Merge branch 'logging'

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

app.py

@@ -1,5 +1,6 @@
 import os
 import json
+import logging
 import time
 import re
 import requests
@@ -42,6 +43,16 @@ app.config['SESSION_PERMANENT'] = False
 db.init_app(app)
 Session(app)
 
+# ---------------------------------------------------------------------------
+# Logging
+# ---------------------------------------------------------------------------
+logging.basicConfig(
+    level=logging.INFO,
+    format='%(asctime)s [%(levelname)s] %(name)s: %(message)s',
+    datefmt='%Y-%m-%d %H:%M:%S',
+)
+logger = logging.getLogger('gaze')
+
 # ---------------------------------------------------------------------------
 # Generation Job Queue
 # ---------------------------------------------------------------------------
@@ -78,6 +89,7 @@ def _enqueue_job(label, workflow, finalize_fn):
     with _job_queue_lock:
         _job_queue.append(job)
         _job_history[job['id']] = job
+    logger.info("Job queued: [%s] %s", job['id'][:8], label)
     _queue_worker_event.set()
     return job
 
@@ -104,6 +116,8 @@ def _queue_worker():
             with _job_queue_lock:
                 job['status'] = 'processing'
 
+            logger.info("Job started: [%s] %s", job['id'][:8], job['label'])
+
             try:
                 with app.app_context():
                     # Send workflow to ComfyUI
@@ -114,6 +128,7 @@ def _queue_worker():
                     comfy_id = prompt_response['prompt_id']
                     with _job_queue_lock:
                         job['comfy_prompt_id'] = comfy_id
+                    logger.info("Job [%s] queued in ComfyUI as %s", job['id'][:8], comfy_id)
 
                     # Poll until done (max ~10 minutes)
                     max_retries = 300
@@ -129,15 +144,17 @@ def _queue_worker():
                     if not finished:
                         raise Exception("ComfyUI generation timed out")
 
+                    logger.info("Job [%s] generation complete, finalizing...", job['id'][:8])
                     # Run the finalize callback (saves image to disk / DB)
                     # finalize_fn(comfy_prompt_id, job) — job is passed so callback can store result
                     job['finalize_fn'](comfy_id, job)
 
                 with _job_queue_lock:
                     job['status'] = 'done'
+                logger.info("Job done: [%s] %s", job['id'][:8], job['label'])
 
             except Exception as e:
-                print(f"[Queue] Job {job['id']} failed: {e}")
+                logger.exception("Job failed: [%s] %s — %s", job['id'][:8], job['label'], e)
                 with _job_queue_lock:
                     job['status'] = 'failed'
                     job['error'] = str(e)
@@ -2078,16 +2095,8 @@ def replace_cover_from_preview(slug):
     return redirect(url_for('detail', slug=slug))
 
 def _log_workflow_prompts(label, workflow):
-    """Print the final assembled ComfyUI prompts in a consistent, readable block."""
+    """Log the final assembled ComfyUI prompts in a consistent, readable block."""
     sep = "=" * 72
-    print(f"\n{sep}")
-    print(f"  WORKFLOW PROMPTS  [{label}]")
-    print(sep)
-    print(f"  Checkpoint : {workflow['4']['inputs'].get('ckpt_name', '(not set)')}")
-    print(f"  Seed       : {workflow['3']['inputs'].get('seed', '(not set)')}")
-    print(f"  Resolution : {workflow['5']['inputs'].get('width', '?')} x {workflow['5']['inputs'].get('height', '?')}")
-    print(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', '?')}")
-    # LoRA chain summary
     active_loras = []
     for node_id, label_str in [("16", "char/look"), ("17", "outfit"), ("18", "action"), ("19", "style/detail/scene")]:
         if node_id in workflow:
@@ -2095,16 +2104,26 @@ def _log_workflow_prompts(label, workflow):
             if name:
                 w = 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}")
-    print(f"  LoRAs      : {' | '.join(active_loras) if active_loras else '(none)'}")
-    print(f"  [+] Positive : {workflow['6']['inputs'].get('text', '')}")
-    print(f"  [-] Negative : {workflow['7']['inputs'].get('text', '')}")
     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,
+        f"  Checkpoint : {workflow['4']['inputs'].get('ckpt_name', '(not set)')}",
+        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"  LoRAs      : {' | '.join(active_loras) if active_loras else '(none)'}",
+        f"  [+] Positive : {workflow['6']['inputs'].get('text', '')}",
+        f"  [-] Negative : {workflow['7']['inputs'].get('text', '')}",
+    ]
     if face_text:
-        print(f"  [F] Face     : {face_text}")
+        lines.append(f"  [F] Face     : {face_text}")
     if hand_text:
-        print(f"  [H] Hand     : {hand_text}")
+        lines.append(f"  [H] Hand     : {hand_text}")
-    print(f"{sep}\n")
+    lines.append(sep)
+    logger.info("\n%s", "\n".join(lines))
 
 
 def _prepare_workflow(workflow, character, prompts, checkpoint=None, custom_negative=None, outfit=None, action=None, style=None, detailer=None, scene=None, width=None, height=None, checkpoint_data=None, look=None, fixed_seed=None):
@@ -2150,7 +2169,7 @@ def _prepare_workflow(workflow, character, prompts, checkpoint=None, custom_nega
         workflow["16"]["inputs"]["clip"] = ["4", 1]   # From checkpoint
         model_source = ["16", 0]
         clip_source = ["16", 1]
-        print(f"Character LoRA: {char_lora_name} @ {_w16}")
+        logger.debug("Character LoRA: %s @ %s", char_lora_name, _w16)
     
     # Outfit LoRA (Node 17) - chains from character LoRA or checkpoint
     outfit_lora_data = outfit.data.get('lora', {}) if outfit else {}
@@ -2166,7 +2185,7 @@ def _prepare_workflow(workflow, character, prompts, checkpoint=None, custom_nega
         workflow["17"]["inputs"]["clip"] = clip_source
         model_source = ["17", 0]
         clip_source = ["17", 1]
-        print(f"Outfit LoRA: {outfit_lora_name} @ {_w17}")
+        logger.debug("Outfit LoRA: %s @ %s", outfit_lora_name, _w17)
 
     # Action LoRA (Node 18) - chains from previous LoRA or checkpoint
     action_lora_data = action.data.get('lora', {}) if action else {}
@@ -2182,7 +2201,7 @@ def _prepare_workflow(workflow, character, prompts, checkpoint=None, custom_nega
         workflow["18"]["inputs"]["clip"] = clip_source
         model_source = ["18", 0]
         clip_source = ["18", 1]
-        print(f"Action LoRA: {action_lora_name} @ {_w18}")
+        logger.debug("Action LoRA: %s @ %s", action_lora_name, _w18)
 
     # Style/Detailer/Scene LoRA (Node 19) - chains from previous LoRA or checkpoint
     # Priority: Style > Detailer > Scene (Scene LoRAs are rare but supported)
@@ -2200,7 +2219,7 @@ def _prepare_workflow(workflow, character, prompts, checkpoint=None, custom_nega
         workflow["19"]["inputs"]["clip"] = clip_source
         model_source = ["19", 0]
         clip_source = ["19", 1]
-        print(f"Style/Detailer LoRA: {style_lora_name} @ {_w19}")
+        logger.debug("Style/Detailer LoRA: %s @ %s", style_lora_name, _w19)
 
     # Apply connections to all model/clip consumers
     workflow["3"]["inputs"]["model"] = model_source