775 lines
35 KiB
Python
775 lines
35 KiB
Python
import asyncio
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import json
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import logging
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import time
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import heapq
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from typing import Optional, Any, Dict, Tuple, List, Callable, Set
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from aiohttp import web
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from .database import QueueDatabase
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from PIL import Image
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import os
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import hashlib
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import folder_paths
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from .thumbnail_service import ThumbnailService
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from .queue_hook_manager import QueueHookManager
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from .routes_helper import RoutesHelper
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class PersistentQueueManager:
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"""Coordinator for persistent queue persistence, API handlers, and hooks."""
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def __init__(self):
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self.db: QueueDatabase = QueueDatabase()
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self.thumbs: ThumbnailService = ThumbnailService(max_size=128, quality=60)
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# Default to paused state on startup for safety - user can resume when ready
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self.paused: bool = True
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self.current_job: Optional[Any] = None
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self._installed: bool = False
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self._hooks: Optional[QueueHookManager] = None
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# IDs allowed to run while paused (run-selected mode)
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self._run_selected_remaining: Set[str] = set()
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def initialize(self) -> None:
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"""Install hooks and API routes after PromptServer is created."""
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if self._installed:
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return
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# Import here to avoid circular dependencies
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from server import PromptServer
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# Register on-prompt handler to persist incoming prompts
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PromptServer.instance.add_on_prompt_handler(self._on_prompt)
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# Install queue hooks
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self._hooks = QueueHookManager(
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is_paused_fn=lambda: self.paused,
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on_job_started=lambda prompt_id: self.db.update_job_status(prompt_id, 'running'),
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on_task_done=self._on_task_done_persist,
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should_run_when_paused=self._is_prompt_allowed_while_paused,
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)
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self._hooks.install()
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# Add API routes
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try:
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app = PromptServer.instance.app
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RoutesHelper(app).register(self)
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except Exception as e:
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logging.debug(f"PersistentQueue add routes failed: {e}")
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# Restore pending jobs on startup
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self._schedule_restore_pending_jobs()
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self._installed = True
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# Log initial state
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logging.info("PersistentQueue initialized in PAUSED state. Use UI to resume queue processing.")
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def _on_task_done_persist(self, args: Tuple[Any, Any, Any]) -> None:
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"""Persist history and generate thumbnails before original task_done completes.
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Args:
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args: Tuple of (q_self, item_id, history_result, status) from task_done wrapper.
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"""
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try:
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q_self, item_id, history_result, status = args
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item = q_self.currently_running.get(item_id)
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if item is None:
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return
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prompt_id = item[1]
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prompt = item[2]
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status_str = status.status_str if status is not None else 'success'
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completed = (status.completed if status is not None else True)
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cancelled = isinstance(status_str, str) and status_str.lower() in ('cancelled', 'canceled', 'interrupted', 'cancel')
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new_state = 'completed'
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if not completed:
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new_state = 'interrupted' if cancelled else 'failed'
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# Persist history and thumbnails BEFORE notifying original logic, to avoid UI race
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self.db.update_job_status(prompt_id, new_state, error=None if completed else status_str)
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# Ensure any user-provided rename is reflected in the workflow stored to history
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try:
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if isinstance(prompt, dict):
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# If DB has a more recent renamed workflow JSON, prefer its name field(s)
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db_row = self.db.get_job(prompt_id)
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if db_row and db_row.get('workflow'):
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try:
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db_wf = json.loads(db_row['workflow']) if isinstance(db_row['workflow'], str) else db_row['workflow']
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except Exception:
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db_wf = None
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if isinstance(db_wf, dict):
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def _extract_name(wf):
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try:
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return (wf.get('workflow') or {}).get('name') or wf.get('name')
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except Exception:
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return None
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db_name = _extract_name(db_wf)
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if isinstance(db_name, str) and db_name.strip():
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if isinstance(prompt.get('workflow'), dict):
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prompt['workflow']['name'] = db_name.strip()
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else:
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prompt['name'] = db_name.strip()
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except Exception:
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pass
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history_id = self.db.add_history(
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prompt_id=prompt_id,
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workflow=prompt,
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outputs=history_result.get('outputs', {}),
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status=status_str,
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duration_seconds=None,
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)
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try:
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workflow_json = json.dumps(prompt) if isinstance(prompt, (dict, list)) else str(prompt)
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outputs = history_result.get('outputs', {})
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thumbs = self.thumbs.generate_thumbnails_from_outputs(outputs, workflow_json=workflow_json, extras=None)
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if not thumbs:
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ph = self.thumbs.generate_placeholder_thumbnail(new_state, workflow_json=workflow_json)
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if ph:
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thumbs = [ph]
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if thumbs:
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self.db.save_history_thumbnails(history_id, thumbs)
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except Exception as te:
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logging.debug(f"PersistentQueue: failed to save thumbnails: {te}")
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except Exception as e:
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logging.debug(f"PersistentQueue _on_task_done_persist failed: {e}")
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# After persisting, if we are in run-selected mode, update remaining set
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try:
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q_self, item_id, history_result, status = args
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item = q_self.currently_running.get(item_id)
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if item is not None:
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pid = str(item[1])
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if pid in self._run_selected_remaining:
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self._run_selected_remaining.discard(pid)
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if not self._run_selected_remaining:
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# All selected jobs finished; keep queue paused and clear state
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logging.info("PersistentQueue: Finished all selected jobs; queue remains paused.")
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except Exception:
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pass
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def _on_prompt(self, json_data: Dict[str, Any]) -> Dict[str, Any]:
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try:
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if "prompt" in json_data:
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prompt = json_data["prompt"]
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prompt_id = str(json_data.get("prompt_id")) if json_data.get("prompt_id") else None
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if prompt_id is None:
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import uuid
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prompt_id = uuid.uuid4().hex
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json_data["prompt_id"] = prompt_id
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# Optional: extract suggested name from extra_data
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try:
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extra = json_data.get('extra_data') or {}
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name_hint = None
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if isinstance(extra, dict):
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name_hint = extra.get('pqueue_workflow_name')
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# Build a persistence-only copy with the name; DO NOT mutate json_data['prompt']
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persist_prompt = prompt
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if isinstance(name_hint, str) and name_hint.strip() and isinstance(prompt, dict):
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if isinstance(prompt.get('workflow'), dict):
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persist_prompt = dict(prompt)
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wf = dict(persist_prompt['workflow'])
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wf['name'] = name_hint.strip()
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persist_prompt['workflow'] = wf
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else:
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persist_prompt = dict(prompt)
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persist_prompt['name'] = name_hint.strip()
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else:
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persist_prompt = prompt
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except Exception:
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persist_prompt = prompt
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# Priority scaffold (0 default)
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priority = 0
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self.db.add_job(prompt_id, persist_prompt, priority=priority)
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except Exception as e:
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logging.debug(f"PersistentQueue on_prompt persist failed: {e}")
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return json_data
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def pause_queue(self):
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"""Pause queue execution"""
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self.paused = True
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def resume_queue(self):
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"""Resume queue execution"""
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self.paused = False
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def reorder_job(self, prompt_id: str, new_priority: int):
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"""Change job priority"""
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self.db.update_job_priority(prompt_id, new_priority)
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def _schedule_restore_pending_jobs(self):
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try:
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from server import PromptServer
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loop = PromptServer.instance.loop
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loop.create_task(self._restore_pending_jobs_async())
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except Exception as e:
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logging.debug(f"PersistentQueue schedule restore failed: {e}")
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async def _restore_pending_jobs_async(self):
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from server import PromptServer
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import execution
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server_instance = PromptServer.instance
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pending_jobs = self.db.get_pending_jobs()
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for job in pending_jobs:
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try:
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prompt_id = job["prompt_id"]
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workflow_json = job["workflow"]
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prompt = json.loads(workflow_json) if isinstance(workflow_json, str) else workflow_json
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valid, err, outputs_to_execute, node_errors = await execution.validate_prompt(prompt_id, prompt, None)
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if valid:
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number = server_instance.number
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server_instance.number += 1
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extra_data = {}
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server_instance.prompt_queue.put((number, prompt_id, prompt, extra_data, outputs_to_execute))
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else:
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self.db.update_job_status(prompt_id, 'failed', error=(err or {}).get('message') if isinstance(err, dict) else str(err))
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except Exception as e:
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logging.debug(f"PersistentQueue restore job failed: {e}")
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# API Routes
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async def _api_get_pqueue(self, request: web.Request) -> web.Response:
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from server import PromptServer
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running, queued = PromptServer.instance.prompt_queue.get_current_queue_volatile()
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# Ensure queued list is sorted by execution order (heap array is not fully ordered)
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try:
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queued_sorted = sorted(queued, key=lambda it: (it[0], str(it[1])))
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except Exception:
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queued_sorted = queued
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# Compute per-prompt progress (0..1) using global progress registry when available
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progress_map = {}
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try:
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from comfy_execution.progress import get_progress_state
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reg = get_progress_state()
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if reg is not None and getattr(reg, 'nodes', None) and reg.prompt_id:
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total_max = 0.0
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total_val = 0.0
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for st in reg.nodes.values():
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try:
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mv = float(st.get('max', 1.0) or 1.0)
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vv = float(st.get('value', 0.0) or 0.0)
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except Exception:
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mv = 1.0
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vv = 0.0
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if mv <= 0:
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mv = 1.0
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total_max += mv
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total_val += max(0.0, min(vv, mv))
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frac = (total_val / total_max) if total_max > 0 else 0.0
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progress_map[reg.prompt_id] = max(0.0, min(1.0, frac))
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except Exception:
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pass
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return web.json_response({
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"paused": self.paused,
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"db_pending": self.db.get_pending_jobs(),
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"queue_running": running,
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"queue_pending": queued_sorted,
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"running_progress": progress_map,
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# Provide DB rows for ALL visible queue items (pending + running) so UI
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# can derive labels (including renamed names) even after status changes
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"db_by_id": self._build_db_lookup_for_queue_items(running, queued_sorted),
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})
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def _build_db_lookup_for_queue_items(self, running: List[Tuple], queued: List[Tuple]) -> Dict[str, Dict[str, Any]]:
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"""Return a mapping of prompt_id -> DB row for all running and queued items.
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Includes at least the workflow text so the UI can derive renamed labels.
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"""
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try:
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pids_set: Set[str] = set()
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try:
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for it in running or []:
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try:
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pids_set.add(str(it[1]))
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except Exception:
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pass
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except Exception:
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pass
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try:
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for it in queued or []:
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try:
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pids_set.add(str(it[1]))
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except Exception:
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pass
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except Exception:
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pass
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pids = [pid for pid in pids_set if pid]
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if not pids:
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return {}
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rows: Dict[str, Dict[str, Any]] = {}
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# Prefer a single SQL round-trip
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try:
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with self.db._get_conn() as conn:
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placeholders = ",".join(["?"] * len(pids))
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cur = conn.execute(f"SELECT * FROM queue_items WHERE prompt_id IN ({placeholders})", tuple(pids))
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for r in cur.fetchall():
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try:
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d = dict(r)
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pid = str(d.get('prompt_id')) if d.get('prompt_id') is not None else None
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if pid:
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rows[pid] = d
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except Exception:
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pass
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except Exception:
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# Fallback to per-id lookup if bulk query fails
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for pid in pids:
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try:
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row = self.db.get_job(pid)
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if row:
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rows[pid] = row
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except Exception:
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pass
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return rows
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except Exception:
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return {}
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async def _api_get_history(self, request: web.Request) -> web.Response:
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# Support both simple and paginated calls. Frontend can pass sort/filter + cursor for keyset pagination.
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q = request.rel_url.query
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try:
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limit = int(q.get("limit", "50"))
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except Exception:
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limit = 50
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sort_by = q.get("sort_by") or "id"
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sort_dir = q.get("sort_dir") or "desc"
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# Cursor-based pagination
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cursor_id = None
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cursor_value = None
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try:
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if q.get("cursor_id") is not None:
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cursor_id = int(q.get("cursor_id"))
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except Exception:
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cursor_id = None
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if q.get("cursor_value") is not None:
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cursor_value = q.get("cursor_value")
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status = q.get("status")
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search_q = q.get("q")
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since = q.get("since")
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until = q.get("until")
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try:
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min_duration = float(q.get("min_duration")) if q.get("min_duration") is not None else None
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except Exception:
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min_duration = None
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try:
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max_duration = float(q.get("max_duration")) if q.get("max_duration") is not None else None
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except Exception:
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max_duration = None
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# If only limit is provided and no advanced params, keep legacy behavior
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legacy_mode = (
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(q.keys() <= {"limit"}) or
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(set(q.keys()) == set() )
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)
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if legacy_mode:
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return web.json_response({"history": self.db.list_history(limit=limit)})
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result = self.db.list_history_paginated(
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limit=limit,
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sort_by=sort_by,
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sort_dir=sort_dir,
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cursor_id=cursor_id,
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cursor_value=cursor_value,
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status=status,
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q=search_q,
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since=since,
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until=until,
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min_duration=min_duration,
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max_duration=max_duration,
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)
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return web.json_response(result)
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# _generate_thumbnails_from_outputs removed in favor of ThumbnailService
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async def _api_pause(self, request: web.Request) -> web.Response:
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self.pause_queue()
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return web.json_response({"paused": True})
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async def _api_resume(self, request: web.Request) -> web.Response:
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self.resume_queue()
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return web.json_response({"paused": False})
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async def _api_reorder(self, request: web.Request) -> web.Response:
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try:
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body = await request.json()
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order: List[str] = body.get("order", [])
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self._rebuild_queue_by_prompt_ids(order)
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return web.json_response({"ok": True})
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except Exception as e:
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logging.warning(f"PersistentQueue reorder failed: {e}")
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return web.json_response({"ok": False, "error": str(e)}, status=400)
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async def _api_priority(self, request: web.Request) -> web.Response:
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try:
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body = await request.json()
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prompt_id: str = body.get("prompt_id")
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priority: int = int(body.get("priority"))
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if not prompt_id:
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return web.json_response({"ok": False, "error": "prompt_id required"}, status=400)
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self.db.update_job_priority(prompt_id, priority)
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# Apply DB priority to in-memory queue
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self._apply_priority_to_pending()
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return web.json_response({"ok": True})
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except Exception as e:
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logging.warning(f"PersistentQueue set priority failed: {e}")
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return web.json_response({"ok": False, "error": str(e)}, status=400)
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async def _api_delete(self, request: web.Request) -> web.Response:
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try:
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from server import PromptServer
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body = await request.json()
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prompt_ids: List[str] = body.get("prompt_ids", [])
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q = PromptServer.instance.prompt_queue
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for pid in prompt_ids:
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self.db.remove_job(pid)
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def match(item):
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return item[1] == pid
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q.delete_queue_item(match)
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return web.json_response({"ok": True})
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except Exception as e:
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logging.warning(f"PersistentQueue delete failed: {e}")
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return web.json_response({"ok": False, "error": str(e)}, status=400)
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async def _api_rename(self, request: web.Request) -> web.Response:
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try:
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from server import PromptServer
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body = await request.json()
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prompt_id: str = body.get('prompt_id')
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new_name: str = body.get('name')
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if not prompt_id or new_name is None:
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return web.json_response({"ok": False, "error": "prompt_id and name required"}, status=400)
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# Persist to DB
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ok = self.db.update_job_name(prompt_id, str(new_name))
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if not ok:
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return web.json_response({"ok": False, "error": "job not found"}, status=404)
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# Update in-memory queue copy to reflect quickly
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q = PromptServer.instance.prompt_queue
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with q.mutex:
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for idx, item in enumerate(list(q.queue)):
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try:
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if item[1] == prompt_id:
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# item = (number, prompt_id, prompt, extra_data, outputs_to_execute)
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prompt = item[2]
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if isinstance(prompt, dict):
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if isinstance(prompt.get('workflow'), dict):
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prompt['workflow']['name'] = str(new_name)
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else:
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prompt['name'] = str(new_name)
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q.queue[idx] = (item[0], item[1], prompt, item[3], item[4])
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except Exception:
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pass
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return web.json_response({"ok": True})
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except Exception as e:
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logging.warning(f"PersistentQueue rename failed: {e}")
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return web.json_response({"ok": False, "error": str(e)}, status=400)
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async def _api_run_selected(self, request: web.Request) -> web.Response:
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"""Run selected jobs when queue is paused"""
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try:
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from server import PromptServer
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import execution
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body = await request.json()
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prompt_ids: List[str] = body.get('prompt_ids', [])
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|
|
logging.info(f"PersistentQueue: run_selected called with {len(prompt_ids)} jobs: {prompt_ids}")
|
|
logging.info(f"PersistentQueue: paused state = {self.paused}")
|
|
|
|
if not self.paused:
|
|
return web.json_response({"ok": False, "error": "Queue must be paused to run selected jobs"}, status=400)
|
|
|
|
q = PromptServer.instance.prompt_queue
|
|
server_instance = PromptServer.instance
|
|
|
|
# First, ensure selected jobs are properly loaded into the queue
|
|
executed_ids = []
|
|
selected_items = []
|
|
|
|
# Prepare selected items and determine order by queue number (ascending = top-most first)
|
|
missing_ids: List[str] = []
|
|
with q.mutex:
|
|
# Map current queue items by prompt_id
|
|
queue_by_id = {str(item[1]): item for item in q.queue}
|
|
|
|
selected_set = set(map(str, prompt_ids))
|
|
# Sort selected that are present by their current number descending (newest/bottom first)
|
|
selected_present = [queue_by_id[pid] for pid in selected_set if pid in queue_by_id]
|
|
selected_present_sorted = sorted(selected_present, key=lambda it: it[0])
|
|
executed_ids = [str(it[1]) for it in selected_present_sorted]
|
|
|
|
# Any selected IDs not in queue are missing; handle after lock
|
|
missing_ids = [pid for pid in map(str, prompt_ids) if pid not in queue_by_id]
|
|
|
|
# Load and validate any missing selected from DB (outside of queue lock)
|
|
for prompt_id in missing_ids:
|
|
job = self.db.get_job(prompt_id)
|
|
if not job:
|
|
continue
|
|
try:
|
|
workflow_json = job["workflow"]
|
|
prompt = json.loads(workflow_json) if isinstance(workflow_json, str) else workflow_json
|
|
# Clean rename metadata
|
|
if isinstance(prompt, dict):
|
|
if 'workflow' in prompt and isinstance(prompt['workflow'], dict):
|
|
prompt.pop('workflow', None)
|
|
if 'name' in prompt and isinstance(prompt['name'], str):
|
|
prompt.pop('name', None)
|
|
valid, err, outputs_to_execute, node_errors = await execution.validate_prompt(prompt_id, prompt, None)
|
|
if valid:
|
|
number = server_instance.number
|
|
server_instance.number += 1
|
|
extra_data = {}
|
|
item = (number, prompt_id, prompt, extra_data, outputs_to_execute)
|
|
# Insert this new item at end for now; reorder shortly
|
|
with q.mutex:
|
|
q.queue.append(item)
|
|
heapq.heapify(q.queue)
|
|
executed_ids.append(prompt_id)
|
|
else:
|
|
logging.warning(f"PersistentQueue: Invalid prompt {prompt_id}: {err}")
|
|
except Exception as e:
|
|
logging.error(f"PersistentQueue: Failed to load job {prompt_id}: {e}")
|
|
|
|
# Rebuild queue with selected items first, preserving their relative order by number (desc)
|
|
if executed_ids:
|
|
with q.mutex:
|
|
# Build final selected from current queue and sort by number asc to preserve queue order
|
|
current_by_id = {str(item[1]): item for item in q.queue}
|
|
selected_final = [current_by_id[pid] for pid in executed_ids if pid in current_by_id]
|
|
selected_final_sorted = sorted(selected_final, key=lambda it: it[0])
|
|
selected_ids_final = [str(it[1]) for it in selected_final_sorted]
|
|
self._rebuild_queue_by_prompt_ids(selected_ids_final)
|
|
|
|
# Enable run-selected mode while keeping queue paused so only selected items run
|
|
self._run_selected_remaining = set(map(str, executed_ids))
|
|
logging.info(f"PersistentQueue: Run-selected mode enabled for {len(executed_ids)} jobs; queue remains paused")
|
|
|
|
return web.json_response({"ok": True, "executed": executed_ids})
|
|
except Exception as e:
|
|
logging.error(f"PersistentQueue run selected failed: {e}", exc_info=True)
|
|
return web.json_response({"ok": False, "error": str(e)}, status=500)
|
|
|
|
async def _api_skip_selected(self, request: web.Request) -> web.Response:
|
|
"""Skip selected jobs (remove from queue)"""
|
|
try:
|
|
from server import PromptServer
|
|
body = await request.json()
|
|
prompt_ids: List[str] = body.get('prompt_ids', [])
|
|
|
|
if self.paused:
|
|
return web.json_response({"ok": False, "error": "Queue must be running to skip jobs"}, status=400)
|
|
|
|
q = PromptServer.instance.prompt_queue
|
|
skipped_ids = []
|
|
|
|
for pid in prompt_ids:
|
|
try:
|
|
q.delete(pid)
|
|
self.db.update_job_status(pid, 'cancelled')
|
|
skipped_ids.append(pid)
|
|
except Exception:
|
|
pass
|
|
|
|
return web.json_response({"ok": True, "skipped": skipped_ids})
|
|
except Exception as e:
|
|
logging.warning(f"PersistentQueue skip selected failed: {e}")
|
|
return web.json_response({"ok": False, "error": str(e)}, status=500)
|
|
|
|
def _rebuild_queue_by_prompt_ids(self, selected_ids_in_order: List[str]) -> None:
|
|
"""Promote only the selected prompt_ids to the front and leave others unchanged.
|
|
|
|
The selected_ids_in_order must be in desired execution order (first executes first).
|
|
We assign them numbers lower than any existing number to ensure they run next,
|
|
while keeping all other items' numbers intact to preserve global order.
|
|
"""
|
|
from server import PromptServer
|
|
q = PromptServer.instance.prompt_queue
|
|
with q.mutex:
|
|
# Normalize to strings for safe comparisons
|
|
sel_ids = [str(pid) for pid in selected_ids_in_order]
|
|
pos_map: Dict[str, int] = {pid: idx for idx, pid in enumerate(sel_ids)}
|
|
selected_set = set(sel_ids)
|
|
|
|
# Find current minimum number so we can place selected before it
|
|
try:
|
|
min_num = min((it[0] for it in q.queue), default=0)
|
|
except Exception:
|
|
min_num = 0
|
|
new_num_start = min_num - len(sel_ids)
|
|
|
|
new_items: List[Tuple] = []
|
|
for old in q.queue:
|
|
pid = str(old[1])
|
|
prompt = old[2]
|
|
# Clean rename metadata for all items to avoid accidental drift
|
|
if isinstance(prompt, dict) and ('workflow' in prompt or 'name' in prompt):
|
|
prompt = {k: v for k, v in prompt.items() if k not in ['workflow', 'name']}
|
|
if pid in selected_set:
|
|
idx = pos_map.get(pid, 0)
|
|
new_num = new_num_start + idx
|
|
new_items.append((new_num, old[1], prompt, old[3], old[4]))
|
|
else:
|
|
# Keep existing number to preserve original order
|
|
new_items.append((old[0], old[1], prompt, old[3], old[4]))
|
|
|
|
q.queue = new_items
|
|
heapq.heapify(q.queue)
|
|
q.server.queue_updated()
|
|
try:
|
|
# Nudge workers to pick up newly promoted items immediately
|
|
q.not_empty.notify_all()
|
|
except Exception:
|
|
pass
|
|
|
|
def _is_prompt_allowed_while_paused(self, prompt_id: str) -> bool:
|
|
try:
|
|
return str(prompt_id) in self._run_selected_remaining
|
|
except Exception:
|
|
return False
|
|
|
|
def _apply_priority_to_pending(self) -> None:
|
|
"""Rebuild in-memory queue using DB priority DESC, then created_at ASC."""
|
|
from server import PromptServer
|
|
q = PromptServer.instance.prompt_queue
|
|
pending = self.db.get_pending_jobs()
|
|
# order prompt_ids by priority desc, created_at asc
|
|
ordered_ids = [row["prompt_id"] for row in sorted(pending, key=lambda r: (-int(r.get("priority", 0)), r.get("created_at") or ""))]
|
|
self._rebuild_queue_by_prompt_ids(ordered_ids)
|
|
|
|
def _install_api_routes(self):
|
|
try:
|
|
from server import PromptServer
|
|
app = PromptServer.instance.app
|
|
app.add_routes([
|
|
web.get('/api/pqueue', self._api_get_pqueue),
|
|
web.get('/api/pqueue/history', self._api_get_history),
|
|
web.get('/api/pqueue/history/thumb/{history_id:\\d+}', self._api_get_history_thumb),
|
|
web.get('/api/pqueue/preview', self._api_preview_image),
|
|
web.post('/api/pqueue/pause', self._api_pause),
|
|
web.post('/api/pqueue/resume', self._api_resume),
|
|
web.post('/api/pqueue/reorder', self._api_reorder),
|
|
web.patch('/api/pqueue/priority', self._api_priority),
|
|
web.post('/api/pqueue/delete', self._api_delete),
|
|
web.patch('/api/pqueue/rename', self._api_rename),
|
|
web.post('/api/pqueue/run-selected', self._api_run_selected),
|
|
web.post('/api/pqueue/skip-selected', self._api_skip_selected),
|
|
])
|
|
except Exception as e:
|
|
logging.debug(f"PersistentQueue add routes failed: {e}")
|
|
|
|
async def _api_get_history_thumb(self, request: web.Request) -> web.Response:
|
|
try:
|
|
history_id = int(request.match_info.get('history_id', '0'))
|
|
idx = int(request.rel_url.query.get('idx', '0'))
|
|
row = self.db.get_history_thumbnail(history_id, idx)
|
|
if not row:
|
|
return web.Response(status=404)
|
|
return web.Response(body=row['data'], content_type=row.get('mime') or 'image/webp')
|
|
except Exception:
|
|
return web.Response(status=500)
|
|
|
|
async def _api_preview_image(self, request: web.Request) -> web.Response:
|
|
"""Serve cached previews with embedded workflow metadata if available.
|
|
|
|
Splits concerns into small helpers to keep logic simple (KISS/DRY).
|
|
"""
|
|
try:
|
|
params = self._parse_preview_params(request)
|
|
file = self._resolve_preview_filepath(params)
|
|
if file is None:
|
|
return web.Response(status=400)
|
|
if not os.path.isfile(file):
|
|
return web.Response(status=404)
|
|
|
|
cache_path = self._compute_preview_cache_path(file, params)
|
|
if cache_path and os.path.exists(cache_path):
|
|
return web.FileResponse(cache_path, headers={"Content-Disposition": f"filename=\"{params['filename']}\""})
|
|
|
|
# Render and cache
|
|
cache_path = self._render_and_cache_preview(file, params, cache_path)
|
|
return web.FileResponse(cache_path, headers={"Content-Disposition": f"filename=\"{params['filename']}\""})
|
|
except Exception:
|
|
return web.Response(status=500)
|
|
|
|
def _parse_preview_params(self, request: web.Request) -> Dict[str, Any]:
|
|
preview_q = request.rel_url.query.get('preview', 'webp;50')
|
|
preview_info = preview_q.split(';')
|
|
image_format = preview_info[0] if preview_info else 'webp'
|
|
if image_format not in ['webp', 'jpeg', 'png']:
|
|
image_format = 'webp'
|
|
quality = 90
|
|
if len(preview_info) > 1 and preview_info[-1].isdigit():
|
|
quality = int(preview_info[-1])
|
|
|
|
pid = request.rel_url.query.get('pid')
|
|
return {
|
|
'filename': request.rel_url.query.get('filename'),
|
|
'subfolder': request.rel_url.query.get('subfolder', ''),
|
|
'type': request.rel_url.query.get('type', 'output'),
|
|
'pid': pid,
|
|
'image_format': image_format,
|
|
'quality': quality,
|
|
'workflow_json': self._lookup_workflow_json(pid) if pid else None,
|
|
}
|
|
|
|
def _lookup_workflow_json(self, pid: Optional[str]) -> Optional[str]:
|
|
if not pid:
|
|
return None
|
|
try:
|
|
with self.db._get_conn() as conn:
|
|
cur = conn.execute('SELECT workflow FROM job_history WHERE prompt_id = ? ORDER BY id DESC LIMIT 1', (pid,))
|
|
row = cur.fetchone()
|
|
if row and row['workflow']:
|
|
return row['workflow']
|
|
except Exception:
|
|
pass
|
|
job = self.db.get_job(pid)
|
|
if job:
|
|
return job.get('workflow')
|
|
return None
|
|
|
|
def _resolve_preview_filepath(self, params: Dict[str, Any]) -> Optional[str]:
|
|
base_dir = folder_paths.get_directory_by_type(params.get('type') or 'output')
|
|
if base_dir is None:
|
|
return None
|
|
output_dir = base_dir
|
|
subfolder = params.get('subfolder') or ''
|
|
if subfolder:
|
|
full_output_dir = os.path.join(base_dir, subfolder)
|
|
if os.path.commonpath((os.path.abspath(full_output_dir), base_dir)) != base_dir:
|
|
return None
|
|
output_dir = full_output_dir
|
|
filename = os.path.basename(params.get('filename') or '')
|
|
return os.path.join(output_dir, filename)
|
|
|
|
def _compute_preview_cache_path(self, file: str, params: Dict[str, Any]) -> Optional[str]:
|
|
temp_dir = folder_paths.get_temp_directory()
|
|
cache_dir = os.path.join(temp_dir, 'preview_cache')
|
|
os.makedirs(cache_dir, exist_ok=True)
|
|
wf_hash = hashlib.sha256(((params.get('workflow_json') or '')).encode('utf-8')).hexdigest()[:16]
|
|
stat = os.stat(file)
|
|
cache_key = f"{os.path.abspath(file)}|{stat.st_mtime}|{stat.st_size}|{params['image_format']}|{params['quality']}|{wf_hash}"
|
|
cache_name = hashlib.sha256(cache_key.encode('utf-8')).hexdigest() + f'.{params["image_format"]}'
|
|
return os.path.join(cache_dir, cache_name)
|
|
|
|
def _render_and_cache_preview(self, file: str, params: Dict[str, Any], cache_path: Optional[str]) -> str:
|
|
with Image.open(file) as img:
|
|
save_kwargs: Dict[str, Any] = {"format": params['image_format']}
|
|
if params['image_format'] in ['webp', 'jpeg']:
|
|
save_kwargs['quality'] = params['quality']
|
|
|
|
# Embed metadata
|
|
workflow_json = params.get('workflow_json')
|
|
if params['image_format'] == 'webp':
|
|
self.thumbs.embed_webp_metadata(img, save_kwargs, workflow_json)
|
|
elif params['image_format'] == 'png':
|
|
self.thumbs.embed_png_metadata(img, save_kwargs, workflow_json)
|
|
|
|
img.save(cache_path, **save_kwargs)
|
|
return cache_path
|
|
|
|
|