Compare commits

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Author SHA1 Message Date
EmmanuelMr18 d97994a66e fix(upload outputs): skip images/gifs/files/mesh when env var is true
The env var is `CD_BYPASS_UPLOAD`.
When that variables is `True`, we don't upload the media to our comfy
deploy s3 bucket.

There are 2 steps.
1. save the file into our s3 bucket
2. save the saving into our database.

When `CD_BYPASS_UPLOAD` is True:
1. Skip the save file into our s3 bucket
2. Skip the save into our database

Previously we were skipping the step 1, but not the step 2. So that is
the reason of why we keep seeing the comfy deploy URL when fetching the
run details:

```
outputs: [
  {
    data:{
      gifs: [
        {
          url: "https://comfy-deploy-output.s3.amazonaws.com/video.mp4"
        }
      ],
      text: [
        "A text that you displayed with show text node"
      ]
    }
  }
]
```

With the new changes we don't save that into our database, and fetching
the details of a run will look like this:
```
outputs: [
  {
    data:{
      text: [
        "A text that you displayed with show text node"
      ]
    }
  }
]
```
2024-07-07 19:16:40 -06:00
EmmanuelMr18 e70a9c5e9e Revert "fix(image upload): skip when using the CD_BYPASS_UPLOAD env var"
This reverts commit 384eda63e6.
2024-07-07 18:52:21 -06:00
EmmanuelMr18 384eda63e6 fix(image upload): skip when using the CD_BYPASS_UPLOAD env var 2024-07-06 13:02:30 -06:00
nick c6fe88bf66 new route 2024-06-15 17:29:51 -07:00
bennykok 9b24b12006 fix: file upload issues with cloudflare 2024-06-11 17:42:52 -07:00
bennykok ff70bbdcec fix: correctly set the file content type for images, webp, jepg, png 2024-05-29 08:59:53 -07:00
haohaocreates 840bea79e8 chore(publish): Add Github Action for Publishing to Comfy Registry (#48) 2024-05-26 23:25:15 +08:00
BennyKok 0f423ce1c3 Update pyproject.toml 2024-05-26 23:21:13 +08:00
haohaocreates 2aa1a446e5 chore(pyproject): Add pyproject.toml for Custom Node Registry (#47) 2024-05-26 23:20:50 +08:00
karrix 07a7feb6ac add: slider number support 2024-05-11 14:50:46 +08:00
bennykok c5ac1b5f94 perf: turn back on async file upload 2024-05-10 13:08:37 +09:00
bennykok 00d827e232 feat: CD_BYPASS_UPLOAD 2024-05-10 11:36:00 +09:00
karrix 697fd52349 add: bool custom node 2024-05-09 14:26:43 +08:00
karrix 6b9c431df8 add: boolean input and 3d mesh support 2024-05-09 14:25:22 +08:00
bennykok 3c508c7eec feat: redirect queue prompt to iframe event in workspace mode 2024-05-07 00:42:36 +08:00
Nick Kao 409ca6f1dd Merge pull request #45 from NicholasKao1029/main
video node
2024-05-04 10:19:07 -07:00
nick df391e867e video node 2024-05-04 10:14:33 -07:00
Nick Kao c37b8be00a Merge pull request #44 from NicholasKao1029/main
Video node
2024-04-30 12:56:30 -07:00
nick a5a73e4209 clean up 2024-04-30 12:55:04 -07:00
nick c7841deea2 vid node 2024-04-30 12:19:41 -07:00
nick b0b1d64b6b external video 2024-04-27 13:32:50 -07:00
bennykok c8dc189f99 fix: external number input 2024-04-25 18:36:24 +08:00
bennykok cd5e4a5d01 fix: duplicated file upload 2024-04-25 16:14:14 +08:00
bennykok 95c15f095d chore: add file upload time log 2024-04-25 15:55:34 +08:00
nick b4c27bbbea fix: external lora 2024-04-24 23:27:01 -07:00
bennykok 810aec5135 fix: empty inputs causing run issues 2024-04-25 13:15:55 +08:00
nick c843926d6e fix: external lora takes in value outside of default 2024-04-24 17:35:09 -07:00
11 changed files with 903 additions and 57 deletions
+21
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@@ -0,0 +1,21 @@
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 }}
+25
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@@ -0,0 +1,25 @@
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)"}
+25 -23
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@@ -16,8 +16,8 @@ class ComfyUIDeployExternalLora:
), ),
}, },
"optional": { "optional": {
"default_lora_name": (folder_paths.get_filename_list("loras"), ), "default_lora_name": (folder_paths.get_filename_list("loras"),),
} },
} }
RETURN_TYPES = (folder_paths.get_filename_list("loras"),) RETURN_TYPES = (folder_paths.get_filename_list("loras"),)
@@ -32,27 +32,29 @@ class ComfyUIDeployExternalLora:
import os import os
import uuid import uuid
print('external lora using') if default_lora_name.startswith("http"):
print("input id: ", input_id) unique_filename = str(uuid.uuid4()) + ".safetensors"
print("default lora : ", default_lora_name) print(unique_filename)
print(folder_paths.folder_names_and_paths["loras"][0][0])
destination_path = os.path.join(
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(
input_id,
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 (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(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(input_id, 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:
return (input_id,)
return (default_lora_name,)
NODE_CLASS_MAPPINGS = {"ComfyUIDeployExternalLora": ComfyUIDeployExternalLora} NODE_CLASS_MAPPINGS = {"ComfyUIDeployExternalLora": ComfyUIDeployExternalLora}
NODE_DISPLAY_NAME_MAPPINGS = {"ComfyUIDeployExternalLora": "External Lora (ComfyUI Deploy)"} NODE_DISPLAY_NAME_MAPPINGS = {
"ComfyUIDeployExternalLora": "External Lora (ComfyUI Deploy)"
}
+1 -1
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@@ -29,7 +29,7 @@ class ComfyUIDeployExternalNumberInt:
CATEGORY = "number" CATEGORY = "number"
def run(self, input_id, default_value=None): def run(self, input_id, default_value=None):
if not input_id or not input_id.strip().isdigit(): if not input_id or (isinstance(input_id, str) and not input_id.strip().isdigit()):
return [default_value] return [default_value]
return [int(input_id)] return [int(input_id)]
+48
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@@ -0,0 +1,48 @@
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)"}
+78
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@@ -0,0 +1,78 @@
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"
}
+594
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@@ -0,0 +1,594 @@
# credit goes to https://github.com/Kosinkadink/ComfyUI-VideoHelperSuite and is meant to work with
import os
import itertools
import numpy as np
import torch
import cv2
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 get_sorted_dir_files_from_directory(
directory: str,
skip_first_images: int = 0,
select_every_nth: int = 1,
extensions: Iterable = None,
):
directory = directory.strip()
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, "-v", "error", "-i", file]
if start_time > 0:
args += ["-ss", str(start_time)]
if duration > 0:
args += ["-t", str(duration)]
try:
res = subprocess.run(
args + ["-f", "wav", "-"], stdout=subprocess.PIPE, check=True
).stdout
except subprocess.CalledProcessError as e:
return False
return res
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 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 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(video)
if not video_cap.isOpened():
raise ValueError(f"{video} could not be loaded with cv.")
# 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)
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) / 255.0
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 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 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,
):
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,
)
else:
(gen, width, height, fps, duration, total_frames, target_frame_time) = (
meta_batch.inputs[unique_id]
)
if meta_batch is not None:
gen = itertools.islice(gen, meta_batch.frames_per_batch)
# 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, (height, width, 3))))
)
if len(images) == 0:
raise RuntimeError("No frames generated")
if force_size != "Disabled":
new_size = target_size(width, height, force_size, custom_width, custom_height)
if new_size[0] != width or new_size[1] != height:
s = images.movedim(-1, 1)
s = common_upscale(s, new_size[0], new_size[1], "lanczos", "center")
images = s.movedim(1, -1)
# Setup lambda for lazy audio capture
audio = lambda: 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": images.shape[2],
"loaded_height": images.shape[1],
}
return (images, len(images), lazy_eval(audio), video_info)
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",),
"default_value": (sorted(files),),
},
"hidden": {"unique_id": "UNIQUE_ID"},
}
CATEGORY = "Video Helper Suite 🎥🅥🅗🅢"
RETURN_TYPES = (
"IMAGE",
"INT",
"VHS_AUDIO",
"VHS_VIDEOINFO",
)
RETURN_NAMES = (
"IMAGE",
"frame_count",
"audio",
"video_info",
)
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)"
}
+57 -16
View File
@@ -30,6 +30,10 @@ api_task = None
cd_enable_log = os.environ.get('CD_ENABLE_LOG', 'false').lower() == 'true' 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' 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'
print("CD_BYPASS_UPLOAD", bypass_upload)
def clear_current_prompt(sid): def clear_current_prompt(sid):
prompt_server = server.PromptServer.instance prompt_server = server.PromptServer.instance
@@ -118,7 +122,7 @@ def apply_inputs_to_workflow(workflow_api: Any, inputs: Any, sid: str = None):
if (value["class_type"] == "ComfyDeployWebscoketImageInput"): if (value["class_type"] == "ComfyDeployWebscoketImageInput"):
value['inputs']["client_id"] = sid value['inputs']["client_id"] = sid
if "input_id" in value['inputs'] and value['inputs']['input_id'] in inputs: if "input_id" in value['inputs'] and inputs is not None and value['inputs']['input_id'] in inputs:
new_value = inputs[value['inputs']['input_id']] new_value = inputs[value['inputs']['input_id']]
# Lets skip it if its an image # Lets skip it if its an image
@@ -137,6 +141,15 @@ def apply_inputs_to_workflow(workflow_api: Any, inputs: Any, sid: str = None):
if (value["class_type"] == "ComfyUIDeployExternalImageBatch"): if (value["class_type"] == "ComfyUIDeployExternalImageBatch"):
value['inputs']["images"] = new_value 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): def send_prompt(sid: str, inputs: StreamingPrompt):
# workflow_api = inputs.workflow_api # workflow_api = inputs.workflow_api
@@ -344,7 +357,7 @@ async def upload_file_endpoint(request):
with open(file_path, 'rb') as f: with open(file_path, 'rb') as f:
headers = { headers = {
"Content-Type": file_type, "Content-Type": file_type,
"x-amz-acl": "public-read", # "x-amz-acl": "public-read",
"Content-Length": str(file_size) "Content-Length": str(file_size)
} }
async with session.put(upload_url, data=f, headers=headers) as upload_response: async with session.put(upload_url, data=f, headers=headers) as upload_response:
@@ -815,20 +828,27 @@ 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}" 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) result = requests.get(target_url)
end_time = time.time() # End timing after the request is complete
print("Time taken for getting file upload endpoint: {:.2f} seconds".format(end_time - start_time))
ok = result.json() ok = result.json()
start_time = time.time() # Start timing here
with open(file, 'rb') as f: with open(file, 'rb') as f:
data = f.read() data = f.read()
headers = { headers = {
"x-amz-acl": "public-read", # "x-amz-acl": "public-read",
"Content-Type": content_type, "Content-Type": content_type,
"Content-Length": str(len(data)), "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)
async with aiohttp.ClientSession() as session: async with aiohttp.ClientSession() as session:
async with session.put(ok.get("url"), headers=headers, data=data) as response: async with session.put(ok.get("url"), headers=headers, data=data) as response:
print("upload file response", response.status) print("Upload file response", response.status)
end_time = time.time() # End timing after the request is complete
print("Upload time: {:.2f} seconds".format(end_time - start_time))
def have_pending_upload(prompt_id): def have_pending_upload(prompt_id):
if prompt_id in prompt_metadata and len(prompt_metadata[prompt_id].uploading_nodes) > 0: if prompt_id in prompt_metadata and len(prompt_metadata[prompt_id].uploading_nodes) > 0:
@@ -914,7 +934,7 @@ async def update_file_status(prompt_id: str, data, uploading, have_error=False,
# if there are no nodes that are uploading, then we set the status to success # 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): elif not uploading and not have_pending_upload(prompt_id) and is_prompt_done(prompt_id=prompt_id):
update_run(prompt_id, Status.SUCCESS) update_run(prompt_id, Status.SUCCESS)
print("Status: SUCCUSS") # print("Status: SUCCUSS")
await send("success", { await send("success", {
"prompt_id": prompt_id, "prompt_id": prompt_id,
}) })
@@ -925,12 +945,22 @@ async def handle_upload(prompt_id: str, data, key: str, content_type_key: str, d
# # Skipping temp files # # Skipping temp files
if item.get("type") == "temp": if item.get("type") == "temp":
continue 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( await upload_file(
prompt_id, prompt_id,
item.get("filename"), item.get("filename"),
subfolder=item.get("subfolder"), subfolder=item.get("subfolder"),
type=item.get("type"), type=item.get("type"),
content_type=item.get(content_type_key, default_content_type) content_type=file_type
) )
# Upload files in the background # Upload files in the background
@@ -940,6 +970,7 @@ 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") await handle_upload(prompt_id, data, 'files', "content_type", "image/png")
# This will also be mp4 # This will also be mp4
await handle_upload(prompt_id, data, 'gifs', "format", "image/gif") await handle_upload(prompt_id, data, 'gifs', "format", "image/gif")
await handle_upload(prompt_id, data, 'mesh', "format", "application/octet-stream")
if have_upload: if have_upload:
await update_file_status(prompt_id, data, False, node_id=node_id) await update_file_status(prompt_id, data, False, node_id=node_id)
@@ -959,19 +990,23 @@ async def update_run_with_output(prompt_id, data, node_id=None):
"run_id": prompt_id, "run_id": prompt_id,
"output_data": data "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
try: if have_upload_media:
have_upload = 'images' in data or 'files' in data or 'gifs' in data try:
print("\nhave_upload", have_upload, node_id) print("\nhave_upload", have_upload_media, node_id)
if have_upload: if have_upload_media:
await update_file_status(prompt_id, data, True, node_id=node_id) 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)) asyncio.create_task(upload_in_background(prompt_id, data, node_id=node_id, have_upload=have_upload_media))
# await upload_in_background(prompt_id, data, node_id=node_id, have_upload=have_upload)
except Exception as e: except Exception as e:
await handle_error(prompt_id, data, e) await handle_error(prompt_id, data, e)
requests.post(status_endpoint, json=body) requests.post(status_endpoint, json=body)
@@ -1027,3 +1062,9 @@ def run_in_new_thread(coroutine):
if cd_enable_log: if cd_enable_log:
run_in_new_thread(watch_file_changes(log_file_path, send_logs_to_websocket)) 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})
+15
View File
@@ -0,0 +1,15 @@
[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 = ""
+3 -1
View File
@@ -1,2 +1,4 @@
aiofiles aiofiles
pydantic pydantic
opencv-python
imageio-ffmpeg
+36 -16
View File
@@ -30,6 +30,30 @@ const ext = {
if (workspace_mode) { if (workspace_mode) {
document.querySelector(".comfy-menu").style.display = "none"; 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(); const data = getData();
@@ -204,7 +228,8 @@ const ext = {
// } // }
}); });
app.graph.onAfterChange = ((originalFunction) => async function () { app.graph.onAfterChange = ((originalFunction) =>
async function () {
const prompt = await app.graphToPrompt(); const prompt = await app.graphToPrompt();
sendEventToCD("cd_plugin_onAfterChange", prompt); sendEventToCD("cd_plugin_onAfterChange", prompt);
@@ -454,9 +479,7 @@ async function deployWorkflow() {
console.log(file); console.log(file);
loadingDialog.showLoading("Generating hash", file); loadingDialog.showLoading("Generating hash", file);
const hash = await fetch( const hash = await fetch(
`/comfyui-deploy/get-file-hash?file_path=${encodeURIComponent( `/comfyui-deploy/get-file-hash?file_path=${encodeURIComponent(file)}`,
file,
)}`,
).then((x) => x.json()); ).then((x) => x.json());
loadingDialog.showLoading("Generating hash", file); loadingDialog.showLoading("Generating hash", file);
console.log(hash); console.log(hash);
@@ -466,17 +489,14 @@ async function deployWorkflow() {
console.log("Uploading ", file); console.log("Uploading ", file);
loadingDialog.showLoading("Uploading file", file); loadingDialog.showLoading("Uploading file", file);
try { try {
const { download_url } = await fetch( const { download_url } = await fetch(`/comfyui-deploy/upload-file`, {
`/comfyui-deploy/upload-file`, method: "POST",
{ body: JSON.stringify({
method: "POST", file_path: file,
body: JSON.stringify({ token: apiKey,
file_path: file, url: endpoint + "/api/upload-url",
token: apiKey, }),
url: endpoint + "/api/upload-url", })
}),
},
)
.then((x) => x.json()) .then((x) => x.json())
.catch(() => { .catch(() => {
loadingDialog.close(); loadingDialog.close();
@@ -608,7 +628,7 @@ function addButton() {
deploy.style.display = "block"; deploy.style.display = "block";
deploy.innerHTML = "<div id='button-title'>Deploy</div>"; deploy.innerHTML = "<div id='button-title'>Deploy</div>";
deploy.onclick = async () => { deploy.onclick = async () => {
await deployWorkflow() await deployWorkflow();
}; };
const config = document.createElement("img"); const config = document.createElement("img");