Models sometimes stacked text lines at the same y (unreadable) and emitted accent
shapes after text, so a band could hide the words.
- deoverlapTexts: push a line down only when it also overlaps horizontally
(leaves side-by-side text alone), with conservative line-height clearance so
real rendering doesn't re-overlap; shift the stack up if it ran past the bottom.
- Order shapes before text in the output so accent bands always render behind the
words.
Verified: 0 text-on-text overlaps across multiple prompts (Playwright DOM check);
unit test asserts overlapping lines get separated + shapes precede text. 63/63.
Text could run off the edge (long/large headlines, nowrap) and shapes placed at
the far edge (e.g. a bottom band at y=100) spilled over.
- Server-side fit pass on every generated element: shrink text fontSize so it
fits the canvas width (chars*fontSize*0.075, tuned for bold/uppercase
headlines) and height (incl. line-height), then nudge x/y within 4% margins;
clamp shapes so x+width<=100 and y+height<=100. Deterministic - doesn't rely on
the model getting layout right.
- Designer preview: vw -> cqw (+ container-type on the canvas) so text scales to
the canvas, not the browser window. The preview was overstating size vs what
actually publishes; now it matches. Published widget keeps vw (scales on the
player).
Verified: Playwright DOM check shows zero elements overflowing the canvas after
generation; unit test asserts long text is shrunk + repositioned in-bounds. 62/62.
Competitor pressure (Mandoe 'AI Magic Create'): prompt -> signage. We answer it
in a way that's actually BETTER for signage and costs the operator nothing.
Key idea: don't generate raw images (AI garbles text - fatal for menus/promos).
The LLM returns a STRUCTURED design spec (headline, supporting text, accent
shapes, palette) that the existing Designer renders with real fonts - crisp and
fully editable. Reuses the whole Designer.
BYOK, fully under the customer's control: each workspace configures its own
OpenAI-COMPATIBLE endpoint + key - OpenAI cloud OR self-hosted (Ollama / LM Studio
/ llama.cpp). Operator bears zero AI cost/liability.
- server/lib/secretbox.js: AES-256-GCM for the key at rest (never returned).
- routes/ai.js: GET/PUT /api/ai/settings (admin; key write-only) + POST
/generate-design (editor+). Output is strictly validated/normalized (cap count,
clamp ranges, px->%, strip HTML, validate colors) - never trust the model.
SSRF guard: hosted instances block private/internal targets; self-hosted (the
whole point of local AI) may point at localhost/LAN.
- Designer: an 'AI generate' panel (prompt + Generate) + a settings modal.
Verified end-to-end against local Ollama (llama3.1:8b): prompt -> editable design
on the canvas. Unit tests cover normalization + the SSRF guard. Suite 61/61.
Phase 2 (next): AI background images (OpenAI images / AUTOMATIC1111).
