diff --git a/__init__.py b/__init__.py
index 334761a..dd14aae 100644
--- a/__init__.py
+++ b/__init__.py
@@ -1,5 +1,5 @@
 WEB_DIRECTORY = "js"
-NODE_CLASS_MAPPINGS = {}
+from .nodes import NODE_CLASS_MAPPINGS
 __all__ = ['NODE_CLASS_MAPPINGS']
 
 from aiohttp import ClientSession, web
diff --git a/nodes.py b/nodes.py
new file mode 100644
index 0000000..30b6843
--- /dev/null
+++ b/nodes.py
@@ -0,0 +1,51 @@
+import soundfile as sf
+import requests
+import io
+import numpy as np
+import torch
+
+class AudioLoadPath:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required": { "path": ("STRING", {"default": "X://insert/path/here.mp4"}),
+                              "sample_rate": ("INT", {"default": 22050, "min": 6000, "max": 192000, "step": 1}),
+                              "offset": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 1e6, "step": 0.001}),
+                              "duration": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 1e6, "step": 0.001})}}
+
+    RETURN_TYPES = ("AUDIO", )
+    CATEGORY = "Audio Reactor"
+    FUNCTION = "load"
+
+    def load(self, path: str, sample_rate: int, offset: float, duration: float|None):
+        if duration == 0.0:
+            duration = None
+
+        if path.startswith(('http://', 'https://')):
+            # 对于网络路径，直接从内存加载
+            try:
+                response = requests.get(path)
+                response.raise_for_status()
+                audio_data = io.BytesIO(response.content)
+
+                # 使用 soundfile 从内存中读取音频数据
+                audio, file_sr = sf.read(audio_data)
+
+                # 如果需要重采样
+                if file_sr != sample_rate:
+                    # 这里需要添加重采样逻辑
+                    # 可以使用 librosa.resample 或其他方法
+                    pass
+
+            except Exception as e:
+                raise Exception(f"加载网络音频失败: {str(e)}")
+        else:
+            # 本地文件使用原有的 librosa 方式加载
+            audio, _ = librosa.load(path, sr=sample_rate, offset=offset, duration=duration)
+
+        # 转换为 torch tensor 并调整维度
+        audio = torch.from_numpy(audio)[None,:,None]
+        return (audio,)
+
+NODE_CLASS_MAPPINGS = {
+    "AudioLoadPath": AudioLoadPath,
+}
\ No newline at end of file