From f024492f81fce4f2ac0650e3e356e618559da8d6 Mon Sep 17 00:00:00 2001
From: Talmaj <Talmaj@users.noreply.github.com>
Date: Thu, 9 Jul 2026 15:29:06 +0200
Subject: [PATCH] New Lora nodes using DynamicGroup widget (CORE-186) (#14655)

---
 comfy_extras/nodes_lora_stack.py | 107 +++++++++++++++++++++++++++++++
 nodes.py                         |   1 +
 2 files changed, 108 insertions(+)
 create mode 100644 comfy_extras/nodes_lora_stack.py

diff --git a/comfy_extras/nodes_lora_stack.py b/comfy_extras/nodes_lora_stack.py
new file mode 100644
index 000000000..61ce1c0b8
--- /dev/null
+++ b/comfy_extras/nodes_lora_stack.py
@@ -0,0 +1,107 @@
+from __future__ import annotations
+
+from typing_extensions import override
+
+import comfy.sd
+import comfy.utils
+import folder_paths
+from comfy_api.latest import ComfyExtension, io
+
+
+def _load_lora_file(lora_name: str):
+    lora_path = folder_paths.get_full_path_or_raise("loras", lora_name)
+    return comfy.utils.load_torch_file(lora_path, safe_load=True, return_metadata=True)
+
+
+def _lora_template() -> list[io.Input]:
+    return [
+        io.Combo.Input("lora_name", options=folder_paths.get_filename_list("loras"),
+                       tooltip="The name of the LoRA file to apply."),
+        io.Float.Input("strength", default=1.0, min=-100.0, max=100.0, step=0.01,
+                       tooltip="How strongly to apply this LoRA. 0 = off, negative inverts the effect."),
+    ]
+
+
+class LoadLoraModel(io.ComfyNode):
+    @classmethod
+    def define_schema(cls):
+        return io.Schema(
+            node_id="LoadLoraModel",
+            display_name="Load LoRA (Model)",
+            search_aliases=["lora", "load lora", "apply lora", "lora model", "lora stack"],
+            category="model/loaders",
+            description="Apply a stack of LoRAs to a diffusion model. Add one row per LoRA; "
+                        "each row picks a LoRA file and its strength.",
+            inputs=[
+                io.Model.Input("model", tooltip="The diffusion model the LoRAs will be applied to."),
+                io.DynamicGroup.Input(
+                    "loras",
+                    template=_lora_template(),
+                    min=1,
+                    max=50,
+                    tooltip="Each row applies one LoRA to the model.",
+                    group_name="LoRA",
+                ),
+            ],
+            outputs=[io.Model.Output(tooltip="The modified diffusion model.")],
+        )
+
+    @classmethod
+    def execute(cls, model, loras: list[dict]) -> io.NodeOutput:
+        for row in loras:
+            lora_name = row.get("lora_name")
+            strength = row.get("strength", 1.0)
+            if not lora_name or lora_name == "none" or strength == 0:
+                continue
+            lora, metadata = _load_lora_file(lora_name)
+            model, _ = comfy.sd.load_lora_for_models(model, None, lora, strength, 0, lora_metadata=metadata)
+        return io.NodeOutput(model)
+
+
+class LoadLoraTextEncoder(io.ComfyNode):
+    @classmethod
+    def define_schema(cls):
+        return io.Schema(
+            node_id="LoadLoraTextEncoder",
+            display_name="Load LoRA (Text Encoder)",
+            search_aliases=["lora", "load lora", "apply lora", "clip lora", "lora stack"],
+            category="model/loaders",
+            description="Apply a stack of LoRAs to a CLIP text encoder. Add one row per LoRA; "
+                        "each row picks a LoRA file and its strength.",
+            inputs=[
+                io.Clip.Input("clip", tooltip="The CLIP text encoder the LoRAs will be applied to."),
+                io.DynamicGroup.Input(
+                    "loras",
+                    template=_lora_template(),
+                    min=1,
+                    max=50,
+                    tooltip="Each row applies one LoRA to the text encoder.",
+                    group_name="LoRA",
+                ),
+            ],
+            outputs=[io.Clip.Output(tooltip="The modified CLIP text encoder.")],
+        )
+
+    @classmethod
+    def execute(cls, clip, loras: list[dict]) -> io.NodeOutput:
+        for row in loras:
+            lora_name = row.get("lora_name")
+            strength = row.get("strength", 1.0)
+            if not lora_name or lora_name == "none" or strength == 0:
+                continue
+            lora, metadata = _load_lora_file(lora_name)
+            _, clip = comfy.sd.load_lora_for_models(None, clip, lora, 0, strength, lora_metadata=metadata)
+        return io.NodeOutput(clip)
+
+
+class LoraStackExtension(ComfyExtension):
+    @override
+    async def get_node_list(self) -> list[type[io.ComfyNode]]:
+        return [
+            LoadLoraModel,
+            LoadLoraTextEncoder,
+        ]
+
+
+async def comfy_entrypoint() -> LoraStackExtension:
+    return LoraStackExtension()
diff --git a/nodes.py b/nodes.py
index 9043a8d0a..c881444fc 100644
--- a/nodes.py
+++ b/nodes.py
@@ -2502,6 +2502,7 @@ async def init_builtin_extra_nodes():
         "nodes_triposplat.py",
         "nodes_depth_anything_3.py",
         "nodes_seed.py",
+        "nodes_lora_stack.py",
     ]
 
     import_failed = []