"""Text generation helpers used by scripts and loading examples."""

from __future__ import annotations

import torch

from .tokenizer import CharTokenizer


def generate_text(
    model: torch.nn.Module,
    tokenizer: CharTokenizer,
    prompt: str,
    max_new_tokens: int = 200,
    temperature: float = 0.8,
    top_k: int | None = 40,
    seed: int = 1337,
) -> str:
    encoded = tokenizer.encode(prompt)
    if not encoded:
        raise ValueError("prompt must not be empty")
    input_ids = torch.tensor([encoded], dtype=torch.long, device=next(model.parameters()).device)
    generator = torch.Generator(device=input_ids.device).manual_seed(seed)
    output = model.generate(
        input_ids,
        max_new_tokens=max_new_tokens,
        temperature=temperature,
        top_k=top_k,
        generator=generator,
    )
    return tokenizer.decode(output[0].tolist())