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/dynamic_context.py

@@ -0,0 +1,56 @@
+"""The Dynamic Context node."""
+from mimetypes import add_type
+from .constants import get_category, get_name
+from .utils import ByPassTypeTuple, FlexibleOptionalInputType
+
+
+class RgthreeDynamicContext:
+  """The Dynamic Context node.
+
+  Similar to the static Context and Context Big nodes, this allows users to add any number and
+  variety of inputs to a Dynamic Context node, and return the outputs by key name.
+  """
+
+  NAME = get_name("Dynamic Context")
+  CATEGORY = get_category()
+
+  @classmethod
+  def INPUT_TYPES(cls):  # pylint: disable = invalid-name,missing-function-docstring
+    return {
+      "required": {},
+      "optional": FlexibleOptionalInputType(add_type),
+      "hidden": {},
+    }
+
+  RETURN_TYPES = ByPassTypeTuple(("RGTHREE_DYNAMIC_CONTEXT",))
+  RETURN_NAMES = ByPassTypeTuple(("CONTEXT",))
+  FUNCTION = "main"
+
+  def main(self, **kwargs):
+    """Creates a new context from the provided data, with an optional base ctx to start.
+
+    This node takes a list of named inputs that are the named keys (with an optional "+ " prefix)
+    which are to be stored within the ctx dict as well as a list of keys contained in `output_keys`
+    to determine the list of output data.
+    """
+
+    base_ctx = kwargs.get('base_ctx', None)
+    output_keys = kwargs.get('output_keys', None)
+
+    new_ctx = base_ctx.copy() if base_ctx is not None else {}
+
+    for key_raw, value in kwargs.items():
+      if key_raw in ['base_ctx', 'output_keys']:
+        continue
+      key = key_raw.upper()
+      if key.startswith('+ '):
+        key = key[2:]
+      new_ctx[key] = value
+
+    print(new_ctx)
+
+    res = [new_ctx]
+    output_keys = output_keys.split(',') if output_keys is not None else []
+    for key in output_keys:
+      res.append(new_ctx[key] if key in new_ctx else None)
+    return tuple(res)