update: don't randomize noise_seed if it's an input from another node

This reverts commit 7552353e30.

.gitignore

@@ -1,2 +1,3 @@
 __pycache__
-.DS_Store
+.DS_Store
+file-hash-cache.json

README.md

@@ -2,6 +2,9 @@
 
 Open source comfyui deployment platform, a `vercel` for generative workflow infra. (serverless hosted gpu with vertical intergation with comfyui)
 
+> [!NOTE]  
+> Im looking for creative hacker to join ComfyDeploy's core team! DM me on [twitter](https://x.com/BennyKokMusic)
+
 Join [Discord](https://discord.gg/EEYcQmdYZw) to chat more or visit [Comfy Deploy](https://comfydeploy.com/) to get started!
 
 Check out our latest [nextjs starter kit](https://github.com/BennyKok/comfyui-deploy-next-example) with Comfy Deploy

comfy-nodes/external_audio.py

@@ -0,0 +1,57 @@
+import os
+import io
+import torchaudio
+from folder_paths import get_annotated_filepath
+
+class ComfyUIDeployExternalAudio:
+    RETURN_TYPES = ("AUDIO",)
+    RETURN_NAMES = ("audio",)
+    FUNCTION = "load_audio"
+    
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "input_id": (
+                    "STRING",
+                    {"multiline": False, "default": "input_audio"},
+                ),
+                "audio_file": ("STRING", {"default": ""}),
+            },
+            "optional": {
+                "default_value": ("AUDIO",),
+                "display_name": (
+                    "STRING",
+                    {"multiline": False, "default": ""},
+                ),
+                "description": (
+                    "STRING",
+                    {"multiline": False, "default": ""},
+                ),
+            }
+        }
+    
+    @classmethod
+    def VALIDATE_INPUTS(s, audio_file, **kwargs):
+        return True
+
+    def load_audio(self, input_id, audio_file, default_value=None, display_name=None, description=None):
+        if audio_file and audio_file != "":
+            if audio_file.startswith(('http://', 'https://')):
+                # Handle URL input
+                import requests
+                response = requests.get(audio_file)
+                audio_data = io.BytesIO(response.content)
+                waveform, sample_rate = torchaudio.load(audio_data)
+            else:
+                # Handle local file
+                audio_path = get_annotated_filepath(audio_file)
+                waveform, sample_rate = torchaudio.load(audio_path)
+            
+            audio = {"waveform": waveform.unsqueeze(0), "sample_rate": sample_rate}
+            return (audio,)
+        else:
+            return (default_value,)
+
+NODE_CLASS_MAPPINGS = {"ComfyUIDeployExternalAudio": ComfyUIDeployExternalAudio}
+NODE_DISPLAY_NAME_MAPPINGS = {"ComfyUIDeployExternalAudio": "External Audio (ComfyUI Deploy)"}

comfy-nodes/external_exr.py

@@ -0,0 +1,109 @@
+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"
+    
+    @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_image.py

@@ -21,8 +21,9 @@ class ComfyUIDeployExternalImage:
                 ),
                 "description": (
                     "STRING",
-                    {"multiline": True, "default": ""},
+                    {"multiline": False, "default": ""},
                 ),
+                "default_value_url": ("STRING", {"image_preview": True, "default": ""}),
             }
         }
 
@@ -33,32 +34,44 @@ class ComfyUIDeployExternalImage:
 
     CATEGORY = "image"
 
-    def run(self, input_id, default_value=None, display_name=None, description=None):
+    def run(self, input_id, default_value=None, display_name=None, description=None, default_value_url=None):
         image = default_value
-        try:
-            if input_id.startswith('http'):
-                import requests
-                from io import BytesIO
-                print("Fetching image from url: ", input_id)
-                response = requests.get(input_id)
-                image = Image.open(BytesIO(response.content))
-            elif input_id.startswith('data:image/png;base64,') or input_id.startswith('data:image/jpeg;base64,') or input_id.startswith('data:image/jpg;base64,'):
-                import base64
-                from io import BytesIO
-                print("Decoding base64 image")
-                base64_image = input_id[input_id.find(",")+1:]
-                decoded_image = base64.b64decode(base64_image)
-                image = Image.open(BytesIO(decoded_image))
-            else:
-                raise ValueError("Invalid image url provided.")
-
-            image = ImageOps.exif_transpose(image)
-            image = image.convert("RGB")
-            image = np.array(image).astype(np.float32) / 255.0
-            image = torch.from_numpy(image)[None,]
-            return [image]
-        except:
-            return [image]
+        
+        # Try both input_id and default_value_url
+        urls_to_try = [url for url in [input_id, default_value_url] if url]
+        
+        print(default_value_url)
+        
+        for url in urls_to_try:
+            try:
+                if url.startswith('http'):
+                    import requests
+                    from io import BytesIO
+                    print(f"Fetching image from url: {url}")
+                    response = requests.get(url)
+                    image = Image.open(BytesIO(response.content))
+                    break
+                elif url.startswith(('data:image/png;base64,', 'data:image/jpeg;base64,', 'data:image/jpg;base64,')):
+                    import base64
+                    from io import BytesIO
+                    print("Decoding base64 image")
+                    base64_image = url[url.find(",")+1:]
+                    decoded_image = base64.b64decode(base64_image)
+                    image = Image.open(BytesIO(decoded_image))
+                    break
+            except:
+                continue
+        
+        if image is not None:
+            try:
+                image = ImageOps.exif_transpose(image)
+                image = image.convert("RGB")
+                image = np.array(image).astype(np.float32) / 255.0
+                image = torch.from_numpy(image)[None,]
+            except:
+                pass
+                
+        return [image]
 
 
 NODE_CLASS_MAPPINGS = {"ComfyUIDeployExternalImage": ComfyUIDeployExternalImage}

comfy-nodes/external_lora.py

@@ -64,32 +64,42 @@ class ComfyUIDeployExternalLora:
         import os
         import uuid
 
-        if lora_url and lora_url.startswith("http"):
-            if lora_save_name:
-                existing_loras = folder_paths.get_filename_list("loras")
-                # Check if lora_save_name exists in the list
-                if lora_save_name in existing_loras:
-                    print(f"using lora: {lora_save_name}")
-                    return (lora_save_name,)
+        if lora_url:
+            if lora_url.startswith("http"):
+                if lora_save_name:
+                    existing_loras = folder_paths.get_filename_list("loras")
+                    # Check if lora_save_name exists in the list
+                    if lora_save_name in existing_loras:
+                        print(f"using lora: {lora_save_name}")
+                        return (lora_save_name,)
+                else:
+                    lora_save_name = str(uuid.uuid4()) + ".safetensors"
+                print(lora_save_name)
+                print(folder_paths.folder_names_and_paths["loras"][0][0])
+                destination_path = os.path.join(
+                    folder_paths.folder_names_and_paths["loras"][0][0], lora_save_name
+                )
+                print(destination_path)
+                print(
+                    "Downloading external lora - "
+                    + lora_url
+                    + " to "
+                    + destination_path
+                )
+                response = requests.get(
+                    lora_url,
+                    headers={"User-Agent": "Mozilla/5.0"},
+                    allow_redirects=True,
+                )
+                with open(destination_path, "wb") as out_file:
+                    out_file.write(response.content)
+                print(f"Ext Lora loading: {lora_url} to {lora_save_name}")
+                return (lora_save_name,)
             else:
-                lora_save_name = str(uuid.uuid4()) + ".safetensors"
-            print(lora_save_name)
-            print(folder_paths.folder_names_and_paths["loras"][0][0])
-            destination_path = os.path.join(
-                folder_paths.folder_names_and_paths["loras"][0][0], lora_save_name
-            )
-            print(destination_path)
-            print("Downloading external lora - " + lora_url + " to " + destination_path)
-            response = requests.get(
-                lora_url,
-                headers={"User-Agent": "Mozilla/5.0"},
-                allow_redirects=True,
-            )
-            with open(destination_path, "wb") as out_file:
-                out_file.write(response.content)
-            return (lora_save_name,)
+                print(f"Ext Lora loading: {lora_url}")
+                return (lora_url,)
         else:
-            print(f"using lora: {default_lora_name}")
+            print(f"Ext Lora loading: {default_lora_name}")
             return (default_lora_name,)
 
 

comfy-nodes/external_string_combine.py

@@ -0,0 +1,53 @@
+import re
+
+
+class StringFunction:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "action": (["append", "replace"], {}),
+                "tidy_tags": (["yes", "no"], {}),
+            },
+            "optional": {
+                "text_a": ("STRING", {"multiline": True, "dynamicPrompts": False}),
+                "text_b": ("STRING", {"multiline": True, "dynamicPrompts": False}),
+                "text_c": ("STRING", {"multiline": True, "dynamicPrompts": False}),
+            },
+        }
+
+    RETURN_TYPES = ("STRING",)
+    FUNCTION = "exec"
+    CATEGORY = "utils"
+    OUTPUT_NODE = True
+
+    def exec(self, action, tidy_tags, text_a="", text_b="", text_c=""):
+        tidy_tags = tidy_tags == "yes"
+        out = ""
+        if action == "append":
+            out = (", " if tidy_tags else "").join(
+                filter(None, [text_a, text_b, text_c])
+            )
+        else:
+            if text_c is None:
+                text_c = ""
+            if text_b.startswith("/") and text_b.endswith("/"):
+                regex = text_b[1:-1]
+                out = re.sub(regex, text_c, text_a)
+            else:
+                out = text_a.replace(text_b, text_c)
+        if tidy_tags:
+            out = re.sub(r"\s{2,}", " ", out)
+            out = out.replace(" ,", ",")
+            out = re.sub(r",{2,}", ",", out)
+            out = out.strip()
+        return {"ui": {"text": (out,)}, "result": (out,)}
+
+
+NODE_CLASS_MAPPINGS = {
+    "ComfyUIDeployStringCombine": StringFunction,
+}
+
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "ComfyUIDeployStringCombine": "String Combine (ComfyUI Deploy)",
+}

comfy-nodes/output_image.py

@@ -0,0 +1,100 @@
+import os
+import json
+import numpy as np
+from PIL import Image
+from PIL.PngImagePlugin import PngInfo
+import folder_paths
+
+
+class ComfyDeployOutputImage:
+    def __init__(self):
+        self.output_dir = folder_paths.get_output_directory()
+        self.type = "output"
+        self.prefix_append = ""
+        self.compress_level = 4
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "images": ("IMAGE", {"tooltip": "The images to save."}),
+                "filename_prefix": (
+                    "STRING",
+                    {
+                        "default": "ComfyUI",
+                        "tooltip": "The prefix for the file to save. This may include formatting information such as %date:yyyy-MM-dd% or %Empty Latent Image.width% to include values from nodes.",
+                    },
+                ),
+                "file_type": (["png", "jpg", "webp"], {"default": "webp"}),
+                "quality": ("INT", {"default": 80, "min": 1, "max": 100, "step": 1}),
+                "output_id": (
+                    "STRING",
+                    {"multiline": False, "default": "output_images"},
+                ),
+            },
+            "hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"},
+        }
+
+    RETURN_TYPES = ()
+    FUNCTION = "run"
+
+    OUTPUT_NODE = True
+
+    CATEGORY = "output"
+    DESCRIPTION = "Saves the input images to your ComfyUI output directory."
+
+    def run(
+        self,
+        images,
+        filename_prefix="ComfyUI",
+        file_type="png",
+        quality=80,
+        output_id="output_images",
+        prompt=None,
+        extra_pnginfo=None,
+    ):
+        filename_prefix += self.prefix_append
+        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 batch_number, image in enumerate(images):
+            i = 255.0 * image.cpu().numpy()
+            img = Image.fromarray(np.clip(i, 0, 255).astype(np.uint8))
+            metadata = PngInfo()
+            if prompt is not None:
+                metadata.add_text("prompt", json.dumps(prompt))
+            if extra_pnginfo is not None:
+                for x in extra_pnginfo:
+                    metadata.add_text(x, json.dumps(extra_pnginfo[x]))
+
+            filename_with_batch_num = filename.replace("%batch_num%", str(batch_number))
+            file = f"{filename_with_batch_num}_{counter:05}_.{file_type}"
+            file_path = os.path.join(full_output_folder, file)
+
+            if file_type == "png":
+                img.save(
+                    file_path, pnginfo=metadata, compress_level=self.compress_level
+                )
+            elif file_type == "jpg":
+                img.save(file_path, quality=quality, optimize=True)
+            elif file_type == "webp":
+                img.save(file_path, quality=quality)
+
+            results.append(
+                {
+                    "filename": file,
+                    "subfolder": subfolder,
+                    "type": self.type,
+                    "output_id": output_id,
+                }
+            )
+            counter += 1
+
+        return {"ui": {"images": results}}
+
+
+NODE_CLASS_MAPPINGS = {"ComfyDeployOutputImage": ComfyDeployOutputImage}
+NODE_DISPLAY_NAME_MAPPINGS = {"ComfyDeployOutputImage": "Image Output (ComfyDeploy)"}

custom_routes.py

@@ -26,6 +26,10 @@ import copy
 import struct
 from aiohttp import web, ClientSession, ClientError, ClientTimeout, ClientResponseError
 import atexit
+from model_management import get_torch_device
+import torch
+import psutil
+from collections import OrderedDict
 
 # Global session
 client_session = None
@@ -299,6 +303,7 @@ def apply_random_seed_to_workflow(workflow_api):
     for key in workflow_api:
         if "inputs" in workflow_api[key]:
             if "seed" in workflow_api[key]["inputs"]:
+                # If seed is a list, it's an input from another node (generally `external number int`)
                 if isinstance(workflow_api[key]["inputs"]["seed"], list):
                     continue
                 if workflow_api[key]["class_type"] == "PromptExpansion":
@@ -313,6 +318,9 @@ def apply_random_seed_to_workflow(workflow_api):
                 )
 
             if "noise_seed" in workflow_api[key]["inputs"]:
+                # If noise_seed is a list, it's an input from another node (generally `external number int`)
+                if isinstance(workflow_api[key]["inputs"]["noise_seed"], list):
+                    continue
                 if workflow_api[key]["class_type"] == "RandomNoise":
                     workflow_api[key]["inputs"]["noise_seed"] = randomSeed()
                     logger.info(
@@ -383,6 +391,12 @@ def apply_inputs_to_workflow(workflow_api: Any, inputs: Any, sid: str = None):
                 if value["class_type"] == "ComfyUIDeployExternalFaceModel":
                     value["inputs"]["face_model_url"] = new_value
 
+                if value["class_type"] == "ComfyUIDeployExternalAudio":
+                    value["inputs"]["audio_file"] = new_value
+
+                if value["class_type"] == "ComfyUIDeployExternalEXR":
+                    value["inputs"]["exr_file"] = new_value
+
 
 def send_prompt(sid: str, inputs: StreamingPrompt):
     # workflow_api = inputs.workflow_api
@@ -1071,7 +1085,7 @@ async def send(event, data, sid=None):
 @server.PromptServer.instance.routes.post("/comfydeploy/{tail:.*}")
 async def proxy_to_comfydeploy(request):
     # Get the base URL
-    base_url = f'https://www.comfydeploy.com/{request.match_info["tail"]}'
+    base_url = f"https://www.comfydeploy.com/{request.match_info['tail']}"
 
     # Get all query parameters
     query_params = request.query_string
@@ -1120,6 +1134,144 @@ async def proxy_to_comfydeploy(request):
 
 
 prompt_server = server.PromptServer.instance
+
+
+NODE_EXECUTION_TIMES = {}  # New dictionary to store node execution times
+CURRENT_START_EXECUTION_DATA = None
+
+
+def get_peak_memory():
+    device = get_torch_device()
+    if device.type == "cuda":
+        return torch.cuda.max_memory_allocated(device)
+    elif device.type == "mps":
+        # Return system memory usage for MPS devices
+        return psutil.Process().memory_info().rss
+    return 0
+
+
+def reset_peak_memory_record():
+    device = get_torch_device()
+    if device.type == "cuda":
+        torch.cuda.reset_max_memory_allocated(device)
+    # MPS doesn't need reset as we're not tracking its memory
+
+
+def handle_execute(class_type, last_node_id, prompt_id, server, unique_id):
+    if not CURRENT_START_EXECUTION_DATA:
+        return
+    start_time = CURRENT_START_EXECUTION_DATA["nodes_start_perf_time"].get(unique_id)
+    start_vram = CURRENT_START_EXECUTION_DATA["nodes_start_vram"].get(unique_id)
+    if start_time:
+        end_time = time.perf_counter()
+        execution_time = end_time - start_time
+
+        end_vram = get_peak_memory()
+        vram_used = end_vram - start_vram
+        global NODE_EXECUTION_TIMES
+        # print(f"end_vram - start_vram: {end_vram} - {start_vram} = {vram_used}")
+        NODE_EXECUTION_TIMES[unique_id] = {
+            "time": execution_time,
+            "class_type": class_type,
+            "vram_used": vram_used,
+        }
+        # print(f"#{unique_id} [{class_type}]: {execution_time:.2f}s - vram {vram_used}b")
+
+
+try:
+    origin_execute = execution.execute
+
+    def swizzle_execute(
+        server,
+        dynprompt,
+        caches,
+        current_item,
+        extra_data,
+        executed,
+        prompt_id,
+        execution_list,
+        pending_subgraph_results,
+    ):
+        unique_id = current_item
+        class_type = dynprompt.get_node(unique_id)["class_type"]
+        last_node_id = server.last_node_id
+        result = origin_execute(
+            server,
+            dynprompt,
+            caches,
+            current_item,
+            extra_data,
+            executed,
+            prompt_id,
+            execution_list,
+            pending_subgraph_results,
+        )
+        handle_execute(class_type, last_node_id, prompt_id, server, unique_id)
+        return result
+
+    execution.execute = swizzle_execute
+except Exception as e:
+    pass
+
+
+def format_table(headers, data):
+    # Calculate column widths
+    widths = [len(h) for h in headers]
+    for row in data:
+        for i, cell in enumerate(row):
+            widths[i] = max(widths[i], len(str(cell)))
+
+    # Create separator line
+    separator = "+" + "+".join("-" * (w + 2) for w in widths) + "+"
+
+    # Format header
+    result = [separator]
+    header_row = "|" + "|".join(f" {h:<{w}} " for w, h in zip(widths, headers)) + "|"
+    result.append(header_row)
+    result.append(separator)
+
+    # Format data rows
+    for row in data:
+        data_row = (
+            "|" + "|".join(f" {str(cell):<{w}} " for w, cell in zip(widths, row)) + "|"
+        )
+        result.append(data_row)
+
+    result.append(separator)
+    return "\n".join(result)
+
+
+origin_func = server.PromptServer.send_sync
+
+
+def swizzle_send_sync(self, event, data, sid=None):
+    # print(f"swizzle_send_sync, event: {event}, data: {data}")
+    global CURRENT_START_EXECUTION_DATA
+    if event == "execution_start":
+        global NODE_EXECUTION_TIMES
+        NODE_EXECUTION_TIMES = {}  # Reset execution times at start
+        CURRENT_START_EXECUTION_DATA = dict(
+            start_perf_time=time.perf_counter(),
+            nodes_start_perf_time={},
+            nodes_start_vram={},
+        )
+
+    origin_func(self, event=event, data=data, sid=sid)
+
+    if event == "executing" and data and CURRENT_START_EXECUTION_DATA:
+        if data.get("node") is not None:
+            node_id = data.get("node")
+            CURRENT_START_EXECUTION_DATA["nodes_start_perf_time"][node_id] = (
+                time.perf_counter()
+            )
+            reset_peak_memory_record()
+            CURRENT_START_EXECUTION_DATA["nodes_start_vram"][node_id] = (
+                get_peak_memory()
+            )
+
+
+server.PromptServer.send_sync = swizzle_send_sync
+
 send_json = prompt_server.send_json
 
 
@@ -1145,11 +1297,63 @@ async def send_json_override(self, event, data, sid=None):
     asyncio.create_task(update_run_ws_event(prompt_id, event, data))
 
     if event == "execution_start":
-        await update_run(prompt_id, Status.RUNNING)
-
         if prompt_id in prompt_metadata:
             prompt_metadata[prompt_id].start_time = time.perf_counter()
 
+        logger.info("Executing prompt: " + prompt_id)
+
+        asyncio.create_task(update_run(prompt_id, Status.RUNNING))
+
+    if event == "executing" and data and CURRENT_START_EXECUTION_DATA:
+        if data.get("node") is None:
+            start_perf_time = CURRENT_START_EXECUTION_DATA.get("start_perf_time")
+            new_data = data.copy()
+            if start_perf_time is not None:
+                execution_time = time.perf_counter() - start_perf_time
+                new_data["execution_time"] = int(execution_time * 1000)
+
+            # Replace the print statements with tabulate
+            headers = ["Node ID", "Type", "Time (s)", "VRAM (GB)"]
+            table_data = []
+            node_execution_array = []  # New array to store execution data
+
+            for node_id, node_data in NODE_EXECUTION_TIMES.items():
+                vram_gb = node_data["vram_used"] / (1024**3)  # Convert bytes to GB
+                table_data.append(
+                    [
+                        f"#{node_id}",
+                        node_data["class_type"],
+                        f"{node_data['time']:.2f}",
+                        f"{vram_gb:.2f}",
+                    ]
+                )
+
+                # Add to our new array format
+                node_execution_array.append(
+                    {
+                        "id": node_id,
+                        **node_data,
+                    }
+                )
+
+            # Add total execution time as the last row
+            table_data.append(["TOTAL", "-", f"{execution_time:.2f}", "-"])
+
+            prompt_id = data.get("prompt_id")
+            asyncio.create_task(
+                update_run_with_output(
+                    prompt_id,
+                    node_execution_array,  # Send the array instead of the OrderedDict
+                )
+            )
+
+            print(node_execution_array)
+
+            # print("\n=== Node Execution Times ===")
+            logger.info("Printing Node Execution Times")
+            logger.info(format_table(headers, table_data))
+            # print("========================\n")
+
     # the last executing event is none, then the workflow is finished
     if event == "executing" and data.get("node") is None:
         mark_prompt_done(prompt_id=prompt_id)
@@ -1160,10 +1364,12 @@ async def send_json_override(self, event, data, sid=None):
                 if prompt_metadata[prompt_id].start_time is not None:
                     elapsed_time = current_time - prompt_metadata[prompt_id].start_time
                     logger.info(f"Elapsed time: {elapsed_time} seconds")
-                    await send(
-                        "elapsed_time",
-                        {"prompt_id": prompt_id, "elapsed_time": elapsed_time},
-                        sid=sid,
+                    asyncio.create_task(
+                        send(
+                            "elapsed_time",
+                            {"prompt_id": prompt_id, "elapsed_time": elapsed_time},
+                            sid=sid,
+                        )
                     )
 
     if event == "executing" and data.get("node") is not None:
@@ -1188,17 +1394,21 @@ async def send_json_override(self, event, data, sid=None):
             prompt_metadata[prompt_id].last_updated_node = node
             class_type = prompt_metadata[prompt_id].workflow_api[node]["class_type"]
             logger.info(f"At: {round(calculated_progress * 100)}% - {class_type}")
-            await send(
-                "live_status",
-                {
-                    "prompt_id": prompt_id,
-                    "current_node": class_type,
-                    "progress": calculated_progress,
-                },
-                sid=sid,
+            asyncio.create_task(
+                send(
+                    "live_status",
+                    {
+                        "prompt_id": prompt_id,
+                        "current_node": class_type,
+                        "progress": calculated_progress,
+                    },
+                    sid=sid,
+                )
             )
-            await update_run_live_status(
-                prompt_id, "Executing " + class_type, calculated_progress
+            asyncio.create_task(
+                update_run_live_status(
+                    prompt_id, "Executing " + class_type, calculated_progress
+                )
             )
 
     if event == "execution_cached" and data.get("nodes") is not None:
@@ -1227,7 +1437,8 @@ async def send_json_override(self, event, data, sid=None):
                 "node_class": class_type,
             }
             if class_type == "PreviewImage":
-                logger.info("Skipping preview image")
+                pass
+                # logger.info("Skipping preview image")
             else:
                 await update_run_with_output(
                     prompt_id,
@@ -1239,9 +1450,10 @@ async def send_json_override(self, event, data, sid=None):
                     comfy_message_queues[prompt_id].put_nowait(
                         {"event": "output_ready", "data": data}
                     )
-            logger.info(f"Executed {class_type} {data}")
+            # logger.info(f"Executed {class_type} {data}")
         else:
-            logger.info(f"Executed {data}")
+            pass
+            # logger.info(f"Executed {data}")
 
 
 # Global variable to keep track of the last read line number
@@ -1713,16 +1925,22 @@ async def upload_in_background(
         # await handle_upload(prompt_id, data, 'files', "content_type", "image/png")
         # await handle_upload(prompt_id, data, 'gifs', "format", "image/gif")
         # await handle_upload(prompt_id, data, 'mesh', "format", "application/octet-stream")
-        upload_tasks = [
-            handle_upload(prompt_id, data, "images", "content_type", "image/png"),
-            handle_upload(prompt_id, data, "files", "content_type", "image/png"),
-            handle_upload(prompt_id, data, "gifs", "format", "image/gif"),
-            handle_upload(
-                prompt_id, data, "mesh", "format", "application/octet-stream"
-            ),
-        ]
 
-        await asyncio.gather(*upload_tasks)
+        file_upload_endpoint = prompt_metadata[prompt_id].file_upload_endpoint
+
+        if file_upload_endpoint is not None and file_upload_endpoint != "":
+            upload_tasks = [
+                handle_upload(prompt_id, data, "images", "content_type", "image/png"),
+                handle_upload(prompt_id, data, "files", "content_type", "image/png"),
+                handle_upload(prompt_id, data, "gifs", "format", "image/gif"),
+                handle_upload(
+                    prompt_id, data, "mesh", "format", "application/octet-stream"
+                ),
+            ]
+
+            await asyncio.gather(*upload_tasks)
+        else:
+            print("No file upload endpoint, skipping file upload")
 
         status_endpoint = prompt_metadata[prompt_id].status_endpoint
         token = prompt_metadata[prompt_id].token

pyproject.toml

@@ -2,7 +2,7 @@
 name = "comfyui-deploy"
 description = "Open source comfyui deployment platform, a vercel for generative workflow infra."
 version = "1.1.0"
-license = "LICENSE"
+license = { file = "LICENSE" }
 dependencies = ["aiofiles", "pydantic", "opencv-python", "imageio-ffmpeg"]
 
 [project.urls]

requirements.txt

@@ -3,4 +3,5 @@ pydantic
 opencv-python
 imageio-ffmpeg
 brotli
+tabulate
 # logfire

web-plugin/api.js

@@ -1,4 +0,0 @@
-/** @typedef {import('../../../web/scripts/api.js').api} API*/
-import { api as _api } from '../../scripts/api.js';
-/** @type {API} */
-export const api = _api;

web-plugin/app.js

@@ -1,4 +0,0 @@
-/** @typedef {import('../../../web/scripts/app.js').ComfyApp} ComfyApp*/
-import { app as _app } from '../../scripts/app.js';
-/** @type {ComfyApp} */
-export const app = _app;

web-plugin/index.js

@@ -1,8 +1,44 @@
-import { app } from "./app.js";
-import { api } from "./api.js";
-import { ComfyWidgets, LGraphNode } from "./widgets.js";
+import { app } from "../../scripts/app.js";
+import { api } from "../../scripts/api.js";
+// import { LGraphNode } from "../../scripts/widgets.js";
+LGraphNode = LiteGraph.LGraphNode;
+import { ComfyDialog, $el } from "../../scripts/ui.js";
+
 import { generateDependencyGraph } from "https://esm.sh/comfyui-json@0.1.25";
-import { ComfyDeploy } from "https://esm.sh/comfydeploy@0.0.19-beta.30";
+import { ComfyDeploy } from "https://esm.sh/comfydeploy@2.0.0-beta.69";
+
+const styles = `
+.comfydeploy-menu-item {
+    background: linear-gradient(to right, rgba(74, 144, 226, 0.9), rgba(103, 178, 111, 0.9)) !important;
+    color: white !important;
+    position: relative !important;
+    padding-left: 20px !important;
+}
+
+.comfydeploy-menu-item:hover {
+    filter: brightness(1.1) !important;
+    cursor: pointer !important;
+}
+
+.comfydeploy-menu-item::before {
+    content: '';
+    position: absolute;
+    left: 4px;
+    top: 50%;
+    transform: translateY(-50%);
+    width: 12px;
+    height: 12px;
+    background-image: url('https://www.comfydeploy.com/icon.svg');
+    background-size: contain;
+    background-repeat: no-repeat;
+    background-position: center;
+}
+`;
+
+// Add stylesheet to document
+const styleSheet = document.createElement("style");
+styleSheet.textContent = styles;
+document.head.appendChild(styleSheet);
 
 const loadingIcon = `<svg xmlns="http://www.w3.org/2000/svg" width="32" height="32" viewBox="0 0 24 24"><g fill="none" stroke="#888888" stroke-linecap="round" stroke-width="2"><path stroke-dasharray="60" stroke-dashoffset="60" stroke-opacity=".3" d="M12 3C16.9706 3 21 7.02944 21 12C21 16.9706 16.9706 21 12 21C7.02944 21 3 16.9706 3 12C3 7.02944 7.02944 3 12 3Z"><animate fill="freeze" attributeName="stroke-dashoffset" dur="1.3s" values="60;0"/></path><path stroke-dasharray="15" stroke-dashoffset="15" d="M12 3C16.9706 3 21 7.02944 21 12"><animate fill="freeze" attributeName="stroke-dashoffset" dur="0.3s" values="15;0"/><animateTransform attributeName="transform" dur="1.5s" repeatCount="indefinite" type="rotate" values="0 12 12;360 12 12"/></path></g></svg>`;
 
@@ -14,6 +50,14 @@ function sendEventToCD(event, data) {
   window.parent.postMessage(JSON.stringify(message), "*");
 }
 
+function sendDirectEventToCD(event, data) {
+  const message = {
+    type: event,
+    data: data,
+  };
+  window.parent.postMessage(message, "*");
+}
+
 function dispatchAPIEventData(data) {
   const msg = JSON.parse(data);
 
@@ -122,6 +166,146 @@ function setSelectedWorkflowInfo(info) {
   context.selectedWorkflowInfo = info;
 }
 
+const VALID_TYPES = [
+  "STRING",
+  "combo",
+  "number",
+  "toggle",
+  "BOOLEAN",
+  "text",
+  "string",
+];
+
+function hideWidget(node, widget, suffix = "") {
+  if (widget.type?.startsWith(CONVERTED_TYPE)) return;
+  widget.origType = widget.type;
+  widget.origComputeSize = widget.computeSize;
+  widget.origSerializeValue = widget.serializeValue;
+  widget.computeSize = () => [0, -4];
+  widget.type = CONVERTED_TYPE + suffix;
+  widget.serializeValue = () => {
+    if (!node.inputs) {
+      return void 0;
+    }
+    let node_input = node.inputs.find((i) => i.widget?.name === widget.name);
+    if (!node_input || !node_input.link) {
+      return void 0;
+    }
+    return widget.origSerializeValue
+      ? widget.origSerializeValue()
+      : widget.value;
+  };
+  if (widget.linkedWidgets) {
+    for (const w of widget.linkedWidgets) {
+      hideWidget(node, w, ":" + widget.name);
+    }
+  }
+}
+
+function getWidgetType(config) {
+  let type = config[0];
+  if (type instanceof Array) {
+    type = "COMBO";
+  }
+  return { type };
+}
+
+const GET_CONFIG = Symbol();
+
+function convertToInput(node, widget, config) {
+  console.log(node);
+  if (node.type == "LoadImage") {
+    var inputNode = LiteGraph.createNode("ComfyUIDeployExternalImage");
+    console.log(widget);
+
+    const currentOutputsLinks = node.outputs[0].links;
+
+    // const index = node.inputs.findIndex((x) => x.name == widget.name);
+    // console.log(node.widgets_values, index);
+    // inputNode.configure({
+    //   widgets_values: ["input_text", widget.value],
+    // });
+    inputNode.pos = node.pos;
+    inputNode.id = ++app.graph.last_node_id;
+    // inputNode.pos[0] += node.size[0] + 40;
+    node.pos[0] -= inputNode.size[0] + 20;
+    console.log(inputNode);
+    console.log(app.graph);
+    app.graph.add(inputNode);
+
+    const links = app.graph.links;
+
+    console.log(currentOutputsLinks);
+
+    for (let i = 0; i < currentOutputsLinks.length; i++) {
+      const link = currentOutputsLinks[i];
+      const llink = links[link];
+      console.log(links[link]);
+      setTimeout(
+        () => inputNode.connect(0, llink.target_id, llink.target_slot),
+        100,
+      );
+    }
+
+    node.connect(0, inputNode, 0);
+
+    return null;
+  }
+
+  hideWidget(node, widget);
+  const { type } = getWidgetType(config);
+  const sz = node.size;
+  const inputIsOptional = !!widget.options?.inputIsOptional;
+  const input = node.addInput(widget.name, type, {
+    widget: { name: widget.name, [GET_CONFIG]: () => config },
+    ...(inputIsOptional ? { shape: LiteGraph.SlotShape.HollowCircle } : {}),
+  });
+  for (const widget2 of node.widgets) {
+    widget2.last_y += LiteGraph.NODE_SLOT_HEIGHT;
+  }
+  node.setSize([Math.max(sz[0], node.size[0]), Math.max(sz[1], node.size[1])]);
+
+  if (type == "STRING") {
+    var inputNode = LiteGraph.createNode("ComfyUIDeployExternalText");
+    console.log(widget);
+    const index = node.inputs.findIndex((x) => x.name == widget.name);
+    console.log(node.widgets_values, index);
+    inputNode.configure({
+      widgets_values: ["input_text", widget.value],
+    });
+    inputNode.id = ++app.graph.last_node_id;
+    inputNode.pos = node.pos;
+    inputNode.pos[0] -= node.size[0] + 40;
+    console.log(inputNode);
+    console.log(app.graph);
+    app.graph.add(inputNode);
+    inputNode.connect(0, node, index);
+  }
+
+  return input;
+}
+
+const CONVERTED_TYPE = "converted-widget";
+
+function getConfig(widgetName) {
+  const { nodeData } = this.constructor;
+  return (
+    nodeData?.input?.required?.[widgetName] ??
+    nodeData?.input?.optional?.[widgetName]
+  );
+}
+
+function isConvertibleWidget(widget, config) {
+  return (
+    (VALID_TYPES.includes(widget.type) || VALID_TYPES.includes(config[0])) &&
+    !widget.options?.forceInput
+  );
+}
+
+var __defProp = Object.defineProperty;
+var __name = (target, value) =>
+  __defProp(target, "name", { value, configurable: true });
+
 /** @typedef {import('../../../web/types/comfy.js').ComfyExtension} ComfyExtension*/
 /** @type {ComfyExtension} */
 const ext = {
@@ -232,6 +416,125 @@ const ext = {
     }
   },
 
+  async beforeRegisterNodeDef(nodeType, nodeData, app2) {
+    const origGetExtraMenuOptions = nodeType.prototype.getExtraMenuOptions;
+    nodeType.prototype.getExtraMenuOptions = function (_, options) {
+      const r = origGetExtraMenuOptions
+        ? origGetExtraMenuOptions.apply(this, arguments)
+        : void 0;
+      if (this.widgets) {
+        let toInput = [];
+        let toWidget = [];
+        for (const w of this.widgets) {
+          if (w.options?.forceInput) {
+            continue;
+          }
+          if (w.type === CONVERTED_TYPE) {
+            toWidget.push({
+              content: `Convert ${w.name} to widget`,
+              callback: /* @__PURE__ */ __name(
+                () => convertToWidget(this, w),
+                "callback",
+              ),
+            });
+          } else {
+            const config = getConfig.call(this, w.name) ?? [
+              w.type,
+              w.options || {},
+            ];
+            if (isConvertibleWidget(w, config)) {
+              toInput.push({
+                content: `Convert ${w.name} to external input`,
+                callback: /* @__PURE__ */ __name(
+                  () => convertToInput(this, w, config),
+                  "callback",
+                ),
+                className: "comfydeploy-menu-item",
+              });
+            }
+          }
+        }
+        if (toInput.length) {
+          if (true) {
+            options.push();
+
+            let optionIndex = options.findIndex((o) => o.content === "Outputs");
+            if (optionIndex === -1) optionIndex = options.length;
+            else optionIndex++;
+            options.splice(
+              0,
+              0,
+              // {
+              //   content: "[ComfyDeploy] Convert to External Input",
+              //   submenu: {
+              //     options: toInput,
+              //   },
+              //   className: "comfydeploy-menu-item"
+              // },
+              ...toInput,
+              null,
+            );
+          } else {
+            options.push(...toInput, null);
+          }
+        }
+        // if (toWidget.length) {
+        //   if (useConversionSubmenusSetting.value) {
+        //     options.push({
+        //       content: "Convert Input to Widget",
+        //       submenu: {
+        //         options: toWidget,
+        //       },
+        //     });
+        //   } else {
+        //     options.push(...toWidget, null);
+        //   }
+        // }
+      }
+      return r;
+    };
+
+    if (
+      nodeData?.input?.optional?.default_value_url?.[1]?.image_preview === true
+    ) {
+      nodeData.input.optional.default_value_url = ["IMAGEPREVIEW"];
+      console.log(nodeData.input.optional.default_value_url);
+    }
+
+    // const origonNodeCreated = nodeType.prototype.onNodeCreated;
+    // nodeType.prototype.onNodeCreated = function () {
+    //   const r = origonNodeCreated
+    //     ? origonNodeCreated.apply(this, arguments)
+    //     : void 0;
+
+    //   if (!this.widgets) {
+    //     return;
+    //   }
+
+    //   console.log(this.widgets);
+
+    //   this.widgets.forEach(element => {
+    //     if (element.type != "customtext") return
+
+    //     console.log(element.element);
+
+    //     const parent = element.element.parentElement
+
+    //     console.log(element.element.parentElement)
+    //     const btn = document.createElement("button");
+    //     // const div = document.createElement("div");
+    //     // parent.removeChild(element.element)
+    //     // div.appendChild(element.element)
+    //     // parent.appendChild(div)
+    //     // element.element = div
+    //     // console.log(element.element);
+    //     // btn.style = element.element.style
+    //   });
+
+    //   return r
+    // };
+  },
+
   registerCustomNodes() {
     /** @type {LGraphNode}*/
     class ComfyDeploy extends LGraphNode {
@@ -324,6 +627,78 @@ const ext = {
     ComfyDeploy.category = "deploy";
   },
 
+  getCustomWidgets() {
+    return {
+      IMAGEPREVIEW(node, inputName, inputData) {
+        // Find or create the URL input widget
+        const urlWidget = node.addWidget(
+          "string",
+          inputName,
+          /* value=*/ "",
+          () => {},
+          { serialize: true },
+        );
+
+        const buttonWidget = node.addWidget(
+          "button",
+          "Open Assets Browser",
+          /* value=*/ "",
+          () => {
+            sendEventToCD("assets", {
+              node: node.id,
+              inputName: inputName,
+            });
+            // console.log("load image");
+          },
+          { serialize: false },
+        );
+
+        console.log(node.widgets);
+
+        console.log("urlWidget", urlWidget);
+
+        // Add image preview functionality
+        function showImage(url) {
+          const img = new Image();
+          img.onload = () => {
+            node.imgs = [img];
+            app.graph.setDirtyCanvas(true);
+            node.setSizeForImage?.();
+          };
+          img.onerror = () => {
+            node.imgs = [];
+            app.graph.setDirtyCanvas(true);
+          };
+          img.src = url;
+        }
+
+        // Set up URL widget value handling
+        let default_value = urlWidget.value;
+        Object.defineProperty(urlWidget, "value", {
+          set: function (value) {
+            this._real_value = value;
+            // Preview image when URL changes
+            if (value) {
+              showImage(value);
+            }
+          },
+          get: function () {
+            return this._real_value || default_value;
+          },
+        });
+
+        // Show initial image if URL exists
+        requestAnimationFrame(() => {
+          if (urlWidget.value) {
+            showImage(urlWidget.value);
+          }
+        });
+
+        return { widget: urlWidget };
+      },
+    };
+  },
+
   async setup() {
     // const graphCanvas = document.getElementById("graph-canvas");
 
@@ -351,6 +726,7 @@ const ext = {
             }
             console.log("loadGraphData");
             app.loadGraphData(comfyUIWorkflow);
+            sendEventToCD("graph_loaded");
           }
         } else if (message.type === "deploy") {
           // deployWorkflow();
@@ -365,11 +741,35 @@ const ext = {
             console.warn("api.handlePromptGenerated is not a function");
           }
           sendEventToCD("cd_plugin_onQueuePrompt", prompt);
+        } else if (message.type === "configure_queue_buttons") {
+          addQueueButtons(message.data);
+        } else if (message.type === "configure_menu_right_buttons") {
+          addMenuRightButtons(message.data);
+        } else if (message.type === "configure_menu_buttons") {
+          addMenuButtons(message.data);
         } else if (message.type === "get_prompt") {
           const prompt = await app.graphToPrompt();
           sendEventToCD("cd_plugin_onGetPrompt", prompt);
         } else if (message.type === "event") {
           dispatchAPIEventData(message.data);
+        } else if (message.type === "update_widget") {
+          // New handler for updating widget values
+          const { nodeId, widgetName, value } = message.data;
+          const node = app.graph.getNodeById(nodeId);
+
+          if (!node) {
+            console.warn(`Node with ID ${nodeId} not found`);
+            return;
+          }
+
+          const widget = node.widgets?.find((w) => w.name === widgetName);
+          if (!widget) {
+            console.warn(`Widget ${widgetName} not found in node ${nodeId}`);
+            return;
+          }
+
+          widget.value = value;
+          app.graph.setDirtyCanvas(true);
         } else if (message.type === "add_node") {
           console.log("add node", message.data);
           app.graph.beforeChange();
@@ -463,13 +863,13 @@ 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",
-          "right"
+          "left",
         );
-        localStorage.setItem("Comfy.MenuPosition.Docked", "true");
+        // localStorage.setItem("Comfy.MenuPosition.Docked", "true");
         console.log("native mode manmanman");
       } catch (error) {
         console.error("Error setting validation to false", error);
@@ -1002,8 +1402,6 @@ function addButton() {
 
 app.registerExtension(ext);
 
-import { ComfyDialog, $el } from "../../scripts/ui.js";
-
 export class InfoDialog extends ComfyDialog {
   constructor() {
     super();
@@ -1474,7 +1872,7 @@ app.extensionManager.registerSidebarTab({
       <div style="padding: 20px;">
         <h3>Comfy Deploy</h3>
         <div id="deploy-container" style="margin-bottom: 20px;"></div>
-        <div id="workflows-container">
+        <div id="workflows-container" style="display: none;">
           <h4>Your Workflows</h4>
           <div id="workflows-loading" style="display: flex; justify-content: center; align-items: center; height: 100px;">
             ${loadingIcon}
@@ -1574,10 +1972,16 @@ async function loadWorkflowApi(versionId) {
 
 const orginal_fetch_api = api.fetchApi;
 api.fetchApi = async (route, options) => {
-  console.log("Fetch API called with args:", route, options, ext.native_mode);
+  // console.log("Fetch API called with args:", route, options, ext.native_mode);
 
   if (route.startsWith("/prompt") && ext.native_mode) {
     const info = await getSelectedWorkflowInfo();
+
+    if (!info.workflow_id) {
+      console.log("No workflow id found, fallback to original fetch");
+      return await orginal_fetch_api.call(api, route, options);
+    }
+
     console.log("info", info);
     if (info) {
       const body = JSON.parse(options.body);
@@ -1591,6 +1995,7 @@ api.fetchApi = async (route, options) => {
         workflow_id: info.workflow_id,
         native_run_api_endpoint: info.native_run_api_endpoint,
         gpu_event_id: info.gpu_event_id,
+        gpu: info.gpu,
       };
 
       return await fetch("/comfyui-deploy/run", {
@@ -1606,3 +2011,306 @@ api.fetchApi = async (route, options) => {
 
   return await orginal_fetch_api.call(api, route, options);
 };
+
+// Intercept window drag and drop events
+const originalDropHandler = document.ondrop;
+document.ondrop = async (e) => {
+  console.log("Drop event intercepted:", e);
+
+  // Prevent default browser behavior
+  e.preventDefault();
+
+  // Handle files if present
+  if (e.dataTransfer?.files?.length > 0) {
+    const files = Array.from(e.dataTransfer.files);
+
+    // Send file data to parent directly as JSON
+    sendDirectEventToCD("file_drop", {
+      files: files,
+      x: e.clientX,
+      y: e.clientY,
+      timestamp: Date.now(),
+    });
+  }
+
+  // Call original handler if exists
+  if (originalDropHandler) {
+    originalDropHandler(e);
+  }
+};
+
+const originalDragEnterHandler = document.ondragenter;
+document.ondragenter = (e) => {
+  // Prevent default to allow drop
+  e.preventDefault();
+
+  // Send dragenter event to parent directly as JSON
+  sendDirectEventToCD("file_dragenter", {
+    x: e.clientX,
+    y: e.clientY,
+    timestamp: Date.now(),
+  });
+
+  if (originalDragEnterHandler) {
+    originalDragEnterHandler(e);
+  }
+};
+
+const originalDragLeaveHandler = document.ondragleave;
+document.ondragleave = (e) => {
+  // Prevent default to allow drop
+  e.preventDefault();
+
+  // Send dragleave event to parent directly as JSON
+  sendDirectEventToCD("file_dragleave", {
+    x: e.clientX,
+    y: e.clientY,
+    timestamp: Date.now(),
+  });
+
+  if (originalDragLeaveHandler) {
+    originalDragLeaveHandler(e);
+  }
+};
+
+const originalDragOverHandler = document.ondragover;
+document.ondragover = (e) => {
+  // Prevent default to allow drop
+  e.preventDefault();
+
+  // Send dragover event to parent directly as JSON
+  sendDirectEventToCD("file_dragover", {
+    x: e.clientX,
+    y: e.clientY,
+    timestamp: Date.now(),
+  });
+
+  if (originalDragOverHandler) {
+    originalDragOverHandler(e);
+  }
+};
+
+// Function to create a single button
+function createQueueButton(config) {
+  const button = document.createElement("button");
+  button.id = `cd-button-${config.id}`;
+  button.className =
+    "p-button p-component p-button-icon-only p-button-secondary p-button-text";
+  button.innerHTML = `
+    <span class="p-button-icon pi ${config.icon}"></span>
+    <span class="p-button-label">&nbsp;</span>
+  `;
+  button.onclick = () => {
+    const eventData =
+      typeof config.eventData === "function"
+        ? config.eventData()
+        : config.eventData || {};
+    sendEventToCD(config.event, eventData);
+  };
+  button.setAttribute("data-pd-tooltip", config.tooltip);
+  return button;
+}
+
+// Function to add buttons to queue group
+function addQueueButtons(buttonConfigs = DEFAULT_BUTTONS) {
+  const queueButtonGroup = document.querySelector(".queue-button-group.flex");
+  if (!queueButtonGroup) return;
+
+  // Remove any existing CD buttons
+  const existingButtons =
+    queueButtonGroup.querySelectorAll('[id^="cd-button-"]');
+  existingButtons.forEach((button) => button.remove());
+
+  // Add new buttons
+  buttonConfigs.forEach((config) => {
+    const button = createQueueButton(config);
+    queueButtonGroup.appendChild(button);
+  });
+}
+
+// addMenuRightButtons([
+//   {
+//     id: "cd-button-save-image",
+//     icon: "pi-save",
+//     label: "Snapshot",
+//     tooltip: "Save the current image to your output directory.",
+//     event: "save_image",
+//     eventData: () => ({}),
+//   },
+// ]);
+
+// addMenuLeftButtons([
+//   {
+//     id: "cd-button-back",
+//     icon: `<svg width="16" height="16" viewBox="0 0 24 24" fill="none" xmlns="http://www.w3.org/2000/svg">
+//       <path d="M15 18L9 12L15 6" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"/>
+//     </svg>`,
+//     tooltip: "Go back to the previous page.",
+//     event: "back",
+//     eventData: () => ({}),
+//   },
+// ]);
+
+// addMenuButtons({
+//   containerSelector: "body > div.comfyui-body-top > div",
+//   buttonConfigs: [
+//     {
+//       id: "cd-button-workflow-1",
+//       icon: `<svg xmlns="http://www.w3.org/2000/svg" width="20" height="20" viewBox="0 0 24 24"><path fill="none" stroke="currentColor" stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="m16 3l4 4l-4 4m-6-4h10M8 13l-4 4l4 4m-4-4h9"/></svg>`,
+//       label: "Workflow",
+//       tooltip: "Go to Workflow 1",
+//       event: "workflow_1",
+//       // btnClasses: "",
+//       eventData: () => ({}),
+//     },
+//     {
+//       id: "cd-button-workflow-3",
+//       // icon: `<svg xmlns="http://www.w3.org/2000/svg" width="20" height="20" viewBox="0 0 24 24"><path fill="none" stroke="currentColor" stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="m16 3l4 4l-4 4m-6-4h10M8 13l-4 4l4 4m-4-4h9"/></svg>`,
+//       label: "v1",
+//       tooltip: "Go to Workflow 1",
+//       event: "workflow_1",
+//       // btnClasses: "",
+//       eventData: () => ({}),
+//     },
+//     {
+//       id: "cd-button-workflow-2",
+//       icon: `<svg xmlns="http://www.w3.org/2000/svg" width="20" height="20" viewBox="0 0 24 24"><g fill="none" stroke="currentColor" stroke-linecap="round" stroke-linejoin="round" stroke-width="2"><path d="M12 3v6"/><circle cx="12" cy="12" r="3"/><path d="M12 15v6"/></g></svg>`,
+//       label: "Commit",
+//       tooltip: "Commit the current workflow",
+//       event: "commit",
+//       style: {
+//         backgroundColor: "oklch(.476 .114 61.907)",
+//       },
+//       eventData: () => ({}),
+//     },
+//   ],
+//   buttonIdPrefix: "cd-button-workflow-",
+//   insertBefore:
+//     "body > div.comfyui-body-top > div > div.flex-grow.min-w-0.app-drag.h-full",
+//   // containerStyle: { order: "3" }
+// });
+
+// addMenuButtons({
+//   containerSelector:
+//     "body > div.comfyui-body-top > div > div.flex-grow.min-w-0.app-drag.h-full",
+//   clearContainer: true,
+//   buttonConfigs: [],
+//   buttonIdPrefix: "cd-button-p-",
+//   containerStyle: { order: "-1" },
+// });
+
+// Function to add buttons to a menu container
+function addMenuButtons(options) {
+  const {
+    containerSelector,
+    buttonConfigs,
+    buttonIdPrefix = "cd-button-",
+    containerClass = "comfyui-button-group",
+    containerStyle = {},
+    clearContainer = false,
+    insertBefore = null, // New option to specify selector for insertion point
+  } = options;
+
+  const menuContainer = document.querySelector(containerSelector);
+
+  if (!menuContainer) return;
+
+  // Remove any existing CD buttons
+  const existingButtons = document.querySelectorAll(
+    `[id^="${buttonIdPrefix}"]`,
+  );
+  existingButtons.forEach((button) => button.remove());
+
+  const container = document.createElement("div");
+  container.className = containerClass;
+
+  // Apply container styles
+  Object.assign(container.style, containerStyle);
+
+  // Clear existing content if specified
+  if (clearContainer) {
+    menuContainer.innerHTML = "";
+  }
+
+  // Create and add buttons
+  buttonConfigs.forEach((config) => {
+    const button = createMenuButton({
+      ...config,
+      idPrefix: buttonIdPrefix,
+    });
+    container.appendChild(button);
+  });
+
+  // Insert before specified element if provided, otherwise append
+  if (insertBefore) {
+    const targetElement = menuContainer.querySelector(insertBefore);
+    if (targetElement) {
+      menuContainer.insertBefore(container, targetElement);
+    } else {
+      menuContainer.appendChild(container);
+    }
+  } else {
+    menuContainer.appendChild(container);
+  }
+}
+
+function createMenuButton(config) {
+  const {
+    id,
+    icon,
+    label,
+    btnClasses = "",
+    tooltip,
+    event,
+    eventData,
+    idPrefix,
+    style = {},
+  } = config;
+
+  const button = document.createElement("button");
+  button.id = `${idPrefix}${id}`;
+  button.className = `comfyui-button ${btnClasses}`;
+  Object.assign(button.style, style);
+
+  // Only add icon if provided
+  const iconHtml = icon
+    ? icon.startsWith("<svg")
+      ? icon
+      : `<span class="p-button-icon pi ${icon}"></span>`
+    : "";
+
+  button.innerHTML = `
+    ${iconHtml}
+    ${label ? `<span class="p-button-label text-sm">${label}</span>` : ""}
+  `;
+
+  button.onclick = () => {
+    const data =
+      typeof eventData === "function" ? eventData() : eventData || {};
+    sendEventToCD(event, data);
+  };
+
+  if (tooltip) {
+    button.setAttribute("data-pd-tooltip", tooltip);
+  }
+  return button;
+}
+
+// Refactored menu button functions
+function addMenuLeftButtons(buttonConfigs) {
+  addMenuButtons({
+    containerSelector: "body > div.comfyui-body-top > div",
+    buttonConfigs,
+    buttonIdPrefix: "cd-button-left-",
+    containerStyle: { order: "-1" },
+  });
+}
+
+function addMenuRightButtons(buttonConfigs) {
+  addMenuButtons({
+    containerSelector: ".comfyui-menu-right .flex",
+    buttonConfigs,
+    buttonIdPrefix: "cd-button-",
+    containerStyle: {},
+  });
+}

web-plugin/widgets.js

@@ -1,18 +0,0 @@
-// /** @typedef {import('../../../web/scripts/api.js').api} API*/
-// import { api as _api } from "../../scripts/api.js";
-// /** @type {API} */
-// export const api = _api;
-
-/** @typedef {typeof import('../../../web/scripts/widgets.js').ComfyWidgets} Widgets*/
-import { ComfyWidgets as _ComfyWidgets } from "../../scripts/widgets.js";
-
-/**
- * @type {Widgets}
- */
-export const ComfyWidgets = _ComfyWidgets;
-
-// import { LGraphNode as _LGraphNode } from "../../types/litegraph.js";
-
-/** @typedef {typeof import('../../../web/types/litegraph.js').LGraphNode} LGraphNode*/
-/** @type {LGraphNode}*/
-export const LGraphNode = LiteGraph.LGraphNode;