utopic 0.1.3

Python package manager for the Utopic native runtime

Utopic Package Manager

Python package management for the Utopic native runtime.

This repository is intentionally thin. The wheel installs Python launchers plus the small Utopic native source tree. Dependency checkout, build configuration, and binary installation all happen later through utopic setup.

Install

uv tool install utopic
utopic setup

utopic setup detects the best local backend and builds the matching native runtime:

• macOS with a usable Metal device: metal
• NVIDIA host with a usable CUDA compiler: cuda
• everything else: cpu

The setup command prints the selected backend, detected device, and reason before building. It installs runtime binaries under ~/.cache/utopic/bin.

If you prefer a project-local environment:

python3 -m venv ~/.venvs/utopic
~/.venvs/utopic/bin/pip install utopic
~/.venvs/utopic/bin/utopic setup

For local development from this checkout:

git clone https://github.com/adavyas/utopic-package-manager.git
cd utopic-package-manager
pip install .
utopic setup

Backend Overrides

Most users should run plain utopic setup. To force a backend:

On NVIDIA hosts, build the CUDA backend:

utopic setup --backend cuda

The CUDA setup path detects the local GPU architecture and selects a suitable CUDA compiler when possible, including CUDA 13 on GB10/DGX Spark hosts. On constrained hosts, limit build parallelism:

utopic setup --backend cuda --jobs 2

If a Mac cannot initialize Metal, or you want a portable CPU-only build:

utopic setup --backend cpu

To force Metal on macOS:

utopic setup --backend metal

Commands

The package installs these launchers:

• utopic
• utopic-server
• utopic-mcp
• utopic-acp

Run a one-shot prompt:

utopic run -m /path/to/model.gguf -p "Answer with one word: 2+2?" -n 16

For DiffusionGemma-style canvas models, use the entropy-bound path:

utopic run -m /path/to/diffusiongemma.gguf -p "Answer with one word: 2+2?" -n 16 --eb-steps 48

Run the OpenAI-compatible local server:

utopic-server -m /path/to/model.gguf --host 127.0.0.1 --port 8910 -ngl 99

Health and model list:

curl http://127.0.0.1:8910/health
curl http://127.0.0.1:8910/v1/models

What Setup Owns

The package manager owns the user-facing setup path:

• use the packaged Utopic native source
• fetch the pinned compatible public llama.cpp dependency source
• configure the native build for CPU or CUDA, including CUDA compiler and architecture detection
• build the dependency layer and Utopic
• copy the final binaries into the Utopic cache

The published wheel stays pure Python and does not fetch or compile native code during pip install. Users should not need to clone dependency repositories or run build-system commands directly for normal setup.

Use the package-managed binary produced by utopic setup for user-facing runs. On the 2026-06-21 GB10 smoke, /home/adavya/.cache/utopic-current/bin/utopic successfully generated from the installed Dream Q4, LLaDA Q4, DiffusionGemma BF16, and DiffusionGemma Q4 GGUFs. The repo-local native build loaded the same files, but was stale for DiffusionGemma prompt wrapping.

Development

Build a wheel:

python -m pip wheel . --no-deps -w dist/