Publish current ComfyUI O1Key code baseline

Replace the prior release tree with the current plugin, frontend, tests, and documentation. Document retired node IDs and the public Gitea update source.

nodes/grid_splitter.py

@@ -8,6 +8,7 @@ separator bands near the expected grid lines, then crops each cell.
 
 from __future__ import annotations
 
+import os
 from dataclasses import dataclass
 from typing import List, Sequence, Tuple
 
@@ -327,6 +328,30 @@ def _split_one(
     return crops, info
 
 
+_IMAGE_EXTS = (".png", ".jpg", ".jpeg", ".bmp", ".webp", ".tiff", ".tif", ".gif")
+
+
+def _load_folder_images(folder: str) -> List[Image.Image]:
+    if not os.path.isdir(folder):
+        raise ValueError(f"合并图切割：图片路径不是有效的文件夹：{folder}")
+
+    names = sorted(
+        name for name in os.listdir(folder)
+        if name.lower().endswith(_IMAGE_EXTS)
+    )
+    images: List[Image.Image] = []
+    for name in names:
+        path = os.path.join(folder, name)
+        if not os.path.isfile(path):
+            continue
+        with Image.open(path) as opened:
+            images.append(opened.convert("RGB"))
+
+    if not images:
+        raise ValueError(f"合并图切割：文件夹中没有可读取的图片：{folder}")
+    return images
+
+
 class O1keyGridSplitter:
     """Split AI-generated grid/contact-sheet images into individual cells."""
 
@@ -343,6 +368,7 @@ class O1keyGridSplitter:
                 "裁掉外边距": ("BOOLEAN", {"default": True}),
                 "最小分隔线px": ("INT", {"default": 2, "min": 0, "max": 64, "step": 1}),
                 "最大输出张数": ("INT", {"default": 16, "min": 1, "max": 144, "step": 1}),
+                "图片路径": ("STRING", {"default": "", "multiline": False}),
             }
         }
 
@@ -366,8 +392,12 @@ class O1keyGridSplitter:
         裁掉外边距: bool = True,
         最小分隔线px: int = 2,
         最大输出张数: int = 16,
+        图片路径: str = "",
     ):
-        source_images = tensor_to_pil(图像)
+        if 图片路径 and 图片路径.strip():
+            source_images = _load_folder_images(图片路径.strip())
+        else:
+            source_images = tensor_to_pil(图像)
         all_crops: List[Image.Image] = []
         info_lines: List[str] = []