"""Capture block-0 QKV before and after ComfyUI attention preparation."""

from pathlib import Path


model = Path("/opt/ComfyUI/comfy/ldm/minimax/model.py")
source = model.read_text(encoding="utf-8")

old = "            block._h3_capture_index = i\n            comfy.model_prefetch.prefetch_queue_pop(prefetch_queue, device, block)\n"
new = "            block._h3_capture_index = i\n            block.attn._h3_capture_index = i\n            comfy.model_prefetch.prefetch_queue_pop(prefetch_queue, device, block)\n"
if source.count(old) == 1:
    source = source.replace(old, new)
elif new not in source:
    raise RuntimeError("Unable to locate the H3 block loop.")

old = "        v = v.transpose(0, 1).unsqueeze(0)\n        out = optimized_attention(q, k, v, self.heads, mask=None, skip_reshape=True, transformer_options=transformer_options)\n"
new = (
    "        v = v.transpose(0, 1).unsqueeze(0)\n"
    "        if getattr(self, \"_h3_capture_index\", -1) == 0 and H3_CAPTURE_ACTIVE:\n"
    "            capture_dir = os.getenv(\"H3_CAPTURE_DIR\")\n"
    "            if capture_dir:\n"
    "                torch.save({\"q\": q.detach().cpu(), \"k\": k.detach().cpu(), \"v\": v.detach().cpu()}, os.path.join(capture_dir, \"block0_qkv_prepared.pt\"))\n"
    "        out = optimized_attention(q, k, v, self.heads, mask=None, skip_reshape=True, transformer_options=transformer_options)\n"
)
if source.count(old) == 1:
    source = source.replace(old, new)
elif new not in source:
    raise RuntimeError("Unable to locate the prepared QKV call.")

model.write_text(source, encoding="utf-8")
print("Applied H3 block-0 QKV capture patch.")