Track bundled vendor runtime sources
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2026-07-07 10:05:50 +08:00
parent fbe179ab53
commit 52636c91ae
2111 changed files with 1850012 additions and 14 deletions

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import asyncio
import contextlib
import logging
import time
import uuid
from io import BytesIO
from urllib.parse import urlparse
import aiohttp
import torch
from pydantic import BaseModel, Field
from comfy_api.latest import IO, Input, Types
from . import request_logger
from ._helpers import is_processing_interrupted, sleep_with_interrupt
from .client import (
ApiEndpoint,
_diagnose_connectivity,
_display_time_progress,
sync_op,
)
from .common_exceptions import ApiServerError, LocalNetworkError, ProcessingInterrupted
from .conversions import (
audio_ndarray_to_bytesio,
audio_tensor_to_contiguous_ndarray,
tensor_to_bytesio,
)
class UploadRequest(BaseModel):
file_name: str = Field(..., description="Filename to upload")
content_type: str | None = Field(
None,
description="Mime type of the file. For example: image/png, image/jpeg, video/mp4, etc.",
)
class UploadResponse(BaseModel):
download_url: str = Field(..., description="URL to GET uploaded file")
upload_url: str = Field(..., description="URL to PUT file to upload")
async def upload_images_to_comfyapi(
cls: type[IO.ComfyNode],
image: torch.Tensor | list[torch.Tensor],
*,
max_images: int = 8,
mime_type: str | None = None,
wait_label: str | None = "Uploading",
show_batch_index: bool = True,
total_pixels: int | None = 2048 * 2048,
) -> list[str]:
"""
Uploads images to ComfyUI API and returns download URLs.
To upload multiple images, stack them in the batch dimension first.
"""
tensors: list[torch.Tensor] = []
if isinstance(image, list):
for img in image:
is_batch = len(img.shape) > 3
if is_batch:
tensors.extend(img[i] for i in range(img.shape[0]))
else:
tensors.append(img)
else:
is_batch = len(image.shape) > 3
if is_batch:
tensors.extend(image[i] for i in range(image.shape[0]))
else:
tensors.append(image)
# if batched, try to upload each file if max_images is greater than 0
download_urls: list[str] = []
num_to_upload = min(len(tensors), max_images)
batch_start_ts = time.monotonic()
for idx in range(num_to_upload):
tensor = tensors[idx]
img_io = tensor_to_bytesio(tensor, total_pixels=total_pixels, mime_type=mime_type)
effective_label = wait_label
if wait_label and show_batch_index and num_to_upload > 1:
effective_label = f"{wait_label} ({idx + 1}/{num_to_upload})"
url = await upload_file_to_comfyapi(cls, img_io, img_io.name, mime_type, effective_label, batch_start_ts)
download_urls.append(url)
return download_urls
async def upload_image_to_comfyapi(
cls: type[IO.ComfyNode],
image: torch.Tensor,
*,
mime_type: str | None = None,
wait_label: str | None = "Uploading",
total_pixels: int | None = 2048 * 2048,
) -> str:
"""Uploads a single image to ComfyUI API and returns its download URL."""
return (
await upload_images_to_comfyapi(
cls,
image,
max_images=1,
mime_type=mime_type,
wait_label=wait_label,
show_batch_index=False,
total_pixels=total_pixels,
)
)[0]
async def upload_audio_to_comfyapi(
cls: type[IO.ComfyNode],
audio: Input.Audio,
*,
container_format: str = "mp4",
codec_name: str = "aac",
mime_type: str = "audio/mp4",
) -> str:
"""
Uploads a single audio input to ComfyUI API and returns its download URL.
Encodes the raw waveform into the specified format before uploading.
"""
sample_rate: int = audio["sample_rate"]
waveform: torch.Tensor = audio["waveform"]
audio_data_np = audio_tensor_to_contiguous_ndarray(waveform)
audio_bytes_io = audio_ndarray_to_bytesio(audio_data_np, sample_rate, container_format, codec_name)
return await upload_file_to_comfyapi(cls, audio_bytes_io, f"{uuid.uuid4()}.{container_format}", mime_type)
async def upload_video_to_comfyapi(
cls: type[IO.ComfyNode],
video: Input.Video,
*,
container: Types.VideoContainer = Types.VideoContainer.MP4,
codec: Types.VideoCodec = Types.VideoCodec.H264,
max_duration: int | None = None,
wait_label: str | None = "Uploading",
) -> str:
"""
Uploads a single video to ComfyUI API and returns its download URL.
Uses the specified container and codec for saving the video before upload.
"""
if max_duration is not None:
try:
actual_duration = video.get_duration()
if actual_duration > max_duration:
raise ValueError(
f"Video duration ({actual_duration:.2f}s) exceeds the maximum allowed ({max_duration}s)."
)
except Exception as e:
logging.error("Error getting video duration: %s", str(e))
raise ValueError(f"Could not verify video duration from source: {e}") from e
upload_mime_type = f"video/{container.value.lower()}"
filename = f"{uuid.uuid4()}.{container.value.lower()}"
# Convert VideoInput to BytesIO using specified container/codec
video_bytes_io = BytesIO()
video.save_to(video_bytes_io, format=container, codec=codec)
video_bytes_io.seek(0)
return await upload_file_to_comfyapi(cls, video_bytes_io, filename, upload_mime_type, wait_label)
_3D_MIME_TYPES = {
"glb": "model/gltf-binary",
"obj": "model/obj",
"fbx": "application/octet-stream",
}
async def upload_3d_model_to_comfyapi(
cls: type[IO.ComfyNode],
model_3d: Types.File3D,
file_format: str,
) -> str:
"""Uploads a 3D model file to ComfyUI API and returns its download URL."""
return await upload_file_to_comfyapi(
cls,
model_3d.get_data(),
f"{uuid.uuid4()}.{file_format}",
_3D_MIME_TYPES.get(file_format, "application/octet-stream"),
)
async def upload_file_to_comfyapi(
cls: type[IO.ComfyNode],
file_bytes_io: BytesIO,
filename: str,
upload_mime_type: str | None,
wait_label: str | None = "Uploading",
progress_origin_ts: float | None = None,
) -> str:
"""Uploads a single file to ComfyUI API and returns its download URL."""
if upload_mime_type is None:
request_object = UploadRequest(file_name=filename)
else:
request_object = UploadRequest(file_name=filename, content_type=upload_mime_type)
create_resp = await sync_op(
cls,
endpoint=ApiEndpoint(path="/customers/storage", method="POST"),
data=request_object,
response_model=UploadResponse,
final_label_on_success=None,
monitor_progress=False,
)
await upload_file(
cls,
create_resp.upload_url,
file_bytes_io,
content_type=upload_mime_type,
wait_label=wait_label,
progress_origin_ts=progress_origin_ts,
)
return create_resp.download_url
async def upload_file(
cls: type[IO.ComfyNode],
upload_url: str,
file: BytesIO | str,
*,
content_type: str | None = None,
max_retries: int = 3,
retry_delay: float = 1.0,
retry_backoff: float = 2.0,
wait_label: str | None = None,
progress_origin_ts: float | None = None,
) -> None:
"""
Upload a file to a signed URL (e.g., S3 pre-signed PUT) with retries, Comfy progress display, and interruption.
Raises:
ProcessingInterrupted, LocalNetworkError, ApiServerError, Exception
"""
if isinstance(file, BytesIO):
with contextlib.suppress(Exception):
file.seek(0)
data = file.read()
elif isinstance(file, str):
with open(file, "rb") as f:
data = f.read()
else:
raise ValueError("file must be a BytesIO or a filesystem path string")
headers: dict[str, str] = {}
skip_auto_headers: set[str] = set()
if content_type:
headers["Content-Type"] = content_type
else:
skip_auto_headers.add("Content-Type") # Don't let aiohttp add Content-Type, it can break the signed request
attempt = 0
delay = retry_delay
start_ts = progress_origin_ts if progress_origin_ts is not None else time.monotonic()
op_uuid = uuid.uuid4().hex[:8]
while True:
attempt += 1
operation_id = _generate_operation_id("PUT", upload_url, attempt, op_uuid)
timeout = aiohttp.ClientTimeout(total=None)
stop_evt = asyncio.Event()
async def _monitor():
try:
while not stop_evt.is_set():
if is_processing_interrupted():
return
if wait_label:
_display_time_progress(cls, wait_label, int(time.monotonic() - start_ts), None)
await asyncio.sleep(1.0)
except asyncio.CancelledError:
return
monitor_task = asyncio.create_task(_monitor())
sess: aiohttp.ClientSession | None = None
try:
request_logger.log_request_response(
operation_id=operation_id,
request_method="PUT",
request_url=upload_url,
request_headers=headers or None,
request_params=None,
request_data=f"[File data {len(data)} bytes]",
)
sess = aiohttp.ClientSession(timeout=timeout)
req = sess.put(upload_url, data=data, headers=headers, skip_auto_headers=skip_auto_headers)
req_task = asyncio.create_task(req)
done, pending = await asyncio.wait({req_task, monitor_task}, return_when=asyncio.FIRST_COMPLETED)
if monitor_task in done and req_task in pending:
req_task.cancel()
raise ProcessingInterrupted("Upload cancelled")
try:
resp = await req_task
except asyncio.CancelledError:
raise ProcessingInterrupted("Upload cancelled") from None
async with resp:
if resp.status >= 400:
with contextlib.suppress(Exception):
try:
body = await resp.json()
except Exception:
body = await resp.text()
msg = f"Upload failed with status {resp.status}"
request_logger.log_request_response(
operation_id=operation_id,
request_method="PUT",
request_url=upload_url,
response_status_code=resp.status,
response_headers=dict(resp.headers),
response_content=body,
error_message=msg,
)
if resp.status in {408, 429, 500, 502, 503, 504} and attempt <= max_retries:
await sleep_with_interrupt(
delay,
cls,
wait_label,
start_ts,
None,
display_callback=_display_time_progress if wait_label else None,
)
delay *= retry_backoff
continue
raise Exception(f"Failed to upload (HTTP {resp.status}).")
request_logger.log_request_response(
operation_id=operation_id,
request_method="PUT",
request_url=upload_url,
response_status_code=resp.status,
response_headers=dict(resp.headers),
response_content="File uploaded successfully.",
)
return
except asyncio.CancelledError:
raise ProcessingInterrupted("Task cancelled") from None
except (aiohttp.ClientError, OSError) as e:
if attempt <= max_retries:
request_logger.log_request_response(
operation_id=operation_id,
request_method="PUT",
request_url=upload_url,
request_headers=headers or None,
request_data=f"[File data {len(data)} bytes]",
error_message=f"{type(e).__name__}: {str(e)} (will retry)",
)
await sleep_with_interrupt(
delay,
cls,
wait_label,
start_ts,
None,
display_callback=_display_time_progress if wait_label else None,
)
delay *= retry_backoff
continue
diag = await _diagnose_connectivity()
if not diag["internet_accessible"]:
raise LocalNetworkError(
"Unable to connect to the network. Please check your internet connection and try again."
) from e
raise ApiServerError("The API service appears unreachable at this time.") from e
finally:
stop_evt.set()
if monitor_task:
monitor_task.cancel()
with contextlib.suppress(Exception):
await monitor_task
if sess:
with contextlib.suppress(Exception):
await sess.close()
def _generate_operation_id(method: str, url: str, attempt: int, op_uuid: str) -> str:
try:
parsed = urlparse(url)
slug = (parsed.path.rsplit("/", 1)[-1] or parsed.netloc or "upload").strip("/").replace("/", "_")
except Exception:
slug = "upload"
return f"{method}_{slug}_{op_uuid}_try{attempt}"