"""Spark smoke test for standalone Qwen3-VL prompt-only conditioning."""

import argparse
from pathlib import Path

import torch

from h3_blackwell_runtime.conditioning import H3PromptTokenizer
from h3_blackwell_runtime.qwen3vl_text import Qwen3VL32BTextEncoder


def main() -> None:
    parser = argparse.ArgumentParser()
    parser.add_argument("--checkpoint", type=Path)
    parser.add_argument("--tokenizer-dir", type=Path, default=Path("src/h3_blackwell_runtime/qwen25_tokenizer"))
    parser.add_argument("--prompt", default="A brass-and-paper dragon in a rainy clockmaker workshop.")
    parser.add_argument("--construct-model", action="store_true")
    args = parser.parse_args()

    tokenizer = H3PromptTokenizer(args.tokenizer_dir)
    token_ids = tokenizer(args.prompt, device="cuda" if torch.cuda.is_available() else "cpu")
    print({"token_shape": tuple(token_ids.shape), "token_ids": token_ids[0].tolist()})
    if args.construct_model:
        if args.checkpoint is None:
            parser.error("--construct-model requires --checkpoint")
        model = Qwen3VL32BTextEncoder(args.checkpoint)
        print({"layers": len(model.layers), "embedding_shape": tuple(model.embed_tokens.shape), "dtype": str(model.dtype)})


if __name__ == "__main__":
    main()