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Includes 30 custom nodes committed directly, 7 Civitai-exclusive loras stored via Git LFS, and a setup script that installs all dependencies and downloads HuggingFace-hosted models on vast.ai. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
105 lines
4.1 KiB
Python
105 lines
4.1 KiB
Python
"""Utilities for Power Prompt nodes."""
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import re
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import os
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import folder_paths
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from .log import log_node_warn, log_node_info
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def get_and_strip_loras(prompt, silent=False, log_node="Power Prompt"):
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"""Collects and strips lora tags from a prompt."""
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pattern = r'<lora:([^:>]*?)(?::(-?\d*(?:\.\d*)?))?>'
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lora_paths = folder_paths.get_filename_list('loras')
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matches = re.findall(pattern, prompt)
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loras = []
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unfound_loras = []
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skipped_loras = []
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for match in matches:
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tag_path = match[0]
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strength = float(match[1] if len(match) > 1 and len(match[1]) else 1.0)
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if strength == 0:
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if not silent:
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log_node_info(log_node, f'Skipping "{tag_path}" with strength of zero')
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skipped_loras.append({'lora': tag_path, 'strength': strength})
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continue
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lora_path = get_lora_by_filename(tag_path, lora_paths, log_node=None if silent else log_node)
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if lora_path is None:
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unfound_loras.append({'lora': tag_path, 'strength': strength})
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continue
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loras.append({'lora': lora_path, 'strength': strength})
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return (re.sub(pattern, '', prompt), loras, skipped_loras, unfound_loras)
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# pylint: disable = too-many-return-statements, too-many-branches
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def get_lora_by_filename(file_path, lora_paths=None, log_node=None):
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"""Returns a lora by filename, looking for exactl paths and then fuzzier matching."""
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lora_paths = lora_paths if lora_paths is not None else folder_paths.get_filename_list('loras')
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if file_path in lora_paths:
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return file_path
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lora_paths_no_ext = [os.path.splitext(x)[0] for x in lora_paths]
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# See if we've entered the exact path, but without the extension
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if file_path in lora_paths_no_ext:
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found = lora_paths[lora_paths_no_ext.index(file_path)]
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return found
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# Same check, but ensure file_path is without extension.
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file_path_force_no_ext = os.path.splitext(file_path)[0]
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if file_path_force_no_ext in lora_paths_no_ext:
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found = lora_paths[lora_paths_no_ext.index(file_path_force_no_ext)]
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return found
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# See if we passed just the name, without paths.
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lora_filenames_only = [os.path.basename(x) for x in lora_paths]
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if file_path in lora_filenames_only:
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found = lora_paths[lora_filenames_only.index(file_path)]
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if log_node is not None:
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log_node_info(log_node, f'Matched Lora input "{file_path}" to "{found}".')
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return found
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# Same, but force the input to be without paths
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file_path_force_filename = os.path.basename(file_path)
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lora_filenames_only = [os.path.basename(x) for x in lora_paths]
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if file_path_force_filename in lora_filenames_only:
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found = lora_paths[lora_filenames_only.index(file_path_force_filename)]
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if log_node is not None:
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log_node_info(log_node, f'Matched Lora input "{file_path}" to "{found}".')
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return found
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# Check the filenames and without extension.
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lora_filenames_and_no_ext = [os.path.splitext(os.path.basename(x))[0] for x in lora_paths]
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if file_path in lora_filenames_and_no_ext:
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found = lora_paths[lora_filenames_and_no_ext.index(file_path)]
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if log_node is not None:
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log_node_info(log_node, f'Matched Lora input "{file_path}" to "{found}".')
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return found
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# And, one last forcing the input to be the same
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file_path_force_filename_and_no_ext = os.path.splitext(os.path.basename(file_path))[0]
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if file_path_force_filename_and_no_ext in lora_filenames_and_no_ext:
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found = lora_paths[lora_filenames_and_no_ext.index(file_path_force_filename_and_no_ext)]
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if log_node is not None:
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log_node_info(log_node, f'Matched Lora input "{file_path}" to "{found}".')
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return found
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# Finally, super fuzzy, we'll just check if the input exists in the path at all.
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for index, lora_path in enumerate(lora_paths):
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if file_path in lora_path:
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found = lora_paths[index]
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if log_node is not None:
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log_node_warn(log_node, f'Fuzzy-matched Lora input "{file_path}" to "{found}".')
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return found
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if log_node is not None:
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log_node_warn(log_node, f'Lora "{file_path}" not found, skipping.')
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return None
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