Merge pull request #77 from outis1one/claude/exciting-allen-uea3dx
Claude/exciting allen uea3dx
This commit is contained in:
Outis
@@ -67,7 +67,7 @@ Update them any time with `sudo ./setup.sh configure`.
|
||||
|-------|---------|
|
||||
| `base` | `net-tools`, `ncdu`, `git`, `curl`, `wget`, `htop`, `tree`, `zip`/`unzip`, `ca-certificates`, `gnupg`, `jq`, `rsync`; `glow` (terminal markdown reader, Charm apt repo) |
|
||||
| `homelab` | `caddy`, `crowdsec`, `authelia`, `homeassistant`, `asterisk` |
|
||||
| `utilities` | `actualbudget`, `archivebox`, `changedetection`, `ddclient`, `filebrowser`, `fmd`, `gatus`, `homebox`, `joplin`, `koha`, `magicmirror`, `mail-archiver`, `mattermost`, `mealie`, `meshcentral`, `n8n`, `nextcloud`, `ntfy`, `onlyoffice`, `portainer`, `rustdesk`, `stirling-pdf`, `syncthing`, `traccar`, `unifi`, `uptimekuma`, `vaultwarden`, `watchyourlan`, `watchtower`, `wg-easy` |
|
||||
| `utilities` | `actualbudget`, `ai-gpu`, `archivebox`, `changedetection`, `ddclient`, `filebrowser`, `fmd`, `gatus`, `homebox`, `iopaint`, `joplin`, `koha`, `magicmirror`, `mail-archiver`, `mattermost`, `mealie`, `meshcentral`, `n8n`, `nextcloud`, `ntfy`, `onlyoffice`, `portainer`, `rustdesk`, `stirling-pdf`, `syncthing`, `traccar`, `unifi`, `uptimekuma`, `vaultwarden`, `watchyourlan`, `watchtower`, `wg-easy` |
|
||||
| `media` | `arm`, `audiobookshelf`, `calibre-web`, `emby`, `immich`, `jellyfin`, `lyrion` |
|
||||
| `cameras` | `frigate`, `frigate-audio`, `frigate-notify`, `sky-cam` |
|
||||
| `gaming` | `drum-rhythm-game`, `js99er`, `minecraft`, `wolf`, `wolf-pair` |
|
||||
|
||||
@@ -0,0 +1,573 @@
|
||||
#!/bin/bash
|
||||
# services/ai-gpu.sh — GPU AI stack: InvokeAI image gen + Ollama/OpenWebUI LLM + swap portal.
|
||||
# Part of the modular post-install system (sourced by setup.sh).
|
||||
#
|
||||
# Can also be run standalone on any machine:
|
||||
# sudo bash ai-gpu.sh
|
||||
# (Docker + nvidia-container-toolkit must already be installed)
|
||||
#
|
||||
# Clones https://github.com/outis1one/ai-6gb-gpu and installs three stacks:
|
||||
# image-gen/ — InvokeAI (port 9090), nvidia GPU, optimised for 6 GB VRAM
|
||||
# llm/ — Ollama (11434) + Open WebUI (3000) + SearXNG (internal)
|
||||
# portal/ — Flask app (port 8080), mounts Docker socket, hot-swaps GPU between stacks
|
||||
#
|
||||
# Because a 6 GB GPU can only run ONE stack at a time, the portal handles the swap:
|
||||
# stop the active stack, start the requested one. Stop image-gen before starting llm, and vice versa.
|
||||
|
||||
# ── Standalone bootstrap ──────────────────────────────────────────────────────
|
||||
if [[ "${BASH_SOURCE[0]}" == "${0}" ]]; then
|
||||
[[ "$(id -u)" == "0" ]] || { echo "Run with sudo: sudo bash $0"; exit 1; }
|
||||
|
||||
_SELF_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
|
||||
_COMMON="$_SELF_DIR/../lib/common.sh"
|
||||
|
||||
if [[ -f "$_COMMON" ]]; then
|
||||
source "$_COMMON"
|
||||
else
|
||||
log_info() { echo -e "\033[0;34m[INFO]\033[0m $*"; }
|
||||
log_success() { echo -e "\033[0;32m[OK]\033[0m $*"; }
|
||||
log_warning() { echo -e "\033[1;33m[WARN]\033[0m $*"; }
|
||||
log_error() { echo -e "\033[0;31m[ERROR]\033[0m $*" >&2; }
|
||||
|
||||
require_docker() {
|
||||
command -v docker &>/dev/null || {
|
||||
log_error "Docker not found. Install it first:"
|
||||
log_error " curl -fsSL https://get.docker.com | sudo sh"
|
||||
return 1
|
||||
}
|
||||
docker compose version &>/dev/null || {
|
||||
log_error "Docker Compose plugin missing:"
|
||||
log_error " sudo apt-get install -y docker-compose-plugin"
|
||||
return 1
|
||||
}
|
||||
}
|
||||
|
||||
ensure_docker_dir_ownership() {
|
||||
chown -R "$ACTUAL_USER:$ACTUAL_USER" "$@" 2>/dev/null || true
|
||||
}
|
||||
|
||||
prompt_text() {
|
||||
local _q="$1" _def="$2" _var="$3" _r
|
||||
[[ "${UNATTENDED:-false}" == "true" ]] && { eval "$_var='$_def'"; return; }
|
||||
read -r -p " $_q " _r
|
||||
eval "$_var='${_r:-$_def}'"
|
||||
}
|
||||
|
||||
prompt_yn() {
|
||||
local _q="$1" _def="$2" _var="$3" _r
|
||||
[[ "${UNATTENDED:-false}" == "true" ]] && { eval "$_var='$_def'"; return; }
|
||||
read -r -p " $_q " _r
|
||||
eval "$_var='${_r:-$_def}'"
|
||||
}
|
||||
|
||||
configure_caddy_for_service() {
|
||||
local _name="$1" _upstream="$2" _subdomain="$3" _extra="${4:-}"
|
||||
local _caddy_dir="$DOCKER_DIR/caddy"
|
||||
local _caddyfile="$_caddy_dir/Caddyfile"
|
||||
local _display_port="${_upstream##*:}"
|
||||
|
||||
local _mode="none"
|
||||
[[ -d "$_caddy_dir" ]] && _mode="local"
|
||||
[[ -n "${CADDY_REMOTE_HOST:-}" ]] && [[ "$_mode" != "local" ]] && _mode="remote"
|
||||
[[ "$_mode" == "none" ]] && {
|
||||
log_info "Access $_name directly on port $_display_port."
|
||||
return 0
|
||||
}
|
||||
|
||||
echo ""
|
||||
local _do_caddy=""
|
||||
if [[ "$_mode" == "remote" ]]; then
|
||||
log_info "Remote Caddy configured (${CADDY_REMOTE_HOST})."
|
||||
log_info "A snippet file will be saved to ~/docker/caddy-snippets/."
|
||||
fi
|
||||
read -r -p " Configure Caddy reverse proxy for $_name? [y/N]: " _do_caddy
|
||||
[[ "${_do_caddy,,}" == "y" ]] || {
|
||||
log_info "Skipping — access at: http://localhost:$_display_port"
|
||||
return 0
|
||||
}
|
||||
|
||||
local _default_domain=""
|
||||
if [[ -n "${SITE_DOMAIN:-}" ]] && [[ "$SITE_DOMAIN" != "example.com" ]]; then
|
||||
_default_domain="${_subdomain}.${SITE_DOMAIN}"
|
||||
log_info "Default: $_default_domain"
|
||||
fi
|
||||
local _domain=""
|
||||
read -r -p " Domain [${_default_domain:-required}]: " _domain
|
||||
_domain="${_domain:-$_default_domain}"
|
||||
[[ -n "$_domain" ]] || { log_warning "No domain entered — skipping Caddy."; return 0; }
|
||||
|
||||
local _block_upstream="$_upstream"
|
||||
if [[ "$_mode" == "remote" ]]; then
|
||||
_block_upstream="${CADDY_REMOTE_HOST}:${_display_port}"
|
||||
fi
|
||||
|
||||
local _site_block
|
||||
_site_block="$(cat << CBLOCK
|
||||
|
||||
# $_name
|
||||
${_domain} {
|
||||
reverse_proxy ${_block_upstream}
|
||||
|
||||
header {
|
||||
Strict-Transport-Security "max-age=31536000; includeSubDomains; preload"
|
||||
X-Content-Type-Options "nosniff"
|
||||
X-Frame-Options "SAMEORIGIN"
|
||||
Referrer-Policy "strict-origin-when-cross-origin"
|
||||
}
|
||||
|
||||
log {
|
||||
output file /var/log/caddy/${_domain}.log
|
||||
format json
|
||||
}
|
||||
${_extra}
|
||||
}
|
||||
CBLOCK
|
||||
)"
|
||||
|
||||
if [[ "$_mode" == "local" ]]; then
|
||||
if [[ -f "$_caddyfile" ]]; then
|
||||
local _bk="$_caddy_dir/Caddyfile.backup.$(date +%Y%m%d-%H%M%S)"
|
||||
cp "$_caddyfile" "$_bk"
|
||||
log_info "Backed up Caddyfile to $(basename "$_bk")"
|
||||
else
|
||||
touch "$_caddyfile"
|
||||
fi
|
||||
|
||||
if grep -q "^${_domain}" "$_caddyfile" 2>/dev/null; then
|
||||
log_warning "$_domain already in Caddyfile"
|
||||
local _ow=""
|
||||
read -r -p " Overwrite? [y/N]: " _ow
|
||||
[[ "${_ow,,}" == "y" ]] || { log_info "Keeping existing entry."; return 0; }
|
||||
sed -i "/^${_domain}/,/^}/d" "$_caddyfile"
|
||||
fi
|
||||
|
||||
printf '%s\n' "$_site_block" >> "$_caddyfile"
|
||||
log_success "Added $_domain to Caddyfile"
|
||||
docker exec caddy caddy fmt --overwrite /etc/caddy/Caddyfile 2>/dev/null || true
|
||||
if docker exec caddy caddy reload --config /etc/caddy/Caddyfile 2>/dev/null; then
|
||||
log_success "$_name accessible at: https://$_domain"
|
||||
else
|
||||
log_warning "Reload failed — check: docker logs caddy"
|
||||
log_info "Manual reload: docker exec caddy caddy reload --config /etc/caddy/Caddyfile"
|
||||
fi
|
||||
else
|
||||
local _snippet_dir="$DOCKER_DIR/caddy-snippets"
|
||||
local _snippet_file="$_snippet_dir/${_subdomain}.caddy"
|
||||
mkdir -p "$_snippet_dir"
|
||||
printf '%s\n' "$_site_block" > "$_snippet_file"
|
||||
chown "$ACTUAL_USER:$ACTUAL_USER" "$_snippet_file" 2>/dev/null || true
|
||||
log_success "Snippet saved: $_snippet_file"
|
||||
log_info "Copy to Caddy machine:"
|
||||
log_info " scp $_snippet_file caddy-host:~/caddy-snippets/"
|
||||
log_info " rsync -av $_snippet_dir/ caddy-host:~/caddy-snippets/ (all at once)"
|
||||
fi
|
||||
}
|
||||
|
||||
write_readme() {
|
||||
local _dir="$1"
|
||||
mkdir -p "$_dir"
|
||||
[[ "${DRY_RUN:-false}" == "true" ]] && return 0
|
||||
cat > "$_dir/README.md"
|
||||
}
|
||||
|
||||
generate_password() {
|
||||
local _len="${1:-32}"
|
||||
tr -dc 'A-Za-z0-9' < /dev/urandom | head -c "$_len"
|
||||
echo
|
||||
}
|
||||
fi
|
||||
|
||||
ACTUAL_USER="${ACTUAL_USER:-${SUDO_USER:-$USER}}"
|
||||
ACTUAL_HOME="$(getent passwd "$ACTUAL_USER" 2>/dev/null | cut -d: -f6 || echo "${HOME:-/root}")"
|
||||
DOCKER_DIR="${DOCKER_DIR:-$ACTUAL_HOME/docker}"
|
||||
DRY_RUN="${DRY_RUN:-false}"
|
||||
UNATTENDED="${UNATTENDED:-false}"
|
||||
SITE_TZ="${SITE_TZ:-$(cat /etc/timezone 2>/dev/null || echo UTC)}"
|
||||
SITE_DOMAIN="${SITE_DOMAIN:-example.com}"
|
||||
SITE_CADDY_NET="${SITE_CADDY_NET:-caddy_net}"
|
||||
CADDY_REMOTE_HOST="${CADDY_REMOTE_HOST:-}"
|
||||
|
||||
register_service() { :; }
|
||||
_RUN_STANDALONE=1
|
||||
fi
|
||||
# ─────────────────────────────────────────────────────────────────────────────
|
||||
|
||||
register_service ai-gpu utilities "GPU AI stack — InvokeAI image gen + Ollama/OpenWebUI LLM (6 GB VRAM)" 9090
|
||||
|
||||
install_ai_gpu() {
|
||||
require_docker || return 1
|
||||
log_info "Installing AI GPU stack (InvokeAI + Ollama/OpenWebUI + portal)..."
|
||||
log_info "Requires: nvidia GPU with 6 GB+ VRAM, nvidia-container-toolkit installed."
|
||||
|
||||
local AI_DIR="$DOCKER_DIR/ai-gpu"
|
||||
local REPO_URL="https://github.com/outis1one/ai-6gb-gpu.git"
|
||||
local REPO_DIR="$AI_DIR/src"
|
||||
|
||||
if [ "$DRY_RUN" = true ]; then
|
||||
echo "[DRY-RUN] Would clone $REPO_URL to $REPO_DIR"
|
||||
echo "[DRY-RUN] Would create stacks: image-gen (InvokeAI:9090), llm (Ollama:11434 + OpenWebUI:3000), portal (8080)"
|
||||
echo "[DRY-RUN] Would prompt for Ollama and InvokeAI model selection"
|
||||
echo "[DRY-RUN] Would auto-pull selected Ollama models after LLM stack starts"
|
||||
echo "[DRY-RUN] Would queue InvokeAI starter model via REST API"
|
||||
return 0
|
||||
fi
|
||||
|
||||
# ── Timezone ──────────────────────────────────────────────────────────────
|
||||
local TZ_VAL="${SITE_TZ:-UTC}"
|
||||
prompt_text "Timezone (e.g. America/New_York) [$TZ_VAL]:" "$TZ_VAL" TZ_VAL
|
||||
TZ_VAL="${TZ_VAL:-UTC}"
|
||||
|
||||
# ── Ollama model selection ────────────────────────────────────────────────
|
||||
echo ""
|
||||
log_info "Ollama LLM models — select which to download (enter numbers separated by spaces):"
|
||||
log_info "All models are quantized (Q4_K_M) and run comfortably on 6 GB VRAM."
|
||||
echo ""
|
||||
log_info " 1) llama3.2:3b ~2.0 GB Fast general chat. Great all-rounder. ← Recommended"
|
||||
log_info " 2) llama3.2:1b ~1.3 GB Ultra-fast. Light tasks, low latency."
|
||||
log_info " 3) qwen2.5:7b ~4.7 GB Top code + math model. Strong reasoning."
|
||||
log_info " 4) mistral:7b ~4.1 GB Solid all-rounder. Good at instruction follow."
|
||||
log_info " 5) phi4-mini ~2.5 GB Microsoft Phi-4 mini. Excellent for coding."
|
||||
log_info " 6) gemma3:4b ~2.5 GB Google Gemma 3. Well-rounded, multilingual."
|
||||
log_info " 7) deepseek-r1:7b ~4.7 GB Strong reasoning and math. Think-step model."
|
||||
log_info " 8) nomic-embed-text ~274 MB Embedding model — enables RAG/doc search."
|
||||
log_info " Recommended to add alongside a chat model."
|
||||
echo ""
|
||||
log_info " Example: '1 8' pulls llama3.2:3b + nomic-embed-text"
|
||||
log_info " Enter '0' or leave blank to skip and pull models manually later."
|
||||
echo ""
|
||||
|
||||
local OLLAMA_CHOICES=""
|
||||
prompt_text "Models to download [1 8]:" "1 8" OLLAMA_CHOICES
|
||||
|
||||
declare -a OLLAMA_MODELS=()
|
||||
for _n in $OLLAMA_CHOICES; do
|
||||
case "$_n" in
|
||||
1) OLLAMA_MODELS+=("llama3.2:3b") ;;
|
||||
2) OLLAMA_MODELS+=("llama3.2:1b") ;;
|
||||
3) OLLAMA_MODELS+=("qwen2.5:7b") ;;
|
||||
4) OLLAMA_MODELS+=("mistral:7b") ;;
|
||||
5) OLLAMA_MODELS+=("phi4-mini") ;;
|
||||
6) OLLAMA_MODELS+=("gemma3:4b") ;;
|
||||
7) OLLAMA_MODELS+=("deepseek-r1:7b") ;;
|
||||
8) OLLAMA_MODELS+=("nomic-embed-text") ;;
|
||||
esac
|
||||
done
|
||||
|
||||
# ── InvokeAI model selection ──────────────────────────────────────────────
|
||||
echo ""
|
||||
log_info "InvokeAI image generation models (for 6 GB VRAM with partial GPU offload):"
|
||||
log_info "InvokeAI uses VRAM=3 GB + 8 GB RAM cache, so all models below work on 6 GB."
|
||||
echo ""
|
||||
log_info " 1) stabilityai/stable-diffusion-v1-5 ~4 GB SD 1.5 — fast, huge style/LoRA library."
|
||||
log_info " Best starting model for most uses."
|
||||
log_info " 2) stabilityai/sdxl-turbo ~7 GB SDXL Turbo — 4-step generation."
|
||||
log_info " Fast, high quality, slightly slower on 6 GB."
|
||||
log_info " 3) stabilityai/stable-diffusion-xl-base-1.0"
|
||||
log_info " ~7 GB SDXL base — best quality at 1024px."
|
||||
log_info " Slowest due to RAM offload on 6 GB."
|
||||
log_info " 4) Skip — install models via the Model Manager at http://localhost:9090"
|
||||
echo ""
|
||||
log_info " Tip: SD 1.5 (choice 1) is fastest and most compatible. Start here."
|
||||
log_info " HuggingFace token: required for some gated models (free at huggingface.co/settings/tokens)"
|
||||
echo ""
|
||||
|
||||
local INVOKE_CHOICE=""
|
||||
prompt_text "InvokeAI starter model [1]:" "1" INVOKE_CHOICE
|
||||
|
||||
local INVOKE_MODEL_SOURCE=""
|
||||
local INVOKE_MODEL_NAME=""
|
||||
case "$INVOKE_CHOICE" in
|
||||
2) INVOKE_MODEL_SOURCE="stabilityai/sdxl-turbo"
|
||||
INVOKE_MODEL_NAME="SDXL Turbo" ;;
|
||||
3) INVOKE_MODEL_SOURCE="stabilityai/stable-diffusion-xl-base-1.0"
|
||||
INVOKE_MODEL_NAME="SDXL Base" ;;
|
||||
4) INVOKE_MODEL_SOURCE=""
|
||||
INVOKE_MODEL_NAME="" ;;
|
||||
*) INVOKE_MODEL_SOURCE="stabilityai/stable-diffusion-v1-5"
|
||||
INVOKE_MODEL_NAME="SD 1.5" ;;
|
||||
esac
|
||||
|
||||
local HF_TOKEN=""
|
||||
if [ -n "$INVOKE_MODEL_SOURCE" ]; then
|
||||
prompt_text "HuggingFace token (optional — needed for gated models, enter to skip):" "" HF_TOKEN
|
||||
fi
|
||||
|
||||
# ── Clone / update repo ───────────────────────────────────────────────────
|
||||
mkdir -p "$AI_DIR"
|
||||
if [ -d "$REPO_DIR/.git" ]; then
|
||||
log_info "Updating ai-6gb-gpu repo..."
|
||||
git -C "$REPO_DIR" pull --ff-only 2>/dev/null \
|
||||
&& log_success "Repo updated" \
|
||||
|| log_warning "Could not pull latest — using existing version"
|
||||
else
|
||||
log_info "Cloning ai-6gb-gpu repo..."
|
||||
git clone --depth 1 "$REPO_URL" "$REPO_DIR" \
|
||||
|| { log_error "Clone failed — check network and git access"; return 1; }
|
||||
fi
|
||||
|
||||
# ── Image-gen stack (InvokeAI) ────────────────────────────────────────────
|
||||
local IMAGE_GEN_DIR="$AI_DIR/image-gen"
|
||||
mkdir -p "$IMAGE_GEN_DIR"
|
||||
if [ -d "$REPO_DIR/ai-image-gen" ]; then
|
||||
cp -rn "$REPO_DIR/ai-image-gen/." "$IMAGE_GEN_DIR/" 2>/dev/null || true
|
||||
find "$IMAGE_GEN_DIR" -name "docker-compose.yml" -exec \
|
||||
sed -i "s|America/New_York|$TZ_VAL|g" {} \;
|
||||
fi
|
||||
|
||||
cat > "$IMAGE_GEN_DIR/.env" << IMGENV
|
||||
# InvokeAI — image generation
|
||||
TZ=${TZ_VAL}
|
||||
# VRAM cap: 3 GB leaves headroom on a 6 GB card; remaining model layers go to RAM
|
||||
INVOKEAI_vram=3
|
||||
# RAM cache size for model layer offload
|
||||
INVOKEAI_ram=8
|
||||
${HF_TOKEN:+HUGGING_FACE_HUB_TOKEN=${HF_TOKEN}}
|
||||
CADDY_NET=${SITE_CADDY_NET}
|
||||
IMGENV
|
||||
chmod 600 "$IMAGE_GEN_DIR/.env"
|
||||
|
||||
# ── LLM stack (Ollama + Open WebUI + SearXNG) ─────────────────────────────
|
||||
local LLM_DIR="$AI_DIR/llm"
|
||||
mkdir -p "$LLM_DIR"
|
||||
if [ -d "$REPO_DIR/ai-llm" ]; then
|
||||
cp -rn "$REPO_DIR/ai-llm/." "$LLM_DIR/" 2>/dev/null || true
|
||||
find "$LLM_DIR" -name "docker-compose.yml" -exec \
|
||||
sed -i "s|America/New_York|$TZ_VAL|g" {} \;
|
||||
fi
|
||||
|
||||
local WEBUI_SECRET
|
||||
WEBUI_SECRET="$(generate_password 32)"
|
||||
|
||||
cat > "$LLM_DIR/.env" << LLMENV
|
||||
# Ollama + Open WebUI + SearXNG
|
||||
TZ=${TZ_VAL}
|
||||
WEBUI_SECRET_KEY=${WEBUI_SECRET}
|
||||
# Open WebUI: enable SearXNG for web search in chats
|
||||
ENABLE_RAG_WEB_SEARCH=true
|
||||
RAG_WEB_SEARCH_ENGINE=searxng
|
||||
SEARXNG_QUERY_URL=http://searxng:8080/search?q=<query>&format=json
|
||||
CADDY_NET=${SITE_CADDY_NET}
|
||||
LLMENV
|
||||
chmod 600 "$LLM_DIR/.env"
|
||||
|
||||
# ── Portal stack (Flask GPU swap controller) ──────────────────────────────
|
||||
local PORTAL_DIR="$AI_DIR/portal"
|
||||
mkdir -p "$PORTAL_DIR"
|
||||
if [ -d "$REPO_DIR/ai-portal" ]; then
|
||||
cp -rn "$REPO_DIR/ai-portal/." "$PORTAL_DIR/" 2>/dev/null || true
|
||||
if [ -f "$PORTAL_DIR/docker-compose.yml" ]; then
|
||||
sed -i \
|
||||
"s|/home/[^/]*/docker:|${ACTUAL_HOME}/docker:|g" \
|
||||
"$PORTAL_DIR/docker-compose.yml"
|
||||
sed -i "s|America/New_York|$TZ_VAL|g" "$PORTAL_DIR/docker-compose.yml"
|
||||
fi
|
||||
fi
|
||||
|
||||
cat > "$PORTAL_DIR/.env" << PORTALENV
|
||||
# AI Portal — GPU stack swap controller
|
||||
TZ=${TZ_VAL}
|
||||
# Paths inside the container (/docker maps to ${ACTUAL_HOME}/docker via volume mount)
|
||||
IMAGE_STACK=/docker/ai-gpu/image-gen
|
||||
LLM_STACK=/docker/ai-gpu/llm
|
||||
CADDY_NET=${SITE_CADDY_NET}
|
||||
PORTALENV
|
||||
chmod 600 "$PORTAL_DIR/.env"
|
||||
|
||||
ensure_docker_dir_ownership "$AI_DIR"
|
||||
|
||||
echo ""
|
||||
log_success "AI GPU stacks configured under $AI_DIR"
|
||||
log_warning "Only ONE GPU stack can run at a time on a 6 GB card."
|
||||
log_info "Use the portal (port 8080) to hot-swap between image-gen and llm."
|
||||
echo ""
|
||||
|
||||
# ── Caddy ─────────────────────────────────────────────────────────────────
|
||||
configure_caddy_for_service "AI Portal" "ai-portal:8080" "localai"
|
||||
configure_caddy_for_service "InvokeAI" "invokeai:9090" "images"
|
||||
|
||||
# ── README ────────────────────────────────────────────────────────────────
|
||||
write_readme "$AI_DIR" << MD
|
||||
# AI GPU Stack
|
||||
|
||||
Three Docker stacks optimised for a 6 GB VRAM nvidia GPU.
|
||||
Source: https://github.com/outis1one/ai-6gb-gpu
|
||||
|
||||
## Stacks
|
||||
|
||||
| Stack | Service | Port | Notes |
|
||||
|-------|---------|------|-------|
|
||||
| \`image-gen/\` | InvokeAI | 9090 | Image generation (SD 1.5, SDXL, Flux…) |
|
||||
| \`llm/\` | Ollama | 11434 | LLM inference engine |
|
||||
| \`llm/\` | Open WebUI | 3000 | Chat UI — models, RAG, web search |
|
||||
| \`llm/\` | SearXNG | internal | Web search backend for RAG in OpenWebUI |
|
||||
| \`portal/\` | AI Portal | 8080 | GPU swap controller — start/stop stacks |
|
||||
|
||||
## GPU time-sharing (important)
|
||||
|
||||
A 6 GB GPU can only run one AI stack at a time.
|
||||
Use the portal at http://localhost:8080 to swap.
|
||||
|
||||
Manual swap:
|
||||
\`\`\`bash
|
||||
docker compose -f $AI_DIR/llm/docker-compose.yml down
|
||||
docker compose -f $AI_DIR/image-gen/docker-compose.yml up -d
|
||||
\`\`\`
|
||||
|
||||
## InvokeAI — add more models
|
||||
|
||||
Models installed at setup are in the Model Manager. To add more:
|
||||
1. Open http://localhost:9090 → Model Manager → Add Model
|
||||
2. Paste a HuggingFace repo ID (e.g. \`stabilityai/stable-diffusion-2-1\`)
|
||||
3. Or import a local .safetensors file
|
||||
|
||||
For gated models, add \`HUGGING_FACE_HUB_TOKEN=xxx\` to \`image-gen/.env\`.
|
||||
|
||||
Recommended models for 6 GB (with partial GPU offload):
|
||||
|
||||
| Model | Source | Notes |
|
||||
|-------|--------|-------|
|
||||
| SD 1.5 | \`stabilityai/stable-diffusion-v1-5\` | Fast, huge LoRA library |
|
||||
| SDXL Turbo | \`stabilityai/sdxl-turbo\` | 4-step, good quality |
|
||||
| SDXL Base | \`stabilityai/stable-diffusion-xl-base-1.0\` | Best quality, slower |
|
||||
| SD 2.1 | \`stabilityai/stable-diffusion-2-1\` | Good mid-size choice |
|
||||
|
||||
## Ollama — add more models
|
||||
|
||||
\`\`\`bash
|
||||
# Pull any model while llm stack is running
|
||||
docker exec ollama ollama pull llama3.2:3b
|
||||
docker exec ollama ollama pull nomic-embed-text # RAG embeddings
|
||||
docker exec ollama ollama list # see installed models
|
||||
\`\`\`
|
||||
|
||||
Browse models at: https://ollama.com/library
|
||||
For 6 GB cards, stick to 7B or smaller with Q4_K_M quantisation (~4.5 GB).
|
||||
|
||||
## Open WebUI — first login
|
||||
|
||||
Open http://localhost:3000 and create your admin account on first visit.
|
||||
Models pulled into Ollama appear automatically in the model dropdown.
|
||||
Enable web search: Settings → Admin → Web Search (SearXNG is pre-configured).
|
||||
|
||||
## Manage individual stacks
|
||||
\`\`\`bash
|
||||
cd $AI_DIR/image-gen && docker compose up -d # start InvokeAI
|
||||
cd $AI_DIR/llm && docker compose up -d # start Ollama + OpenWebUI
|
||||
cd $AI_DIR/portal && docker compose up -d # start portal
|
||||
docker compose -f $AI_DIR/image-gen/docker-compose.yml logs -f invokeai
|
||||
docker compose -f $AI_DIR/llm/docker-compose.yml logs -f openwebui
|
||||
\`\`\`
|
||||
|
||||
## Update
|
||||
\`\`\`bash
|
||||
cd $REPO_DIR && git pull
|
||||
cd $AI_DIR/image-gen && docker compose pull && docker compose up -d
|
||||
cd $AI_DIR/llm && docker compose pull && docker compose up -d
|
||||
cd $AI_DIR/portal && docker compose build --pull && docker compose up -d
|
||||
\`\`\`
|
||||
MD
|
||||
|
||||
# ── Start stacks + pull models ────────────────────────────────────────────
|
||||
echo ""
|
||||
log_info "What would you like to start now?"
|
||||
log_info " 1) Portal only — start the swap controller, configure the rest later"
|
||||
log_info " 2) Portal + LLM stack — start Ollama/OpenWebUI and pull selected models"
|
||||
log_info " 3) Portal + image-gen — start InvokeAI and queue the starter model download"
|
||||
log_info " 4) None — start manually later"
|
||||
echo ""
|
||||
|
||||
local START_CHOICE=""
|
||||
prompt_text "Choice [2]:" "2" START_CHOICE
|
||||
|
||||
# Always start portal if any stack is starting
|
||||
if [[ "$START_CHOICE" =~ ^[123]$ ]]; then
|
||||
docker compose -f "$PORTAL_DIR/docker-compose.yml" up -d \
|
||||
&& log_success "Portal started — http://localhost:8080" \
|
||||
|| log_warning "Portal start failed — check: docker compose -f $PORTAL_DIR/docker-compose.yml logs"
|
||||
fi
|
||||
|
||||
if [[ "$START_CHOICE" == "2" ]]; then
|
||||
# Start LLM stack
|
||||
docker compose -f "$LLM_DIR/docker-compose.yml" up -d \
|
||||
&& log_success "LLM stack started" \
|
||||
|| { log_warning "LLM stack start failed"; START_CHOICE="0"; }
|
||||
|
||||
# Pull Ollama models if any were selected
|
||||
if [ ${#OLLAMA_MODELS[@]} -gt 0 ] && [[ "$START_CHOICE" == "2" ]]; then
|
||||
log_info "Waiting for Ollama to be ready..."
|
||||
local _w=0
|
||||
while ! curl -sf "http://localhost:11434/api/version" &>/dev/null; do
|
||||
sleep 3; _w=$((_w+3))
|
||||
[[ $_w -ge 90 ]] && { log_warning "Ollama not responding after 90s — pull models manually later"; break; }
|
||||
done
|
||||
|
||||
if curl -sf "http://localhost:11434/api/version" &>/dev/null; then
|
||||
for _m in "${OLLAMA_MODELS[@]}"; do
|
||||
log_info "Pulling $_m (this may take a while)..."
|
||||
docker exec ollama ollama pull "$_m" \
|
||||
&& log_success "$_m ready" \
|
||||
|| log_warning "Pull failed for $_m — retry: docker exec ollama ollama pull $_m"
|
||||
done
|
||||
log_success "Open WebUI ready at: http://localhost:3000"
|
||||
log_info "Create your admin account on the first visit."
|
||||
fi
|
||||
fi
|
||||
fi
|
||||
|
||||
if [[ "$START_CHOICE" == "3" ]]; then
|
||||
# Start image-gen stack
|
||||
docker compose -f "$IMAGE_GEN_DIR/docker-compose.yml" up -d \
|
||||
&& log_success "InvokeAI started" \
|
||||
|| { log_warning "InvokeAI start failed — check: docker compose -f $IMAGE_GEN_DIR/docker-compose.yml logs"; START_CHOICE="0"; }
|
||||
|
||||
# Queue starter model via InvokeAI REST API
|
||||
if [ -n "$INVOKE_MODEL_SOURCE" ] && [[ "$START_CHOICE" == "3" ]]; then
|
||||
log_info "Waiting for InvokeAI to be ready (model database initialises on first start)..."
|
||||
local _w=0
|
||||
while ! curl -sf "http://localhost:9090/api/v1/app/version" &>/dev/null; do
|
||||
sleep 5; _w=$((_w+5))
|
||||
[[ $_w -ge 180 ]] && { log_warning "InvokeAI not responding after 3 min"; break; }
|
||||
done
|
||||
|
||||
if curl -sf "http://localhost:9090/api/v1/app/version" &>/dev/null; then
|
||||
log_info "Queuing $INVOKE_MODEL_NAME download..."
|
||||
local _resp
|
||||
_resp=$(curl -s -X POST "http://localhost:9090/api/v2/models/install" \
|
||||
-H "Content-Type: application/json" \
|
||||
-d "{\"source\": \"${INVOKE_MODEL_SOURCE}\"}" 2>/dev/null)
|
||||
if echo "$_resp" | grep -q '"id"'; then
|
||||
log_success "$INVOKE_MODEL_NAME queued — downloading in background"
|
||||
log_info "Track progress: http://localhost:9090 → Model Manager → In Progress"
|
||||
else
|
||||
log_warning "Could not queue via API. Install manually:"
|
||||
log_info " Open http://localhost:9090 → Model Manager → Add Model"
|
||||
log_info " Source: $INVOKE_MODEL_SOURCE"
|
||||
fi
|
||||
fi
|
||||
fi
|
||||
fi
|
||||
|
||||
if [[ "$START_CHOICE" == "4" ]] || [[ "$START_CHOICE" == "0" ]]; then
|
||||
log_info "Start when ready:"
|
||||
log_info " docker compose -f $PORTAL_DIR/docker-compose.yml up -d"
|
||||
log_info " docker compose -f $LLM_DIR/docker-compose.yml up -d"
|
||||
log_info " docker compose -f $IMAGE_GEN_DIR/docker-compose.yml up -d"
|
||||
fi
|
||||
|
||||
echo ""
|
||||
echo " Portal: http://localhost:8080 (GPU swap controller)"
|
||||
echo " InvokeAI: http://localhost:9090 (image-gen stack)"
|
||||
echo " Open WebUI: http://localhost:3000 (llm stack)"
|
||||
echo " Ollama API: http://localhost:11434 (llm stack)"
|
||||
echo " Source repo: $REPO_DIR"
|
||||
echo ""
|
||||
if [ ${#OLLAMA_MODELS[@]} -gt 0 ]; then
|
||||
echo " Ollama models queued: ${OLLAMA_MODELS[*]}"
|
||||
fi
|
||||
if [ -n "$INVOKE_MODEL_NAME" ]; then
|
||||
echo " InvokeAI starter: $INVOKE_MODEL_NAME ($INVOKE_MODEL_SOURCE)"
|
||||
fi
|
||||
echo ""
|
||||
}
|
||||
|
||||
[[ "${_RUN_STANDALONE:-0}" == 1 ]] && install_ai_gpu
|
||||
@@ -0,0 +1,475 @@
|
||||
#!/bin/bash
|
||||
# services/iopaint.sh — AI image editing: erase objects, fill regions, replace with text prompt.
|
||||
# Part of the modular post-install system (sourced by setup.sh).
|
||||
#
|
||||
# Can also be run standalone on any machine:
|
||||
# sudo bash iopaint.sh
|
||||
# (Docker must already be installed when run standalone)
|
||||
#
|
||||
# Three use cases:
|
||||
# Erase/remove — mask an object, AI fills the gap (LaMa, CPU-safe)
|
||||
# Inpaint/fill — restore damaged areas, remove watermarks (multiple models)
|
||||
# Replace — mask + text prompt → AI draws new content (PowerPaint, GPU required)
|
||||
#
|
||||
# IOPaint is local-only: it cannot call a remote GPU or InvokeAI on another machine.
|
||||
# For text-guided replacement the GPU must be on this same machine.
|
||||
# IOPaint has no built-in auth — protect with Authelia via Caddy.
|
||||
|
||||
# ── Standalone bootstrap ──────────────────────────────────────────────────────
|
||||
if [[ "${BASH_SOURCE[0]}" == "${0}" ]]; then
|
||||
[[ "$(id -u)" == "0" ]] || { echo "Run with sudo: sudo bash $0"; exit 1; }
|
||||
|
||||
_SELF_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
|
||||
_COMMON="$_SELF_DIR/../lib/common.sh"
|
||||
|
||||
if [[ -f "$_COMMON" ]]; then
|
||||
source "$_COMMON"
|
||||
else
|
||||
log_info() { echo -e "\033[0;34m[INFO]\033[0m $*"; }
|
||||
log_success() { echo -e "\033[0;32m[OK]\033[0m $*"; }
|
||||
log_warning() { echo -e "\033[1;33m[WARN]\033[0m $*"; }
|
||||
log_error() { echo -e "\033[0;31m[ERROR]\033[0m $*" >&2; }
|
||||
|
||||
require_docker() {
|
||||
command -v docker &>/dev/null || {
|
||||
log_error "Docker not found. Install it first:"
|
||||
log_error " curl -fsSL https://get.docker.com | sudo sh"
|
||||
return 1
|
||||
}
|
||||
docker compose version &>/dev/null || {
|
||||
log_error "Docker Compose plugin missing:"
|
||||
log_error " sudo apt-get install -y docker-compose-plugin"
|
||||
return 1
|
||||
}
|
||||
}
|
||||
|
||||
ensure_docker_dir_ownership() {
|
||||
chown -R "$ACTUAL_USER:$ACTUAL_USER" "$@" 2>/dev/null || true
|
||||
}
|
||||
|
||||
prompt_text() {
|
||||
local _q="$1" _def="$2" _var="$3" _r
|
||||
[[ "${UNATTENDED:-false}" == "true" ]] && { eval "$_var='$_def'"; return; }
|
||||
read -r -p " $_q " _r
|
||||
eval "$_var='${_r:-$_def}'"
|
||||
}
|
||||
|
||||
prompt_yn() {
|
||||
local _q="$1" _def="$2" _var="$3" _r
|
||||
[[ "${UNATTENDED:-false}" == "true" ]] && { eval "$_var='$_def'"; return; }
|
||||
read -r -p " $_q " _r
|
||||
eval "$_var='${_r:-$_def}'"
|
||||
}
|
||||
|
||||
configure_caddy_for_service() {
|
||||
local _name="$1" _upstream="$2" _subdomain="$3" _extra="${4:-}"
|
||||
local _caddy_dir="$DOCKER_DIR/caddy"
|
||||
local _caddyfile="$_caddy_dir/Caddyfile"
|
||||
local _display_port="${_upstream##*:}"
|
||||
|
||||
local _mode="none"
|
||||
[[ -d "$_caddy_dir" ]] && _mode="local"
|
||||
[[ -n "${CADDY_REMOTE_HOST:-}" ]] && [[ "$_mode" != "local" ]] && _mode="remote"
|
||||
[[ "$_mode" == "none" ]] && {
|
||||
log_info "Access $_name directly on port $_display_port."
|
||||
return 0
|
||||
}
|
||||
|
||||
echo ""
|
||||
local _do_caddy=""
|
||||
if [[ "$_mode" == "remote" ]]; then
|
||||
log_info "Remote Caddy configured (${CADDY_REMOTE_HOST})."
|
||||
log_info "A snippet file will be saved to ~/docker/caddy-snippets/."
|
||||
fi
|
||||
read -r -p " Configure Caddy reverse proxy for $_name? [y/N]: " _do_caddy
|
||||
[[ "${_do_caddy,,}" == "y" ]] || {
|
||||
log_info "Skipping — access at: http://localhost:$_display_port"
|
||||
return 0
|
||||
}
|
||||
|
||||
local _default_domain=""
|
||||
if [[ -n "${SITE_DOMAIN:-}" ]] && [[ "$SITE_DOMAIN" != "example.com" ]]; then
|
||||
_default_domain="${_subdomain}.${SITE_DOMAIN}"
|
||||
log_info "Default: $_default_domain"
|
||||
fi
|
||||
local _domain=""
|
||||
read -r -p " Domain [${_default_domain:-required}]: " _domain
|
||||
_domain="${_domain:-$_default_domain}"
|
||||
[[ -n "$_domain" ]] || { log_warning "No domain entered — skipping Caddy."; return 0; }
|
||||
|
||||
local _block_upstream="$_upstream"
|
||||
if [[ "$_mode" == "remote" ]]; then
|
||||
_block_upstream="${CADDY_REMOTE_HOST}:${_display_port}"
|
||||
fi
|
||||
|
||||
local _site_block
|
||||
_site_block="$(cat << CBLOCK
|
||||
|
||||
# $_name
|
||||
${_domain} {
|
||||
reverse_proxy ${_block_upstream}
|
||||
|
||||
header {
|
||||
Strict-Transport-Security "max-age=31536000; includeSubDomains; preload"
|
||||
X-Content-Type-Options "nosniff"
|
||||
X-Frame-Options "SAMEORIGIN"
|
||||
Referrer-Policy "strict-origin-when-cross-origin"
|
||||
}
|
||||
|
||||
log {
|
||||
output file /var/log/caddy/${_domain}.log
|
||||
format json
|
||||
}
|
||||
${_extra}
|
||||
}
|
||||
CBLOCK
|
||||
)"
|
||||
|
||||
if [[ "$_mode" == "local" ]]; then
|
||||
if [[ -f "$_caddyfile" ]]; then
|
||||
local _bk="$_caddy_dir/Caddyfile.backup.$(date +%Y%m%d-%H%M%S)"
|
||||
cp "$_caddyfile" "$_bk"
|
||||
log_info "Backed up Caddyfile to $(basename "$_bk")"
|
||||
else
|
||||
touch "$_caddyfile"
|
||||
fi
|
||||
|
||||
if grep -q "^${_domain}" "$_caddyfile" 2>/dev/null; then
|
||||
log_warning "$_domain already in Caddyfile"
|
||||
local _ow=""
|
||||
read -r -p " Overwrite? [y/N]: " _ow
|
||||
[[ "${_ow,,}" == "y" ]] || { log_info "Keeping existing entry."; return 0; }
|
||||
sed -i "/^${_domain}/,/^}/d" "$_caddyfile"
|
||||
fi
|
||||
|
||||
printf '%s\n' "$_site_block" >> "$_caddyfile"
|
||||
log_success "Added $_domain to Caddyfile"
|
||||
docker exec caddy caddy fmt --overwrite /etc/caddy/Caddyfile 2>/dev/null || true
|
||||
if docker exec caddy caddy reload --config /etc/caddy/Caddyfile 2>/dev/null; then
|
||||
log_success "$_name accessible at: https://$_domain"
|
||||
else
|
||||
log_warning "Reload failed — check: docker logs caddy"
|
||||
log_info "Manual reload: docker exec caddy caddy reload --config /etc/caddy/Caddyfile"
|
||||
fi
|
||||
else
|
||||
local _snippet_dir="$DOCKER_DIR/caddy-snippets"
|
||||
local _snippet_file="$_snippet_dir/${_subdomain}.caddy"
|
||||
mkdir -p "$_snippet_dir"
|
||||
printf '%s\n' "$_site_block" > "$_snippet_file"
|
||||
chown "$ACTUAL_USER:$ACTUAL_USER" "$_snippet_file" 2>/dev/null || true
|
||||
log_success "Snippet saved: $_snippet_file"
|
||||
log_info "Copy to Caddy machine:"
|
||||
log_info " scp $_snippet_file caddy-host:~/caddy-snippets/"
|
||||
log_info " rsync -av $_snippet_dir/ caddy-host:~/caddy-snippets/ (all at once)"
|
||||
fi
|
||||
}
|
||||
|
||||
write_readme() {
|
||||
local _dir="$1"
|
||||
mkdir -p "$_dir"
|
||||
[[ "${DRY_RUN:-false}" == "true" ]] && return 0
|
||||
cat > "$_dir/README.md"
|
||||
}
|
||||
fi
|
||||
|
||||
ACTUAL_USER="${ACTUAL_USER:-${SUDO_USER:-$USER}}"
|
||||
ACTUAL_HOME="$(getent passwd "$ACTUAL_USER" 2>/dev/null | cut -d: -f6 || echo "${HOME:-/root}")"
|
||||
DOCKER_DIR="${DOCKER_DIR:-$ACTUAL_HOME/docker}"
|
||||
DRY_RUN="${DRY_RUN:-false}"
|
||||
UNATTENDED="${UNATTENDED:-false}"
|
||||
SITE_TZ="${SITE_TZ:-$(cat /etc/timezone 2>/dev/null || echo UTC)}"
|
||||
SITE_DOMAIN="${SITE_DOMAIN:-example.com}"
|
||||
SITE_CADDY_NET="${SITE_CADDY_NET:-caddy_net}"
|
||||
CADDY_REMOTE_HOST="${CADDY_REMOTE_HOST:-}"
|
||||
|
||||
register_service() { :; }
|
||||
_RUN_STANDALONE=1
|
||||
fi
|
||||
# ─────────────────────────────────────────────────────────────────────────────
|
||||
|
||||
register_service iopaint utilities "AI image inpainting — erase objects, fill, restore (IOPaint)" 8100
|
||||
|
||||
install_iopaint() {
|
||||
require_docker || return 1
|
||||
log_info "Installing IOPaint..."
|
||||
|
||||
local IOPAINT_DIR="$DOCKER_DIR/iopaint"
|
||||
|
||||
if [ "$DRY_RUN" = true ]; then
|
||||
echo "[DRY-RUN] Would create $IOPAINT_DIR"
|
||||
echo "[DRY-RUN] Would prompt for model and GPU (CUDA) support"
|
||||
echo "[DRY-RUN] Would write docker-compose.yml and .env"
|
||||
echo "[DRY-RUN] Would offer Authelia SSO"
|
||||
return 0
|
||||
fi
|
||||
|
||||
mkdir -p "$IOPAINT_DIR"
|
||||
ensure_docker_dir_ownership "$IOPAINT_DIR"
|
||||
cd "$IOPAINT_DIR" || return 1
|
||||
|
||||
# ── GPU ──────────────────────────────────────────────────────────────────
|
||||
log_info "IOPaint can:"
|
||||
log_info " • Erase / remove — mask an object, AI fills the gap (works CPU-only)"
|
||||
log_info " • Inpaint / fill — restore damaged areas, remove watermarks"
|
||||
log_info " • Replace — mask + type what goes there → AI draws it (needs GPU)"
|
||||
log_info " Note: inference is always local — IOPaint cannot use a GPU on another machine."
|
||||
echo ""
|
||||
local USE_GPU=""
|
||||
prompt_yn "Enable CUDA GPU support? Requires nvidia-container-toolkit (y/n):" "n" USE_GPU
|
||||
|
||||
# ── Model selection ───────────────────────────────────────────────────────
|
||||
echo ""
|
||||
log_info "Select default model (you can switch models in the UI without restarting):"
|
||||
echo ""
|
||||
log_info " ── CPU-safe — work on any machine ─────────────────────────────────────────"
|
||||
log_info " 1) lama Erase / removal. Intelligent gap fill. ~200 MB ← Recommended"
|
||||
log_info " 2) cv2 OpenCV fill. No download, instant. Rough quality."
|
||||
log_info " 3) zits Portrait & face restoration. ~200 MB."
|
||||
log_info " 4) manga Comic/manga text bubble removal. ~100 MB."
|
||||
echo ""
|
||||
if [[ "$USE_GPU" =~ ^[Yy]$ ]]; then
|
||||
log_info " ── GPU-accelerated fill ───────────────────────────────────────────────────"
|
||||
log_info " 5) migan MiGAN: fast GPU inpainting. ~50 MB."
|
||||
log_info " 6) fcf FcF: high-quality contextual fill. ~600 MB."
|
||||
log_info " 7) mat MAT: large missing region fill. ~300 MB."
|
||||
log_info " 8) ldm LDM: latent diffusion texture fill. ~1.2 GB."
|
||||
echo ""
|
||||
log_info " ── Text-guided REPLACEMENT (GPU + Stable Diffusion) ───────────────────────"
|
||||
log_info " 9) Sanster/PowerPaint-V2-filling"
|
||||
log_info " Mask + type 'a red barn' → AI draws it. ~4 GB."
|
||||
log_info " Modes: text-guided, shape-guided, erase, outpaint."
|
||||
log_info " 10) runwayml/stable-diffusion-inpainting"
|
||||
log_info " Classic SD 1.5 inpaint. Huge LoRA/style library. ~4 GB."
|
||||
echo ""
|
||||
fi
|
||||
|
||||
local MODEL_NUM=""
|
||||
prompt_text "Model choice [1=lama]:" "1" MODEL_NUM
|
||||
|
||||
local IOPAINT_MODEL="lama"
|
||||
case "$MODEL_NUM" in
|
||||
2) IOPAINT_MODEL="cv2" ;;
|
||||
3) IOPAINT_MODEL="zits" ;;
|
||||
4) IOPAINT_MODEL="manga" ;;
|
||||
5) IOPAINT_MODEL="migan" ;;
|
||||
6) IOPAINT_MODEL="fcf" ;;
|
||||
7) IOPAINT_MODEL="mat" ;;
|
||||
8) IOPAINT_MODEL="ldm" ;;
|
||||
9) IOPAINT_MODEL="Sanster/PowerPaint-V2-filling" ;;
|
||||
10) IOPAINT_MODEL="runwayml/stable-diffusion-inpainting" ;;
|
||||
*) IOPAINT_MODEL="lama" ;;
|
||||
esac
|
||||
|
||||
local DEVICE_VAL="cpu"
|
||||
[[ "$USE_GPU" =~ ^[Yy]$ ]] && DEVICE_VAL="cuda"
|
||||
|
||||
# ── docker-compose.yml ────────────────────────────────────────────────────
|
||||
# MODEL and DEVICE come from .env — change them there and restart to switch.
|
||||
# Volume ./models:/root/.cache persists ALL model caches:
|
||||
# /root/.cache/torch/hub/checkpoints/ (LaMa, CV2, ZITS, etc.)
|
||||
# /root/.cache/huggingface/ (SD, PowerPaint, LDM, etc.)
|
||||
if [[ "$USE_GPU" =~ ^[Yy]$ ]]; then
|
||||
cat > docker-compose.yml << 'IOPAINT_GPU'
|
||||
name: iopaint
|
||||
|
||||
services:
|
||||
iopaint:
|
||||
image: cwq1913/iopaint:latest
|
||||
container_name: iopaint
|
||||
hostname: iopaint
|
||||
restart: unless-stopped
|
||||
command: >-
|
||||
iopaint start
|
||||
--model=${MODEL:-lama}
|
||||
--device=${DEVICE:-cuda}
|
||||
--port=8080
|
||||
--host=0.0.0.0
|
||||
ports:
|
||||
- "8100:8080"
|
||||
env_file: .env
|
||||
volumes:
|
||||
- ./models:/root/.cache
|
||||
- ./input:/app/input
|
||||
- ./output:/app/output
|
||||
deploy:
|
||||
resources:
|
||||
reservations:
|
||||
devices:
|
||||
- driver: nvidia
|
||||
count: 1
|
||||
capabilities: [gpu]
|
||||
networks:
|
||||
- caddy_net
|
||||
|
||||
networks:
|
||||
caddy_net:
|
||||
external: true
|
||||
name: ${CADDY_NET:-caddy_net}
|
||||
IOPAINT_GPU
|
||||
else
|
||||
cat > docker-compose.yml << 'IOPAINT_CPU'
|
||||
name: iopaint
|
||||
|
||||
services:
|
||||
iopaint:
|
||||
image: cwq1913/iopaint:latest
|
||||
container_name: iopaint
|
||||
hostname: iopaint
|
||||
restart: unless-stopped
|
||||
command: >-
|
||||
iopaint start
|
||||
--model=${MODEL:-lama}
|
||||
--device=${DEVICE:-cpu}
|
||||
--port=8080
|
||||
--host=0.0.0.0
|
||||
ports:
|
||||
- "8100:8080"
|
||||
env_file: .env
|
||||
volumes:
|
||||
- ./models:/root/.cache
|
||||
- ./input:/app/input
|
||||
- ./output:/app/output
|
||||
networks:
|
||||
- caddy_net
|
||||
|
||||
networks:
|
||||
caddy_net:
|
||||
external: true
|
||||
name: ${CADDY_NET:-caddy_net}
|
||||
IOPAINT_CPU
|
||||
fi
|
||||
|
||||
# ── .env ─────────────────────────────────────────────────────────────────
|
||||
cat > .env << IOPAINT_ENV
|
||||
# IOPaint — change MODEL and restart to switch (no need to edit docker-compose.yml)
|
||||
|
||||
# Current model (set during install — see README for full model list)
|
||||
MODEL=${IOPAINT_MODEL}
|
||||
|
||||
# Device: cpu or cuda
|
||||
# For GPU: also requires the deploy: block in docker-compose.yml
|
||||
DEVICE=${DEVICE_VAL}
|
||||
|
||||
# Caddy network
|
||||
CADDY_NET=${SITE_CADDY_NET}
|
||||
IOPAINT_ENV
|
||||
chmod 600 .env
|
||||
|
||||
mkdir -p models input output
|
||||
chown -R "$ACTUAL_USER:$ACTUAL_USER" "$IOPAINT_DIR"
|
||||
|
||||
echo ""
|
||||
log_success "IOPaint configured — model: $IOPAINT_MODEL | device: $DEVICE_VAL"
|
||||
if [[ "$IOPAINT_MODEL" == *"PowerPaint"* ]] || [[ "$IOPAINT_MODEL" == *"stable-diffusion"* ]]; then
|
||||
log_info "SD-based model selected (~4 GB). It downloads from HuggingFace on first start."
|
||||
log_info "If the download fails, try: HF_TOKEN=your_token docker compose up -d"
|
||||
else
|
||||
log_info "Model downloads automatically on first start (LaMa ~200 MB)."
|
||||
fi
|
||||
log_info "Switch models any time by editing MODEL= in .env and restarting."
|
||||
|
||||
# No built-in auth — offer Authelia SSO protection
|
||||
local EXTRA_BLOCK=""
|
||||
if [ -d "$DOCKER_DIR/authelia" ]; then
|
||||
local _use_auth=""
|
||||
prompt_yn "Protect IOPaint with Authelia SSO? (y/n):" "y" _use_auth
|
||||
[[ "$_use_auth" =~ ^[Yy]$ ]] && EXTRA_BLOCK=" import authelia"
|
||||
fi
|
||||
|
||||
configure_caddy_for_service "IOPaint" "iopaint:8080" "inpaint" "$EXTRA_BLOCK"
|
||||
|
||||
write_readme "$IOPAINT_DIR" << 'MD'
|
||||
# IOPaint
|
||||
|
||||
AI-powered image editing:
|
||||
- **Erase / remove** — mask an object, AI fills the background (LaMa, works CPU-only)
|
||||
- **Inpaint / restore** — fix damaged areas, remove watermarks
|
||||
- **Replace with AI** — mask something + type what goes there → AI draws it (PowerPaint, GPU)
|
||||
|
||||
Note: IOPaint is **local only** — all inference runs on this machine.
|
||||
For text-guided replacement a CUDA GPU on this machine is required.
|
||||
|
||||
## Access
|
||||
- URL: http://localhost:8100
|
||||
- No built-in login — protect via Authelia SSO if exposed
|
||||
|
||||
## Switching models
|
||||
Edit `MODEL=` in `.env` and restart — no need to touch `docker-compose.yml`:
|
||||
```bash
|
||||
cd ~/docker/iopaint
|
||||
nano .env # change MODEL= line
|
||||
docker compose restart
|
||||
```
|
||||
|
||||
## Model reference
|
||||
|
||||
| # | Model | Type | Size | Best for |
|
||||
|---|-------|------|------|---------|
|
||||
| 1 | `lama` | CPU-safe | ~200 MB | **Object erase/removal** (default) |
|
||||
| 2 | `cv2` | CPU-safe | built-in | Basic fill, no download |
|
||||
| 3 | `zits` | CPU-safe | ~200 MB | Portrait & face restoration |
|
||||
| 4 | `manga` | CPU-safe | ~100 MB | Comic/manga text bubble removal |
|
||||
| 5 | `migan` | GPU | ~50 MB | Fast GPU inpainting |
|
||||
| 6 | `fcf` | GPU | ~600 MB | High-quality contextual fill |
|
||||
| 7 | `mat` | GPU | ~300 MB | Large missing region fill |
|
||||
| 8 | `ldm` | GPU | ~1.2 GB | Latent diffusion texture fill |
|
||||
| 9 | `Sanster/PowerPaint-V2-filling` | GPU+SD | ~4 GB | **Text-guided replacement** |
|
||||
| 10 | `runwayml/stable-diffusion-inpainting` | GPU+SD | ~4 GB | SD 1.5 inpaint, large LoRA library |
|
||||
|
||||
SD-based models (9, 10) download from HuggingFace on first start.
|
||||
If a gated model needs a token: add `HF_TOKEN=xxx` to `.env`.
|
||||
|
||||
## How to use
|
||||
1. Open http://localhost:8100
|
||||
2. Upload an image (or drag & drop)
|
||||
3. Paint a mask over the area to change
|
||||
4. For erase models: click Run → gap fills automatically
|
||||
5. For SD models (PowerPaint): type a text prompt → AI draws it into the masked area
|
||||
|
||||
## GPU acceleration
|
||||
Requires `nvidia-container-toolkit`. The GPU compose adds a `deploy:` block.
|
||||
Re-run the installer with GPU=y to regenerate docker-compose.yml, or manually add:
|
||||
```yaml
|
||||
deploy:
|
||||
resources:
|
||||
reservations:
|
||||
devices:
|
||||
- driver: nvidia
|
||||
count: 1
|
||||
capabilities: [gpu]
|
||||
```
|
||||
Then change `DEVICE=cuda` in `.env` and restart.
|
||||
|
||||
## Manage
|
||||
```bash
|
||||
cd ~/docker/iopaint
|
||||
docker compose up -d
|
||||
docker compose down
|
||||
docker compose logs -f
|
||||
docker compose pull && docker compose down && docker compose up -d
|
||||
```
|
||||
|
||||
## Files
|
||||
- docker-compose.yml — stack (MODEL and DEVICE come from .env)
|
||||
- .env — model and device config
|
||||
- models/ — all cached model weights (torch + HuggingFace)
|
||||
- input/, output/ — optional file staging
|
||||
MD
|
||||
|
||||
local START_IO=""
|
||||
prompt_yn "Start IOPaint now? (y/n):" "y" START_IO
|
||||
if [ "$START_IO" = "y" ] || [ "$START_IO" = "Y" ]; then
|
||||
docker compose up -d \
|
||||
&& log_success "IOPaint started — model downloads on first use" \
|
||||
|| log_warning "Start failed — check: docker compose logs"
|
||||
fi
|
||||
|
||||
echo ""
|
||||
echo " URL: http://localhost:8100"
|
||||
echo " Model: $IOPAINT_MODEL"
|
||||
echo " Device: $DEVICE_VAL"
|
||||
echo " Switch: edit MODEL= in $IOPAINT_DIR/.env and restart"
|
||||
echo ""
|
||||
}
|
||||
|
||||
[[ "${_RUN_STANDALONE:-0}" == 1 ]] && install_iopaint
|
||||
Reference in New Issue
Block a user