Skip to main content

Fleet manager for local LLM inference engines on Apple Silicon

Project description

asiai-inference-server

Fleet manager for local LLM inference engines on Apple Silicon.

Status: v0.3.0 — released on PyPI. Lifecycle, memory reclaim, presets, upgrades, fleet push and health probing are functional. See the roadmap below for what each version shipped.

asiai-inference-server is the control plane companion to asiai (the observability/benchmark CLI). Where asiai observes what's running on your Mac, this project manages it: install, start, stop, unload, and orchestrate inference engines (llama.cpp, Ollama, LM Studio, oMLX, TurboQuant, mlx-lm, vMLX, …) across one or several Apple Silicon machines.

It also fixes the long-standing macOS pain point: engine memory that never gets freed because of the unified-memory compressor. Killing a process doesn't release the VRAM. This tool combines per-engine unload APIs, full LaunchDaemon restart, and sudo purge to reclaim memory deterministically — and reports the actual delta measured, not a marketing promise.

Why

After a year of running multi-engine LLM inference on Apple Silicon (MacBook M1 Max, Mac Mini M4 Pro, MacBook M5 Max), the operational gap became obvious:

  • Install/uninstall an engine should not require chasing brews, plists and firewall rules across READMEs.
  • Switching profiles ("coding agent on Qwen-Coder 32B" → "70B chat on TurboQuant") should be a single command, not five.
  • Memory unload should actually free the VRAM, not let the macOS compressor sit on it.
  • A fleet of Macs should be a single dashboard, not three SSH sessions.
  • AI agents (Claude Code, Cursor, Windsurf) should be able to manage the fleet via MCP, not just observe it.

asiai-inference-server ships these one at a time, building on the asiai observability stack.

Roadmap

Version Scope Status
v0.1 Install/uninstall/start/stop/restart + unload + purge memory, pf firewall anchor, sudoers bootstrap shipped
v0.2 aisctl upgrade (brew, whitelisted), asiai versions provider, fleet Phase 2 (loopback serve + orchestrator fleet push) shipped
v0.3 status --deep (generation probe, catches GPU-OOM zombies), install records + reinstall, single preset location, disable/enable (cold standby) shipped
v0.4 asiai-priv privileged helper — a root-owned, content-validating helper replaces the wildcard sudoers: generate-don't-validate plists, a closed action allowlist, forced non-root run-as, and an append-only audit log; NOPASSWD is reduced to the helper alone shipped
v0.5 SMAppService app bundle + asiai-launch (named entry with custom icon in Background Items) in review
later Profile switching (apply/rollback), fleet inventory, web cockpit, MCP write tools planned

Architecture (high level)

  • CLI: aisctl <command> (standalone) or asiai engine <command> (auto-injected sub-CLI when asiai-inference-server is installed alongside asiai).
  • Python stdlib only for the core (consistent with asiai). The package depends on asiai>=1.8.0 (auth.loopback for fleet Phase 2). Optional extras: mcp (for future write tools).
  • macOS Apple Silicon only. We rely on launchctl, vm_stat, sudo purge, pfctl, iogpu.wired_limit_mb.
  • HTTP agent for fleet operations (loopback serve + fleet push orchestrator, shipped v0.2).
  • TOML for human-edited files (engine manifests, profiles, fleet inventory). JSON for runtime state.

License

Apache-2.0 © 2026 Jean-Marc Nahlovsky

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

asiai_inference_server-0.4.0.tar.gz (242.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

asiai_inference_server-0.4.0-py3-none-any.whl (156.9 kB view details)

Uploaded Python 3

File details

Details for the file asiai_inference_server-0.4.0.tar.gz.

File metadata

  • Download URL: asiai_inference_server-0.4.0.tar.gz
  • Upload date:
  • Size: 242.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for asiai_inference_server-0.4.0.tar.gz
Algorithm Hash digest
SHA256 faa3f2aabeda5e631e3ccac2f00c2769153c7a06274e5b603e6fa94cdf405203
MD5 f9da6a7249105bc367fdfdf1da975e75
BLAKE2b-256 90029378ae865e7a474169051cd22368ec0aca3be5df0aefca69937201dbc4ec

See more details on using hashes here.

Provenance

The following attestation bundles were made for asiai_inference_server-0.4.0.tar.gz:

Publisher: release.yml on druide67/asiai-inference-server

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file asiai_inference_server-0.4.0-py3-none-any.whl.

File metadata

File hashes

Hashes for asiai_inference_server-0.4.0-py3-none-any.whl
Algorithm Hash digest
SHA256 b8ce50aad5a06b813bfcd8993f02b0dbaeadbc855043f66bc4f1148bfc42e65e
MD5 8a51ae30d2ecc74178960ed5959c824f
BLAKE2b-256 15f15c3047dd0703efcaf61439bda43b51188836bcbe5a6b1469a0453606ccd8

See more details on using hashes here.

Provenance

The following attestation bundles were made for asiai_inference_server-0.4.0-py3-none-any.whl:

Publisher: release.yml on druide67/asiai-inference-server

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page