Add StepName.BLENDER_CINEMATIC and full graph runtime support so cinematic
output types can be promoted from legacy_only to graph/shadow rollout mode.
- process_steps.py: add BLENDER_CINEMATIC = "blender_cinematic" enum value
- workflow_executor.py: map to render_cinematic_task in STEP_TASK_MAP
- workflow_node_registry.py: node definition with render/scene/camera fields
(no animation params — cinematic is fixed at 250 frames @ 25fps)
- workflow_graph_runtime.py: _ORDER_LINE_RENDER_STEPS, _CINEMATIC_TASK_KEYS,
shadow queue routing, predict_render_output_artifact (mp4),
_build_task_kwargs, _artifact_kind_override_for_step
- tasks.py: _normalize_cinematic_params + render_cinematic_task Celery task
(calls render_cinematic_to_file, publishes as turntable asset type since mp4)
No DB migration needed: admins can now manually set cinematic output types
to graph rollout mode via the admin panel and assign a workflow definition.
docs: learnings erfasst — BLENDER_CINEMATIC workflow graph node M1
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
M3: cors_origins setting in config.py (env CORS_ORIGINS); main.py reads from settings.
M4: add build_order_line_step_render_dir() to render_paths.py; tasks.py drops placeholder.mp4 trick.
M5: unknown workflow graph nodes now fail the run (status="failed" + logger.error) instead of silently skipping.
M6: invoice line description is now "{product} — {output_type}" instead of bare UUID; eager-loads relations.
M7: order_number_prefix setting in config.py (env ORDER_NUMBER_PREFIX, default "SA").
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- @timed_step decorator with wall-clock + RSS tracking (pipeline_logger)
- Blender timing laps for sharp edges and material assignment
- MeshRegistry pattern: eliminate 13 scene.traverse() calls across viewers
- Lazy material cloning (clone-on-first-write in both viewers)
- _pipeline_session context manager: 7 create_engine() → 2 in render_thumbnail
- KD-tree spatial pre-filter for sharp edge marking (bbox-based pruning)
- Batch material library append: N bpy.ops.wm.append → single bpy.data.libraries.load
- GMSH single-session batching: compound all solids into one tessellation call
- Validate part-materials save endpoints against parsed_objects (prevents bogus keys)
- ROADMAP updated with completion status
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Phase 1 of PLAN_REFACTOR.md — all four sub-tasks implemented:
1.1 PipelineLogger (backend/app/core/pipeline_logger.py)
- Structured step_start/step_done/step_error/step_progress API
- Publishes to Python logging AND Redis SSE via log_task_event
- Context manager `pl.step("name")` for auto-timing
1.2 RenderJobDocument (backend/app/domains/rendering/job_document.py)
- Pydantic JSONB schema: state machine + per-step records + timing
- begin_step/finish_step/fail_step/skip_step helpers
- Migration 048: adds render_job_doc JSONB column to order_lines
- OrderLine model updated with render_job_doc field
1.3 TenantContextMiddleware (backend/app/core/middleware.py)
- Decodes JWT, stores tenant_id + role in request.state
- get_db updated to auto-apply RLS SET LOCAL from request.state
- Registered in main.py (runs before every request)
- JWT now embeds tenant_id claim via create_access_token()
- Login endpoint passes tenant_id to token creation
1.4 ProcessStep Registry (backend/app/core/process_steps.py)
- StepName StrEnum with all 20 pipeline step names
- Single source of truth for log prefixes, DB records, UI labels
Also adds db_utils.py with set_tenant_sync() + get_sync_session()
for use inside Celery tasks (bypass-safe RLS helper).
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
HartmutandClaude Sonnet 4.6