Add custom nodes, Civitai loras (LFS), and vast.ai setup script

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>

custom_nodes/rgthree-comfy/py/power_prompt_utils.py

@@ -0,0 +1,104 @@
+"""Utilities for Power Prompt nodes."""
+import re
+import os
+import folder_paths
+
+from .log import log_node_warn, log_node_info
+
+
+def get_and_strip_loras(prompt, silent=False, log_node="Power Prompt"):
+  """Collects and strips lora tags from a prompt."""
+  pattern = r'<lora:([^:>]*?)(?::(-?\d*(?:\.\d*)?))?>'
+  lora_paths = folder_paths.get_filename_list('loras')
+
+  matches = re.findall(pattern, prompt)
+
+  loras = []
+  unfound_loras = []
+  skipped_loras = []
+  for match in matches:
+    tag_path = match[0]
+
+    strength = float(match[1] if len(match) > 1 and len(match[1]) else 1.0)
+    if strength == 0:
+      if not silent:
+        log_node_info(log_node, f'Skipping "{tag_path}" with strength of zero')
+      skipped_loras.append({'lora': tag_path, 'strength': strength})
+      continue
+
+    lora_path = get_lora_by_filename(tag_path, lora_paths, log_node=None if silent else log_node)
+    if lora_path is None:
+      unfound_loras.append({'lora': tag_path, 'strength': strength})
+      continue
+
+    loras.append({'lora': lora_path, 'strength': strength})
+
+  return (re.sub(pattern, '', prompt), loras, skipped_loras, unfound_loras)
+
+
+# pylint: disable = too-many-return-statements, too-many-branches
+def get_lora_by_filename(file_path, lora_paths=None, log_node=None):
+  """Returns a lora by filename, looking for exactl paths and then fuzzier matching."""
+  lora_paths = lora_paths if lora_paths is not None else folder_paths.get_filename_list('loras')
+
+  if file_path in lora_paths:
+    return file_path
+
+  lora_paths_no_ext = [os.path.splitext(x)[0] for x in lora_paths]
+
+  # See if we've entered the exact path, but without the extension
+  if file_path in lora_paths_no_ext:
+    found = lora_paths[lora_paths_no_ext.index(file_path)]
+    return found
+
+  # Same check, but ensure file_path is without extension.
+  file_path_force_no_ext = os.path.splitext(file_path)[0]
+  if file_path_force_no_ext in lora_paths_no_ext:
+    found = lora_paths[lora_paths_no_ext.index(file_path_force_no_ext)]
+    return found
+
+  # See if we passed just the name, without paths.
+  lora_filenames_only = [os.path.basename(x) for x in lora_paths]
+  if file_path in lora_filenames_only:
+    found = lora_paths[lora_filenames_only.index(file_path)]
+    if log_node is not None:
+      log_node_info(log_node, f'Matched Lora input "{file_path}" to "{found}".')
+    return found
+
+  # Same, but force the input to be without paths
+  file_path_force_filename = os.path.basename(file_path)
+  lora_filenames_only = [os.path.basename(x) for x in lora_paths]
+  if file_path_force_filename in lora_filenames_only:
+    found = lora_paths[lora_filenames_only.index(file_path_force_filename)]
+    if log_node is not None:
+      log_node_info(log_node, f'Matched Lora input "{file_path}" to "{found}".')
+    return found
+
+  # Check the filenames and without extension.
+  lora_filenames_and_no_ext = [os.path.splitext(os.path.basename(x))[0] for x in lora_paths]
+  if file_path in lora_filenames_and_no_ext:
+    found = lora_paths[lora_filenames_and_no_ext.index(file_path)]
+    if log_node is not None:
+      log_node_info(log_node, f'Matched Lora input "{file_path}" to "{found}".')
+    return found
+
+  # And, one last forcing the input to be the same
+  file_path_force_filename_and_no_ext = os.path.splitext(os.path.basename(file_path))[0]
+  if file_path_force_filename_and_no_ext in lora_filenames_and_no_ext:
+    found = lora_paths[lora_filenames_and_no_ext.index(file_path_force_filename_and_no_ext)]
+    if log_node is not None:
+      log_node_info(log_node, f'Matched Lora input "{file_path}" to "{found}".')
+    return found
+
+  # Finally, super fuzzy, we'll just check if the input exists in the path at all.
+  for index, lora_path in enumerate(lora_paths):
+    if file_path in lora_path:
+      found = lora_paths[index]
+      if log_node is not None:
+        log_node_warn(log_node, f'Fuzzy-matched Lora input "{file_path}" to "{found}".')
+      return found
+
+  if log_node is not None:
+    log_node_warn(log_node, f'Lora "{file_path}" not found, skipping.')
+
+  return None