ollaya-dev / ollaya

ollaya 
 Run open decision models locally, the way Ollama runs LLMs. 
 Website ·
 Models ·
 Bench ·
 Docs ·
 Releases ·
 Hugging Face 
 Created and maintained by Mert Cobanov ( @mertcobanov ). 
A decision model reads a *state* (a message, an email, a ticket, any JSON) plus typed questions
(`choice`, `score`, `noul`) and returns calibrated probabilities in a single forward pass, in
milliseconds. It never generates text. Ollaya pulls these models by name, serves them from a
local daemon, and speaks TypeSafe's `/v1/systemone` wire format, so existing Jev clients work by
changing one environment variable.
 [code] 
 [code] 
Or ask your own questions: `ollaya run kev --ask "Is a refund requested?" --ask "Which team?" --choice billing --choice sales 
## Install
- **Linux** (x86_64 or arm64, glibc ≥ 2.38, e.g. Ubuntu 24.04+):
 `curl -fsSL https://ollaya.dev/install.sh | sh`. When an NVIDIA GPU is present
 (driver R525+), the installer adds the CUDA runtime: CUDA 13 for R580+, CUDA 12 for older drivers.
- **macOS** (Apple silicon): the same command.
- **Windows** (x64): `irm https://ollaya.dev/install.ps1 | iex` in PowerShell. When an NVIDIA GPU is
 present (driver R527+), the installer adds the CUDA runtime, as on Linux.
- **Desktop app** for macOS, Windows and Linux: start and stop the server, download models and run
 them in one window. On macOS it lives in the menu bar. Get it from
 ollaya.dev/download.
- **Docker:** `docker run -d --gpus=all -p 11435:11435 ghcr.io/ollaya-dev/ollaya:cuda`
 (`:cuda12` for host drivers older than R580), or `ghcr.io/ollaya-dev/ollaya` for CPU only.
Configuration is through environment variables: `OLLAYA_HOST`, `OLLAYA_MODELS`,
`OLLAYA_KEEP_ALIVE`, `OLLAYA_DEVICE`, `OLLAYA_API_KEY` and others, listed in
docs/api.md §15.
## Repository
| Path | What |
|---|---|
| `crates/ollaya` | The binary: CLI, daemon, runner |
| `crates/ollaya-server` | HTTP API, scheduler (one runner process per model), model resolution |
| `crates/ollaya-api` | API types and client; the contract is docs/api.md |
| `crates/ollaya-registry` | Model names, manifests, blob store, resumable pulls |
| `crates/ollaya-decision` | Question schema, sequence layouts, calibration, answers |
| `crates/ollaya-runner` | Inference engines (ONNX Runtime, and llama.cpp for GGUF models) |
| `crates/ollaya-lang` | Script and language detection for routers |
| `convert/` | Build-time Python: ONNX export, parity checks, packaging |
| `site/` | The website and the static model registry host |
## Development
 [code] 
`convert/` rebuilds models. It exports them, checks parity against the PyTorch reference,
generates golden fixtures, and packages the result into `registry/`. See the module docstrings.
`cd convert && uv sync` installs it: with CUDA 13 torch on Linux and Windows, and with the CPU and
MPS build from PyPI on Apple silicon Macs, where exports and parity run on the CPU.
## License
Apache-2.0. Each model keeps its own license: `laya` (Convai Innovations), `decider` (