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[Partner Nodes] feat(BFL): add Flux 3 video model (#15295) 

* [Partner Nodes] feat(BFL): add Flux 3 video model

Signed-off-by: Alexander Piskun <bigcat88@icloud.com>

* [Partner Nodes] fix(BFL): harden keyframe value check

Signed-off-by: Alexander Piskun <bigcat88@icloud.com>

---------

Signed-off-by: Alexander Piskun <bigcat88@icloud.com>
Co-authored-by: Jedrzej Kosinski <kosinkadink1@gmail.com>
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Alexander Piskun 2026-08-05 03:26:10 +03:00 committed by GitHub
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2 changed files with 426 additions and 1 deletions
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36
comfy_api_nodes/apis/bfl.py
View File

@ -1,7 +1,7 @@
from enum import Enum
from typing import Any
from pydantic import BaseModel, Field
from pydantic import BaseModel, ConfigDict, Field
class BFLFluxExpandImageRequest(BaseModel):
@ -121,6 +121,8 @@ class BFLFluxProGenerateResponse(BaseModel):
class BFLStatus(str, Enum):
task_not_found = "Task not found"
pending = "Pending"
reasoning = "Reasoning"
generating = "Generating"
request_moderated = "Request Moderated"
content_moderated = "Content Moderated"
ready = "Ready"
@ -132,3 +134,35 @@ class BFLFluxStatusResponse(BaseModel):
status: BFLStatus = Field(...)
result: dict[str, Any] | None = Field(None)
progress: float | None = Field(None, ge=0.0, le=1.0)
class Flux3VideoRequest(BaseModel):
"""Fields shared by every generation mode of /v1/flux-3-video."""
model_config = ConfigDict(extra="forbid")
prompt: str = Field(...)
aspect_ratio: str = Field("auto")
duration: int | str = Field("auto", description="Whole seconds, or 'auto'.")
resolution: str = Field("hd", description="'hd' is the 720p class, 'fhd' the 1080p class.")
generate_audio: bool = Field(True)
safety_tolerance: int = Field(2, description="0 is the strictest; conditioned modes cap at 2.")
class Flux3TextToVideoRequest(Flux3VideoRequest):
mode: str = Field("t2v")
class Flux3ImageToVideoRequest(Flux3VideoRequest):
mode: str = Field("i2v")
keyframes: list[str] | list[tuple[float, str]] = Field(
...,
description="Images (URL or base64), or [seconds, image] pairs pinning each to a time.",
)
class Flux3VideoContinuationRequest(Flux3VideoRequest):
mode: str = Field("v2v")
start_video: str = Field(
..., description="MP4 (URL or base64); the new clip carries on from its final frames."
)

391
comfy_api_nodes/nodes_bfl.py
View File

@ -1,3 +1,5 @@
import math
import torch
from pydantic import BaseModel
from typing_extensions import override
@ -14,16 +16,23 @@ from comfy_api_nodes.apis.bfl import (
BFLFluxVTORequest,
BFLStatus,
Flux2ProGenerateRequest,
Flux3ImageToVideoRequest,
Flux3TextToVideoRequest,
Flux3VideoContinuationRequest,
Flux3VideoRequest,
)
from comfy_api_nodes.util import (
ApiEndpoint,
convert_mask_to_image,
download_url_to_image_tensor,
download_url_to_video_output,
get_number_of_images,
poll_op,
resize_mask_to_image,
sync_op,
tensor_to_base64_string,
upload_images_to_comfyapi,
upload_video_to_comfyapi,
validate_aspect_ratio_string,
validate_image_dimensions,
validate_string,
@ -1007,6 +1016,385 @@ class Flux2ImageNode(IO.ComfyNode):
return IO.NodeOutput(await download_url_to_image_tensor(response.result["sample"]))
_FLUX3_ASPECT_RATIOS = ["auto", "21:9", "2:1", "16:9", "4:3", "1:1", "3:4", "9:16"]
_FLUX3_MIN_DURATION = 5
_FLUX3_MAX_DURATION = 20
_FLUX3_DURATIONS = ["auto"] + [str(i) for i in range(_FLUX3_MIN_DURATION, _FLUX3_MAX_DURATION + 1)]
_FLUX3_RESOLUTIONS = {"720p": "hd", "1080p": "fhd"}
_FLUX3_MAX_IMAGES = 10
_FLUX3_MIN_IMAGE_SIDE = 256
_FLUX3_MAX_IMAGE_ASPECT = 64
def _flux3_validate_image(image: torch.Tensor) -> None:
validate_image_dimensions(image, min_width=_FLUX3_MIN_IMAGE_SIDE, min_height=_FLUX3_MIN_IMAGE_SIDE)
height, width = image.shape[-3], image.shape[-2]
if max(width, height) > _FLUX3_MAX_IMAGE_ASPECT * min(width, height):
raise ValueError(
f"Image aspect ratio is too extreme ({width}x{height}); "
f"FLUX 3 accepts at most {_FLUX3_MAX_IMAGE_ASPECT}:1."
)
def _flux3_collect_images(images: dict | None, field_name: str) -> list[torch.Tensor]:
"""Flatten Autogrow slots (each possibly batched) into single images and validate them."""
flat: list[torch.Tensor] = []
for tensor in (images or {}).values():
if tensor is None:
continue
if tensor.ndim == 4:
flat.extend(tensor[i] for i in range(tensor.shape[0]))
else:
flat.append(tensor)
if len(flat) > _FLUX3_MAX_IMAGES:
raise ValueError(f"FLUX 3 supports at most {_FLUX3_MAX_IMAGES} {field_name}, got {len(flat)}.")
for tensor in flat:
_flux3_validate_image(tensor)
return flat
def _flux3_parse_times(value: str, image_count: int, duration: int | str) -> list[float]:
"""Parse one keyframe time in seconds per image: increasing, inside the clip."""
parts = [part.strip() for part in value.split(",") if part.strip()]
if len(parts) != image_count:
raise ValueError(
f"Give one time per keyframe image: got {len(parts)} time(s) for {image_count} image(s)."
)
try:
times = [float(part) for part in parts]
except ValueError as exc:
raise ValueError(f"Keyframe times must be numbers in seconds, comma-separated; got '{value}'.") from exc
if not all(math.isfinite(time) for time in times):
raise ValueError(f"Keyframe times must be finite numbers in seconds; got '{value}'.")
if any(later <= earlier for earlier, later in zip(times, times[1:])):
raise ValueError(f"Keyframe times must increase; got {times}.")
if times[0] < 0:
raise ValueError(f"Keyframe times cannot be negative; got {times[0]}.")
cap = _FLUX3_MAX_DURATION if duration == "auto" else int(duration)
if times[-1] > cap:
raise ValueError(f"Keyframe time {times[-1]}s is past the end of a {cap}s clip.")
return times
class Flux3VideoNodeBase(IO.ComfyNode):
"""Shared widgets, request plumbing and polling for the FLUX 3 generation modes."""
RATE_HD: float
RATE_FHD: float
@classmethod
def common_inputs(cls) -> list:
return [
IO.Combo.Input(
"aspect_ratio",
options=_FLUX3_ASPECT_RATIOS,
default="auto",
tooltip="Output aspect ratio. 'auto' picks one from the prompt and inputs.",
),
IO.Combo.Input(
"duration",
options=_FLUX3_DURATIONS,
default="auto",
tooltip="Clip length in seconds. 'auto' fits the length to the content.",
),
IO.Combo.Input(
"resolution",
options=list(_FLUX3_RESOLUTIONS),
default="720p",
tooltip="Output resolution.",
),
IO.Boolean.Input(
"generate_audio",
default=True,
tooltip="Generate synchronized audio (ambient, speech, effects). "
"Off produces a video with no audio track.",
),
IO.Int.Input(
"safety_tolerance",
default=2,
min=0,
max=4,
advanced=True,
tooltip="Moderation tolerance, 0 is the strictest. Requests that send images or "
"video are capped at 2 whatever you set here.",
),
IO.Int.Input(
"seed",
default=42,
min=0,
max=0xFFFFFFFF,
control_after_generate=True,
tooltip="Seed to determine if node should re-run; FLUX 3 picks its own seed, so "
"actual results are nondeterministic regardless of this value.",
),
]
@classmethod
def common_fields(
cls,
prompt: str,
aspect_ratio: str,
duration: str,
resolution: str,
generate_audio: bool,
safety_tolerance: int,
) -> dict:
validate_string(prompt, field_name="prompt", min_length=1)
return {
"prompt": prompt,
"aspect_ratio": aspect_ratio,
"duration": duration if duration == "auto" else int(duration),
"resolution": _FLUX3_RESOLUTIONS[resolution],
"generate_audio": generate_audio,
"safety_tolerance": safety_tolerance,
}
@classmethod
def price_badge(cls) -> IO.PriceBadge:
return IO.PriceBadge(
depends_on=IO.PriceBadgeDepends(widgets=["resolution", "duration"]),
expr=f"""
(
$rate := widgets.resolution = "1080p" ? {cls.RATE_FHD} : {cls.RATE_HD};
$type(widgets.duration) = "string" and widgets.duration != "auto"
? {{"type":"usd","usd": $rate * $number(widgets.duration)}}
: {{"type":"usd","usd": $rate, "format": {{"suffix": "/second"}}}}
)
""",
)
async def _flux3_execute(cls: type[IO.ComfyNode], request: Flux3VideoRequest) -> IO.NodeOutput:
initial_response = await sync_op(
cls,
ApiEndpoint(path="/proxy/bfl/v1/flux-3-video", method="POST"),
response_model=BFLFluxProGenerateResponse,
data=request,
)
def price_extractor(_r: BaseModel) -> float | None:
return None if initial_response.cost is None else initial_response.cost / 100
response = await poll_op(
cls,
ApiEndpoint(initial_response.polling_url),
response_model=BFLFluxStatusResponse,
status_extractor=lambda r: r.status,
progress_extractor=lambda r: r.progress,
price_extractor=price_extractor,
completed_statuses=[BFLStatus.ready],
failed_statuses=[
BFLStatus.request_moderated,
BFLStatus.content_moderated,
BFLStatus.error,
BFLStatus.task_not_found,
],
queued_statuses=[BFLStatus.pending],
poll_interval=8.0,
# a failed task answers the poll with a retryable-class HTTP 5xx (500 and 503 observed);
# a small retry budget surfaces real failures quickly
max_retries_per_poll=3,
)
return IO.NodeOutput(await download_url_to_video_output(response.result["sample"]))
class Flux3TextToVideoNode(Flux3VideoNodeBase):
RATE_HD = 0.2431
RATE_FHD = 0.4147
@classmethod
def define_schema(cls) -> IO.Schema:
return IO.Schema(
node_id="Flux3TextToVideoNode",
display_name="Flux 3 Text to Video",
category="partner/video/BFL",
description="Generates a video with synchronized audio from a text prompt via FLUX 3.",
inputs=[
IO.String.Input(
"prompt",
multiline=True,
default="",
tooltip="What you want, in plain language; the prompt is interpreted and expanded "
"before generation. Describe ambient sound, music and speech separately for layered audio.",
),
*cls.common_inputs(),
],
outputs=[IO.Video.Output()],
hidden=[
IO.Hidden.auth_token_comfy_org,
IO.Hidden.api_key_comfy_org,
IO.Hidden.unique_id,
],
is_api_node=True,
price_badge=cls.price_badge(),
)
@classmethod
async def execute(
cls,
prompt: str,
aspect_ratio: str,
duration: str,
resolution: str,
generate_audio: bool,
safety_tolerance: int,
seed: int,
) -> IO.NodeOutput:
request = Flux3TextToVideoRequest(
**cls.common_fields(prompt, aspect_ratio, duration, resolution, generate_audio, safety_tolerance)
)
return await _flux3_execute(cls, request)
class Flux3ImageToVideoNode(Flux3VideoNodeBase):
RATE_HD = 0.2431
RATE_FHD = 0.4147
@classmethod
def define_schema(cls) -> IO.Schema:
return IO.Schema(
node_id="Flux3ImageToVideoNode",
display_name="Flux 3 Image to Video",
category="partner/video/BFL",
description="Animates 1 to 10 images with FLUX 3. Each image becomes a frame of the clip: "
"one image opens it, two morph from the first to the second, and more are spread across it "
"or pinned to times you choose.",
inputs=[
IO.String.Input(
"prompt",
multiline=True,
default="",
tooltip="How the scene should move and sound; the prompt is interpreted and "
"expanded before generation.",
),
IO.Autogrow.Input(
"keyframes",
template=IO.Autogrow.TemplatePrefix(
IO.Image.Input("image", tooltip="Keyframe image."),
prefix="image_",
min=1,
max=_FLUX3_MAX_IMAGES,
),
tooltip="1 to 10 images, in playback order. Minimum 256x256 pixels each.",
),
IO.DynamicCombo.Input(
"placement",
options=[
IO.DynamicCombo.Option("spread across the clip", []),
IO.DynamicCombo.Option(
"at times",
[
IO.String.Input(
"times",
default="0",
tooltip="One time in seconds per image, comma-separated and "
"increasing, e.g. '0, 2.5, 5'.",
),
],
),
],
tooltip="'spread across the clip' lets FLUX 3 place the images (one opens the clip, "
"two become its start and end); 'at times' pins every image to a second you choose.",
),
*cls.common_inputs(),
],
outputs=[IO.Video.Output()],
hidden=[
IO.Hidden.auth_token_comfy_org,
IO.Hidden.api_key_comfy_org,
IO.Hidden.unique_id,
],
is_api_node=True,
price_badge=cls.price_badge(),
)
@classmethod
async def execute(
cls,
prompt: str,
keyframes: IO.Autogrow.Type,
placement: dict,
aspect_ratio: str,
duration: str,
resolution: str,
generate_audio: bool,
safety_tolerance: int,
seed: int,
) -> IO.NodeOutput:
fields = cls.common_fields(prompt, aspect_ratio, duration, resolution, generate_audio, safety_tolerance)
images = _flux3_collect_images(keyframes, "keyframes")
if not images:
raise ValueError("Connect at least one keyframe image.")
times = None
if placement["placement"] == "at times":
times = _flux3_parse_times(placement["times"], len(images), fields["duration"])
elif len(images) >= 3 and fields["duration"] == "auto":
# spread images land evenly between the first and last, which needs a known length
raise ValueError(
f"Spreading {len(images)} images across the clip needs an explicit duration: "
"set duration, or place the images yourself with 'at times'."
)
urls = await upload_images_to_comfyapi(
cls, images, max_images=_FLUX3_MAX_IMAGES, wait_label="Uploading keyframes"
)
request = Flux3ImageToVideoRequest(
keyframes=list(zip(times, urls)) if times is not None else urls,
**fields,
)
return await _flux3_execute(cls, request)
class Flux3VideoContinuationNode(Flux3VideoNodeBase):
RATE_HD = 0.5863
RATE_FHD = 0.7579
@classmethod
def define_schema(cls) -> IO.Schema:
return IO.Schema(
node_id="Flux3VideoContinuationNode",
display_name="Flux 3 Video Continuation",
category="partner/video/BFL",
description="Continues a video with FLUX 3: the new clip carries on from the final frames "
"of the one you provide.",
inputs=[
IO.Video.Input("video", tooltip="The clip to continue."),
IO.String.Input(
"prompt",
multiline=True,
default="",
tooltip="What the continuation should show; the prompt is interpreted and expanded "
"before generation.",
),
*cls.common_inputs(),
],
outputs=[IO.Video.Output()],
hidden=[
IO.Hidden.auth_token_comfy_org,
IO.Hidden.api_key_comfy_org,
IO.Hidden.unique_id,
],
is_api_node=True,
price_badge=cls.price_badge(),
)
@classmethod
async def execute(
cls,
video: Input.Video,
prompt: str,
aspect_ratio: str,
duration: str,
resolution: str,
generate_audio: bool,
safety_tolerance: int,
seed: int,
) -> IO.NodeOutput:
fields = cls.common_fields(prompt, aspect_ratio, duration, resolution, generate_audio, safety_tolerance)
url = await upload_video_to_comfyapi(cls, video, wait_label="Uploading source video")
request = Flux3VideoContinuationRequest(start_video=url, **fields)
return await _flux3_execute(cls, request)
class BFLExtension(ComfyExtension):
@override
async def get_node_list(self) -> list[type[IO.ComfyNode]]:
@ -1021,6 +1409,9 @@ class BFLExtension(ComfyExtension):
Flux2ProImageNode,
Flux2MaxImageNode,
Flux2ImageNode,
Flux3TextToVideoNode,
Flux3ImageToVideoNode,
Flux3VideoContinuationNode,
]