Wire GPT resolution to input aspect ratio

README.md

@@ -70,13 +70,14 @@ You must have a **Fal.ai API Key** to use this node.
 * **num_inference_steps**: Number of inference steps for supported models.
 * **seed**: Seed for reproducibility.
 * **aspect_ratio**: Set target aspect ratio (e.g., 16:9, 1:1).
+* **resolution**: Sets the maximum output edge for GPT Image models while preserving the first input image's aspect ratio: `0.5K` = 512px, `1K` = 1024px, `2K` = 2048px, and `4K` = 3840px.
 * **quality**: GPT quality. GPT Image 2 supports `auto` through `high`; GPT Image 2.5 also supports `xhigh` and `max`.
 * **enable_web_search**: Enables web search context for supported models.
 * **thinking_level**: `off`, `minimal`, or `high` for supported models.
 * **concurrent_runs**: Number of independent fal.ai queue jobs to submit in parallel from this node. This is separate from workflow-level concurrency, which automatically overlaps independent NanoSeed nodes. Each run requests its own `num_images`; outputs are returned in run order. Models with an explicit seed increment it for each additional run.
 * **queue_timeout**: Maximum wait per queue job in seconds. Timed-out jobs receive a best-effort cancellation request.
 * **gpt_background**: `auto`, `transparent`, or `opaque` for GPT Image models.
-* **gpt_image_size**: GPT output-size preset, including 1080p, 1440p, and 3840x2160. Non-zero `width` and `height` override this preset.
+* **gpt_image_size**: Optional GPT aspect-ratio override. `auto` follows the first input image; presets or non-zero `width` and `height` override the aspect ratio, while `resolution` still caps the longest edge.
 * **gpt_output_format**: `png`, `jpeg`, or `webp` for GPT Image models.
 * **gpt_output_compression**: Optional GPT Image 2.5 JPEG/WebP compression from 0-100. Leave at `-1` to use the API default.
 
@@ -88,7 +89,9 @@ Different models have different requirements implemented in the node:
     * Supports all 10 NanoSeed reference-image sockets and up to **10 output images**.
     * Supports `auto`, `low`, `medium`, `high`, `xhigh`, and `max` quality. Higher levels increase cost and latency.
     * Supports automatic, transparent, or opaque backgrounds and PNG, JPEG, or WebP output.
-    * Includes 1080p, 1440p, and **3840x2160** presets. Custom non-zero `width` and `height` take priority.
+    * `resolution` automatically calculates dimensions from the first input image: 1K, 2K, or 4K sets a 1024px, 2048px, or 3840px maximum edge.
+    * Calculated dimensions are multiples of 16, and input aspect ratios beyond the API limit are clamped to 3:1.
+    * `gpt_image_size` or non-zero `width` and `height` can override the aspect ratio, but not the selected resolution cap.
     * Supports the shared GPT `mask` socket.
 
 2.  **Flux 2 Edit (`flux_2_edit`)**:

nano_seed.py

@@ -1,4 +1,5 @@
 import asyncio
+import math
 import os
 import re
 import time
@@ -21,6 +22,15 @@ GPT_IMAGE_25_EDIT_URLS = {
     "gpt_image_2_5_sunburst_edit": "https://fal.run/openai/gpt-image-2.5/sunburst/edit",
 }
 
+GPT_IMAGE_EDIT_MODELS = {"gpt_image_2_edit", *GPT_IMAGE_25_EDIT_URLS}
+
+GPT_RESOLUTION_MAX_EDGE = {
+    "0.5K": 512,
+    "1K": 1024,
+    "2K": 2048,
+    "4K": 3840,
+}
+
 GPT_IMAGE_SIZE_OPTIONS = [
     "auto",
     "square_hd",
@@ -35,6 +45,12 @@ GPT_IMAGE_SIZE_OPTIONS = [
 ]
 
 GPT_IMAGE_SIZE_DIMENSIONS = {
+    "square_hd": {"width": 1024, "height": 1024},
+    "square": {"width": 512, "height": 512},
+    "portrait_4_3": {"width": 768, "height": 1024},
+    "portrait_16_9": {"width": 576, "height": 1024},
+    "landscape_4_3": {"width": 1024, "height": 768},
+    "landscape_16_9": {"width": 1024, "height": 576},
     "1920x1080": {"width": 1920, "height": 1080},
     "2560x1440": {"width": 2560, "height": 1440},
     "3840x2160": {"width": 3840, "height": 2160},
@@ -176,10 +192,54 @@ def _prepare_image_data_uris(images, resize_to=None):
     return data_uris
 
 
-def _resolve_gpt_image_size(width, height, image_size):
+def _gpt_source_dimensions(image_tensor, width, height, image_size):
     if width > 0 and height > 0:
-        return {"width": width, "height": height}
-    return GPT_IMAGE_SIZE_DIMENSIONS.get(image_size, image_size)
+        return width, height
+
+    preset = GPT_IMAGE_SIZE_DIMENSIONS.get(image_size)
+    if preset is not None:
+        return preset["width"], preset["height"]
+
+    shape = image_tensor.shape
+    if len(shape) == 4:
+        return int(shape[2]), int(shape[1])
+    if len(shape) == 3:
+        return int(shape[1]), int(shape[0])
+    raise ValueError("GPT image input must use ComfyUI IMAGE tensor dimensions.")
+
+
+def _resolve_gpt_image_size(image_tensor, resolution, width, height, image_size):
+    max_edge = GPT_RESOLUTION_MAX_EDGE.get(resolution)
+    if max_edge is None:
+        raise ValueError(f"Unsupported GPT resolution: {resolution!r}")
+
+    source_width, source_height = _gpt_source_dimensions(
+        image_tensor,
+        width,
+        height,
+        image_size,
+    )
+    if source_width <= 0 or source_height <= 0:
+        raise ValueError("GPT image dimensions must be greater than zero.")
+
+    if source_width >= source_height:
+        aspect_ratio = min(source_width / source_height, 3.0)
+        output_width = max_edge
+        output_height = _round_to_multiple(output_width / aspect_ratio, 16)
+        output_height = max(
+            output_height,
+            math.ceil((output_width / 3.0) / 16) * 16,
+        )
+    else:
+        aspect_ratio = min(source_height / source_width, 3.0)
+        output_height = max_edge
+        output_width = _round_to_multiple(output_height / aspect_ratio, 16)
+        output_width = max(
+            output_width,
+            math.ceil((output_height / 3.0) / 16) * 16,
+        )
+
+    return {"width": output_width, "height": output_height}
 
 
 def _safe_error_detail(detail):
@@ -467,11 +527,27 @@ class NanoSeedEdit:
         images = [img for img in image_inputs if img is not None]
         if not images:
             raise ValueError("At least one image input must be connected.")
-        
+
+        resolved_gpt_image_size = None
+        if model in GPT_IMAGE_EDIT_MODELS:
+            resolved_gpt_image_size = _resolve_gpt_image_size(
+                images[0],
+                resolution,
+                width,
+                height,
+                gpt_image_size,
+            )
+
         custom_size = (width > 0 and height > 0)
         resize_to = None
         if custom_size and model not in ["nano_banana", "nano_banana_pro", "nano_banana_2"]:
-            resize_to = (width, height)
+            if resolved_gpt_image_size is not None:
+                resize_to = (
+                    resolved_gpt_image_size["width"],
+                    resolved_gpt_image_size["height"],
+                )
+            else:
+                resize_to = (width, height)
         img_data_uris = await asyncio.to_thread(
             _prepare_image_data_uris,
             images,
@@ -530,7 +606,7 @@ class NanoSeedEdit:
                 "image_urls": img_data_uris,
                 "quality": quality,
                 "background": gpt_background,
-                "image_size": _resolve_gpt_image_size(width, height, gpt_image_size),
+                "image_size": resolved_gpt_image_size,
                 "num_images": min(num_images, 4),
                 "output_format": gpt_output_format,
                 "sync_mode": False,
@@ -546,7 +622,7 @@ class NanoSeedEdit:
                 "image_urls": img_data_uris,
                 "quality": quality,
                 "background": gpt_background,
-                "image_size": _resolve_gpt_image_size(width, height, gpt_image_size),
+                "image_size": resolved_gpt_image_size,
                 "num_images": num_images,
                 "output_format": gpt_output_format,
                 "sync_mode": False,