, and the WIP plugin systems for everyone to integrate things.

This means that アイリ is capable of running on modern browsers and devices and even on mobile devices (already done with PWA support). This brings a lot of possibilities for us (the developers) to build and extend the power of アイリ VTuber to the next level, while still leaving the flexibilities for users to enable features that requires TCP connections or other non-Web technologies such as connecting to a Discord voice channel or playing Minecraft and Factorio with friends.

Note

We are still in the early stage of development where we are seeking out talented developers to join us and help us to make アイリ a reality.

It's ok if you are not familiar with Vue.js, TypeScript, and devtools required for this project, you can join us as an artist, designer, or even help us to launch our first live stream.

Even if you are a big fan of React, Svelte or even Solid, we welcome you. You can open a sub-directory to add features that you want to see in アイリ, or would like to experiment with.

Fields (and related projects) that we are looking for:

  • Live2D modeller
  • VRM modeller
  • VRChat avatar designer
  • Computer Vision
  • Reinforcement Learning
  • Speech Recognition
  • Speech Synthesis
  • ONNX Runtime
  • Transformers.js
  • vLLM
  • WebGPU
  • Three.js
  • WebXR (checkout the another project we have under the @moeru-ai organization)

If you are interested, why not introduce yourself here? Would like to join part of us to build AIRI?

Current Progress

Capable of

  • Brain
  • Ears
    • Audio input from browser
    • Audio input from Discord
    • Client side speech recognition
    • Client side talking detection
  • Mouth
  • Body
    • VRM support
      • Control VRM model
    • VRM model animations
      • Auto blink
      • Auto look at
      • Idle eye movement
    • Live2D support
      • Control Live2D model
    • Live2D model animations
      • Auto blink
      • Auto look at
      • Idle eye movement

Development

For detailed instructions to develop this project, follow CONTRIBUTING.md

Note

By default, pnpm dev will start the development server for the Stage Web (browser version). If you would like to try developing the desktop version, please make sure you read CONTRIBUTING.md to setup the environment correctly.

pnpm i
pnpm dev

Stage Web (Browser Version at airi.moeru.ai)

pnpm dev

Stage Tamagotchi (Desktop Version)

pnpm dev:tamagotchi

A Nix package for Tamagotchi is included. To run airi with Nix, first make sure to enable flakes, then run:

nix run github:moeru-ai/airi

NixOS

Electron requires shared libraries that aren't in standard paths on NixOS. Use the FHS shell defined in flake.nix:

nix develop .#fhs
pnpm dev:tamagotchi

Stage Pocket (Mobile Version)

Start the development server for the capacitor:

pnpm dev:pocket:ios --target <DEVICE_ID_OR_SIMULATOR_NAME>
# Or
CAPACITOR_DEVICE_ID_IOS=<DEVICE_ID_OR_SIMULATOR_NAME> pnpm dev:pocket:ios

You can see the list of available devices and simulators by running pnpm exec cap run ios --list.

If you need to connect server channel on pocket in wireless mode, you need to start tamagotchi as root:

sudo pnpm dev:tamagotchi

Then enable secure websocket in tamagotchi settings/connections.

Documentation Site

pnpm dev:docs

Publish

Run bumpp to update the monorepo version:

npx bumpp --no-commit --no-tag

Support of LLM API Providers (powered by xsai)

Sub-projects Born from This Project

%%{ init: { 'flowchart': { 'curve': 'catmullRom' } } }%%

flowchart TD
  Core("Core")
  Unspeech("unspeech")
  DBDriver("@proj-airi/drizzle-duckdb-wasm")
  MemoryDriver("[WIP] Memory Alaya")
  DB1("@proj-airi/duckdb-wasm")
  SVRT("@proj-airi/server-runtime")
  Memory("Memory")
  STT("STT")
  Stage("Stage")
  StageUI("@proj-airi/stage-ui")
  UI("@proj-airi/ui")

  subgraph AIRI
    DB1 --> DBDriver --> MemoryDriver --> Memory --> Core
    UI --> StageUI --> Stage --> Core
    Core --> STT
    Core --> SVRT
  end

  subgraph UI_Components
    UI --> StageUI
    UITransitions("@proj-airi/ui-transitions") --> StageUI
    UILoadingScreens("@proj-airi/ui-loading-screens") --> StageUI
    FontCJK("@proj-airi/font-cjkfonts-allseto") --> StageUI
    FontXiaolai("@proj-airi/font-xiaolai") --> StageUI
  end

  subgraph Apps
    Stage --> StageWeb("@proj-airi/stage-web")
    Stage --> StageTamagotchi("@proj-airi/stage-tamagotchi")
    Core --> RealtimeAudio("@proj-airi/realtime-audio")
    Core --> PromptEngineering("@proj-airi/playground-prompt-engineering")
  end

  subgraph Server_Components
    Core --> ServerSDK("@proj-airi/server-sdk")
    ServerShared("@proj-airi/server-shared") --> SVRT
    ServerShared --> ServerSDK
  end

  STT -->|Speaking| Unspeech
  SVRT -->|Playing Factorio| F_AGENT
  SVRT -->|Playing Minecraft| MC_AGENT

  subgraph Factorio_Agent
    F_AGENT("Factorio Agent")
    F_API("Factorio RCON API")
    factorio-server("factorio-server")
    F_MOD1("autorio")

    F_AGENT --> F_API -.-> factorio-server
    F_MOD1 -.-> factorio-server
  end

  subgraph Minecraft_Agent
    MC_AGENT("Minecraft Agent")
    Mineflayer("Mineflayer")
    minecraft-server("minecraft-server")

    MC_AGENT --> Mineflayer -.-> minecraft-server
  end

  XSAI("xsAI") --> Core
  XSAI --> F_AGENT
  XSAI --> MC_AGENT

  Memory_PGVector("@proj-airi/memory-pgvector") --> Memory

  style Core fill:#f9d4d4,stroke:#333,stroke-width:1px
  style AIRI fill:#fcf7f7,stroke:#333,stroke-width:1px
  style UI fill:#d4f9d4,stroke:#333,stroke-width:1px
  style Stage fill:#d4f9d4,stroke:#333,stroke-width:1px
  style UI_Components fill:#d4f9d4,stroke:#333,stroke-width:1px
  style Server_Components fill:#d4e6f9,stroke:#333,stroke-width:1px
  style Apps fill:#d4d4f9,stroke:#333,stroke-width:1px
  style Factorio_Agent fill:#f9d4f2,stroke:#333,stroke-width:1px
  style Minecraft_Agent fill:#f9d4f2,stroke:#333,stroke-width:1px

  style DBDriver fill:#f9f9d4,stroke:#333,stroke-width:1px
  style MemoryDriver fill:#f9f9d4,stroke:#333,stroke-width:1px
  style DB1 fill:#f9f9d4,stroke:#333,stroke-width:1px
  style Memory fill:#f9f9d4,stroke:#333,stroke-width:1px
  style Memory_PGVector fill:#f9f9d4,stroke:#333,stroke-width:1px

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Project Status

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Acknowledgements

Supporters

Thank you for supporting Project AIRI through OpenCollective, Patreon, and Ko-fi.

Project AIRI supporters

Special Thanks

Special thanks to all contributors for their contributions to Project AIRI ❤️

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Re-creating Neuro-sama, a soul container of AI waifu / virtual characters to bring them into our world.
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