mirror of
https://github.com/comfyanonymous/ComfyUI.git
synced 2026-01-09 13:50:49 +08:00
backends and other changes - remove uv.lock since it will not be used in most cases for installation - add cli args to prevent some custom nodes from installing packages at runtime - temp directories can now be shared between workers without being deleted - propcache yanked is now in the dependencies - fix configuration arguments loading in some tests
330 lines
12 KiB
Python
330 lines
12 KiB
Python
import asyncio
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import contextvars
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import gc
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import logging
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import os
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import shutil
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import threading
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import time
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from pathlib import Path
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from typing import Optional
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# main_pre must be the earliest import
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from .main_pre import tracer
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from ..cli_args_types import Configuration
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from ..component_model.file_counter import cleanup_temp as fc_cleanup_temp
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from ..execution_context import current_execution_context
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from . import hook_breaker_ac10a0
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from .extra_model_paths import load_extra_path_config
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from .. import model_management
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from ..analytics.analytics import initialize_event_tracking
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from ..cmd import cuda_malloc
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from ..cmd import folder_paths
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from ..cmd import server as server_module
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from ..component_model.abstract_prompt_queue import AbstractPromptQueue
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from ..component_model.entrypoints_common import configure_application_paths, executor_from_args
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from ..distributed.distributed_prompt_queue import DistributedPromptQueue
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from ..distributed.server_stub import ServerStub
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from ..nodes.package import import_all_nodes_in_workspace
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from ..nodes_context import get_nodes
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logger = logging.getLogger(__name__)
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def cuda_malloc_warning():
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device = model_management.get_torch_device()
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device_name = model_management.get_torch_device_name(device)
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cuda_malloc_warning = False
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if "cudaMallocAsync" in device_name:
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for b in cuda_malloc.blacklist:
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if b in device_name:
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cuda_malloc_warning = True
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if cuda_malloc_warning:
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logger.warning(
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"\nWARNING: this card most likely does not support cuda-malloc, if you get \"CUDA error\" please run ComfyUI with: --disable-cuda-malloc\n")
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def prompt_worker(q: AbstractPromptQueue, server_instance: server_module.PromptServer):
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asyncio.run(_prompt_worker(q, server_instance))
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async def _prompt_worker(q: AbstractPromptQueue, server_instance: server_module.PromptServer):
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from ..cmd import execution
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from ..component_model import queue_types
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from .. import model_management
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args = current_execution_context().configuration
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cache_type = execution.CacheType.CLASSIC
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if args.cache_lru > 0:
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cache_type = execution.CacheType.LRU
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elif args.cache_none:
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cache_type = execution.CacheType.DEPENDENCY_AWARE
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e = execution.PromptExecutor(server_instance, cache_type=cache_type, cache_size=args.cache_lru)
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last_gc_collect = 0
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need_gc = False
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gc_collect_interval = 10.0
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current_time = 0.0
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while True:
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timeout = 1000.0
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if need_gc:
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timeout = max(gc_collect_interval - (current_time - last_gc_collect), 0.0)
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queue_item = q.get(timeout=timeout)
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if queue_item is not None:
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item, item_id = queue_item
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execution_start_time = time.perf_counter()
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prompt_id = item[1]
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server_instance.last_prompt_id = prompt_id
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await e.execute_async(item[2], prompt_id, item[3], item[4])
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need_gc = True
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q.task_done(item_id,
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e.history_result,
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status=queue_types.ExecutionStatus(
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status_str='success' if e.success else 'error',
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completed=e.success,
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messages=e.status_messages))
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if server_instance.client_id is not None:
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server_instance.send_sync("executing", {"node": None, "prompt_id": prompt_id},
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server_instance.client_id)
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current_time = time.perf_counter()
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execution_time = current_time - execution_start_time
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# Log Time in a more readable way after 10 minutes
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if execution_time > 600:
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execution_time = time.strftime("%H:%M:%S", time.gmtime(execution_time))
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logger.info(f"Prompt executed in {execution_time}")
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else:
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logger.info("Prompt executed in {:.2f} seconds".format(execution_time))
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flags = q.get_flags()
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free_memory = flags.get("free_memory", False)
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if flags.get("unload_models", free_memory):
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model_management.unload_all_models()
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need_gc = True
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last_gc_collect = 0
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if free_memory:
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e.reset()
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need_gc = True
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last_gc_collect = 0
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if need_gc:
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current_time = time.perf_counter()
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if (current_time - last_gc_collect) > gc_collect_interval:
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gc.collect()
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model_management.soft_empty_cache()
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last_gc_collect = current_time
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need_gc = False
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hook_breaker_ac10a0.restore_functions()
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async def run(server_instance, address='', port=8188, verbose=True, call_on_start=None):
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addresses = []
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for addr in address.split(","):
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addresses.append((addr, port))
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await asyncio.gather(server_instance.start_multi_address(addresses, call_on_start), server_instance.publish_loop())
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def cleanup_temp():
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try:
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folder_paths.get_temp_directory()
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temp_dir = folder_paths.get_temp_directory()
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if os.path.exists(temp_dir):
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shutil.rmtree(temp_dir, ignore_errors=True)
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except NameError:
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# __file__ was not defined
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pass
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def start_comfyui(asyncio_loop: asyncio.AbstractEventLoop = None):
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asyncio_loop = asyncio_loop or asyncio.get_event_loop()
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asyncio_loop.run_until_complete(_start_comfyui())
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def setup_database():
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from ..app.database.db import dependencies_available, init_db
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if dependencies_available():
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init_db()
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async def _start_comfyui(from_script_dir: Optional[Path] = None, configuration: Optional[Configuration] = None):
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from ..execution_context import context_configuration
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from ..cli_args import cli_args_configuration
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configuration = configuration or cli_args_configuration()
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with (
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context_configuration(configuration),
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fc_cleanup_temp()
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):
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await __start_comfyui(from_script_dir=from_script_dir)
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async def __start_comfyui(from_script_dir: Optional[Path] = None):
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"""
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Runs ComfyUI's frontend and backend like upstream.
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:param from_script_dir: when set to a path, assumes that you are running ComfyUI's legacy main.py entrypoint at the root of the git repository located at the path
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"""
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args = current_execution_context().configuration
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if not from_script_dir:
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os_getcwd = os.getcwd()
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else:
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os_getcwd = str(from_script_dir)
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if args.temp_directory:
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temp_dir = os.path.join(os.path.abspath(args.temp_directory), "temp")
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logger.debug(f"Setting temp directory to: {temp_dir}")
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folder_paths.set_temp_directory(temp_dir)
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if args.user_directory:
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user_dir = os.path.abspath(args.user_directory)
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logger.info(f"Setting user directory to: {user_dir}")
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folder_paths.set_user_directory(user_dir)
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# configure extra model paths earlier
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try:
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extra_model_paths_config_path = os.path.join(os_getcwd, "extra_model_paths.yaml")
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if os.path.isfile(extra_model_paths_config_path):
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load_extra_path_config(extra_model_paths_config_path)
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except NameError:
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pass
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if args.extra_model_paths_config:
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for config_path in args.extra_model_paths_config:
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load_extra_path_config(config_path)
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if args.create_directories:
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# then, import and exit
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import_all_nodes_in_workspace(raise_on_failure=False)
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folder_paths.create_directories()
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exit(0)
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elif args.quick_test_for_ci:
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import_all_nodes_in_workspace(raise_on_failure=True)
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exit(0)
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if args.windows_standalone_build:
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try:
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from . import new_updater
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new_updater.update_windows_updater()
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except:
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pass
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loop = asyncio.get_event_loop()
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server = server_module.PromptServer(loop)
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if args.external_address is not None:
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server.external_address = args.external_address
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# at this stage, it's safe to import nodes
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hook_breaker_ac10a0.save_functions()
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nodes_to_import = get_nodes()
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logger.debug(f"Imported {len(nodes_to_import)} nodes")
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server.nodes = nodes_to_import
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hook_breaker_ac10a0.restore_functions()
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# as a side effect, this also populates the nodes for execution
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if args.distributed_queue_connection_uri is not None:
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distributed = True
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q = DistributedPromptQueue(
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caller_server=server if args.distributed_queue_frontend else None,
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connection_uri=args.distributed_queue_connection_uri,
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is_caller=args.distributed_queue_frontend,
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is_callee=args.distributed_queue_worker,
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loop=loop,
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queue_name=args.distributed_queue_name
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)
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await q.init()
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else:
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distributed = False
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from .execution import PromptQueue
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q = PromptQueue(server)
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server.prompt_queue = q
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server.add_routes()
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cuda_malloc_warning()
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setup_database()
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# in a distributed setting, the default prompt worker will not be able to send execution events via the websocket
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worker_thread_server = server if not distributed else ServerStub()
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if not distributed or args.distributed_queue_worker:
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if distributed:
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logger.warning(
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f"Distributed workers started in the default thread loop cannot notify clients of progress updates. Instead of comfyui or main.py, use comfyui-worker.")
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# todo: this should really be using an executor instead of doing things this jankilicious way
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ctx = contextvars.copy_context()
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threading.Thread(target=lambda _q, _worker_thread_server: ctx.run(prompt_worker, _q, _worker_thread_server),
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daemon=True, args=(q, worker_thread_server,)).start()
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# server has been imported and things should be looking good
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initialize_event_tracking(loop)
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if args.output_directory:
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output_dir = os.path.abspath(args.output_directory)
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logger.debug(f"Setting output directory to: {output_dir}")
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folder_paths.set_output_directory(output_dir)
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# These are the default folders that checkpoints, clip and vae models will be saved to when using CheckpointSave, etc.. nodes
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folder_paths.add_model_folder_path("checkpoints", os.path.join(folder_paths.get_output_directory(), "checkpoints"))
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folder_paths.add_model_folder_path("clip", os.path.join(folder_paths.get_output_directory(), "clip"))
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folder_paths.add_model_folder_path("vae", os.path.join(folder_paths.get_output_directory(), "vae"))
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folder_paths.add_model_folder_path("diffusion_models",
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os.path.join(folder_paths.get_output_directory(), "diffusion_models"))
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folder_paths.add_model_folder_path("loras", os.path.join(folder_paths.get_output_directory(), "loras"))
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if args.input_directory:
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input_dir = os.path.abspath(args.input_directory)
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logger.debug(f"Setting input directory to: {input_dir}")
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folder_paths.set_input_directory(input_dir)
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# now that nodes are loaded, create directories
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folder_paths.create_directories()
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if len(args.workflows) > 0:
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configure_application_paths(args)
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executor = await executor_from_args(args)
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from ..entrypoints.workflow import run_workflows
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await run_workflows(executor, args.workflows)
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return
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# replaced my folder_paths.create_directories
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call_on_start = None
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if args.auto_launch:
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def startup_server(scheme="http", address="localhost", port=8188):
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import webbrowser
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if os.name == 'nt' and address == '0.0.0.0' or address == '':
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address = '127.0.0.1'
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if ':' in address:
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address = "[{}]".format(address)
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webbrowser.open(f"{scheme}://{address}:{port}")
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call_on_start = startup_server
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first_listen_addr = args.listen.split(',')[0] if ',' in args.listen else args.listen
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server.address = first_listen_addr
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server.port = args.port
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try:
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await server.setup()
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await run(server, address=first_listen_addr, port=args.port, verbose=not args.dont_print_server,
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call_on_start=call_on_start)
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except (asyncio.CancelledError, KeyboardInterrupt):
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logger.debug("Stopped server")
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finally:
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if distributed:
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await q.close()
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def entrypoint():
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try:
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asyncio.run(_start_comfyui())
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except KeyboardInterrupt:
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logger.info(f"Gracefully shutting down due to KeyboardInterrupt")
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def main():
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entrypoint()
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if __name__ == "__main__":
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entrypoint()
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