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strata-docker

Run Strata on an Intel Arc card under Slackware, without installing oneAPI on the host. It wraps upstream's documented Docker route: the SYCL engine is built and run inside the strata-sycl-dev image, the setup and server run on the host. Defaults to an Arc B580 and the Gyro-S model.

Upstream's Intel engine is experimental. Expect rough edges.

Requirements

  • Intel Arc on the xe (or i915) kernel driver, /dev/dri/renderD128 usable by your user
  • Docker, your user in the docker group
  • Python 3.10+ with venv, git
  • Disk: about 13 GB for the image, about 58 GB for Gyro-S
  • Memory: Gyro-S needs about 21 GiB of free RAM for the expert mirror

Usage

./strata-docker fetch     # clone Strata, check out the pinned tag (v0.2.2)
./strata-docker image     # build the strata-sycl-dev image (~6 min, 13 GB)
./strata-docker build     # build the engine for bmg-g21 (~3 min)
./strata-docker setup     # download Gyro-S and start serving
./strata-docker setup --check     # what fits, changes nothing

setup passes extra arguments to upstream's setup.py (e.g. --port 8085, --no-start, --yes). Later runs of setup start the model again without downloading.

Variable Default Meaning
STRATA_REF v0.2.2 upstream tag or commit to check out
STRATA_AOT bmg-g21 AOT target (bmg-g31 for a Pro B70, empty for JIT on A-series)

The server listens on http://127.0.0.1:8080 (OpenAI API at /v1).

License

Copyright (C) 2026 Danilo M. danix@danix.xyz

GPLv2 only. See LICENSE for the full text. Strata itself is MIT licensed, the models carry their own licenses.

Development Approach

This project is developed using AI-assisted tools. Code is generated with the help of AI based on human-provided specifications, design decisions, and iterative feedback.

All contributions are reviewed, tested, and curated by the maintainer before being included in the codebase. AI is used as a productivity and exploration tool, while human oversight remains central to all decisions.

The goal is to combine the flexibility of AI-assisted development with standard open-source practices such as transparency, review, and accountability.