tweak

Co-authored-by: tristan22mc <tristan22mc@gmail.com>

comfy-nodes/external_exr.py

@@ -0,0 +1,110 @@
+import os
+import io
+import cv2 as cv
+import numpy as np
+import torch
+import requests
+from folder_paths import get_annotated_filepath
+
+class ComfyUIDeployExternalEXR:
+    RETURN_TYPES = ("IMAGE", "MASK")
+    RETURN_NAMES = ("image", "mask") 
+    FUNCTION = "load_exr"
+    CATEGORY = "🔗ComfyDeploy"
+    
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "input_id": (
+                    "STRING",
+                    {"multiline": False, "default": "input_exr"},
+                ),
+                "exr_file": ("STRING", {"default": ""}),
+                "tonemap": (["linear", "sRGB", "Reinhard"], {"default": "sRGB"}),
+            },
+            "optional": {
+                "default_image": ("IMAGE",),
+                "default_mask": ("MASK",),
+                "display_name": (
+                    "STRING", 
+                    {"multiline": False, "default": ""},
+                ),
+                "description": (
+                    "STRING",
+                    {"multiline": False, "default": ""},
+                ),
+            }
+        }
+
+    @classmethod
+    def VALIDATE_INPUTS(s, exr_file, **kwargs):
+        return True
+
+    def sRGBtoLinear(self, npArray):
+        less = npArray <= 0.0404482362771082
+        npArray[less] = npArray[less] / 12.92
+        npArray[~less] = np.power((npArray[~less] + 0.055) / 1.055, 2.4)
+
+    def linearToSRGB(self, npArray):
+        less = npArray <= 0.0031308
+        npArray[less] = npArray[less] * 12.92
+        npArray[~less] = np.power(npArray[~less], 1/2.4) * 1.055 - 0.055
+
+    def load_exr(self, input_id, exr_file, tonemap="sRGB", 
+                 default_image=None, default_mask=None,
+                 display_name=None, description=None):
+        try:
+            if exr_file and exr_file != "":
+                if exr_file.startswith(('http://', 'https://')):
+                    # Handle URL input
+                    response = requests.get(exr_file)
+                    # Write to temp buffer
+                    buffer = io.BytesIO(response.content)
+                    nparr = np.frombuffer(buffer.getvalue(), np.uint8)
+                    image = cv.imdecode(nparr, cv.IMREAD_UNCHANGED).astype(np.float32)
+                else:
+                    # Handle local file
+                    exr_path = get_annotated_filepath(exr_file)
+                    image = cv.imread(exr_path, cv.IMREAD_UNCHANGED).astype(np.float32)
+
+                if len(image.shape) == 2:
+                    image = np.repeat(image[..., np.newaxis], 3, axis=2)
+                
+                # Extract RGB and flip channels
+                rgb = np.flip(image[:,:,:3], 2).copy()
+                
+                # Apply tonemapping
+                if tonemap == "sRGB":
+                    self.linearToSRGB(rgb)
+                    rgb = np.clip(rgb, 0, 1)
+                elif tonemap == "Reinhard":
+                    rgb = np.clip(rgb, 0, None)
+                    rgb = rgb / (rgb + 1)
+                    self.linearToSRGB(rgb)
+                    rgb = np.clip(rgb, 0, 1)
+                
+                rgb = torch.unsqueeze(torch.from_numpy(rgb), 0)
+                
+                # Handle alpha/mask
+                mask = torch.zeros((1, image.shape[0], image.shape[1]), dtype=torch.float32)
+                if image.shape[2] > 3:
+                    mask[0] = torch.from_numpy(np.clip(image[:,:,3], 0, 1))
+
+                return (rgb, mask)
+            else:
+                # Return defaults if no file provided
+                return (default_image, default_mask)
+
+        except Exception as e:
+            print(f"Error loading EXR: {str(e)}")
+            # Return defaults on error
+            return (default_image, default_mask)
+
+NODE_CLASS_MAPPINGS = {
+    "ComfyUIDeployExternalEXR": ComfyUIDeployExternalEXR
+}
+
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "ComfyUIDeployExternalEXR": "External EXR (ComfyUI Deploy)"
+}

comfy-nodes/external_exr_input.py

@@ -1,93 +0,0 @@
-import os
-os.environ["OPENCV_IO_ENABLE_OPENEXR"] = "1"
-import cv2 as cv
-import numpy as np
-import torch
-from folder_paths import get_annotated_filepath
-
-def linear_to_srgb(np_array):
-    """Converts a linear RGB numpy array to sRGB."""
-    less = np_array <= 0.0031308
-    np_array[less] = np_array[less] * 12.92
-    np_array[~less] = np.power(np_array[~less], 1/2.4) * 1.055 - 0.055
-    return np_array
-
-class ExternalExrInput:
-    """
-    Node to load a single EXR image from a local file path.
-    """
-    @classmethod
-    def INPUT_TYPES(cls):
-        return {
-            "required": {
-                "exr_file": ("STRING", {"default": "path/to/image.exr"}),
-                "tonemap": (["linear", "sRGB", "Reinhard"], {"default": "sRGB"}),
-            },
-            "optional": {
-                "default_image": ("IMAGE",),
-                "default_mask": ("MASK",),
-            }
-        }
-
-    RETURN_TYPES = ("IMAGE", "MASK")
-    RETURN_NAMES = ("image", "mask",)
-    FUNCTION = "run"
-    CATEGORY = "🔗ComfyDeploy/EXR"
-
-    def run(self, exr_file, tonemap, default_image=None, default_mask=None):
-        image = None
-        try:
-            if exr_file and exr_file.strip() != "":
-                exr_path = get_annotated_filepath(exr_file)
-                if os.path.exists(exr_path):
-                    image = cv.imread(exr_path, cv.IMREAD_UNCHANGED).astype(np.float32)
-                else:
-                    print(f"Warning: File not found at {exr_path}")
-            
-            if image is None:
-                raise ValueError("Image could not be loaded.")
-
-            if len(image.shape) == 2: # Grayscale
-                image = np.repeat(image[..., np.newaxis], 3, axis=2)
-            
-            rgb = np.flip(image[:, :, :3], 2).copy() # BGR to RGB
-            
-            # Apply tonemapping
-            if tonemap == "sRGB":
-                rgb = linear_to_srgb(rgb)
-                rgb = np.clip(rgb, 0, 1)
-            elif tonemap == "Reinhard":
-                rgb = np.clip(rgb, 0, None)
-                rgb = rgb / (rgb + 1)
-                rgb = linear_to_srgb(rgb)
-                rgb = np.clip(rgb, 0, 1)
-            
-            rgb_tensor = torch.from_numpy(rgb).unsqueeze(0)
-            
-            # Handle alpha/mask
-            if image.shape[2] > 3:
-                mask = np.clip(image[:, :, 3], 0, 1)
-            else:
-                mask = np.ones_like(rgb[:, :, 0])
-            mask_tensor = torch.from_numpy(mask).unsqueeze(0)
-
-            return (rgb_tensor, mask_tensor)
-
-        except Exception as e:
-            print(f"Error loading EXR file '{exr_file}': {e}")
-            if default_image is not None and default_mask is not None:
-                print("Returning default image.")
-                return (default_image, default_mask)
-            
-            print("Warning: Error loading EXR and no default image. Returning a black image.")
-            blank_image = torch.zeros((1, 64, 64, 3), dtype=torch.float32)
-            blank_mask = torch.zeros((1, 64, 64), dtype=torch.float32)
-            return (blank_image, blank_mask)
-
-NODE_CLASS_MAPPINGS = {
-    "ExternalExrInput": ExternalExrInput
-}
-
-NODE_DISPLAY_NAME_MAPPINGS = {
-    "ExternalExrInput": "External EXR Input (ComfyDeploy)"
-} 

comfy-nodes/external_exr_output.py

@@ -1,73 +0,0 @@
-import os
-os.environ["OPENCV_IO_ENABLE_OPENEXR"] = "1"
-import cv2 as cv
-import torch
-import numpy as np
-import folder_paths
-
-def srgb_to_linear(np_array):
-    """Converts an sRGB numpy array to linear RGB."""
-    less = np_array <= 0.0404482362771082
-    np_array[less] = np_array[less] / 12.92
-    np_array[~less] = np.power((np_array[~less] + 0.055) / 1.055, 2.4)
-    return np_array
-
-class ExternalExrOutput:
-    """
-    Node to save a single image as an EXR file to a local path.
-    """
-    def __init__(self):
-        self.output_dir = folder_paths.get_output_directory()
-        self.type = "output"
-
-    @classmethod
-    def INPUT_TYPES(cls):
-        return {
-            "required": {
-                "images": ("IMAGE",),
-                "filepath": ("STRING", {"default": "/tmp/output.exr"}),
-                "tonemap": (["linear", "sRGB"], {"default": "linear"}),
-            },
-        }
-
-    RETURN_TYPES = ()
-    FUNCTION = "run"
-    OUTPUT_NODE = True
-    CATEGORY = "🔗ComfyDeploy/EXR"
-
-    def run(self, images, filepath, tonemap):
-        if not filepath.endswith(".exr"):
-            raise ValueError("Filepath must end with '.exr'")
-
-        output_dir = os.path.dirname(filepath)
-        if not os.path.isabs(output_dir):
-            raise ValueError("Filepath must be an absolute path.")
-        
-        os.makedirs(output_dir, exist_ok=True)
-        
-        # We only process the first image in the batch
-        image_tensor = images[0]
-        
-        linear = image_tensor.cpu().numpy().astype(np.float32)
-        
-        # If the source is sRGB, convert to linear
-        if tonemap == "sRGB":
-            linear[...,:3] = srgb_to_linear(linear[...,:3])
-
-        # Convert RGB to BGR for OpenCV
-        bgr = np.flip(linear, 2).copy()
-        
-        # Save the image
-        cv.imwrite(filepath, bgr)
-        
-        print(f"Saved EXR file to: {filepath}")
-
-        return {"ui": {"images": [{"filename": os.path.basename(filepath), "subfolder": os.path.dirname(filepath), "type": self.type}]}}
-
-NODE_CLASS_MAPPINGS = {
-    "ExternalExrOutput": ExternalExrOutput
-}
-
-NODE_DISPLAY_NAME_MAPPINGS = {
-    "ExternalExrOutput": "External EXR Output (ComfyDeploy)"
-} 

comfy-nodes/external_exr_sequence_input.py

@@ -1,159 +0,0 @@
-import os
-os.environ["OPENCV_IO_ENABLE_OPENEXR"] = "1"
-import cv2 as cv
-import numpy as np
-import torch
-import re
-from folder_paths import get_annotated_filepath
-
-def linear_to_srgb(np_array):
-    """Converts a linear RGB numpy array to sRGB."""
-    less = np_array <= 0.0031308
-    np_array[less] = np_array[less] * 12.92
-    np_array[~less] = np.power(np_array[~less], 1/2.4) * 1.055 - 0.055
-    return np_array
-
-class ExternalExrSequenceInput:
-    """
-    Node to load a sequence of EXR images from a local filepath pattern, a directory,
-    or a single file within a sequence.
-    """
-    @classmethod
-    def INPUT_TYPES(cls):
-        return {
-            "required": {
-                "path_or_pattern": ("STRING", {"default": "path/to/frames_or_pattern"}),
-                "tonemap": (["linear", "sRGB", "Reinhard"], {"default": "sRGB"}),
-                "start_frame": ("INT", {"default": 1, "min": 1}),
-                "end_frame": ("INT", {"default": 50, "min": 1}),
-            },
-            "optional": {
-                "default_image": ("IMAGE",),
-                "default_mask": ("MASK",),
-            }
-        }
-
-    RETURN_TYPES = ("IMAGE", "MASK")
-    RETURN_NAMES = ("image", "mask",)
-    FUNCTION = "run"
-    CATEGORY = "🔗ComfyDeploy/EXR"
-
-    def get_image_paths(self, path_input, start_frame, end_frame):
-        image_paths = []
-        
-        # Case 1: Input is a C-style pattern
-        if '%' in path_input:
-            print(f"Pattern detected: {path_input}")
-            for i in range(start_frame, end_frame + 1):
-                fpath = get_annotated_filepath(path_input % i)
-                if os.path.exists(fpath):
-                    image_paths.append(fpath)
-            return image_paths
-
-        annotated_path = get_annotated_filepath(path_input)
-        
-        # Case 2: Input is a directory
-        if os.path.isdir(annotated_path):
-            print(f"Directory detected: {annotated_path}")
-            files_in_dir = sorted(os.listdir(annotated_path))
-            for filename in files_in_dir:
-                if not filename.lower().endswith('.exr'):
-                    continue
-                
-                matches = re.findall(r'\d+', filename)
-                if not matches:
-                    continue
-                
-                frame_number = int(matches[-1])
-                if start_frame <= frame_number <= end_frame:
-                    image_paths.append(os.path.join(annotated_path, filename))
-            return image_paths
-            
-        # Case 3: Input is a single file from a sequence
-        if os.path.isfile(annotated_path):
-            print(f"Single file detected: {annotated_path}. Attempting to find sequence.")
-            base_dir = os.path.dirname(annotated_path)
-            filename = os.path.basename(annotated_path)
-
-            matches = list(re.finditer(r'(\d+)', filename))
-            if not matches: # It's a single file with no frame number
-                return [annotated_path]
-
-            last_match = matches[-1]
-            num_start_pos, num_end_pos = last_match.span()
-            prefix = filename[:num_start_pos]
-            suffix = filename[num_end_pos:]
-            padding = len(last_match.group(0))
-
-            for i in range(start_frame, end_frame + 1):
-                potential_filename = f"{prefix}{str(i).zfill(padding)}{suffix}"
-                potential_path = os.path.join(base_dir, potential_filename)
-                if os.path.exists(potential_path):
-                    image_paths.append(potential_path)
-            return image_paths
-
-        return [] # Return empty if no cases match
-
-    def run(self, path_or_pattern, tonemap, start_frame, end_frame, default_image=None, default_mask=None):
-        try:
-            image_paths = self.get_image_paths(path_or_pattern, start_frame, end_frame)
-            if not image_paths:
-                raise ValueError(f"No EXR files found for '{path_or_pattern}' between frames {start_frame}-{end_frame}.")
-
-            print(f"Found {len(image_paths)} EXR files to load.")
-            rgb_frames = []
-            mask_frames = []
-            
-            for path in image_paths:
-                image = cv.imread(path, cv.IMREAD_UNCHANGED)
-                if image is None:
-                    print(f"Warning: Could not read file {path}, skipping.")
-                    continue
-                
-                image = image.astype(np.float32)
-                if len(image.shape) == 2:
-                    image = np.repeat(image[..., np.newaxis], 3, axis=2)
-                
-                rgb = np.flip(image[:, :, :3], 2).copy()
-                
-                if tonemap == "sRGB":
-                    rgb = linear_to_srgb(rgb)
-                    rgb = np.clip(rgb, 0, 1)
-                elif tonemap == "Reinhard":
-                    rgb = np.clip(rgb, 0, None)
-                    rgb = rgb / (rgb + 1)
-                    rgb = linear_to_srgb(rgb)
-                    rgb = np.clip(rgb, 0, 1)
-                
-                rgb_frames.append(torch.from_numpy(rgb))
-                
-                if image.shape[2] > 3:
-                    mask = np.clip(image[:, :, 3], 0, 1)
-                else:
-                    mask = np.ones_like(rgb[:, :, 0])
-                mask_frames.append(torch.from_numpy(mask))
-
-            if not rgb_frames:
-                raise ValueError("No frames were loaded successfully.")
-
-            print(f"Successfully loaded {len(rgb_frames)} frames into a batch.")
-            return (torch.stack(rgb_frames, 0), torch.stack(mask_frames, 0))
-
-        except Exception as e:
-            print(f"Error loading EXR sequence: {e}")
-            if default_image is not None and default_mask is not None:
-                print("Returning default image.")
-                return (default_image, default_mask)
-
-            print("Warning: Error loading sequence and no default image. Returning a black image.")
-            blank_image = torch.zeros((1, 64, 64, 3), dtype=torch.float32)
-            blank_mask = torch.zeros((1, 64, 64), dtype=torch.float32)
-            return (blank_image, blank_mask)
-
-NODE_CLASS_MAPPINGS = {
-    "ExternalExrSequenceInput": ExternalExrSequenceInput
-}
-
-NODE_DISPLAY_NAME_MAPPINGS = {
-    "ExternalExrSequenceInput": "External EXR Sequence Input (ComfyDeploy)"
-} 

comfy-nodes/external_exr_sequence_output.py

@@ -1,88 +0,0 @@
-import os
-os.environ["OPENCV_IO_ENABLE_OPENEXR"] = "1"
-import cv2 as cv
-import torch
-import numpy as np
-import re
-
-def srgb_to_linear(np_array):
-    """Converts an sRGB numpy array to linear RGB."""
-    less = np_array <= 0.0404482362771082
-    np_array[less] = np_array[less] / 12.92
-    np_array[~less] = np.power((np_array[~less] + 0.055) / 1.055, 2.4)
-    return np_array
-
-class ExternalExrSequenceOutput:
-    """
-    Node to save a sequence of images as EXR files to a local directory.
-    It uses a filepath pattern like 'path/to/frame_%04d.exr' to save each frame.
-    """
-    def __init__(self):
-        self.type = "output"
-
-    @classmethod
-    def INPUT_TYPES(cls):
-        return {
-            "required": {
-                "images": ("IMAGE",),
-                "filepath_pattern": ("STRING", {"default": "/tmp/exr_sequence/frame_%04d.exr"}),
-                "tonemap": (["linear", "sRGB"], {"default": "linear"}),
-            },
-        }
-
-    RETURN_TYPES = ()
-    FUNCTION = "run"
-    OUTPUT_NODE = True
-    CATEGORY = "🔗ComfyDeploy/EXR"
-
-    def run(self, images, filepath_pattern, tonemap):
-        # Basic validation for the filepath pattern
-        if not re.search(r'%0?\d+d', filepath_pattern):
-            raise ValueError("Filepath pattern must contain a C-style format specifier like '%04d'.")
-            
-        if not filepath_pattern.endswith(".exr"):
-            raise ValueError("Filepath pattern must end with '.exr'.")
-
-        output_dir = os.path.dirname(filepath_pattern)
-        if not os.path.isabs(output_dir):
-            raise ValueError("Filepath must be an absolute path.")
-            
-        os.makedirs(output_dir, exist_ok=True)
-        
-        # Convert tensor to numpy array
-        linear_images = images.cpu().numpy().astype(np.float32)
-        
-        # If the source is sRGB, convert to linear
-        if tonemap == "sRGB":
-            srgb_to_linear(linear_images[...,:3])
-        
-        # Convert RGB to BGR for OpenCV
-        bgr_images = np.flip(linear_images, 3).copy()
-
-        results = []
-        for i, bgr_image in enumerate(bgr_images):
-            frame_num = i + 1
-            try:
-                # Use the pattern to format the full file path
-                file_path = filepath_pattern % frame_num
-            except TypeError:
-                raise ValueError("Invalid format specifier in filepath_pattern. Use '%d', '%04d', etc.")
-
-            # Save the image
-            cv.imwrite(file_path, bgr_image)
-            
-            results.append({
-                "filename": os.path.basename(file_path),
-                "subfolder": os.path.dirname(file_path),
-                "type": self.type,
-            })
-        
-        return {"ui": {"images": results}}
-
-NODE_CLASS_MAPPINGS = {
-    "ExternalExrSequenceOutput": ExternalExrSequenceOutput
-}
-
-NODE_DISPLAY_NAME_MAPPINGS = {
-    "ExternalExrSequenceOutput": "External EXR Sequence Output (ComfyDeploy)"
-} 

comfy-nodes/http_exr_input.py

@@ -1,111 +0,0 @@
-import os
-os.environ["OPENCV_IO_ENABLE_OPENEXR"] = "1"
-import cv2 as cv
-import numpy as np
-import torch
-import requests
-
-def linear_to_srgb(np_array):
-    """Converts a linear RGB numpy array to sRGB."""
-    less = np_array <= 0.0031308
-    np_array[less] = np_array[less] * 12.92
-    np_array[~less] = np.power(np_array[~less], 1/2.4) * 1.055 - 0.055
-    return np_array
-
-class HttpExrInput:
-    """
-    Node to load a single EXR image from a URL, with optional tonemapping.
-    This node is designed to be used in a ComfyDeploy environment where input files are provided via signed URLs.
-    """
-    @classmethod
-    def INPUT_TYPES(cls):
-        return {
-            "required": {
-                "get_signed_url": ("STRING", {"multiline": True, "default": ""}),
-                "tonemap": (["linear", "sRGB", "Reinhard"], {"default": "sRGB"}),
-                "seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff}),
-            },
-            "optional": {
-                "default_image": ("IMAGE",),
-                "default_mask": ("MASK",),
-            },
-        }
-
-    RETURN_TYPES = ("IMAGE", "MASK")
-    RETURN_NAMES = ("image", "mask",)
-    FUNCTION = "run"
-    CATEGORY = "🔗ComfyDeploy/EXR"
-
-    def load_exr_from_data(self, exr_data):
-        try:
-            nparr = np.frombuffer(exr_data, np.uint8)
-            # Use cv.IMREAD_UNCHANGED to keep all channels (e.g., alpha)
-            image = cv.imdecode(nparr, cv.IMREAD_UNCHANGED)
-            if image is None:
-                raise ValueError("Failed to decode EXR data.")
-            return image.astype(np.float32)
-        except Exception as e:
-            print(f"Error decoding EXR data: {e}")
-            return None
-
-    def run(self, get_signed_url, tonemap, seed, default_image=None, default_mask=None):
-        if not get_signed_url or get_signed_url.strip() == "":
-            print("Warning: No input URL provided. Returning default image if available.")
-            if default_image is not None and default_mask is not None:
-                return (default_image, default_mask)
-            
-            print("Warning: No input URL and no default image. Returning a black image.")
-            blank_image = torch.zeros((1, 64, 64, 3), dtype=torch.float32)
-            blank_mask = torch.zeros((1, 64, 64), dtype=torch.float32)
-            return (blank_image, blank_mask)
-
-        image = None
-        try:
-            print(f"Fetching EXR from URL: {get_signed_url}")
-            response = requests.get(get_signed_url)
-            response.raise_for_status()
-            image = self.load_exr_from_data(response.content)
-        except requests.exceptions.RequestException as e:
-            print(f"Error fetching EXR from URL {get_signed_url}: {e}")
-
-        if image is None:
-            print("Warning: Could not load or decode EXR image. Returning default image if available.")
-            if default_image is not None and default_mask is not None:
-                return (default_image, default_mask)
-
-            print("Warning: Failed to load EXR and no default image. Returning a black image.")
-            blank_image = torch.zeros((1, 64, 64, 3), dtype=torch.float32)
-            blank_mask = torch.zeros((1, 64, 64), dtype=torch.float32)
-            return (blank_image, blank_mask)
-                    
-        # BGR to RGB conversion and channel handling
-        if len(image.shape) == 2: # Grayscale
-            image = np.repeat(image[..., np.newaxis], 3, axis=2)
-        
-        rgb = np.flip(image[:, :, :3], 2).copy() # OpenCV loads as BGR, convert to RGB
-        
-        # Tonemapping
-        if tonemap == "sRGB":
-            rgb = linear_to_srgb(rgb)
-            rgb = np.clip(rgb, 0, 1)
-        elif tonemap == "Reinhard":
-            rgb = np.clip(rgb, 0, None) # Ensure no negative values
-            rgb = rgb / (rgb + 1)
-            rgb = linear_to_srgb(rgb)
-            rgb = np.clip(rgb, 0, 1)
-        
-        # Handle alpha channel if it exists
-        if image.shape[2] > 3:
-            mask = np.clip(image[:, :, 3], 0, 1)
-        else:
-            mask = np.ones_like(rgb[:, :, 0]) # Create a full white mask if no alpha
-
-        return (torch.from_numpy(rgb).unsqueeze(0), torch.from_numpy(mask).unsqueeze(0),)
-
-NODE_CLASS_MAPPINGS = {
-    "HttpExrInput": HttpExrInput
-}
-
-NODE_DISPLAY_NAME_MAPPINGS = {
-    "HttpExrInput": "HTTP EXR Input (ComfyDeploy)"
-} 

comfy-nodes/http_exr_output.py

@@ -1,80 +0,0 @@
-import os
-os.environ["OPENCV_IO_ENABLE_OPENEXR"] = "1"
-import cv2 as cv
-import torch
-import numpy as np
-import requests
-
-def srgb_to_linear(np_array):
-    """Converts an sRGB numpy array to linear RGB."""
-    less = np_array <= 0.0404482362771082
-    np_array[less] = np_array[less] / 12.92
-    np_array[~less] = np.power((np_array[~less] + 0.055) / 1.055, 2.4)
-    return np_array
-
-class HttpExrOutput:
-    """
-    Node to save a single EXR image to a pre-signed URL.
-    This node is designed for ComfyDeploy to upload the generated EXR file.
-    """
-    @classmethod
-    def INPUT_TYPES(cls):
-        return {
-            "required": {
-                "images": ("IMAGE",),
-                "put_signed_url": ("STRING", {"multiline": True, "default": ""}),
-                "tonemap": (["linear", "sRGB"], {"default": "linear"}),
-            },
-            "hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"},
-        }
-
-    RETURN_TYPES = ()
-    FUNCTION = "run"
-    OUTPUT_NODE = True
-    CATEGORY = "ComfyDeploy/EXR"
-
-    def run(self, images, put_signed_url, tonemap, prompt=None, extra_pnginfo=None):
-        if not put_signed_url or put_signed_url.strip() == "":
-            print("Warning: No put_signed_url provided. Nothing will be uploaded.")
-            return {"ui": {"images": []}}
-        
-        # We process only the first image of the batch
-        image_tensor = images[0]
-        
-        # Convert tensor to numpy array, assuming it's in range [0, 1]
-        linear = image_tensor.cpu().numpy().astype(np.float32)
-        
-        # If the source is sRGB, convert to linear
-        if tonemap == "sRGB":
-            linear[...,:3] = srgb_to_linear(linear[...,:3])
-
-        # Convert RGB to BGR for OpenCV
-        bgr = np.flip(linear, 2).copy()
-        
-        results = []
-        try:
-            # Encode the image to the EXR format in memory
-            is_success, buffer = cv.imencode(".exr", bgr)
-            if not is_success:
-                raise Exception("Failed to encode image to EXR format.")
-            
-            # Upload the image data to the pre-signed URL
-            response = requests.put(put_signed_url, data=buffer.tobytes(), headers={'Content-Type': 'image/x-exr'})
-            response.raise_for_status()
-            
-            print(f"Successfully uploaded EXR to: {put_signed_url}")
-            # The UI can optionally display a link or confirmation
-            results.append({"url": put_signed_url, "output_id": "output_http_exr"})
-            
-        except Exception as e:
-            print(f"Error uploading EXR to signed URL: {e}")
-
-        return {"ui": {"images": results}}
-
-NODE_CLASS_MAPPINGS = {
-    "HttpExrOutput": HttpExrOutput
-}
-
-NODE_DISPLAY_NAME_MAPPINGS = {
-    "HttpExrOutput": "HTTP EXR Output (ComfyDeploy)"
-} 

comfy-nodes/http_exr_sequence_input.py

@@ -1,126 +0,0 @@
-import os
-os.environ["OPENCV_IO_ENABLE_OPENEXR"] = "1"
-import cv2 as cv
-import numpy as np
-import torch
-import requests
-import json
-
-def linear_to_srgb(np_array):
-    """Converts a linear RGB numpy array to sRGB."""
-    less = np_array <= 0.0031308
-    np_array[less] = np_array[less] * 12.92
-    np_array[~less] = np.power(np_array[~less], 1/2.4) * 1.055 - 0.055
-    return np_array
-
-class HttpExrSequenceInput:
-    """
-    Node to load a sequence of EXR images from a list of URLs provided as a JSON string.
-    """
-    @classmethod
-    def INPUT_TYPES(cls):
-        return {
-            "required": {
-                "urls_json": ("STRING", {"multiline": True, "default": "[]"}),
-                "tonemap": (["linear", "sRGB", "Reinhard"], {"default": "sRGB"}),
-                "seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff}),
-            },
-            "optional": {
-                "default_image": ("IMAGE",),
-                "default_mask": ("MASK",),
-            },
-        }
-
-    RETURN_TYPES = ("IMAGE", "MASK")
-    RETURN_NAMES = ("image", "mask",)
-    FUNCTION = "run"
-    CATEGORY = "🔗ComfyDeploy/EXR"
-
-    def load_exr_from_data(self, exr_data):
-        try:
-            nparr = np.frombuffer(exr_data, np.uint8)
-            image = cv.imdecode(nparr, cv.IMREAD_UNCHANGED)
-            if image is None:
-                raise ValueError("Failed to decode EXR data.")
-            return image.astype(np.float32)
-        except Exception as e:
-            print(f"Error decoding EXR data: {e}")
-            return None
-
-    def run(self, urls_json, tonemap, seed, default_image=None, default_mask=None):
-        try:
-            urls = json.loads(urls_json)
-            if not isinstance(urls, list) or not all(isinstance(u, str) for u in urls):
-                raise ValueError("urls_json must be a JSON array of URL strings.")
-        except (json.JSONDecodeError, ValueError) as e:
-            print(f"Error parsing urls_json: {e}. Using default image if available.")
-            urls = []
-
-        if not urls:
-            if default_image is not None and default_mask is not None:
-                return (default_image, default_mask)
-            
-            print("Warning: No valid URLs and no default image. Returning a black image.")
-            blank_image = torch.zeros((1, 64, 64, 3), dtype=torch.float32)
-            blank_mask = torch.zeros((1, 64, 64), dtype=torch.float32)
-            return (blank_image, blank_mask)
-
-        rgb_frames = []
-        mask_frames = []
-
-        for url in urls:
-            image = None
-            try:
-                print(f"Fetching EXR from URL: {url}")
-                response = requests.get(url)
-                response.raise_for_status()
-                image = self.load_exr_from_data(response.content)
-            except requests.exceptions.RequestException as e:
-                print(f"Error fetching EXR from URL {url}: {e}")
-            
-            if image is None:
-                print(f"Warning: Could not decode EXR from {url}. Skipping frame.")
-                continue
-                
-            if len(image.shape) == 2: # Grayscale
-                image = np.repeat(image[..., np.newaxis], 3, axis=2)
-            
-            rgb = np.flip(image[:, :, :3], 2).copy() # BGR to RGB
-            
-            if tonemap == "sRGB":
-                rgb = linear_to_srgb(rgb)
-                rgb = np.clip(rgb, 0, 1)
-            elif tonemap == "Reinhard":
-                rgb = np.clip(rgb, 0, None)
-                rgb = rgb / (rgb + 1)
-                rgb = linear_to_srgb(rgb)
-                rgb = np.clip(rgb, 0, 1)
-            
-            rgb_frames.append(torch.from_numpy(rgb))
-
-            if image.shape[2] > 3:
-                mask = np.clip(image[:, :, 3], 0, 1)
-            else:
-                mask = np.ones_like(rgb[:, :, 0])
-            mask_frames.append(torch.from_numpy(mask))
-
-        if not rgb_frames:
-            print("Could not load any frames. Returning default image if available.")
-            if default_image is not None and default_mask is not None:
-                return (default_image, default_mask)
-            
-            print("Warning: Failed to load any frames and no default image. Returning a black image.")
-            blank_image = torch.zeros((1, 64, 64, 3), dtype=torch.float32)
-            blank_mask = torch.zeros((1, 64, 64), dtype=torch.float32)
-            return (blank_image, blank_mask)
-
-        print(f"Loaded {len(rgb_frames)} frames successfully.")
-        return (torch.stack(rgb_frames, 0), torch.stack(mask_frames, 0))
-
-NODE_CLASS_MAPPINGS = {
-    "HttpExrSequenceInput": HttpExrSequenceInput
-}
-
-NODE_DISPLAY_NAME_MAPPINGS = {
-    "HttpExrSequenceInput": "HTTP EXR Sequence Input (ComfyDeploy)"
-} 

comfy-nodes/http_exr_sequence_output.py

@@ -1,91 +0,0 @@
-import os
-os.environ["OPENCV_IO_ENABLE_OPENEXR"] = "1"
-import cv2 as cv
-import torch
-import numpy as np
-import requests
-import json
-
-def srgb_to_linear(np_array):
-    """Converts an sRGB numpy array to linear RGB."""
-    less = np_array <= 0.0404482362771082
-    np_array[less] = np_array[less] / 12.92
-    np_array[~less] = np.power((np_array[~less] + 0.055) / 1.055, 2.4)
-    return np_array
-
-class HttpExrSequenceOutput:
-    """
-    Node to save a sequence of images as EXR files to a list of pre-signed URLs.
-    """
-    def __init__(self):
-        self.type = "output"
-
-    @classmethod
-    def INPUT_TYPES(cls):
-        return {
-            "required": {
-                "images": ("IMAGE",),
-                "upload_urls_json": ("STRING", {"multiline": True, "default": "[]"}),
-                "tonemap": (["linear", "sRGB"], {"default": "linear"}),
-            },
-        }
-
-    RETURN_TYPES = ()
-    FUNCTION = "run"
-    OUTPUT_NODE = True
-    CATEGORY = "🔗ComfyDeploy/EXR"
-
-    def run(self, images, upload_urls_json, tonemap):
-        try:
-            upload_urls = json.loads(upload_urls_json)
-            if not isinstance(upload_urls, list) or not all(isinstance(u, str) for u in upload_urls):
-                raise ValueError("upload_urls_json must be a JSON array of URL strings.")
-        except (json.JSONDecodeError, ValueError) as e:
-            print(f"Error parsing upload_urls_json: {e}. Aborting upload.")
-            return {"ui": {"images": []}}
-
-        if not upload_urls:
-            print("Warning: No upload URLs provided. Nothing will be uploaded.")
-            return {"ui": {"images": []}}
-        
-        if len(images) != len(upload_urls):
-            print(f"Warning: Mismatch between number of images ({len(images)}) and upload URLs ({len(upload_urls)}). Aborting upload.")
-            return {"ui": {"images": []}}
-
-        # Convert tensor to numpy array
-        linear_images = images.cpu().numpy().astype(np.float32)
-        
-        # If the source is sRGB, convert all images to linear
-        if tonemap == "sRGB":
-            srgb_to_linear(linear_images[...,:3])
-        
-        # Convert RGB to BGR for OpenCV
-        bgr_images = np.flip(linear_images, 3).copy()
-
-        results = []
-        for i, (bgr_image, url) in enumerate(zip(bgr_images, upload_urls)):
-            try:
-                # Encode the image to the EXR format in memory
-                is_success, buffer = cv.imencode(".exr", bgr_image)
-                if not is_success:
-                    raise Exception("Failed to encode image to EXR format.")
-                
-                # Upload the image data to the pre-signed URL
-                response = requests.put(url, data=buffer.tobytes(), headers={'Content-Type': 'image/x-exr'})
-                response.raise_for_status()
-                
-                print(f"Successfully uploaded frame {i+1} to: {url}")
-                results.append({"url": url})
-                
-            except Exception as e:
-                print(f"Error uploading frame {i+1} to {url}: {e}")
-
-        return {"ui": {"images": results}}
-
-NODE_CLASS_MAPPINGS = {
-    "HttpExrSequenceOutput": HttpExrSequenceOutput
-}
-
-NODE_DISPLAY_NAME_MAPPINGS = {
-    "HttpExrSequenceOutput": "HTTP EXR Sequence Output (ComfyDeploy)"
-} 

comfy-nodes/output_exr.py

@@ -0,0 +1,78 @@
+# In file: comfyui-deploy/comfy-nodes/output_exr.py
+
+import os
+import numpy as np
+import folder_paths
+
+# Try to set up OpenCV for EXR writing.
+try:
+    os.environ["OPENCV_IO_ENABLE_OPENEXR"] = "1"
+    import cv2
+    OPENCV_AVAILABLE = True
+except ImportError:
+    print("Warning: OpenCV not found for ComfyDeployOutputEXR. Please add opencv-python-headless to requirements.txt")
+    OPENCV_AVAILABLE = False
+
+# ALIGNED: Renamed class to match project conventions
+class ComfyDeployOutputEXR:
+    def __init__(self):
+        self.output_dir = folder_paths.get_output_directory()
+        self.type = "output"
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "images": ("IMAGE", ),
+                "filename_prefix": ("STRING", {"default": "ComfyDeploy_EXR"})
+            },
+            # ADDED: Optional output_id for consistency with other ComfyDeploy nodes
+            "optional": {
+                "output_id": ("STRING", {"multiline": False, "default": "output_exr"}),
+            },
+        }
+    
+    RETURN_TYPES = ()
+    # ALIGNED: Changed function name to 'run'
+    FUNCTION = "run"
+    OUTPUT_NODE = True
+    # ALIGNED: Matched the category name
+    CATEGORY = "🔗ComfyDeploy"
+    DESCRIPTION = "Saves the input images as EXR (HDR) files."
+
+    def run(self, images, filename_prefix="ComfyDeploy_EXR", output_id="output_exr"):
+        if not OPENCV_AVAILABLE:
+            raise ImportError("OpenCV is required to save EXR files. Please ensure opencv-python-headless is in requirements.txt.")
+
+        full_output_folder, filename, counter, subfolder, filename_prefix = (
+            folder_paths.get_save_image_path(
+                filename_prefix, self.output_dir, images[0].shape[1], images[0].shape[0]
+            )
+        )
+        results = list()
+
+        for image in images:
+            image_np = image.cpu().numpy()
+
+            if image_np.dtype != np.float32:
+                 image_np = image_np.astype(np.float32)
+
+            file = f"{filename}_{counter:05}.exr"
+            file_path = os.path.join(full_output_folder, file)
+
+            image_np_bgr = cv2.cvtColor(image_np, cv2.COLOR_RGB2BGR)
+            cv2.imwrite(file_path, image_np_bgr)
+
+            results.append({
+                "filename": file,
+                "subfolder": subfolder,
+                "type": self.type,
+                "output_id": output_id, # ADDED
+            })
+            counter += 1
+
+        return {"ui": {"images": results}}
+
+# ALIGNED: Mappings are defined at the bottom of the node file in this project
+NODE_CLASS_MAPPINGS = {"ComfyDeployOutputEXR": ComfyDeployOutputEXR}
+NODE_DISPLAY_NAME_MAPPINGS = {"ComfyDeployOutputEXR": "EXR Output (ComfyDeploy)"}

comfy-nodes/output_text.py

@@ -92,7 +92,7 @@ class ComfyDeployOutputText:
             }
         )
 
-        return {"ui": {"text_file": results}}
+        return {"ui": {"text_file": results, "text": [text]}}
 
 
 NODE_CLASS_MAPPINGS = {"ComfyDeployOutputText": ComfyDeployOutputText}

custom_routes.py

@@ -31,6 +31,7 @@ import torch
 import psutil
 from collections import OrderedDict
 import io
+from urllib.parse import urlencode
 
 # Global session
 client_session = None
@@ -2769,9 +2770,13 @@ class UploadQueue:
                                 del self.node_uploads[prompt_id][node_id]
                                 if prompt_id in self.node_output_data:
                                     if node_id in self.node_output_data[prompt_id]:
-                                        if self.node_output_data[prompt_id][node_id]["data"]:
+                                        if self.node_output_data[prompt_id][node_id][
+                                            "data"
+                                        ]:
                                             # Send final node data to API before cleanup
-                                            if prompt_metadata[prompt_id].status_endpoint:
+                                            if prompt_metadata[
+                                                prompt_id
+                                            ].status_endpoint:
                                                 body = {
                                                     "run_id": prompt_id,
                                                     "output_data": self.node_output_data[
@@ -2785,7 +2790,9 @@ class UploadQueue:
                                                         prompt_metadata[
                                                             prompt_id
                                                         ].status_endpoint,
-                                                        token=prompt_metadata[prompt_id].token,
+                                                        token=prompt_metadata[
+                                                            prompt_id
+                                                        ].token,
                                                         json=body,
                                                     )
                                                 except Exception as e:
@@ -2885,3 +2892,171 @@ def format_execution_timeline(execution_times):
         current_time += duration
 
     return format_table(headers, rows)
+
+
+@server.PromptServer.instance.routes.get("/comfyui-deploy/auth-response")
+async def auth_response_proxy(request):
+    request_id = request.rel_url.query.get("request_id")
+    api_url = request.rel_url.query.get("api_url", "https://api.comfydeploy.com")
+
+    if not request_id:
+        return web.json_response({"error": "request_id is required"}, status=400)
+
+    target_url = f"{api_url}/api/platform/comfyui/auth-response?request_id={request_id}"
+
+    try:
+        await ensure_client_session()
+        async with client_session.get(target_url) as response:
+            json_data = await response.json()
+            return web.json_response(json_data, status=response.status)
+    except Exception as e:
+        return web.json_response({"error": str(e)}, status=500)
+
+
+@server.PromptServer.instance.routes.post("/comfyui-deploy/workflow")
+async def create_workflow_proxy(request):
+    data = await request.json()
+    name = data.get("name")
+    workflow_json = data.get("workflow_json")
+    workflow_api = data.get("workflow_api")
+    api_url = data.get("api_url", "https://api.comfydeploy.com")
+
+    auth_header = request.headers.get("Authorization")
+    if not auth_header:
+        return web.json_response(
+            {"error": "Authorization header is required"}, status=401
+        )
+
+    if not name or not workflow_json or not workflow_api:
+        return web.json_response(
+            {"error": "name, workflow_json, workflow_api are required"}, status=400
+        )
+
+    target_url = f"{api_url}/api/workflow"
+
+    request_body = {
+        "name": name,
+        "workflow_json": json.dumps(workflow_json),
+        "workflow_api": json.dumps(workflow_api),
+    }
+
+    try:
+        await ensure_client_session()
+        async with client_session.post(
+            target_url,
+            json=request_body,
+            headers={
+                "Content-Type": "application/json",
+                "Authorization": auth_header,
+            },
+        ) as response:
+            json_data = await response.json()
+            return web.json_response(json_data, status=response.status)
+    except Exception as e:
+        return web.json_response({"error": str(e)}, status=500)
+
+
+@server.PromptServer.instance.routes.post("/comfyui-deploy/workflow/version")
+async def create_workflow_version_proxy(request):
+    data = await request.json()
+    workflow_id = data.get("workflow_id")
+    workflow = data.get("workflow")
+    workflow_api = data.get("workflow_api")
+    comment = data.get("comment", "")
+    api_url = data.get("api_url", "https://api.comfydeploy.com")
+
+    auth_header = request.headers.get("Authorization")
+
+    if not auth_header:
+        return web.json_response(
+            {"error": "Authorization header is required"}, status=401
+        )
+
+    target_url = f"{api_url}/api/workflow/{workflow_id}/version"
+
+    request_body = {
+        "workflow": workflow,
+        "workflow_api": workflow_api,
+        "comment": comment,
+    }
+
+    try:
+        await ensure_client_session()
+        async with client_session.post(
+            target_url,
+            json=request_body,
+            headers={
+                "Content-Type": "application/json",
+                "Authorization": auth_header,
+            },
+        ) as response:
+            json_data = await response.json()
+            return web.json_response(json_data, status=response.status)
+    except Exception as e:
+        return web.json_response({"error": str(e)}, status=500)
+
+
+@server.PromptServer.instance.routes.get("/comfyui-deploy/workflows")
+async def get_workflows_proxy(request):
+    api_url = request.rel_url.query.get("api_url", "https://api.comfydeploy.com")
+    search = request.rel_url.query.get("search", "")
+    limit = request.rel_url.query.get("limit", 10)
+    offset = request.rel_url.query.get("offset", 0)
+    auth_header = request.headers.get("Authorization")
+
+    if not auth_header:
+        return web.json_response(
+            {"error": "Authorization header is required"}, status=401
+        )
+
+    # Build query parameters properly
+    params = {}
+    if search:
+        params["search"] = search
+    if limit:
+        params["limit"] = limit
+    if offset:
+        params["offset"] = offset
+
+    target_url = f"{api_url}/api/workflows"
+    if params:
+        target_url += f"?{urlencode(params)}"
+
+    try:
+        await ensure_client_session()
+        async with client_session.get(
+            target_url,
+            headers={
+                "Content-Type": "application/json",
+                "Authorization": auth_header,
+            },
+        ) as response:
+            json_data = await response.json()
+            return web.json_response(json_data, status=response.status)
+    except Exception as e:
+        return web.json_response({"error": str(e)}, status=500)
+
+
+# for getting a workflow by id
+@server.PromptServer.instance.routes.get("/comfyui-deploy/workflow")
+async def get_workflow_proxy(request):
+    workflow_id = request.rel_url.query.get("workflow_id")
+    api_url = request.rel_url.query.get("api_url", "https://api.comfydeploy.com")
+    auth_header = request.headers.get("Authorization")
+
+    if not auth_header:
+        return web.json_response(
+            {"error": "Authorization header is required"}, status=401
+        )
+
+    target_url = f"{api_url}/api/workflow/{workflow_id}"
+
+    try:
+        await ensure_client_session()
+        async with client_session.get(
+            target_url, headers={"Authorization": auth_header}
+        ) as response:
+            json_data = await response.json()
+            return web.json_response(json_data, status=response.status)
+    except Exception as e:
+        return web.json_response({"error": str(e)}, status=500)

globals.py

@@ -56,27 +56,11 @@ streaming_prompt_metadata: dict[str, StreamingPrompt] = {}
 class BinaryEventTypes:
     PREVIEW_IMAGE = 1
     UNENCODED_PREVIEW_IMAGE = 2
-    EXR_IMAGE = 4
 
 
 max_output_id_length = 24
 
 
-async def send_exr(image_data, sid=None, output_id: str = None):
-    max_length = max_output_id_length
-    output_id = output_id[:max_length]
-    padded_output_id = output_id.ljust(max_length, "\x00")
-    encoded_output_id = padded_output_id.encode("ascii", "replace")
-
-    bytesIO = BytesIO()
-    # 10 bytes for the output_id
-    bytesIO.write(encoded_output_id)
-    bytesIO.write(image_data)
-
-    preview_bytes = bytesIO.getvalue()
-    await send_bytes(BinaryEventTypes.EXR_IMAGE, preview_bytes, sid=sid)
-
-
 async def send_image(image_data, sid=None, output_id: str = None):
     max_length = max_output_id_length
     output_id = output_id[:max_length]

web-plugin/index.js

@@ -3,6 +3,7 @@ import { api } from "../../scripts/api.js";
 // import { LGraphNode } from "../../scripts/widgets.js";
 LGraphNode = LiteGraph.LGraphNode;
 import { ComfyDialog, $el } from "../../scripts/ui.js";
+import { initializeWorkflowsList, addWorkflowSearch } from "./workflow-list.js";
 
 import { generateDependencyGraph } from "https://esm.sh/comfyui-json@0.1.25";
 // import { ComfyDeploy } from "https://esm.sh/comfydeploy@2.0.0-beta.69";
@@ -96,7 +97,7 @@ function dispatchAPIEventData(data) {
       break;
     case "executing":
       api.dispatchEvent(
-        new CustomEvent("executing", { detail: msg.data.node }),
+        new CustomEvent("executing", { detail: msg.data.node })
       );
       break;
     case "executed":
@@ -104,17 +105,17 @@ function dispatchAPIEventData(data) {
       break;
     case "execution_start":
       api.dispatchEvent(
-        new CustomEvent("execution_start", { detail: msg.data }),
+        new CustomEvent("execution_start", { detail: msg.data })
       );
       break;
     case "execution_error":
       api.dispatchEvent(
-        new CustomEvent("execution_error", { detail: msg.data }),
+        new CustomEvent("execution_error", { detail: msg.data })
       );
       break;
     case "execution_cached":
       api.dispatchEvent(
-        new CustomEvent("execution_cached", { detail: msg.data }),
+        new CustomEvent("execution_cached", { detail: msg.data })
       );
       break;
     default:
@@ -217,28 +218,26 @@ async function convertToInput(node, widget, config) {
 
   console.log(node, widget, config);
 
-  const result = await app.extensionManager.dialog.prompt(
-    {
-      title: "Convert " + widget.name + " to external input",
-      message: "Input name",
-      defaultValue: widget.name,
-    }
-  );
+  const result = await app.extensionManager.dialog.prompt({
+    title: "Convert " + widget.name + " to external input",
+    message: "Input name",
+    defaultValue: widget.name,
+  });
 
   if (!result) return;
 
   // Check for duplicate input IDs across existing external input nodes
   const existingInputIds = Object.values(app.graph.nodes)
-    .filter(n => n.type.startsWith("ComfyUIDeployExternal"))
-    .map(n => n.widgets_values?.[0])
+    .filter((n) => n.type.startsWith("ComfyUIDeployExternal"))
+    .map((n) => n.widgets_values?.[0])
     .filter(Boolean);
 
   if (existingInputIds.includes(result)) {
     app.extensionManager.toast.add({
-      severity: 'error',
-      summary: 'Input ID already exists',
-      detail: 'Please choose a different name.',
-      life: 3000
+      severity: "error",
+      summary: "Input ID already exists",
+      detail: "Please choose a different name.",
+      life: 3000,
     });
     return;
   }
@@ -273,7 +272,7 @@ async function convertToInput(node, widget, config) {
         console.log(links[link]);
         setTimeout(
           () => inputNode.connect(0, llink.target_id, llink.target_slot),
-          100,
+          100
         );
       }
 
@@ -309,7 +308,10 @@ async function convertToInput(node, widget, config) {
 
   node.convertWidgetToInput(widget);
 
-  var inputNode = LiteGraph.createNode(externalNode, "External Input: " + inputId);
+  var inputNode = LiteGraph.createNode(
+    externalNode,
+    "External Input: " + inputId
+  );
 
   // if (type === "COMBO") {
   //   inputNode = LiteGraph.createNode(externalNode, "External Input: " + inputId, {
@@ -342,7 +344,8 @@ async function convertToInput(node, widget, config) {
   if (type === "COMBO") {
     console.log(inputNode);
     console.log(options);
-    inputNode.widgets.find((x) => x.name == "default_value").options.values = options;
+    inputNode.widgets.find((x) => x.name == "default_value").options.values =
+      options;
   }
 
   app.graph.add(inputNode);
@@ -365,7 +368,11 @@ function getConfig(widgetName) {
 
 function isConvertibleWidget(node, widget, config) {
   // console.log(config);
-  if (node.type === "LoadImage" && widget.type === "combo" && widget.name == "image") {
+  if (
+    node.type === "LoadImage" &&
+    widget.type === "combo" &&
+    widget.name == "image"
+  ) {
     return true;
   }
 
@@ -447,7 +454,7 @@ const ext = {
     } else {
       loadingDialog.showLoading(
         "Loading workflow from " + org_display,
-        "Please wait...",
+        "Please wait..."
       );
       fetch(endpoint + "/api/workflow-version/" + workflow_version_id, {
         method: "GET",
@@ -483,13 +490,61 @@ const ext = {
           window.history.replaceState(
             {},
             document.title,
-            window.location.pathname,
+            window.location.pathname
           );
         });
     }
   },
 
   async beforeRegisterNodeDef(nodeType, nodeData, app2) {
+    // Add text display functionality for ComfyDeployOutputText
+    if (nodeData.name === "ComfyDeployOutputText") {
+      const onNodeCreated = nodeType.prototype.onNodeCreated;
+      nodeType.prototype.onNodeCreated = function () {
+        onNodeCreated ? onNodeCreated.apply(this, []) : undefined;
+
+        // Wait a bit to ensure all other widgets are created first
+        setTimeout(() => {
+          // Import ComfyWidgets if not available globally
+          const ComfyWidgets = app2.widgets || window.ComfyWidgets;
+
+          // Create widget exactly like rgthree does
+          this.textDisplayWidget = ComfyWidgets["STRING"](
+            this,
+            "displayed_text",
+            ["STRING", { multiline: true }],
+            app2
+          ).widget;
+
+          // Make it read-only
+          this.textDisplayWidget.inputEl.readOnly = true;
+
+          // Style it
+          this.textDisplayWidget.inputEl.style.fontFamily = "monospace";
+
+          // Ensure it doesn't get serialized
+          this.textDisplayWidget.serializeValue = () => undefined;
+          this.textDisplayWidget.serialize = false;
+
+          // Remove it from widgets_values array if it exists
+          const widgetIndex = this.widgets.indexOf(this.textDisplayWidget);
+          if (widgetIndex > -1 && this.widgets_values) {
+            this.widgets_values.splice(widgetIndex, 1);
+          }
+        }, 100);
+      };
+
+      const onExecuted = nodeType.prototype.onExecuted;
+      nodeType.prototype.onExecuted = function (message) {
+        onExecuted?.apply(this, [message]);
+
+        // Display the text output on the node
+        if (message.text && message.text.length > 0 && this.textDisplayWidget) {
+          this.textDisplayWidget.value = message.text[0];
+        }
+      };
+    }
+
     const origGetExtraMenuOptions = nodeType.prototype.getExtraMenuOptions;
     nodeType.prototype.getExtraMenuOptions = function (_, options) {
       const r = origGetExtraMenuOptions
@@ -507,7 +562,7 @@ const ext = {
               content: `Convert ${w.name} to widget`,
               callback: /* @__PURE__ */ __name(
                 () => convertToWidget(this, w),
-                "callback",
+                "callback"
               ),
             });
           } else {
@@ -520,7 +575,7 @@ const ext = {
                 content: `Convert ${w.name} to external input`,
                 callback: /* @__PURE__ */ __name(
                   async () => convertToInput(this, w, config),
-                  "callback",
+                  "callback"
                 ),
                 className: "comfydeploy-menu-item",
               });
@@ -545,7 +600,7 @@ const ext = {
               //   className: "comfydeploy-menu-item"
               // },
               ...toInput,
-              null,
+              null
             );
           } else {
             options.push(...toInput, null);
@@ -574,9 +629,7 @@ const ext = {
       console.log(nodeData.input.optional.default_value_url);
     }
 
-    if (
-      nodeData?.input?.optional?.default_value?.[1]?.dynamic_enum === true
-    ) {
+    if (nodeData?.input?.optional?.default_value?.[1]?.dynamic_enum === true) {
       nodeData.input.optional.default_value = ["DYNAMIC_ENUM"];
       // console.log(nodeData.input.optional.default_value);
     }
@@ -642,7 +695,7 @@ const ext = {
           (v) => {
             this.properties.workflow_name = v;
           },
-          { multiline: false },
+          { multiline: false }
         );
 
         this.addWidget(
@@ -652,7 +705,7 @@ const ext = {
           (v) => {
             this.properties.workflow_id = v;
           },
-          { multiline: false },
+          { multiline: false }
         );
 
         this.addWidget(
@@ -662,7 +715,7 @@ const ext = {
           (v) => {
             this.properties.version = v;
           },
-          { multiline: false },
+          { multiline: false }
         );
 
         this.widgets_start_y = 10;
@@ -688,8 +741,19 @@ const ext = {
 
       onConfigure(o) {
         // This method is called when the node is being configured (e.g., when loading a saved graph)
-        // Ensure all necessary data is restored
-        if (o.properties) {
+        // ComfyUI stores widget values in widgets_values array, not properties
+        if (o.widgets_values && o.widgets_values.length >= 3) {
+          // Set the widget values directly
+          this.widgets[0].value = o.widgets_values[0] || "";
+          this.widgets[1].value = o.widgets_values[1] || "";
+          this.widgets[2].value = o.widgets_values[2] || "1";
+
+          // Also update properties to stay in sync
+          this.properties.workflow_name = o.widgets_values[0] || "";
+          this.properties.workflow_id = o.widgets_values[1] || "";
+          this.properties.version = o.widgets_values[2] || "1";
+        } else if (o.properties) {
+          // Fallback to properties if widgets_values is not available
           this.properties = { ...this.properties, ...o.properties };
           this.widgets[0].value = this.properties.workflow_name || "";
           this.widgets[1].value = this.properties.workflow_id || "";
@@ -705,7 +769,7 @@ const ext = {
         title: "Comfy Deploy",
         title_mode: LiteGraph.NORMAL_TITLE,
         collapsable: true,
-      }),
+      })
     );
 
     ComfyDeploy.category = "deploy";
@@ -719,8 +783,8 @@ const ext = {
           "string",
           inputName,
           /* value=*/ "",
-          () => { },
-          { serialize: true },
+          () => {},
+          { serialize: true }
         );
 
         const buttonWidget = node.addWidget(
@@ -734,7 +798,7 @@ const ext = {
             });
             // console.log("load image");
           },
-          { serialize: false },
+          { serialize: false }
         );
 
         console.log(node.widgets);
@@ -783,12 +847,10 @@ const ext = {
 
       DYNAMIC_ENUM(node, inputName, inputData) {
         // console.log("DYNAMIC_ENUM", JSON.parse(JSON.stringify(node)), inputName, inputData);
-        const enumWidget = node.addWidget(
-          "combo",
-          inputName,
-          "",
-          { serialize: true, values: [] },
-        );
+        const enumWidget = node.addWidget("combo", inputName, "", {
+          serialize: true,
+          values: [],
+        });
 
         return { widget: enumWidget };
       },
@@ -796,10 +858,14 @@ const ext = {
   },
 
   async afterConfigureGraph() {
-    app.graph.nodes.forEach(node => {
+    app.graph.nodes.forEach((node) => {
       if (node.type === "ComfyUIDeployExternalEnum") {
-        const default_value_index = node.widgets.findIndex(x => x.name === "default_value");
-        const options_index = node.widgets.findIndex(x => x.name === "options");
+        const default_value_index = node.widgets.findIndex(
+          (x) => x.name === "default_value"
+        );
+        const options_index = node.widgets.findIndex(
+          (x) => x.name === "options"
+        );
 
         var dynamic_enum_options = [node.widgets[default_value_index].value];
         if (node.widgets[options_index].value) {
@@ -828,12 +894,12 @@ const ext = {
             try {
               await window["app"].ui.settings.setSettingValueAsync(
                 "Comfy.Validation.Workflows",
-                true,
+                true
               );
             } catch (error) {
               console.warning(
                 "Error setting validation to false, is fine to ignore this",
-                error,
+                error
               );
             }
             console.log("loadGraphData");
@@ -975,11 +1041,11 @@ const ext = {
         await app.ui.settings.setSettingValueAsync("Comfy.UseNewMenu", "Top");
         await app.ui.settings.setSettingValueAsync(
           "Comfy.Sidebar.Size",
-          "small",
+          "small"
         );
         await app.ui.settings.setSettingValueAsync(
           "Comfy.Sidebar.Location",
-          "left",
+          "left"
         );
         // localStorage.setItem("Comfy.MenuPosition.Docked", "true");
         console.log("native mode manmanman");
@@ -998,7 +1064,6 @@ const ext = {
         }
       })(app.graph.onAfterChange);
 
-
     sendEventToCD("cd_plugin_setup");
   },
 };
@@ -1010,7 +1075,7 @@ const ext = {
 
 function showError(title, message) {
   infoDialog.show(
-    `<h3 style="margin: 0px; color: red;">${title}</h3><br><span>${message}</span> `,
+    `<h3 style="margin: 0px; color: red;">${title}</h3><br><span>${message}</span> `
   );
 }
 
@@ -1033,10 +1098,10 @@ function createDynamicUIHtml(data) {
           <h3 style="font-size: 14px; font-weight: semibold; margin-bottom: 8px;">Missing Nodes</h3>
           <p style="font-size: 12px;">These nodes are not found with any matching custom_nodes in the ComfyUI Manager Database</p>
           ${data.missing_nodes
-        .map((node) => {
-          return `<p style="font-size: 14px; color: #d69e2e;">${node}</p>`;
-        })
-        .join("")}
+            .map((node) => {
+              return `<p style="font-size: 14px; color: #d69e2e;">${node}</p>`;
+            })
+            .join("")}
       </div>
   `;
   }
@@ -1044,14 +1109,17 @@ function createDynamicUIHtml(data) {
   Object.values(data.custom_nodes).forEach((node) => {
     html += `
           <div style="border-bottom: 1px solid #e2e8f0; padding-top: 16px;">
-              <a href="${node.url
-      }" target="_blank" style="font-size: 18px; font-weight: semibold; color: white; text-decoration: none;">${node.name
-      }</a>
+              <a href="${
+                node.url
+              }" target="_blank" style="font-size: 18px; font-weight: semibold; color: white; text-decoration: none;">${
+      node.name
+    }</a>
               <p style="font-size: 14px; color: #4b5563;">${node.hash}</p>
-              ${node.warning
-        ? `<p style="font-size: 14px; color: #d69e2e;">${node.warning}</p>`
-        : ""
-      }
+              ${
+                node.warning
+                  ? `<p style="font-size: 14px; color: #d69e2e;">${node.warning}</p>`
+                  : ""
+              }
           </div>
       `;
   });
@@ -1065,8 +1133,9 @@ function createDynamicUIHtml(data) {
   Object.entries(data.models).forEach(([section, items]) => {
     html += `
     <div style="border-bottom: 1px solid #e2e8f0; padding-top: 8px; padding-bottom: 8px;">
-        <h3 style="font-size: 18px; font-weight: semibold; margin-bottom: 8px;">${section.charAt(0).toUpperCase() + section.slice(1)
-      }</h3>`;
+        <h3 style="font-size: 18px; font-weight: semibold; margin-bottom: 8px;">${
+          section.charAt(0).toUpperCase() + section.slice(1)
+        }</h3>`;
     items.forEach((item) => {
       html += `<p style="font-size: 14px; color: ${textColor};">${item.name}</p>`;
     });
@@ -1082,8 +1151,9 @@ function createDynamicUIHtml(data) {
   Object.entries(data.files).forEach(([section, items]) => {
     html += `
     <div style="border-bottom: 1px solid #e2e8f0; padding-top: 8px; padding-bottom: 8px;">
-        <h3 style="font-size: 18px; font-weight: semibold; margin-bottom: 8px;">${section.charAt(0).toUpperCase() + section.slice(1)
-      }</h3>`;
+        <h3 style="font-size: 18px; font-weight: semibold; margin-bottom: 8px;">${
+          section.charAt(0).toUpperCase() + section.slice(1)
+        }</h3>`;
     items.forEach((item) => {
       html += `<p style="font-size: 14px; color: ${textColor};">${item.name}</p>`;
     });
@@ -1102,9 +1172,9 @@ async function deployWorkflow() {
   /** @type {LGraph} */
   const graph = app.graph;
 
-  let { endpoint, apiKey, displayName } = getData();
+  let { endpoint, apiKey, apiUrl, displayName } = getData();
 
-  if (!endpoint || !apiKey || apiKey === "" || endpoint === "") {
+  if (!endpoint || !apiKey || apiKey === "" || endpoint === "" || !apiUrl) {
     configDialog.show();
     return;
   }
@@ -1114,7 +1184,7 @@ async function deployWorkflow() {
   if (deployMeta.length == 0) {
     const text = await inputDialog.input(
       "Create your deployment",
-      "Workflow name",
+      "Workflow name"
     );
     if (!text) return;
     console.log(text);
@@ -1148,62 +1218,111 @@ async function deployWorkflow() {
 
     <br><br>
     <label>
-    <input id="include-deps" type="checkbox" checked>Include dependency</input>
+    <input id="include-deps" type="checkbox">Include dependency</input>
     </label>
     <br>
     <label>
     <input id="reuse-hash" type="checkbox" checked>Reuse hash from last version</input>
     </label>
     </div>
-    `,
+    `
   );
   if (!ok) return;
 
   const includeDeps = document.getElementById("include-deps").checked;
   const reuseHash = document.getElementById("reuse-hash").checked;
 
+  const prompt = await app.graphToPrompt();
+  let deps = undefined;
+
+  console.log(prompt);
+
+  if (workflow_id.trim() !== "") {
+    const text = await inputDialog.input("Save changes", "Comment");
+    if (!text) return;
+
+    try {
+      loadingDialog.showLoading("Saving changes");
+
+      const body = {
+        api_url: apiUrl,
+        workflow: prompt.workflow,
+        workflow_id: workflow_id,
+        workflow_api: prompt.output,
+        comment: text,
+      };
+
+      let data = await fetch("/comfyui-deploy/workflow/version", {
+        method: "POST",
+        body: JSON.stringify(body),
+        headers: {
+          "Content-Type": "application/json",
+          Authorization: "Bearer " + apiKey,
+        },
+      });
+
+      if (data.status !== 200) {
+        throw new Error(await data.text());
+      } else {
+        data = await data.json();
+
+        console.log(data);
+
+        infoDialog.show(
+          `<span style="color:green;">New version created!</span> <br/> <br/> Workflow ID: ${data.workflow_id} <br/> Workflow Name: ${workflow_name} <br/> Workflow Version: ${data.version} <br/>`
+        );
+
+        deployMetaNode.widgets[2].value = data.version;
+        graph.change();
+      }
+    } catch (e) {
+      infoDialog.showError("Error", e.message);
+      return;
+    } finally {
+      loadingDialog.close();
+      return;
+    }
+  }
+
   if (endpoint.endsWith("/")) {
     endpoint = endpoint.slice(0, -1);
   }
   loadingDialog.showLoading("Generating snapshot");
 
   const snapshot = await fetch("/snapshot/get_current").then((x) => x.json());
-  // console.log(snapshot);
+  console.log(snapshot);
   loadingDialog.close();
 
   if (!snapshot) {
     showError(
       "Error when deploying",
-      "Unable to generate snapshot, please install ComfyUI Manager",
+      "Unable to generate snapshot, please install ComfyUI Manager"
     );
     return;
   }
 
   const title = deploy.querySelector("#button-title");
 
-  const prompt = await app.graphToPrompt();
-  let deps = undefined;
-
-  console.log(prompt);
-
   if (includeDeps) {
     loadingDialog.showLoading("Fetching existing version");
 
     const existing_workflow = await fetch(
-      endpoint + "/api/workflow/" + workflow_id,
+      apiUrl + "/api/workflow/" + workflow_id,
       {
         method: "GET",
         headers: {
           "Content-Type": "application/json",
           Authorization: "Bearer " + apiKey,
         },
-      },
+      }
     )
       .then((x) => x.json())
       .catch(() => {
         return {};
       });
 
+    console.log("workflow", existing_workflow);
+
     loadingDialog.close();
 
     loadingDialog.showLoading("Generating dependency graph");
@@ -1216,7 +1335,7 @@ async function deployWorkflow() {
         // Match previous hash for models
         if (reuseHash && existing_workflow?.dependencies?.models) {
           const previousModelHash = Object.entries(
-            existing_workflow?.dependencies?.models,
+            existing_workflow?.dependencies?.models
           ).flatMap(([key, value]) => {
             return Object.values(value).map((x) => ({
               ...x,
@@ -1238,7 +1357,7 @@ async function deployWorkflow() {
         console.log(file);
         loadingDialog.showLoading("Generating hash", file);
         const hash = await fetch(
-          `/comfyui-deploy/get-file-hash?file_path=${encodeURIComponent(file)}`,
+          `/comfyui-deploy/get-file-hash?file_path=${encodeURIComponent(file)}`
         ).then((x) => x.json());
         loadingDialog.showLoading("Generating hash", file);
         console.log(hash);
@@ -1287,6 +1406,7 @@ async function deployWorkflow() {
       };
 
     loadingDialog.close();
+    console.log(deps);
 
     const depsOk = await confirmDialog.confirm(
       "Check dependencies",
@@ -1305,13 +1425,12 @@ async function deployWorkflow() {
       <iframe 
       style="z-index: 10; min-width: 600px; max-width: 1024px; min-height: 600px; border: none; background-color: transparent;"
       src="https://www.comfydeploy.com/dependency-graph?deps=${encodeURIComponent(
-        JSON.stringify(deps),
-      )}" />`,
+        JSON.stringify(deps)
+      )}" />`
       // createDynamicUIHtml(deps),
     );
-    if (!depsOk) return;
 
-    console.log(deps);
+    if (!depsOk) return;
   }
 
   loadingDialog.showLoading("Deploying...");
@@ -1319,28 +1438,15 @@ async function deployWorkflow() {
   title.innerText = "Deploying...";
   title.style.color = "orange";
 
-  // console.log(prompt);
-
-  // TODO trim the ending / from endpoint is there is
-  if (endpoint.endsWith("/")) {
-    endpoint = endpoint.slice(0, -1);
-  }
-
-  // console.log(prompt.workflow);
-
-  const apiRoute = endpoint + "/api/workflow";
-  // const userId = apiKey
   try {
     const body = {
-      workflow_name,
-      workflow_id,
-      workflow: prompt.workflow,
+      name: workflow_name,
+      workflow_json: prompt.workflow,
       workflow_api: prompt.output,
-      snapshot: snapshot,
-      dependencies: deps,
+      api_url: apiUrl,
     };
     console.log(body);
-    let data = await fetch(apiRoute, {
+    let data = await fetch("/comfyui-deploy/workflow", {
       method: "POST",
       body: JSON.stringify(body),
       headers: {
@@ -1350,11 +1456,11 @@ async function deployWorkflow() {
     });
 
     console.log(data);
-
     if (data.status !== 200) {
       throw new Error(await data.text());
     } else {
       data = await data.json();
+      await refreshWorkflowListIfOpen();
     }
 
     loadingDialog.close();
@@ -1363,20 +1469,37 @@ async function deployWorkflow() {
     title.style.color = "green";
 
     deployMetaNode.widgets[1].value = data.workflow_id;
-    deployMetaNode.widgets[2].value = data.version;
+    deployMetaNode.widgets[2].value = 2;
     graph.change();
 
-    infoDialog.show(
-      `<span style="color:green;">Deployed successfully!</span>  <a style="color:white;" target="_blank" href=${endpoint}/workflows/${data.workflow_id}>-> View here</a> <br/> <br/> Workflow ID: ${data.workflow_id} <br/> Workflow Name: ${workflow_name} <br/> Workflow Version: ${data.version} <br/>`,
-    );
+    if (data.workflow_id) {
+      const prompt_with_workflow_id = await app.graphToPrompt();
 
-    // // Refresh the workflows list in the sidebar
-    // const sidebarEl = document.querySelector(
-    //   '.comfy-sidebar-tab[data-id="search"]',
-    // );
-    // if (sidebarEl) {
-    //   refreshWorkflowsList(sidebarEl);
-    // }
+      const body = {
+        api_url: apiUrl,
+        workflow: prompt_with_workflow_id.workflow,
+        workflow_id: data.workflow_id,
+        workflow_api: prompt_with_workflow_id.output,
+        comment: "chore: apply workflow id",
+      };
+
+      let new_version_data = await fetch("/comfyui-deploy/workflow/version", {
+        method: "POST",
+        body: JSON.stringify(body),
+        headers: {
+          "Content-Type": "application/json",
+          Authorization: "Bearer " + apiKey,
+        },
+      });
+
+      if (new_version_data.status !== 200) {
+        throw new Error(await new_version_data.text());
+      }
+    }
+
+    infoDialog.show(
+      `<span style="color:green;">Deployed successfully!</span>  <a style="color:white;" target="_blank" href=${endpoint}/workflows/${data.workflow_id}>-> View here</a> <br/> <br/> Workflow ID: ${data.workflow_id} <br/> Workflow Name: ${workflow_name} <br/> Workflow Version: 2 <br/>`
+    );
 
     setTimeout(() => {
       title.textContent = "Deploy";
@@ -1489,6 +1612,24 @@ export class InfoDialog extends ComfyDialog {
         </div>
       `);
   }
+
+  showError(title, message) {
+    this.show(`
+      <div style="width: 100%; max-width: 600px; display: flex; gap: 18px; flex-direction: column; overflow: unset">
+        <h3 style="margin: 0px; color: #ff4444; display: flex; align-items: center; gap: 8px;">
+          <svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round">
+            <path d="M18 6L6 18M6 6l12 12"/>
+          </svg>
+          ${title}
+        </h3>
+        <div style="padding: 12px;">
+          ${message}
+        </div>
+      </div>
+    `);
+    // Set higher z-index to appear above config dialog
+    this.element.style.zIndex = 1010;
+  }
 }
 
 export class LoadingDialog extends ComfyDialog {
@@ -1524,12 +1665,14 @@ export class LoadingDialog extends ComfyDialog {
   showLoading(title, message) {
     this.show(`
       <div style="width: 400px; display: flex; gap: 18px; flex-direction: column; overflow: unset">
-        <h3 style="margin: 0px; display: flex; align-items: center; justify-content: center; gap: 12px;">${title} ${this.loadingIcon
-      }</h3>
-          ${message
-        ? `<label style="max-width: 100%; white-space: pre-wrap; word-wrap: break-word;">${message}</label>`
-        : ""
-      }
+        <h3 style="margin: 0px; display: flex; align-items: center; justify-content: center; gap: 12px;">${title} ${
+      this.loadingIcon
+    }</h3>
+          ${
+            message
+              ? `<label style="max-width: 100%; white-space: pre-wrap; word-wrap: break-word;">${message}</label>`
+              : ""
+          }
         </div>
       `);
   }
@@ -1578,7 +1721,7 @@ export class InputDialog extends InfoDialog {
               }
             },
           }),
-        ],
+        ]
       ),
     ];
   }
@@ -1639,7 +1782,7 @@ export class ConfirmDialog extends InfoDialog {
               this.close();
             },
           }),
-        ],
+        ]
       ),
     ];
   }
@@ -1674,12 +1817,14 @@ function getData(environment) {
   if (!data) {
     if (deployOption == "cloud")
       return {
-        endpoint: "https://www.comfydeploy.com",
+        endpoint: "https://app.comfydeploy.com",
+        apiUrl: "https://api.comfydeploy.com",
         apiKey: "",
       };
     else
       return {
-        endpoint: "http://localhost:3000",
+        endpoint: "http://localhost:3001",
+        apiUrl: "http://localhost:3011",
         apiKey: "",
       };
   }
@@ -1696,7 +1841,7 @@ function getData(environment) {
 function saveData(data) {
   localStorage.setItem(
     "comfy_deploy_env_data_" + data.environment,
-    JSON.stringify(data),
+    JSON.stringify(data)
   );
 }
 
@@ -1745,7 +1890,7 @@ export class ConfigDialog extends ComfyDialog {
               this.close();
             },
           }),
-        ],
+        ]
       ),
     ];
   }
@@ -1756,7 +1901,7 @@ export class ConfigDialog extends ComfyDialog {
     clearTimeout(this.timeout);
   }
 
-  save(api_key, displayName) {
+  async save(api_key, displayName) {
     const deployOption = this.container.querySelector("#deployOption").value;
     localStorage.setItem("comfy_deploy_env", deployOption);
 
@@ -1773,10 +1918,14 @@ export class ConfigDialog extends ComfyDialog {
 
     saveData({
       endpoint,
+      apiUrl: getData(deployOption).apiUrl,
       apiKey,
       displayName,
       environment: deployOption,
     });
+
+    // Refresh workflow list after saving configuration
+    await refreshWorkflowListIfOpen();
   }
 
   show() {
@@ -1789,23 +1938,33 @@ export class ConfigDialog extends ComfyDialog {
     <h3 style="margin: 0px;">Comfy Deploy Config</h3>
     <label style="color: white; width: 100%;">
       <select id="deployOption" style="margin: 8px 0px; width: 100%; height:30px; box-sizing: border-box;" >
-        <option value="cloud" ${data.environment === "cloud" ? "selected" : ""}>Cloud</option>
-        <option value="local" ${data.environment === "local" ? "selected" : ""}>Local</option>
+        <option value="cloud" ${
+          data.environment === "cloud" ? "selected" : ""
+        }>Cloud</option>
+        <option value="local" ${
+          data.environment === "local" ? "selected" : ""
+        }>Local</option>
       </select>
     </label>
       <label style="color: white; width: 100%;">
         Endpoint:
-        <input id="endpoint" style="margin-top: 8px; width: 100%; height:40px; box-sizing: border-box; padding: 0px 6px;" type="text" value="${data.endpoint
-      }">
+        <input id="endpoint" style="margin-top: 8px; width: 100%; height:40px; box-sizing: border-box; padding: 0px 6px;" type="text" value="${
+          data.endpoint
+        }">
       </label>
       <div style="color: white;">
-        API Key: User / Org <button style="font-size: 18px;">${data.displayName ?? ""
-      }</button>
-        <input id="apiKey" style="margin-top: 8px; width: 100%; height:40px; box-sizing: border-box; padding: 0px 6px;" type="password" value="${data.apiKey
-      }">
+        API Key: User / Org ${
+          data.displayName
+            ? `<button style="font-size: 18px;">${data.displayName}</button>`
+            : ""
+        }
+        <input id="apiKey" style="margin-top: 8px; width: 100%; height:40px; box-sizing: border-box; padding: 0px 6px;" type="password" value="${
+          data.apiKey
+        }">
         <button id="loginButton" style="margin-top: 8px; width: 100%; height:40px; box-sizing: border-box; padding: 0px 6px;">
-          ${data.apiKey ? "Re-login with ComfyDeploy" : "Login with ComfyDeploy"
-      }
+          ${
+            data.apiKey ? "Re-login with ComfyDeploy" : "Login with ComfyDeploy"
+          }
         </button>
       </div>
       </div>
@@ -1816,21 +1975,23 @@ export class ConfigDialog extends ComfyDialog {
       this.save();
       const data = getData();
 
-      const uuid =
-        Math.random().toString(36).substring(2, 15) +
-        Math.random().toString(36).substring(2, 15);
-      window.open(data.endpoint + "/auth-request/" + uuid, "_blank");
+      const uuid = crypto.randomUUID();
+      window.open(data.endpoint + "/auth/request/" + uuid, "_blank");
 
       this.timeout = setTimeout(() => {
-        clearInterval(poll);
-        infoDialog.showMessage(
+        clearInterval(this.poll);
+        infoDialog.showError(
           "Timeout",
-          "Wait too long for the response, please try re-login",
+          "Wait too long for the response, please try re-login"
         );
       }, 30000); // Stop polling after 30 seconds
 
       this.poll = setInterval(() => {
-        fetch(data.endpoint + "/api/auth-response/" + uuid)
+        fetch(
+          `/comfyui-deploy/auth-response?request_id=${uuid}&api_url=${encodeURIComponent(
+            data.apiUrl
+          )}`
+        )
           .then((response) => response.json())
           .then(async (json) => {
             if (json.api_key) {
@@ -1843,8 +2004,9 @@ export class ConfigDialog extends ComfyDialog {
               // Refresh dialog
               const a = await confirmDialog.confirm(
                 "Authenticated",
-                `<div>You will be able to upload workflow to <button style="font-size: 18px; width: fit;">${json.name}</button></div>`,
+                `<div>You will be able to upload workflow to <button style="font-size: 18px; width: fit;">${json.name}</button></div>`
               );
+
               configDialog.show();
             }
           })
@@ -1899,7 +2061,7 @@ if (isLocalhost) {
     title: "Deploy",
     tooltip: "Deploy and Configure",
     type: "custom",
-    render: (el) => {
+    render: async (el) => {
       el.innerHTML = `
         <div style="padding: 20px;">
           <h3>Comfy Deploy</h3>
@@ -1964,7 +2126,12 @@ if (isLocalhost) {
       const workflowsList = el.querySelector("#workflows-list");
       const workflowsLoading = el.querySelector("#workflows-loading");
 
-      // refreshWorkflowsList(el);
+      // Initialize workflows list and search
+      const data = getData();
+      if (data.apiKey) {
+        addWorkflowSearch(el, getData, getTimeAgo);
+        await initializeWorkflowsList(el, getData, getTimeAgo);
+      }
     },
   });
 }
@@ -2250,7 +2417,7 @@ function addMenuButtons(options) {
 
   // Remove any existing CD buttons
   const existingButtons = document.querySelectorAll(
-    `[id^="${buttonIdPrefix}"]`,
+    `[id^="${buttonIdPrefix}"]`
   );
   existingButtons.forEach((button) => button.remove());
 
@@ -2347,3 +2514,34 @@ function addMenuRightButtons(buttonConfigs) {
     containerStyle: {},
   });
 }
+
+// Function to refresh workflow list if sidebar is open
+async function refreshWorkflowListIfOpen() {
+  try {
+    const workflowsContainer = document.querySelector("#workflows-container");
+    const workflowsList = document.querySelector("#workflows-list");
+
+    // Only refresh if workflows container is visible and has been initialized
+    if (!workflowsContainer || !workflowsList) {
+      return;
+    }
+
+    // Import the functions we need
+    const { initializeWorkflowsList } = await import("./workflow-list.js");
+
+    // Clear existing workflows and reset state safely
+    workflowsList.innerHTML = "";
+    if (window.workflowsState) {
+      window.workflowsState.initialized = false;
+      window.workflowsState.workflows = [];
+      window.workflowsState.offset = 0;
+      window.workflowsState.hasMore = true;
+    }
+    // Reinitialize the workflow list
+    await initializeWorkflowsList(document, getData, getTimeAgo);
+
+    console.log("Workflow list refreshed successfully");
+  } catch (error) {
+    console.error("Error refreshing workflow list:", error);
+  }
+}

web-plugin/workflow-list.js

@@ -0,0 +1,387 @@
+// Workflow list management
+let workflowsState = {
+  workflows: [],
+  offset: 0,
+  limit: 20,
+  loading: false,
+  hasMore: true,
+  initialized: false,
+  currentSearch: "",
+};
+
+// Make workflowsState accessible globally
+window.workflowsState = workflowsState;
+
+async function fetchWorkflows(getData, offset = 0, limit = 20, search = "") {
+  try {
+    const data = getData();
+    if (!data.apiKey) {
+      throw new Error("API key not configured");
+    }
+
+    const params = new URLSearchParams({
+      offset: offset.toString(),
+      limit: limit.toString(),
+      api_url: data.apiUrl || "https://api.comfydeploy.com",
+      ...(search && { search }),
+    });
+
+    const response = await fetch(`/comfyui-deploy/workflows?${params}`, {
+      method: "GET",
+      headers: {
+        Authorization: `Bearer ${data.apiKey}`,
+        "Content-Type": "application/json",
+      },
+    });
+
+    if (!response.ok) {
+      throw new Error(`Failed to fetch workflows: ${response.status}`);
+    }
+
+    const result = await response.json();
+    console.log("result", result);
+    return Array.isArray(result) ? result : [];
+  } catch (error) {
+    console.error("Error fetching workflows:", error);
+    return [];
+  }
+}
+
+function createWorkflowItem(workflow, getTimeAgo, getData) {
+  const li = document.createElement("li");
+  li.style.cssText = `
+      border-bottom: 1px solid #444;
+      background: transparent;
+      transition: all 0.2s ease;
+      cursor: pointer;
+    `;
+
+  li.addEventListener("mouseenter", () => {
+    li.style.background = "#333";
+  });
+
+  li.addEventListener("mouseleave", () => {
+    li.style.background = "transparent";
+  });
+
+  // Add click handler to fetch and load workflow data
+  li.addEventListener("click", async () => {
+    try {
+      const data = getData();
+      if (!data.apiKey) {
+        console.error("No API key configured");
+        return;
+      }
+
+      // Show loading toast
+      const loadingToast = window.app.extensionManager.toast.add({
+        severity: "info",
+        summary: "Loading workflow...",
+        detail: `Loading "${workflow.name}"`,
+        life: 3000,
+      });
+
+      const params = new URLSearchParams({
+        workflow_id: workflow.id,
+        api_url: data.apiUrl || "https://api.comfydeploy.com",
+      });
+
+      const response = await fetch(`/comfyui-deploy/workflow?${params}`, {
+        method: "GET",
+        headers: {
+          Authorization: `Bearer ${data.apiKey}`,
+          "Content-Type": "application/json",
+        },
+      });
+
+      if (!response.ok) {
+        throw new Error(`Failed to fetch workflow: ${response.status}`);
+      }
+
+      const workflowData = await response.json();
+      console.log("Workflow data:", workflowData);
+
+      // Load the workflow into the graph
+      if (workflowData.versions && workflowData.versions.length > 0) {
+        const latestVersion = workflowData.versions[0];
+        if (latestVersion.workflow && window.app) {
+          // Load the workflow
+          window.app.loadGraphData(latestVersion.workflow);
+
+          // Show success toast
+          window.app.extensionManager.toast.add({
+            severity: "success",
+            summary: "Workflow loaded successfully",
+            detail: `Loaded "${workflow.name}" v${latestVersion.version}`,
+            life: 3000,
+          });
+        }
+      }
+    } catch (error) {
+      console.error("Error loading workflow:", error);
+      // Show error toast
+      window.app.extensionManager.toast.add({
+        severity: "error",
+        summary: "Failed to load workflow",
+        detail: error.message,
+        life: 5000,
+      });
+    } finally {
+      loadingToast.close();
+    }
+  });
+
+  const updatedDate = new Date(workflow.updated_at);
+  const timeAgo = getTimeAgo(updatedDate);
+
+  li.innerHTML = `
+      <div style="padding: 12px 16px;">
+        <div style="display: flex; align-items: flex-start; gap: 12px;">
+          ${
+            workflow.cover_image
+              ? `<img src="${workflow.cover_image}" 
+                     style="width: 40px; height: 40px; border-radius: 4px; object-fit: cover; flex-shrink: 0;"
+                     onerror="this.style.display='none'">`
+              : `<div style="width: 40px; height: 40px; border-radius: 4px; background: #444; flex-shrink: 0; display: flex; align-items: center; justify-content: center; font-size: 14px; color: #888;">
+                   ${workflow.name.charAt(0).toUpperCase()}
+                 </div>`
+          }
+          
+          <div style="flex: 1; min-width: 0;">
+            <div style="display: flex; align-items: center; gap: 8px; margin-bottom: 4px;">
+              <h4 style="margin: 0; font-size: 14px; font-weight: 400; color: #fff; white-space: nowrap; overflow: hidden; text-overflow: ellipsis;">
+                ${workflow.name}
+              </h4>
+              ${
+                workflow.pinned
+                  ? `<span style="color: #ffd700; font-size: 12px;">📌</span>`
+                  : ""
+              }
+            </div>
+            
+            ${
+              workflow.description
+                ? `<p style="margin: 0 0 8px 0; font-size: 12px; color: #bbb; line-height: 1.3; overflow: hidden; display: -webkit-box; -webkit-line-clamp: 2; -webkit-box-orient: vertical;">
+                     ${workflow.description}
+                   </p>`
+                : ""
+            }
+            
+            <div style="display: flex; align-items: center; gap: 8px; margin-top: 8px;">
+              <img src="${workflow.user_icon}" 
+                   style="width: 16px; height: 16px; border-radius: 50%;"
+                   onerror="this.style.display='none'">
+              <span style="font-size: 11px; color: #888;">
+                ${workflow.user_name} • Updated ${timeAgo}
+              </span>
+            </div>
+          </div>
+        </div>
+      </div>
+    `;
+
+  return li;
+}
+
+async function loadMoreWorkflows(element, getData, getTimeAgo) {
+  if (workflowsState.loading || !workflowsState.hasMore) return;
+
+  workflowsState.loading = true;
+
+  const workflowsList = element.querySelector("#workflows-list");
+  const workflowsLoading = element.querySelector("#workflows-loading");
+
+  // Show loading indicator
+  workflowsLoading.style.display = "flex";
+
+  try {
+    const newWorkflows = await fetchWorkflows(
+      getData,
+      workflowsState.offset,
+      workflowsState.limit,
+      workflowsState.currentSearch
+    );
+
+    if (newWorkflows.length === 0) {
+      workflowsState.hasMore = false;
+    } else {
+      workflowsState.workflows.push(...newWorkflows);
+      workflowsState.offset += newWorkflows.length;
+
+      // Render new workflow items
+      newWorkflows.forEach((workflow) => {
+        const workflowItem = createWorkflowItem(workflow, getTimeAgo, getData);
+        workflowsList.appendChild(workflowItem);
+      });
+    }
+  } catch (error) {
+    console.error("Error loading more workflows:", error);
+  } finally {
+    workflowsState.loading = false;
+    workflowsLoading.style.display = "none";
+  }
+}
+
+function setupInfiniteScroll(container, element, getData, getTimeAgo) {
+  let isScrolling = false;
+
+  container.addEventListener("scroll", () => {
+    if (isScrolling) return;
+
+    const { scrollTop, scrollHeight, clientHeight } = container;
+
+    // Load more when scrolled to bottom (with 100px threshold)
+    if (scrollTop + clientHeight >= scrollHeight - 100) {
+      isScrolling = true;
+      loadMoreWorkflows(element, getData, getTimeAgo).finally(() => {
+        isScrolling = false;
+      });
+    }
+  });
+}
+
+async function initializeWorkflowsList(element, getData, getTimeAgo) {
+  const workflowsContainer = element.querySelector("#workflows-container");
+  const workflowsList = element.querySelector("#workflows-list");
+  const workflowsLoading = element.querySelector("#workflows-loading");
+
+  // Check if already initialized AND the DOM elements still exist
+  if (
+    workflowsState.initialized &&
+    workflowsList &&
+    workflowsList.children.length > 0
+  )
+    return;
+
+  try {
+    // Reset state (always reset when reinitializing)
+    workflowsState = {
+      workflows: [],
+      offset: 0,
+      limit: 20,
+      loading: false,
+      hasMore: true,
+      initialized: true,
+      currentSearch: "",
+    };
+
+    // Clear existing content in case of reinitialization
+    if (workflowsList) {
+      workflowsList.innerHTML = "";
+    }
+
+    // Show container and loading
+    workflowsContainer.style.display = "block";
+    workflowsLoading.style.display = "flex";
+
+    // Style the workflows list for full height scrolling
+    workflowsList.style.cssText = `
+        list-style-type: none;
+        padding: 0;
+        margin: 0;
+        height: calc(100vh - 350px);
+        overflow-y: auto;
+        scrollbar-width: thin;
+        scrollbar-color: #666 transparent;
+        border-top: 1px solid #444;
+      `;
+
+    // Add webkit scrollbar styles
+    const style = document.createElement("style");
+    style.textContent = `
+        #workflows-list::-webkit-scrollbar {
+          width: 6px;
+        }
+        #workflows-list::-webkit-scrollbar-track {
+          background: transparent;
+        }
+        #workflows-list::-webkit-scrollbar-thumb {
+          background: #666;
+          border-radius: 3px;
+        }
+        #workflows-list::-webkit-scrollbar-thumb:hover {
+          background: #777;
+        }
+      `;
+    document.head.appendChild(style);
+
+    // Setup infinite scroll
+    setupInfiniteScroll(workflowsList, element, getData, getTimeAgo);
+
+    // Load initial workflows
+    await loadMoreWorkflows(element, getData, getTimeAgo);
+
+    // Show the list
+    workflowsList.style.display = "block";
+  } catch (error) {
+    console.error("Error initializing workflows list:", error);
+    workflowsLoading.innerHTML = `
+        <div style="text-align: center; color: #e74c3c; font-size: 12px; padding: 20px;">
+          <div>Failed to load workflows</div>
+          <button onclick="initializeWorkflowsList(this.closest('.comfy-menu'), getData, getTimeAgo)" 
+                  style="margin-top: 8px; padding: 4px 8px; font-size: 11px; background: #f0f0f0; border: 1px solid #ccc; border-radius: 4px; cursor: pointer;">
+            Retry
+          </button>
+        </div>
+      `;
+  }
+}
+
+// Search functionality
+function addWorkflowSearch(element, getData, getTimeAgo) {
+  const workflowsContainer = element.querySelector("#workflows-container");
+  const h4 = workflowsContainer.querySelector("h4");
+
+  const searchContainer = document.createElement("div");
+  searchContainer.style.cssText = "margin-bottom: 12px;";
+
+  const searchInput = document.createElement("input");
+  searchInput.type = "text";
+  searchInput.placeholder = "Search workflows...";
+  searchInput.style.cssText = `
+      width: 100%;
+      padding: 8px 12px;
+      border: 1px solid #555;
+      border-radius: 6px;
+      font-size: 12px;
+      box-sizing: border-box;
+      background: #333;
+      color: #fff;
+    `;
+
+  let searchTimeout;
+  searchInput.addEventListener("input", (e) => {
+    clearTimeout(searchTimeout);
+    searchTimeout = setTimeout(async () => {
+      const searchTerm = e.target.value.trim();
+
+      // Update the tracked search term
+      workflowsState.currentSearch = searchTerm;
+
+      // Reset state for new search
+      workflowsState.workflows = [];
+      workflowsState.offset = 0;
+      workflowsState.hasMore = true;
+
+      // Clear current list
+      const workflowsList = element.querySelector("#workflows-list");
+      workflowsList.innerHTML = "";
+
+      // Load with search term
+      workflowsState.loading = false;
+      await loadMoreWorkflows(element, getData, getTimeAgo);
+    }, 300);
+  });
+
+  searchContainer.appendChild(searchInput);
+  h4.after(searchContainer);
+}
+
+// Export the functions
+export {
+  initializeWorkflowsList,
+  addWorkflowSearch,
+  workflowsState,
+  fetchWorkflows,
+  loadMoreWorkflows,
+};