feat: project scaffolding with shared utils and node registration

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

__init__.py

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+"""
+ComfyUI-PrismAudio: Video-to-Audio and Text-to-Audio generation using PrismAudio (ICLR 2026).
+"""
+from .nodes import NODE_CLASS_MAPPINGS, NODE_DISPLAY_NAME_MAPPINGS
+
+__all__ = ["NODE_CLASS_MAPPINGS", "NODE_DISPLAY_NAME_MAPPINGS"]

nodes/__init__.py

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+NODE_CLASS_MAPPINGS = {}
+NODE_DISPLAY_NAME_MAPPINGS = {}
+
+_NODES = {
+    "PrismAudioModelLoader": (".model_loader", "PrismAudioModelLoader", "PrismAudio Model Loader"),
+    "PrismAudioFeatureLoader": (".feature_loader", "PrismAudioFeatureLoader", "PrismAudio Feature Loader"),
+    "PrismAudioFeatureExtractor": (".feature_extractor", "PrismAudioFeatureExtractor", "PrismAudio Feature Extractor"),
+    "PrismAudioSampler": (".sampler", "PrismAudioSampler", "PrismAudio Sampler"),
+    "PrismAudioTextOnly": (".text_only", "PrismAudioTextOnly", "PrismAudio Text Only"),
+}
+
+for key, (module_path, class_name, display_name) in _NODES.items():
+    try:
+        import importlib
+        mod = importlib.import_module(module_path, package=__name__)
+        NODE_CLASS_MAPPINGS[key] = getattr(mod, class_name)
+        NODE_DISPLAY_NAME_MAPPINGS[key] = display_name
+    except (ImportError, AttributeError) as e:
+        print(f"[PrismAudio] Skipping {key}: {e}")

nodes/utils.py

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+import os
+import torch
+import folder_paths
+import comfy.model_management as mm
+
+PRISMAUDIO_CATEGORY = "PrismAudio"
+SAMPLE_RATE = 44100
+DOWNSAMPLING_RATIO = 2048
+IO_CHANNELS = 64
+
+def get_prismaudio_model_dir():
+    model_dir = os.path.join(folder_paths.models_dir, "prismaudio")
+    os.makedirs(model_dir, exist_ok=True)
+    return model_dir
+
+def register_model_folder():
+    model_dir = get_prismaudio_model_dir()
+    folder_paths.add_model_folder_path("prismaudio", model_dir)
+
+def get_device():
+    return mm.get_torch_device()
+
+def get_offload_device():
+    return mm.unet_offload_device()
+
+def get_free_memory(device=None):
+    if device is None:
+        device = get_device()
+    return mm.get_free_memory(device)
+
+def soft_empty_cache():
+    mm.soft_empty_cache()
+
+def determine_precision(preference, device):
+    if preference != "auto":
+        return {"fp32": torch.float32, "fp16": torch.float16, "bf16": torch.bfloat16}[preference]
+    if device.type == "cpu":
+        return torch.float32
+    if torch.cuda.is_available() and torch.cuda.is_bf16_supported():
+        return torch.bfloat16
+    return torch.float16
+
+def determine_offload_strategy(preference):
+    if preference != "auto":
+        return preference
+    free_mem = get_free_memory()
+    gb = free_mem / (1024 ** 3)
+    if gb >= 24:
+        return "keep_in_vram"
+    else:
+        return "offload_to_cpu"
+
+def try_import_flash_attn():
+    try:
+        import flash_attn
+        return flash_attn
+    except ImportError:
+        return None
+
+def resolve_hf_token():
+    env_token = os.environ.get("HF_TOKEN")
+    if env_token:
+        return env_token
+    return None

requirements.txt

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+einops>=0.7.0
+safetensors
+huggingface_hub
+transformers>=4.52.3
+k-diffusion>=0.1.1
+alias-free-torch
+descript-audio-codec
+tqdm