fix: lora

2024-04-24 17:00:16 -07:00
15 changed files with 286 additions and 1740 deletions
@@ -1,21 +0,0 @@
 name: Publish to Comfy registry
 on:
  workflow_dispatch:
  push:
    branches:
      - main
    paths:
      - "pyproject.toml"
 jobs:
  publish-node:
    name: Publish Custom Node to registry
    runs-on: ubuntu-latest
    steps:
      - name: Check out code
        uses: actions/checkout@v4
      - name: Publish Custom Node
        uses: Comfy-Org/publish-node-action@main
        with:
          ## Add your own personal access token to your Github Repository secrets and reference it here.
          personal_access_token: ${{ secrets.REGISTRY_ACCESS_TOKEN }}
@@ -1,25 +0,0 @@
 class ComfyUIDeployExternalBoolean:
    @classmethod    
    def INPUT_TYPES(s):
        return {
            "required": {
                "input_id": (
                    "STRING",
                    {"multiline": False, "default": "input_bool"},
                ),
                "default_value": ("BOOLEAN", {"default": False})
            }
        }
    RETURN_TYPES = ("BOOLEAN",)
    RETURN_NAMES = ("bool_value",)
    FUNCTION = "run"
    def run(self, input_id, default_value=None):
        print(f"Node '{input_id}' processing with switch set to {default_value}")
        return [default_value]
 NODE_CLASS_MAPPINGS = {"ComfyUIDeployExternalBoolean": ComfyUIDeployExternalBoolean}
 NODE_DISPLAY_NAME_MAPPINGS = {"ComfyUIDeployExternalBoolean": "External Boolean (ComfyUI Deploy)"}
@@ -5,12 +5,6 @@ import torch
 import folder_paths
 from tqdm import tqdm
 class AnyType(str):
    def __ne__(self, __value: object) -> bool:
        return False
 WILDCARD = AnyType("*")
 class ComfyUIDeployExternalCheckpoint:
    @classmethod
    def INPUT_TYPES(s):
@@ -26,7 +20,7 @@ class ComfyUIDeployExternalCheckpoint:
            }
        }
-    RETURN_TYPES = (WILDCARD,)
+    RETURN_TYPES = (folder_paths.get_filename_list("checkpoints"),)
    RETURN_NAMES = ("path",)
    FUNCTION = "run"
@@ -4,11 +4,6 @@ import numpy as np
 import torch
 import folder_paths
 class AnyType(str):
    def __ne__(self, __value: object) -> bool:
        return False
 WILDCARD = AnyType("*")
 class ComfyUIDeployExternalLora:
    @classmethod
@@ -21,11 +16,11 @@ class ComfyUIDeployExternalLora:
                ),
            },
            "optional": {
-                "default_lora_name": (folder_paths.get_filename_list("loras"),),
+                "default_lora_name": (folder_paths.get_filename_list("loras"), ),
-            },
+            }
        }
-    RETURN_TYPES = (WILDCARD,)
+    RETURN_TYPES = (folder_paths.get_filename_list("loras"),)
    RETURN_NAMES = ("path",)
    FUNCTION = "run"
@@ -37,29 +32,27 @@ class ComfyUIDeployExternalLora:
        import os
        import uuid
-        if default_lora_name.startswith("http"):
+        print('external lora using')
        print("input id: ", input_id)
        print("default lora : ", default_lora_name)
        if input_id:
            if input_id.startswith('http'):
                unique_filename = str(uuid.uuid4()) + ".safetensors"
                print(unique_filename)
                print(folder_paths.folder_names_and_paths["loras"][0][0])
-            destination_path = os.path.join(
+                destination_path = os.path.join(folder_paths.folder_names_and_paths["loras"][0][0], unique_filename)
                folder_paths.folder_names_and_paths["loras"][0][0], unique_filename
            )
                print(destination_path)
                print("Downloading external lora - " + input_id + " to " + destination_path)
-            response = requests.get(
+                response = requests.get(input_id, headers={'User-Agent': 'Mozilla/5.0'}, allow_redirects=True)
-                input_id,
+                with open(destination_path, 'wb') as out_file:
                headers={"User-Agent": "Mozilla/5.0"},
                allow_redirects=True,
            )
            with open(destination_path, "wb") as out_file:
                    out_file.write(response.content)
                return (unique_filename,)
            else:
-            print(f"using lora: {default_lora_name}")
+                return (input_id,)
        return (default_lora_name,)
 NODE_CLASS_MAPPINGS = {"ComfyUIDeployExternalLora": ComfyUIDeployExternalLora}
-NODE_DISPLAY_NAME_MAPPINGS = {
+NODE_DISPLAY_NAME_MAPPINGS = {"ComfyUIDeployExternalLora": "External Lora (ComfyUI Deploy)"}
    "ComfyUIDeployExternalLora": "External Lora (ComfyUI Deploy)"
 }
@@ -29,7 +29,7 @@ class ComfyUIDeployExternalNumberInt:
    CATEGORY = "number"
    def run(self, input_id, default_value=None):
-        if not input_id or (isinstance(input_id, str) and not input_id.strip().isdigit()):
+        if not input_id or not input_id.strip().isdigit():
            return [default_value]
        return [int(input_id)]
@@ -1,48 +0,0 @@
 class ComfyUIDeployExternalNumberSlider:
    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "input_id": (
                    "STRING",
                    {"multiline": False, "default": "input_number_slider"},
                ),
            },
            "optional": {
                "default_value": (
                    "FLOAT",
                    {"multiline": True, "display": "number", "default": 0.5, "step": 0.01},
                ),
                "min_value": (
                    "FLOAT",
                    {"multiline": True, "display": "number", "default": 0, "step": 0.01},
                ),
                "max_value": (
                    "FLOAT",
                    {"multiline": True, "display": "number", "default": 1, "step": 0.01},
                ),
            }
        }
    RETURN_TYPES = ("FLOAT",)
    RETURN_NAMES = ("value",)
    FUNCTION = "run"
    CATEGORY = "number"
    def run(self, input_id, default_value=None, min_value=0, max_value=1):
        try:
            float_value = float(input_id)
            if min_value <= float_value <= max_value:
                print("my number", float_value)
                return [float_value]
            else:
                print("Number out of range. Returning default value:", default_value)
                return [default_value]
        except ValueError:
            print("Invalid input. Returning default value:", default_value)
            return [default_value]
 NODE_CLASS_MAPPINGS = {"ComfyUIDeployExternalNumberSlider": ComfyUIDeployExternalNumberSlider}
 NODE_DISPLAY_NAME_MAPPINGS = {"ComfyUIDeployExternalNumberSlider": "External Number Slider (ComfyUI Deploy)"}
@@ -1,78 +0,0 @@
 import os
 import folder_paths
 import uuid
 from tqdm import tqdm
 video_extensions = ["webm", "mp4", "mkv", "gif"]
 class ComfyUIDeployExternalVideo:
    @classmethod
    def INPUT_TYPES(s):
        input_dir = folder_paths.get_input_directory()
        files = []
        for f in os.listdir(input_dir):
            if os.path.isfile(os.path.join(input_dir, f)):
                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"},
                ),
            },
            "optional": {
                "meta_batch": ("VHS_BatchManager",),
                "default_value": (sorted(files),),
            },
        }
    CATEGORY = "Video Helper Suite 🎥🅥🅗🅢"
    RETURN_TYPES = ("STRING",)
    RETURN_NAMES = ("video")
    FUNCTION = "load_video"
    def load_video(self, input_id, default_value):
        input_dir = folder_paths.get_input_directory()
        if input_id.startswith("http"):
            import requests
            print("Fetching video from URL: ", input_id)
            response = requests.get(input_id, stream=True)
            file_size = int(response.headers.get("Content-Length", 0))
            file_extension = input_id.split(".")[-1].split("?")[
                0
            ]  # Extract extension and handle URLs with parameters
            if file_extension not in video_extensions:
                file_extension = ".mp4"
            unique_filename = str(uuid.uuid4()) + "." + file_extension
            video_path = os.path.join(input_dir, unique_filename)
            chunk_size = 1024  # 1 Kibibyte
            num_bars = int(file_size / chunk_size)
            with open(video_path, "wb") as out_file:
                for chunk in tqdm(
                    response.iter_content(chunk_size=chunk_size),
                    total=num_bars,
                    unit="KB",
                    desc="Downloading",
                    leave=True,
                ):
                    out_file.write(chunk)
        else:
            video_path = os.path.abspath(os.path.join(input_dir, default_value))
        return (video_path,)
 NODE_CLASS_MAPPINGS = {"ComfyUIDeployExternalVid": ComfyUIDeployExternalVideo}
 NODE_DISPLAY_NAME_MAPPINGS = {
    "ComfyUIDeployExternalVid": "External Video (ComfyUI Deploy) path"
 }
@@ -1,855 +0,0 @@
 # credit goes to https://github.com/Kosinkadink/ComfyUI-VideoHelperSuite
 # Intended to work with https://github.com/NicholasKao1029/ComfyUI-VideoHelperSuite/tree/main
 import os
 import itertools
 import numpy as np
 import torch
 from typing import Union
 from torch import Tensor
 import cv2
 import psutil
 from collections.abc import Mapping
 import folder_paths
 from comfy.utils import common_upscale
 ### Utils
 import hashlib
 from typing import Iterable
 import shutil
 import subprocess
 import re
 import uuid
 import server
 from tqdm import tqdm
 BIGMIN = -(2**53 - 1)
 BIGMAX = 2**53 - 1
 DIMMAX = 8192
 def ffmpeg_suitability(path):
    try:
        version = subprocess.run(
            [path, "-version"], check=True, capture_output=True
        ).stdout.decode("utf-8")
    except:
        return 0
    score = 0
    # rough layout of the importance of various features
    simple_criterion = [
        ("libvpx", 20),
        ("264", 10),
        ("265", 3),
        ("svtav1", 5),
        ("libopus", 1),
    ]
    for criterion in simple_criterion:
        if version.find(criterion[0]) >= 0:
            score += criterion[1]
    # obtain rough compile year from copyright information
    copyright_index = version.find("2000-2")
    if copyright_index >= 0:
        copyright_year = version[copyright_index + 6 : copyright_index + 9]
        if copyright_year.isnumeric():
            score += int(copyright_year)
    return score
 if "VHS_FORCE_FFMPEG_PATH" in os.environ:
    ffmpeg_path = os.environ.get("VHS_FORCE_FFMPEG_PATH")
 else:
    ffmpeg_paths = []
    try:
        from imageio_ffmpeg import get_ffmpeg_exe
        imageio_ffmpeg_path = get_ffmpeg_exe()
        ffmpeg_paths.append(imageio_ffmpeg_path)
    except:
        if "VHS_USE_IMAGEIO_FFMPEG" in os.environ:
            raise
    if "VHS_USE_IMAGEIO_FFMPEG" in os.environ:
        ffmpeg_path = imageio_ffmpeg_path
    else:
        system_ffmpeg = shutil.which("ffmpeg")
        if system_ffmpeg is not None:
            ffmpeg_paths.append(system_ffmpeg)
        if os.path.isfile("ffmpeg"):
            ffmpeg_paths.append(os.path.abspath("ffmpeg"))
        if os.path.isfile("ffmpeg.exe"):
            ffmpeg_paths.append(os.path.abspath("ffmpeg.exe"))
        if len(ffmpeg_paths) == 0:
            ffmpeg_path = None
        elif len(ffmpeg_paths) == 1:
            # Evaluation of suitability isn't required, can take sole option
            # to reduce startup time
            ffmpeg_path = ffmpeg_paths[0]
        else:
            ffmpeg_path = max(ffmpeg_paths, key=ffmpeg_suitability)
 gifski_path = os.environ.get("VHS_GIFSKI", None)
 if gifski_path is None:
    gifski_path = os.environ.get("JOV_GIFSKI", None)
    if gifski_path is None:
        gifski_path = shutil.which("gifski")
 def is_safe_path(path):
    if "VHS_STRICT_PATHS" not in os.environ:
        return True
    basedir = os.path.abspath(".")
    try:
        common_path = os.path.commonpath([basedir, path])
    except:
        # Different drive on windows
        return False
    return common_path == basedir
 def get_sorted_dir_files_from_directory(
    directory: str,
    skip_first_images: int = 0,
    select_every_nth: int = 1,
    extensions: Iterable = None,
 ):
    directory = strip_path(directory)
    dir_files = os.listdir(directory)
    dir_files = sorted(dir_files)
    dir_files = [os.path.join(directory, x) for x in dir_files]
    dir_files = list(filter(lambda filepath: os.path.isfile(filepath), dir_files))
    # filter by extension, if needed
    if extensions is not None:
        extensions = list(extensions)
        new_dir_files = []
        for filepath in dir_files:
            ext = "." + filepath.split(".")[-1]
            if ext.lower() in extensions:
                new_dir_files.append(filepath)
        dir_files = new_dir_files
    # start at skip_first_images
    dir_files = dir_files[skip_first_images:]
    dir_files = dir_files[0::select_every_nth]
    return dir_files
 # modified from https://stackoverflow.com/questions/22058048/hashing-a-file-in-python
 def calculate_file_hash(filename: str, hash_every_n: int = 1):
    # Larger video files were taking >.5 seconds to hash even when cached,
    # so instead the modified time from the filesystem is used as a hash
    h = hashlib.sha256()
    h.update(filename.encode())
    h.update(str(os.path.getmtime(filename)).encode())
    return h.hexdigest()
 prompt_queue = server.PromptServer.instance.prompt_queue
 def requeue_workflow_unchecked():
    """Requeues the current workflow without checking for multiple requeues"""
    currently_running = prompt_queue.currently_running
    (_, _, prompt, extra_data, outputs_to_execute) = next(
        iter(currently_running.values())
    )
    # Ensure batch_managers are marked stale
    prompt = prompt.copy()
    for uid in prompt:
        if prompt[uid]["class_type"] == "VHS_BatchManager":
            prompt[uid]["inputs"]["requeue"] = (
                prompt[uid]["inputs"].get("requeue", 0) + 1
            )
    # execution.py has guards for concurrency, but server doesn't.
    # TODO: Check that this won't be an issue
    number = -server.PromptServer.instance.number
    server.PromptServer.instance.number += 1
    prompt_id = str(server.uuid.uuid4())
    prompt_queue.put((number, prompt_id, prompt, extra_data, outputs_to_execute))
 requeue_guard = [None, 0, 0, {}]
 def requeue_workflow(requeue_required=(-1, True)):
    assert len(prompt_queue.currently_running) == 1
    global requeue_guard
    (run_number, _, prompt, _, _) = next(iter(prompt_queue.currently_running.values()))
    if requeue_guard[0] != run_number:
        # Calculate a count of how many outputs are managed by a batch manager
        managed_outputs = 0
        for bm_uid in prompt:
            if prompt[bm_uid]["class_type"] == "VHS_BatchManager":
                for output_uid in prompt:
                    if prompt[output_uid]["class_type"] in ["VHS_VideoCombine"]:
                        for inp in prompt[output_uid]["inputs"].values():
                            if inp == [bm_uid, 0]:
                                managed_outputs += 1
        requeue_guard = [run_number, 0, managed_outputs, {}]
    requeue_guard[1] = requeue_guard[1] + 1
    requeue_guard[3][requeue_required[0]] = requeue_required[1]
    if requeue_guard[1] == requeue_guard[2] and max(requeue_guard[3].values()):
        requeue_workflow_unchecked()
 def get_audio(file, start_time=0, duration=0):
    args = [ffmpeg_path, "-i", file]
    if start_time > 0:
        args += ["-ss", str(start_time)]
    if duration > 0:
        args += ["-t", str(duration)]
    try:
        # TODO: scan for sample rate and maintain
        res = subprocess.run(
            args + ["-f", "f32le", "-"], capture_output=True, check=True
        )
        audio = torch.frombuffer(bytearray(res.stdout), dtype=torch.float32)
        match = re.search(", (\\d+) Hz, (\\w+), ", res.stderr.decode("utf-8"))
    except subprocess.CalledProcessError as e:
        raise Exception(
            f"VHS failed to extract audio from {file}:\n" + e.stderr.decode("utf-8")
        )
    if match:
        ar = int(match.group(1))
        # NOTE: Just throwing an error for other channel types right now
        # Will deal with issues if they come
        ac = {"mono": 1, "stereo": 2}[match.group(2)]
    else:
        ar = 44100
        ac = 2
    audio = audio.reshape((-1, ac)).transpose(0, 1).unsqueeze(0)
    return {"waveform": audio, "sample_rate": ar}
 class LazyAudioMap(Mapping):
    def __init__(self, file, start_time, duration):
        self.file = file
        self.start_time = start_time
        self.duration = duration
        self._dict = None
    def __getitem__(self, key):
        if self._dict is None:
            self._dict = get_audio(self.file, self.start_time, self.duration)
        return self._dict[key]
    def __iter__(self):
        if self._dict is None:
            self._dict = get_audio(self.file, self.start_time, self.duration)
        return iter(self._dict)
    def __len__(self):
        if self._dict is None:
            self._dict = get_audio(self.file, self.start_time, self.duration)
        return len(self._dict)
 def lazy_get_audio(file, start_time=0, duration=0):
    return LazyAudioMap(file, start_time, duration)
 def lazy_eval(func):
    class Cache:
        def __init__(self, func):
            self.res = None
            self.func = func
        def get(self):
            if self.res is None:
                self.res = self.func()
            return self.res
    cache = Cache(func)
    return lambda: cache.get()
 def is_url(url):
    return url.split("://")[0] in ["http", "https"]
 def validate_sequence(path):
    # Check if path is a valid ffmpeg sequence that points to at least one file
    (path, file) = os.path.split(path)
    if not os.path.isdir(path):
        return False
    match = re.search("%0?\d+d", file)
    if not match:
        return False
    seq = match.group()
    if seq == "%d":
        seq = "\\\\d+"
    else:
        seq = "\\\\d{%s}" % seq[1:-1]
    file_matcher = re.compile(re.sub("%0?\d+d", seq, file))
    for file in os.listdir(path):
        if file_matcher.fullmatch(file):
            return True
    return False
 def strip_path(path):
    # This leaves whitespace inside quotes and only a single "
    # thus ' ""test"' -> '"test'
    # consider path.strip(string.whitespace+"\"")
    # or weightier re.fullmatch("[\\s\"]*(.+?)[\\s\"]*", path).group(1)
    path = path.strip()
    if path.startswith('"'):
        path = path[1:]
    if path.endswith('"'):
        path = path[:-1]
    return path
 def hash_path(path):
    if path is None:
        return "input"
    if is_url(path):
        return "url"
    return calculate_file_hash(path.strip('"'))
 def validate_path(path, allow_none=False, allow_url=True):
    if path is None:
        return allow_none
    if is_url(path):
        # Probably not feasible to check if url resolves here
        return True if allow_url else "URLs are unsupported for this path"
    if not os.path.isfile(path.strip('"')):
        return "Invalid file path: {}".format(path)
    return True
 ### Utils
 video_extensions = ["webm", "mp4", "mkv", "gif"]
 def is_gif(filename) -> bool:
    file_parts = filename.split(".")
    return len(file_parts) > 1 and file_parts[-1] == "gif"
 def target_size(
    width, height, force_size, custom_width, custom_height
 ) -> tuple[int, int]:
    if force_size == "Custom":
        return (custom_width, custom_height)
    elif force_size == "Custom Height":
        force_size = "?x" + str(custom_height)
    elif force_size == "Custom Width":
        force_size = str(custom_width) + "x?"
    if force_size != "Disabled":
        force_size = force_size.split("x")
        if force_size[0] == "?":
            width = (width * int(force_size[1])) // height
            # Limit to a multple of 8 for latent conversion
            width = int(width) + 4 & ~7
            height = int(force_size[1])
        elif force_size[1] == "?":
            height = (height * int(force_size[0])) // width
            height = int(height) + 4 & ~7
            width = int(force_size[0])
        else:
            width = int(force_size[0])
            height = int(force_size[1])
    return (width, height)
 def validate_index(
    index: int,
    length: int = 0,
    is_range: bool = False,
    allow_negative=False,
    allow_missing=False,
 ) -> int:
    # if part of range, do nothing
    if is_range:
        return index
    # otherwise, validate index
    # validate not out of range - only when latent_count is passed in
    if length > 0 and index > length - 1 and not allow_missing:
        raise IndexError(f"Index '{index}' out of range for {length} item(s).")
    # if negative, validate not out of range
    if index < 0:
        if not allow_negative:
            raise IndexError(f"Negative indeces not allowed, but was '{index}'.")
        conv_index = length + index
        if conv_index < 0 and not allow_missing:
            raise IndexError(
                f"Index '{index}', converted to '{conv_index}' out of range for {length} item(s)."
            )
        index = conv_index
    return index
 def convert_to_index_int(
    raw_index: str,
    length: int = 0,
    is_range: bool = False,
    allow_negative=False,
    allow_missing=False,
 ) -> int:
    try:
        return validate_index(
            int(raw_index),
            length=length,
            is_range=is_range,
            allow_negative=allow_negative,
            allow_missing=allow_missing,
        )
    except ValueError as e:
        raise ValueError(f"Index '{raw_index}' must be an integer.", e)
 def convert_str_to_indexes(
    indexes_str: str, length: int = 0, allow_missing=False
 ) -> list[int]:
    if not indexes_str:
        return []
    int_indexes = list(range(0, length))
    allow_negative = length > 0
    chosen_indexes = []
    # parse string - allow positive ints, negative ints, and ranges separated by ':'
    groups = indexes_str.split(",")
    groups = [g.strip() for g in groups]
    for g in groups:
        # parse range of indeces (e.g. 2:16)
        if ":" in g:
            index_range = g.split(":", 2)
            index_range = [r.strip() for r in index_range]
            start_index = index_range[0]
            if len(start_index) > 0:
                start_index = convert_to_index_int(
                    start_index,
                    length=length,
                    is_range=True,
                    allow_negative=allow_negative,
                    allow_missing=allow_missing,
                )
            else:
                start_index = 0
            end_index = index_range[1]
            if len(end_index) > 0:
                end_index = convert_to_index_int(
                    end_index,
                    length=length,
                    is_range=True,
                    allow_negative=allow_negative,
                    allow_missing=allow_missing,
                )
            else:
                end_index = length
            # support step as well, to allow things like reversing, every-other, etc.
            step = 1
            if len(index_range) > 2:
                step = index_range[2]
                if len(step) > 0:
                    step = convert_to_index_int(
                        step,
                        length=length,
                        is_range=True,
                        allow_negative=True,
                        allow_missing=True,
                    )
                else:
                    step = 1
            # if latents were passed in, base indeces on known latent count
            if len(int_indexes) > 0:
                chosen_indexes.extend(int_indexes[start_index:end_index][::step])
            # otherwise, assume indeces are valid
            else:
                chosen_indexes.extend(list(range(start_index, end_index, step)))
        # parse individual indeces
        else:
            chosen_indexes.append(
                convert_to_index_int(
                    g,
                    length=length,
                    allow_negative=allow_negative,
                    allow_missing=allow_missing,
                )
            )
    return chosen_indexes
 def select_indexes(input_obj: Union[Tensor, list], idxs: list):
    if type(input_obj) == Tensor:
        return input_obj[idxs]
    else:
        return [input_obj[i] for i in idxs]
 def select_indexes_from_str(
    input_obj: Union[Tensor, list], indexes: str, err_if_missing=True, err_if_empty=True
 ):
    real_idxs = convert_str_to_indexes(
        indexes, len(input_obj), allow_missing=not err_if_missing
    )
    if err_if_empty and len(real_idxs) == 0:
        raise Exception(f"Nothing was selected based on indexes found in '{indexes}'.")
    return select_indexes(input_obj, real_idxs)
 ###
 def cv_frame_generator(
    video,
    force_rate,
    frame_load_cap,
    skip_first_frames,
    select_every_nth,
    meta_batch=None,
    unique_id=None,
 ):
    video_cap = cv2.VideoCapture(strip_path(video))
    if not video_cap.isOpened():
        raise ValueError(f"{video} could not be loaded with cv.")
    pbar = None
    # extract video metadata
    fps = video_cap.get(cv2.CAP_PROP_FPS)
    width = int(video_cap.get(cv2.CAP_PROP_FRAME_WIDTH))
    height = int(video_cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
    total_frames = int(video_cap.get(cv2.CAP_PROP_FRAME_COUNT))
    duration = total_frames / fps
    # set video_cap to look at start_index frame
    total_frame_count = 0
    total_frames_evaluated = -1
    frames_added = 0
    base_frame_time = 1 / fps
    prev_frame = None
    if force_rate == 0:
        target_frame_time = base_frame_time
    else:
        target_frame_time = 1 / force_rate
    yield (width, height, fps, duration, total_frames, target_frame_time)
    if meta_batch is not None:
        yield min(frame_load_cap, total_frames)
    time_offset = target_frame_time - base_frame_time
    while video_cap.isOpened():
        if time_offset < target_frame_time:
            is_returned = video_cap.grab()
            # if didn't return frame, video has ended
            if not is_returned:
                break
            time_offset += base_frame_time
        if time_offset < target_frame_time:
            continue
        time_offset -= target_frame_time
        # if not at start_index, skip doing anything with frame
        total_frame_count += 1
        if total_frame_count <= skip_first_frames:
            continue
        else:
            total_frames_evaluated += 1
        # if should not be selected, skip doing anything with frame
        if total_frames_evaluated % select_every_nth != 0:
            continue
        # opencv loads images in BGR format (yuck), so need to convert to RGB for ComfyUI use
        # follow up: can videos ever have an alpha channel?
        # To my testing: No. opencv has no support for alpha
        unused, frame = video_cap.retrieve()
        frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
        # convert frame to comfyui's expected format
        # TODO: frame contains no exif information. Check if opencv2 has already applied
        frame = np.array(frame, dtype=np.float32)
        torch.from_numpy(frame).div_(255)
        if prev_frame is not None:
            inp = yield prev_frame
            if inp is not None:
                # ensure the finally block is called
                return
        prev_frame = frame
        frames_added += 1
        if pbar is not None:
            pbar.update_absolute(frames_added, frame_load_cap)
        # if cap exists and we've reached it, stop processing frames
        if frame_load_cap > 0 and frames_added >= frame_load_cap:
            break
    if meta_batch is not None:
        meta_batch.inputs.pop(unique_id)
        meta_batch.has_closed_inputs = True
    if prev_frame is not None:
        yield prev_frame
 def batched(it, n):
    while batch := tuple(itertools.islice(it, n)):
        yield batch
 def batched_vae_encode(images, vae, frames_per_batch):
    for batch in batched(images, frames_per_batch):
        image_batch = torch.from_numpy(np.array(batch))
        yield from vae.encode(image_batch).numpy()
 def load_video_cv(
    video: str,
    force_rate: int,
    force_size: str,
    custom_width: int,
    custom_height: int,
    frame_load_cap: int,
    skip_first_frames: int,
    select_every_nth: int,
    meta_batch=None,
    unique_id=None,
    memory_limit_mb=None,
    vae=None,
 ):
    if meta_batch is None or unique_id not in meta_batch.inputs:
        gen = cv_frame_generator(
            video,
            force_rate,
            frame_load_cap,
            skip_first_frames,
            select_every_nth,
            meta_batch,
            unique_id,
        )
        (width, height, fps, duration, total_frames, target_frame_time) = next(gen)
        if meta_batch is not None:
            meta_batch.inputs[unique_id] = (
                gen,
                width,
                height,
                fps,
                duration,
                total_frames,
                target_frame_time,
            )
            meta_batch.total_frames = min(meta_batch.total_frames, next(gen))
    else:
        (gen, width, height, fps, duration, total_frames, target_frame_time) = (
            meta_batch.inputs[unique_id]
        )
    memory_limit = None
    if memory_limit_mb is not None:
        memory_limit *= 2**20
    else:
        # TODO: verify if garbage collection should be performed here.
        # leaves ~128 MB unreserved for safety
        try:
            memory_limit = (
                psutil.virtual_memory().available + psutil.swap_memory().free
            ) - 2**27
        except:
            print(
                "Failed to calculate available memory. Memory load limit has been disabled"
            )
    if memory_limit is not None:
        if vae is not None:
            # space required to load as f32, exist as latent with wiggle room, decode to f32
            max_loadable_frames = int(
                memory_limit // (width * height * 3 * (4 + 4 + 1 / 10))
            )
        else:
            # TODO: use better estimate for when vae is not None
            # Consider completely ignoring for load_latent case?
            max_loadable_frames = int(memory_limit // (width * height * 3 * (0.1)))
        if meta_batch is not None:
            if meta_batch.frames_per_batch > max_loadable_frames:
                raise RuntimeError(
                    f"Meta Batch set to {meta_batch.frames_per_batch} frames but only {max_loadable_frames} can fit in memory"
                )
            gen = itertools.islice(gen, meta_batch.frames_per_batch)
        else:
            original_gen = gen
            gen = itertools.islice(gen, max_loadable_frames)
    downscale_ratio = getattr(vae, "downscale_ratio", 8)
    frames_per_batch = (1920 * 1080 * 16) // (width * height) or 1
    if force_size != "Disabled" or vae is not None:
        new_size = target_size(
            width, height, force_size, custom_width, custom_height, downscale_ratio
        )
        if new_size[0] != width or new_size[1] != height:
            def rescale(frame):
                s = torch.from_numpy(
                    np.fromiter(frame, np.dtype((np.float32, (height, width, 3))))
                )
                s = s.movedim(-1, 1)
                s = common_upscale(s, new_size[0], new_size[1], "lanczos", "center")
                return s.movedim(1, -1).numpy()
            gen = itertools.chain.from_iterable(
                map(rescale, batched(gen, frames_per_batch))
            )
    else:
        new_size = width, height
    if vae is not None:
        gen = batched_vae_encode(gen, vae, frames_per_batch)
        vw, vh = new_size[0] // downscale_ratio, new_size[1] // downscale_ratio
        images = torch.from_numpy(np.fromiter(gen, np.dtype((np.float32, (4, vh, vw)))))
    else:
        # Some minor wizardry to eliminate a copy and reduce max memory by a factor of ~2
        images = torch.from_numpy(
            np.fromiter(gen, np.dtype((np.float32, (new_size[1], new_size[0], 3))))
        )
    if meta_batch is None and memory_limit is not None:
        try:
            next(original_gen)
            raise RuntimeError(
                f"Memory limit hit after loading {len(images)} frames. Stopping execution."
            )
        except StopIteration:
            pass
    if len(images) == 0:
        raise RuntimeError("No frames generated")
    # Setup lambda for lazy audio capture
    audio = lazy_get_audio(
        video,
        skip_first_frames * target_frame_time,
        frame_load_cap * target_frame_time * select_every_nth,
    )
    # Adjust target_frame_time for select_every_nth
    target_frame_time *= select_every_nth
    video_info = {
        "source_fps": fps,
        "source_frame_count": total_frames,
        "source_duration": duration,
        "source_width": width,
        "source_height": height,
        "loaded_fps": 1 / target_frame_time,
        "loaded_frame_count": len(images),
        "loaded_duration": len(images) * target_frame_time,
        "loaded_width": new_size[0],
        "loaded_height": new_size[1],
    }
    if vae is None:
        return (images, len(images), audio, video_info, None)
    else:
        return (None, len(images), audio, video_info, {"samples": images})
 # modeled after Video upload node
 class ComfyUIDeployExternalVideo:
    @classmethod
    def INPUT_TYPES(s):
        input_dir = folder_paths.get_input_directory()
        files = []
        for f in os.listdir(input_dir):
            if os.path.isfile(os.path.join(input_dir, f)):
                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_value": (sorted(files),),
                },
                "hidden": {
                    "unique_id": "UNIQUE_ID"
                },
                }
    CATEGORY = "Video Helper Suite 🎥🅥🅗🅢"
    RETURN_TYPES = ("IMAGE", "INT", "AUDIO", "VHS_VIDEOINFO", "LATENT")
    RETURN_NAMES = (
        "IMAGE",
        "frame_count",
        "audio",
        "video_info",
        "LATENT",
    )
    FUNCTION = "load_video"
    def load_video(self, **kwargs):
        input_id = kwargs.get("input_id")
        force_rate = kwargs.get("force_rate")
        force_size = kwargs.get("force_size", "Disabled")
        custom_width = kwargs.get("custom_width")
        custom_height = kwargs.get("custom_height")
        frame_load_cap = kwargs.get("frame_load_cap")
        skip_first_frames = kwargs.get("skip_first_frames")
        select_every_nth = kwargs.get("select_every_nth")
        meta_batch = kwargs.get("meta_batch")
        unique_id = kwargs.get("unique_id")
        video = kwargs.get("default_value")
        video_path = folder_paths.get_annotated_filepath(video.strip('"'))
        input_dir = folder_paths.get_input_directory()
        if input_id.startswith("http"):
            import requests
            print("Fetching video from URL: ", input_id)
            response = requests.get(input_id, stream=True)
            file_size = int(response.headers.get("Content-Length", 0))
            file_extension = input_id.split(".")[-1].split("?")[
                0
            ]  # Extract extension and handle URLs with parameters
            if file_extension not in video_extensions:
                file_extension = ".mp4"
            unique_filename = str(uuid.uuid4()) + "." + file_extension
            video_path = os.path.join(input_dir, unique_filename)
            chunk_size = 1024  # 1 Kibibyte
            num_bars = int(file_size / chunk_size)
            with open(video_path, "wb") as out_file:
                for chunk in tqdm(
                    response.iter_content(chunk_size=chunk_size),
                    total=num_bars,
                    unit="KB",
                    desc="Downloading",
                    leave=True,
                ):
                    out_file.write(chunk)
        print("video path: ", video_path)
        return load_video_cv(
            video=video_path,
            force_rate=force_rate,
            force_size=force_size,
            custom_width=custom_width,
            custom_height=custom_height,
            frame_load_cap=frame_load_cap,
            skip_first_frames=skip_first_frames,
            select_every_nth=select_every_nth,
            meta_batch=meta_batch,
            unique_id=unique_id,
        )
    @classmethod
    def IS_CHANGED(s, video, **kwargs):
        image_path = folder_paths.get_annotated_filepath(video)
        return calculate_file_hash(image_path)
 NODE_CLASS_MAPPINGS = {"ComfyUIDeployExternalVideo": ComfyUIDeployExternalVideo}
 NODE_DISPLAY_NAME_MAPPINGS = {
    "ComfyUIDeployExternalVideo": "External Video (ComfyUI Deploy x VHS)"
 }
@@ -18,146 +18,28 @@ import threading
 import hashlib
 import aiohttp
 import aiofiles
-from typing import Dict, List, Union, Any, Optional
+from typing import List, Union, Any, Optional
 from PIL import Image
 import copy
 import struct
 from aiohttp import ClientError
 import atexit
 # Global session
 client_session = None
 # def create_client_session():
 #     global client_session
 #     if client_session is None:
 #         client_session = aiohttp.ClientSession()
 async def ensure_client_session():
    global client_session
    if client_session is None:
        client_session = aiohttp.ClientSession()
 async def cleanup():
    global client_session
    if client_session:
        await client_session.close()
 def exit_handler():
    print("Exiting the application. Initiating cleanup...")
    loop = asyncio.get_event_loop()
    loop.run_until_complete(cleanup())
 atexit.register(exit_handler)
 max_retries = int(os.environ.get('MAX_RETRIES', '3'))
 retry_delay_multiplier = float(os.environ.get('RETRY_DELAY_MULTIPLIER', '2'))
 print(f"max_retries: {max_retries}, retry_delay_multiplier: {retry_delay_multiplier}")
 async def async_request_with_retry(method, url, **kwargs):
    global client_session
    await ensure_client_session()
    retry_delay = 1  # Start with 1 second delay
    for attempt in range(max_retries):
        try:
            async with client_session.request(method, url, **kwargs) as response:
                response.raise_for_status()
                return response
        except ClientError as e:
            if attempt == max_retries - 1:
                logger.error(f"Request failed after {max_retries} attempts: {e}")
                # raise
            logger.warning(f"Request failed (attempt {attempt + 1}/{max_retries}): {e}")
            await asyncio.sleep(retry_delay)
            retry_delay *= retry_delay_multiplier  # Exponential backoff
 from logging import basicConfig, getLogger
 # Check for an environment variable to enable/disable Logfire
 use_logfire = os.environ.get('USE_LOGFIRE', 'false').lower() == 'true'
 if use_logfire:
    try:
        import logfire
        logfire.configure(
            send_to_logfire="if-token-present"
        )
        logger = logfire
    except ImportError:
        print("Logfire not installed or disabled. Using standard Python logger.")
        use_logfire = False
 if not use_logfire:
    # Use a standard Python logger when Logfire is disabled or not available
    logger = getLogger("comfy-deploy")
    basicConfig(level="INFO")  # You can adjust the logging level as needed
 def log(level, message, **kwargs):
    if use_logfire:
        getattr(logger, level)(message, **kwargs)
    else:
        getattr(logger, level)(f"{message} {kwargs}")
 # For a span, you might need to create a context manager
 from contextlib import contextmanager
@contextmanager
 def log_span(name):
    if use_logfire:
        with logger.span(name):
            yield
    # else:
    #     logger.info(f"Start: {name}")
    #     yield
    #     logger.info(f"End: {name}")
 from globals import StreamingPrompt, Status, sockets, SimplePrompt, streaming_prompt_metadata, prompt_metadata
 class EventEmitter:
    def __init__(self):
        self.listeners = {}
    def on(self, event, listener):
        if event not in self.listeners:
            self.listeners[event] = []
        self.listeners[event].append(listener)
    def off(self, event, listener):
        if event in self.listeners:
            self.listeners[event].remove(listener)
            if not self.listeners[event]:
                del self.listeners[event]
    def emit(self, event, *args, **kwargs):
        if event in self.listeners:
            for listener in self.listeners[event]:
                listener(*args, **kwargs)
 # Create a global event emitter instance
 event_emitter = EventEmitter()
 api = None
 api_task = None
 cd_enable_log = os.environ.get('CD_ENABLE_LOG', 'false').lower() == 'true'
 cd_enable_run_log = os.environ.get('CD_ENABLE_RUN_LOG', 'false').lower() == 'true'
 bypass_upload = os.environ.get('CD_BYPASS_UPLOAD', 'false').lower() == 'true'
 logger.info(f"CD_BYPASS_UPLOAD {bypass_upload}")
 def clear_current_prompt(sid):
    prompt_server = server.PromptServer.instance
    to_delete = list(streaming_prompt_metadata[sid].running_prompt_ids)  # Convert set to list
-    logger.info(f"clearing out prompt: {to_delete}")
+    print("clearning out prompt: ", to_delete)
    for id_to_delete in to_delete:
        delete_func = lambda a: a[1] == id_to_delete
        prompt_server.prompt_queue.delete_queue_item(delete_func)
-        logger.info(f"deleted prompt: {id_to_delete}, remaining tasks: {prompt_server.prompt_queue.get_tasks_remaining()}")
+        print("deleted prompt: ", id_to_delete, prompt_server.prompt_queue.get_tasks_remaining())
    streaming_prompt_metadata[sid].running_prompt_ids.clear()
@@ -198,7 +80,7 @@ def post_prompt(json_data):
            }
            return response
        else:
-            logger.info("invalid prompt:", valid[1])
+            print("invalid prompt:", valid[1])
            return {"error": valid[1], "node_errors": valid[3]}
    else:
        return {"error": "no prompt", "node_errors": []}
@@ -236,7 +118,7 @@ def apply_inputs_to_workflow(workflow_api: Any, inputs: Any, sid: str = None):
                if (value["class_type"] == "ComfyDeployWebscoketImageInput"):
                    value['inputs']["client_id"] = sid
-            if "input_id" in value['inputs'] and inputs is not None and value['inputs']['input_id'] in inputs:
+            if "input_id" in value['inputs'] and value['inputs']['input_id'] in inputs:
                new_value = inputs[value['inputs']['input_id']]
                # Lets skip it if its an image
@@ -256,15 +138,6 @@ 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"] == "ComfyUIDeployExternalLora":
                    value["inputs"]["default_lora_name"] = new_value
                if value["class_type"] == "ComfyUIDeployExternalSlider":
                    value["inputs"]["default_value"] = new_value
                if value["class_type"] == "ComfyUIDeployExternalBoolean":
                    value["inputs"]["default_value"] = new_value
 def send_prompt(sid: str, inputs: StreamingPrompt):
    # workflow_api = inputs.workflow_api
    workflow_api = copy.deepcopy(inputs.workflow_api)
@@ -272,11 +145,11 @@ def send_prompt(sid: str, inputs: StreamingPrompt):
    # Random seed
    apply_random_seed_to_workflow(workflow_api)
-    logger.info("getting inputs" , inputs.inputs)
+    print("getting inputs" , inputs.inputs)
    apply_inputs_to_workflow(workflow_api, inputs.inputs, sid=sid)
-    logger.info(workflow_api)
+    print(workflow_api)
    prompt_id = str(uuid.uuid4())
@@ -299,11 +172,12 @@ def send_prompt(sid: str, inputs: StreamingPrompt):
        error_type = type(e).__name__
        stack_trace_short = traceback.format_exc().strip().split('\n')[-2]
        stack_trace = traceback.format_exc().strip()
-        logger.info(f"error: {error_type}, {e}")
+        print(f"error: {error_type}, {e}")
-        logger.info(f"stack trace: {stack_trace_short}")
+        print(f"stack trace: {stack_trace_short}")
@server.PromptServer.instance.routes.post("/comfyui-deploy/run")
 async def comfy_deploy_run(request):
    prompt_server = server.PromptServer.instance
    data = await request.json()
    # In older version, we use workflow_api, but this has inputs already swapped in nextjs frontend, which is tricky
@@ -334,8 +208,8 @@ async def comfy_deploy_run(request):
        error_type = type(e).__name__
        stack_trace_short = traceback.format_exc().strip().split('\n')[-2]
        stack_trace = traceback.format_exc().strip()
-        logger.info(f"error: {error_type}, {e}")
+        print(f"error: {error_type}, {e}")
-        logger.info(f"stack trace: {stack_trace_short}")
+        print(f"stack trace: {stack_trace_short}")
        await update_run_with_output(prompt_id, {
            "error": {
                "error_type": error_type,
@@ -347,6 +221,13 @@ async def comfy_deploy_run(request):
        return web.Response(status=500, reason=f"{error_type}: {e}, {stack_trace_short}")
    status = 200
    # if "error" in res:
    #     status = 400
    #     await update_run_with_output(prompt_id, {
    #         "error": {
    #             **res
    #         }
    #     })
    if "node_errors" in res and res["node_errors"]:
        # Even tho there are node_errors it can still be run
@@ -363,134 +244,24 @@ async def comfy_deploy_run(request):
    return web.json_response(res, status=status)
 async def stream_prompt(data):
    # In older version, we use workflow_api, but this has inputs already swapped in nextjs frontend, which is tricky
    workflow_api = data.get("workflow_api_raw")
    # The prompt id generated from comfy deploy, can be None
    prompt_id = data.get("prompt_id")
    inputs = data.get("inputs")
    # Now it handles directly in here
    apply_random_seed_to_workflow(workflow_api)
    apply_inputs_to_workflow(workflow_api, inputs)
    prompt = {
        "prompt": workflow_api,
        "client_id": "comfy_deploy_instance", #api.client_id
        "prompt_id": prompt_id
    }
    prompt_metadata[prompt_id] = SimplePrompt(
        status_endpoint=data.get('status_endpoint'),
        file_upload_endpoint=data.get('file_upload_endpoint'),
        workflow_api=workflow_api
    )
    log('info', "Begin prompt", prompt=prompt)
    try:
        res = post_prompt(prompt)
    except Exception as e:
        error_type = type(e).__name__
        stack_trace_short = traceback.format_exc().strip().split('\n')[-2]
        stack_trace = traceback.format_exc().strip()
        logger.info(f"error: {error_type}, {e}")
        logger.info(f"stack trace: {stack_trace_short}")
        await update_run_with_output(prompt_id, {
            "error": {
                "error_type": error_type,
                "stack_trace": stack_trace
            }
        })
         # When there are critical errors, the prompt is actually not run
        await update_run(prompt_id, Status.FAILED)
        # return web.Response(status=500, reason=f"{error_type}: {e}, {stack_trace_short}")
        # raise Exception("Prompt failed")
    status = 200
    if "node_errors" in res and res["node_errors"]:
        # Even tho there are node_errors it can still be run
        status = 400
        await update_run_with_output(prompt_id, {
            "error": {
                **res
            }
        })
        # When there are critical errors, the prompt is actually not run
        if "error" in res:
            await update_run(prompt_id, Status.FAILED)
            # raise Exception("Prompt failed")
    return res
    # return web.json_response(res, status=status)
 comfy_message_queues: Dict[str, asyncio.Queue] = {}
@server.PromptServer.instance.routes.post('/comfyui-deploy/run/streaming')
 async def stream_response(request):
    response = web.StreamResponse(status=200, reason='OK', headers={'Content-Type': 'text/event-stream'})
    await response.prepare(request)
    pending = True
    data = await request.json()
    prompt_id = data.get("prompt_id")
    comfy_message_queues[prompt_id] = asyncio.Queue()
    with log_span('Streaming Run'):
        log('info', 'Streaming prompt')
        try:
            result = await stream_prompt(data=data)
            await response.write(f"event: event_update\ndata: {json.dumps(result)}\n\n".encode('utf-8'))
            # await response.write(.encode('utf-8'))
            await response.drain()  # Ensure the buffer is flushed
            while pending:
                if prompt_id in comfy_message_queues:
                    if not comfy_message_queues[prompt_id].empty():
                        data = await comfy_message_queues[prompt_id].get()
                        log('info', data["event"], data=json.dumps(data))
                        # logger.info("listener", data)
                        await response.write(f"event: event_update\ndata: {json.dumps(data)}\n\n".encode('utf-8'))
                        await response.drain()  # Ensure the buffer is flushed
                        if data["event"] == "status":
                            if data["data"]["status"] in (Status.FAILED.value, Status.SUCCESS.value):
                                pending = False
                await asyncio.sleep(0.1)  # Adjust the sleep duration as needed
        except asyncio.CancelledError:
            log('info', "Streaming was cancelled")
            raise
        except Exception as e:
            log('error', "Streaming error", error=e)
        finally:
            # event_emitter.off("send_json", task)
            await response.write_eof()
            comfy_message_queues.pop(prompt_id, None)
            return response
 def get_comfyui_path_from_file_path(file_path):
    file_path_parts = file_path.split("\\")
    if file_path_parts[0] == "input":
-        logger.info("matching input")
+        print("matching input")
        file_path = os.path.join(folder_paths.get_directory_by_type("input"), *file_path_parts[1:])
    elif file_path_parts[0] == "models":
-        logger.info("matching models")
+        print("matching models")
        file_path = folder_paths.get_full_path(file_path_parts[1], os.path.join(*file_path_parts[2:]))
-    logger.info(file_path)
+    print(file_path)
    return file_path
 # Form ComfyUI Manager
 async def compute_sha256_checksum(filepath):
-    logger.info("computing sha256 checksum")
+    print("computing sha256 checksum")
    chunk_size = 1024 * 256  # Example: 256KB
    filepath = get_comfyui_path_from_file_path(filepath)
    """Compute the SHA256 checksum of a file, in chunks, asynchronously"""
@@ -513,7 +284,7 @@ async def get_installed_models(request):
        file_list = folder_paths.get_filename_list(key)
        value_json_compatible = (value[0], list(value[1]), file_list)
        new_dict[key] = value_json_compatible
-    # logger.info(new_dict)
+    # print(new_dict)
    return web.json_response(new_dict)
 # This is start uploading the files to Comfy Deploy
@@ -523,7 +294,7 @@ async def upload_file_endpoint(request):
    file_path = data.get("file_path")
-    logger.info("Original file path", file_path)
+    print("Original file path", file_path)
    file_path = get_comfyui_path_from_file_path(file_path)
@@ -562,9 +333,10 @@ async def upload_file_endpoint(request):
    if get_url:
        try:
            async with aiohttp.ClientSession() as session:
                headers = {'Authorization': f'Bearer {token}'}
                params = {'file_size': file_size, 'type': file_type}
-            response = await async_request_with_retry('GET', get_url, params=params, headers=headers)
+                async with session.get(get_url, params=params, headers=headers) as response:
                    if response.status == 200:
                        content = await response.json()
                        upload_url = content["upload_url"]
@@ -572,10 +344,10 @@ async def upload_file_endpoint(request):
                        with open(file_path, 'rb') as f:
                            headers = {
                                "Content-Type": file_type,
-                        # "x-amz-acl": "public-read",
+                                "x-amz-acl": "public-read",
                                "Content-Length": str(file_size)
                            }
-                    upload_response = await async_request_with_retry('PUT', upload_url, data=f, headers=headers)
+                            async with session.put(upload_url, data=f, headers=headers) as upload_response:
                                if upload_response.status == 200:
                                    return web.json_response({
                                        "message": "File uploaded successfully",
@@ -644,7 +416,7 @@ async def get_file_hash(request):
            file_hash = await compute_sha256_checksum(full_file_path)
            end_time = time.time()
            elapsed_time = end_time - start_time
-            logger.info(f"Cache miss -> Execution time: {elapsed_time} seconds")
+            print(f"Cache miss -> Execution time: {elapsed_time} seconds")
            # Update the in-memory cache
            file_hash_cache[full_file_path] = file_hash
@@ -664,10 +436,10 @@ async def update_realtime_run_status(realtime_id: str, status_endpoint: str, sta
        "run_id": realtime_id,
        "status": status.value,
    }
    if (status_endpoint is None):
        return
    # requests.post(status_endpoint, json=body)
-    await async_request_with_retry('POST', status_endpoint, json=body)
+    async with aiohttp.ClientSession() as session:
        async with session.post(status_endpoint, json=body) as response:
            pass
@server.PromptServer.instance.routes.get('/comfyui-deploy/ws')
 async def websocket_handler(request):
@@ -688,12 +460,13 @@ async def websocket_handler(request):
    status_endpoint = request.rel_url.query.get('status_endpoint', None)
    if auth_token is not None and get_workflow_endpoint_url is not None:
        async with aiohttp.ClientSession() as session:
            headers = {'Authorization': f'Bearer {auth_token}'}
-        response = await async_request_with_retry('GET', get_workflow_endpoint_url, headers=headers)
+            async with session.get(get_workflow_endpoint_url, headers=headers) as response:
                if response.status == 200:
                    workflow = await response.json()
-            logger.info(f"Loaded workflow version ${workflow['version']}")
+                    print("Loaded workflow version ",workflow["version"])
                    streaming_prompt_metadata[sid] = StreamingPrompt(
                        workflow_api=workflow["workflow_api"], 
@@ -707,7 +480,7 @@ async def websocket_handler(request):
                    # await send("workflow_api", workflow_api, sid)
                else:
                    error_message = await response.text()
-            logger.info(f"Failed to fetch workflow endpoint. Status: {response.status}, Error: {error_message}")
+                    print(f"Failed to fetch workflow endpoint. Status: {response.status}, Error: {error_message}")
                    # await send("error", {"message": error_message}, sid)
    try:
@@ -722,10 +495,10 @@ async def websocket_handler(request):
            if msg.type == aiohttp.WSMsgType.TEXT:
                try:
                    data = json.loads(msg.data)
-                    logger.info(data)
+                    print(data)
                    event_type = data.get('event')
                    if event_type == 'input':
-                        logger.info(f"Got input: ${data.get('inputs')}")
+                        print("Got input: ", data.get("inputs"))
                        input = data.get('inputs')
                        streaming_prompt_metadata[sid].inputs.update(input)
                    elif event_type == 'queue_prompt':
@@ -735,7 +508,7 @@ async def websocket_handler(request):
                        # Handle other event types
                        pass
                except json.JSONDecodeError:
-                    logger.info('Failed to decode JSON from message')
+                    print('Failed to decode JSON from message')
            if msg.type == aiohttp.WSMsgType.BINARY:
                data = msg.data
@@ -744,9 +517,9 @@ async def websocket_handler(request):
                    image_type_code, = struct.unpack("<I", data[4:8])
                    input_id_bytes = data[8:32]  # Extract the next 24 bytes for the input ID
                    input_id = input_id_bytes.decode('ascii').strip()  # Decode the input ID from ASCII
-                    logger.info(event_type)
+                    print(event_type)
-                    logger.info(image_type_code)
+                    print(image_type_code)
-                    logger.info(input_id)
+                    print(input_id)
                    image_data = data[32:]  # The rest is the image data
                    if image_type_code == 1:
                        image_type = "JPEG"
@@ -755,7 +528,7 @@ async def websocket_handler(request):
                    elif image_type_code == 3:
                        image_type = "WEBP"
                    else:
-                        logger.info(f"Unknown image type code: ${image_type_code}")
+                        print("Unknown image type code:", image_type_code)
                        return
                    image = Image.open(BytesIO(image_data))
                    # Check if the input ID already exists and replace the input with the new one
@@ -766,14 +539,14 @@ async def websocket_handler(request):
                            if hasattr(existing_image, 'close'):
                                existing_image.close()
                        except Exception as e:
-                            logger.info(f"Error closing previous image for input ID {input_id}: {e}")
+                            print(f"Error closing previous image for input ID {input_id}: {e}")
                    streaming_prompt_metadata[sid].inputs[input_id] = image
                    # clear_current_prompt(sid)
                    # send_prompt(sid, streaming_prompt_metadata[sid])
-                    logger.info(f"Received {image_type} image of size {image.size} with input ID {input_id}")
+                    print(f"Received {image_type} image of size {image.size} with input ID {input_id}")
            if msg.type == aiohttp.WSMsgType.ERROR:
-                logger.info('ws connection closed with exception %s' % ws.exception())
+                print('ws connection closed with exception %s' % ws.exception())
    finally:
        sockets.pop(sid, None)
@@ -818,16 +591,16 @@ async def send(event, data, sid=None):
                if not ws.closed:  # Check if the WebSocket connection is open and not closing
                    await ws.send_json({ 'event': event, 'data': data })
    except Exception as e:
-        logger.info(f"Exception: {e}")
+        print(f"Exception: {e}")
        traceback.print_exc()
-
+logging.basicConfig(level=logging.INFO)
 prompt_server = server.PromptServer.instance
 send_json = prompt_server.send_json
 async def send_json_override(self, event, data, sid=None):
-    # logger.info("INTERNAL:", event, data, sid)
+    # print("INTERNAL:", event, data, sid)
    prompt_id = data.get('prompt_id')
    target_sid = sid
@@ -840,19 +613,8 @@ async def send_json_override(self, event, data, sid=None):
        asyncio.create_task(self.send_json_original(event, data, sid))
    ])
    if prompt_id in comfy_message_queues:
        comfy_message_queues[prompt_id].put_nowait({
            "event": event,
            "data": data
        })
    # event_emitter.emit("send_json", {
    #     "event": event,
    #     "data": data
    # })
    if event == 'execution_start':
-        await update_run(prompt_id, Status.RUNNING)
+        update_run(prompt_id, Status.RUNNING)
        if prompt_id in prompt_metadata:
            prompt_metadata[prompt_id].start_time = time.perf_counter()
@@ -861,12 +623,12 @@ async def send_json_override(self, event, data, sid=None):
    if event == 'executing' and data.get('node') is None:
        mark_prompt_done(prompt_id=prompt_id)
        if not have_pending_upload(prompt_id):
-            await update_run(prompt_id, Status.SUCCESS)
+            update_run(prompt_id, Status.SUCCESS)
            if prompt_id in prompt_metadata:
                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
-                    logger.info(f"Elapsed time: {elapsed_time} seconds")
+                    print(f"Elapsed time: {elapsed_time} seconds")
                    await send("elapsed_time", {
                        "prompt_id": prompt_id,
                        "elapsed_time": elapsed_time
@@ -881,14 +643,13 @@ async def send_json_override(self, event, data, sid=None):
            prompt_metadata[prompt_id].progress.add(node)
            calculated_progress = len(prompt_metadata[prompt_id].progress) / len(prompt_metadata[prompt_id].workflow_api)
-            calculated_progress = round(calculated_progress, 2)
+            # print("calculated_progress", calculated_progress)
            # logger.info("calculated_progress", calculated_progress)
            if prompt_metadata[prompt_id].last_updated_node is not None and prompt_metadata[prompt_id].last_updated_node == node:
                return
            prompt_metadata[prompt_id].last_updated_node = node
            class_type = prompt_metadata[prompt_id].workflow_api[node]['class_type']
-            logger.info(f"At: {calculated_progress * 100}% - {class_type}")
+            print("updating run live status", class_type)
            await send("live_status", {
                "prompt_id": prompt_id,
                "current_node": class_type,
@@ -909,19 +670,18 @@ async def send_json_override(self, event, data, sid=None):
    if event == 'execution_error':
        # Careful this might not be fully awaited.
        await update_run_with_output(prompt_id, data)
-        await update_run(prompt_id, Status.FAILED)
+        update_run(prompt_id, Status.FAILED)
        # await update_run_with_output(prompt_id, data)
    if event == 'executed' and 'node' in data and 'output' in data:
        print("executed", data)
        if prompt_id in prompt_metadata:
            node = data.get('node')
            class_type = prompt_metadata[prompt_id].workflow_api[node]['class_type']
-            logger.info(f"Executed {class_type} {data}")
+            print("executed", class_type)
            if class_type == "PreviewImage":
-                logger.info("Skipping preview image")
+                print("skipping preview image")
                return
        else:
            logger.info(f"Executed {data}")
        await update_run_with_output(prompt_id, data.get('output'), node_id=data.get('node'))
        # await update_run_with_output(prompt_id, data.get('output'), node_id=data.get('node'))
@@ -937,34 +697,21 @@ async def update_run_live_status(prompt_id, live_status, calculated_progress: fl
    if prompt_metadata[prompt_id].is_realtime is True:
        return
    print("progress", calculated_progress)
    status_endpoint = prompt_metadata[prompt_id].status_endpoint
    if (status_endpoint is None):
        return
    # logger.info(f"progress {calculated_progress}")
    body = {
        "run_id": prompt_id,
        "live_status": live_status,
        "progress": calculated_progress
    }
    if prompt_id in comfy_message_queues:
        comfy_message_queues[prompt_id].put_nowait({
            "event": "live_status",
            "data": {
                "prompt_id": prompt_id,
                "live_status": live_status,
                "progress": calculated_progress
            }
        })
    # requests.post(status_endpoint, json=body)
-    await async_request_with_retry('POST', status_endpoint, json=body)
+    async with aiohttp.ClientSession() as session:
        async with session.post(status_endpoint, json=body) as response:
            pass
-async def update_run(prompt_id: str, status: Status):
+def update_run(prompt_id: str, status: Status):
    global last_read_line_number
    if prompt_id not in prompt_metadata:
@@ -987,20 +734,18 @@ async def update_run(prompt_id: str, status: Status):
            "run_id": prompt_id,
            "status": status.value,
        }
-        logger.info(f"Status: {status.value}")
+        print(f"Status: {status.value}")
        try:
-            # requests.post(status_endpoint, json=body)
+            requests.post(status_endpoint, json=body)
            if (status_endpoint is not None):
                await async_request_with_retry('POST', status_endpoint, json=body)
-            if (status_endpoint is not None) and cd_enable_run_log and (status == Status.SUCCESS or status == Status.FAILED):
+            if cd_enable_run_log and (status == Status.SUCCESS or status == Status.FAILED):
                try:
                    with open(comfyui_file_path, 'r') as log_file:
                        # log_data = log_file.read()
                        # Move to the last read line
                        all_log_data = log_file.read()  # Read all log data
-                        # logger.info("All log data before skipping: ")  # Log all data before skipping
+                        print("All log data before skipping:", all_log_data)  # Log all data before skipping
                        log_file.seek(0)  # Reset file pointer to the beginning
                        for _ in range(last_read_line_number):
@@ -1008,9 +753,9 @@ async def update_run(prompt_id: str, status: Status):
                        log_data = log_file.read()
                        # Update the last read line number
                        last_read_line_number += log_data.count('\n')
-                        # logger.info("last_read_line_number", last_read_line_number)
+                        print("last_read_line_number", last_read_line_number)
-                        # logger.info("log_data", log_data)
+                        print("log_data", log_data)
-                        # logger.info("log_data.count(n)", log_data.count('\n'))
+                        print("log_data.count(n)", log_data.count('\n'))
                        body = {
                            "run_id": prompt_id,
@@ -1021,26 +766,16 @@ async def update_run(prompt_id: str, status: Status):
                                }
                            ]
                        }
-
+                        requests.post(status_endpoint, json=body)
                        await async_request_with_retry('POST', status_endpoint, json=body)
                        # requests.post(status_endpoint, json=body)
                except Exception as log_error:
-                    logger.info(f"Error reading log file: {log_error}")
+                    print(f"Error reading log file: {log_error}")
        except Exception as e:
            error_type = type(e).__name__
            stack_trace = traceback.format_exc().strip()
-            logger.info(f"Error occurred while updating run: {e} {stack_trace}")
+            print(f"Error occurred while updating run: {e} {stack_trace}")
        finally:
            prompt_metadata[prompt_id].status = status
            if prompt_id in comfy_message_queues:
                comfy_message_queues[prompt_id].put_nowait({
                    "event": "status",
                    "data": {
                        "prompt_id": prompt_id,
                        "status": status.value,
                    }
                })
 async def upload_file(prompt_id, filename, subfolder=None, content_type="image/png", type="output"):
@@ -1058,7 +793,7 @@ async def upload_file(prompt_id, filename, subfolder=None, content_type="image/p
        output_dir = folder_paths.get_directory_by_type(type)
    if output_dir is None:
-        logger.info(f"{filename} Upload failed: output_dir is None")
+        print(filename, "Upload failed: output_dir is None")
        return 
    if subfolder != None:
@@ -1070,7 +805,7 @@ async def upload_file(prompt_id, filename, subfolder=None, content_type="image/p
    filename = os.path.basename(filename)
    file = os.path.join(output_dir, filename)
-    logger.info(f"Uploading file {file}")
+    print("uploading file", file)
    file_upload_endpoint = prompt_metadata[prompt_id].file_upload_endpoint
@@ -1080,33 +815,27 @@ async def upload_file(prompt_id, filename, subfolder=None, content_type="image/p
    target_url = f"{file_upload_endpoint}?file_name={filename}&run_id={prompt_id}&type={content_type}"
    start_time = time.time()  # Start timing here
    result = requests.get(target_url)
    end_time = time.time()  # End timing after the request is complete
    logger.info("Time taken for getting file upload endpoint: {:.2f} seconds".format(end_time - start_time))
    ok = result.json()
    start_time = time.time()  # Start timing here
    with open(file, 'rb') as f:
        data = f.read()
        headers = {
-            # "x-amz-acl": "public-read",
+            "x-amz-acl": "public-read",
            "Content-Type": content_type,
            "Content-Length": str(len(data)),
        }
-        # response = requests.put(ok.get("url"), headers=headers, data=data)
+        response = requests.put(ok.get("url"), headers=headers, data=data)
-        response = await async_request_with_retry('PUT', ok.get("url"), headers=headers, data=data)
+        async with aiohttp.ClientSession() as session:
-        logger.info(f"Upload file response status: {response.status}, status text: {response.reason}")
+            async with session.put(ok.get("url"), headers=headers, data=data) as response:
-        end_time = time.time()  # End timing after the request is complete
+                print("upload file response", response.status)
        logger.info("Upload time: {:.2f} seconds".format(end_time - start_time))
 def have_pending_upload(prompt_id):
    if prompt_id in prompt_metadata and len(prompt_metadata[prompt_id].uploading_nodes) > 0:
-        logger.info(f"Have pending upload {len(prompt_metadata[prompt_id].uploading_nodes)}")
+        print("have pending upload ", len(prompt_metadata[prompt_id].uploading_nodes))
        return True
-    logger.info("No pending upload")
+    print("no pending upload")
    return False
 def mark_prompt_done(prompt_id):
@@ -1118,7 +847,7 @@ def mark_prompt_done(prompt_id):
    """
    if prompt_id in prompt_metadata:
        prompt_metadata[prompt_id].done = True
-        logger.info("Prompt done")
+        print("Prompt done")
 def is_prompt_done(prompt_id: str):
    """
@@ -1150,8 +879,8 @@ async def handle_error(prompt_id, data, e: Exception):
        }
    }
    await update_file_status(prompt_id, data, False, have_error=True)
-    logger.info(body)
+    print(body)
-    logger.info(f"Error occurred while uploading file: {e}")
+    print(f"Error occurred while uploading file: {e}")
 # Mark the current prompt requires upload, and block it from being marked as success
 async def update_file_status(prompt_id: str, data, uploading, have_error=False, node_id=None):
@@ -1164,11 +893,11 @@ async def update_file_status(prompt_id: str, data, uploading, have_error=False,
        else:
            prompt_metadata[prompt_id].uploading_nodes.discard(node_id)
-    logger.info(f"Remaining uploads: {prompt_metadata[prompt_id].uploading_nodes}")
+    print(prompt_metadata[prompt_id].uploading_nodes)
    # Update the remote status
    if have_error:
-        await update_run(prompt_id, Status.FAILED)
+        update_run(prompt_id, Status.FAILED)
        await send("failed", {
            "prompt_id": prompt_id,
        })
@@ -1177,15 +906,15 @@ async def update_file_status(prompt_id: str, data, uploading, have_error=False,
    # 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)
+            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 not uploading and not have_pending_upload(prompt_id) and is_prompt_done(prompt_id=prompt_id):
-        await update_run(prompt_id, Status.SUCCESS)
+        update_run(prompt_id, Status.SUCCESS)
-        # logger.info("Status: SUCCUSS")
+        print("Status: SUCCUSS")
        await send("success", {
            "prompt_id": prompt_id,
        })
@@ -1196,22 +925,12 @@ async def handle_upload(prompt_id: str, data, key: str, content_type_key: str, d
        # # Skipping temp files
        if item.get("type") == "temp":
            continue
        file_type = item.get(content_type_key, default_content_type)
        file_extension = os.path.splitext(item.get("filename"))[1]
        if file_extension in ['.jpg', '.jpeg']:
            file_type = 'image/jpeg'
        elif file_extension == '.png':
            file_type = 'image/png'
        elif file_extension == '.webp':
            file_type = 'image/webp'
        await upload_file(
            prompt_id,
            item.get("filename"),
            subfolder=item.get("subfolder"),
            type=item.get("type"),
-            content_type=file_type
+            content_type=item.get(content_type_key, default_content_type)
        )
 # Upload files in the background
@@ -1221,7 +940,6 @@ async def upload_in_background(prompt_id: str, data, node_id=None, have_upload=T
        await handle_upload(prompt_id, data, 'files', "content_type", "image/png")
        # This will also be mp4
        await handle_upload(prompt_id, data, 'gifs', "format", "image/gif")
        await handle_upload(prompt_id, data, 'mesh', "format", "application/octet-stream")
        if have_upload:
            await update_file_status(prompt_id, data, False, node_id=node_id)
@@ -1241,27 +959,21 @@ async def update_run_with_output(prompt_id, data, node_id=None):
        "run_id": prompt_id,
        "output_data": data
    }
    have_upload_media = 'images' in data or 'files' in data or 'gifs' in data or 'mesh' in data
    if bypass_upload and have_upload_media:
        print("CD_BYPASS_UPLOAD is enabled, skipping the upload of the output:", node_id)
        return
    if have_upload_media:
    try:
-            logger.info(f"\nHave_upload {have_upload_media} Node Id: {node_id}")
+        have_upload = 'images' in data or 'files' in data or 'gifs' in data
        print("\nhave_upload", have_upload, node_id)
-            if have_upload_media:
+        if have_upload:
            await update_file_status(prompt_id, data, True, node_id=node_id)
-            asyncio.create_task(upload_in_background(prompt_id, data, node_id=node_id, have_upload=have_upload_media))
+        asyncio.create_task(upload_in_background(prompt_id, data, node_id=node_id, have_upload=have_upload))
            # await upload_in_background(prompt_id, data, node_id=node_id, have_upload=have_upload)
    except Exception as e:
        await handle_error(prompt_id, data, e)
-    # requests.post(status_endpoint, json=body)
+
-    if status_endpoint is not None:
+    requests.post(status_endpoint, json=body)
        await async_request_with_retry('POST', status_endpoint, json=body)
    await send('outputs_uploaded', {
        "prompt_id": prompt_id
@@ -1315,9 +1027,3 @@ def run_in_new_thread(coroutine):
 if cd_enable_log:
    run_in_new_thread(watch_file_changes(log_file_path, send_logs_to_websocket))
 # use after calling GET /object_info (it populates the `filename_list_cache` variable)
@server.PromptServer.instance.routes.get("/comfyui-deploy/filename_list_cache")
 async def get_filename_list_cache(_):
    from folder_paths import filename_list_cache
    return web.json_response({'filename_list': filename_list_cache})
@@ -22,13 +22,12 @@ class StreamingPrompt(BaseModel):
    auth_token: str
    inputs: dict[str, Union[str, bytes, Image.Image]]
    running_prompt_ids: set[str] = set()
-    status_endpoint: Optional[str]
+    status_endpoint: str
-    file_upload_endpoint: Optional[str]
+    file_upload_endpoint: str
 class SimplePrompt(BaseModel):
-    status_endpoint: Optional[str]
+    status_endpoint: str
-    file_upload_endpoint: Optional[str]
+    file_upload_endpoint: str
    workflow_api: dict
    status: Status = Status.NOT_STARTED
    progress: set = set()
@@ -1,15 +0,0 @@
 [project]
 name = "comfyui-deploy"
 description = "Open source comfyui deployment platform, a vercel for generative workflow infra."
 version = "1.0.0"
 license = "LICENSE"
 dependencies = ["aiofiles", "pydantic", "opencv-python", "imageio-ffmpeg"]
 [project.urls]
 Repository = "https://github.com/BennyKok/comfyui-deploy"
 #  Used by Comfy Registry https://comfyregistry.org
 [tool.comfy]
 PublisherId = "comfydeploy"
 DisplayName = "comfyui-deploy"
 Icon = ""
@@ -1,5 +1,2 @@
 aiofiles
 pydantic
 opencv-python
 imageio-ffmpeg
 # logfire
@@ -13,75 +13,6 @@ function sendEventToCD(event, data) {
  window.parent.postMessage(JSON.stringify(message), "*");
 }
 function dispatchAPIEventData(data) {
  const msg = JSON.parse(data);
  // Custom parse error
  if (msg.error) {
    let message = msg.error.message;
    if (msg.error.details) message += ": " + msg.error.details;
    for (const [nodeID, nodeError] of Object.entries(msg.node_errors)) {
      message += "\n" + nodeError.class_type + ":";
      for (const errorReason of nodeError.errors) {
        message +=
          "\n    - " + errorReason.message + ": " + errorReason.details;
      }
    }
    app.ui.dialog.show(message);
    if (msg.node_errors) {
      app.lastNodeErrors = msg.node_errors;
      app.canvas.draw(true, true);
    }
  }
  switch (msg.event) {
    case "error":
      break;
    case "status":
      if (msg.data.sid) {
        // this.clientId = msg.data.sid;
        // window.name = this.clientId; // use window name so it isnt reused when duplicating tabs
        // sessionStorage.setItem("clientId", this.clientId); // store in session storage so duplicate tab can load correct workflow
      }
      api.dispatchEvent(new CustomEvent("status", { detail: msg.data.status }));
      break;
    case "progress":
      api.dispatchEvent(new CustomEvent("progress", { detail: msg.data }));
      break;
    case "executing":
      api.dispatchEvent(
        new CustomEvent("executing", { detail: msg.data.node }),
      );
      break;
    case "executed":
      api.dispatchEvent(new CustomEvent("executed", { detail: msg.data }));
      break;
    case "execution_start":
      api.dispatchEvent(
        new CustomEvent("execution_start", { detail: msg.data }),
      );
      break;
    case "execution_error":
      api.dispatchEvent(
        new CustomEvent("execution_error", { detail: msg.data }),
      );
      break;
    case "execution_cached":
      api.dispatchEvent(
        new CustomEvent("execution_cached", { detail: msg.data }),
      );
      break;
    default:
      api.dispatchEvent(new CustomEvent(msg.type, { detail: msg.data }));
    // default:
    // if (this.#registered.has(msg.type)) {
    // } else {
    // throw new Error(`Unknown message type ${msg.type}`);
    // }
  }
 }
 /** @typedef {import('../../../web/types/comfy.js').ComfyExtension} ComfyExtension*/
 /** @type {ComfyExtension} */
 const ext = {
@@ -99,29 +30,6 @@ const ext = {
    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);
      // // Intercept the onkeydown event
      // window.addEventListener(
      //   "keydown",
      //   (event) => {
      //     // Check for specific keys if necessary
      //     console.log("hi");
      //     if ((event.metaKey || event.ctrlKey) && event.key === "Enter") {
      //       event.preventDefault();
      //       event.stopImmediatePropagation();
      //       event.stopPropagation();
      //       sendEventToCD("cd_plugin_onQueuePrompt", prompt);
      //     }
      //   },
      //   true,
      // );
    }
    const data = getData();
@@ -258,56 +166,32 @@ const ext = {
    // const graphCanvas = document.getElementById("graph-canvas");
    window.addEventListener("message", async (event) => {
      //   console.log("message", event);
      try {
        const message = JSON.parse(event.data);
        if (message.type === "graph_load") {
          const comfyUIWorkflow = message.data;
-          // console.log("recieved: ", comfyUIWorkflow);
+          console.log("recieved: ", comfyUIWorkflow);
          // Assuming there's a method to load the workflow data into the ComfyUI
          // 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) {
            console.log("loadGraphData");
            app.loadGraphData(comfyUIWorkflow);
          }
        } else if (message.type === "deploy") {
          // deployWorkflow();
          const prompt = await app.graphToPrompt();
          // api.handlePromptGenerated(prompt);
          sendEventToCD("cd_plugin_onDeployChanges", prompt);
        } else if (message.type === "queue_prompt") {
          const prompt = await app.graphToPrompt();
          api.handlePromptGenerated(prompt);
          sendEventToCD("cd_plugin_onQueuePrompt", prompt);
        } else if (message.type === "get_prompt") {
          const prompt = await app.graphToPrompt();
          sendEventToCD("cd_plugin_onGetPrompt", prompt);
        } else if (message.type === "event") {
          dispatchAPIEventData(message.data);
        } else if (message.type === "add_node") {
          console.log("add node", message.data);
          app.graph.beforeChange();
          var node = LiteGraph.createNode(message.data.type);
          node.configure({
            widgets_values: message.data.widgets_values,
          });
          console.log("node", node);
          const graphMouse = app.canvas.graph_mouse;
          node.pos = [graphMouse[0], graphMouse[1]];
          app.graph.add(node);
          app.graph.afterChange();
        }
        // else if (message.type === "refresh") {
        //   sendEventToCD("cd_plugin_onRefresh");
        // }
      } catch (error) {
        // console.error("Error processing message:", error);
      }
      // if (!event.data.flow || Object.entries(event.data.flow).length <= 0)
      //   return;
      //   updateBlendshapesPrompts(event.data.flow);
    });
    api.addEventListener("executed", (evt) => {
@@ -320,8 +204,7 @@ const ext = {
      //   }
    });
-    app.graph.onAfterChange = ((originalFunction) =>
+    app.graph.onAfterChange = ((originalFunction) => async function () {
      async function () {
        const prompt = await app.graphToPrompt();
        sendEventToCD("cd_plugin_onAfterChange", prompt);
@@ -375,11 +258,14 @@ function createDynamicUIHtml(data) {
  Object.values(data.custom_nodes).forEach((node) => {
    html += `
          <div style="border-bottom: 1px solid #e2e8f0; padding-top: 16px;">
-              <a href="${node.url
+              <a href="${
-      }" target="_blank" style="font-size: 18px; font-weight: semibold; color: white; text-decoration: none;">${node.name
+                node.url
              }" target="_blank" style="font-size: 18px; font-weight: semibold; color: white; text-decoration: none;">${
                node.name
              }</a>
              <p style="font-size: 14px; color: #4b5563;">${node.hash}</p>
-              ${node.warning
+              ${
                node.warning
                  ? `<p style="font-size: 14px; color: #d69e2e;">${node.warning}</p>`
                  : ""
              }
@@ -396,7 +282,8 @@ function createDynamicUIHtml(data) {
  Object.entries(data.models).forEach(([section, items]) => {
    html += `
    <div style="border-bottom: 1px solid #e2e8f0; padding-top: 8px; padding-bottom: 8px;">
-        <h3 style="font-size: 18px; font-weight: semibold; margin-bottom: 8px;">${section.charAt(0).toUpperCase() + section.slice(1)
+        <h3 style="font-size: 18px; font-weight: semibold; margin-bottom: 8px;">${
          section.charAt(0).toUpperCase() + section.slice(1)
        }</h3>`;
    items.forEach((item) => {
      html += `<p style="font-size: 14px; color: ${textColor};">${item.name}</p>`;
@@ -413,7 +300,8 @@ function createDynamicUIHtml(data) {
  Object.entries(data.files).forEach(([section, items]) => {
    html += `
    <div style="border-bottom: 1px solid #e2e8f0; padding-top: 8px; padding-bottom: 8px;">
-        <h3 style="font-size: 18px; font-weight: semibold; margin-bottom: 8px;">${section.charAt(0).toUpperCase() + section.slice(1)
+        <h3 style="font-size: 18px; font-weight: semibold; margin-bottom: 8px;">${
          section.charAt(0).toUpperCase() + section.slice(1)
        }</h3>`;
    items.forEach((item) => {
      html += `<p style="font-size: 14px; color: ${textColor};">${item.name}</p>`;
@@ -566,7 +454,9 @@ async function deployWorkflow() {
        console.log(file);
        loadingDialog.showLoading("Generating hash", file);
        const hash = await fetch(
-          `/comfyui-deploy/get-file-hash?file_path=${encodeURIComponent(file)}`,
+          `/comfyui-deploy/get-file-hash?file_path=${encodeURIComponent(
            file,
          )}`,
        ).then((x) => x.json());
        loadingDialog.showLoading("Generating hash", file);
        console.log(hash);
@@ -576,14 +466,17 @@ async function deployWorkflow() {
        console.log("Uploading ", file);
        loadingDialog.showLoading("Uploading file", file);
        try {
-          const { download_url } = await fetch(`/comfyui-deploy/upload-file`, {
+          const { download_url } = await fetch(
            `/comfyui-deploy/upload-file`,
            {
              method: "POST",
              body: JSON.stringify({
                file_path: file,
                token: apiKey,
                url: endpoint + "/api/upload-url",
              }),
-          })
+            },
          )
            .then((x) => x.json())
            .catch(() => {
              loadingDialog.close();
@@ -715,7 +608,7 @@ function addButton() {
  deploy.style.display = "block";
  deploy.innerHTML = "<div id='button-title'>Deploy</div>";
  deploy.onclick = async () => {
-    await deployWorkflow();
+    await deployWorkflow()
  };
  const config = document.createElement("img");
@@ -837,9 +730,11 @@ export class LoadingDialog extends ComfyDialog {
  showLoading(title, message) {
    this.show(`
      <div style="width: 400px; display: flex; gap: 18px; flex-direction: column; overflow: unset">
-        <h3 style="margin: 0px; display: flex; align-items: center; justify-content: center; gap: 12px;">${title} ${this.loadingIcon
+        <h3 style="margin: 0px; display: flex; align-items: center; justify-content: center; gap: 12px;">${title} ${
          this.loadingIcon
        }</h3>
-          ${message
+          ${
            message
              ? `<label style="max-width: 100%; white-space: pre-wrap; word-wrap: break-word;">${message}</label>`
              : ""
          }
@@ -1108,16 +1003,20 @@ export class ConfigDialog extends ComfyDialog {
    </label>
      <label style="color: white; width: 100%;">
        Endpoint:
-        <input id="endpoint" style="margin-top: 8px; width: 100%; height:40px; box-sizing: border-box; padding: 0px 6px;" type="text" value="${data.endpoint
+        <input id="endpoint" style="margin-top: 8px; width: 100%; height:40px; box-sizing: border-box; padding: 0px 6px;" type="text" value="${
          data.endpoint
        }">
      </label>
      <div style="color: white;">
-        API Key: User / Org <button style="font-size: 18px;">${data.displayName ?? ""
+        API Key: User / Org <button style="font-size: 18px;">${
          data.displayName ?? ""
        }</button>
-        <input id="apiKey" style="margin-top: 8px; width: 100%; height:40px; box-sizing: border-box; padding: 0px 6px;" type="password" value="${data.apiKey
+        <input id="apiKey" style="margin-top: 8px; width: 100%; height:40px; box-sizing: border-box; padding: 0px 6px;" type="password" value="${
          data.apiKey
        }">
        <button id="loginButton" style="margin-top: 8px; width: 100%; height:40px; box-sizing: border-box; padding: 0px 6px;">
-          ${data.apiKey ? "Re-login with ComfyDeploy" : "Login with ComfyDeploy"
+          ${
            data.apiKey ? "Re-login with ComfyDeploy" : "Login with ComfyDeploy"
          }
        </button>
      </div>
@@ -74,7 +74,7 @@
    "mitata": "^0.1.6",
    "ms": "^2.1.3",
    "nanoid": "^5.0.4",
-    "next": "14.2",
+    "next": "14.1",
    "next-plausible": "^3.12.0",
    "next-themes": "^0.2.1",
    "next-usequerystate": "^1.13.2",
@@ -102,7 +102,7 @@ export const createRun = withServerPromise(
    let prompt_id: string | undefined = undefined;
    const shareData = {
-      workflow_api_raw: workflow_api,
+      workflow_api: workflow_api,
      status_endpoint: `${origin}/api/update-run`,
      file_upload_endpoint: `${origin}/api/file-upload`,
    };