jason.mei
db0b8fa266
- Add SoraText2VideoNode for OpenAI Sora2 text-to-video generation * Support both standard and Pro model variants * Configurable video size, duration, and prompt parameters * Pro version supports extended resolution options (1024x1792, 1792x1024) - Add SoraImg2VideoNode for OpenAI Sora2 image-to-video generation * Support both standard and Pro model variants * Accept first frame as image or URL input * Pro version supports 1080p resolution - Implement async task polling with configurable retry logic - Integrate with ModelverseClient for API communication - Add comprehensive input validation and error handling - Follow established video generation patterns from Vidu and Wan AI nodes
123 lines
4.5 KiB
Python
123 lines
4.5 KiB
Python
"""
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OpenAI Sora2 Img2Video - 图生视频模型
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Models: openai/sora-2/image-to-video, openai/sora-2/image-to-video-pro
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"""
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import time
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from .modelverse_api.client import ModelverseClient
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from .modelverse_api.utils import image_to_base64
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from comfy.comfy_types.node_typing import IO
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MODELS = ["openai/sora-2/image-to-video", "openai/sora-2/image-to-video-pro"]
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RESOLUTIONS_PRO = ["720p", "1080p"]
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DURATIONS = [4, 8, 12]
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class SoraImg2VideoNode:
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"""
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OpenAI Sora2 Img2Video - 图生视频
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Models: image-to-video (普通版), image-to-video-pro (Pro版，支持1080p)
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"""
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@classmethod
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def INPUT_TYPES(cls):
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return {
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"required": {
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"client": ("MODELVERSE_API_CLIENT",),
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"model": (MODELS, {"default": "openai/sora-2/image-to-video", "tooltip": "image-to-video: 普通版, image-to-video-pro: Pro版(支持1080p)"}),
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},
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"optional": {
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"first_frame_image": (IO.IMAGE, {"tooltip": "首帧图片"}),
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"first_frame_url": (IO.STRING, {"default": "", "tooltip": "首帧图片URL (与image二选一)"}),
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"prompt": (IO.STRING, {"multiline": True, "default": "", "tooltip": "提示词，用于指导视频生成"}),
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"resolution": (RESOLUTIONS_PRO, {"default": "720p", "tooltip": "分辨率 (Pro版支持1080p)"}),
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"duration": (DURATIONS, {"default": 4, "tooltip": "视频时长(秒): 4, 8, 12"}),
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}
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}
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RETURN_TYPES = (IO.STRING, IO.STRING)
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RETURN_NAMES = ("url", "task_id")
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FUNCTION = "generate"
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CATEGORY = "UCLOUD_MODELVERSE/Sora"
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def generate(self, client, model, first_frame_image=None, first_frame_url="",
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prompt="", resolution="720p", duration=4):
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api_key = client.get("api_key")
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if not api_key:
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raise ValueError("API key is not set")
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# Validate resolution for non-pro model
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if model == "openai/sora-2/image-to-video" and resolution == "1080p":
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raise ValueError("普通版不支持 1080p，请使用 Pro 版")
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mv_client = ModelverseClient(api_key)
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# Validate first frame input
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has_url = first_frame_url and first_frame_url.strip()
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has_image = first_frame_image is not None
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if has_url and has_image:
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raise ValueError("请提供 first_frame_image 或 first_frame_url，不能同时提供")
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if not has_url and not has_image:
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raise ValueError("必须提供 first_frame_image 或 first_frame_url")
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task_input = {}
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if has_url:
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task_input["first_frame_url"] = first_frame_url.strip()
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else:
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task_input["first_frame_url"] = image_to_base64(first_frame_image)
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if prompt and prompt.strip():
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task_input["prompt"] = prompt.strip()
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parameters = {
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"duration": duration,
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}
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# Pro版支持resolution参数
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if model == "openai/sora-2/image-to-video-pro":
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parameters["resolution"] = resolution
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# Submit task
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submit_res = mv_client.submit_task(model, task_input, parameters)
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task_id = submit_res.get("output", {}).get("task_id")
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if not task_id:
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raise Exception(f"Failed to submit task: {submit_res}")
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print(f"Sora I2V task submitted: {task_id}")
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# Poll for result
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video_url = self._poll_task(mv_client, task_id)
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return (video_url, task_id)
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def _poll_task(self, mv_client, task_id, max_retries=180):
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for i in range(max_retries):
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status_res = mv_client.get_task_status(task_id)
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task_status = status_res.get("output", {}).get("task_status")
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if task_status == "Success":
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urls = status_res.get("output", {}).get("urls", [])
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if urls:
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return urls[0]
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raise Exception("Task succeeded but no video URL returned")
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elif task_status == "Failure":
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error = status_res.get("output", {}).get("error_message", "Unknown error")
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raise Exception(f"Task failed: {error}")
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elif task_status in ["Pending", "Running"]:
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print(f"Task {task_id}: {task_status} ({i+1}/{max_retries})")
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time.sleep(5)
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else:
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raise Exception(f"Unknown status: {task_status}")
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raise Exception("Task timed out")
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NODE_CLASS_MAPPINGS = {
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"Sora_Img2Video": SoraImg2VideoNode,
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}
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NODE_DISPLAY_NAME_MAPPINGS = {
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"Sora_Img2Video": "Sora Img2Video",
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}
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