# Framework Desktop

- [Framework Desktop](#framework-desktop)
  - [BIOS](#bios)
  - [References](#references)
  - [Notes](#notes)
    - [Volume Locations](#volume-locations)
  - [Setup](#setup)
    - [Create the AI user](#create-the-ai-user)
    - [Helper aliases](#helper-aliases)
    - [Create the models dir](#create-the-models-dir)
    - [Install the Hugging Face CLI](#install-the-hugging-face-cli)
    - [Download models](#download-models)
      - [Text models](#text-models)
      - [Image models](#image-models)
    - [Create the systemd-ai pod](#create-the-systemd-ai-pod)
  - [llama.cpp](#llamacpp)
  - [stable-diffusion.cpp](#stable-diffusioncpp)
  - [open-webui](#open-webui)
  - [Install the whole thing with quadlets (TM)](#install-the-whole-thing-with-quadlets-tm)
    - [Install the update script](#install-the-update-script)

## BIOS

<https://knowledgebase.frame.work/en_us/changing-memory-allocation-amd-ryzen-ai-max-300-series-By1LG5Yrll>

1. Set GPU memory to 512MB

## References

<https://docs.podman.io/en/latest/markdown/podman-systemd.unit.5.html>

## Notes

### Volume Locations

`~/.local/share/containers/storage/volumes/`

## Setup

### Create the AI user

```bash
# Create your local ai user. This will be the user you launch podman processes from.
useradd -m ai
loginctl enable-linger ai
su -l ai
mkdir -p ~/.config/containers/systemd/
```

Models are big. You'll want some tools to help find large files quickly when space runs out.

### Helper aliases

Add these to your .bashrc:

```bash
# Calculate all folder sizes in current dir 
alias {dudir,dud}='du -h --max-depth 1 | sort -h'

# Calculate all file sizes in current dir
alias {dufile,duf}='ls -lhSr'

# Restart llama-server / follow logs
alias llama-reload="systemctl --user daemon-reload && systemctl --user restart llama-server.service"
alias llama-logs="journalctl --user -fu llama-server"

# Restart stable diffusion gen and edit server / follow logs
alias sd-gen-reload='systemctl --user daemon-reload && systemctl --user restart stable-diffusion-gen-server'
alias sd-gen-logs='journalctl --user -xeu stable-diffusion-gen-server'
alias sd-edit-reload='systemctl --user daemon-reload && systemctl --user restart stable-diffusion-edit-server'
alias sd-edit-logs='journalctl --user -xeu stable-diffusion-edit-server'
```

### Create the models dir

```bash
mkdir -p /home/ai/models/{text,image,video}
```

### Install the Hugging Face CLI

<https://huggingface.co/docs/huggingface_hub/en/guides/cli#getting-started>

```bash
# Install
curl -LsSf https://hf.co/cli/install.sh | bash

# Login
hf auth login
```

### Download models

#### Text models

<https://huggingface.co/ggml-org/collections>

```bash
# gpt-oss-120b
mkdir /home/ai/models/text/gpt-oss-120b
hf download --local-dir /home/ai/models/text/gpt-oss-120b ggml-org/gpt-oss-120b-GGUF

# gpt-oss-20b
mkdir /home/ai/models/text/gpt-oss-20b
hf download --local-dir /home/ai/models/text/gpt-oss-20b ggml-org/gpt-oss-20b-GGUF

# devstral-2-123b
mkdir /home/ai/models/text/devstral-2-123b
hf download --local-dir /home/ai/models/text/devstral-2-123b unsloth/Devstral-2-123B-Instruct-2512-GGUF Q4_K_M/Devstral-2-123B-Instruct-2512-Q4_K_M-00001-of-00002.gguf
hf download --local-dir /home/ai/models/text/devstral-2-123b unsloth/Devstral-2-123B-Instruct-2512-GGUF Q4_K_M/Devstral-2-123B-Instruct-2512-Q4_K_M-00002-of-00002.gguf

# devstral-small-2-24b
mkdir /home/ai/models/text/devstral-small-2-24b
hf download --local-dir /home/ai/models/text/devstral-small-2-24b unsloth/Devstral-Small-2-24B-Instruct-2512-GGUF Devstral-Small-2-24B-Instruct-2512-Q4_K_M.gguf

# ministral-3-14b
mkdir /home/ai/models/text/ministral-3-14b
hf download --local-dir /home/ai/models/text/ministral-3-14b ggml-org/Ministral-3-14B-Reasoning-2512-GGUF

# ministral-3-3b-instruct
mkdir /home/ai/models/text/ministral-3-3b-instruct
hf download --local-dir /home/ai/models/text/ministral-3-3b-instruct ggml-org/Ministral-3-3B-Instruct-2512-GGUF

# nemotron-nano-30b
mkdir /home/ai/models/text/nemotron-nano-30b
hf download --local-dir /home/ai/models/text/nemotron-nano-30b ggml-org/Nemotron-Nano-3-30B-A3B-GGUF Nemotron-Nano-3-30B-A3B-Q4_K_M.gguf

# qwen3-30b-a3b-instruct
mkdir /home/ai/models/text/qwen3-30b-a3b-instruct
hf download --local-dir /home/ai/models/text/qwen3-30b-a3b-instruct ggml-org/Qwen3-30B-A3B-Instruct-2507-Q8_0-GGUF

# qwen3-coder-30b-a3b-instruct
mkdir /home/ai/models/text/qwen3-coder-30b-a3b-instruct
hf download --local-dir /home/ai/models/text/qwen3-coder-30b-a3b-instruct ggml-org/Qwen3-Coder-30B-A3B-Instruct-Q8_0-GGUF
```

#### Image models

```bash
# z-turbo
mkdir /home/ai/models/image/z-turbo
hf download --local-dir /home/ai/models/image/z-turbo QuantStack/FLUX.1-Kontext-dev-GGUF flux1-kontext-dev-Q4_K_M.gguf
hf download --local-dir /home/ai/models/image/z-turbo black-forest-labs/FLUX.1-schnell ae.safetensors
hf download --local-dir /home/ai/models/image/z-turbo unsloth/Qwen3-4B-Instruct-2507-GGUF Qwen3-4B-Instruct-2507-Q4_K_M.gguf

# flux-1-kontext
mkdir /home/ai/models/image/flux-1-kontext
hf download --local-dir /home/ai/models/image/flux-1-kontext leejet/Z-Image-Turbo-GGUF z_image_turbo-Q4_K.gguf
hf download --local-dir /home/ai/models/image/flux-1-kontext black-forest-labs/FLUX.1-dev ae.safetensors
hf download --local-dir /home/ai/models/image/flux-1-kontext comfyanonymous/flux_text_encoders clip_l.safetensors
hf download --local-dir /home/ai/models/image/flux-1-kontext comfyanonymous/flux_text_encoders t5xxl_fp16.safetensors
```

### Create the systemd-ai pod

You'll at least want the ai pod and network. Copy `ai.pod` and `ai.network` out
of `quadlets` into `~/.config/containers/systemd`.

Then run `systemctl --user daemon-reload && systemctl --user start ai-pod`

## llama.cpp

<https://github.com/ggml-org/llama.cpp/tree/master/tools/server>

```bash
# Build the llama.cpp container image
git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
export BUILD_TAG=$(date +"%Y-%m-%d-%H-%M-%S")

# Vulkan
podman build -f .devops/vulkan.Dockerfile -t llama-cpp-vulkan:${BUILD_TAG} -t llama-cpp-vulkan:latest .

# Run llama server (Available on port 8000)
# Add `--n-cpu-moe 32` to gpt-oss-120b to keep minimal number of expert in GPU
podman run \
--rm \
--name llama-server-demo \
--pod systemd-ai \
--device=/dev/kfd \
--device=/dev/dri \
-v /home/ai/models/text:/models:z \
localhost/llama-cpp-vulkan:latest \
--port 8000 \
-c 64000 \
-b 64000 \
-ub 500 \
--perf \
--n-gpu-layers all \
--jinja \
--models-max 1 \
--models-dir /models
```

## stable-diffusion.cpp

Server: <https://github.com/leejet/stable-diffusion.cpp/tree/master/examples/server>

CLI: <https://github.com/leejet/stable-diffusion.cpp/tree/master/examples/cli>

```bash
git clone https://github.com/leejet/stable-diffusion.cpp.git
cd stable-diffusion.cpp
git submodule update --init --recursive
export BUILD_TAG=$(date +"%Y-%m-%d-%H-%M-%S")

# Vulkan
podman build -f Dockerfile.vulkan -t stable-diffusion-cpp:${BUILD_TAG} -t stable-diffusion-cpp:latest .
```

```bash
# z-turbo
podman run --rm \
-v /home/ai/models:/models:z \
-v /home/ai/output:/output:z \
--device /dev/kfd \
--device /dev/dri \
localhost/stable-diffusion-cpp:latest \
--diffusion-model /models/image/z-turbo/z_image_turbo-Q4_K.gguf \
--vae /models/image/z-turbo/ae.safetensors  \
--llm /models/image/z-turbo/Qwen3-4B-Instruct-2507-Q4_K_M.gguf \
--cfg-scale 1.0 \
-v \
-H 1024 \
-W 1024 \
--seed -1 \
--steps 8 \
--vae-conv-direct \
-o /output/output.png \
-p "A photorealistic dragon"

# Edit with flux kontext
podman run --rm \
-v /home/ai/models:/models:z \
-v /home/ai/output:/output:z \
--device /dev/kfd \
--device /dev/dri \
localhost/stable-diffusion-cpp:latest \
--diffusion-model /models/image/flux-1-kontext/flux1-kontext-dev-Q4_K_M.gguf \
--vae /models/image/flux-1-kontext/ae.safetensors \
--clip_l /models/image/flux-1-kontext/clip_l.safetensors \
--t5xxl /models/image/flux-1-kontext/t5xxl_fp16.safetensors \
--cfg-scale 1.0 \
--sampling-method euler \
--seed -1 \
--steps 28 \
--vae-conv-direct \
-v \
-H 512 \
-W 512 \
-o /output/output.png \
-r /output/everquest_logo.png \
-p "Add the text 'EverQuest'"
```

## open-webui

```bash
mkdir /home/ai/.env
# Create a file called open-webui-env with `WEBUI_SECRET_KEY="some-random-key"
scp active/device_framework_desktop/secrets/open-webui-env deskwork-ai:.env/

# Will be available on port 8080
podman run \
-d \
--pod ai \
-v open-webui:/app/backend/data \
--name open-webui \
--restart always \
ghcr.io/open-webui/open-webui:main
```

## Install the whole thing with quadlets (TM)

```bash
# Installs and runs all services in `quadlets/`
scp -r active/device_framework_desktop/quadlets/* deskwork-ai:.config/containers/systemd/
ssh deskwork-ai
systemctl --user daemon-reload
systemctl --user restart ai-pod.service
```

Note, all services will be available at `host.containers.internal`. So llama.cpp
will be up at `http://host.containers.internal:8000`.

### Install the update script

```bash
# 1. Builds the latest llama.cpp and stable-diffusion.cpp
# 2. Pulls the latest open-webui
# 3. Restarts all services
scp active/device_framework_desktop/update-script.sh deskwork:
ssh deskwork-ai
chmod +x update-script.sh
./update-script.sh
```