- Added a new PostHog client for capturing server-side business events such as Stripe webhooks and subscription state changes.
- Implemented various tracking functions for pricing funnel steps, character creation, and chat session starts.
- Enhanced the flux meter tests to handle partial charges and report unbilled flux correctly.
- Updated the CharacterDialog and Flux settings pages to track user interactions with analytics events.
- Introduced a mechanism to identify users on PostHog based on authentication state to ensure accurate funnel tracking.
- Added necessary dependencies for PostHog integration in the project.
## Summary
Adds the experimental Godot stage sidecar path for `stage-tamagotchi`.
This PR wires the existing Tamagotchi model selection flow into an
external Godot runtime window. The renderer gates Godot scene input to
VRM models, Electron main materialises the selected model bytes to a
local file, and the Godot sidecar receives the native path over a local
WebSocket bridge before importing and displaying the avatar at runtime.
## What Changed
- Added a typed Godot scene input contract with `format: "vrm"`.
- Added renderer-side VRM-only gating before sending selected model data
to Electron main.
- Added Electron main sidecar management for:
- launching Godot
- starting the local WebSocket bridge
- materialising selected VRM bytes under app `userData`
- forwarding scene apply messages to Godot
- optional remote debugging support
- Added Godot runtime scripts for:
- sidecar startup and WebSocket orchestration
- message envelope parsing
- avatar import and atomic replacement
- runtime VRM import through Godot `GLTFDocument`
- Added engine-local docs for runtime import, live debugging, vendor
patches, and current VRM support boundaries.
- Removed temporary tests after using them to verify the glue behaviour
locally, to keep the review surface smaller.
## Vendor Code Note
A large part of this PR is vendored Godot add-on code, not AIRI business
logic.
The bulk of the added files under:
- `engines/stage-tamagotchi-godot/addons/vrm/**`
- `engines/stage-tamagotchi-godot/addons/Godot-MToon-Shader/**`
comes from V-Sekai Godot VRM / MToon add-ons. These files are required
because Godot plugins are project-local source/assets rather than
package-manager dependencies.
The intended review scope for vendor code is limited to:
- source baseline metadata
- license/plugin config
- Godot-generated metadata notes
- the documented local patch in `addons/vrm/vrm_extension.gd`
The application/runtime code to review is mainly under:
- `apps/stage-tamagotchi/src/shared/eventa/index.ts`
- `apps/stage-tamagotchi/src/renderer/pages/settings/models/`
- `apps/stage-tamagotchi/src/main/services/airi/godot-stage/`
- `engines/stage-tamagotchi-godot/scripts/`
## Current Boundary
This is still an experimental G1 Godot sidecar path.
The runtime scene input contract accepts `.vrm` files only. The current
Godot runtime importer covers the VRM 0.x path used by the local fixture
through AIRI’s runtime bridge over the vendored VRM extension. VRM 1.0
editor import support exists in the vendored add-on, but the sidecar
runtime importer does not yet register the full `VRMC_*` extension set,
so this PR does not claim full VRM 1.0 runtime support.
---------
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## Description
<!-- Please insert your description here and especially provide info
about the "what" this PR is solving -->
It has no effect. The actions are run in parallel anyway. They have been
previously updated to not fail when run in parallel.
## Linked Issues
<!-- Optional, if you have any -->
## Additional Context
<!-- e.g. is there anything you'd like reviewers to focus on? -->
## Description
This PR introduces `@proj-airi/stage-tamagotchi-godot` as the initial
Godot C# workspace package for the desktop-only `stage-tamagotchi` stage
runtime track.
The current scope is intentionally limited to G0 bootstrap work:
- add the Godot/.NET project files and workspace wrapper files
- establish the package boundary for the Godot-backed desktop stage
runtime
- add a minimal runnable scene and script so the Godot project can be
opened, built, and executed inside the repo
Concretely, this PR adds:
- the new `packages/stage-tamagotchi-godot` package
- Godot project files (`project.godot`, `.csproj`, `.sln`, editor/config
files)
- a minimal `stage-root` scene and `StageRoot.cs` script
- basic visible scene contents for runtime validation (`Camera3D`,
`OmniLight3D`, `Box`)
- a package README describing scope and ownership boundaries
- minimal package scripts for build/typecheck via `dotnet build`
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Co-authored-by: Garfield Lee <Garfield550@users.noreply.github.com>
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Depends on #1487
## Summary
- Introduce `packages/core-agent` — a new pure-runtime package that
extracts zero-Vue/Pinia algorithmic logic from `@proj-airi/stage-ui`,
following a "compatible facade + core sinking" strategy
- Migrate shared chat types, LLM streaming types, chat hook registry,
session message merge logic, context registry algorithm, and LLM service
utilities into `core-agent`
- `stage-ui` files are preserved as re-exports / thin wrappers — all
external imports, store IDs, and public APIs remain unchanged
## Motivation
`stage-ui` currently mixes pure agent runtime logic (algorithms, type
definitions, stateless utilities) with Vue/Pinia state management and
browser-specific adapters. This coupling makes it hard to:
- Test agent logic in isolation
- Reuse agent algorithms outside of Vue contexts (e.g., server-side,
CLI, other frameworks)
- Reason about the boundary between "what the agent does" vs "how the UI
manages state"
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## Summary
Address maintainer feedback from #1622 ([@nekomeowww's
comment](https://github.com/moeru-ai/airi/pull/1622#discussion_r2342632282)).
The project already uses `async-mutex` in other packages
(`stage-tamagotchi`, `electron-screen-capture`), and it's in the
workspace catalog. This replaces the custom `AsyncMutex` implementation
with the shared dependency.
- Replace `AsyncMutex.run()` → `Mutex.runExclusive()`
- Replace `AsyncMutex.reset()` → `Mutex.cancel()`
- Remove `async-mutex.ts` and its unit tests
- Remove `AsyncMutex` from inference barrel exports
- Add `async-mutex` as direct dependency of `@proj-airi/stage-ui`
**Regarding `@moeru/eventa` suggestion**
([comment](https://github.com/moeru-ai/airi/pull/1622#discussion_r2342631692)):
The `waitForMessage` pattern is a thin request-response abstraction over
`postMessage`, where the worker is driven by `@huggingface/transformers`
internally. Eventa's transport-agnostic RPC is better suited for
bidirectional channels (Electron IPC, WebSocket) than for this one-way
"post and wait" pattern. No change for now.
## Test plan
- [x] `pnpm exec vitest run packages/stage-ui/src/libs/inference/` — 11
tests pass (4 removed with custom impl)
- [x] `pnpm -F @proj-airi/stage-ui typecheck` — no errors
- [x] `pnpm lint:fix` — no new errors in changed files
---------
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## 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-...`)
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RainbowBird