Multiple bug fixes.

CLAUDE.md

@@ -298,10 +298,10 @@ All generation routes use the background job queue. Frontend polls:
 Image retrieval is handled server-side by the `_make_finalize()` callback; there are no separate client-facing finalize routes.
 
 ### Utilities
-- `POST /set_default_checkpoint` — save default checkpoint to session
+- `POST /set_default_checkpoint` — save default checkpoint to session and persist to `comfy_workflow.json`
-- `GET /get_missing_{characters,outfits,actions,scenes}` — AJAX: list items without cover images
+- `GET /get_missing_{characters,outfits,actions,scenes,styles,detailers,looks,checkpoints}` — AJAX: list items without cover images (sorted by display name)
 - `POST /generate_missing` — batch generate covers for all characters missing one (uses job queue)
-- `POST /clear_all_covers` / `clear_all_{outfit,action,scene}_covers`
+- `POST /clear_all_covers` / `clear_all_{outfit,action,scene,style,detailer,look,checkpoint}_covers`
 - `GET /gallery` — global image gallery browsing `static/uploads/`
 - `GET/POST /settings` — LLM provider configuration
 - `POST /resource/<category>/<slug>/delete` — soft (JSON only) or hard (JSON + safetensors) delete
@@ -321,6 +321,11 @@ Image retrieval is handled server-side by the `_make_finalize()` callback; there
 - Context processors inject `all_checkpoints`, `default_checkpoint_path`, and `COMFYUI_WS_URL` into every template.
 - **No `{% block head %}` exists** in layout.html — do not try to use it.
 - Generation is async: JS submits the form via AJAX (`X-Requested-With: XMLHttpRequest`), receives a `{"job_id": ...}` response, then polls `/api/queue/<job_id>/status` every ~1.5 seconds until `status == "done"`. The server-side worker handles all ComfyUI polling and image saving via the `_make_finalize()` callback. There are no client-facing finalize HTTP routes.
+- **Batch generation** (library pages): Uses a two-phase pattern:
+  1. **Queue phase**: All jobs are submitted upfront via sequential fetch calls, collecting job IDs
+  2. **Poll phase**: All jobs are polled concurrently via `Promise.all()`, updating UI as each completes
+  3. **Progress tracking**: Displays currently processing items in real-time using a `Set` to track active jobs
+  4. **Sorting**: All batch operations sort items by display `name` (not `filename`) for better UX
 
 ---
 

app.py

@@ -47,12 +47,16 @@ Session(app)
 # ---------------------------------------------------------------------------
 # Logging
 # ---------------------------------------------------------------------------
+log_level_str = os.environ.get('LOG_LEVEL', 'INFO').upper()
+log_level = getattr(logging, log_level_str, logging.INFO)
+
 logging.basicConfig(
-    level=logging.INFO,
+    level=log_level,
     format='%(asctime)s [%(levelname)s] %(name)s: %(message)s',
     datefmt='%Y-%m-%d %H:%M:%S',
 )
 logger = logging.getLogger('gaze')
+logger.setLevel(log_level)
 
 # ---------------------------------------------------------------------------
 # Generation Job Queue
@@ -117,11 +121,43 @@ def _queue_worker():
             with _job_queue_lock:
                 job['status'] = 'processing'
 
-            logger.info("Job started: [%s] %s", job['id'][:8], job['label'])
+            logger.info("=" * 80)
+            logger.info("JOB STARTED: [%s] %s", job['id'][:8], job['label'])
+            logger.info("Job created at: %s", time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(job['created_at'])))
+            
+            # Log workflow summary before sending to ComfyUI
+            workflow = job['workflow']
+            logger.info("Workflow summary:")
+            logger.info("  Checkpoint: %s", workflow.get('4', {}).get('inputs', {}).get('ckpt_name', '(not set)'))
+            logger.info("  Seed: %s", workflow.get('3', {}).get('inputs', {}).get('seed', '(not set)'))
+            logger.info("  Resolution: %sx%s",
+                       workflow.get('5', {}).get('inputs', {}).get('width', '?'),
+                       workflow.get('5', {}).get('inputs', {}).get('height', '?'))
+            logger.info("  Sampler: %s / %s (steps=%s, cfg=%s)",
+                       workflow.get('3', {}).get('inputs', {}).get('sampler_name', '?'),
+                       workflow.get('3', {}).get('inputs', {}).get('scheduler', '?'),
+                       workflow.get('3', {}).get('inputs', {}).get('steps', '?'),
+                       workflow.get('3', {}).get('inputs', {}).get('cfg', '?'))
+            
+            # Log active LoRAs
+            active_loras = []
+            for node_id, label_str in [("16", "char/look"), ("17", "outfit"), ("18", "action"), ("19", "style/detail/scene")]:
+                if node_id in workflow:
+                    lora_name = workflow[node_id]["inputs"].get("lora_name", "")
+                    if lora_name:
+                        strength = workflow[node_id]["inputs"].get("strength_model", "?")
+                        active_loras.append(f"{label_str}:{lora_name.split('/')[-1]}@{strength}")
+            logger.info("  Active LoRAs: %s", ' | '.join(active_loras) if active_loras else '(none)')
+            
+            # Log prompts
+            logger.info("  Positive prompt: %s", workflow.get('6', {}).get('inputs', {}).get('text', '(not set)')[:200])
+            logger.info("  Negative prompt: %s", workflow.get('7', {}).get('inputs', {}).get('text', '(not set)')[:200])
+            logger.info("=" * 80)
 
             try:
                 with app.app_context():
                     # Send workflow to ComfyUI
+                    logger.info("Sending workflow to ComfyUI...")
                     prompt_response = queue_prompt(job['workflow'])
                     if 'prompt_id' not in prompt_response:
                         raise Exception(f"ComfyUI rejected job: {prompt_response.get('error', 'unknown error')}")
@@ -134,11 +170,19 @@ def _queue_worker():
                     # Poll until done (max ~10 minutes)
                     max_retries = 300
                     finished = False
+                    poll_count = 0
+                    logger.info("Polling ComfyUI for completion (max %d retries, 2s interval)...", max_retries)
                     while max_retries > 0:
                         history = get_history(comfy_id)
                         if comfy_id in history:
                             finished = True
+                            logger.info("Generation completed after %d polls (%d seconds)",
+                                      poll_count, poll_count * 2)
                             break
+                        poll_count += 1
+                        if poll_count % 10 == 0:  # Log every 20 seconds
+                            logger.info("Still waiting for generation... (%d polls, %d seconds elapsed)",
+                                      poll_count, poll_count * 2)
                         time.sleep(2)
                         max_retries -= 1
 
@@ -152,10 +196,14 @@ def _queue_worker():
 
                 with _job_queue_lock:
                     job['status'] = 'done'
-                logger.info("Job done: [%s] %s", job['id'][:8], job['label'])
+                logger.info("=" * 80)
+                logger.info("JOB COMPLETED: [%s] %s", job['id'][:8], job['label'])
+                logger.info("=" * 80)
 
             except Exception as e:
-                logger.exception("Job failed: [%s] %s — %s", job['id'][:8], job['label'], e)
+                logger.error("=" * 80)
+                logger.exception("JOB FAILED: [%s] %s — %s", job['id'][:8], job['label'], e)
+                logger.error("=" * 80)
                 with _job_queue_lock:
                     job['status'] = 'failed'
                     job['error'] = str(e)
@@ -185,28 +233,59 @@ def _make_finalize(category, slug, db_model_class=None, action=None):
     action          — 'replace' → update DB; None → always update; anything else → skip
     """
     def _finalize(comfy_prompt_id, job):
+        logger.debug("=" * 80)
+        logger.debug("FINALIZE - Starting finalization for prompt ID: %s", comfy_prompt_id)
+        logger.debug("Category: %s, Slug: %s, Action: %s", category, slug, action)
+        
         history = get_history(comfy_prompt_id)
         outputs = history[comfy_prompt_id]['outputs']
-        for node_output in outputs.values():
+        
+        logger.debug("Processing outputs from %d node(s)", len(outputs))
+        for node_id, node_output in outputs.items():
+            logger.debug("  Node %s: %s", node_id, list(node_output.keys()))
             if 'images' in node_output:
+                logger.debug("  Found %d image(s) in node %s", len(node_output['images']), node_id)
                 image_info = node_output['images'][0]
+                logger.debug("  Image info: filename=%s, subfolder=%s, type=%s",
+                           image_info['filename'], image_info['subfolder'], image_info['type'])
+                
                 image_data = get_image(image_info['filename'], image_info['subfolder'], image_info['type'])
+                
                 folder = os.path.join(app.config['UPLOAD_FOLDER'], f"{category}/{slug}")
                 os.makedirs(folder, exist_ok=True)
                 filename = f"gen_{int(time.time())}.png"
-                with open(os.path.join(folder, filename), 'wb') as f:
+                full_path = os.path.join(folder, filename)
+                
+                logger.debug("  Saving image to: %s", full_path)
+                with open(full_path, 'wb') as f:
                     f.write(image_data)
+                logger.info("Image saved: %s (%d bytes)", full_path, len(image_data))
+                
                 relative_path = f"{category}/{slug}/{filename}"
                 job['result'] = {
                     'image_url': f'/static/uploads/{relative_path}',
                     'relative_path': relative_path,
                 }
+                
                 if db_model_class and (action is None or action == 'replace'):
+                    logger.debug("  Updating database: %s.image_path = %s", db_model_class.__name__, relative_path)
                     obj = db_model_class.query.filter_by(slug=slug).first()
                     if obj:
                         obj.image_path = relative_path
                         db.session.commit()
+                        logger.debug("  Database updated successfully")
+                    else:
+                        logger.warning("  Object not found in database: %s(slug=%s)", db_model_class.__name__, slug)
+                else:
+                    logger.debug("  Skipping database update (db_model_class=%s, action=%s)",
+                               db_model_class.__name__ if db_model_class else None, action)
+                
+                logger.debug("FINALIZE - Completed successfully")
+                logger.debug("=" * 80)
                 return
+        
+        logger.warning("FINALIZE - No images found in outputs!")
+        logger.debug("=" * 80)
     return _finalize
 
 
@@ -402,8 +481,38 @@ def inject_default_checkpoint():
 
 @app.route('/set_default_checkpoint', methods=['POST'])
 def set_default_checkpoint():
-    session['default_checkpoint'] = request.form.get('checkpoint_path', '')
+    checkpoint_path = request.form.get('checkpoint_path', '')
+    session['default_checkpoint'] = checkpoint_path
     session.modified = True
+    
+    # Persist to database Settings so it survives across server restarts
+    try:
+        settings = Settings.query.first()
+        if not settings:
+            settings = Settings()
+            db.session.add(settings)
+        settings.default_checkpoint = checkpoint_path
+        db.session.commit()
+        logger.info("Default checkpoint saved to database: %s", checkpoint_path)
+    except Exception as e:
+        logger.error(f"Failed to persist checkpoint to database: {e}")
+        db.session.rollback()
+    
+    # Also persist to comfy_workflow.json for backwards compatibility
+    try:
+        workflow_path = 'comfy_workflow.json'
+        with open(workflow_path, 'r') as f:
+            workflow = json.load(f)
+        
+        # Update node 4 (CheckpointLoaderSimple) with the new checkpoint
+        if '4' in workflow and 'inputs' in workflow['4']:
+            workflow['4']['inputs']['ckpt_name'] = checkpoint_path
+            
+            with open(workflow_path, 'w') as f:
+                json.dump(workflow, f, indent=2)
+    except Exception as e:
+        logger.error(f"Failed to persist checkpoint to workflow file: {e}")
+    
     return {'status': 'ok'}
 
 
@@ -455,6 +564,44 @@ def api_status_mcp():
         pass
     return {'status': 'error'}
 
+
+@app.route('/api/status/llm')
+def api_status_llm():
+    """Return whether the configured LLM provider is reachable."""
+    try:
+        settings = Settings.query.first()
+        if not settings:
+            return {'status': 'error', 'message': 'Settings not configured'}
+        
+        is_local = settings.llm_provider != 'openrouter'
+        
+        if not is_local:
+            # Check OpenRouter
+            if not settings.openrouter_api_key:
+                return {'status': 'error', 'message': 'API key not configured'}
+            
+            # Try to fetch models list as a lightweight check
+            headers = {
+                "Authorization": f"Bearer {settings.openrouter_api_key}",
+            }
+            resp = requests.get("https://openrouter.ai/api/v1/models", headers=headers, timeout=5)
+            if resp.ok:
+                return {'status': 'ok', 'provider': 'OpenRouter'}
+        else:
+            # Check local provider (Ollama or LMStudio)
+            if not settings.local_base_url:
+                return {'status': 'error', 'message': 'Base URL not configured'}
+            
+            # Try to reach the models endpoint
+            url = f"{settings.local_base_url.rstrip('/')}/models"
+            resp = requests.get(url, timeout=5)
+            if resp.ok:
+                return {'status': 'ok', 'provider': settings.llm_provider.title()}
+    except Exception as e:
+        return {'status': 'error', 'message': str(e)}
+    
+    return {'status': 'error'}
+
 ALLOWED_EXTENSIONS = {'png', 'jpg', 'jpeg', 'gif', 'webp'}
 
 _LORA_DEFAULTS = {
@@ -622,6 +769,44 @@ def _append_background(prompts, character=None):
     bg = f"{primary_color} simple background" if primary_color else "simple background"
     prompts['main'] = f"{prompts['main']}, {bg}"
 
+def _count_look_assignments():
+    """Return a dict mapping look_id to the count of characters it's assigned to."""
+    # Looks are assigned via the character_id field in the Look model
+    assignment_counts = {}
+    looks = Look.query.all()
+    for look in looks:
+        if look.character_id:
+            assignment_counts[look.look_id] = 1  # Each look is assigned to at most one character
+        else:
+            assignment_counts[look.look_id] = 0
+    return assignment_counts
+
+def _count_outfit_lora_assignments():
+    """Return a dict mapping outfit LoRA filename to the count of characters using it."""
+    assignment_counts = {}
+    characters = Character.query.all()
+    
+    for character in characters:
+        # Check character's own LoRA (in case it's actually an outfit LoRA)
+        char_lora = character.data.get('lora', {}).get('lora_name', '')
+        if char_lora and 'Clothing' in char_lora:
+            assignment_counts[char_lora] = assignment_counts.get(char_lora, 0) + 1
+        
+        # Check all wardrobe outfits for LoRA references
+        wardrobe = character.data.get('wardrobe', {})
+        # Handle both nested (new) and flat (legacy) wardrobe formats
+        if 'default' in wardrobe and isinstance(wardrobe.get('default'), dict):
+            # New nested format - check each outfit
+            for outfit_name, outfit_data in wardrobe.items():
+                if isinstance(outfit_data, dict):
+                    outfit_lora = outfit_data.get('lora', {})
+                    if isinstance(outfit_lora, dict):
+                        lora_name = outfit_lora.get('lora_name', '')
+                        if lora_name:
+                            assignment_counts[lora_name] = assignment_counts.get(lora_name, 0) + 1
+    
+    return assignment_counts
+
 def build_prompt(data, selected_fields=None, default_fields=None, active_outfit='default'):
     def is_selected(section, key):
         # Priority: 
@@ -745,21 +930,104 @@ def build_prompt(data, selected_fields=None, default_fields=None, active_outfit=
         "hand": _dedup_tags(", ".join(hand_parts))
     }
 
+def _ensure_checkpoint_loaded(checkpoint_path):
+    """Check if the desired checkpoint is loaded in ComfyUI, and force reload if not."""
+    if not checkpoint_path:
+        return
+    
+    try:
+        # Get currently loaded checkpoint from ComfyUI history
+        url = app.config.get('COMFYUI_URL', 'http://127.0.0.1:8188')
+        resp = requests.get(f'{url}/history', timeout=3)
+        if resp.ok:
+            history = resp.json()
+            if history:
+                latest = max(history.values(), key=lambda j: j.get('status', {}).get('status_str', ''))
+                nodes = latest.get('prompt', [None, None, {}])[2]
+                loaded_ckpt = nodes.get('4', {}).get('inputs', {}).get('ckpt_name')
+                
+                # If the loaded checkpoint matches what we want, no action needed
+                if loaded_ckpt == checkpoint_path:
+                    logger.info(f"Checkpoint {checkpoint_path} already loaded in ComfyUI")
+                    return
+        
+        # Checkpoint doesn't match or couldn't determine - force unload all models
+        logger.info(f"Forcing ComfyUI to unload models to ensure {checkpoint_path} loads")
+        requests.post(f'{url}/free', json={'unload_models': True}, timeout=5)
+    except Exception as e:
+        logger.warning(f"Failed to check/force checkpoint reload: {e}")
+
 def queue_prompt(prompt_workflow, client_id=None):
+    # Ensure the checkpoint in the workflow is loaded in ComfyUI
+    checkpoint_path = prompt_workflow.get('4', {}).get('inputs', {}).get('ckpt_name')
+    _ensure_checkpoint_loaded(checkpoint_path)
+    
     p = {"prompt": prompt_workflow}
     if client_id:
         p["client_id"] = client_id
+    
+    # Log the full request being sent to ComfyUI
+    logger.debug("=" * 80)
+    logger.debug("COMFYUI REQUEST - Sending prompt to %s/prompt", app.config['COMFYUI_URL'])
+    logger.debug("Checkpoint: %s", checkpoint_path)
+    logger.debug("Client ID: %s", client_id if client_id else "(none)")
+    logger.debug("Full workflow JSON:")
+    logger.debug(json.dumps(prompt_workflow, indent=2))
+    logger.debug("=" * 80)
+    
     data = json.dumps(p).encode('utf-8')
     response = requests.post(f"{app.config['COMFYUI_URL']}/prompt", data=data)
-    return response.json()
+    response_json = response.json()
+    
+    # Log the response from ComfyUI
+    logger.debug("COMFYUI RESPONSE - Status: %s", response.status_code)
+    logger.debug("Response JSON: %s", json.dumps(response_json, indent=2))
+    if 'prompt_id' in response_json:
+        logger.info("ComfyUI accepted prompt with ID: %s", response_json['prompt_id'])
+    else:
+        logger.error("ComfyUI rejected prompt: %s", response_json)
+    logger.debug("=" * 80)
+    
+    return response_json
 
 def get_history(prompt_id):
     response = requests.get(f"{app.config['COMFYUI_URL']}/history/{prompt_id}")
-    return response.json()
+    history_json = response.json()
+    
+    # Log detailed history response for debugging
+    if prompt_id in history_json:
+        logger.debug("=" * 80)
+        logger.debug("COMFYUI HISTORY - Prompt ID: %s", prompt_id)
+        logger.debug("Status: %s", response.status_code)
+        
+        # Extract key information from the history
+        prompt_data = history_json[prompt_id]
+        if 'status' in prompt_data:
+            logger.debug("Generation status: %s", prompt_data['status'])
+        
+        if 'outputs' in prompt_data:
+            logger.debug("Outputs available: %s", list(prompt_data['outputs'].keys()))
+            for node_id, output in prompt_data['outputs'].items():
+                if 'images' in output:
+                    logger.debug("  Node %s produced %d image(s)", node_id, len(output['images']))
+                    for img in output['images']:
+                        logger.debug("    - %s (subfolder: %s, type: %s)",
+                                   img.get('filename'), img.get('subfolder'), img.get('type'))
+        
+        logger.debug("Full history response:")
+        logger.debug(json.dumps(history_json, indent=2))
+        logger.debug("=" * 80)
+    else:
+        logger.debug("History not yet available for prompt ID: %s", prompt_id)
+    
+    return history_json
 
 def get_image(filename, subfolder, folder_type):
     data = {"filename": filename, "subfolder": subfolder, "type": folder_type}
+    logger.debug("Fetching image from ComfyUI: filename=%s, subfolder=%s, type=%s",
+                filename, subfolder, folder_type)
     response = requests.get(f"{app.config['COMFYUI_URL']}/view", params=data)
+    logger.debug("Image retrieved: %d bytes (status: %s)", len(response.content), response.status_code)
     return response.content
 
 from sqlalchemy.orm.attributes import flag_modified
@@ -2218,30 +2486,87 @@ def _log_workflow_prompts(label, workflow):
     """Log the final assembled ComfyUI prompts in a consistent, readable block."""
     sep = "=" * 72
     active_loras = []
+    lora_details = []
+    
+    # Collect detailed LoRA information
     for node_id, label_str in [("16", "char/look"), ("17", "outfit"), ("18", "action"), ("19", "style/detail/scene")]:
         if node_id in workflow:
             name = workflow[node_id]["inputs"].get("lora_name", "")
             if name:
-                w = workflow[node_id]["inputs"].get("strength_model", "?")
+                strength_model = workflow[node_id]["inputs"].get("strength_model", "?")
-                active_loras.append(f"{label_str}:{name.split('/')[-1]}@{w:.3f}" if isinstance(w, float) else f"{label_str}:{name.split('/')[-1]}@{w}")
+                strength_clip = workflow[node_id]["inputs"].get("strength_clip", "?")
+                
+                # Short version for summary
+                if isinstance(strength_model, float):
+                    active_loras.append(f"{label_str}:{name.split('/')[-1]}@{strength_model:.3f}")
+                else:
+                    active_loras.append(f"{label_str}:{name.split('/')[-1]}@{strength_model}")
+                
+                # Detailed version
+                lora_details.append(f"    Node {node_id} ({label_str}): {name}")
+                lora_details.append(f"      strength_model={strength_model}, strength_clip={strength_clip}")
+    
+    # Extract VAE information
+    vae_info = "(integrated)"
+    if '21' in workflow:
+        vae_info = workflow['21']['inputs'].get('vae_name', '(custom)')
+    
+    # Extract adetailer information
+    adetailer_info = []
+    for node_id, node_name in [("11", "Face"), ("13", "Hand")]:
+        if node_id in workflow:
+            adetailer_info.append(f"    {node_name} (Node {node_id}): steps={workflow[node_id]['inputs'].get('steps', '?')}, "
+                                f"cfg={workflow[node_id]['inputs'].get('cfg', '?')}, "
+                                f"denoise={workflow[node_id]['inputs'].get('denoise', '?')}")
+    
     face_text = workflow.get('14', {}).get('inputs', {}).get('text', '')
     hand_text = workflow.get('15', {}).get('inputs', {}).get('text', '')
+    
     lines = [
         sep,
         f"  WORKFLOW PROMPTS  [{label}]",
         sep,
+        "  MODEL CONFIGURATION:",
         f"    Checkpoint : {workflow['4']['inputs'].get('ckpt_name', '(not set)')}",
+        f"    VAE        : {vae_info}",
+        "",
+        "  GENERATION SETTINGS:",
         f"    Seed       : {workflow['3']['inputs'].get('seed', '(not set)')}",
         f"    Resolution : {workflow['5']['inputs'].get('width', '?')} x {workflow['5']['inputs'].get('height', '?')}",
-        f"  Sampler    : {workflow['3']['inputs'].get('sampler_name', '?')} / {workflow['3']['inputs'].get('scheduler', '?')}  steps={workflow['3']['inputs'].get('steps', '?')}  cfg={workflow['3']['inputs'].get('cfg', '?')}",
+        f"    Sampler    : {workflow['3']['inputs'].get('sampler_name', '?')} / {workflow['3']['inputs'].get('scheduler', '?')}",
-        f"  LoRAs      : {' | '.join(active_loras) if active_loras else '(none)'}",
+        f"    Steps      : {workflow['3']['inputs'].get('steps', '?')}",
+        f"    CFG Scale  : {workflow['3']['inputs'].get('cfg', '?')}",
+        f"    Denoise    : {workflow['3']['inputs'].get('denoise', '1.0')}",
+    ]
+    
+    # Add LoRA details
+    if active_loras:
+        lines.append("")
+        lines.append("  LORA CONFIGURATION:")
+        lines.extend(lora_details)
+    else:
+        lines.append("")
+        lines.append("  LORA CONFIGURATION: (none)")
+    
+    # Add adetailer details
+    if adetailer_info:
+        lines.append("")
+        lines.append("  ADETAILER CONFIGURATION:")
+        lines.extend(adetailer_info)
+    
+    # Add prompts
+    lines.extend([
+        "",
+        "  PROMPTS:",
         f"    [+] Positive : {workflow['6']['inputs'].get('text', '')}",
         f"    [-] Negative : {workflow['7']['inputs'].get('text', '')}",
-    ]
+    ])
+    
     if face_text:
         lines.append(f"    [F] Face     : {face_text}")
     if hand_text:
         lines.append(f"    [H] Hand     : {hand_text}")
+    
     lines.append(sep)
     logger.info("\n%s", "\n".join(lines))
 
@@ -2258,9 +2583,16 @@ def _prepare_workflow(workflow, character, prompts, checkpoint=None, custom_nega
     if "15" in workflow:
         workflow["15"]["inputs"]["text"] = workflow["15"]["inputs"]["text"].replace("{{HAND_PROMPT}}", prompts["hand"])
 
-    # 2. Update Checkpoint
+    # 2. Update Checkpoint - always set one, fall back to default if not provided
+    if not checkpoint:
+        default_ckpt, default_ckpt_data = _get_default_checkpoint()
+        checkpoint = default_ckpt
+        if not checkpoint_data:
+            checkpoint_data = default_ckpt_data
     if checkpoint:
         workflow["4"]["inputs"]["ckpt_name"] = checkpoint
+    else:
+        raise ValueError("No checkpoint specified and no default checkpoint configured")
 
     # 3. Handle LoRAs - Node 16 for character, Node 17 for outfit, Node 18 for action, Node 19 for style/detailer
     # Start with direct checkpoint connections
@@ -2394,18 +2726,38 @@ def _prepare_workflow(workflow, character, prompts, checkpoint=None, custom_nega
     return workflow
 
 def _get_default_checkpoint():
-    """Return (checkpoint_path, checkpoint_data) from the session default, or (None, None)."""
+    """Return (checkpoint_path, checkpoint_data) from the database Settings, session, or fall back to workflow file."""
     ckpt_path = session.get('default_checkpoint')
+    
+    # If no session checkpoint, try to read from database Settings
+    if not ckpt_path:
+        settings = Settings.query.first()
+        if settings and settings.default_checkpoint:
+            ckpt_path = settings.default_checkpoint
+            logger.debug("Loaded default checkpoint from database: %s", ckpt_path)
+    
+    # If still no checkpoint, try to read from the workflow file
+    if not ckpt_path:
+        try:
+            with open('comfy_workflow.json', 'r') as f:
+                workflow = json.load(f)
+            ckpt_path = workflow.get('4', {}).get('inputs', {}).get('ckpt_name')
+            logger.debug("Loaded default checkpoint from workflow file: %s", ckpt_path)
+        except Exception:
+            pass
+    
     if not ckpt_path:
         return None, None
+    
     ckpt = Checkpoint.query.filter_by(checkpoint_path=ckpt_path).first()
     if not ckpt:
-        return None, None
+        # Checkpoint path exists but not in DB - return path with empty data
+        return ckpt_path, {}
     return ckpt.checkpoint_path, ckpt.data or {}
 
 @app.route('/get_missing_characters')
 def get_missing_characters():
-    missing = Character.query.filter((Character.image_path == None) | (Character.image_path == '')).order_by(Character.filename).all()
+    missing = Character.query.filter((Character.image_path == None) | (Character.image_path == '')).order_by(Character.name).all()
     return {'missing': [{'slug': c.slug, 'name': c.name} for c in missing]}
 
 @app.route('/clear_all_covers', methods=['POST'])
@@ -2420,7 +2772,7 @@ def clear_all_covers():
 def generate_missing():
     missing = Character.query.filter(
         (Character.image_path == None) | (Character.image_path == '')
-    ).order_by(Character.filename).all()
+    ).order_by(Character.name).all()
 
     if not missing:
         flash("No characters missing cover images.")
@@ -2490,7 +2842,7 @@ def save_defaults(slug):
 
 @app.route('/get_missing_outfits')
 def get_missing_outfits():
-    missing = Outfit.query.filter((Outfit.image_path == None) | (Outfit.image_path == '')).order_by(Outfit.filename).all()
+    missing = Outfit.query.filter((Outfit.image_path == None) | (Outfit.image_path == '')).order_by(Outfit.name).all()
     return {'missing': [{'slug': o.slug, 'name': o.name} for o in missing]}
 
 @app.route('/clear_all_outfit_covers', methods=['POST'])
@@ -2503,7 +2855,7 @@ def clear_all_outfit_covers():
 
 @app.route('/get_missing_actions')
 def get_missing_actions():
-    missing = Action.query.filter((Action.image_path == None) | (Action.image_path == '')).order_by(Action.filename).all()
+    missing = Action.query.filter((Action.image_path == None) | (Action.image_path == '')).order_by(Action.name).all()
     return {'missing': [{'slug': a.slug, 'name': a.name} for a in missing]}
 
 @app.route('/clear_all_action_covers', methods=['POST'])
@@ -2516,7 +2868,7 @@ def clear_all_action_covers():
 
 @app.route('/get_missing_scenes')
 def get_missing_scenes():
-    missing = Scene.query.filter((Scene.image_path == None) | (Scene.image_path == '')).order_by(Scene.filename).all()
+    missing = Scene.query.filter((Scene.image_path == None) | (Scene.image_path == '')).order_by(Scene.name).all()
     return {'missing': [{'slug': s.slug, 'name': s.name} for s in missing]}
 
 @app.route('/clear_all_scene_covers', methods=['POST'])
@@ -2947,7 +3299,8 @@ def get_missing_presets():
 @app.route('/outfits')
 def outfits_index():
     outfits = Outfit.query.order_by(Outfit.name).all()
-    return render_template('outfits/index.html', outfits=outfits)
+    lora_assignments = _count_outfit_lora_assignments()
+    return render_template('outfits/index.html', outfits=outfits, lora_assignments=lora_assignments)
 
 @app.route('/outfits/rescan', methods=['POST'])
 def rescan_outfits():
@@ -4293,12 +4646,12 @@ def replace_style_cover_from_preview(slug):
 
 @app.route('/get_missing_styles')
 def get_missing_styles():
-    missing = Style.query.filter((Style.image_path == None) | (Style.image_path == '')).order_by(Style.filename).all()
+    missing = Style.query.filter((Style.image_path == None) | (Style.image_path == '')).order_by(Style.name).all()
     return {'missing': [{'slug': s.slug, 'name': s.name} for s in missing]}
 
 @app.route('/get_missing_detailers')
 def get_missing_detailers():
-    missing = Detailer.query.filter((Detailer.image_path == None) | (Detailer.image_path == '')).order_by(Detailer.filename).all()
+    missing = Detailer.query.filter((Detailer.image_path == None) | (Detailer.image_path == '')).order_by(Detailer.name).all()
     return {'missing': [{'slug': d.slug, 'name': d.name} for d in missing]}
 
 @app.route('/clear_all_detailer_covers', methods=['POST'])
@@ -4321,7 +4674,7 @@ def clear_all_style_covers():
 def generate_missing_styles():
     missing = Style.query.filter(
         (Style.image_path == None) | (Style.image_path == '')
-    ).order_by(Style.filename).all()
+    ).order_by(Style.name).all()
 
     if not missing:
         flash("No styles missing cover images.")
@@ -5673,7 +6026,7 @@ def save_checkpoint_json(slug):
 
 @app.route('/get_missing_checkpoints')
 def get_missing_checkpoints():
-    missing = Checkpoint.query.filter((Checkpoint.image_path == None) | (Checkpoint.image_path == '')).order_by(Checkpoint.checkpoint_path).all()
+    missing = Checkpoint.query.filter((Checkpoint.image_path == None) | (Checkpoint.image_path == '')).order_by(Checkpoint.name).all()
     return {'missing': [{'slug': c.slug, 'name': c.name} for c in missing]}
 
 @app.route('/clear_all_checkpoint_covers', methods=['POST'])
@@ -5790,7 +6143,8 @@ def bulk_create_checkpoints():
 @app.route('/looks')
 def looks_index():
     looks = Look.query.order_by(Look.name).all()
-    return render_template('looks/index.html', looks=looks)
+    look_assignments = _count_look_assignments()
+    return render_template('looks/index.html', looks=looks, look_assignments=look_assignments)
 
 @app.route('/looks/rescan', methods=['POST'])
 def rescan_looks():
@@ -6036,7 +6390,7 @@ def create_look():
 
 @app.route('/get_missing_looks')
 def get_missing_looks():
-    missing = Look.query.filter((Look.image_path == None) | (Look.image_path == '')).order_by(Look.filename).all()
+    missing = Look.query.filter((Look.image_path == None) | (Look.image_path == '')).order_by(Look.name).all()
     return {'missing': [{'slug': l.slug, 'name': l.name} for l in missing]}
 
 @app.route('/clear_all_look_covers', methods=['POST'])
@@ -6932,6 +7286,7 @@ if __name__ == '__main__':
             ('lora_dir_scenes',     "VARCHAR(500) DEFAULT '/ImageModels/lora/Illustrious/Backgrounds'"),
             ('lora_dir_detailers',  "VARCHAR(500) DEFAULT '/ImageModels/lora/Illustrious/Detailers'"),
             ('checkpoint_dirs',     "VARCHAR(1000) DEFAULT '/ImageModels/Stable-diffusion/Illustrious,/ImageModels/Stable-diffusion/Noob'"),
+            ('default_checkpoint',  "VARCHAR(500)"),
         ]
         for col_name, col_type in columns_to_add:
             try:
@@ -6950,6 +7305,15 @@ if __name__ == '__main__':
             db.session.commit()
             print("Created default settings")
         
+        # Log the default checkpoint on startup
+        settings = Settings.query.first()
+        if settings and settings.default_checkpoint:
+            logger.info("=" * 80)
+            logger.info("DEFAULT CHECKPOINT loaded from database: %s", settings.default_checkpoint)
+            logger.info("=" * 80)
+        else:
+            logger.info("No default checkpoint set in database")
+        
         sync_characters()
         sync_outfits()
         sync_actions()

comfy_workflow.json

@@ -16,7 +16,7 @@
   },
   "4": {
     "inputs": {
-      "ckpt_name": "Noob/oneObsession_v19Atypical.safetensors"
+      "ckpt_name": ""
     },
     "class_type": "CheckpointLoaderSimple"
   },

data/characters/delinquent_mother_flim13.json

@@ -1,6 +1,6 @@
 {
   "character_id": "delinquent_mother_flim13",
-  "character_name": "Delinquent Mother",
+  "character_name": "Gyaru Mother",
   "identity": {
     "base_specs": "1girl, milf, gyaru, tall",
     "hair": "blonde hair, long hair",

data/characters/kda_all_out_akali.json

@@ -22,7 +22,7 @@
     "default": {
       "full_body": "",
       "headwear": "",
-      "top": "black crop top, blue and silver motorcycle jacket",
+      "top": "black crop top, blue and silver jacket",
       "bottom": "black leather pants",
       "legwear": "",
       "footwear": "blue sneakers",

data/checkpoints/illustrious_zukinewcuteill_newv20.json

@@ -1,11 +1,11 @@
 {
-  "checkpoint_path": "Illustrious/zukiNewCuteILL_newV20.safetensors",
-  "checkpoint_name": "zukiNewCuteILL_newV20.safetensors",
-  "base_positive": "anime",
   "base_negative": "text, logo",
-  "steps": 25,
+  "base_positive": "anime, cute, loli, moe",
   "cfg": 5,
-  "scheduler": "normal",
+  "checkpoint_name": "zukiNewCuteILL_newV20.safetensors",
+  "checkpoint_path": "Illustrious/zukiNewCuteILL_newV20.safetensors",
   "sampler_name": "euler_ancestral",
+  "scheduler": "normal",
+  "steps": 25,
   "vae": "integrated"
 }

data/clothing/golddripnunchaindresslingerieill.json

@@ -1,23 +1,13 @@
 {
-  "outfit_id": "golddripnunchaindresslingerieill",
-  "outfit_name": "Golddripnunchaindresslingerieill",
-  "wardrobe": {
-    "full_body": "revealing nun dress with gold drip accents",
-    "headwear": "nun veil, jewelry",
-    "top": "lingerie top, gold chains",
-    "bottom": "skirt, gold trim",
-    "legwear": "thighhighs, garter straps",
-    "footwear": "heels",
-    "hands": "",
-    "accessories": "gold chains, cross necklace, body chain"
-  },
   "lora": {
-    "lora_name": "Illustrious/Clothing/GoldDripNunChainDressLingerieILL.safetensors",
+    "lora_name": "",
+    "lora_triggers": "",
     "lora_weight": 0.8,
-    "lora_triggers": "GoldDripNunChainDressLingerieILL",
+    "lora_weight_max": 0.8,
-    "lora_weight_min": 0.8,
+    "lora_weight_min": 0.8
-    "lora_weight_max": 0.8
   },
+  "outfit_id": "golddripnunchaindresslingerieill",
+  "outfit_name": "Nun (with Gold)",
   "tags": [
     "nun",
     "veil",
@@ -33,5 +23,15 @@
     "dripping",
     "gold",
     "body_chain"
-  ]
+  ],
+  "wardrobe": {
+    "accessories": "gold chains, cross necklace, body chain",
+    "bottom": "skirt, gold trim",
+    "footwear": "heels",
+    "full_body": "revealing nun dress with gold drip accents",
+    "hands": "",
+    "headwear": "nun veil, jewelry",
+    "legwear": "thighhighs, garter straps",
+    "top": "lingerie top, gold chains"
+  }
 }

data/looks/jn_tron_bonne_illus.json

@@ -1,9 +1,7 @@
 {
+  "character_id": null,
   "look_id": "jn_tron_bonne_illus",
   "look_name": "Jn Tron Bonne Illus",
-  "character_id": "",
-  "positive": "tron_bonne_(mega_man), brown_hair, short_hair, spiked_hair, goggles_on_head, pink_jacket, crop_top, midriff, navel, skull_print, pink_shorts, boots, large_earrings, servbot_(mega_man)",
-  "negative": "pubic hair, 3d, realistic, loli, censored, bad anatomy, sketch, monochrome",
   "lora": {
     "lora_name": "Illustrious/Looks/JN_Tron_Bonne_Illus.safetensors",
     "lora_weight": 0.8,
@@ -11,6 +9,8 @@
     "lora_weight_min": 0.8,
     "lora_weight_max": 0.8
   },
+  "negative": "pubic hair, 3d, realistic, loli, censored, bad anatomy, sketch, monochrome",
+  "positive": "tron_bonne_(mega_man), brown_hair, short_hair, spiked_hair, purple cropped jacket,  pantyhose, metal panties, short pink dress, boots, skull_earrings, servbot_(mega_man)",
   "tags": [
     "tron_bonne_(mega_man)",
     "goggles_on_head",

data/presets/example_01.json

@@ -55,7 +55,7 @@
     }
   },
   "style": {
-    "style_id": null,
+    "style_id": "random",
     "use_lora": true
   },
   "scene": {

data/styles/7b_style.json

@@ -2,8 +2,8 @@
   "style_id": "7b_style",
   "style_name": "7B Dream",
   "style": {
-    "artist_name": "7b_Dream",
+    "artist_name": "7b",
-    "artistic_style": "3d"
+    "artistic_style": "3d, blender, semi-realistic"
   },
   "lora": {
     "lora_name": "Illustrious/Styles/7b-style.safetensors",

data/styles/bckiwi_3d_style_il_2_7_rank16_fp16.json

@@ -1,15 +0,0 @@
-{
-  "style_id": "bckiwi_3d_style_il_2_7_rank16_fp16",
-  "style_name": "Bckiwi 3D Style Il 2 7 Rank16 Fp16",
-  "style": {
-    "artist_name": "",
-    "artistic_style": ""
-  },
-  "lora": {
-    "lora_name": "Illustrious/Styles/BCkiwi_3D_style_IL_2.7_rank16_fp16.safetensors",
-    "lora_weight": 1.0,
-    "lora_triggers": "BCkiwi_3D_style_IL_2.7_rank16_fp16",
-    "lora_weight_min": 1.0,
-    "lora_weight_max": 1.0
-  }
-}

docker-compose.yml

@@ -13,6 +13,9 @@ services:
       # ComfyUI runs on the Docker host
       COMFYUI_URL: http://10.0.0.200:8188     # Compose manages danbooru-mcp — skip the app's auto-start logic
       SKIP_MCP_AUTOSTART: "true"
+      # Enable debug logging
+      FLASK_DEBUG: "1"
+      LOG_LEVEL: "DEBUG"
     volumes:
       # Persistent data
       - ./data:/app/data

models.py

@@ -154,6 +154,8 @@ class Settings(db.Model):
     lora_dir_detailers  = db.Column(db.String(500), default='/ImageModels/lora/Illustrious/Detailers')
     # Checkpoint scan directories (comma-separated list of absolute paths)
     checkpoint_dirs     = db.Column(db.String(1000), default='/ImageModels/Stable-diffusion/Illustrious,/ImageModels/Stable-diffusion/Noob')
+    # Default checkpoint path (persisted across server restarts)
+    default_checkpoint  = db.Column(db.String(500), nullable=True)
 
     def __repr__(self):
         return '<Settings>'

static/style.css

@@ -356,6 +356,34 @@ h5, h6 { color: var(--text); }
   object-fit: cover;
 }
 
+/* Assignment badge — shows count of characters using this resource */
+.assignment-badge {
+  position: absolute;
+  top: 8px;
+  right: 8px;
+  background: linear-gradient(135deg, var(--accent) 0%, var(--accent-dim) 100%);
+  color: #fff;
+  font-size: 0.7rem;
+  font-weight: 700;
+  min-width: 22px;
+  height: 22px;
+  border-radius: 11px;
+  display: flex;
+  align-items: center;
+  justify-content: center;
+  padding: 0 6px;
+  line-height: 1;
+  z-index: 2;
+  box-shadow: 0 2px 8px rgba(0, 0, 0, 0.4);
+  border: 1.5px solid rgba(255, 255, 255, 0.15);
+  transition: transform 0.2s ease, box-shadow 0.2s ease;
+}
+
+.character-card:hover .assignment-badge {
+  transform: scale(1.1);
+  box-shadow: 0 4px 12px rgba(139, 126, 255, 0.5);
+}
+
 /* Generator result container */
 #result-container {
   background-color: var(--bg-raised) !important;

templates/actions/index.html

@@ -160,7 +160,10 @@
             statusText.textContent = `0 / ${jobs.length} done`;
 
             let completed = 0;
+            let currentItem = '';
             await Promise.all(jobs.map(async ({ item, jobId }) => {
+                currentItem = item.name;
+                itemNameText.textContent = `Processing: ${currentItem}`;
                 try {
                     const jobResult = await waitForJob(jobId);
                     if (jobResult.result && jobResult.result.image_url) {

templates/checkpoints/index.html

@@ -115,53 +115,68 @@
             regenAllBtn.disabled = true;
             container.classList.remove('d-none');
 
-            let completed = 0;
+            // Phase 1: Queue all jobs upfront
-            for (const ckpt of missing) {
+            progressBar.style.width = '100%';
-                const percent = Math.round((completed / missing.length) * 100);
+            progressBar.textContent = '';
-                progressBar.style.width = `${percent}%`;
+            progressBar.classList.add('progress-bar-striped', 'progress-bar-animated');
-                progressBar.textContent = `${percent}%`;
-                statusText.textContent = `Batch Generating: ${completed + 1} / ${missing.length}`;
-                ckptNameText.textContent = `Current: ${ckpt.name}`;
             nodeStatus.textContent = 'Queuing…';
-                taskProgressBar.style.width = '100%';
-                taskProgressBar.textContent = '';
-                taskProgressBar.classList.add('progress-bar-striped', 'progress-bar-animated');
 
+            const jobs = [];
+            for (const ckpt of missing) {
+                statusText.textContent = `Queuing ${jobs.length + 1} / ${missing.length}…`;
                 try {
                     const genResp = await fetch(`/checkpoint/${ckpt.slug}/generate`, {
                         method: 'POST',
-                        body: new URLSearchParams({ 'character_slug': '__random__' }),
+                        body: new URLSearchParams({ character_slug: '__random__' }),
                         headers: { 'X-Requested-With': 'XMLHttpRequest' }
                     });
                     const genData = await genResp.json();
-                    currentJobId = genData.job_id;
+                    if (genData.job_id) jobs.push({ item: ckpt, jobId: genData.job_id });
+                } catch (err) {
+                    console.error(`Failed to queue ${ckpt.name}:`, err);
+                }
+            }
 
-                    const jobResult = await waitForJob(currentJobId);
+            // Phase 2: Poll all concurrently
-                    currentJobId = null;
+            progressBar.classList.remove('progress-bar-striped', 'progress-bar-animated');
+            progressBar.style.width = '0%';
+            progressBar.textContent = '0%';
+            statusText.textContent = `0 / ${jobs.length} done`;
 
+            let completed = 0;
+            let currentItem = '';
+            await Promise.all(jobs.map(async ({ item, jobId }) => {
+                currentItem = item.name;
+                ckptNameText.textContent = `Processing: ${currentItem}`;
+                try {
+                    const jobResult = await waitForJob(jobId);
                     if (jobResult.result && jobResult.result.image_url) {
-                        const img = document.getElementById(`img-${ckpt.slug}`);
+                        const img = document.getElementById(`img-${item.slug}`);
-                        const noImgSpan = document.getElementById(`no-img-${ckpt.slug}`);
+                        const noImgSpan = document.getElementById(`no-img-${item.slug}`);
                         if (img) { img.src = jobResult.result.image_url; img.classList.remove('d-none'); }
                         if (noImgSpan) noImgSpan.classList.add('d-none');
                     }
                 } catch (err) {
-                    console.error(`Failed for ${ckpt.name}:`, err);
+                    console.error(`Failed for ${item.name}:`, err);
-                    currentJobId = null;
                 }
                 completed++;
-            }
+                const pct = Math.round((completed / jobs.length) * 100);
+                progressBar.style.width = `${pct}%`;
+                progressBar.textContent = `${pct}%`;
+                statusText.textContent = `${completed} / ${jobs.length} done`;
+            }));
 
             progressBar.style.width = '100%';
             progressBar.textContent = '100%';
-            statusText.textContent = 'Batch Generation Complete!';
+            statusText.textContent = 'Batch Checkpoint Generation Complete!';
             ckptNameText.textContent = '';
             nodeStatus.textContent = 'Done';
+            stepProgressText.textContent = '';
             taskProgressBar.style.width = '0%';
             taskProgressBar.textContent = '';
             batchBtn.disabled = false;
             regenAllBtn.disabled = false;
-            setTimeout(() => { container.classList.add('d-none'); }, 5000);
+            setTimeout(() => container.classList.add('d-none'), 5000);
         }
 
         batchBtn.addEventListener('click', async () => {

templates/detailers/index.html

@@ -162,7 +162,10 @@
             statusText.textContent = `0 / ${jobs.length} done`;
 
             let completed = 0;
+            let currentItem = '';
             await Promise.all(jobs.map(async ({ item, jobId }) => {
+                currentItem = item.name;
+                detailerNameText.textContent = `Processing: ${currentItem}`;
                 try {
                     const jobResult = await waitForJob(jobId);
                     if (jobResult.result && jobResult.result.image_url) {

templates/index.html

@@ -161,7 +161,10 @@
             statusText.textContent = `0 / ${jobs.length} done`;
 
             let completed = 0;
+            let currentItem = '';
             await Promise.all(jobs.map(async ({ item, jobId }) => {
+                currentItem = item.name;
+                charNameText.textContent = `Processing: ${currentItem}`;
                 try {
                     const jobResult = await waitForJob(jobId);
                     if (jobResult.result && jobResult.result.image_url) {

templates/layout.html

@@ -45,6 +45,10 @@
                     <span class="status-dot status-checking"></span>
                     <span class="status-label d-none d-xl-inline">MCP</span>
                 </span>
+                <span id="status-llm" class="service-status" title="LLM" data-bs-toggle="tooltip" data-bs-placement="bottom" data-bs-title="LLM: checking…">
+                    <span class="status-dot status-checking"></span>
+                    <span class="status-label d-none d-xl-inline">LLM</span>
+                </span>
             </div>
         </div>
     </nav>
@@ -343,6 +347,7 @@
         const services = [
             { id: 'status-comfyui', url: '/api/status/comfyui', label: 'ComfyUI' },
             { id: 'status-mcp',     url: '/api/status/mcp',     label: 'Danbooru MCP' },
+            { id: 'status-llm',     url: '/api/status/llm',     label: 'LLM' },
         ];
 
         function setStatus(id, label, ok) {

templates/looks/index.html

@@ -59,6 +59,9 @@
                 <img id="img-{{ look.slug }}" src="" alt="{{ look.name }}" class="d-none">
                 <span id="no-img-{{ look.slug }}" class="text-muted">No Image</span>
                 {% endif %}
+                {% if look_assignments.get(look.look_id, 0) > 0 %}
+                <span class="assignment-badge" title="Assigned to {{ look_assignments.get(look.look_id, 0) }} character(s)">{{ look_assignments.get(look.look_id, 0) }}</span>
+                {% endif %}
             </div>
             <div class="card-body">
                 <h5 class="card-title text-center">{{ look.name }}</h5>
@@ -106,6 +109,22 @@
         const stepProgressText = document.getElementById('current-step-progress');
 
         let currentJobId = null;
+        let queuePollInterval = null;
+
+        async function updateCurrentJobLabel() {
+            try {
+                const resp = await fetch('/api/queue');
+                const data = await resp.json();
+                const processingJob = data.jobs.find(j => j.status === 'processing');
+                if (processingJob) {
+                    itemNameText.textContent = `Processing: ${processingJob.label}`;
+                } else {
+                    itemNameText.textContent = '';
+                }
+            } catch (err) {
+                console.error('Failed to fetch queue:', err);
+            }
+        }
 
         async function waitForJob(jobId) {
             return new Promise((resolve, reject) => {
@@ -136,30 +155,42 @@
             regenAllBtn.disabled = true;
             container.classList.remove('d-none');
 
-            let completed = 0;
+            // Phase 1: Queue all jobs upfront
-            for (const item of missing) {
+            progressBar.style.width = '100%';
-                const percent = Math.round((completed / missing.length) * 100);
+            progressBar.textContent = '';
-                progressBar.style.width = `${percent}%`;
+            progressBar.classList.add('progress-bar-striped', 'progress-bar-animated');
-                progressBar.textContent = `${percent}%`;
+            nodeStatus.textContent = 'Queuing…';
-                statusText.textContent = `Batch Generating Looks: ${completed + 1} / ${missing.length}`;
-                itemNameText.textContent = `Current: ${item.name}`;
-                nodeStatus.textContent = "Queuing…";
-                taskProgressBar.style.width = '100%';
-                taskProgressBar.textContent = '';
-                taskProgressBar.classList.add('progress-bar-striped', 'progress-bar-animated');
 
+            const jobs = [];
+            for (const item of missing) {
+                statusText.textContent = `Queuing ${jobs.length + 1} / ${missing.length}…`;
                 try {
                     const genResp = await fetch(`/look/${item.slug}/generate`, {
                         method: 'POST',
-                        body: new URLSearchParams({ 'action': 'replace' }),
+                        body: new URLSearchParams({ action: 'replace' }),
                         headers: { 'X-Requested-With': 'XMLHttpRequest' }
                     });
                     const genData = await genResp.json();
-                    currentJobId = genData.job_id;
+                    if (genData.job_id) jobs.push({ item, jobId: genData.job_id });
+                } catch (err) {
+                    console.error(`Failed to queue ${item.name}:`, err);
+                }
+            }
 
-                    const jobResult = await waitForJob(currentJobId);
+            // Phase 2: Poll all concurrently
-                    currentJobId = null;
+            progressBar.classList.remove('progress-bar-striped', 'progress-bar-animated');
+            progressBar.style.width = '0%';
+            progressBar.textContent = '0%';
+            statusText.textContent = `0 / ${jobs.length} done`;
 
+            // Start polling queue for current job label
+            queuePollInterval = setInterval(updateCurrentJobLabel, 1000);
+            updateCurrentJobLabel(); // Initial update
+
+            let completed = 0;
+            await Promise.all(jobs.map(async ({ item, jobId }) => {
+                try {
+                    const jobResult = await waitForJob(jobId);
                     if (jobResult.result && jobResult.result.image_url) {
                         const img = document.getElementById(`img-${item.slug}`);
                         const noImgSpan = document.getElementById(`no-img-${item.slug}`);
@@ -168,22 +199,31 @@
                     }
                 } catch (err) {
                     console.error(`Failed for ${item.name}:`, err);
-                    currentJobId = null;
                 }
                 completed++;
+                const pct = Math.round((completed / jobs.length) * 100);
+                progressBar.style.width = `${pct}%`;
+                progressBar.textContent = `${pct}%`;
+                statusText.textContent = `${completed} / ${jobs.length} done`;
+            }));
+
+            // Stop polling queue
+            if (queuePollInterval) {
+                clearInterval(queuePollInterval);
+                queuePollInterval = null;
             }
 
             progressBar.style.width = '100%';
             progressBar.textContent = '100%';
-            statusText.textContent = "Batch Look Generation Complete!";
+            statusText.textContent = 'Batch Look Generation Complete!';
-            itemNameText.textContent = "";
+            itemNameText.textContent = '';
-            nodeStatus.textContent = "Done";
+            nodeStatus.textContent = 'Done';
-            stepProgressText.textContent = "";
+            stepProgressText.textContent = '';
             taskProgressBar.style.width = '0%';
             taskProgressBar.textContent = '';
             batchBtn.disabled = false;
             regenAllBtn.disabled = false;
-            setTimeout(() => { container.classList.add('d-none'); }, 5000);
+            setTimeout(() => container.classList.add('d-none'), 5000);
         }
 
         batchBtn.addEventListener('click', async () => {

templates/outfits/index.html

@@ -59,6 +59,9 @@
                 <img id="img-{{ outfit.slug }}" src="" alt="{{ outfit.name }}" class="d-none">
                 <span id="no-img-{{ outfit.slug }}" class="text-muted">No Image</span>
                 {% endif %}
+                {% if outfit.data.lora and outfit.data.lora.lora_name and lora_assignments.get(outfit.data.lora.lora_name, 0) > 0 %}
+                <span class="assignment-badge" title="Assigned to {{ lora_assignments.get(outfit.data.lora.lora_name, 0) }} character(s)">{{ lora_assignments.get(outfit.data.lora.lora_name, 0) }}</span>
+                {% endif %}
             </div>
             <div class="card-body">
                 <h5 class="card-title text-center">{{ outfit.name }}</h5>
@@ -160,7 +163,10 @@
             statusText.textContent = `0 / ${jobs.length} done`;
 
             let completed = 0;
+            let currentItem = '';
             await Promise.all(jobs.map(async ({ item, jobId }) => {
+                currentItem = item.name;
+                itemNameText.textContent = `Processing: ${currentItem}`;
                 try {
                     const jobResult = await waitForJob(jobId);
                     if (jobResult.result && jobResult.result.image_url) {

templates/scenes/index.html

@@ -160,7 +160,10 @@
             statusText.textContent = `0 / ${jobs.length} done`;
 
             let completed = 0;
+            let currentItem = '';
             await Promise.all(jobs.map(async ({ item, jobId }) => {
+                currentItem = item.name;
+                itemNameText.textContent = `Processing: ${currentItem}`;
                 try {
                     const jobResult = await waitForJob(jobId);
                     if (jobResult.result && jobResult.result.image_url) {

templates/styles/index.html

@@ -160,7 +160,10 @@
             statusText.textContent = `0 / ${jobs.length} done`;
 
             let completed = 0;
+            let currentItem = '';
             await Promise.all(jobs.map(async ({ item, jobId }) => {
+                currentItem = item.name;
+                styleNameText.textContent = `Processing: ${currentItem}`;
                 try {
                     const jobResult = await waitForJob(jobId);
                     if (jobResult.result && jobResult.result.image_url) {