Local AI Use (route image, TTS, STT through Lemonade)

This is a meta-skill. You run it once. After that, every later request that needs image generation, text-to-speech, or speech-to-text uses the local Lemonade Server instead of a cloud API. The agent's own LLM keeps handling text; only the expensive multimodal calls move on-device.

The skill does three things:

1. Makes sure local Lemonade is installed and running. If no modern lemonade CLI is found, the setup script installs the latest version of Lemonade on the user's behalf. Modern Lemonade has no serve command — the Lemonade service (the lemond daemon) auto-starts on install and is managed by the OS — so the setup script waits for the service and, if it stays down, prints the exact OS-specific command to start it (e.g. sudo systemctl start lemond on Linux).
2. Verifies that local Lemonade is reachable.
3. Drops a Local AI Use block into the workspace AGENTS.md so the agent reads the routing rule on every later turn, in Cursor, Claude Code, Codex, Gemini CLI, and any other agent that respects AGENTS.md.

Requires modern Lemonade (v10.1.0 or newer). Modern Lemonade unified everything under one lemonade CLI (lemonade status, lemonade pull, ...) driving an always-on lemond service. This skill targets that and installs Lemonade only from the official installers (see below) — never via pip install lemonade-sdk, which is a separate, older release line. If an older/incompatible lemonade is already on the PATH (from any channel — an old .msi/.deb or a pip install), it will shadow the modern CLI; uninstall it first (see the removal commands in Step 1a) before running this skill.

Models are not downloaded during setup. Each default model is pulled lazily, on first use, by the routing rule (e.g. the first image request pulls the image model). This keeps setup fast and avoids gigabytes of downloads the user may never need.

When to use this skill

Use this skill when all of the following are true:

• The user wants local Lemonade. If it is not yet installed, the setup script installs the latest version for them automatically.
• The user accepts the default Lemonade endpoint http://localhost:13305.
• The user wants the change to be persistent across future turns and agent restarts (the rule is written to disk).

If the user is instead embedding Lemonade as a private subprocess inside an app installer, do not use this skill; use local-ai-app-integration instead.

Prerequisites

• OS: Windows 11 x64, Ubuntu/Debian x64, or macOS (beta).
• Lemonade: the setup script installs it if missing. It downloads and silently installs the latest version (Windows lemonade.msi, the Ubuntu/Debian ppa:lemonade-team/stable PPA, or the macOS .pkg). The lemond service auto-starts after install; the script waits for it rather than launching it. On Linux/macOS the install needs sudo. Pass --no-install if the user wants to install it themselves instead.
• Disk: ~8 GB free for the three default models (SD-Turbo + Whisper-Tiny
  • kokoro-v1), plus ~0.1 GB for the installer itself.
• Network: required for the install download and the first lemonade pull of each model. After that, every modality runs offline.

The opinionated path

Run this checklist top to bottom. Track progress against it; do not move on until each step verifies.

[ ] 1. Ensure Lemonade Server is installed and running (auto-install if missing)
[ ] 2. Install the routing rule into the workspace AGENTS.md

The single command that does both steps in one shot is:

python scripts/setup_local_ai.py

Always run this script first — even if Lemonade is already installed and the server is already running, and even before generating a single image. Writing the routing rule into AGENTS.md is what makes this skill complete; skipping it because "Lemonade is already up" leaves the workspace unconfigured for future turns. The script is safe to run in that case: it detects the running service, skips the install, and just writes the rule.

It auto-installs the latest version of Lemonade if no modern lemonade CLI is found, waits for the auto-started lemond service, then writes the rule. The script is idempotent: re-running it on a fully configured workspace is a no-op apart from a healthcheck. Read the sections below for what to do when each step fails.

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Step 1: ensure Lemonade Server is installed and running

scripts/setup_local_ai.py handles this end to end, but here is what it does so you can do it by hand or debug it:

1a. Is a modern lemonade CLI installed? Run lemonade status. The check is by capability, not by name: modern Lemonade prints Server is running... or Server is not running. If instead you get an "invalid choice" / usage error, the lemonade on PATH is an old, incompatible build that predates the unified CLI (v10.1.0) — do not use it. It could have come from any install channel, so remove it based on how it was installed, then re-run this skill (or install Lemonade manually):

Installed via	Uninstall with
Windows .msi	winget uninstall -e --id AMD.LemonadeServer, or Settings > Apps > Installed apps > Lemonade Server > Uninstall
Ubuntu/Debian apt/PPA	sudo apt remove lemonade-server
pip	pip uninstall lemonade-sdk
macOS .pkg	Delete the installed Lemonade.app / remove the package receipt

Never try to drive or auto-remove it for the user.

If no lemonade is found at all, install the latest version on the user's behalf:

OS	Install
Windows	Download lemonade.msi from the latest release and run msiexec /i lemonade.msi /qn (silent, per-user, no elevation).
Ubuntu/Debian	sudo add-apt-repository -y ppa:lemonade-team/stable && sudo apt-get update && sudo apt-get install -y lemonade-server (the apt package is lemonade-server; the CLI you then run is lemonade)
macOS (beta)	Download the Lemonade-<ver>-Darwin.pkg from the latest release and run sudo installer -pkg Lemonade-<ver>-Darwin.pkg -target /.

After a Windows install the CLI lands in %LOCALAPPDATA%\lemonade_server and is added to the user PATH (new shells only); the setup script probes that directory so it works in the same run.

1b. Is the service running? Check lemonade status --json. The lemond service auto-starts on install — there is no lemonade serve in modern Lemonade.

lemonade status says	Action
Server is running on port 13305	Continue to Step 2.
Server is not running	Wait a few seconds for the auto-started service (the script polls /api/v1/health). If it stays down, start it via the OS service manager: sudo systemctl start lemond (Linux system install) or systemctl --user start lemond (per-user install); launchctl load /Library/LaunchDaemons/com.lemonade.server.plist (macOS); the Lemonade tray app or Start-Service lemond (Windows).

Only if the automatic install genuinely fails (no apt-get, no sudo, download blocked) should you stop and point the user at https://lemonade-server.ai/docs/guide/install/.

The rest of this skill assumes the endpoint is http://localhost:13305/api/v1 and no API key is required (the system-wide server defaults to no auth on loopback). If the user has set LEMONADE_API_KEY, the routing rule template in templates/local-ai-rule.md shows where to add the Authorization header.

Default modality models (pulled on first use, not during setup)

Setup does not download these. The installed rule pulls each one the first time that modality is requested. They are the Lite Collection defaults from Lemonade OmniRouter, sized to keep token-and-cost savings real on commodity hardware:

Modality	Model	Size	Why this default
Image generation	SD-Turbo	~5 GB	Single-step generation, runs on CPU and AMD iGPU/dGPU
Text-to-speech	kokoro-v1	~0.3 GB	Only TTS model Lemonade currently supports; CPU-only, low latency
Speech-to-text	Whisper-Tiny	~0.1 GB	Smallest Whisper; fast on CPU. Upgrade to Whisper-Large-v3-Turbo if accuracy matters more than latency.

To write a different model ID into the rule, pass it to the setup script. For example, to make future image requests use SDXL:

python scripts/setup_local_ai.py --image-model SDXL-Turbo

That model ID is written into the installed AGENTS.md rule and pulled on its first use. The same pattern works for --tts-model and --stt-model. For larger / higher-quality alternatives (SDXL-Turbo, Flux-2-Klein-4B, Whisper-Large-v3-Turbo), see the model picker in reference.md.

Step 2: install the routing rule into AGENTS.md

The rule is a Markdown block stored in templates/local-ai-rule.md. Append it to the workspace's AGENTS.md (create the file if missing). Both Cursor and Claude Code load AGENTS.md automatically on every turn, so the agent will see the rule on its next message without any further setup.

scripts/setup_local_ai.py does this for you. It bakes the selected endpoint and model IDs into the rule, surrounded by stable markers so re-running the script replaces the block in place rather than appending a second copy. The markers look like:

<!-- BEGIN amd-skills:local-ai-use -->
...rule...
<!-- END amd-skills:local-ai-use -->

If you write the file by hand, keep those exact markers. The script relies on them for idempotent updates.

If the user's agent only respects a different convention, mirror the same block to:

• CLAUDE.md (Claude Code, project-scoped) or ~/.claude/CLAUDE.md (global)
• .cursor/rules/local-ai-use.mdc (Cursor user/project rules)
• GEMINI.md (Gemini CLI)

The rule's content is identical; only the file location changes.

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What changes after this skill runs

From the next turn onward, the agent reads the rule in AGENTS.md on every message. The rule explicitly tells the agent:

• For image generation: call POST /api/v1/images/generations on the local server. Do not call any cloud image API and do not use the built-in GenerateImage tool (that path bills tokens to the cloud provider).
• For text-to-speech: call POST /api/v1/audio/speech. Do not call cloud TTS providers (OpenAI TTS, ElevenLabs, etc.).
• For speech-to-text: call POST /api/v1/audio/transcriptions. Do not call cloud transcription providers.
• Fallback: only fall back to a cloud API after one local attempt has failed and the user has been told the local call failed. Never silently fall back; the whole point of this skill is to keep cost predictable.

The agent's own text reasoning continues to use whatever LLM Cursor / Claude Code / Codex is configured with. This skill does not redirect chat tokens; it only redirects the multimodal calls that would otherwise leave the machine.

Troubleshooting cheatsheet

Symptom	Cause	Recovery
lemonade: command not found	CLI not installed	Re-run python scripts/setup_local_ai.py (auto-installs the latest version). If it just installed on Windows, open a new shell so the user PATH refreshes, or the script will find it under %LOCALAPPDATA%\lemonade_server.
status gives an "invalid choice" / usage error	An old, incompatible lemonade (pre-v10.1.0, from any install channel) is shadowing the modern CLI	Uninstall it the way it was installed (see the Step 1a table: winget uninstall -e --id AMD.LemonadeServer / sudo apt remove lemonade-server / pip uninstall lemonade-sdk), then re-run the setup script or install Lemonade from the docs link.
Server is not running	lemond service stopped	Start it via the OS service manager — sudo systemctl start lemond / systemctl --user start lemond (Linux), launchctl load /Library/LaunchDaemons/com.lemonade.server.plist (macOS), or the tray app / Start-Service lemond (Windows). There is no lemonade serve.
POST /v1/images/generations returns 404 model not found	Image model not downloaded	lemonade pull SD-Turbo and retry.
lemonade pull keeps printing Progress: NN% but never finishes	Download target is a bad path (out of space, no write permission, quota, read-only mount). The write error may surface only in the server log while the console keeps showing progress	Check the target and free space first: GET /api/v1/system-info reports models_dir and model_storage.free_bytes. If a pull stalls, read the recent lines of the server log (typically lemonade-server.log in the OS temp dir) for the real error (e.g. a download/write failure like CURL code 23, or an out-of-space message), then point the download at a writable disk with room.
Image generation is slow on CPU (~4–5 min)	sd-cpp on CPU backend	Install the GPU backend on supported AMD hardware: lemonade backends install sd-cpp:rocm.
POST /v1/audio/transcriptions returns 400 unsupported format	Input is not 16 kHz mono WAV	Re-encode with ffmpeg -i in.* -ar 16000 -ac 1 out.wav.
POST /v1/audio/speech returns 404	TTS model not downloaded	lemonade pull kokoro-v1.
401 Unauthorized on every request	User has set LEMONADE_API_KEY	Add Authorization: Bearer $LEMONADE_API_KEY to every request and to the rule block.

Verification checklist

Mark this skill complete only when all of the following are true:

• [ ] lemonade status --json reports the server running on port 13305.
• [ ] The workspace AGENTS.md contains the amd-skills:local-ai-use block. This is required even when Lemonade was already installed and running — generating an image alone does not complete the skill.
• [ ] On a follow-up turn, asking the agent to "generate an image of X" causes it to POST to http://localhost:13305/api/v1/images/generations (pulling the model on first use) rather than calling a cloud tool.

If any box is unchecked, the user is still paying cloud cost for at least one modality.

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Reference

For the full model picker, alternate-quality options, the complete endpoint reference, the API-key flow, and the OmniRouter tool definitions you can hand to an agent's tool-calling loop, see reference.md.