diff --git a/__init__.py b/__init__.py
index fc86acb7..f7415957 100644
--- a/__init__.py
+++ b/__init__.py
@@ -37,3 +37,8 @@
 NODE_DISPLAY_NAME_MAPPINGS.update(
     **nodes_controlnet_union_sdxl.NODE_DISPLAY_NAME_MAPPINGS
 )
+
+from . import mzkolors
+
+NODE_CLASS_MAPPINGS.update(**mzkolors.NODE_CLASS_MAPPINGS)
+NODE_DISPLAY_NAME_MAPPINGS.update(**mzkolors.NODE_DISPLAY_NAME_MAPPINGS)
diff --git a/mzkolors.py b/mzkolors.py
new file mode 100644
index 00000000..629c58e7
--- /dev/null
+++ b/mzkolors.py
@@ -0,0 +1,73 @@
+import os
+import uuid
+
+import torch
+
+from .utils import (
+    decode_and_deserialize,
+    send_post_request,
+    serialize_and_encode,
+    get_api_key,
+)
+
+
+CATEGORY_NAME = "☁️BizyAir/Kolors"
+
+BIZYAIR_SERVER_ADDRESS = os.getenv(
+    "BIZYAIR_SERVER_ADDRESS", "https://api.siliconflow.cn"
+)
+
+
+class BizyAirMZChatGLM3TextEncode:
+    API_URL = f"{BIZYAIR_SERVER_ADDRESS}/supernode/mzkolorschatglm3"
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "text": ("STRING", {"multiline": True, "dynamicPrompts": True}),
+            }
+        }
+
+    RETURN_TYPES = ("CONDITIONING",)
+
+    FUNCTION = "encode"
+    CATEGORY = CATEGORY_NAME
+
+    def encode(self, text):
+        API_KEY = get_api_key()
+        assert len(text) <= 4096, f"the prompt is too long, length: {len(text)}"
+
+        payload = {
+            "text": text,
+        }
+        auth = f"Bearer {API_KEY}"
+        headers = {
+            "accept": "application/json",
+            "content-type": "application/json",
+            "authorization": auth,
+        }
+
+        response: str = send_post_request(
+            self.API_URL, payload=payload, headers=headers
+        )
+        tensors_np = decode_and_deserialize(response)
+
+        ret_conditioning = []
+        for item in tensors_np:
+            t, d = item
+            t_tensor = torch.from_numpy(t)
+            d_dict = {}
+            for k, v in d.items():
+                d_dict[k] = torch.from_numpy(v)
+            ret_conditioning.append([t_tensor, d_dict])
+
+        return (ret_conditioning,)
+
+
+NODE_CLASS_MAPPINGS = {
+    "BizyAirMZChatGLM3TextEncode": BizyAirMZChatGLM3TextEncode,
+}
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "BizyAirMZChatGLM3TextEncode": "☁️BizyAir ChatGLM3 Text Encode",
+}