- Implements sequential job queue with background worker thread (_enqueue_job, _queue_worker)
- All generate routes now return job_id instead of prompt_id; frontend polls /api/queue/<id>/status
- Queue management UI in navbar with live badge, job list, pause/resume/remove controls
- Fix: replaced url_for() calls inside finalize callbacks with direct string paths (url_for raises RuntimeError without request context in background threads)
- Batch cover generation now uses two-phase pattern: queue all jobs upfront, then poll concurrently via Promise.all so page navigation doesn't interrupt the process
- Strengths gallery sweep migrated to same two-phase pattern; sgStop() cancels queued jobs server-side
- LoRA weight randomisation via lora_weight_min/lora_weight_max already present in _resolve_lora_weight
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- app.py: add subprocess import; add _ensure_mcp_repo() to clone/pull
danbooru-mcp from https://git.liveaodh.com/aodhan/danbooru-mcp into
tools/danbooru-mcp/ at startup; add ensure_mcp_server_running() which
calls _ensure_mcp_repo() then starts the Docker container if not running;
add GET /api/status/comfyui and GET /api/status/mcp health endpoints;
fix call_llm() to retry up to 3 times on unexpected response format
(KeyError/IndexError), logging the raw response and prompting the LLM
to respond with valid JSON before each retry
- templates/layout.html: add ComfyUI and MCP status dot indicators to
navbar; add polling JS that checks both endpoints on load and every 30s
- static/style.css: add .service-status, .status-dot, .status-ok,
.status-error, .status-checking styles and status-pulse keyframe animation
- .gitignore: add tools/ to exclude the cloned danbooru-mcp repo
- New Checkpoint model (slug, name, checkpoint_path, data JSON, image_path)
- sync_checkpoints() loads metadata from data/checkpoints/*.json and falls
back to template defaults for models without a JSON file
- _apply_checkpoint_settings() applies per-checkpoint steps, CFG, sampler,
base positive/negative prompts, and VAE (with dynamic VAELoader node
injection for non-integrated VAEs) to the ComfyUI workflow
- Bulk Create from Checkpoints: scans Illustrious/Noob model directories,
reads matching HTML files, uses LLM to populate metadata, falls back to
template defaults when no HTML is present
- Gallery index with batch cover generation and WebSocket progress bar
- Detail page showing Generation Settings and Base Prompts cards
- Checkpoints nav link added to layout
- New data/prompts/checkpoint_system.txt LLM system prompt
- Updated README with all current galleries and file structure
- Also includes accumulated action/scene JSON updates, new actions, and
other template/generator improvements from prior sessions
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Add outfit gallery with CRUD operations (create, read, update, delete)
- Add AI-powered profile generation for both characters and outfits
- Add toggle to switch between AI generation and manual creation
- Auto-generate filenames from names with incrementing for duplicates
- Add 'full_body' and 'bottom' fields to wardrobe structure
- Update all character and outfit JSON files with new wardrobe fields
- Reorganize data into data/characters and data/clothing directories
- Update README with new features and JSON structure documentation
