Claude
8fe8498df2
Add local GPU inference: auto-detect GPU, auto-download best diffusion models
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Adds AI_PROVIDER=local_gpu — a fully self-contained GPU inference engine
using HuggingFace Diffusers that requires zero InvokeAI/ComfyUI setup.
All existing providers (InvokeAI, ComfyUI, OpenAI, Replicate) remain intact
and can be mixed with local GPU via per-operation overrides.
New features:
- GPU auto-detection (CUDA/NVIDIA, MPS/Apple Silicon, CPU fallback)
- VRAM-tiered model selection:
ultra ≥16 GB → SDXL inpaint + SDXL base
high 8-16 GB → SDXL inpaint + SDXL base
medium 4-8 GB → SD 2.x inpaint + SD 2.1
low <4 GB → SD 2.x (small)
- Auto-download model weights to HuggingFace disk cache at startup
(background task; first request loads from local disk, not internet)
- LRU pipeline cache evicts oldest GPU pipeline when VRAM limit reached
- Per-operation model overrides via HF_MODEL_INPAINT / HF_MODEL_TXT2IMG etc.
- Optional HF_TOKEN for gated/private HuggingFace models
New files:
- backend/app/services/gpu_detect.py — GPU detection + tier/model mapping
- backend/app/services/local_diffusion.py — Diffusers provider + LRU cache
- backend/app/routers/gpu_status.py — GET /api/gpu/status, POST /api/gpu/prefetch
- backend/requirements.gpu.txt — Diffusers ecosystem deps (GPU only)
- docker-compose.gpu.yml — NVIDIA GPU compose (one-command startup)
- Dockerfile.gpu — pytorch/pytorch:2.1.0-cuda12.1 base image
- scripts/gpu_setup.py — Startup GPU info logger
Modified:
- backend/app/config.py — local_gpu settings added
- backend/app/services/remote_provider.py — local_gpu registered as provider
- backend/app/routers/ai_tools.py — /api/config exposes GPU tier + caps
- backend/app/main.py — GPU router + background prefetch task
- backend/entrypoint.sh — runs gpu_setup.py at container start
- .env.example — local_gpu documented as first option
Quick start with GPU:
docker compose -f docker-compose.gpu.yml up --build
https://claude.ai/code/session_01WVDg7amsy1TTtxvpku7bcM
2026-06-13 15:08:41 +00:00
Claude
d01c11f948
Add per-operation AI provider routing
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Each operation (inpaint, txt2img, img2img, outpaint) can now use a different
provider. Resolution order: per-op override → global AI_PROVIDER default.
Example: txt2img→openai, inpaint→invokeai, everything else→invokeai default.
Backend:
- config.py: add AI_PROVIDER_INPAINT / TXT2IMG / IMG2IMG / OUTPAINT settings
- remote_provider.py: get_remote_provider(operation) resolves override then default;
_build_provider() extracted as shared factory; _OP_FIELD maps op→setting name
- ai_tools.py: each endpoint passes its operation to _require_remote();
GET /api/config runs per-op health checks concurrently, returns operations map
and overrides; POST /api/config accepts and applies per-op override fields
Frontend:
- ai_provider_settings.js: four new selects (inpaint/txt2img/img2img/outpaint);
persists to localStorage and sends per-op fields to POST /api/config
- provider-badge.js: shows override summary (e.g. "invokeai · txt2img→openai")
and per-op health in tooltip
- .env.example: document per-op override env vars with examples
https://claude.ai/code/session_01B58MaJCU1R6KwBDJCp8AfN
2026-06-09 18:14:12 +00:00
Claude
27261c4ef4
Add LaMa magic eraser, remote provider abstraction, and AI tool infrastructure
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Backend:
- requirements.txt: add simple-lama-inpainting, rembg[gpu]; upgrade opencv to 4.10+
- app/config.py: add InvokeAI (url, model) and ComfyUI (url, model) settings; OPENAI_MODEL
- app/services/local_inpaint.py: LaMa, OpenCV, rembg wrappers (auto GPU/CPU)
- app/services/remote_provider.py: abstract RemoteAIProvider + OpenAI, InvokeAI, ComfyUI drivers
- app/routers/ai_tools.py: new /api/* endpoints — /erase, /inpaint/lama, /inpaint/fast,
/background/remove, /inpaint/remote, /generate/txt2img, /generate/img2img,
/generate/outpaint, GET /config (capability flags)
- app/main.py: register ai_tools router
Frontend:
- services/api.js: add erase(), textToImage(), imageToImage(), remoteInpaint(), getConfig()
- api/capabilities.js: lazy-fetch /api/config singleton; hasRemote() helper
- tools/ai_lama_erase.js: brush-paint mask → LaMa erase → apply to layer
- tools/ai_smart_inpaint.js: brush mask + dialog (Fast/Quality mode + prompt) → inpaint
- core/components/provider-badge.js: shows active provider + health in toolbar
- config.js: register ai_lama_erase and ai_smart_inpaint tools
- main.js: mount provider badge on load
- .env.example: document InvokeAI, ComfyUI, OpenAI provider settings
https://claude.ai/code/session_01B58MaJCU1R6KwBDJCp8AfN
2026-06-09 17:42:48 +00:00
Claude