Vili

Vili is the GameCult Persona animation daemon.

It owns the bridge from Persona performance intent to body-motion generation. Its backend is Kimodo, run by Vili's own daemon as a CPU-only Python process tree on Linux. It is built to run on Yggdrasil as an Idunn target (planned, not live; see Front Door).

Front Door

• Value: a supervised path from a text prompt to generated body motion. The daemon spawns one resident Kimodo worker, caps its threads, and returns motion artifacts (motion.npz, optional BVH) for a job.
• Problem: Personas and games need generated motion, but cold per-request model loads cost minutes. One daemon owns job identity, worker lifecycle, the thread budget and artifact references, so callers touch no model state.
• Entry points: scripts/vili-daemon.mjs (the daemon; npm start, npm test), scripts/idunn-entry.mjs (the process Idunn runs), deployment/idunn/recipe.toml (the sealed release), scripts/kimodo-resident-worker.py (the worker it spawns), scripts/kimodo-text-encode.py (the one-shot encoder child), POST /motion/generate (see Motion Generation), docs/verse-service-contract.md and docs/motion-pipeline-target.md.
• Live: the process tree below, run by hand for development and tests: POST /motion/generate, GET /health, GET /operator-state, and the CultCache service store. It produces motion.npz and optional BVH on the SOMA skeleton; there is no FBX export.
• Planned: the Idunn target vili on Yggdrasil at http://10.77.0.1:8824 over WireGuard, with its provisioning runbook in gamecult-ops; neither exists until the first idunn up lands. FBX export and a text-prompt-to-Unity-clip path with no hand steps (docs/motion-pipeline-target.md).

Authority

• Vili owns animation job intake, the worker process lifecycle, and generated motion artifact references.
• 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.
• Operator surfaces wait for Thing 2; today Vili publishes typed state and plain HTTP.

Local Runtime

One Linux CPU process tree:

vili-daemon.mjs          job intake, worker lifecycle, thread cap, nice 10
  kimodo-resident-worker.py   resident Kimodo model, one generation at a time
    kimodo-text-encode.py     one child per request with cache misses, on CPU

Setup: git submodule update --init (CultLib, Kimodo, SOMA-X); in vendor/CultLib, npm ci --ignore-scripts and npm run build --workspace=packages/cultcache-ts and --workspace=packages/cultnet-ts; then npm ci --install-links here. The worker needs a Python environment with Kimodo's pins and Kimodo itself importable, and a Hugging Face cache (<models root>/hub) holding the Llama 3 base, both LLM2Vec adapters and the Kimodo checkpoint. Everything runs offline.

node scripts/vili-daemon.mjs --python <python> --models-root <hf home> --kimodo-commit <sha> --python-env <env id> [--threads 8]

Flags, each with an environment twin: --host (VILI_DAEMON_HOST, 127.0.0.1), --port (VILI_DAEMON_PORT, 8824), --state-root (VILI_STATE_ROOT, .vili), --python (VILI_PYTHON), --worker-entry (VILI_WORKER_ENTRY, the test seam), --models-root (VILI_MODELS_ROOT), --threads (VILI_THREADS, 1 to 16, default 8), --kimodo-commit (VILI_KIMODO_COMMIT), --python-env (VILI_PYTHON_ENV, the environment's identity). A generate request without a models root, Kimodo commit and Python environment id gets 503 worker-unconfigured before anything spawns.

The daemon starts the worker on the first job, on a port the worker binds itself and reports in its ready line, and respawns it after an exit. The worker runs at nice 10 with torch limited to --threads (also OMP_NUM_THREADS and MKL_NUM_THREADS), so a shared host keeps its other services. Its log is <state>/logs/worker.log. The daemon owns the whole worker process group: it is killed when the worker exits for any reason, on SIGTERM or SIGINT, and, for a hand-run daemon, at start-up if a crashed predecessor left one (<state>/worker.pid). Under Idunn the unit's cgroup owns the tree.

A hand-run daemon holds its state root through a listening socket in Linux's abstract namespace, named by the root's real path: the bind is the atomic claim, so a second daemon on a live root prints that it is held and exits 2, killing nothing, and a dead daemon's claim is gone with it (there is no lock file). Two daemons in separate network namespaces do not exclude each other.

On Yggdrasil

Idunn runs node vili/scripts/idunn-entry.mjs --state-root <root> --kimodo-commit <sha> from a sealed release of three trees: node, vili (the daemon, worker, child, node_modules, cultcache-py) and python (python-build-standalone CPython 3.12 with the hash-locked packages, Kimodo, MotionCorrection and SOMA-X installed into it; no venv). The weights are the read-only cache /srv/vili/models; state is /var/lib/gamecult/vili. Idunn's process write lease is the one writer authority: until the daemon holds it, POST /motion/generate answers 503 write-lease-pending and nothing is written; if the lease is lost the worker tree is killed and it answers 503 write-lease-lost. Idunn proves readiness with its own POST /cultnet/snapshot challenge, answered with a signed runtime presence (an Origin is still refused).

POST /motion/generate refuses any POST that carries an Origin or is not application/json with 403 cross-site; no route answers a preflight.

Vili writes daemon-owned state to .vili/vili.service.cc: operator state, the command boundary and the transport profile. Jobs are .vili/jobs/<jobId>.json, artifacts .vili/artifacts/<jobId>/.

Routes: GET /health, GET /operator-state, POST /motion/generate; under Idunn also POST /cultnet/snapshot, Idunn's route challenge.

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 Kimodo input folder on the worker host 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 path on the worker host
• 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

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, <state>/embeddings/text-embeddings.cc (gamecult.vili.text_embedding.v0, through the cultcache-py in vendor/CultLib). A vector's key is sha256(encoderIdentity + newline + text). The identity names the three Hugging Face snapshot revisions, the encoder assembly and prompt form, the device, dtype, the torch, transformers, peft and accelerate versions, the Kimodo commit and the sha256 of kimodo-text-encode.py, so a changed input misses instead of serving a stale vector. Thread count is provenance, recorded in the worker identity, not identity.

The encoder is the Llama 3 base with the MNTP adapter merged, then the supervised adapter, in bfloat16 on CPU, and kimodo-text-encode.py wraps every prompt in Llama 3 Instruct's chat header itself (text_encoding.chat_header, pooled after LLM2Vec's query marker), as Kimodo's LLM2Vec does when loaded from the repo ids. The identity names that prompt form. A fresh child vector matches Kimodo's own encoder from the repo ids (test_text_encoding.ReferenceVector, run on Yggdrasil). The measured timings are in docs/research/vili-on-yggdrasil-cpu-2026-10.md. 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 that loads the encoder, encodes, writes its answer and exits, so the OS reclaims its RAM; hits never touch it. Each job carries the encoder record (hits, misses, seconds, vector hashes) and the worker identity. The cache starts empty on a new host: vectors from another assembly or device are never copied in.