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uzu

Agents & models

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Updated 10-29 04:36

About this skill

Uzu operator

When to use this skill

Use this skill for trymirai/uzu operations: host/tool availability checks, the published mirai CLI, a source checkout pinned to the reviewed commit, local chat or an OpenAI-compatible server, a local benchmark, and model-resource/license decisions. It is not a generic local-LLM router. If the request names llama.cpp or LM Studio, route to that product's skill; if it asks for arbitrary GGUF conversion, route to a conversion-specific skill.

Instructions

  1. Run the side-effect-free helper before choosing a path: 
    python3 .agent-skills/uzu/scripts/preflight.py --json
    From an installed skill root, use: 
    python3 "$SKILLS_ROOT/uzu/scripts/preflight.py" --json
    Add --repo PATH --expect-commit d76d468a1898cacc9c4920accf8f5ff099967107 only when a local checkout exists. The helper never runs Rust, Mirai, model, network, or service commands; runtime_verified remains false.
  2. Prefer the published mirai path on Apple Silicon macOS when it is already available and the user has a confirmed model. Otherwise use the source path only with cargo and rustc present, a checkout at the reviewed commit, and explicit approval for any build or download side effects.
  3. Read references/upstream.md for the pinned command, benchmark, target, model/license, and resource matrices before performing that branch. It is the source of truth for exact commands and citations.
  4. Keep source and model actions separate. cargo tools setup can install rustup, uv, pnpm, targets, and Metal tooling; never invoke it as a probe. A first mirai or source-CLI run may download a checkpoint; obtain consent first and review disk/RAM or unified-memory capacity.
  5. Keep serving loopback-bound (127.0.0.1) by default. Check /v1/models before one chat-completions request. Expose another interface only with an explicit secured target and controls.
  6. State platform uncertainty plainly: Apple Silicon macOS is the primary Metal path; Intel macOS, Linux, Windows, WASM, and other non-Apple source targets are CPU-oriented and/or marked in progress. Do not claim CUDA, Linux-GPU acceleration, or production readiness from this preflight.
  7. Treat Uzu's custom model format as a hard boundary. A model card's license applies to its weights; Uzu's MIT source license does not relicense them, and arbitrary GGUF compatibility is not implied.

Examples

  • "Can Uzu run on this Mac?" Run the helper, report OS/architecture plus separate mirai and source cargo/rustc availability, and label Metal/runtime activation as unverified. Do not install anything.
  • "Serve my already-downloaded model from a pinned checkout." Preflight with --repo and --expect-commit, then follow the source server command in the reference, keeping localhost and recording model/host/commit metadata.
  • "Benchmark two models." Use the reference bench command with a fixed task file and local paths; report measured host-specific results only, never catalog-page numbers as reproduced evidence.
  • "Document Uzu CUDA/GGUF/LM Studio support." Reject the unsupported premise and route the named product or conversion workflow elsewhere.

Best practices

  • Keep the preflight result distinct from runtime proof: ok means offline checks passed, not that a model loaded, Metal accelerated, or a service answered.
  • Pin the exact Uzu commit and resolve the model repository/card, LICENSE, and base-model license before downloading or redistributing weights.
  • Record model identifier, revision/quantization, host, Uzu commit, task file, generation settings, and output path for every run.
  • Use one loaded model/session at a time when memory is constrained; report approximate sizes as budgeting hints and re-check current card metadata.
  • Troubleshoot in order: checkout/commit and tool availability, target/backend, model identifier/format, then loopback endpoint. Do not switch inference engines to hide a Uzu limitation.

References