Merge branch 'comfyanonymous:master' into master

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patientx 2025-10-03 01:01:55 +03:00 committed by GitHub
commit a12b26c630
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4 changed files with 130 additions and 64 deletions

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@ -95,6 +95,7 @@ import aiohttp
import asyncio
import logging
import io
import os
import socket
from aiohttp.client_exceptions import ClientError, ClientResponseError
from typing import Dict, Type, Optional, Any, TypeVar, Generic, Callable, Tuple
@ -499,7 +500,9 @@ class ApiClient:
else:
raise ValueError("File must be BytesIO or str path")
operation_id = f"upload_{upload_url.split('/')[-1]}_{uuid.uuid4().hex[:8]}"
parsed = urlparse(upload_url)
basename = os.path.basename(parsed.path) or parsed.netloc or "upload"
operation_id = f"upload_{basename}_{uuid.uuid4().hex[:8]}"
request_logger.log_request_response(
operation_id=operation_id,
request_method="PUT",

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@ -4,16 +4,18 @@ import os
import datetime
import json
import logging
import re
import hashlib
from typing import Any
import folder_paths
# Get the logger instance
logger = logging.getLogger(__name__)
def get_log_directory():
"""
Ensures the API log directory exists within ComfyUI's temp directory
and returns its path.
"""
"""Ensures the API log directory exists within ComfyUI's temp directory and returns its path."""
base_temp_dir = folder_paths.get_temp_directory()
log_dir = os.path.join(base_temp_dir, "api_logs")
try:
@ -24,42 +26,77 @@ def get_log_directory():
return base_temp_dir
return log_dir
def _format_data_for_logging(data):
def _sanitize_filename_component(name: str) -> str:
if not name:
return "log"
sanitized = re.sub(r"[^A-Za-z0-9._-]+", "_", name) # Replace disallowed characters with underscore
sanitized = sanitized.strip(" ._") # Windows: trailing dots or spaces are not allowed
if not sanitized:
sanitized = "log"
return sanitized
def _short_hash(*parts: str, length: int = 10) -> str:
return hashlib.sha1(("|".join(parts)).encode("utf-8")).hexdigest()[:length]
def _build_log_filepath(log_dir: str, operation_id: str, request_url: str) -> str:
"""Build log filepath. We keep it well under common path length limits aiming for <= 240 characters total."""
timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S_%f")
slug = _sanitize_filename_component(operation_id) # Best-effort human-readable slug from operation_id
h = _short_hash(operation_id or "", request_url or "") # Short hash ties log to the full operation and URL
# Compute how much room we have for the slug given the directory length
# Keep total path length reasonably below ~260 on Windows.
max_total_path = 240
prefix = f"{timestamp}_"
suffix = f"_{h}.log"
if not slug:
slug = "op"
max_filename_len = max(60, max_total_path - len(log_dir) - 1)
max_slug_len = max(8, max_filename_len - len(prefix) - len(suffix))
if len(slug) > max_slug_len:
slug = slug[:max_slug_len].rstrip(" ._-")
return os.path.join(log_dir, f"{prefix}{slug}{suffix}")
def _format_data_for_logging(data: Any) -> str:
"""Helper to format data (dict, str, bytes) for logging."""
if isinstance(data, bytes):
try:
return data.decode('utf-8') # Try to decode as text
return data.decode("utf-8") # Try to decode as text
except UnicodeDecodeError:
return f"[Binary data of length {len(data)} bytes]"
elif isinstance(data, (dict, list)):
try:
return json.dumps(data, indent=2, ensure_ascii=False)
except TypeError:
return str(data) # Fallback for non-serializable objects
return str(data) # Fallback for non-serializable objects
return str(data)
def log_request_response(
operation_id: str,
request_method: str,
request_url: str,
request_headers: dict | None = None,
request_params: dict | None = None,
request_data: any = None,
request_data: Any = None,
response_status_code: int | None = None,
response_headers: dict | None = None,
response_content: any = None,
error_message: str | None = None
response_content: Any = None,
error_message: str | None = None,
):
"""
Logs API request and response details to a file in the temp/api_logs directory.
Filenames are sanitized and length-limited for cross-platform safety.
If we still fail to write, we fall back to appending into api.log.
"""
log_dir = get_log_directory()
timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S_%f")
filename = f"{timestamp}_{operation_id.replace('/', '_').replace(':', '_')}.log"
filepath = os.path.join(log_dir, filename)
log_content = []
filepath = _build_log_filepath(log_dir, operation_id, request_url)
log_content: list[str] = []
log_content.append(f"Timestamp: {datetime.datetime.now().isoformat()}")
log_content.append(f"Operation ID: {operation_id}")
log_content.append("-" * 30 + " REQUEST " + "-" * 30)
@ -69,7 +106,7 @@ def log_request_response(
log_content.append(f"Headers:\n{_format_data_for_logging(request_headers)}")
if request_params:
log_content.append(f"Params:\n{_format_data_for_logging(request_params)}")
if request_data:
if request_data is not None:
log_content.append(f"Data/Body:\n{_format_data_for_logging(request_data)}")
log_content.append("\n" + "-" * 30 + " RESPONSE " + "-" * 30)
@ -77,7 +114,7 @@ def log_request_response(
log_content.append(f"Status Code: {response_status_code}")
if response_headers:
log_content.append(f"Headers:\n{_format_data_for_logging(response_headers)}")
if response_content:
if response_content is not None:
log_content.append(f"Content:\n{_format_data_for_logging(response_content)}")
if error_message:
log_content.append(f"Error:\n{error_message}")
@ -89,6 +126,7 @@ def log_request_response(
except Exception as e:
logger.error(f"Error writing API log to {filepath}: {e}")
if __name__ == '__main__':
# Example usage (for testing the logger directly)
logger.setLevel(logging.DEBUG)

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@ -1,24 +1,34 @@
import torch
import comfy.model_management
from typing_extensions import override
from comfy_api.latest import ComfyExtension, io
from kornia.morphology import dilation, erosion, opening, closing, gradient, top_hat, bottom_hat
import kornia.color
class Morphology:
class Morphology(io.ComfyNode):
@classmethod
def INPUT_TYPES(s):
return {"required": {"image": ("IMAGE",),
"operation": (["erode", "dilate", "open", "close", "gradient", "bottom_hat", "top_hat"],),
"kernel_size": ("INT", {"default": 3, "min": 3, "max": 999, "step": 1}),
}}
def define_schema(cls):
return io.Schema(
node_id="Morphology",
display_name="ImageMorphology",
category="image/postprocessing",
inputs=[
io.Image.Input("image"),
io.Combo.Input(
"operation",
options=["erode", "dilate", "open", "close", "gradient", "bottom_hat", "top_hat"],
),
io.Int.Input("kernel_size", default=3, min=3, max=999, step=1),
],
outputs=[
io.Image.Output(),
],
)
RETURN_TYPES = ("IMAGE",)
FUNCTION = "process"
CATEGORY = "image/postprocessing"
def process(self, image, operation, kernel_size):
@classmethod
def execute(cls, image, operation, kernel_size) -> io.NodeOutput:
device = comfy.model_management.get_torch_device()
kernel = torch.ones(kernel_size, kernel_size, device=device)
image_k = image.to(device).movedim(-1, 1)
@ -39,49 +49,63 @@ class Morphology:
else:
raise ValueError(f"Invalid operation {operation} for morphology. Must be one of 'erode', 'dilate', 'open', 'close', 'gradient', 'tophat', 'bottomhat'")
img_out = output.to(comfy.model_management.intermediate_device()).movedim(1, -1)
return (img_out,)
return io.NodeOutput(img_out)
class ImageRGBToYUV:
class ImageRGBToYUV(io.ComfyNode):
@classmethod
def INPUT_TYPES(s):
return {"required": { "image": ("IMAGE",),
}}
def define_schema(cls):
return io.Schema(
node_id="ImageRGBToYUV",
category="image/batch",
inputs=[
io.Image.Input("image"),
],
outputs=[
io.Image.Output(display_name="Y"),
io.Image.Output(display_name="U"),
io.Image.Output(display_name="V"),
],
)
RETURN_TYPES = ("IMAGE", "IMAGE", "IMAGE")
RETURN_NAMES = ("Y", "U", "V")
FUNCTION = "execute"
CATEGORY = "image/batch"
def execute(self, image):
@classmethod
def execute(cls, image) -> io.NodeOutput:
out = kornia.color.rgb_to_ycbcr(image.movedim(-1, 1)).movedim(1, -1)
return (out[..., 0:1].expand_as(image), out[..., 1:2].expand_as(image), out[..., 2:3].expand_as(image))
return io.NodeOutput(out[..., 0:1].expand_as(image), out[..., 1:2].expand_as(image), out[..., 2:3].expand_as(image))
class ImageYUVToRGB:
class ImageYUVToRGB(io.ComfyNode):
@classmethod
def INPUT_TYPES(s):
return {"required": {"Y": ("IMAGE",),
"U": ("IMAGE",),
"V": ("IMAGE",),
}}
def define_schema(cls):
return io.Schema(
node_id="ImageYUVToRGB",
category="image/batch",
inputs=[
io.Image.Input("Y"),
io.Image.Input("U"),
io.Image.Input("V"),
],
outputs=[
io.Image.Output(),
],
)
RETURN_TYPES = ("IMAGE",)
FUNCTION = "execute"
CATEGORY = "image/batch"
def execute(self, Y, U, V):
@classmethod
def execute(cls, Y, U, V) -> io.NodeOutput:
image = torch.cat([torch.mean(Y, dim=-1, keepdim=True), torch.mean(U, dim=-1, keepdim=True), torch.mean(V, dim=-1, keepdim=True)], dim=-1)
out = kornia.color.ycbcr_to_rgb(image.movedim(-1, 1)).movedim(1, -1)
return (out,)
return io.NodeOutput(out)
NODE_CLASS_MAPPINGS = {
"Morphology": Morphology,
"ImageRGBToYUV": ImageRGBToYUV,
"ImageYUVToRGB": ImageYUVToRGB,
}
NODE_DISPLAY_NAME_MAPPINGS = {
"Morphology": "ImageMorphology",
}
class MorphologyExtension(ComfyExtension):
@override
async def get_node_list(self) -> list[type[io.ComfyNode]]:
return [
Morphology,
ImageRGBToYUV,
ImageYUVToRGB,
]
async def comfy_entrypoint() -> MorphologyExtension:
return MorphologyExtension()

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@ -115,6 +115,7 @@ if os.name == "nt":
os.environ['MIMALLOC_PURGE_DELAY'] = '0'
if __name__ == "__main__":
os.environ['TORCH_ROCM_AOTRITON_ENABLE_EXPERIMENTAL'] = '1'
if args.default_device is not None:
default_dev = args.default_device
devices = list(range(32))