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Add Minimax Image to Video node + Cleanup (#51)

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This commit is contained in:
Jedrzej Kosinski 2025-04-30 02:59:27 -05:00
parent c2187140e4
commit 0cd7d44f1c
1 changed files with 145 additions and 12 deletions
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157
comfy_api_nodes/nodes_minimax.py
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@ -1,4 +1,3 @@
from typing import Literal
from comfy.comfy_types.node_typing import IO
from comfy_api.input_impl.video_types import VideoFromFile
from comfy_api_nodes.apis import (
@ -6,6 +5,7 @@ from comfy_api_nodes.apis import (
MinimaxVideoGenerationResponse,
MinimaxFileRetrieveResponse,
MinimaxTaskResultResponse,
SubjectReferenceItem,
Model
)
from comfy_api_nodes.apis.client import (
@ -17,10 +17,11 @@ from comfy_api_nodes.apis.client import (
)
from comfy_api_nodes.nodes_api import (
download_url_to_bytesio,
upload_images_to_comfyapi,
)
import torch
import logging
import folder_paths
class MinimaxTextToVideoNode:
@ -28,10 +29,6 @@ class MinimaxTextToVideoNode:
Generates videos synchronously based on a prompt, and optional parameters using Minimax's API.
"""
def __init__(self):
self.output_dir = folder_paths.get_output_directory()
self.type: Literal["output"] = "output"
@classmethod
def INPUT_TYPES(s):
return {
@ -47,10 +44,7 @@ class MinimaxTextToVideoNode:
"model": (
[
"T2V-01",
"I2V-01-Director",
"S2V-01",
"I2V-01",
"I2V-01-live",
"T2V-01-Director",
],
{
"default": "T2V-01",
@ -87,8 +81,25 @@ class MinimaxTextToVideoNode:
prompt_text,
seed=0,
model="T2V-01",
image: torch.Tensor=None, # used for ImageToVideo
subject: torch.Tensor=None, # used for SubjectToVideo
auth_token=None,
):
'''
Function used between Minimax nodes - supports T2V, I2V, and S2V, based on provided arguments.
'''
# upload image, if passed in
image_url = None
if image is not None:
image_url = upload_images_to_comfyapi(image, max_images=1, auth_token=auth_token)[0]
# TODO: figure out how to deal with subject properly, API returns invalid params when using S2V-01 model
subject_reference = None
if subject is not None:
subject_url = upload_images_to_comfyapi(subject, max_images=1, auth_token=auth_token)[0]
subject_reference = [SubjectReferenceItem(image=subject_url)]
video_generate_operation = SynchronousOperation(
endpoint=ApiEndpoint(
path="/proxy/minimax/video_generation",
@ -100,8 +111,8 @@ class MinimaxTextToVideoNode:
model=Model(model),
prompt=prompt_text,
callback_url=None,
first_frame_image=None,
subject_reference=None,
first_frame_image=image_url,
subject_reference=subject_reference,
prompt_optimizer=None,
),
auth_token=auth_token,
@ -158,13 +169,135 @@ class MinimaxTextToVideoNode:
return (VideoFromFile(video_io),)
class MinimaxImageToVideoNode(MinimaxTextToVideoNode):
"""
Generates videos synchronously based on an image and prompt, and optional parameters using Minimax's API.
"""
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"image": (
IO.IMAGE,
{
"tooltip": "Image to use as first frame of video generation"
},
),
"prompt_text": (
"STRING",
{
"multiline": True,
"default": "",
"tooltip": "Text prompt to guide the video generation",
},
),
"model": (
[
"I2V-01-Director",
"I2V-01",
"I2V-01-live",
],
{
"default": "I2V-01",
"tooltip": "Model to use for video generation",
},
),
},
"optional": {
"seed": (
IO.INT,
{
"default": 0,
"min": 0,
"max": 0xFFFFFFFFFFFFFFFF,
"control_after_generate": True,
"tooltip": "The random seed used for creating the noise.",
},
),
},
"hidden": {
"auth_token": "AUTH_TOKEN_COMFY_ORG",
},
}
RETURN_TYPES = ("VIDEO",)
DESCRIPTION = "Generates videos from an image and prompts using Minimax's API"
FUNCTION = "generate_video"
CATEGORY = "api node/video/Minimax"
API_NODE = True
OUTPUT_NODE = True
class MinimaxSubjectToVideoNode(MinimaxTextToVideoNode):
"""
Generates videos synchronously based on an image and prompt, and optional parameters using Minimax's API.
"""
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"subject": (
IO.IMAGE,
{
"tooltip": "Image of subject to reference video generation"
},
),
"prompt_text": (
"STRING",
{
"multiline": True,
"default": "",
"tooltip": "Text prompt to guide the video generation",
},
),
"model": (
[
"S2V-01",
],
{
"default": "S2V-01",
"tooltip": "Model to use for video generation",
},
),
},
"optional": {
"seed": (
IO.INT,
{
"default": 0,
"min": 0,
"max": 0xFFFFFFFFFFFFFFFF,
"control_after_generate": True,
"tooltip": "The random seed used for creating the noise.",
},
),
},
"hidden": {
"auth_token": "AUTH_TOKEN_COMFY_ORG",
},
}
RETURN_TYPES = ("VIDEO",)
DESCRIPTION = "Generates videos from an image and prompts using Minimax's API"
FUNCTION = "generate_video"
CATEGORY = "api node/video/Minimax"
API_NODE = True
OUTPUT_NODE = True
# A dictionary that contains all nodes you want to export with their names
# NOTE: names should be globally unique
NODE_CLASS_MAPPINGS = {
"MinimaxTextToVideoNode": MinimaxTextToVideoNode,
"MinimaxImageToVideoNode": MinimaxImageToVideoNode,
# "MinimaxSubjectToVideoNode": MinimaxSubjectToVideoNode,
}
# A dictionary that contains the friendly/humanly readable titles for the nodes
NODE_DISPLAY_NAME_MAPPINGS = {
"MinimaxTextToVideoNode": "Minimax Text to Video",
"MinimaxImageToVideoNode": "Minimax Image to Video",
"MinimaxSubjectToVideoNode": "Minimax Subject to Video",
}