tweaks

__init__.py

@@ -149,6 +149,7 @@ from .nodes.prompting.FL_MadLibGenerator import FL_MadLibGenerator
 from .nodes.prompting.FL_Prompt import FL_PromptBasic
 from .nodes.prompting.FL_PromptMulti import FL_PromptMulti
 from .nodes.prompting.FL_PromptSelector import FL_PromptSelector
+from .nodes.prompting.FL_PromptSelectorBasic import FL_PromptSelectorBasic
 
 # UTILITY NODES
 from .nodes.utility.FL_ClipScanner import FL_ClipScanner
@@ -339,6 +340,7 @@ NODE_CLASS_MAPPINGS = {
     "FL_Fal_Sora": FL_Fal_Sora,
     "FL_PromptBasic": FL_PromptBasic,
     "FL_PromptMulti": FL_PromptMulti,
+    "FL_PromptSelectorBasic": FL_PromptSelectorBasic,
     "FL_PaddingRemover": FL_PaddingRemover,
     "FL_GPT_Text": FL_GPT_Text,
     "FL_GoogleCloudStorage": FL_GoogleCloudStorage,
@@ -410,6 +412,7 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "FL_HalftonePattern": "FL Halftone",
     "FL_RandomNumber": "FL Random Number",
     "FL_PromptSelector": "FL Prompt Selector",
+    "FL_PromptSelectorBasic": "FL Prompt Selector Basic",
     "FL_Shadertoy": "FL Shadertoy",
     "FL_PixelArtShader": "FL Pixel Art",
     "FL_InfiniteZoom": "FL Infinite Zoom",
@@ -513,6 +516,7 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "FL_Fal_Sora": "FL Fal Sora 2",
     "FL_PromptBasic": "FL Prompt Basic",
     "FL_PromptMulti": "FL Prompt Multi",
+    "FL_PromptSelectorBasic": "FL Prompt Selector Basic",
     "FL_PaddingRemover": "FL Padding Remover",
     "FL_GPT_Text": "FL GPT Text",
     "FL_GoogleCloudStorage": "FL Google Cloud Storage Uploader",

nodes/prompting/FL_PromptSelector.py

@@ -22,8 +22,8 @@ class FL_PromptSelector:
 
         num_prompts = len(prompt_lines)
 
-        if index < 0 or index >= num_prompts:
-            raise ValueError(f"Index {index} is out of range. Please provide an index between 0 and {num_prompts - 1}.")
+        # Loop through prompts using modulo
+        index = index % num_prompts
 
         selected_prompt = prompt_lines[index].strip()
 

nodes/prompting/FL_PromptSelectorBasic.py

@@ -0,0 +1,34 @@
+class FL_PromptSelectorBasic:
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "prompts": ("STRING", {"multiline": True}),
+                "index": ("INT", {"default": 0, "min": 0, "max": 6969, "step": 1}),
+            },
+        }
+
+    RETURN_TYPES = ("STRING",)
+    FUNCTION = "select_prompt"
+    CATEGORY = "🏵️Fill Nodes/Prompting"
+
+    def select_prompt(self, prompts, index):
+        prompt_lines = prompts.split("\n")
+
+        num_prompts = len(prompt_lines)
+
+        # Loop through prompts using modulo
+        index = index % num_prompts
+
+        selected_prompt = prompt_lines[index].strip()
+
+        return (selected_prompt,)
+
+
+NODE_CLASS_MAPPINGS = {
+    "FL_PromptSelectorBasic": FL_PromptSelectorBasic,
+}
+
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "FL_PromptSelectorBasic": "Prompt Selector Basic 🏵️",
+}

nodes/wip/FL_QwenImageEditStrength.py

@@ -55,11 +55,25 @@ class FL_QwenImageEditStrength:
         images_vl = []
         llama_template = "<|im_start|>system\nDescribe the key features of the input image (color, shape, size, texture, objects, background), then explain how the user's text instruction should alter or modify the image. Generate a new image that meets the user's requirements while maintaining consistency with the original input where appropriate.<|im_end|>\n<|im_start|>user\n{}<|im_end|>\n<|im_start|>assistant\n"
         image_prompt = ""
+        image_dimensions = None  # Track first image dimensions for validation
 
         for i, (image, strength) in enumerate(images):
             if image is not None:
                 samples = image.movedim(-1, 1)
 
+                # Validate that all images have the same dimensions when using VAE
+                if vae is not None:
+                    current_dims = (samples.shape[2], samples.shape[3])  # (height, width)
+                    if image_dimensions is None:
+                        image_dimensions = current_dims
+                    elif current_dims != image_dimensions:
+                        raise ValueError(
+                            f"Image size mismatch: Image {i+1} has dimensions {current_dims[0]}x{current_dims[1]}, "
+                            f"but the first image has dimensions {image_dimensions[0]}x{image_dimensions[1]}. "
+                            f"All images must have the same dimensions when using VAE encoding. "
+                            f"Please resize your images to match before connecting them to this node."
+                        )
+
                 # Resize for vision model (384x384)
                 total = int(384 * 384)
                 scale_by = math.sqrt(total / (samples.shape[3] * samples.shape[2]))
@@ -69,15 +83,9 @@ class FL_QwenImageEditStrength:
                 s = comfy.utils.common_upscale(samples, width, height, "area", "disabled")
                 images_vl.append(s.movedim(1, -1))
 
-                # Encode to latents if VAE is provided
+                # Encode to latents if VAE is provided (using original dimensions)
                 if vae is not None:
-                    total = int(1024 * 1024)
-                    scale_by = math.sqrt(total / (samples.shape[3] * samples.shape[2]))
-                    width = round(samples.shape[3] * scale_by / 8.0) * 8
-                    height = round(samples.shape[2] * scale_by / 8.0) * 8
-
-                    s = comfy.utils.common_upscale(samples, width, height, "area", "disabled")
-                    latent = vae.encode(s.movedim(1, -1)[:, :, :, :3])
+                    latent = vae.encode(samples.movedim(1, -1)[:, :, :, :3])
 
                     individual_latents.append(latent)
                     strengths.append(strength)

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "comfyui_fill-nodes"
 description = "Fill-Nodes is a versatile collection of custom nodes for ComfyUI that extends functionality across multiple domains. Features include advanced image processing (pixelation, slicing, masking), visual effects generation (glitch, halftone, pixel art), comprehensive file handling (PDF creation/extraction, Google Drive integration), AI model interfaces (GPT, DALL-E, Hugging Face), utility nodes for workflow enhancement, and specialized tools for video processing, captioning, and batch operations. The pack provides both practical workflow solutions and creative tools within a unified node collection."
-version = "1.9.9"
+version = "2.0.0"
 license = "LICENSE"
 dependencies = ["diffusers", "librosa", "sounddevice", "glitch_this", "PyOpenGL", "glfw", "scipy>=1.13.1", "requests", "aiohttp", "moviepy", "matplotlib", "reportlab", "openai", "PyPDF2", "pdf2image", "PyMuPDF", "reportlab", "PyPDF2", "ollama", "kornia", "opencv-python", "gdown", "open_clip_torch", "google-genai"]