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/controlaltai-nodes/flux_controlnet_node.py

@@ -0,0 +1,40 @@
+class FluxControlNetApply:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "conditioning": ("CONDITIONING", ),
+                "control_net": ("CONTROL_NET", ),
+                "image": ("IMAGE", ),
+                "strength": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.01})
+            }
+        }
+
+    RETURN_TYPES = ("CONDITIONING",)
+    FUNCTION = "flux_controlnet"
+    CATEGORY = "ControlAltAI Nodes/Flux"
+
+    def flux_controlnet(self, conditioning, control_net, image, strength):
+        if strength == 0:
+            return (conditioning,)
+
+        c = []
+        control_hint = image.movedim(-1, 1)
+        for t in conditioning:
+            n = [t[0], t[1].copy()]
+            c_net = control_net.copy().set_cond_hint(control_hint, strength)
+            if 'control' in t[1]:
+                c_net.set_previous_controlnet(t[1]['control'])
+            n[1]['control'] = c_net
+            n[1]['control_apply_to_uncond'] = False  # This ensures it's only applied to positive
+            c.append(n)
+        
+        return (c,)
+
+NODE_CLASS_MAPPINGS = {
+    "FluxControlNetApply": FluxControlNetApply,
+}
+
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "FluxControlNetApply": "Flux ControlNet",
+}