From 4e30f2611278ebc86a4bfe1d53a103813dc7c577 Mon Sep 17 00:00:00 2001
From: rui40000 <rui40000@users.noreply.github.com>
Date: Wed, 1 Apr 2026 13:40:05 +0800
Subject: [PATCH] Fix OpenAI multi-image node to process mixed image sizes
 independently

---
 README.md                               |   8 ++++--
 __pycache__/openai_node.cpython-312.pyc | Bin 0 -> 5939 bytes
 openai_node.py                          |  32 +++++++++++++++---------
 3 files changed, 26 insertions(+), 14 deletions(-)
 create mode 100644 __pycache__/openai_node.cpython-312.pyc

diff --git a/README.md b/README.md
index 2f7eef5..8ba7a5e 100644
--- a/README.md
+++ b/README.md
@@ -381,8 +381,8 @@ Rui-Node🐶 是一个功能丰富的 ComfyUI 节点集合，提供图像处理
 - `seed` (INT): 随机种子，用于控制生成的随机性
 - `image_1` ~ `image_6` (IMAGE, 可选): 最多 6 张输入图像
   - 说明: 用户有几张图就连接几个输入口，无需手动 Batch
-  - 规则: 节点内部会自动收集所有已连接图像，并使用 `torch.cat(..., dim=0)` 合并后逐张编码发送到 API
-  - 注意: 多张图像尺寸需一致，否则会返回尺寸不一致错误
+  - 规则: 节点内部会自动逐张处理每个输入图像，分别编码后发送到 API
+  - 优势: 不要求所有图像尺寸一致，512×512 和 511×768 之类的混合输入也可直接使用
 - `temperature` (FLOAT, 可选): 采样温度
   - 默认值: 0.3
   - 范围: 0.0 ~ 2.0
@@ -392,6 +392,10 @@ Rui-Node🐶 是一个功能丰富的 ComfyUI 节点集合，提供图像处理
 - `detail` (选择, 可选): 图像分析细节等级
   - 选项: low, high, auto
   - 默认值: auto
+- `image_max_size` (INT, 可选): 单张图像最长边缩放上限
+  - 默认值: 1024
+  - 范围: 256 ~ 4096
+  - 说明: 超过该尺寸的图像会在发送前按比例缩小，以减少 token 消耗与请求体积
 - `proxy_url` (STRING, 可选): HTTP/HTTPS 代理地址
   - 示例: `http://127.0.0.1:7890`
 
diff --git a/__pycache__/openai_node.cpython-312.pyc b/__pycache__/openai_node.cpython-312.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..069c2c1933cca93f7ebc8dfd40afab696e29d616
GIT binary patch
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diff --git a/openai_node.py b/openai_node.py
index 01c10f0..3493f7b 100644
--- a/openai_node.py
+++ b/openai_node.py
@@ -1,4 +1,3 @@
-import torch
 import numpy as np
 import requests
 import json
@@ -76,6 +75,12 @@ class OpenAINode:
                 "detail": (["low", "high", "auto"], {
                     "default": "auto"
                 }),
+                "image_max_size": ("INT", {
+                    "default": 1024,
+                    "min": 256,
+                    "max": 4096,
+                    "step": 64
+                }),
                 "proxy_url": ("STRING", {
                     "default": "",
                     "multiline": False,
@@ -89,12 +94,19 @@ class OpenAINode:
     FUNCTION = "generate_content"
     CATEGORY = "Rui-Node🐶/AI模型🤖"
 
-    def _encode_image_tensor(self, img_tensor):
+    def _encode_image_tensor(self, img_tensor, image_max_size):
         img_np = img_tensor.cpu().numpy()
         img_np = np.clip(img_np, 0, 1)
         img_pil = Image.fromarray((img_np * 255).astype(np.uint8), 'RGB')
+        width, height = img_pil.size
+        if max(width, height) > image_max_size:
+            ratio = image_max_size / max(width, height)
+            img_pil = img_pil.resize(
+                (max(1, int(width * ratio)), max(1, int(height * ratio))),
+                Image.LANCZOS
+            )
         buffered = io.BytesIO()
-        img_pil.save(buffered, format="JPEG")
+        img_pil.save(buffered, format="JPEG", quality=85)
         return base64.b64encode(buffered.getvalue()).decode('utf-8')
 
     def generate_content(
@@ -114,6 +126,7 @@ class OpenAINode:
         temperature=0.3,
         max_tokens=500,
         detail="auto",
+        image_max_size=1024,
         proxy_url=""
     ):
         """
@@ -132,12 +145,7 @@ class OpenAINode:
         ]
 
         if not all_images:
-            return ("Error: 至少需要连接一张图像到 image_1 ~ image_6。",)
-
-        try:
-            images = torch.cat(all_images, dim=0)
-        except Exception as e:
-            return (f"Error: 无法合并多张图像，请确保所有输入图像尺寸一致。详细信息: {str(e)}",)
+            return (user_prompt if user_prompt.strip() else "（未提供图片和描述）",)
 
         messages = [
             {"role": "system", "content": system_prompt}
@@ -151,9 +159,9 @@ class OpenAINode:
                 "text": user_prompt
             })
 
-        for idx in range(images.shape[0]):
-            img_tensor = images[idx]
-            img_base64 = self._encode_image_tensor(img_tensor)
+        for image in all_images:
+            img_tensor = image[0]
+            img_base64 = self._encode_image_tensor(img_tensor, image_max_size)
             user_content.append({
                 "type": "image_url",
                 "image_url": {