agentleFS
michaelnealemichaelneale/mesh-llm/.agents/skills/deploy-windows/SKILL.md

deploy-windows

Skill3.8k starsChanged 20 days agoApache-2.0View on GitHub

Use this skill when installing, deploying, launching, serving, or troubleshooting mesh-llm on a Windows machine — PowerShell install via install.ps1, flavor selection (CUDA/ROCm/Vulkan/CPU), source builds, the contrib helper scripts, and verifying it serves.

We split this skill into the rules it gives an agent

3 rules. About 0 are common, 0 are distinctive, and 3 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈0

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 3

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Use this when standing up mesh-llm on Windows.

    line 10
  2. Very specific:

    Use curl.exe explicitly — bare curl in PowerShell aliases to Invoke-WebRequest with different argument semantics.

    line 123
  3. Very specific:

    Stop: mesh-llm stop (preferred).

    line 132

≈ “Common” is an estimate: at least 1 in 5 of the 308,232 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

deploy-windows

Use this when standing up mesh-llm on Windows. Counterpart to deploy-macos and deploy-linux-gpu. Same single-binary embedded-runtime architecture; the binary is mesh-llm.exe and release archives are .zip (mesh-llm-x86_64-pc-windows-msvc[-<flavor>].zip).

Related skills/docs:

  • mesh-join — creating/joining meshes (tokens, NAT, multi-node)
  • connect-agents — pointing Goose/Claude Code/OpenCode/Pi at a running mesh
  • mesh/docs/USAGE.md — install details; mesh/docs/CLI.md — full command reference
  • mesh/deploy/windows/README.md — local PowerShell helper scripts

The one rule that matters most

mesh-llm resolves and downloads the model itself. Pass --model <ref> and it fetches the GGUF on first use. Do NOT pre-download with hf CLI tools. (Only --gguf takes a local file path you manage yourself.)

Install (PowerShell)

irm https://raw.githubusercontent.com/Mesh-LLM/mesh-llm/main/install.ps1 | iex

Force a flavor non-interactively:

$env:MESH_LLM_INSTALL_FLAVOR = "vulkan"
irm https://raw.githubusercontent.com/Mesh-LLM/mesh-llm/main/install.ps1 | iex

Facts:

  • Flavors: cuda-blackwell, cuda, rocm, vulkan, cpu. No Metal on Windows. The installer probes nvidia-smi (incl. compute capability for Blackwell), ROCm tooling, and vulkaninfo, then recommends; when input/output is redirected (scripted/SSH) it takes the recommendation without prompting.
  • Installs to %LOCALAPPDATA%\mesh-llm\bin (override: -InstallDir / MESH_LLM_INSTALL_DIR) and prepends it to the user Path unless -NoPathUpdate. Open a new shell, or use the full path, after install.
  • CUDA bundles ship their CUDA DLLs alongside mesh-llm.exe — no system CUDA toolkit install is required to run.
  • Other knobs: -PreRelease / MESH_LLM_INSTALL_PRERELEASE=1, MESH_LLM_REQUIRE_CHECKSUM=1 (makes a missing .sha256 sidecar fatal; default is warn-and-continue).

irm | iex gotchas (learned the hard way — PR #828)

  • A missing checksum sidecar on older releases warns and continues; that is expected, not a failure.
  • On Windows PowerShell 5.1, network errors during sidecar download can surface as vague response-less WebExceptions rather than clean 404s. The installer handles this; if you're debugging a fork/older script, know that iex also breaks [ValidateSet] params (param init to "" fails validation before the script body runs). When irm | iex misbehaves, fall back to downloading the script and running it as a file: irm <url> -OutFile install.ps1; .\install.ps1 -Flavor vulkan.

Build from source (dev)

From a repo checkout (needs Rust, CMake + MSVC, Node, just):

just build                 # auto-detects cuda / rocm / vulkan / cpu
just build backend=vulkan  # override backend

Output: target\release\mesh-llm.exe (for just release-build) or target\debug\ for just build. Windows release archives use the dedicated release-build-*-windows / release-bundle-*-windows recipes. On native Windows, just check-release skips the Bash-only parity checks.

Launch

mesh-llm serve --model unsloth/Qwen3.6-27B-GGUF:UD-Q4_K_XL --auto
  • Same surface as other platforms: --auto joins the public mesh; bare serve --model creates a private mesh and prints an invite token (see mesh-join). API on :9337, console on :3131.
  • Pin a specific GPU with --device (e.g. --device Vulkan1, --device cuda:0); list devices with mesh-llm gpus.
  • There is no service install on Windows (no launchd/systemd equivalent in install.ps1). Run it in a terminal, or wrap it yourself (Task Scheduler / NSSM) — startup models go in %USERPROFILE%\.mesh-llm\config.toml and bare mesh-llm serve reads them.

Repo helper scripts (dev checkouts)

contrib\windows\ wraps a local build (falls back to mesh-llm on Path):

.\contrib\windows\StartMeshServer.ps1 -Model Qwen2.5-3B-Instruct-Q4_K_M -Device Vulkan1
.\contrib\windows\StartChat.ps1 -Model Qwen2.5-3B-Instruct-Q4_K_M
.\contrib\windows\CollectSplitDiagnostics.ps1 -Model <ref> -ConsoleUrls http://127.0.0.1:3131 -ApiUrls http://127.0.0.1:9337/v1

The diagnostics collector attaches to running nodes and zips redacted API payloads, GPU/process facts, and skippy-native.log tails — useful when filing split/runtime issues from a Windows box.

Verify

mesh-llm --version
curl.exe -s http://localhost:9337/v1/models
curl.exe -s http://localhost:3131/api/status
curl.exe -s http://localhost:9337/v1/chat/completions -H "Content-Type: application/json" -d '{"model":"auto","messages":[{"role":"user","content":"hi"}],"max_tokens":16}'

Use curl.exe explicitly — bare curl in PowerShell aliases to Invoke-WebRequest with different argument semantics. Model load takes time; poll /v1/models before concluding failure.

Logs, state, stop

  • Runtime/instance state: %USERPROFILE%\.mesh-llm\runtime\<pid>\ — embedded native logs at logs\skippy-native.log.
  • Config: %USERPROFILE%\.mesh-llm\config.toml; identity: .mesh-llm\key.
  • Stop: mesh-llm stop (preferred). Emergency: use the PID for the specific instance being validated: Stop-Process -Id <mesh-llm-pid> -Force.

Troubleshooting

SymptomCauseFix
irm | iex dies before any outputOld script / [ValidateSet]-style param bugUpdate; or download script to a file and run it
"could not download checksum sidecar" hard failureOld installer + release without .sha256Update installer; missing sidecar should warn-and-continue
mesh-llm not found after installNew Path not in current shellOpen a new terminal or use %LOCALAPPDATA%\mesh-llm\bin\mesh-llm.exe
CUDA flavor won't start on new GPUsBlackwell (SM 100/120) is only in the CUDA 13 runtimeUse the -cuda-13.zip bundle / cuda13 runtime, with a driver that supports CUDA 13
GPU not usedWrong flavor or devicemesh-llm gpus; reinstall correct flavor; --device <id>
curl JSON errors in PowerShellcurl is an IWR aliasUse curl.exe, or Invoke-RestMethod
Empty /v1/modelsModel still downloading/loadingWait; check skippy-native.log

Download now (ZIP)

Trending

Quiet since April.about the whole repository

Dec 2025: 0 mentionsJan 2026: 0 mentionsFeb 2026: 0 mentionsMar 2026: 4 mentionsApr 2026: 14 mentionsMay 2026: 0 mentionsJun 2026: 0 mentionsJul 2026: 0 mentionsAug 2026: 0 mentionsSep 2026: 0 mentionsOct 2026: 0 mentionsNov 2026: 0 mentions
Dec 2025Jun 2026Nov 2026
Mentions a month of the michaelneale/mesh-llm repository that our weekly crawl found. There is no adoption data for this file yet.

Who's talking about michaelneale/mesh-llm

The biggest 5 of 18 mentions linking to the repository that our crawl found. Each line is their own headline.

See all 18

Talked about on GitHub, Bluesky and Hacker News (18 times).

On GitHub · 15

10 more on GitHub

On Hacker News · 1

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.