{
 "unet": {
  "class_type": "UNETLoader",
  "_meta": {
   "title": "stock MiniMax-H3 fl2va"
  },
  "inputs": {
   "unet_name": "minimax_h3_fl2va_bf16.safetensors",
   "weight_dtype": "default"
  }
 },
 "teach": {
  "class_type": "LoraLoaderModelOnly",
  "_meta": {
   "title": "Meridian teacher (re-camera)"
  },
  "inputs": {
   "model": [
    "unet",
    0
   ],
   "lora_name": "meridian_teacher_lora.safetensors",
   "strength_model": 1.0
  }
 },
 "turbo": {
  "class_type": "LoraLoaderModelOnly",
  "_meta": {
   "title": "Meridian turbo (3-forward DMD)"
  },
  "inputs": {
   "model": [
    "teach",
    0
   ],
   "lora_name": "meridian_turbo_lora.safetensors",
   "strength_model": 1.0
  }
 },
 "shift": {
  "class_type": "MiniMaxH3SigmaShift",
  "_meta": {
   "title": "shift 3 (student); 12 for teacher alone"
  },
  "inputs": {
   "model": [
    "turbo",
    0
   ],
   "shift_video": 3.0,
   "shift_audio": 3.0
  }
 },
 "clip": {
  "class_type": "CLIPLoader",
  "inputs": {
   "clip_name": "qwen3vl_32b_minimax_h3_bf16.safetensors",
   "type": "minimax"
  }
 },
 "vae": {
  "class_type": "VAELoader",
  "inputs": {
   "vae_name": "minimax_h3_video_vae_fp16.safetensors"
  }
 },
 "avae": {
  "class_type": "VAELoader",
  "inputs": {
   "vae_name": "minimax_h3_audio_vae_fp32.safetensors"
  }
 },
 "ref": {
  "class_type": "MiniMaxH3ReferenceToVideo",
  "_meta": {
   "title": "refs at the 480 class, target at the 768 class"
  },
  "inputs": {
   "clip": [
    "clip",
    0
   ],
   "vae": [
    "vae",
    0
   ],
   "audio_vae": [
    "avae",
    0
   ],
   "prompt": "subject_definitions:\n<Video 1> is the source video for the editing task.\n<Video 2> is a rough render of the same scene from the new camera: the pixels of <Video 1> re-projected through a point cloud, so wherever it shows content its colours, framing and layout are correct, and its flat mid-grey areas are holes where the source camera saw nothing.\n\nsummary:\n[video editing + viewpoint change] The target video shows exactly the same scene as <Video 1>, at exactly the same moments in time, filmed by the second camera that <Video 2> was rendered from. Every subject, every piece of clothing, the background, the lighting and the whole performance are the ones in <Video 1>; only the camera differs, so the same things are seen from a different angle and at a different distance. The target video is <Video 2> completed: its framing and everything it shows are kept, and its grey holes are filled with what belongs there.\n\nretention_analysis:\n<Video 1> (source video editing): fully_preserved - the subjects, their faces, hair, build and clothing, the background, the props and the lighting are the same objects seen from a new viewpoint, and the motion and its timing are frame for frame the motion of <Video 1>. Nothing is added, removed or restyled.\n<Video 2> (layout reference): fully_preserved - the camera path, the framing and the placement of everything it shows are kept exactly; its grey holes are not content and are filled in so that they agree with <Video 1>, and its speckles and jagged edges are cleaned up.\n\ndetailed_description:\n[Shot 1] One continuous shot of the scene of <Video 1>, framed exactly as <Video 2> is, frame for frame. The subjects perform the motion of <Video 1> with the same timing, in the same place, under the same lighting. The camera moves exactly as the camera of <Video 2> does, and there is no cut.\n\noverall_soundscape:\nNo music and no speech.",
   "width": [
    "geo",
    2
   ],
   "height": [
    "geo",
    3
   ],
   "length": [
    "geo",
    4
   ],
   "ref_image_size": "match",
   "ref_videos.ref_video_0": [
    "geo",
    0
   ],
   "ref_videos.ref_video_1": [
    "geo",
    1
   ]
  }
 },
 "froz": {
  "class_type": "MeridianFrozenPrompt",
  "_meta": {
   "title": "swap in the frozen prompt embed"
  },
  "inputs": {
   "conditioning": [
    "ref",
    0
   ],
   "latent": [
    "ref",
    1
   ],
   "assets_dir": "/path/to/release_recam/assets"
  }
 },
 "ks": {
  "class_type": "KSampler",
  "_meta": {
   "title": "3 forwards on sigma 1.0 / 0.857 / 0.600"
  },
  "inputs": {
   "model": [
    "shift",
    0
   ],
   "positive": [
    "froz",
    0
   ],
   "negative": [
    "froz",
    0
   ],
   "latent_image": [
    "ref",
    1
   ],
   "seed": 1234,
   "steps": 3,
   "cfg": 1.0,
   "sampler_name": "euler",
   "scheduler": "simple",
   "denoise": 1.0
  }
 },
 "dec": {
  "class_type": "VAEDecode",
  "inputs": {
   "samples": [
    "ks",
    0
   ],
   "vae": [
    "vae",
    0
   ]
  }
 },
 "mk": {
  "class_type": "CreateVideo",
  "inputs": {
   "images": [
    "dec",
    0
   ],
   "fps": 24.0
  }
 },
 "save": {
  "class_type": "SaveVideo",
  "inputs": {
   "video": [
    "mk",
    0
   ],
   "filename_prefix": "meridian/out",
   "format": "mp4",
   "codec": "h264"
  }
 },
 "geo": {
  "class_type": "MeridianGeometry",
  "_meta": {
   "title": "VGGT-Omega unproject + re-render"
  },
  "inputs": {
   "video": "/path/to/clip.mp4",
   "args": "--pivot 0.5,0.55 --boom 0.35 --ease --sweep",
   "repo": "/path/to/release_recam",
   "python": "python"
  }
 }
}