tweak

- Updated the save method in ConfigDialog to be asynchronous, allowing for smoother handling of configuration saves.
- Added a new function to refresh the workflow list if the sidebar is open, ensuring the UI reflects the latest data after configuration changes.
- Made workflowsState globally accessible for improved state management across components.
- Adjusted the height of the workflows list for better UI layout.

These changes improve the user experience by ensuring that the workflow list is up-to-date and enhancing the overall responsiveness of the configuration dialog.

comfy-nodes/external_audio.py

@@ -1,14 +1,13 @@
-import os
 import io
-import torchaudio
 from folder_paths import get_annotated_filepath
 
+
 class ComfyUIDeployExternalAudio:
     RETURN_TYPES = ("AUDIO",)
     RETURN_NAMES = ("audio",)
     FUNCTION = "load_audio"
     CATEGORY = "🔗ComfyDeploy"
-    
+
     @classmethod
     def INPUT_TYPES(cls):
         return {
@@ -29,30 +28,55 @@ class ComfyUIDeployExternalAudio:
                     "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)
+    def load_audio(
+        self,
+        input_id,
+        audio_file,
+        default_value=None,
+        display_name=None,
+        description=None,
+    ):
+        try:
+            import torchaudio
+
+            if audio_file and audio_file != "":
+                if audio_file.startswith(("http://", "https://")):
+                    # Handle URL input
+                    try:
+                        import requests
+
+                        response = requests.get(audio_file)
+                        audio_data = io.BytesIO(response.content)
+                        waveform, sample_rate = torchaudio.load(audio_data)
+                    except Exception as e:
+                        print(f"Error loading audio from URL: {e}")
+                        return (default_value,)
+                else:
+                    # Handle local file
+                    try:
+                        audio_path = get_annotated_filepath(audio_file)
+                        waveform, sample_rate = torchaudio.load(audio_path)
+                    except Exception as e:
+                        print(f"Error loading local audio file: {e}")
+                        return (default_value,)
+
+                audio = {"waveform": waveform.unsqueeze(0), "sample_rate": sample_rate}
+                return (audio,)
             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,)
+        except ImportError as e:
+            print(f"Error: torchaudio not installed or cannot be imported: {e}")
             return (default_value,)
 
+
 NODE_CLASS_MAPPINGS = {"ComfyUIDeployExternalAudio": ComfyUIDeployExternalAudio}
-NODE_DISPLAY_NAME_MAPPINGS = {"ComfyUIDeployExternalAudio": "External Audio (ComfyUI Deploy)"}
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "ComfyUIDeployExternalAudio": "External Audio (ComfyUI Deploy)"
+}

comfy-nodes/external_lora.py

@@ -1,8 +1,4 @@
 import folder_paths
-from PIL import Image, ImageOps
-import numpy as np
-import torch
-import folder_paths
 
 
 class AnyType(str):
@@ -41,6 +37,10 @@ class ComfyUIDeployExternalLora:
                     "STRING",
                     {"multiline": False, "default": ""},
                 ),
+                "bearer_token": (
+                    "STRING",
+                    {"multiline": False, "default": ""},
+                ),
             },
         }
 
@@ -57,6 +57,7 @@ class ComfyUIDeployExternalLora:
         display_name=None,
         description=None,
         lora_url=None,
+        bearer_token=None,
     ):
         import requests
         import os
@@ -84,9 +85,13 @@ class ComfyUIDeployExternalLora:
                     + " to "
                     + destination_path
                 )
+                headers = {"User-Agent": "Mozilla/5.0"}
+                if bearer_token:
+                    headers["Authorization"] = f"Bearer {bearer_token}"
+                    print("using bearer token")
                 response = requests.get(
                     lora_url,
-                    headers={"User-Agent": "Mozilla/5.0"},
+                    headers=headers,
                     allow_redirects=True,
                 )
                 with open(destination_path, "wb") as out_file:

comfy-nodes/external_number_slider_int.py

@@ -0,0 +1,54 @@
+class ComfyUIDeployExternalNumberSliderInt:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "input_id": (
+                    "STRING",
+                    {"multiline": False, "default": "input_number_slider_int"},
+                ),
+            },
+            "optional": {
+                "default_value": (
+                    "INT",
+                    {"multiline": True, "display": "number", "min": -2147483647, "max": 2147483647, "default": 1, "step": 1},
+                ),
+                "min_value": (
+                    "INT",
+                    {"multiline": True, "display": "number", "min": -2147483647, "max": 2147483647, "default": 0, "step": 1},
+                ),
+                "max_value": (
+                    "INT",
+                    {"multiline": True, "display": "number", "min": -2147483647, "max": 2147483647, "default": 10, "step": 1},
+                ),
+                "display_name": (
+                    "STRING",
+                    {"multiline": False, "default": ""},
+                ),
+                "description": (
+                    "STRING",
+                    {"multiline": True, "default": ""},
+                ),
+            }
+        }
+
+    RETURN_TYPES = ("INT",)
+    RETURN_NAMES = ("value",)
+    FUNCTION = "run"
+    CATEGORY = "🔗ComfyDeploy"
+
+    def run(self, input_id, default_value=None, min_value=0, max_value=10, display_name=None, description=None):
+        try:
+            int_value = int(round(float(input_id)))
+            if min_value <= int_value <= max_value:
+                print("my integer", int_value)
+                return [int_value]
+            else:
+                print("Integer out of range. Returning default value:", default_value)
+                return [default_value]
+        except (ValueError, TypeError):
+            print("Invalid input. Returning default value:", default_value)
+            return [default_value]
+
+NODE_CLASS_MAPPINGS = {"ComfyUIDeployExternalNumberSliderInt": ComfyUIDeployExternalNumberSliderInt}
+NODE_DISPLAY_NAME_MAPPINGS = {"ComfyUIDeployExternalNumberSliderInt": "External Number Slider Int (ComfyUI Deploy)"}

comfy-nodes/external_seed.py

@@ -0,0 +1,116 @@
+import random
+
+
+class ComfyUIDeployExternalSeed:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "input_id": (
+                    "STRING",
+                    {"multiline": False, "default": "input_seed"},
+                ),
+                "default_value": (
+                    "INT",
+                    {"default": -1},
+                ),
+                "min_value": (
+                    "INT",
+                    {"default": 1, "min": 1, "max": 999999999999999},
+                ),
+                "max_value": (
+                    "INT",
+                    {"default": 4294967295, "min": 1, "max": 999999999999999},
+                ),
+            },
+            "optional": {
+                "display_name": (
+                    "STRING",
+                    {"multiline": False, "default": ""},
+                ),
+                "description": (
+                    "STRING",
+                    {
+                        "multiline": True,
+                        "default": 'For default value:\n"-1" (i.e. not in range): Randomize within the min and max value range. \nin range: Fixed, always the same value\n',
+                    },
+                ),
+            },
+        }
+
+    RETURN_TYPES = ("INT",)
+    RETURN_NAMES = ("seed",)
+    FUNCTION = "run"
+    CATEGORY = "🔗ComfyDeploy"
+
+    # Limits
+    _MAX_LIMIT = 999_999_999_999_999  # 15 digits
+
+    # Store cached seed when fixed flag is enabled
+    _cached_seed = None
+
+    @classmethod
+    def IS_CHANGED(
+        cls,
+        input_id,
+        min_value,
+        max_value,
+        default_value=None,
+        **kwargs,
+    ):
+        """Inform ComfyUI whether the node output should be considered changed.
+
+        If default_value is within range (Fixed mode), we return the inputs tuple
+        so the cached result is reused until the user changes something.
+        For Randomize mode, we force re-execution each queue.
+        """
+        # Clamp values to allowed range for check
+        min_value = max(1, min_value)
+        max_value = min(cls._MAX_LIMIT, max_value)
+
+        # Fixed mode when default_value is within range
+        if (
+            default_value is not None
+            and default_value >= min_value
+            and default_value <= max_value
+        ):
+            return (input_id, default_value)
+
+        # For Randomize (default_value is -1 or out of range) we force re-execution
+        import random as _rnd
+
+        return _rnd.random()
+
+    def run(
+        self,
+        input_id,
+        min_value: int,
+        max_value: int,
+        display_name=None,
+        description=None,
+        default_value: int = -1,
+    ):
+        # Clamp values to allowed range
+        min_value = max(1, min_value)
+        max_value = min(self._MAX_LIMIT, max_value)
+
+        # Ensure limits are in correct order after clamping
+        if min_value > max_value:
+            min_value, max_value = max_value, min_value
+
+        # Fixed mode: default_value is within range
+        if default_value >= min_value and default_value <= max_value:
+            seed = int(default_value)
+            self._cached_seed = seed
+            return [seed]
+
+        # Randomize mode: default_value is -1 or out of range
+        seed = random.randint(min_value, max_value)
+        self._cached_seed = seed
+        return [seed]
+
+
+NODE_CLASS_MAPPINGS = {"ComfyUIDeployExternalSeed": ComfyUIDeployExternalSeed}
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "ComfyUIDeployExternalSeed": "External Seed (ComfyUI Deploy)"
+}

comfy-nodes/external_video.py

@@ -748,36 +748,64 @@ class ComfyUIDeployExternalVideo:
                 file_parts = f.split(".")
                 if len(file_parts) > 1 and (file_parts[-1] in video_extensions):
                     files.append(f)
-        return {"required": {
-                    "input_id": (
-                        "STRING",
-                        {"multiline": False, "default": "input_video"},
-                    ),
-                     "force_rate": ("INT", {"default": 0, "min": 0, "max": 60, "step": 1}),
-                     "force_size": (["Disabled", "Custom Height", "Custom Width", "Custom", "256x?", "?x256", "256x256", "512x?", "?x512", "512x512"],),
-                     "custom_width": ("INT", {"default": 512, "min": 0, "max": DIMMAX, "step": 8}),
-                     "custom_height": ("INT", {"default": 512, "min": 0, "max": DIMMAX, "step": 8}),
-                     "frame_load_cap": ("INT", {"default": 0, "min": 0, "max": BIGMAX, "step": 1}),
-                     "skip_first_frames": ("INT", {"default": 0, "min": 0, "max": BIGMAX, "step": 1}),
-                     "select_every_nth": ("INT", {"default": 1, "min": 1, "max": BIGMAX, "step": 1}),
-                     },
-                "optional": {
-                    "meta_batch": ("VHS_BatchManager",),
-                    "vae": ("VAE",),
-                    "default_video": (sorted(files),),
-                    "display_name": (
-                        "STRING",
-                        {"multiline": False, "default": ""},
-                    ),
-                    "description": (
-                        "STRING",
-                        {"multiline": True, "default": ""},
-                    ),
-                },
-                "hidden": {
-                    "unique_id": "UNIQUE_ID"
-                },
-                }
+        return {
+            "required": {
+                "input_id": (
+                    "STRING",
+                    {"multiline": False, "default": "input_video"},
+                ),
+                "force_rate": ("INT", {"default": 0, "min": 0, "max": 60, "step": 1}),
+                "force_size": (
+                    [
+                        "Disabled",
+                        "Custom Height",
+                        "Custom Width",
+                        "Custom",
+                        "256x?",
+                        "?x256",
+                        "256x256",
+                        "512x?",
+                        "?x512",
+                        "512x512",
+                    ],
+                ),
+                "custom_width": (
+                    "INT",
+                    {"default": 512, "min": 0, "max": DIMMAX, "step": 8},
+                ),
+                "custom_height": (
+                    "INT",
+                    {"default": 512, "min": 0, "max": DIMMAX, "step": 8},
+                ),
+                "frame_load_cap": (
+                    "INT",
+                    {"default": 0, "min": 0, "max": BIGMAX, "step": 1},
+                ),
+                "skip_first_frames": (
+                    "INT",
+                    {"default": 0, "min": 0, "max": BIGMAX, "step": 1},
+                ),
+                "select_every_nth": (
+                    "INT",
+                    {"default": 1, "min": 1, "max": BIGMAX, "step": 1},
+                ),
+            },
+            "optional": {
+                "meta_batch": ("VHS_BatchManager",),
+                "vae": ("VAE",),
+                "default_video": (sorted(files),),
+                "display_name": (
+                    "STRING",
+                    {"multiline": False, "default": ""},
+                ),
+                "description": (
+                    "STRING",
+                    {"multiline": True, "default": ""},
+                ),
+                "default_value_url": ("STRING", {"image_preview": True, "default": ""}),
+            },
+            "hidden": {"unique_id": "UNIQUE_ID"},
+        }
 
     CATEGORY = "Video Helper Suite 🎥🅥🅗🅢"
 
@@ -804,16 +832,21 @@ class ComfyUIDeployExternalVideo:
         select_every_nth = kwargs.get("select_every_nth")
         meta_batch = kwargs.get("meta_batch")
         unique_id = kwargs.get("unique_id")
-
+        default_value_url = kwargs.get("default_value_url")
 
         input_dir = folder_paths.get_input_directory()
-        if input_id.startswith("http"):
+        if input_id.startswith("http") or (
+            default_value_url and default_value_url.startswith("http")
+        ):
             import requests
 
-            print("Fetching video from URL: ", input_id)
-            response = requests.get(input_id, stream=True)
+            # Use input_id if it's a URL, otherwise use default_value_url
+            url = input_id if input_id.startswith("http") else default_value_url
+
+            print("Fetching video from URL: ", url)
+            response = requests.get(url, stream=True)
             file_size = int(response.headers.get("Content-Length", 0))
-            file_extension = input_id.split(".")[-1].split("?")[
+            file_extension = url.split(".")[-1].split("?")[
                 0
             ]  # Extract extension and handle URLs with parameters
             if file_extension not in video_extensions:

comfy-nodes/output_text.py

@@ -0,0 +1,99 @@
+import os
+import json
+import folder_paths
+
+
+class ComfyDeployOutputText:
+    def __init__(self):
+        self.output_dir = folder_paths.get_output_directory()
+        self.type = "output"
+        self.prefix_append = ""
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "text": (
+                    "STRING",
+                    {
+                        "multiline": True,
+                        "forceInput": True,
+                        "tooltip": "The text 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% to include values from nodes.",
+                    },
+                ),
+                "file_type": (["txt", "json", "md"], {"default": "txt"}),
+            },
+            "optional": {
+                "output_id": (
+                    "STRING",
+                    {"multiline": False, "default": "output_text"},
+                ),
+            },
+            "hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"},
+        }
+
+    RETURN_TYPES = ()
+    FUNCTION = "run"
+
+    OUTPUT_NODE = True
+    CATEGORY = "🔗ComfyDeploy"
+    DESCRIPTION = "Saves the input text to your ComfyUI output directory."
+
+    def run(
+        self,
+        text,
+        filename_prefix="ComfyUI",
+        file_type="txt",
+        output_id="output_text",
+        prompt=None,
+        extra_pnginfo=None,
+    ):
+        filename_prefix += self.prefix_append
+        # For text, we don't need dimensions, so pass 0, 0
+        full_output_folder, filename, counter, subfolder, filename_prefix = (
+            folder_paths.get_save_image_path(filename_prefix, self.output_dir, 0, 0)
+        )
+
+        results = list()
+
+        # Create file path
+        file = f"{filename}_{counter:05}_.{file_type}"
+        file_path = os.path.join(full_output_folder, file)
+
+        # Save the text based on file type
+        if file_type == "json":
+            try:
+                # Try to save as JSON if the text is valid JSON
+                json_data = json.loads(text) if isinstance(text, str) else text
+                with open(file_path, "w", encoding="utf-8") as f:
+                    json.dump(json_data, f, indent=2)
+            except json.JSONDecodeError:
+                # Fall back to saving as plain text if not valid JSON
+                with open(file_path, "w", encoding="utf-8") as f:
+                    f.write(text)
+        else:
+            # Save as plain text for txt and md
+            with open(file_path, "w", encoding="utf-8") as f:
+                f.write(text)
+
+        results.append(
+            {
+                "filename": file,
+                "subfolder": subfolder,
+                "type": self.type,
+                "output_id": output_id,
+            }
+        )
+
+        return {"ui": {"text_file": results}}
+
+
+NODE_CLASS_MAPPINGS = {"ComfyDeployOutputText": ComfyDeployOutputText}
+NODE_DISPLAY_NAME_MAPPINGS = {"ComfyDeployOutputText": "Text Output (ComfyDeploy)"}

custom_routes.py

@@ -31,6 +31,7 @@ import torch
 import psutil
 from collections import OrderedDict
 import io
+from urllib.parse import urlencode
 
 # Global session
 client_session = None
@@ -139,7 +140,9 @@ async def async_request_with_retry(
                 logger.error(f"Error response body: {error_body}")
 
             if attempt == max_retries - 1:
-                logger.error(f"Request {method} : {url} failed after {max_retries} attempts: {e}")
+                logger.error(
+                    f"Request {method} : {url} failed after {max_retries} attempts: {e}"
+                )
                 raise
 
         await asyncio.sleep(retry_delay)
@@ -156,6 +159,8 @@ from logging import basicConfig, getLogger
 # Check for an environment variable to enable/disable Logfire
 use_logfire = os.environ.get("USE_LOGFIRE", "false").lower() == "true"
 
+API_KEY_COMFY_ORG = os.environ.get("API_KEY_COMFY_ORG", None)
+
 if use_logfire:
     try:
         import logfire
@@ -281,6 +286,9 @@ def post_prompt(json_data):
         if "extra_data" in json_data:
             extra_data = json_data["extra_data"]
 
+        if API_KEY_COMFY_ORG is not None:
+            extra_data["api_key_comfy_org"] = API_KEY_COMFY_ORG
+
         if "client_id" in json_data:
             extra_data["client_id"] = json_data["client_id"]
         if valid[0]:
@@ -314,7 +322,7 @@ def randomSeed(num_digits=15):
     return random.randint(range_start, range_end)
 
 
-def apply_random_seed_to_workflow(workflow_api):
+def apply_random_seed_to_workflow(workflow_api, workflow):
     """
     Applies a random seed to each element in the workflow_api that has a 'seed' input.
 
@@ -327,6 +335,41 @@ def apply_random_seed_to_workflow(workflow_api):
                 # 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
+
+                # Check node type in workflow to determine if we should randomize
+                node_id = key
+                should_skip = (
+                    False  # Add a flag to track if we should skip randomization
+                )
+
+                for node in workflow["nodes"]:
+                    if str(node["id"]) == node_id and node["type"] == "KSampler":
+                        # Check if this node has widgets_values and if seed setting is not "fixed"
+                        if "widgets_values" in node and len(node["widgets_values"]) > 1:
+                            seed_mode = node["widgets_values"][1]
+                            if seed_mode == "fixed":
+                                # Skip randomization for fixed seeds
+                                logger.info(
+                                    f"Skipping random seed for KSampler (node {node_id}) as it's set to fixed"
+                                )
+                                should_skip = True  # Set the flag to skip randomization
+                                break  # Exit the inner loop
+
+                            # Apply random seed for non-fixed seeds (randomize, iter, etc.)
+                            workflow_api[key]["inputs"]["seed"] = randomSeed()
+                            logger.info(
+                                f"Applied random seed {workflow_api[key]['inputs']['seed']} to KSampler (node {node_id})"
+                            )
+                            should_skip = (
+                                True  # Set the flag to skip default randomization
+                            )
+                            break  # Exit the inner loop
+                        break  # This break will skip checking other nodes if widgets_values doesn't exist
+
+                # Skip the rest of the code for this key if we already handled it
+                if should_skip:
+                    continue
+
                 # Special case for SONICSampler
                 if workflow_api[key]["class_type"] == "SONICSampler":
                     workflow_api[key]["inputs"]["seed"] = randomSeed("sonic")
@@ -413,6 +456,9 @@ def apply_inputs_to_workflow(workflow_api: Any, inputs: Any, sid: str = None):
                 if value["class_type"] == "ComfyUIDeployExternalImageBatch":
                     value["inputs"]["images"] = new_value
 
+                if value["class_type"] == "ComfyUIDeployExternalEnum":
+                    value["inputs"]["default_value"] = new_value
+
                 if value["class_type"] == "ComfyUIDeployExternalLora":
                     value["inputs"]["lora_url"] = new_value
 
@@ -431,6 +477,12 @@ def apply_inputs_to_workflow(workflow_api: Any, inputs: Any, sid: str = None):
                 if value["class_type"] == "ComfyUIDeployExternalEXR":
                     value["inputs"]["exr_file"] = new_value
 
+                if value["class_type"] == "ComfyUIDeployExternalSeed":
+                    logger.info(
+                        f"Applied random seed {new_value} to {value['class_type']}"
+                    )
+                    value["inputs"]["default_value"] = new_value
+
 
 def send_prompt(sid: str, inputs: StreamingPrompt):
     # workflow_api = inputs.workflow_api
@@ -438,7 +490,7 @@ def send_prompt(sid: str, inputs: StreamingPrompt):
     workflow = copy.deepcopy(inputs.workflow)
 
     # Random seed
-    apply_random_seed_to_workflow(workflow_api)
+    apply_random_seed_to_workflow(workflow_api, workflow)
 
     logger.info("getting inputs", inputs.inputs)
 
@@ -524,7 +576,7 @@ async def comfy_deploy_run(request):
     workflow = data.get("workflow")
 
     # Now it handles directly in here
-    apply_random_seed_to_workflow(workflow_api)
+    apply_random_seed_to_workflow(workflow_api, workflow)
     apply_inputs_to_workflow(workflow_api, inputs)
 
     prompt = {
@@ -591,7 +643,7 @@ async def stream_prompt(data, token):
     gpu_event_id = data.get("gpu_event_id", None)
 
     # Now it handles directly in here
-    apply_random_seed_to_workflow(workflow_api)
+    apply_random_seed_to_workflow(workflow_api, workflow)
     apply_inputs_to_workflow(workflow_api, inputs)
 
     prompt = {
@@ -1310,7 +1362,7 @@ send_json = prompt_server.send_json
 
 
 async def send_json_override(self, event, data, sid=None):
-    # logger.info("INTERNAL:", event, data, sid)
+    # logger.info(f"INTERNAL: event={event}, data={data}, sid={sid}")
     prompt_id = data.get("prompt_id")
 
     target_sid = sid
@@ -1395,9 +1447,12 @@ async def send_json_override(self, event, data, sid=None):
     # 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)
+        # We will now rely on the UploadQueue worker to set the final SUCCESS status
+        # after all uploads are confirmed complete.
+
         if not have_pending_upload(prompt_id):
-            await update_run(prompt_id, Status.SUCCESS)
-            if prompt_id in prompt_metadata:
+            # await update_run(prompt_id, Status.SUCCESS) # <-- REMOVE/COMMENT OUT
+            if prompt_id in prompt_metadata:  # <-- REMOVE/COMMENT OUT THIS BLOCK
                 current_time = time.perf_counter()
                 if prompt_metadata[prompt_id].start_time is not None:
                     elapsed_time = current_time - prompt_metadata[prompt_id].start_time
@@ -1838,12 +1893,13 @@ async def upload_file(
 
 
 def have_pending_upload(prompt_id):
+    # Check if there are pending uploads in the queue
     if (
-        prompt_id in prompt_metadata
-        and len(prompt_metadata[prompt_id].uploading_nodes) > 0
+        prompt_id in upload_queue.pending_uploads
+        and upload_queue.pending_uploads[prompt_id]
     ):
         logger.info(
-            f"Have pending upload {len(prompt_metadata[prompt_id].uploading_nodes)}"
+            f"Have pending upload {len(upload_queue.pending_uploads[prompt_id])}"
         )
         return True
 
@@ -1898,16 +1954,11 @@ async def handle_error(prompt_id, data, e: Exception):
 async def update_file_status(
     prompt_id: str, data, uploading, have_error=False, node_id=None
 ):
-    # if 'uploading_nodes' not in prompt_metadata[prompt_id]:
-    #     prompt_metadata[prompt_id]['uploading_nodes'] = set()
+    # We're using upload_queue as the single source of truth for tracking uploads
+    # The upload_queue.pending_uploads is managed by the UploadQueue class itself
+    # We no longer need to track uploading_nodes in prompt_metadata
 
-    if node_id is not None:
-        if uploading:
-            prompt_metadata[prompt_id].uploading_nodes.add(node_id)
-        else:
-            prompt_metadata[prompt_id].uploading_nodes.discard(node_id)
-
-    # logger.info(f"Remaining uploads: {prompt_metadata[prompt_id].uploading_nodes}")
+    # logger.info(f"Pending uploads in queue: {upload_queue.pending_uploads.get(prompt_id, set())}")
     # Update the remote status
 
     if have_error:
@@ -1921,15 +1972,15 @@ async def update_file_status(
         return
 
     # if there are still nodes that are uploading, then we set the status to uploading
-    if uploading:
-        if prompt_metadata[prompt_id].status != Status.UPLOADING:
-            await update_run(prompt_id, Status.UPLOADING)
-            await send(
-                "uploading",
-                {
-                    "prompt_id": prompt_id,
-                },
-            )
+    # if uploading:
+    #     if prompt_metadata[prompt_id].status != Status.UPLOADING:
+    #         await update_run(prompt_id, Status.UPLOADING)
+    #         await send(
+    #             "uploading",
+    #             {
+    #                 "prompt_id": prompt_id,
+    #             },
+    #         )
 
     # if there are no nodes that are uploading, then we set the status to success
     elif (
@@ -1955,7 +2006,7 @@ async def handle_upload(
 
     for item in items:
         # Skipping temp files
-        if item.get("type") == "temp":
+        if isinstance(item, dict) and item.get("type") == "temp":
             continue
 
         file_type = item.get(content_type_key, default_content_type)
@@ -2006,22 +2057,29 @@ async def upload_in_background(
                 ("files", "content_type", "image/png"),
                 ("gifs", "format", "image/gif"),
                 ("model_file", "format", "application/octet-stream"),
+                ("result", "format", "application/octet-stream"),
+                ("text_file", "format", "text/plain"),
             ]:
                 items = data.get(file_type, [])
 
                 for item in items:
                     # if is model_file, just add it to the data
-                    if file_type == "model_file":
+                    if file_type == "model_file" or file_type == "result":
                         if isinstance(item, str):
                             filename = os.path.basename(item)
+                            # Extract folder name from the path
+                            folder_path = os.path.dirname(item)
+                            subfolder = (
+                                os.path.basename(folder_path) if folder_path else ""
+                            )
                             item = {
                                 "filename": filename,
-                                "subfolder": "",
+                                "subfolder": subfolder,
                                 "type": "output",
                             }
 
                     # Skip temp files
-                    if item.get("type") == "temp":
+                    if isinstance(item, dict) and item.get("type") == "temp":
                         continue
 
                     # Add to the upload queue instead of uploading immediately
@@ -2086,6 +2144,8 @@ async def update_run_with_output(
             or "files" in data
             or "gifs" in data
             or "model_file" in data
+            or "result" in data
+            or "text_file" in data
         )
     if bypass_upload and have_upload_media:
         print(
@@ -2396,6 +2456,11 @@ class UploadQueue:
             logger.warning(f"No upload endpoint for prompt ID: {prompt_id}")
             return
 
+        # Check if file_info is a valid dictionary with a filename
+        if not isinstance(file_info, dict) or "filename" not in file_info:
+            logger.warning(f"Invalid file_info for prompt ID {prompt_id}: {file_info}")
+            return
+
         filename = file_info.get("filename")
         subfolder = file_info.get("subfolder")
         file_type = file_info.get("type", "output")
@@ -2546,8 +2611,12 @@ class UploadQueue:
                     # If this was the last file for this prompt, show the stats summary
                     if (
                         prompt_id in self.pending_uploads
+                        # We now rely on the worker's finally block for the final SUCCESS update.
+                        # Check if the set becomes empty *after* removal in the worker.
                         and len(self.pending_uploads[prompt_id]) == 1
                     ):
+                        # await update_run(prompt_id, Status.SUCCESS) # <-- REMOVE/COMMENT OUT
+
                         self._log_upload_stats(prompt_id)
                         # Clean up stats
                         del self.upload_stats[prompt_id]
@@ -2668,6 +2737,8 @@ class UploadQueue:
                 node_id = upload_task["node_id"]
                 upload_id = upload_task["upload_id"]
 
+                print(file_info)
+
                 try:
                     # Coordinate the actual start of the upload
                     async with self.upload_lock:
@@ -2697,30 +2768,38 @@ class UploadQueue:
                             # If this was the last upload for this node, clean up node data
                             if not self.node_uploads[prompt_id][node_id]:
                                 del self.node_uploads[prompt_id][node_id]
-                                if self.node_output_data[prompt_id][node_id]["data"]:
-                                    # Send final node data to API before cleanup
-                                    if prompt_metadata[prompt_id].status_endpoint:
-                                        body = {
-                                            "run_id": prompt_id,
-                                            "output_data": self.node_output_data[
+                                if prompt_id in self.node_output_data:
+                                    if node_id in self.node_output_data[prompt_id]:
+                                        if self.node_output_data[prompt_id][node_id][
+                                            "data"
+                                        ]:
+                                            # Send final node data to API before cleanup
+                                            if prompt_metadata[
                                                 prompt_id
-                                            ][node_id]["data"],
-                                            "node_meta": {"node_id": node_id},
-                                        }
-                                        try:
-                                            await async_request_with_retry(
-                                                "POST",
-                                                prompt_metadata[
-                                                    prompt_id
-                                                ].status_endpoint,
-                                                token=prompt_metadata[prompt_id].token,
-                                                json=body,
-                                            )
-                                        except Exception as e:
-                                            logger.error(
-                                                f"Failed to send final node data: {str(e)}"
-                                            )
-                                del self.node_output_data[prompt_id][node_id]
+                                            ].status_endpoint:
+                                                body = {
+                                                    "run_id": prompt_id,
+                                                    "output_data": self.node_output_data[
+                                                        prompt_id
+                                                    ][node_id]["data"],
+                                                    "node_meta": {"node_id": node_id},
+                                                }
+                                                try:
+                                                    await async_request_with_retry(
+                                                        "POST",
+                                                        prompt_metadata[
+                                                            prompt_id
+                                                        ].status_endpoint,
+                                                        token=prompt_metadata[
+                                                            prompt_id
+                                                        ].token,
+                                                        json=body,
+                                                    )
+                                                except Exception as e:
+                                                    logger.error(
+                                                        f"Failed to send final node data: {str(e)}"
+                                                    )
+                                        del self.node_output_data[prompt_id][node_id]
 
                         # Send status update
                         await self.update_queue_status(prompt_id)
@@ -2813,3 +2892,171 @@ def format_execution_timeline(execution_times):
         current_time += duration
 
     return format_table(headers, rows)
+
+
+@server.PromptServer.instance.routes.get("/comfyui-deploy/auth-response")
+async def auth_response_proxy(request):
+    request_id = request.rel_url.query.get("request_id")
+    api_url = request.rel_url.query.get("api_url", "https://api.comfydeploy.com")
+
+    if not request_id:
+        return web.json_response({"error": "request_id is required"}, status=400)
+
+    target_url = f"{api_url}/api/platform/comfyui/auth-response?request_id={request_id}"
+
+    try:
+        await ensure_client_session()
+        async with client_session.get(target_url) as response:
+            json_data = await response.json()
+            return web.json_response(json_data, status=response.status)
+    except Exception as e:
+        return web.json_response({"error": str(e)}, status=500)
+
+
+@server.PromptServer.instance.routes.post("/comfyui-deploy/workflow")
+async def create_workflow_proxy(request):
+    data = await request.json()
+    name = data.get("name")
+    workflow_json = data.get("workflow_json")
+    workflow_api = data.get("workflow_api")
+    api_url = data.get("api_url", "https://api.comfydeploy.com")
+
+    auth_header = request.headers.get("Authorization")
+    if not auth_header:
+        return web.json_response(
+            {"error": "Authorization header is required"}, status=401
+        )
+
+    if not name or not workflow_json or not workflow_api:
+        return web.json_response(
+            {"error": "name, workflow_json, workflow_api are required"}, status=400
+        )
+
+    target_url = f"{api_url}/api/workflow"
+
+    request_body = {
+        "name": name,
+        "workflow_json": json.dumps(workflow_json),
+        "workflow_api": json.dumps(workflow_api),
+    }
+
+    try:
+        await ensure_client_session()
+        async with client_session.post(
+            target_url,
+            json=request_body,
+            headers={
+                "Content-Type": "application/json",
+                "Authorization": auth_header,
+            },
+        ) as response:
+            json_data = await response.json()
+            return web.json_response(json_data, status=response.status)
+    except Exception as e:
+        return web.json_response({"error": str(e)}, status=500)
+
+
+@server.PromptServer.instance.routes.post("/comfyui-deploy/workflow/version")
+async def create_workflow_version_proxy(request):
+    data = await request.json()
+    workflow_id = data.get("workflow_id")
+    workflow = data.get("workflow")
+    workflow_api = data.get("workflow_api")
+    comment = data.get("comment", "")
+    api_url = data.get("api_url", "https://api.comfydeploy.com")
+
+    auth_header = request.headers.get("Authorization")
+
+    if not auth_header:
+        return web.json_response(
+            {"error": "Authorization header is required"}, status=401
+        )
+
+    target_url = f"{api_url}/api/workflow/{workflow_id}/version"
+
+    request_body = {
+        "workflow": workflow,
+        "workflow_api": workflow_api,
+        "comment": comment,
+    }
+
+    try:
+        await ensure_client_session()
+        async with client_session.post(
+            target_url,
+            json=request_body,
+            headers={
+                "Content-Type": "application/json",
+                "Authorization": auth_header,
+            },
+        ) as response:
+            json_data = await response.json()
+            return web.json_response(json_data, status=response.status)
+    except Exception as e:
+        return web.json_response({"error": str(e)}, status=500)
+
+
+@server.PromptServer.instance.routes.get("/comfyui-deploy/workflows")
+async def get_workflows_proxy(request):
+    api_url = request.rel_url.query.get("api_url", "https://api.comfydeploy.com")
+    search = request.rel_url.query.get("search", "")
+    limit = request.rel_url.query.get("limit", 10)
+    offset = request.rel_url.query.get("offset", 0)
+    auth_header = request.headers.get("Authorization")
+
+    if not auth_header:
+        return web.json_response(
+            {"error": "Authorization header is required"}, status=401
+        )
+
+    # Build query parameters properly
+    params = {}
+    if search:
+        params["search"] = search
+    if limit:
+        params["limit"] = limit
+    if offset:
+        params["offset"] = offset
+
+    target_url = f"{api_url}/api/workflows"
+    if params:
+        target_url += f"?{urlencode(params)}"
+
+    try:
+        await ensure_client_session()
+        async with client_session.get(
+            target_url,
+            headers={
+                "Content-Type": "application/json",
+                "Authorization": auth_header,
+            },
+        ) as response:
+            json_data = await response.json()
+            return web.json_response(json_data, status=response.status)
+    except Exception as e:
+        return web.json_response({"error": str(e)}, status=500)
+
+
+# for getting a workflow by id
+@server.PromptServer.instance.routes.get("/comfyui-deploy/workflow")
+async def get_workflow_proxy(request):
+    workflow_id = request.rel_url.query.get("workflow_id")
+    api_url = request.rel_url.query.get("api_url", "https://api.comfydeploy.com")
+    auth_header = request.headers.get("Authorization")
+
+    if not auth_header:
+        return web.json_response(
+            {"error": "Authorization header is required"}, status=401
+        )
+
+    target_url = f"{api_url}/api/workflow/{workflow_id}"
+
+    try:
+        await ensure_client_session()
+        async with client_session.get(
+            target_url, headers={"Authorization": auth_header}
+        ) as response:
+            json_data = await response.json()
+            return web.json_response(json_data, status=response.status)
+    except Exception as e:
+        return web.json_response({"error": str(e)}, status=500)

web-plugin/workflow-list.js

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