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iopaint, ai-gpu: interactive model selection, auto-pull, fixes

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iopaint:
- Add model selection menu (10 choices) with CPU/GPU/SD tiers and
  size/use-case descriptions shown at install time
- Fix volume mount: ./models:/root/.cache (was only /root/.cache/iopaint)
  — now persists both torch hub cache (LaMa) and HuggingFace cache (SD/PowerPaint)
- Refactor compose to use ${MODEL} and ${DEVICE} env vars so switching
  models only requires editing .env + restart, no compose file edit needed
- Add PowerPaint-V2-filling and SD 1.5 inpainting as explicit menu choices
  for text-guided object replacement
- Update header and README to document all three use cases (erase, fill, replace)
  and note that IOPaint is local-only (cannot use a remote GPU)

ai-gpu:
- Add Ollama model selection menu (8 models, multi-select with sizes/descriptions)
  defaulting to llama3.2:3b + nomic-embed-text
- Auto-pull selected Ollama models immediately after LLM stack starts
- Add InvokeAI starter model selection (SD 1.5 / SDXL Turbo / SDXL Base / skip)
- Queue InvokeAI model download via REST API (POST /api/v2/models/install)
  with fallback instructions if the API is unavailable
- Add HuggingFace token prompt; stored as HUGGING_FACE_HUB_TOKEN in image-gen .env
- Wire SearXNG into Open WebUI via ENABLE_RAG_WEB_SEARCH + SEARXNG_QUERY_URL in llm .env
- Default start choice is now 2 (portal + LLM + Ollama pull) so the stack
  is ready to use immediately after install

https://claude.ai/code/session_01JEu7LgCWXKhXo18MeYFRZp
This commit is contained in:
Claude
2026-06-09 03:57:01 +00:00
parent 5c394815b4
commit f9013287d9
2 changed files with 391 additions and 156 deletions
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services/iopaint.sh
+166 -55
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@@ -1,13 +1,18 @@
#!/bin/bash
# services/iopaint.sh — AI image inpainting: object removal, fill, restore (IOPaint + LaMa).
# 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)
#
# Runs the LaMa model (erase/fill objects) by default on CPU.
# For GPU inference set DEVICE=cuda in .env and install nvidia-container-toolkit.
# 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 ──────────────────────────────────────────────────────
@@ -192,8 +197,9 @@ install_iopaint() {
if [ "$DRY_RUN" = true ]; then
echo "[DRY-RUN] Would create $IOPAINT_DIR"
echo "[DRY-RUN] Would prompt for model and GPU (CUDA) support"
echo "[DRY-RUN] Would write docker-compose.yml and .env"
echo "[DRY-RUN] Would offer GPU (CUDA) support and Authelia SSO"
echo "[DRY-RUN] Would offer Authelia SSO"
return 0
fi
@@ -201,10 +207,67 @@ install_iopaint() {
ensure_docker_dir_ownership "$IOPAINT_DIR"
cd "$IOPAINT_DIR" || return 1
# Ask about GPU
# ── GPU ──────────────────────────────────────────────────────────────────
log_info "IOPaint can:"
log_info " • Erase / remove — mask an object, AI fills the gap (works CPU-only)"
log_info " • Inpaint / fill — restore damaged areas, remove watermarks"
log_info " • Replace — mask + type what goes there → AI draws it (needs GPU)"
log_info " Note: inference is always local — IOPaint cannot use a GPU on another machine."
echo ""
local USE_GPU=""
prompt_yn "Enable CUDA GPU support? Requires nvidia-container-toolkit (y/n):" "n" USE_GPU
# ── Model selection ───────────────────────────────────────────────────────
echo ""
log_info "Select default model (you can switch models in the UI without restarting):"
echo ""
log_info " ── CPU-safe — work on any machine ─────────────────────────────────────────"
log_info " 1) lama Erase / removal. Intelligent gap fill. ~200 MB ← Recommended"
log_info " 2) cv2 OpenCV fill. No download, instant. Rough quality."
log_info " 3) zits Portrait & face restoration. ~200 MB."
log_info " 4) manga Comic/manga text bubble removal. ~100 MB."
echo ""
if [[ "$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
@@ -215,15 +278,19 @@ services:
container_name: iopaint
hostname: iopaint
restart: unless-stopped
command: iopaint start --model=lama --device=cuda --port=8080 --host=0.0.0.0
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/iopaint
- ./models:/root/.cache
- ./input:/app/input
- ./output:/app/output
environment:
- DEVICE=cuda
deploy:
resources:
reservations:
@@ -239,7 +306,6 @@ networks:
external: true
name: ${CADDY_NET:-caddy_net}
IOPAINT_GPU
log_info "CUDA GPU mode enabled."
else
cat > docker-compose.yml << 'IOPAINT_CPU'
name: iopaint
@@ -250,11 +316,17 @@ services:
container_name: iopaint
hostname: iopaint
restart: unless-stopped
command: iopaint start --model=lama --device=cpu --port=8080 --host=0.0.0.0
command: >-
iopaint start
--model=${MODEL:-lama}
--device=${DEVICE:-cpu}
--port=8080
--host=0.0.0.0
ports:
- "8100:8080"
env_file: .env
volumes:
- ./models:/root/.cache/iopaint
- ./models:/root/.cache
- ./input:/app/input
- ./output:/app/output
networks:
@@ -265,18 +337,18 @@ networks:
external: true
name: ${CADDY_NET:-caddy_net}
IOPAINT_CPU
log_info "CPU mode (default). Change DEVICE to cuda in .env and update the command to use GPU later."
fi
# ── .env ─────────────────────────────────────────────────────────────────
cat > .env << IOPAINT_ENV
# IOPaint configuration
# IOPaint — change MODEL and restart to switch (no need to edit docker-compose.yml)
# Model to use for inpainting (lama recommended for object removal/erase)
# Other models: ldm, zits, mat, fcf, manga, cv2, migan
MODEL=lama
# Current model (set during install — see README for full model list)
MODEL=${IOPAINT_MODEL}
# Device: cpu or cuda (cuda requires nvidia-container-toolkit + GPU deploy block)
DEVICE=$([ "${USE_GPU,,}" = "y" ] && echo "cuda" || echo "cpu")
# 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}
@@ -287,9 +359,14 @@ IOPAINT_ENV
chown -R "$ACTUAL_USER:$ACTUAL_USER" "$IOPAINT_DIR"
echo ""
log_success "IOPaint configured at $IOPAINT_DIR"
log_info "LaMa model downloads on first start (~170 MB). Upload images via the web UI."
log_info "To switch models later: edit the --model= argument in docker-compose.yml and restart."
log_success "IOPaint configured — model: $IOPAINT_MODEL | device: $DEVICE_VAL"
if [[ "$IOPAINT_MODEL" == *"PowerPaint"* ]] || [[ "$IOPAINT_MODEL" == *"stable-diffusion"* ]]; then
log_info "SD-based model selected (~4 GB). It downloads from HuggingFace on first start."
log_info "If the download fails, try: HF_TOKEN=your_token docker compose up -d"
else
log_info "Model downloads automatically on first start (LaMa ~200 MB)."
fi
log_info "Switch models any time by editing MODEL= in .env and restarting."
# No built-in auth — offer Authelia SSO protection
local EXTRA_BLOCK=""
@@ -301,63 +378,97 @@ IOPAINT_ENV
configure_caddy_for_service "IOPaint" "iopaint:8080" "inpaint" "$EXTRA_BLOCK"
write_readme "$IOPAINT_DIR" << MD
write_readme "$IOPAINT_DIR" << 'MD'
# IOPaint
AI-powered image inpainting — erase objects, fill regions, restore photos.
Uses the LaMa (Large Mask) model for high-quality object removal by default.
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 needed
- No built-in login — protect via Authelia SSO if exposed
## Models
The \`--model\` argument in docker-compose.yml selects the AI model:
| Model | Best for |
|--------|----------|
| \`lama\` | Object removal, erase (default) |
| \`ldm\` | Texture-aware fill |
| \`zits\` | Face/portrait restoration |
| \`mat\` | Large missing region fill |
| \`manga\`| Manga/comic text removal |
## 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
```
Models download automatically on first use. Cached in \`./models/\`.
## 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\`. To enable:
1. Edit docker-compose.yml: change \`--device=cpu\` → \`--device=cuda\`
2. Uncomment the \`deploy:\` block (or re-run this installer with GPU=y)
3. Restart: \`docker compose down && docker compose up -d\`
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 $IOPAINT_DIR
docker compose up -d # start
docker compose down # stop
docker compose logs -f # logs
docker compose pull && docker compose down && docker compose up -d # update
\`\`\`
```bash
cd ~/docker/iopaint
docker compose up -d
docker compose down
docker compose logs -f
docker compose pull && docker compose down && docker compose up -d
```
## Files
- docker-compose.yml — stack definition (edit for model/device changes)
- .env — runtime config
- models/ — cached AI model weights
- input/ — optional: place images here
- output/ — processed images written here
- docker-compose.yml — stack (MODEL and DEVICE come from .env)
- .env — model and device config
- models/ — all cached model weights (torch + HuggingFace)
- input/, output/ — optional file staging
MD
local START_IO=""
prompt_yn "Start IOPaint now? (y/n):" "y" START_IO
if [ "$START_IO" = "y" ] || [ "$START_IO" = "Y" ]; then
docker compose up -d \
&& log_success "IOPaint started — LaMa model will download on first use" \
&& 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: LaMa (erase / object removal)"
echo " Device: $([ "${USE_GPU,,}" = "y" ] && echo "CUDA GPU" || echo "CPU")"
echo " Model: $IOPAINT_MODEL"
echo " Device: $DEVICE_VAL"
echo " Switch: edit MODEL= in $IOPAINT_DIR/.env and restart"
echo ""
}