chore: remove all PrismAudio code from main branch

- Delete prismaudio_core/, data_utils/, scripts/, docs/plans/
- Delete PrismAudio nodes (feature_extractor, feature_loader, model_loader, sampler, text_only)
- Delete PrismAudio workflows (video_to_audio, text_to_audio)
- Clean nodes/utils.py: rename PRISMAUDIO_CATEGORY → SELVA_CATEGORY, remove unused helpers
- Strip PrismAudio-only deps from requirements.txt

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

nodes/utils.py

@@ -1,21 +1,7 @@
-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)
+SELVA_CATEGORY = "SelVA"
 
 def get_device():
     return mm.get_torch_device()
@@ -23,42 +9,13 @@ def get_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:
+    free_mem = mm.get_free_memory(get_device())
+    if free_mem / (1024 ** 3) >= 16:
         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
+    return "offload_to_cpu"