Vili

Vili is the GameCult Persona animation daemon.

It owns the bridge from Persona performance intent to body-motion generation. Its first backend is Kimodo on Raven, running through Docker Engine inside Ubuntu-24.04 WSL with NVIDIA GPU passthrough.

Authority

• Vili owns animation job intake, Kimodo runtime checks, Kimodo resident worker lifecycle, generated motion artifact references, and its operator/provider surface.
• Personas and Weksa may propose performance intent, gesture prompts, and constraints.
• Kimodo owns motion synthesis.
• Future renderers own retargeting, playback, facial performance, camera, and lip sync.
• Odin discovers Vili; Odin does not own Vili's state.
• Vili is started at boot by its scheduled task on Raven today; nothing restarts it after a crash, and Idunn does not manage it until its admission is ruled (deferred until RPS has its clips). Idunn would not own animation decisions.

Local Runtime

On Raven:

E:\Projects\Vili\scripts\restart-vili-daemon.cmd

Default compatibility endpoint:

http://10.77.0.4:8824

Vili is not an Idunn target today. Its lifecycle is the GameCult\Vili scheduled task on Raven, and GET /health is an operator lowering. Admission to Idunn is motion-pipeline❓vili-under-idunn.

Vili also writes daemon-owned service state to:

E:\Projects\Vili\.vili\vili.service.cc

That CultCache store owns the provider advertisement, operator state, Eve surface, command boundary, and transport profile. The adjacent JSON files are compatibility exports for tools that have not learned the .cc store yet.

Important routes:

• GET /health
• GET /provider-advertisement
• GET /operator-state
• GET /eve/operator
• GET /eve/deck/providers
• WS /eve/deck/vili.animation
• GET /smoke
• POST /motion/generate

Motion Generation

POST /motion/generate exposes Kimodo's generation surface through the resident worker. Vili owns job identity, persistence, timeout handling, worker lifecycle, and the output stem; Kimodo owns synthesis and model-specific export formats.

Minimal request:

{
  "prompt": "a person gives a small friendly wave",
  "duration": 1,
  "diffusionSteps": 20,
  "bvh": true
}

Batch requests can use Kimodo-style metadata:

{
  "meta": {
    "texts": [
      "a person gives a small friendly wave",
      "a person takes one careful step"
    ],
    "durations": [0.5, 0.5],
    "num_samples": 1,
    "diffusion_steps": 20
  },
  "numTransitionFrames": 3,
  "cfgType": "regular",
  "cfgWeight": [1.5],
  "seed": 6101,
  "bvh": true,
  "bvhStandardTpose": true,
  "saveExampleDir": true
}

Supported request fields:

• prompt / utterance plus duration / durationSeconds
• texts plus durations, or a full meta object
• inputFolder / input_folder for a container-visible Kimodo input folder with meta.json and optional constraints.json
• model; changing the requested model restarts the single resident worker
• diffusionSteps / diffusion_steps
• numSamples / num_samples
• numTransitionFrames / num_transition_frames
• constraints as an object/list, or constraints, constraintsPath, or constraints_path as a container-visible path
• seed
• cfg, cfgType / cfg_type, cfgWeight / cfg_weight
• bvh, bvhStandardTpose / bvh_standard_tpose
• noPostprocess / no_postprocess
• saveExampleDir / save_example_dir
• timeoutMs, workerTimeoutMs

Vili intentionally does not accept an arbitrary Kimodo output path. Generated artifacts are written under .vili/artifacts/{jobId}/ and referenced from the job record. Kimodo-SOMA-RP-v1.1 produces NPZ and optional BVH output, Kimodo-SMPLX-RP-v1.1 also exports AMASS NPZ, and Kimodo-G1-RP-v1.1 also exports CSV when that model is resident.

Current Runtime State

Raven has a Hugging Face token installed at /root/.cache/huggingface/token inside Ubuntu-24.04. Vili mounts that token read-only into Kimodo containers and passes the standard Hugging Face token environment variables.

Vili keeps Kimodo warm through a resident worker container named vili-kimodo-worker. The worker loads the model once, exposes /health and /generate inside WSL on 127.0.0.1:8825, and serializes generation through the loaded model. Because Raven's Docker Engine runs inside WSL, Vili also keeps a tiny WSL sleep-loop alive while the worker is resident so the Docker substrate does not disappear underneath the model. GET /health observes worker state without launching model load. GET /smoke verifies the backend and starts the resident worker when it is absent.

Kimodo's 8B text encoder (LLM2Vec, Llama 3) never lives in the worker. The worker answers Kimodo's encoder call from a CultCache store of float32 vectors, .vili/embeddings/text-embeddings.cc (gamecult.vili.text_embedding.v0, written through the cultcache-py checkout mounted from E:\Projects\CultLib). A vector's key is sha256(encoderIdentity + newline + text), and the identity names the three Hugging Face snapshot revisions, bfloat16, the transformers and peft versions and the Kimodo commit, so a changed input misses instead of serving a stale vector. Kimodo normalizes the prompt before encoding (A person shrugs sadly.), and the cache keys on that text. A request's misses go to one transient child, scripts/kimodo-text-encode.py: it loads the encoder in bf16 on the GPU, with the layers that do not fit in free VRAM held in RAM, encodes, writes its answer and exits, so the OS reclaims its RAM and VRAM. It refuses with a typed gpu-busy below 2 GiB of free VRAM and has no CPU fallback; hits never touch it. Each /motion/generate job carries the encoder record (hits, misses, seconds, vector hashes) and the worker identity. GET /health shows the identity and the stored count.

Measured on Raven on 2026-10-22, for a 2 second clip at 20 diffusion steps: the worker is healthy 29 seconds after docker rm (was 179) and rests at 2.3 GiB resident (was 10.4 GiB, with 5.8 GB swapped). A cache miss takes 59 to 103 seconds, the encode being nearly all of it (the 103 was with the model files cold in the page cache); the CPU encoder took 316 to 376. A hit takes under one second. The child peaks at 14.1 GiB of VRAM, so a miss needs almost the whole 16 GB card.