32a73b02f5
Replaces old list-format tags (which duplicated prompt content) with structured dict tags per category (origin_series, outfit_type, participants, style_type, scene_type, etc.). Tags are now purely organizational metadata — removed from the prompt pipeline entirely. Adds is_favourite and is_nsfw columns to all 8 resource models. Favourite is DB-only (user preference); NSFW is mirrored in JSON tags for rescan persistence. All library pages get filter controls and favourites-first sorting. Introduces a parallel LLM job queue (_enqueue_task + _llm_queue_worker) for background tag regeneration, with the same status polling UI as ComfyUI jobs. Fixes call_llm() to use has_request_context() fallback for background threads. Adds global search (/search) across resources and gallery images, with navbar search bar. Adds gallery image sidecar JSON for per-image favourite/NSFW metadata. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
230 lines
9.4 KiB
Python
230 lines
9.4 KiB
Python
import json
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import random
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import logging
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from models import db, Character, Checkpoint, Preset
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from services.prompts import build_prompt, _dedup_tags
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from services.workflow import _prepare_workflow, _get_default_checkpoint
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from services.job_queue import _enqueue_job, _make_finalize
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from services.sync import _resolve_preset_entity, _resolve_preset_fields
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logger = logging.getLogger('gaze')
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def generate_from_preset(preset, overrides=None, save_category='presets'):
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"""Execute preset-based generation.
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Args:
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preset: Preset ORM object
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overrides: optional dict with keys:
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checkpoint, extra_positive, extra_negative, seed, width, height, action
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save_category: upload sub-directory ('presets' or 'generator')
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Returns:
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job dict from _enqueue_job()
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"""
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if overrides is None:
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overrides = {}
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action = overrides.get('action', 'preview')
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extra_positive = overrides.get('extra_positive', '').strip()
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extra_negative = overrides.get('extra_negative', '').strip()
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data = preset.data
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# Resolve entities
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char_cfg = data.get('character', {})
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character = _resolve_preset_entity('character', char_cfg.get('character_id'))
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if not character:
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character = Character.query.order_by(db.func.random()).first()
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outfit_cfg = data.get('outfit', {})
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action_cfg = data.get('action', {})
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style_cfg = data.get('style', {})
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scene_cfg = data.get('scene', {})
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detailer_cfg = data.get('detailer', {})
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look_cfg = data.get('look', {})
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ckpt_cfg = data.get('checkpoint', {})
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outfit = _resolve_preset_entity('outfit', outfit_cfg.get('outfit_id'))
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action_obj = _resolve_preset_entity('action', action_cfg.get('action_id'))
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style_obj = _resolve_preset_entity('style', style_cfg.get('style_id'))
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scene_obj = _resolve_preset_entity('scene', scene_cfg.get('scene_id'))
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detailer_obj = _resolve_preset_entity('detailer', detailer_cfg.get('detailer_id'))
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look_obj = _resolve_preset_entity('look', look_cfg.get('look_id'))
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# Build sidecar metadata with resolved entity slugs
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resolved_meta = {
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'preset_slug': preset.slug,
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'preset_name': preset.name,
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'character_slug': character.slug if character else None,
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'outfit_slug': outfit.slug if outfit else None,
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'action_slug': action_obj.slug if action_obj else None,
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'style_slug': style_obj.slug if style_obj else None,
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'scene_slug': scene_obj.slug if scene_obj else None,
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'detailer_slug': detailer_obj.slug if detailer_obj else None,
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'look_slug': look_obj.slug if look_obj else None,
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}
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# Checkpoint: override > preset config > default
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checkpoint_override = overrides.get('checkpoint', '').strip() if overrides.get('checkpoint') else ''
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if checkpoint_override:
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ckpt_obj = Checkpoint.query.filter_by(checkpoint_path=checkpoint_override).first()
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ckpt_path = checkpoint_override
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ckpt_data = ckpt_obj.data if ckpt_obj else None
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else:
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preset_ckpt = ckpt_cfg.get('checkpoint_path')
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if preset_ckpt == 'random':
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ckpt_obj = Checkpoint.query.order_by(db.func.random()).first()
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ckpt_path = ckpt_obj.checkpoint_path if ckpt_obj else None
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ckpt_data = ckpt_obj.data if ckpt_obj else None
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elif preset_ckpt:
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ckpt_obj = Checkpoint.query.filter_by(checkpoint_path=preset_ckpt).first()
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ckpt_path = preset_ckpt
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ckpt_data = ckpt_obj.data if ckpt_obj else None
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else:
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ckpt_path, ckpt_data = _get_default_checkpoint()
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resolved_meta['checkpoint_path'] = ckpt_path
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# Resolve selected fields from preset toggles
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selected_fields = _resolve_preset_fields(data)
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# Check suppress_wardrobe: preset override > action default
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suppress_wardrobe = False
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preset_suppress = action_cfg.get('suppress_wardrobe')
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if preset_suppress == 'random':
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suppress_wardrobe = random.choice([True, False])
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elif preset_suppress is not None:
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suppress_wardrobe = bool(preset_suppress)
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elif action_obj:
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suppress_wardrobe = action_obj.data.get('suppress_wardrobe', False)
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if suppress_wardrobe:
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selected_fields = [f for f in selected_fields if not f.startswith('wardrobe::')]
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# Build combined data for prompt building
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active_wardrobe = char_cfg.get('fields', {}).get('wardrobe', {}).get('outfit', 'default')
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wardrobe_source = outfit.data.get('wardrobe', {}) if outfit else None
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if wardrobe_source is None:
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wardrobe_source = character.get_active_wardrobe() if character else {}
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if suppress_wardrobe:
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wardrobe_source = {}
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combined_data = {
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'character_id': character.character_id if character else 'unknown',
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'identity': character.data.get('identity', {}) if character else {},
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'defaults': character.data.get('defaults', {}) if character else {},
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'wardrobe': wardrobe_source,
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'styles': character.data.get('styles', {}) if character else {},
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'lora': (look_obj.data.get('lora', {}) if look_obj
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else (character.data.get('lora', {}) if character else {})),
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}
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# Build extras prompt from secondary resources
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extras_parts = []
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if action_obj:
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action_fields = action_cfg.get('fields', {})
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from utils import _BODY_GROUP_KEYS
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for key in _BODY_GROUP_KEYS:
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val_cfg = action_fields.get(key, True)
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if val_cfg == 'random':
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val_cfg = random.choice([True, False])
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if val_cfg:
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val = action_obj.data.get('action', {}).get(key, '')
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if val:
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extras_parts.append(val)
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if action_cfg.get('use_lora', True):
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trg = action_obj.data.get('lora', {}).get('lora_triggers', '')
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if trg:
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extras_parts.append(trg)
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if style_obj:
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s = style_obj.data.get('style', {})
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if s.get('artist_name'):
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extras_parts.append(f"by {s['artist_name']}")
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if s.get('artistic_style'):
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extras_parts.append(s['artistic_style'])
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if style_cfg.get('use_lora', True):
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trg = style_obj.data.get('lora', {}).get('lora_triggers', '')
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if trg:
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extras_parts.append(trg)
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if scene_obj:
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scene_fields = scene_cfg.get('fields', {})
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for key in ['background', 'foreground', 'furniture', 'colors', 'lighting', 'theme']:
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val_cfg = scene_fields.get(key, True)
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if val_cfg == 'random':
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val_cfg = random.choice([True, False])
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if val_cfg:
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val = scene_obj.data.get('scene', {}).get(key, '')
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if val:
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extras_parts.append(val)
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if scene_cfg.get('use_lora', True):
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trg = scene_obj.data.get('lora', {}).get('lora_triggers', '')
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if trg:
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extras_parts.append(trg)
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if detailer_obj:
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prompt_val = detailer_obj.data.get('prompt', '')
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if isinstance(prompt_val, list):
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extras_parts.extend(p for p in prompt_val if p)
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elif prompt_val:
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extras_parts.append(prompt_val)
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if detailer_cfg.get('use_lora', True):
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trg = detailer_obj.data.get('lora', {}).get('lora_triggers', '')
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if trg:
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extras_parts.append(trg)
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with open('comfy_workflow.json', 'r') as f:
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workflow = json.load(f)
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prompts = build_prompt(combined_data, selected_fields, default_fields=None,
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active_outfit=active_wardrobe)
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if extras_parts:
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extra_str = ', '.join(filter(None, extras_parts))
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prompts['main'] = _dedup_tags(f"{prompts['main']}, {extra_str}" if prompts['main'] else extra_str)
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if extra_positive:
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prompts["main"] = f"{prompts['main']}, {extra_positive}"
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# Parse optional seed
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fixed_seed = overrides.get('seed')
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if fixed_seed is not None:
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fixed_seed = int(fixed_seed)
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# Resolution: override > preset config > workflow default
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res_cfg = data.get('resolution', {})
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override_width = overrides.get('width')
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override_height = overrides.get('height')
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if override_width and override_height:
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gen_width = int(override_width)
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gen_height = int(override_height)
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elif res_cfg.get('random', False):
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_RES_OPTIONS = [
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(1024, 1024), (1152, 896), (896, 1152), (1344, 768),
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(768, 1344), (1280, 800), (800, 1280),
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]
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gen_width, gen_height = random.choice(_RES_OPTIONS)
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else:
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gen_width = res_cfg.get('width') or None
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gen_height = res_cfg.get('height') or None
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workflow = _prepare_workflow(
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workflow, character, prompts,
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checkpoint=ckpt_path, checkpoint_data=ckpt_data,
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custom_negative=extra_negative or None,
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outfit=outfit if outfit_cfg.get('use_lora', True) else None,
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action=action_obj if action_cfg.get('use_lora', True) else None,
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style=style_obj if style_cfg.get('use_lora', True) else None,
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scene=scene_obj if scene_cfg.get('use_lora', True) else None,
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detailer=detailer_obj if detailer_cfg.get('use_lora', True) else None,
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look=look_obj,
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fixed_seed=fixed_seed,
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width=gen_width,
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height=gen_height,
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)
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label = f"Preset: {preset.name} – {action}"
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db_model = Preset if save_category == 'presets' else None
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job = _enqueue_job(label, workflow, _make_finalize(save_category, preset.slug, db_model, action, metadata=resolved_meta))
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return job
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