tts-voice-creator-clone-and.../architecture/character-visual-identity.md
mARTin-B78 981341de3f feat(characters): check every render, retry with a new seed, and take the sheet's face from the profile
The job checks the portrait crop, then the turnaround, story panel and
same-person against the sheet, re-renders on failure (up to 3 attempts) and
keeps the attempt with the fewest faults. ReActor transfers the profile's face
onto the turnaround and the largest face in the story panel. If the checker is
down, retries stop and the pair is marked unverified. The outcome is saved
with the pair and shown on the character page.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
2026-09-21 10:32:47 +02:00

8.8 KiB
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SOP — Character visual identity and appearance forms

Status: implemented. Covers how a character's avatar and concept (reference) sheet stay the same person, and how one character holds several appearances ("forms") without splitting into several characters or voices.

Single source of truth

  • Appearance facts come from the sheet's physical, clothing, age_estimate, race_species, gender, title, profession, archetype (and the user overrides visual_appearance, visual_species, visual_costume). Both prompts are built by _character_visual_facts in routes/conversation.py; the active form is overlaid first (_character_form_sheet, which never lets a form change its own id/name).
  • image_prompt (portrait) and concept_art_prompt (reference sheet) are deterministic — built server-side from those facts with fixed camera/lighting/period text. Sheet extraction no longer asks the LLM to write image_prompt (it drifted from the concept sheet); the prompt is generated right after extraction by csAutoGenerateExternalPrompts, and again before any avatar-only or per-form generation. A hand-edited prompt (*_user_edited) is never overwritten.
  • Only the two prompts describe an appearance. voice_design_prompt and the SillyTavern prompt belong to the character as a whole, so they always live on the base sheet.

Stale detection

_character_identity_fingerprint (server) and _libIdentityFingerprint (browser) hash the same field list; a test runs the browser code in Node and compares, including list values and non-BMP characters. The three visual_* overrides are appended only when set, so pairs made before they existed keep a valid fingerprint. A pair needs review when its prompt version is not current, its fingerprint is missing or differs, or identity_consistent is false. Regenerating only the avatar or only the reference image sets identity_consistent = false on an existing pair, because a lone regeneration produces a new face.

Where the data lives

base appearance a form
profile image record image form.image
reference image, version, fingerprint, digests, identity_consistent sheet.* form.*
Physical / Clothing text sheet.physical/clothing form.physical/clothing

All visual results are written through one function (_libSaveCharacterVisual), which re-reads the stored record, writes to the active form or the base, and saves. (It used to write the base reference image to the record root, and the consistent-pair generator kept it in memory only, so a base pair lost its reference image and metadata on reload.)

GET /api/characters/visual-pair-review checks the base pair and every form that has images, each against its own metadata and its own fingerprint, and reports form pairs under the form name.

Forms (max 8 per character, enforced in core/validation.py)

Add (starts as a copy of the base Physical/Clothing; only non-empty keys are stored because an empty key would blank the base value when overlaid), rename (unique, ≤160 chars), delete (confirm; the character, its voice and the base look stay), show, and generate matched images for one form or for all forms. Generation rebuilds that form's prompts first (unless hand-edited), saves the pair on that form, then restores whichever appearance was active. Editing Physical/Clothing while a form is active changes only that form.

Image prompt hygiene and the turnaround (1.34.x)

  • Setting. Prompts describe the books as The Dark Eye high-fantasy medieval dress (about 900-1300 AD: wool and linen tunics, belted robes, leather, mail where the sheet names it). The earlier "early Renaissance 1420-1500" wording pulled uniforms, coats, hats and boots that read as musketeer/cowboy/wartime.
  • Wording. Extracted costume text is rewritten at prompt time (_period_wording: Uniform, Weste, Hut, Sporen, Jacke, Schal … become surcoat, jerkin, hood, boots, tunic …). Stored sheets are not changed.
  • Injuries and dirt. _strip_injury_clauses removes clauses about blood, wounds, bandages, burns, limping, torn clothes, soot and dirt from appearance, costume and the story moment; the rest of the sentence stays. The portrait baseline asks for clean skin and garments.
  • Variety. Characters with armour or weapons get an individual garment cut and colour scheme (_character_design_variation, stable per name; colours the sheet names win) instead of one shared list.
  • The turnaround stays one T2I triptych. Drawing front/side/rear one by one with the edit model was tried (2026-09-20) and reverted the next day: it returned three near-identical front views, mixed rendering styles between panels, cropped bodies, and copied the wireframe pose guide into the costume — exactly the failure the triptych was introduced to fix. The portrait/sheet face mismatch is still open and needs a different approach.
  • Props get an object-only period sentence, so a tile no longer turns into a portrait of the character.
  • Older saved prompts are cleaned the same way at render time. Existing image pairs are unchanged until regenerated.

Automatic image check (POST /api/character-image-check)

A vision model reports only what it sees — figure count, the view of each figure left to right, whether every head and foot is in frame, whether the figures are the same person, apparent gender, ear shape (pointed/round/hidden), wounds, and background (plain/scenery). The expected values come from the character sheet and the comparison happens in code (core/character_image_check.py). Asking a model "is this a woman, as required?" invites agreement; asking "what gender is this?" does not, and the expected gender is never revealed in the question.

  • Kinds: portrait, turnaround, scene, same_person (profile vs. a sheet figure).
  • Fail-safe: an unreachable checker, an unreadable answer, or a missing observation is a failure, never a pass. An unreadable answer is returned verbatim (truncated) so it can be diagnosed.
  • Thinking is switched off: a reasoning model spent the whole budget deliberating over a confusing image and returned nothing.
  • Model: the active LLM by default (llm_model), overridable with the image_check_model setting. The model already loaded reads images, so a check never makes llama-swap unload it for a separate vision model on a GPU with no room for both.

Calibration (2026-09-21) on seven panels whose defects were known (three front views, elf ears on a human, a wireframe rendered as a figure, cut-off feet, a man where the sheet says woman, a forest behind a studio portrait, and one correct same-person pair), run twice:

model correct wrong unreadable per check
local Qwen3.8-27B (default) 14/14 0 0 ~4 s
Ling 3.0 Flash VL (vision, free, OpenRouter) 8/14 0 6 ~17 s

Ling never judged wrongly but on every turnaround ignored the JSON-only instruction and answered in prose. It also has free-tier rate limits and sends the images to a third party.

Generation with checks and retries (face from the profile)

The generation job (POST /api/character-generate-consistent-images) now runs:

  1. Identity image (text-to-image, full body). The profile picture is cut from it. Portrait check on exactly that crop (one person, gender, ears, wounds, plain background). On failure: a new seed, up to image_check_max_attempts (default 3), keeping the attempt with the fewest faults.
  2. Sheet (turnaround triptych + story moment + props, one ComfyUI run). The profile's face is then transferred with ReActor (inswapper_128, CodeFormer 0.5 restore): turnaround faces left to right (front and side; the rear has none), and in the story panel only the largest face — the character in the foreground, not an extra. Checks: turnaround, story panel, and same-person (profile vs. the front view). Gender is judged after the face transfer, on what a viewer actually sees. Retried the same way.
  3. The result carries image_check = {verified, passed, attempts, failures[], checks{}}, saved on the sheet and shown on the character page: verified with no faults / faults still found (listed) / not verified.

If the checker itself is unavailable, retries stop at once and the pair is marked not verified: re-rolling images cannot fix a missing checker, and would burn up to three renders per character.

Why face transfer and not rendering the views from the portrait: the edit model keeps the source pose (three front views, the pose guide copied into the costume — tried and reverted 2026-09-21). The text-to-image triptych gets the poses right; swapping only the face afterwards fixes the identity.

Settings: image_check_enabled (default on), image_check_max_attempts (1–5, default 3), image_check_model (default: the active LLM).