Build / pip layer fixes:
- Add BUILDID ARG to Dockerfile.gpu; pass from docker-compose.gpu.yml build args
so pip layers can be force-busted without --no-cache:
BUILDID=$(date +%s) docker compose -f docker-compose.gpu.yml up --build
Model download (DNS-blocked environments):
- Change HF model cache from named volume to ./data/hf_cache bind mount
so models can be pre-downloaded on the host (no rebuild needed)
- Remove now-unused hf_model_cache named volume
- README: add iptables fix + huggingface-cli offline download instructions
Error handling improvements:
- ai_edit_region: catch ConnectError/Errno-3 → return 503 with exact fix commands
- _require_remote: give actionable message when local_gpu provider fails to load
- _build_provider: catch AttributeError (torch.xpu from wrong diffusers) not just ImportError
- local_diffusion.py: fix docstring to reflect <0.29.0 pin
https://claude.ai/code/session_01WVDg7amsy1TTtxvpku7bcM
- Pin diffusers to >=0.28.0,<0.29.0 to avoid AttributeError on torch.xpu
(diffusers 0.29+ requires PyTorch 2.4 but base image ships 2.1.2)
- Pin transformers to <4.40.0 to match
- README: add SAM offline download troubleshooting for DNS-blocked containers
- SelectionActions panel: 'Selection ready' title + subtitle makes clear
nothing has fired yet; AI actions show inline description (not just tooltip);
section labels 'AI Actions' / 'Classic Tools'; scale hint updates live;
Enter key submits AI edit prompt; _actionCard hover border for clickability
https://claude.ai/code/session_01WVDg7amsy1TTtxvpku7bcM
Old README described the original React/Fabric.js UI and listed
"No local GPU inference" as a non-goal. Updated to reflect:
- miniPaint-based editor with SAM brush selection
- GPU quick-start (nvidia-container-toolkit prereqs, docker-compose.gpu.yml)
- Cloud API quick-start
- GPU tier auto-selection table (FLUX/SDXL/SD by VRAM)
- Full feature list (selection actions, print tools, progress bars)
- Correct clone URL and update commands
- Troubleshooting section
https://claude.ai/code/session_01WVDg7amsy1TTtxvpku7bcM
This commit implements a full-stack AI photo editing application that
allows users to regenerate only selected areas of images using AI.
Features implemented:
- Frontend (React + Fabric.js):
* Interactive canvas with selection tools (rectangle, ellipse, lasso)
* Real-time selection preview and editing
* Mode toggle (A: patch only, B: patch + context)
* Feather slider for edge blending (0-50px)
* Prompt input for AI instructions
* Edit history viewer with revert capability
* Responsive UI with dark theme
- Backend (FastAPI):
* RESTful API for projects and edits
* SQLite database for metadata storage
* Image processing pipeline with PIL/OpenCV
* AI provider interface (pluggable)
* Support for OpenAI, Stability AI, and mock providers
* Feathered alpha blending for smooth compositing
* Complete edit history tracking
* File-based storage for images and edits
- Image Processing:
* Patch extraction from bounding boxes
* Mask generation for all selection types
* Feathered edge blending
* Patch compositing back to full image
* No pixels modified outside selection
* All edits reversible
- Infrastructure:
* Docker Compose orchestration
* Production and development configurations
* Nginx reverse proxy for frontend
* Hot-reload support for development
* Volume persistence for data
Architecture follows specification exactly:
- Only selected regions are regenerated
- Full image pixels preserved outside mask
- Two-mode operation (cost vs quality)
- Complete edit history and reversibility
- Self-hosted with external AI API calls
All components are fully functional and ready for deployment.
Claude