fix some missing mappings, add in Checkpoint and VAE selectors

_mappings.py

@@ -5,6 +5,10 @@ from .scheduler import HelperNodes_SchedulerSelector
 
 from .sampler import HelperNodes_SamplerSelector, HelperNodes_SeedSelector
 
+from .conditioning import HelperNodes_CLIPSkip
+
+from .models import HelperNodes_VAESelector, HelperNodes_CheckpointSelector
+
 
 NODE_CLASS_MAPPINGS = {
     "HelperNodes_MultilineStringLiteral": HelperNodes_MultilineStringLiteral,
@@ -15,6 +19,8 @@ NODE_CLASS_MAPPINGS = {
     "HelperNodes_SchedulerSelector": HelperNodes_SchedulerSelector,
     "HelperNodes_SamplerSelector": HelperNodes_SamplerSelector,
     "HelperNodes_SeedSelector": HelperNodes_SeedSelector,
+    "HelperNodes_CheckpointSelector": HelperNodes_CheckpointSelector,
+    "HelperNodes_VAESelector": HelperNodes_VAESelector,
 }
 
 NODE_DISPLAY_NAME_MAPPINGS = {
@@ -23,7 +29,9 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "HelperNodes_Steps": "Steps",
     "HelperNodes_CfgScale": "CFG Scale",
     "HelperNodes_WidthHeight": "Image Dimensions",
-    "HelperNodes_SchedulerSelector": "Scheduler",
-    "HelperNodes_SamplerSelector": "Sampler",
+    "HelperNodes_SchedulerSelector": "Scheduler Selector",
+    "HelperNodes_SamplerSelector": "Sampler Selector",
     "HelperNodes_SeedSelector": "Seed",
+    "HelperNodes_CheckpointSelector": "Checkpoint Selector",
+    "HelperNodes_VAESelector": "VAE Selector",
 }

models.py

@@ -0,0 +1,101 @@
+from .base import BaseNode, GLOBAL_CATEGORY
+
+import comfy.utils
+import folder_paths
+
+MODULE_CATEGORY = f"{GLOBAL_CATEGORY}/models"
+
+
+class HelperNodes_CheckpointSelector(BaseNode):
+    """
+    Simple selector node that allows the selection of Checkpoint/Model.
+
+    This should then be passed into either a conditioner or into a LoRA loader.
+
+    Does not include LoRA selection, which is done in the standard Load LoRA nodes.
+    """
+    @classmethod
+    def INPUT_TYPES(cls) -> dict:
+        return {
+            "required": {
+                "chkpt_name": (folder_paths.get_filename_list("checkpoints"),)
+            }
+        }
+
+    CATEGORY = MODULE_CATEGORY
+
+    RETURN_TYPES = (folder_paths.get_filename_list("checkpoints"),)
+    RETURN_NAMES = ("chkpt_name",)
+
+    def process(self, chkpt_name) -> tuple:
+        return (chkpt_name,)
+
+
+class HelperNodes_VAESelector(BaseNode):
+    """
+    Simple selector node that allows the selection of VAEs.
+
+    This should then be passed to a VAE decoder node as it returns a VAE.
+    """
+
+    @staticmethod
+    def vae_list():
+        # Borrowed verbatim from comfyui's implementations.
+        vaes = folder_paths.get_filename_list("vae")
+        approx_vaes = folder_paths.get_filename_list("vae_approx")
+        sdxl_taesd_enc = False
+        sdxl_taesd_dec = False
+        sd1_taesd_enc = False
+        sd1_taesd_dec = False
+
+        for v in approx_vaes:
+            if v.startswith("taesd_decoder."):
+                sd1_taesd_dec = True
+            elif v.startswith("taesd_encoder."):
+                sd1_taesd_enc = True
+            elif v.startswith("taesdxl_decoder."):
+                sdxl_taesd_dec = True
+            elif v.startswith("taesdxl_encoder."):
+                sdxl_taesd_enc = True
+        if sd1_taesd_dec and sd1_taesd_enc:
+            vaes.append("taesd")
+        if sdxl_taesd_dec and sdxl_taesd_enc:
+            vaes.append("taesdxl")
+        return vaes
+
+    @staticmethod
+    def load_taesd(name):
+        # Borrowed verbatim from comfyui's implementations
+        sd = {}
+        approx_vaes = folder_paths.get_filename_list("vae_approx")
+
+        encoder = next(filter(lambda a: a.startswith("{}_encoder.".format(name)), approx_vaes))
+        decoder = next(filter(lambda a: a.startswith("{}_decoder.".format(name)), approx_vaes))
+
+        enc = comfy.utils.load_torch_file(folder_paths.get_full_path("vae_approx", encoder))
+        for k in enc:
+            sd["taesd_encoder.{}".format(k)] = enc[k]
+
+        dec = comfy.utils.load_torch_file(folder_paths.get_full_path("vae_approx", decoder))
+        for k in dec:
+            sd["taesd_decoder.{}".format(k)] = dec[k]
+
+        if name == "taesd":
+            sd["vae_scale"] = torch.tensor(0.18215)
+        elif name == "taesdxl":
+            sd["vae_scale"] = torch.tensor(0.13025)
+        return sd
+
+    CATEGORY = f"{MODULE_CATEGORY}"
+
+    RETURN_TYPES = ("VAE",)
+    RETURN_NAMES = ("VAE",)
+
+    def process(self, vae_name) -> tuple:
+        if vae_name in ["taesd", "taesdxl"]:
+            sd = self.load_taesd(vae_name)
+        else:
+            vae_path = folder_paths.get_full_path("vae", vae_name)
+            sd = comfy.utils.load_torch_file(vae_path)
+        vae = comfy.sd.VAE(sd=sd)
+        return (vae,)