Merge branch 'logging'
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
Aodhan Collins
59
app.py
59
app.py
@@ -1,5 +1,6 @@
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import os
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import json
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import logging
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import time
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import re
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import requests
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@@ -42,6 +43,16 @@ app.config['SESSION_PERMANENT'] = False
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db.init_app(app)
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Session(app)
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# ---------------------------------------------------------------------------
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# Logging
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# ---------------------------------------------------------------------------
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logging.basicConfig(
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level=logging.INFO,
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format='%(asctime)s [%(levelname)s] %(name)s: %(message)s',
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datefmt='%Y-%m-%d %H:%M:%S',
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)
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logger = logging.getLogger('gaze')
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# ---------------------------------------------------------------------------
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# Generation Job Queue
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# ---------------------------------------------------------------------------
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@@ -78,6 +89,7 @@ def _enqueue_job(label, workflow, finalize_fn):
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with _job_queue_lock:
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_job_queue.append(job)
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_job_history[job['id']] = job
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logger.info("Job queued: [%s] %s", job['id'][:8], label)
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_queue_worker_event.set()
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return job
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@@ -104,6 +116,8 @@ def _queue_worker():
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with _job_queue_lock:
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job['status'] = 'processing'
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logger.info("Job started: [%s] %s", job['id'][:8], job['label'])
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try:
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with app.app_context():
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# Send workflow to ComfyUI
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@@ -114,6 +128,7 @@ def _queue_worker():
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comfy_id = prompt_response['prompt_id']
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with _job_queue_lock:
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job['comfy_prompt_id'] = comfy_id
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logger.info("Job [%s] queued in ComfyUI as %s", job['id'][:8], comfy_id)
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# Poll until done (max ~10 minutes)
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max_retries = 300
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@@ -129,15 +144,17 @@ def _queue_worker():
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if not finished:
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raise Exception("ComfyUI generation timed out")
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logger.info("Job [%s] generation complete, finalizing...", job['id'][:8])
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# Run the finalize callback (saves image to disk / DB)
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# finalize_fn(comfy_prompt_id, job) — job is passed so callback can store result
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job['finalize_fn'](comfy_id, job)
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with _job_queue_lock:
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job['status'] = 'done'
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logger.info("Job done: [%s] %s", job['id'][:8], job['label'])
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except Exception as e:
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print(f"[Queue] Job {job['id']} failed: {e}")
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logger.exception("Job failed: [%s] %s — %s", job['id'][:8], job['label'], e)
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with _job_queue_lock:
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job['status'] = 'failed'
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job['error'] = str(e)
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@@ -2078,16 +2095,8 @@ def replace_cover_from_preview(slug):
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return redirect(url_for('detail', slug=slug))
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def _log_workflow_prompts(label, workflow):
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"""Print the final assembled ComfyUI prompts in a consistent, readable block."""
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"""Log the final assembled ComfyUI prompts in a consistent, readable block."""
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sep = "=" * 72
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print(f"\n{sep}")
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print(f" WORKFLOW PROMPTS [{label}]")
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print(sep)
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print(f" Checkpoint : {workflow['4']['inputs'].get('ckpt_name', '(not set)')}")
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print(f" Seed : {workflow['3']['inputs'].get('seed', '(not set)')}")
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print(f" Resolution : {workflow['5']['inputs'].get('width', '?')} x {workflow['5']['inputs'].get('height', '?')}")
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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', '?')}")
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# LoRA chain summary
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active_loras = []
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for node_id, label_str in [("16", "char/look"), ("17", "outfit"), ("18", "action"), ("19", "style/detail/scene")]:
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if node_id in workflow:
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@@ -2095,16 +2104,26 @@ def _log_workflow_prompts(label, workflow):
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if name:
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w = workflow[node_id]["inputs"].get("strength_model", "?")
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active_loras.append(f"{label_str}:{name.split('/')[-1]}@{w:.3f}" if isinstance(w, float) else f"{label_str}:{name.split('/')[-1]}@{w}")
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print(f" LoRAs : {' | '.join(active_loras) if active_loras else '(none)'}")
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print(f" [+] Positive : {workflow['6']['inputs'].get('text', '')}")
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print(f" [-] Negative : {workflow['7']['inputs'].get('text', '')}")
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face_text = workflow.get('14', {}).get('inputs', {}).get('text', '')
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hand_text = workflow.get('15', {}).get('inputs', {}).get('text', '')
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lines = [
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sep,
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f" WORKFLOW PROMPTS [{label}]",
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sep,
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f" Checkpoint : {workflow['4']['inputs'].get('ckpt_name', '(not set)')}",
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f" Seed : {workflow['3']['inputs'].get('seed', '(not set)')}",
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f" Resolution : {workflow['5']['inputs'].get('width', '?')} x {workflow['5']['inputs'].get('height', '?')}",
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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', '?')}",
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f" LoRAs : {' | '.join(active_loras) if active_loras else '(none)'}",
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f" [+] Positive : {workflow['6']['inputs'].get('text', '')}",
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f" [-] Negative : {workflow['7']['inputs'].get('text', '')}",
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]
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if face_text:
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print(f" [F] Face : {face_text}")
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lines.append(f" [F] Face : {face_text}")
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if hand_text:
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print(f" [H] Hand : {hand_text}")
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print(f"{sep}\n")
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lines.append(f" [H] Hand : {hand_text}")
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lines.append(sep)
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logger.info("\n%s", "\n".join(lines))
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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):
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@@ -2150,7 +2169,7 @@ def _prepare_workflow(workflow, character, prompts, checkpoint=None, custom_nega
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workflow["16"]["inputs"]["clip"] = ["4", 1] # From checkpoint
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model_source = ["16", 0]
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clip_source = ["16", 1]
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print(f"Character LoRA: {char_lora_name} @ {_w16}")
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logger.debug("Character LoRA: %s @ %s", char_lora_name, _w16)
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# Outfit LoRA (Node 17) - chains from character LoRA or checkpoint
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outfit_lora_data = outfit.data.get('lora', {}) if outfit else {}
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@@ -2166,7 +2185,7 @@ def _prepare_workflow(workflow, character, prompts, checkpoint=None, custom_nega
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workflow["17"]["inputs"]["clip"] = clip_source
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model_source = ["17", 0]
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clip_source = ["17", 1]
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print(f"Outfit LoRA: {outfit_lora_name} @ {_w17}")
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logger.debug("Outfit LoRA: %s @ %s", outfit_lora_name, _w17)
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# Action LoRA (Node 18) - chains from previous LoRA or checkpoint
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action_lora_data = action.data.get('lora', {}) if action else {}
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@@ -2182,7 +2201,7 @@ def _prepare_workflow(workflow, character, prompts, checkpoint=None, custom_nega
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workflow["18"]["inputs"]["clip"] = clip_source
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model_source = ["18", 0]
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clip_source = ["18", 1]
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print(f"Action LoRA: {action_lora_name} @ {_w18}")
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logger.debug("Action LoRA: %s @ %s", action_lora_name, _w18)
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# Style/Detailer/Scene LoRA (Node 19) - chains from previous LoRA or checkpoint
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# Priority: Style > Detailer > Scene (Scene LoRAs are rare but supported)
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@@ -2200,7 +2219,7 @@ def _prepare_workflow(workflow, character, prompts, checkpoint=None, custom_nega
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workflow["19"]["inputs"]["clip"] = clip_source
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model_source = ["19", 0]
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clip_source = ["19", 1]
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print(f"Style/Detailer LoRA: {style_lora_name} @ {_w19}")
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logger.debug("Style/Detailer LoRA: %s @ %s", style_lora_name, _w19)
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# Apply connections to all model/clip consumers
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workflow["3"]["inputs"]["model"] = model_source
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