fix(setup): reload the app after adding the localstorage values

The current problem is that if you do `localsStorage.setItem()` the
value is changed, but comfyUI doesn't detect the change because
`ComfyActionbar` was already mounted.

This is a quick fix where we basically trigger a reload of the app
after docking the menu position.

comfy-nodes/comfy_std_output.py

@@ -1,46 +0,0 @@
-import json
-
-
-class AnyType(str):
-    """A special class that is always equal in not equal comparisons. Credit to pythongosssss"""
-
-    def __ne__(self, __value: object) -> bool:
-        return False
-
-
-any = AnyType("*")
-
-
-class ComfyDeployStdOutputAny:
-    @classmethod
-    def INPUT_TYPES(cls):  # pylint: disable = invalid-name, missing-function-docstring
-        return {
-            "required": {
-                "name": ("STRING", {"default": "ComfyUI"}),
-                "source": (any, {}),  # Use "*" to accept any input type
-            },
-        }
-
-    CATEGORY = "output"
-    RETURN_TYPES = ()
-    FUNCTION = "run"
-    OUTPUT_NODE = True
-
-    def run(self, name, source=None):
-        value = "None"
-        if source is not None:
-            try:
-                value = json.dumps(source)
-            except Exception:
-                try:
-                    value = str(source)
-                except Exception:
-                    value = "source exists, but could not be serialized."
-
-        return {"ui": {name: (value,)}}
-
-
-NODE_CLASS_MAPPINGS = {"ComfyDeployStdOutputAny": ComfyDeployStdOutputAny}
-NODE_DISPLAY_NAME_MAPPINGS = {
-    "ComfyDeployStdOutputAny": "Standard Any Output (ComfyDeploy)"
-}

comfy-nodes/comfy_std_output_image.py

@@ -1,92 +0,0 @@
-import os
-import json
-import numpy as np
-from PIL import Image
-from PIL.PngImagePlugin import PngInfo
-import folder_paths
-
-
-class ComfyDeployStdOutputImage:
-    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}),
-            },
-            "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,
-        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}
-            )
-            counter += 1
-
-        return {"ui": {"images": results}}
-
-
-NODE_CLASS_MAPPINGS = {"ComfyDeployStdOutputImage": ComfyDeployStdOutputImage}
-NODE_DISPLAY_NAME_MAPPINGS = {
-    "ComfyDeployStdOutputImage": "Standard Image Output (ComfyDeploy)"
-}

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)",
+}

custom_routes.py

@@ -26,7 +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
 
@@ -1120,9 +1123,138 @@ async def proxy_to_comfydeploy(request):
 
 
 prompt_server = server.PromptServer.instance
-send_json = prompt_server.send_json
 
 
+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
+
 async def send_json_override(self, event, data, sid=None):
     # logger.info("INTERNAL:", event, data, sid)
     prompt_id = data.get("prompt_id")
@@ -1145,10 +1277,60 @@ 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()
+            
+        await 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")
+            await 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:
@@ -1227,7 +1409,8 @@ 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 +1422,10 @@ 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
@@ -1713,17 +1897,23 @@ 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
         gpu_event_id = prompt_metadata[prompt_id].gpu_event_id or None

requirements.txt

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

web-plugin/index.js

@@ -4,6 +4,39 @@ import { ComfyWidgets, LGraphNode } from "./widgets.js";
 import { generateDependencyGraph } from "https://esm.sh/[email protected]";
 import { ComfyDeploy } from "https://esm.sh/[email protected]";
 
+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>`;
 
 function sendEventToCD(event, data) {
@@ -122,6 +155,146 @@ 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 +405,118 @@ 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;
+    };
+
+    // 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 {
@@ -463,13 +748,14 @@ 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"
+          "right",
         );
         localStorage.setItem("Comfy.MenuPosition.Docked", "true");
+        window.location.reload();
         console.log("native mode manmanman");
       } catch (error) {
         console.error("Error setting validation to false", error);