[Partner Nodes] chore(Google): drop retiring Veo 2 and Veo 3.0 models (#15883)

Signed-off-by: Alexander Piskun <bigcat88@icloud.com>
This commit is contained in:
Alexander Piskun
2026-08-26 12:30:06 +04:00
committed by GitHub
parent 12d5279438
commit b133e48368

View File

@@ -23,231 +23,12 @@ from comfy_api_nodes.util import (
AVERAGE_DURATION_VIDEO_GEN = 32
MODELS_MAP = {
"veo-2.0-generate-001": "veo-2.0-generate-001",
"veo-3.1-generate": "veo-3.1-generate-001",
"veo-3.1-fast-generate": "veo-3.1-fast-generate-001",
"veo-3.1-lite": "veo-3.1-lite-generate-001",
"veo-3.0-generate-001": "veo-3.0-generate-001",
"veo-3.0-fast-generate-001": "veo-3.0-fast-generate-001",
}
class VeoVideoGenerationNode(IO.ComfyNode):
"""
Generates videos from text prompts using Google's Veo API.
This node can create videos from text descriptions and optional image inputs,
with control over parameters like aspect ratio, duration, and more.
"""
@classmethod
def define_schema(cls):
return IO.Schema(
node_id="VeoVideoGenerationNode",
display_name="Google Veo 2 Video Generation",
category="partner/video/Veo",
description="Generates videos from text prompts using Google's Veo 2 API",
inputs=[
IO.String.Input(
"prompt",
multiline=True,
default="",
tooltip="Text description of the video",
),
IO.Combo.Input(
"aspect_ratio",
options=["16:9", "9:16"],
default="16:9",
tooltip="Aspect ratio of the output video",
),
IO.String.Input(
"negative_prompt",
multiline=True,
default="",
tooltip="Negative text prompt to guide what to avoid in the video",
optional=True,
),
IO.Int.Input(
"duration_seconds",
default=5,
min=5,
max=8,
step=1,
display_mode=IO.NumberDisplay.number,
tooltip="Duration of the output video in seconds",
optional=True,
),
IO.Boolean.Input(
"enhance_prompt",
default=True,
tooltip="Whether to enhance the prompt with AI assistance",
optional=True,
advanced=True,
),
IO.Combo.Input(
"person_generation",
options=["ALLOW", "BLOCK"],
default="ALLOW",
tooltip="Whether to allow generating people in the video",
optional=True,
advanced=True,
),
IO.Int.Input(
"seed",
default=0,
min=0,
max=0xFFFFFFFF,
step=1,
display_mode=IO.NumberDisplay.number,
control_after_generate=True,
tooltip="Seed for video generation (0 for random)",
optional=True,
),
IO.Image.Input(
"image",
tooltip="Optional reference image to guide video generation",
optional=True,
),
IO.Combo.Input(
"model",
options=["veo-2.0-generate-001"],
default="veo-2.0-generate-001",
tooltip="Veo 2 model to use for video generation",
optional=True,
),
],
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=IO.PriceBadge(
depends_on=IO.PriceBadgeDepends(widgets=["duration_seconds"]),
expr="""{"type":"usd","usd": 0.5 * widgets.duration_seconds}""",
),
)
@classmethod
async def execute(
cls,
prompt,
aspect_ratio="16:9",
negative_prompt="",
duration_seconds=5,
enhance_prompt=True,
person_generation="ALLOW",
seed=0,
image=None,
model="veo-2.0-generate-001",
generate_audio=False,
):
model = MODELS_MAP[model]
# Prepare the instances for the request
instances = []
instance = {"prompt": prompt}
# Add image if provided
if image is not None:
image_base64 = tensor_to_base64_string(image)
if image_base64:
instance["image"] = {"bytesBase64Encoded": image_base64, "mimeType": "image/png"}
instances.append(instance)
# Create parameters dictionary
parameters = {
"aspectRatio": aspect_ratio,
"personGeneration": person_generation,
"durationSeconds": duration_seconds,
"enhancePrompt": enhance_prompt,
}
# Add optional parameters if provided
if negative_prompt:
parameters["negativePrompt"] = negative_prompt
if seed > 0:
parameters["seed"] = seed
# Only add generateAudio for Veo 3 models
if model.find("veo-2.0") == -1:
parameters["generateAudio"] = generate_audio
# force "enhance_prompt" to True for Veo3 models
parameters["enhancePrompt"] = True
initial_response = await sync_op(
cls,
ApiEndpoint(path=f"/proxy/veo/{model}/generate", method="POST"),
response_model=VeoGenVidResponse,
data=VeoGenVidRequest(
instances=instances,
parameters=parameters,
),
)
def status_extractor(response):
# Only return "completed" if the operation is done, regardless of success or failure
# We'll check for errors after polling completes
return "completed" if response.done else "pending"
poll_response = await poll_op(
cls,
ApiEndpoint(path=f"/proxy/veo/{model}/poll", method="POST"),
response_model=VeoGenVidPollResponse,
status_extractor=status_extractor,
data=VeoGenVidPollRequest(
operationName=initial_response.name,
),
poll_interval=5.0,
estimated_duration=AVERAGE_DURATION_VIDEO_GEN,
)
# Now check for errors in the final response
# Check for error in poll response
if poll_response.error:
raise Exception(f"Veo API error: {poll_response.error.message} (code: {poll_response.error.code})")
# Check for RAI filtered content
if (
hasattr(poll_response.response, "raiMediaFilteredCount")
and poll_response.response.raiMediaFilteredCount > 0
):
# Extract reason message if available
if (
hasattr(poll_response.response, "raiMediaFilteredReasons")
and poll_response.response.raiMediaFilteredReasons
):
reason = poll_response.response.raiMediaFilteredReasons[0]
error_message = f"Content filtered by Google's Responsible AI practices: {reason} ({poll_response.response.raiMediaFilteredCount} videos filtered.)"
else:
error_message = f"Content filtered by Google's Responsible AI practices ({poll_response.response.raiMediaFilteredCount} videos filtered.)"
raise Exception(error_message)
# Extract video data
if (
poll_response.response
and hasattr(poll_response.response, "videos")
and poll_response.response.videos
and len(poll_response.response.videos) > 0
):
video = poll_response.response.videos[0]
# Check if video is provided as base64 or URL
if hasattr(video, "bytesBase64Encoded") and video.bytesBase64Encoded:
return IO.NodeOutput(InputImpl.VideoFromFile(BytesIO(base64.b64decode(video.bytesBase64Encoded))))
if hasattr(video, "gcsUri") and video.gcsUri:
return IO.NodeOutput(await download_url_to_video_output(video.gcsUri))
raise Exception("Video returned but no data or URL was provided")
raise Exception("Video generation completed but no video was returned")
class Veo3VideoGenerationNode(IO.ComfyNode):
"""Generates videos from text prompts using Google's Veo 3 API."""
@@ -275,7 +56,7 @@ class Veo3VideoGenerationNode(IO.ComfyNode):
"resolution",
options=["720p", "1080p", "4k"],
default="720p",
tooltip="Output video resolution. 4K is not available for veo-3.1-lite and veo-3.0 models.",
tooltip="Output video resolution. 4K is not available for the veo-3.1-lite model.",
optional=True,
),
IO.String.Input(
@@ -328,13 +109,7 @@ class Veo3VideoGenerationNode(IO.ComfyNode):
),
IO.Combo.Input(
"model",
options=[
"veo-3.1-generate",
"veo-3.1-fast-generate",
"veo-3.1-lite",
"veo-3.0-generate-001",
"veo-3.0-fast-generate-001",
],
options=["veo-3.1-generate", "veo-3.1-fast-generate", "veo-3.1-lite"],
tooltip="Veo 3 model to use for video generation",
optional=True,
),
@@ -365,13 +140,9 @@ class Veo3VideoGenerationNode(IO.ComfyNode):
$pps :=
$contains($m, "lite")
? ($r = "1080p" ? ($a ? 0.08 : 0.05) : ($a ? 0.05 : 0.03))
: $contains($m, "3.1-fast")
: $contains($m, "fast")
? ($r = "4k" ? ($a ? 0.30 : 0.25) : $r = "1080p" ? ($a ? 0.12 : 0.10) : ($a ? 0.10 : 0.08))
: $contains($m, "3.1-generate")
? ($r = "4k" ? ($a ? 0.60 : 0.40) : ($a ? 0.40 : 0.20))
: $contains($m, "3.0-fast")
? ($a ? 0.15 : 0.10)
: ($a ? 0.40 : 0.20);
: ($r = "4k" ? ($a ? 0.60 : 0.40) : ($a ? 0.40 : 0.20));
{"type":"usd","usd": $pps * $seconds}
)
""",
@@ -390,11 +161,11 @@ class Veo3VideoGenerationNode(IO.ComfyNode):
person_generation="ALLOW",
seed=0,
image=None,
model="veo-3.0-generate-001",
model="veo-3.1-generate",
generate_audio=False,
):
if resolution == "4k" and ("lite" in model or "3.0" in model):
raise Exception("4K resolution is not supported by the veo-3.1-lite or veo-3.0 models.")
if resolution == "4k" and "lite" in model:
raise Exception("4K resolution is not supported by the veo-3.1-lite model.")
model = MODELS_MAP[model]
@@ -410,13 +181,12 @@ class Veo3VideoGenerationNode(IO.ComfyNode):
"durationSeconds": duration_seconds,
"enhancePrompt": True,
"generateAudio": generate_audio,
"resolution": resolution,
}
if negative_prompt:
parameters["negativePrompt"] = negative_prompt
if seed > 0:
parameters["seed"] = seed
if "veo-3.1" in model:
parameters["resolution"] = resolution
initial_response = await sync_op(
cls,
@@ -635,7 +405,6 @@ class VeoExtension(ComfyExtension):
@override
async def get_node_list(self) -> list[type[IO.ComfyNode]]:
return [
VeoVideoGenerationNode,
Veo3VideoGenerationNode,
Veo3FirstLastFrameNode,
]