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Add semantic tagging, search, favourite/NSFW filtering, and LLM job queue

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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>
This commit is contained in:
Aodhan Collins
2026-03-21 03:22:09 +00:00
parent 7d79e626a5
commit 32a73b02f5
72 changed files with 3163 additions and 2212 deletions
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132
routes/scenes.py
View File

@@ -1,7 +1,6 @@
import json
import os
import re
import time
import logging
from flask import render_template, request, redirect, url_for, flash, session, current_app
@@ -10,7 +9,7 @@ from sqlalchemy.orm.attributes import flag_modified
from models import db, Character, Scene, Outfit, Action, Style, Detailer, Checkpoint, Settings, Look
from services.workflow import _prepare_workflow, _get_default_checkpoint
from services.job_queue import _enqueue_job, _make_finalize
from services.job_queue import _enqueue_job, _make_finalize, _enqueue_task
from services.prompts import build_prompt, _resolve_character, _ensure_character_fields, _append_background
from services.sync import sync_scenes
from services.file_io import get_available_loras
@@ -37,8 +36,17 @@ def register_routes(app):
@app.route('/scenes')
def scenes_index():
scenes = Scene.query.order_by(Scene.name).all()
return render_template('scenes/index.html', scenes=scenes)
query = Scene.query
fav = request.args.get('favourite')
nsfw = request.args.get('nsfw', 'all')
if fav == 'on':
query = query.filter_by(is_favourite=True)
if nsfw == 'sfw':
query = query.filter_by(is_nsfw=False)
elif nsfw == 'nsfw':
query = query.filter_by(is_nsfw=True)
scenes = query.order_by(Scene.is_favourite.desc(), Scene.name).all()
return render_template('scenes/index.html', scenes=scenes, favourite_filter=fav or '', nsfw_filter=nsfw)
@app.route('/scenes/rescan', methods=['POST'])
def rescan_scenes():
@@ -117,9 +125,12 @@ def register_routes(app):
else:
new_data.setdefault('lora', {}).pop(bound, None)
# Update Tags (comma separated string to list)
tags_raw = request.form.get('tags', '')
new_data['tags'] = [t.strip() for t in tags_raw.split(',') if t.strip()]
# Update Tags (structured dict)
new_data['tags'] = {
'scene_type': request.form.get('tag_scene_type', '').strip(),
'nsfw': 'tag_nsfw' in request.form,
}
scene.is_nsfw = new_data['tags']['nsfw']
scene.data = new_data
flag_modified(scene, "data")
@@ -332,15 +343,16 @@ def register_routes(app):
return redirect(url_for('scenes_index'))
overwrite = request.form.get('overwrite') == 'true'
created_count = 0
skipped_count = 0
overwritten_count = 0
skipped = 0
job_ids = []
system_prompt = load_prompt('scene_system.txt')
if not system_prompt:
flash('Scene system prompt file not found.', 'error')
return redirect(url_for('scenes_index'))
scenes_dir = app.config['SCENES_DIR']
for filename in os.listdir(backgrounds_lora_dir):
if filename.endswith('.safetensors'):
name_base = filename.rsplit('.', 1)[0]
@@ -348,11 +360,11 @@ def register_routes(app):
scene_name = re.sub(r'[^a-zA-Z0-9]+', ' ', name_base).title()
json_filename = f"{scene_id}.json"
json_path = os.path.join(app.config['SCENES_DIR'], json_filename)
json_path = os.path.join(scenes_dir, json_filename)
is_existing = os.path.exists(json_path)
if is_existing and not overwrite:
skipped_count += 1
skipped += 1
continue
html_filename = f"{name_base}.html"
@@ -362,74 +374,69 @@ def register_routes(app):
try:
with open(html_path, 'r', encoding='utf-8', errors='ignore') as hf:
html_raw = hf.read()
# Strip HTML tags but keep text content for LLM context
clean_html = re.sub(r'<script[^>]*>.*?</script>', '', html_raw, flags=re.DOTALL)
clean_html = re.sub(r'<style[^>]*>.*?</style>', '', clean_html, flags=re.DOTALL)
clean_html = re.sub(r'<img[^>]*>', '', clean_html)
clean_html = re.sub(r'<[^>]+>', ' ', clean_html)
html_content = ' '.join(clean_html.split())
except Exception as e:
print(f"Error reading HTML {html_filename}: {e}")
logger.error("Error reading HTML %s: %s", html_filename, e)
try:
print(f"Asking LLM to describe scene: {scene_name}")
prompt = f"Describe a scene for an AI image generation model based on the LoRA filename: '{filename}'"
if html_content:
prompt += f"\n\nHere is descriptive text and metadata extracted from an associated HTML file for this LoRA:\n###\n{html_content[:3000]}\n###"
def make_task(filename, name_base, scene_id, scene_name, json_path, _lora_subfolder, html_content, system_prompt, is_existing):
def task_fn(job):
prompt = f"Describe a scene for an AI image generation model based on the LoRA filename: '{filename}'"
if html_content:
prompt += f"\n\nHere is descriptive text and metadata extracted from an associated HTML file for this LoRA:\n###\n{html_content[:3000]}\n###"
llm_response = call_llm(prompt, system_prompt)
llm_response = call_llm(prompt, system_prompt)
clean_json = llm_response.replace('```json', '').replace('```', '').strip()
scene_data = json.loads(clean_json)
# Clean response
clean_json = llm_response.replace('```json', '').replace('```', '').strip()
scene_data = json.loads(clean_json)
scene_data['scene_id'] = scene_id
scene_data['scene_name'] = scene_name
# Enforce system values while preserving LLM-extracted metadata
scene_data['scene_id'] = scene_id
scene_data['scene_name'] = scene_name
if 'lora' not in scene_data: scene_data['lora'] = {}
scene_data['lora']['lora_name'] = f"Illustrious/{_lora_subfolder}/{filename}"
if 'lora' not in scene_data: scene_data['lora'] = {}
scene_data['lora']['lora_name'] = f"Illustrious/{_lora_subfolder}/{filename}"
if not scene_data['lora'].get('lora_triggers'):
scene_data['lora']['lora_triggers'] = name_base
if scene_data['lora'].get('lora_weight') is None:
scene_data['lora']['lora_weight'] = 1.0
if scene_data['lora'].get('lora_weight_min') is None:
scene_data['lora']['lora_weight_min'] = 0.7
if scene_data['lora'].get('lora_weight_max') is None:
scene_data['lora']['lora_weight_max'] = 1.0
if not scene_data['lora'].get('lora_triggers'):
scene_data['lora']['lora_triggers'] = name_base
if scene_data['lora'].get('lora_weight') is None:
scene_data['lora']['lora_weight'] = 1.0
if scene_data['lora'].get('lora_weight_min') is None:
scene_data['lora']['lora_weight_min'] = 0.7
if scene_data['lora'].get('lora_weight_max') is None:
scene_data['lora']['lora_weight_max'] = 1.0
with open(json_path, 'w') as f:
json.dump(scene_data, f, indent=2)
with open(json_path, 'w') as f:
json.dump(scene_data, f, indent=2)
job['result'] = {'name': scene_name, 'action': 'overwritten' if is_existing else 'created'}
return task_fn
if is_existing:
overwritten_count += 1
else:
created_count += 1
job = _enqueue_task(f"Create scene: {scene_name}", make_task(filename, name_base, scene_id, scene_name, json_path, _lora_subfolder, html_content, system_prompt, is_existing))
job_ids.append(job['id'])
# Small delay to avoid API rate limits if many files
time.sleep(0.5)
except Exception as e:
print(f"Error creating scene for {filename}: {e}")
if created_count > 0 or overwritten_count > 0:
sync_scenes()
msg = f'Successfully processed scenes: {created_count} created, {overwritten_count} overwritten.'
if skipped_count > 0:
msg += f' (Skipped {skipped_count} existing)'
flash(msg)
else:
flash(f'No scenes created or overwritten. {skipped_count} existing scenes found.')
if job_ids:
def sync_task(job):
sync_scenes()
job['result'] = {'synced': True}
_enqueue_task("Sync scenes DB", sync_task)
if request.headers.get('X-Requested-With') == 'XMLHttpRequest':
return {'success': True, 'queued': len(job_ids), 'skipped': skipped}
flash(f'Queued {len(job_ids)} scene tasks ({skipped} skipped).')
return redirect(url_for('scenes_index'))
@app.route('/scene/create', methods=['GET', 'POST'])
def create_scene():
form_data = {}
if request.method == 'POST':
name = request.form.get('name')
slug = request.form.get('filename', '').strip()
form_data = {'name': name, 'filename': slug}
if not slug:
slug = re.sub(r'[^a-zA-Z0-9]+', '_', name.lower()).strip('_')
@@ -478,9 +485,9 @@ def register_routes(app):
except Exception as e:
print(f"Save error: {e}")
flash(f"Failed to create scene: {e}")
return redirect(request.url)
return render_template('scenes/create.html', form_data=form_data)
return render_template('scenes/create.html')
return render_template('scenes/create.html', form_data=form_data)
@app.route('/scene/<path:slug>/clone', methods=['POST'])
def clone_scene(slug):
@@ -538,3 +545,12 @@ def register_routes(app):
with open(file_path, 'w') as f:
json.dump(new_data, f, indent=2)
return {'success': True}
@app.route('/scene/<path:slug>/favourite', methods=['POST'])
def toggle_scene_favourite(slug):
scene = Scene.query.filter_by(slug=slug).first_or_404()
scene.is_favourite = not scene.is_favourite
db.session.commit()
if request.headers.get('X-Requested-With') == 'XMLHttpRequest':
return {'success': True, 'is_favourite': scene.is_favourite}
return redirect(url_for('scene_detail', slug=slug))