"""Panel-driven parallel video generation and durable result nodes.""" from __future__ import annotations import json import os from typing import Any import folder_paths from PIL import Image from comfy_api.latest import InputImpl, io, ui from ..utils.image_utils import pil_to_tensor from ..utils.o1key_video_catalog import ( SEEDANCE_ASSET_CREATION_MODE_OPTIONS, SEEDANCE_MODEL_OPTIONS, SEEDANCE_ROUTE_OPTIONS, VIDEO_ASPECT_RATIO_OPTIONS, VIDEO_DURATION_OPTIONS, VIDEO_GENERATION_MODE_OPTIONS, VIDEO_PROVIDER_OPTIONS, VIDEO_RESOLUTION_OPTIONS, ) def _parse_result_descriptor(value: str | dict[str, Any] | None) -> dict[str, str] | None: if value in (None, "", "{}"): return None try: item = json.loads(value) if isinstance(value, str) else value except json.JSONDecodeError: raise ValueError("视频结果描述符不是有效 JSON") from None if not isinstance(item, dict): raise ValueError("视频结果描述符必须是对象") filename = os.path.basename(str(item.get("filename") or "").strip()) subfolder = str(item.get("subfolder") or "").strip().replace("\\", "/") folder_type = str(item.get("type") or "output").strip() if not filename or folder_type not in {"output", "temp"}: raise ValueError("视频结果描述符无效") if subfolder.startswith("/") or any(part == ".." for part in subfolder.split("/")): raise ValueError("视频结果子目录无效") return {"filename": filename, "subfolder": subfolder, "type": folder_type} def _resolve_result_path(descriptor: dict[str, str]) -> str: root = ( folder_paths.get_output_directory() if descriptor["type"] == "output" else folder_paths.get_temp_directory() ) root = os.path.realpath(os.path.abspath(root)) candidate = os.path.realpath( os.path.abspath(os.path.join(root, descriptor["subfolder"], descriptor["filename"])) ) try: inside = os.path.commonpath((root, candidate)) == root except ValueError: inside = False if not inside or not os.path.isfile(candidate): raise ValueError("视频结果文件不存在或已超出允许目录") return candidate def _result_values( video_manifest: str | dict[str, Any] | None, last_frame_manifest: str | dict[str, Any] | None, ) -> tuple[Any, Any]: video_descriptor = _parse_result_descriptor(video_manifest) if video_descriptor is None: return None, None video_path = _resolve_result_path(video_descriptor) last_frame_tensor = None last_frame_descriptor = _parse_result_descriptor(last_frame_manifest) if last_frame_descriptor is not None: last_frame_path = _resolve_result_path(last_frame_descriptor) with Image.open(last_frame_path) as image: image.load() last_frame_tensor = pil_to_tensor([image.convert("RGB")]) return InputImpl.VideoFromFile(video_path), last_frame_tensor class O1keyVideoGenerator(io.ComfyNode): """A frontend-operated generator; each click creates an independent job.""" @classmethod def define_schema(cls): return io.Schema( node_id="O1keyVideoGenerator", display_name="o1key 视频生成", category="o1key/video", description="点击节点内按钮提交独立后台视频任务，并自动连接原生保存节点。", inputs=[ io.String.Input("prompt", default="", multiline=True, socketless=True), io.Combo.Input("provider", options=VIDEO_PROVIDER_OPTIONS, default="seedance", socketless=True), io.Combo.Input("model", options=SEEDANCE_MODEL_OPTIONS, default="seedance-2.0", socketless=True), io.Combo.Input("route", options=SEEDANCE_ROUTE_OPTIONS, default="domestic", socketless=True), io.Combo.Input("generation_mode", options=VIDEO_GENERATION_MODE_OPTIONS, default="multimodal", socketless=True), io.Combo.Input("resolution", options=VIDEO_RESOLUTION_OPTIONS, default="720p", socketless=True), io.Combo.Input("aspect_ratio", options=VIDEO_ASPECT_RATIO_OPTIONS, default="auto", socketless=True), io.Combo.Input("duration", options=VIDEO_DURATION_OPTIONS, default="5", socketless=True), io.Boolean.Input("generate_audio", default=False, socketless=True), io.Boolean.Input("return_last_frame", default=False, socketless=True), io.Int.Input("seed", default=0, min=0, max=0xFFFFFFFFFFFFFFFF, socketless=True), io.String.Input("media_manifest", default="{}", multiline=True, socketless=True), io.String.Input("asset_manifest", default="{}", multiline=True, socketless=True), io.String.Input("provider_options", default="{}", multiline=True, socketless=True), io.String.Input("filename_prefix", default="o1key_video", socketless=True), io.String.Input("save_location", default="video", socketless=True), # Append-only: keep every released widgets_values position stable. io.Combo.Input( "asset_creation_mode", options=SEEDANCE_ASSET_CREATION_MODE_OPTIONS, default="auto", socketless=True, ), io.String.Input("video_manifest", default="{}", multiline=True, socketless=True), io.String.Input("last_frame_manifest", default="{}", multiline=True, socketless=True), ], outputs=[ io.Video.Output("VIDEO", display_name="VIDEO"), io.Image.Output("LAST_FRAME", display_name="LAST_FRAME"), ], not_idempotent=True, ) @classmethod def execute( cls, video_manifest: str = "{}", last_frame_manifest: str = "{}", **_kwargs, ) -> io.NodeOutput: # Generation remains owned by /o1key/video/jobs. Native execution only # resolves the latest completed local descriptors and never spends again. video, last_frame = _result_values(video_manifest, last_frame_manifest) if video is None: return io.NodeOutput(block_execution="请先在 o1key 视频生成节点中完成一次生成") return io.NodeOutput(video, last_frame) class O1keyVideoResult(io.ComfyNode): """A completed background result that can later feed native VIDEO workflows.""" @classmethod def define_schema(cls): return io.Schema( node_id="O1keyVideoResult", display_name="o1key 视频结果", category="o1key/video", description="显示独立后台任务状态；完成后可向下游输出原生 VIDEO。", is_deprecated=True, inputs=[ io.String.Input("batch_id", default="", socketless=True), io.String.Input("video_manifest", default="{}", multiline=True, socketless=True), io.String.Input("last_frame_manifest", default="{}", multiline=True, socketless=True), ], outputs=[ io.Video.Output("VIDEO", display_name="VIDEO"), io.Image.Output("LAST_FRAME", display_name="LAST_FRAME"), ], ) @classmethod def execute( cls, batch_id: str = "", video_manifest: str = "{}", last_frame_manifest: str = "{}", ) -> io.NodeOutput: del batch_id video_descriptor = _parse_result_descriptor(video_manifest) if video_descriptor is None: raise ValueError("视频任务尚未完成，没有可输出的视频") video, last_frame_tensor = _result_values(video_manifest, last_frame_manifest) preview = ui.PreviewVideo([video_descriptor]) return io.NodeOutput( video, last_frame_tensor, ui=preview, ) NODE_CLASS_MAPPINGS = { "O1keyVideoGenerator": O1keyVideoGenerator, "O1keyVideoResult": O1keyVideoResult, } NODE_DISPLAY_NAME_MAPPINGS = { "O1keyVideoGenerator": "o1key 视频生成", "O1keyVideoResult": "o1key 视频结果", } __all__ = ["O1keyVideoGenerator", "O1keyVideoResult"]