- Per-render-position focal_length_mm/sensor_width_mm (DB → pipeline → Blender)
- FOV-based camera distance with min clamp fix for wide-angle lenses
- Unmapped materials blocking dialog on "Dispatch Renders" with batch alias creation
- Material check endpoint (GET /orders/{id}/check-materials)
- Batch alias endpoint (POST /materials/batch-aliases)
- Quick-map "No alias" badges on Materials page
- Full product hard-delete with storage cleanup (MinIO + disk files + orphaned CadFile)
- Delete button on ProductDetail page with confirmation
- Clickable product names in Media Browser (links to product page)
- Single-line render dispatch/retry (POST /orders/{id}/lines/{id}/dispatch-render)
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
The queue handles far more than thumbnails: OCC tessellation, USD master
generation, GLB production, order line renders, and workflow renders.
asset_pipeline better reflects its role as the render-worker's primary queue.
Updated all references in: task decorators, celery_app.py, beat_tasks.py,
docker-compose.yml worker command, worker.py MONITORED_QUEUES, admin.py,
CLAUDE.md, LEARNINGS.md, Dockerfile, helpTexts.ts, test files,
and all .claude/commands/*.md skill files.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Per-tenant Azure AI config stored in tenants.tenant_config JSONB
- GET/PUT /api/tenants/{id}/ai-config + POST .../test connection
- api_key never returned to frontend (has_api_key: bool pattern)
- azure_ai.py resolves creds from tenant config when ai_enabled=True
- ai_tasks.py loads tenant config and passes it to validate_thumbnail
- Admin GPU Status section: probe button + status badge + last-checked time
- Notifications: _BELL_CHANNELS filter (notification+alert only in bell)
- Tenants.tsx: per-row Azure AI Config modal with URL auto-parse helper
- Remove duplicate in-memory /gpu-probe endpoints (kept DB-backed /probe/gpu)
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- gpu_probe.py: Blender script that probes OPTIX/CUDA/HIP/ONEAPI and
exits 1 on no GPU — used at startup + on-demand from Admin UI
- blender_render.py, still_render.py, turntable_render.py: emit
RENDER_DEVICE_USED: engine=CYCLES device=GPU|CPU compute_type=...
after GPU activation; exit 2 when CYCLES_DEVICE=gpu and CPU fallback
- render_blender.py: parse RENDER_DEVICE_USED token into render_log
(device_used, compute_type, gpu_fallback); handle exit code 2 as
explicit GPU strict-mode failure
- check_version.py: check_gpu() runs gpu_probe.py at container startup;
CYCLES_DEVICE=gpu aborts startup if no GPU found
- docker-compose.yml: CYCLES_DEVICE=${CYCLES_DEVICE:-auto} env var
- gpu_tasks.py: probe_gpu Celery task on thumbnail_rendering queue;
saves result to system_settings.gpu_probe_last_result; beat every 30min
- worker.py: POST /probe/gpu (trigger) + GET /probe/gpu/result (last result)
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Single chronological list sorted by updated_at (newest first)
- Type badges distinguish CAD processing (FileCode2) from Render jobs (Image)
- Render job rows now link directly to the order (/orders/:id)
- Remove separate "Render Jobs" and "CAD File Processing" sections
- Stat cards simplified to 4: CAD active/failed + Render active/failed
- Backend: add order_id to RenderJobEntry response
- Frontend: add order_id to RenderJobEntry interface, remove flamenco_job_id
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Hartmut