import argparse
import json
from pathlib import Path

import torch
from safetensors.torch import load_model
from tokenizers import Tokenizer

from model import CED


def main():
    parser = argparse.ArgumentParser()
    parser.add_argument(
        "--model-dir",
        type=Path,
        default=Path(__file__).resolve().parent,
    )
    parser.add_argument("--text", default="Once upon a time, a little rabbit")
    parser.add_argument("--device", choices=["cpu", "cuda"], default="cpu")
    parser.add_argument("--temperature", type=float, default=0.8)
    parser.add_argument("--max-new-tokens", type=int, default=150)
    args = parser.parse_args()

    config = json.loads((args.model_dir / "config.json").read_text())
    model = CED(
        vocab=config["vocab_size"],
        dim=config["hidden_size"],
        heads=config["num_attention_heads"],
        ff=config["intermediate_size"],
        layers=config["num_hidden_layers"],
        window=config["local_window_size"],
    )
    load_model(model, args.model_dir / "model.safetensors")
    model = model.to(args.device).eval()
    tokenizer = Tokenizer.from_file(str(args.model_dir / "tokenizer.json"))

    ids = [config["bos_token_id"]] + tokenizer.encode(args.text).ids
    context_length = config["max_position_embeddings"]
    if len(ids) > context_length:
        raise ValueError(f"Prompt exceeds the {context_length}-token context length")

    torch.manual_seed(123)
    with torch.inference_mode():
        for _ in range(min(args.max_new_tokens, context_length - len(ids))):
            logits = model(torch.tensor([ids], device=args.device))[0, -1].float()
            logits[
                [config["pad_token_id"], config["bos_token_id"], config["unk_token_id"]]
            ] = -torch.inf
            if args.temperature <= 0:
                token = int(logits.argmax())
            else:
                token = int(torch.multinomial((logits / args.temperature).softmax(-1), 1))
            ids.append(token)
            if token == config["eos_token_id"]:
                break

    print(tokenizer.decode(ids))


if __name__ == "__main__":
    main()