edge-ai-lab

A lab for edge AI — the exploration engine for the mesh's edge and local-model work: designs, runs and compares experiments across edge hardware and model stacks, then hands proven configurations to lobes-cli, which is the runtime that serves them.

Where it sits

• lobes-cli (binary lobes) is the runtime this lab feeds. lobes runs, assesses, and switches the local vLLM fleet the Culture mesh consumes, tuned per card by machine profiles and composed per box by deployment shapes. A configuration this lab proves lands there — as a profile/shape value, a catalog entry, a per-model doc, or an evidence transcript — via a PR or issue on that repo.
• sparkrun is the recipe-driven launcher for inference workloads on one or more NVIDIA DGX Sparks (vLLM / SGLang / llama.cpp, multi-node tensor parallelism). It is the natural experiment runner for Spark-class arms: an arm is a recipe YAML.
• dgx-spark-cli / rtx-spark-cli operate the boxes themselves (setup, health, monitoring).

Current state: this repository is the mesh-agent scaffold — identity, agent-first CLI, vendored skill kit, CI/publish baseline. The experiment harness and results store are not built yet; the conventions they must follow (evidence-before-claims, benchmark-the-incumbent-first, keep unadopted experiments on record) are documented in CLAUDE.md.

What you get

• An agent-first CLI cited from teken (afi-cli) — the runtime package has no third-party dependencies.
• A mesh identity — culture.yaml (suffix: edge-ai-lab, backend: colleague) and the matching resident prompt file AGENTS.colleague.md.
• The canonical guildmaster skill kit under .claude/skills/, vendored cite-don't-import. See docs/skill-sources.md.
• A build + deploy baseline — pytest, lint, the agent-first rubric gate, and PyPI Trusted Publishing wired into GitHub Actions.

Quickstart

uv sync
uv run pytest -n auto                 # run the test suite
uv run lab whoami                     # identity from culture.yaml
uv run lab learn                      # self-teaching prompt (add --json)
uv run teken cli doctor . --strict    # the agent-first rubric gate CI runs

The console script is lab (python -m edge_ai_lab is equivalent).

CLI

Every command supports --json. Results go to stdout, errors/diagnostics to stderr (never mixed). Exit codes: 0 success, 1 user error, 2 environment error, 3+ reserved.

Contributing

Every PR bumps the version (python3 .claude/skills/version-bump/scripts/bump.py <patch|minor|major> — one bump type per run; CI blocks merge otherwise) and goes through the cicd skill (devex pr + SonarCloud gate). Lint is black / isort / flake8 (line length 100) / bandit / markdownlint plus teken cli doctor . --strict. Full conventions — worktree placement, memory discipline, the ask-colleague reflex, the hand-off contract to lobes-cli — are in CLAUDE.md.

License

Apache 2.0 — see LICENSE.