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/external_face_model.py

@@ -0,0 +1,108 @@
+from PIL import Image, ImageOps
+import numpy as np
+import torch
+import folder_paths
+
+
+class AnyType(str):
+    def __ne__(self, __value: object) -> bool:
+        return False
+
+
+WILDCARD = AnyType("*")
+
+
+class ComfyUIDeployExternalFaceModel:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "input_id": (
+                    "STRING",
+                    {"multiline": False, "default": "input_reactor_face_model"},
+                ),
+            },
+            "optional": {
+                "default_face_model_name": (
+                    "STRING",
+                    {"multiline": False, "default": ""},
+                ),
+                "face_model_save_name": (  # if `default_face_model_name` is a link to download a file, we will attempt to save it with this name
+                    "STRING",
+                    {"multiline": False, "default": ""},
+                ),
+                "display_name": (
+                    "STRING",
+                    {"multiline": False, "default": ""},
+                ),
+                "description": (
+                    "STRING",
+                    {"multiline": True, "default": ""},
+                ),
+                "face_model_url": (
+                    "STRING",
+                    {"multiline": False, "default": ""},
+                ),
+            },
+        }
+
+    RETURN_TYPES = (WILDCARD,)
+    RETURN_NAMES = ("path",)
+
+    FUNCTION = "run"
+
+    CATEGORY = "deploy"
+
+    def run(
+        self,
+        input_id,
+        default_face_model_name=None,
+        face_model_save_name=None,
+        display_name=None,
+        description=None,
+        face_model_url=None,
+    ):
+        import requests
+        import os
+        import uuid
+
+        if face_model_url and face_model_url.startswith("http"):
+            if face_model_save_name:
+                existing_face_models = folder_paths.get_filename_list("reactor/faces")
+                # Check if face_model_save_name exists in the list
+                if face_model_save_name in existing_face_models:
+                    print(f"using face model: {face_model_save_name}")
+                    return (face_model_save_name,)
+            else:
+                face_model_save_name = str(uuid.uuid4()) + ".safetensors"
+            print(face_model_save_name)
+            print(folder_paths.folder_names_and_paths["reactor/faces"][0][0])
+            destination_path = os.path.join(
+                folder_paths.folder_names_and_paths["reactor/faces"][0][0],
+                face_model_save_name,
+            )
+
+            print(destination_path)
+            print(
+                "Downloading external face model - "
+                + face_model_url
+                + " to "
+                + destination_path
+            )
+            response = requests.get(
+                face_model_url,
+                headers={"User-Agent": "Mozilla/5.0"},
+                allow_redirects=True,
+            )
+            with open(destination_path, "wb") as out_file:
+                out_file.write(response.content)
+            return (face_model_save_name,)
+        else:
+            print(f"using face model: {default_face_model_name}")
+            return (default_face_model_name,)
+
+
+NODE_CLASS_MAPPINGS = {"ComfyUIDeployExternalFaceModel": ComfyUIDeployExternalFaceModel}
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "ComfyUIDeployExternalFaceModel": "External Face Model (ComfyUI Deploy)"
+}

comfy-nodes/external_image_batch.py

@@ -39,14 +39,34 @@ class ComfyUIDeployExternalImageBatch:
 
     CATEGORY = "image"
     
+    def process_image(self, image):
+        image = ImageOps.exif_transpose(image)
+        image = image.convert("RGB")
+        image = np.array(image).astype(np.float32) / 255.0
+        image_tensor = torch.from_numpy(image)[None,]
+        return image_tensor
+    
     def run(self, input_id, images=None, default_value=None, display_name=None, description=None):
+        import requests
+        import zipfile
+        import io
+        
         processed_images = []
         try:
             images_list = json.loads(images)  # Assuming images is a JSON array string
             print(images_list)
             for img_input in images_list:
-                if img_input.startswith('http'):
-                    import requests
+                if img_input.startswith('http') and img_input.endswith('.zip'):
+                    print("Fetching zip file from url: ", img_input)
+                    response = requests.get(img_input)
+                    zip_file = zipfile.ZipFile(io.BytesIO(response.content))
+                    for file_name in zip_file.namelist():
+                        if file_name.lower().endswith(('.png', '.jpg', '.jpeg')):
+                            with zip_file.open(file_name) as file:
+                                image = Image.open(file)
+                                image = self.process_image(image)
+                                processed_images.append(image)
+                elif  img_input.startswith('http'):
                     from io import BytesIO
                     print("Fetching image from url: ", img_input)
                     response = requests.get(img_input)

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/external_text_any.py

@@ -0,0 +1,46 @@
+class AnyType(str):
+    def __ne__(self, __value: object) -> bool:
+        return False
+
+
+WILDCARD = AnyType("*")
+
+class ComfyUIDeployExternalTextAny:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "input_id": (
+                    "STRING",
+                    {"multiline": False, "default": "input_text"},
+                ),
+            },
+            "optional": {
+                "default_value": (
+                    "STRING",
+                    {"multiline": True, "default": ""},
+                ),
+                "display_name": (
+                    "STRING",
+                    {"multiline": False, "default": ""},
+                ),
+                "description": (
+                    "STRING",
+                    {"multiline": True, "default": ""},
+                ),
+            }
+        }
+
+    RETURN_TYPES = (WILDCARD,)
+    RETURN_NAMES = ("text",)
+
+    FUNCTION = "run"
+
+    CATEGORY = "text"
+
+    def run(self, input_id, default_value=None, display_name=None, description=None):
+        return [default_value]
+
+
+NODE_CLASS_MAPPINGS = {"ComfyUIDeployExternalTextAny": ComfyUIDeployExternalTextAny}
+NODE_DISPLAY_NAME_MAPPINGS = {"ComfyUIDeployExternalTextAny": "External Text Any (ComfyUI Deploy)"}

comfy-nodes/external_text_list.py

@@ -1,52 +0,0 @@
-import folder_paths
-from PIL import Image, ImageOps
-import numpy as np
-import torch
-import json
-
-class ComfyUIDeployExternalTextList:
-    @classmethod
-    def INPUT_TYPES(s):
-        return {
-            "required": {
-                "input_id": (
-                    "STRING",
-                    {"multiline": False, "default": 'input_text_list'},
-                ),
-                 "text": (
-                    "STRING",
-                    {"multiline": True, "default": "[]"},
-                ),
-            },
-            "optional": {
-                "display_name": (
-                    "STRING",
-                    {"multiline": False, "default": ""},
-                ),
-                "description": (
-                    "STRING",
-                    {"multiline": True, "default": ""},
-                ),
-            }
-        }
-
-    RETURN_TYPES = ("STRING",)
-    RETURN_NAMES = ("text",)
-
-    OUTPUT_IS_LIST = (True,)
-
-    FUNCTION = "run"
-
-    CATEGORY = "text"
-
-    def run(self, input_id, text=None, display_name=None, description=None):
-        text_list = []
-        try:
-            text_list = json.loads(text)  # Assuming text is a JSON array string
-        except Exception as e:
-            print(f"Error processing images: {e}")
-            pass
-        return ([text_list],)
-
-NODE_CLASS_MAPPINGS = {"ComfyUIDeployExternalTextList": ComfyUIDeployExternalTextList}
-NODE_DISPLAY_NAME_MAPPINGS = {"ComfyUIDeployExternalTextList": "External Text List (ComfyUI Deploy)"}

comfy-nodes/model_list.py

@@ -0,0 +1,60 @@
+import folder_paths
+class AnyType(str):
+    def __ne__(self, __value: object) -> bool:
+        return False
+
+from os import walk
+
+WILDCARD = AnyType("*")
+
+MODEL_EXTENSIONS = {
+    "safetensors": "SafeTensors file format",
+    "ckpt": "Checkpoint file",
+    "pth": "PyTorch serialized file",
+    "pkl": "Pickle file",
+    "onnx": "ONNX file",
+}
+
+def fetch_files(path):
+    for (dirpath, dirnames, filenames) in walk(path):
+        fs = []
+        if len(dirnames) > 0:
+            for dirname in dirnames:
+                fs.extend(fetch_files(f"{dirpath}/{dirname}"))
+        for filename in filenames:
+            # Remove "./models/" from the beginning of dirpath
+            relative_dirpath = dirpath.replace("./models/", "", 1)
+            file_path = f"{relative_dirpath}/{filename}"
+            
+            # Only add files that are known model extensions
+            file_extension = filename.split('.')[-1].lower()
+            if file_extension in MODEL_EXTENSIONS:
+                fs.append(file_path)
+
+        return fs
+allModels = fetch_files("./models")
+
+class ComfyUIDeployModalList:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "model": (allModels, ),
+            }
+        }
+
+    RETURN_TYPES = (WILDCARD,)
+    RETURN_NAMES = ("model",)
+
+    FUNCTION = "run"
+
+    CATEGORY = "model"
+
+    def run(self, model=""):
+        # Split the model path by '/' and select the last item
+        model_name = model.split('/')[-1]
+        return [model_name]
+
+
+NODE_CLASS_MAPPINGS = {"ComfyUIDeployModelList": ComfyUIDeployModalList}
+NODE_DISPLAY_NAME_MAPPINGS = {"ComfyUIDeployModelList": "Model List (ComfyUI Deploy)"}

globals.py

@@ -6,10 +6,12 @@ from PIL import Image, ImageOps
 from io import BytesIO
 from pydantic import BaseModel as PydanticBaseModel
 
+
 class BaseModel(PydanticBaseModel):
     class Config:
         arbitrary_types_allowed = True
-        
+
+
 class Status(Enum):
     NOT_STARTED = "not-started"
     RUNNING = "running"
@@ -17,6 +19,7 @@ class Status(Enum):
     FAILED = "failed"
     UPLOADING = "uploading"
 
+
 class StreamingPrompt(BaseModel):
     workflow_api: Any
     auth_token: str
@@ -24,44 +27,52 @@ class StreamingPrompt(BaseModel):
     running_prompt_ids: set[str] = set()
     status_endpoint: Optional[str]
     file_upload_endpoint: Optional[str]
-    
+    workflow: Any
+    gpu_event_id: Optional[str] = None
+
+
 class SimplePrompt(BaseModel):
     status_endpoint: Optional[str]
     file_upload_endpoint: Optional[str]
-    
+
     token: Optional[str]
-    
+
     workflow_api: dict
     status: Status = Status.NOT_STARTED
     progress: set = set()
-    last_updated_node: Optional[str] = None,
+    last_updated_node: Optional[str] = None
     uploading_nodes: set = set()
     done: bool = False
-    is_realtime: bool = False,
-    start_time: Optional[float] = None,
+    is_realtime: bool = False
+    start_time: Optional[float] = None
+    gpu_event_id: Optional[str] = None
+
 
 sockets = dict()
 prompt_metadata: dict[str, SimplePrompt] = {}
 streaming_prompt_metadata: dict[str, StreamingPrompt] = {}
 
+
 class BinaryEventTypes:
     PREVIEW_IMAGE = 1
     UNENCODED_PREVIEW_IMAGE = 2
-    
+
+
 max_output_id_length = 24
 
-async def send_image(image_data, sid=None, output_id:str = None):
+
+async def send_image(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')
-    
+    padded_output_id = output_id.ljust(max_length, "\x00")
+    encoded_output_id = padded_output_id.encode("ascii", "replace")
+
     image_type = image_data[0]
     image = image_data[1]
     max_size = image_data[2]
     quality = image_data[3]
     if max_size is not None:
-        if hasattr(Image, 'Resampling'):
+        if hasattr(Image, "Resampling"):
             resampling = Image.Resampling.BILINEAR
         else:
             resampling = Image.ANTIALIAS
@@ -85,17 +96,23 @@ async def send_image(image_data, sid=None, output_id:str = None):
     position_after = bytesIO.tell()
     bytes_written = position_after - position_before
     print(f"Bytes written: {bytes_written}")
-    
+
     image.save(bytesIO, format=image_type, quality=quality, compress_level=1)
     preview_bytes = bytesIO.getvalue()
     await send_bytes(BinaryEventTypes.PREVIEW_IMAGE, preview_bytes, sid=sid)
-        
+
+
 async def send_socket_catch_exception(function, message):
     try:
         await function(message)
-    except (aiohttp.ClientError, aiohttp.ClientPayloadError, ConnectionResetError) as err:
+    except (
+        aiohttp.ClientError,
+        aiohttp.ClientPayloadError,
+        ConnectionResetError,
+    ) as err:
         print("send error:", err)
 
+
 def encode_bytes(event, data):
     if not isinstance(event, int):
         raise RuntimeError(f"Binary event types must be integers, got {event}")
@@ -105,9 +122,10 @@ def encode_bytes(event, data):
     message.extend(data)
     return message
 
+
 async def send_bytes(event, data, sid=None):
     message = encode_bytes(event, data)
-    
+
     print("sending image to ", event, sid)
 
     if sid is None:
@@ -115,4 +133,4 @@ async def send_bytes(event, data, sid=None):
         for ws in _sockets:
             await send_socket_catch_exception(ws.send_bytes, message)
     elif sid in sockets:
-        await send_socket_catch_exception(sockets[sid].send_bytes, message)
+        await send_socket_catch_exception(sockets[sid].send_bytes, message)

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "comfyui-deploy"
 description = "Open source comfyui deployment platform, a vercel for generative workflow infra."
-version = "1.0.0"
+version = "1.1.0"
 license = "LICENSE"
 dependencies = ["aiofiles", "pydantic", "opencv-python", "imageio-ffmpeg"]
 

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) {
@@ -83,11 +116,192 @@ function dispatchAPIEventData(data) {
   }
 }
 
+const context = {
+  selectedWorkflowInfo: null,
+};
+// let selectedWorkflowInfo = {
+//   workflow_id: "05da8f2b-63af-4c0c-86dd-08d01ec512b7",
+//   machine_id: "45ac5f85-b7b6-436f-8d97-2383b25485f3",
+//   native_run_api_endpoint: "http://localhost:3011/api/run",
+// };
+
+async function getSelectedWorkflowInfo() {
+  const workflow_info_promise = new Promise((resolve) => {
+    try {
+      const handleMessage = (event) => {
+        try {
+          const message = JSON.parse(event.data);
+          if (message.type === "workflow_info") {
+            resolve(message.data);
+            window.removeEventListener("message", handleMessage);
+          }
+        } catch (error) {
+          console.error(error);
+          resolve(undefined);
+        }
+      };
+      window.addEventListener("message", handleMessage);
+      sendEventToCD("workflow_info");
+    } catch (error) {
+      console.error(error);
+      resolve(undefined);
+    }
+  });
+
+  return workflow_info_promise;
+}
+
+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 = {
   name: "BennyKok.ComfyUIDeploy",
 
+  native_mode: false,
+
   init(app) {
     addButton();
 
@@ -97,16 +311,17 @@ const ext = {
     const org_display = queryParams.get("org_display");
     const origin = queryParams.get("origin");
     const workspace_mode = queryParams.get("workspace_mode");
+    this.native_mode = queryParams.get("native_mode") === "true";
 
     if (workspace_mode) {
       document.querySelector(".comfy-menu").style.display = "none";
 
       sendEventToCD("cd_plugin_onInit");
 
-      app.queuePrompt = ((originalFunction) => async () => {
-        // const prompt = await app.graphToPrompt();
-        sendEventToCD("cd_plugin_onQueuePromptTrigger");
-      })(app.queuePrompt);
+      // app.queuePrompt = ((originalFunction) => async () => {
+      //   // const prompt = await app.graphToPrompt();
+      //   sendEventToCD("cd_plugin_onQueuePromptTrigger");
+      // })(app.queuePrompt);
 
       // // Intercept the onkeydown event
       // window.addEventListener(
@@ -190,13 +405,127 @@ 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 {
-      color = LGraphCanvas.node_colors.yellow.color;
-      bgcolor = LGraphCanvas.node_colors.yellow.bgcolor;
-      groupcolor = LGraphCanvas.node_colors.yellow.groupcolor;
+    class ComfyDeploy extends LGraphNode {
       constructor() {
+        super();
+        this.color = LGraphCanvas.node_colors.yellow.color;
+        this.bgcolor = LGraphCanvas.node_colors.yellow.bgcolor;
+        this.groupcolor = LGraphCanvas.node_colors.yellow.groupcolor;
+
         if (!this.properties) {
           this.properties = {};
           this.properties.workflow_name = "";
@@ -204,62 +533,75 @@ const ext = {
           this.properties.version = "";
         }
 
-        ComfyWidgets.STRING(
-          this,
+        this.addWidget(
+          "text",
           "workflow_name",
-          [
-            "",
-            {
-              default: this.properties.workflow_name,
-              multiline: false,
-            },
-          ],
-          app,
+          this.properties.workflow_name,
+          (v) => {
+            this.properties.workflow_name = v;
+          },
+          { multiline: false },
         );
 
-        ComfyWidgets.STRING(
-          this,
+        this.addWidget(
+          "text",
           "workflow_id",
-          [
-            "",
-            {
-              default: this.properties.workflow_id,
-              multiline: false,
-            },
-          ],
-          app,
+          this.properties.workflow_id,
+          (v) => {
+            this.properties.workflow_id = v;
+          },
+          { multiline: false },
         );
 
-        ComfyWidgets.STRING(
-          this,
+        this.addWidget(
+          "text",
           "version",
-          ["", { default: this.properties.version, multiline: false }],
-          app,
+          this.properties.version,
+          (v) => {
+            this.properties.version = v;
+          },
+          { multiline: false },
         );
 
-        // this.widgets.forEach((w) => {
-        //   // w.computeSize = () => [200,10]
-        //   w.computedHeight = 2;
-        // })
-
         this.widgets_start_y = 10;
-        this.setSize(this.computeSize());
-
-        // const config = {  };
-
-        // console.log(this);
         this.serialize_widgets = true;
         this.isVirtualNode = true;
       }
+
+      onExecute() {
+        // This method is called when the node is executed
+        // You can add any necessary logic here
+      }
+
+      onSerialize(o) {
+        // This method is called when the node is being serialized
+        // Ensure all necessary data is saved
+        if (!o.properties) {
+          o.properties = {};
+        }
+        o.properties.workflow_name = this.properties.workflow_name;
+        o.properties.workflow_id = this.properties.workflow_id;
+        o.properties.version = this.properties.version;
+      }
+
+      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) {
+          this.properties = { ...this.properties, ...o.properties };
+          this.widgets[0].value = this.properties.workflow_name || "";
+          this.widgets[1].value = this.properties.workflow_id || "";
+          this.widgets[2].value = this.properties.version || "1";
+        }
+      }
     }
 
-    // Load default visibility
-
+    // Register the node type
     LiteGraph.registerNodeType(
       "ComfyDeploy",
       Object.assign(ComfyDeploy, {
-        title_mode: LiteGraph.NORMAL_TITLE,
         title: "Comfy Deploy",
+        title_mode: LiteGraph.NORMAL_TITLE,
         collapsable: true,
       }),
     );
@@ -281,6 +623,17 @@ const ext = {
           // This part of the code would depend on how the ComfyUI expects to receive and process the workflow data
           // For demonstration, let's assume there's a loadWorkflow method in the ComfyUI API
           if (comfyUIWorkflow && app && app.loadGraphData) {
+            try {
+              await window["app"].ui.settings.setSettingValueAsync(
+                "Comfy.Validation.Workflows",
+                false,
+              );
+            } catch (error) {
+              console.warning(
+                "Error setting validation to false, is fine to ignore this",
+                error,
+              );
+            }
             console.log("loadGraphData");
             app.loadGraphData(comfyUIWorkflow);
           }
@@ -368,6 +721,8 @@ const ext = {
           }
 
           animate();
+        } else if (message.type === "workflow_info") {
+          setSelectedWorkflowInfo(message.data);
         }
         // else if (message.type === "refresh") {
         //   sendEventToCD("cd_plugin_onRefresh");
@@ -387,6 +742,26 @@ const ext = {
       //   }
     });
 
+    if (this.native_mode) {
+      // console.log("native mode", window, window.app);
+      try {
+        await app.ui.settings.setSettingValueAsync("Comfy.UseNewMenu", "Top");
+        await app.ui.settings.setSettingValueAsync(
+          "Comfy.Sidebar.Size",
+          "small",
+        );
+        await app.ui.settings.setSettingValueAsync(
+          "Comfy.Sidebar.Location",
+          "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);
+      }
+    }
+
     app.graph.onAfterChange = ((originalFunction) =>
       async function () {
         const prompt = await app.graphToPrompt();
@@ -1482,3 +1857,38 @@ async function loadWorkflowApi(versionId) {
     // Show an error message to the user
   }
 }
+
+const orginal_fetch_api = api.fetchApi;
+api.fetchApi = async (route, options) => {
+  console.log("Fetch API called with args:", route, options, ext.native_mode);
+
+  if (route.startsWith("/prompt") && ext.native_mode) {
+    const info = await getSelectedWorkflowInfo();
+    console.log("info", info);
+    if (info) {
+      const body = JSON.parse(options.body);
+
+      const data = {
+        client_id: body.client_id,
+        workflow_api_json: body.prompt,
+        workflow: body?.extra_data?.extra_pnginfo?.workflow,
+        is_native_run: true,
+        machine_id: info.machine_id,
+        workflow_id: info.workflow_id,
+        native_run_api_endpoint: info.native_run_api_endpoint,
+        gpu_event_id: info.gpu_event_id,
+      };
+
+      return await fetch("/comfyui-deploy/run", {
+        method: "POST",
+        headers: {
+          Authorization: `Bearer ${info.cd_token}`,
+          "Content-Type": "application/json",
+        },
+        body: JSON.stringify(data),
+      });
+    }
+  }
+
+  return await orginal_fetch_api.call(api, route, options);
+};

web/src/components/customInputNodes.tsx

@@ -6,4 +6,5 @@ export const customInputNodes: Record<string, string> = {
   ComfyUIDeployExternalNumberInt: "integer",
   ComfyUIDeployExternalLora: "string - (public lora download url)",
   ComfyUIDeployExternalCheckpoint: "string - (public checkpoints download url)",
+  ComfyUIDeployExternalFaceModel: "string - (public face model download url)",
 };