/**
 * @fileoverview Local small-model next-word prediction utility (DistilGPT2 via
 * HuggingFace Transformers). Currently disabled/commented out; kept for reference.
 */
// import { pipeline, type TextGenerationSingle } from "@huggingface/transformers";

// /**
//  * Generates the next words for a given prompt using a text generation model.
//  *
//  * The DistilGPT2 model is a distilled, smaller version of OpenAI's GPT-2, featuring
//  * around 82 million parameters (~80MB), and available in Hugging Face Transformers
//  * for efficient next word (next-token) prediction tasks in English text. It is
//  * well-suited for sequence generation and can be used as a next word prediction
//  * model with code similar to GPT2, but offers faster and lighter inference compared
//  * GPT-2 (124M parameter) model, preserving most capabilities but running
//  * significantly faster and requiring less memory.
//  * @see https://huggingface.co/Xenova/distilgpt2
//  * @param {string} prompt - The input prompt to complete.
//  * @param {Object} [options] - Generation options.
//  * @param {number} [options.maxTokens=16] - Maximum number of new tokens to generate.
//  * @param {string} [options.model='Xenova/distilgpt2'] - The model identifier to use.
//  * @returns {Promise<string>} - The generated text completions.
//  */
// export async function predictNextWordsWithSmallLocalModel(
//   prompt: string,
//   { model = "Xenova/distilgpt2", maxTokens = 16, modelParams = {} } = {}
// ): Promise<string> {
//   if (!prompt) throw new Error("Prompt is required");
//   return (
//     await (
//       await pipeline("text-generation", model, {
//         dtype: "fp16",
//         device: "cpu",
//         ...modelParams,
//       })
//     )(prompt, { max_new_tokens: maxTokens })
//   )
//     .map((res) => (res as TextGenerationSingle).generated_text)
//     .join(" ")
//     .replace(prompt, "")
//     .trim();
// }