import { pipeline } from '@huggingface/transformers';

const classifier = await pipeline('sentiment-analysis');

const result = await classifier('I love transformers!');
// [{'label': 'POSITIVE', 'score': 0.9998}]

const result = await classifier(['I love transformers!', 'I hate transformers!']);
// [{'label': 'POSITIVE', 'score': 0.9998}, {'label': 'NEGATIVE', 'score': 0.9982}]

const reviewer = await pipeline('sentiment-analysis', 'Xenova/bert-base-multilingual-uncased-sentiment');

const result = await reviewer('The Shawshank Redemption is a true masterpiece of cinema.');
// [{label: '5 stars', score: 0.8167929649353027}]

// Create a pipeline for Automatic Speech Recognition
const transcriber = await pipeline('automatic-speech-recognition', 'Xenova/whisper-small.en');

// Transcribe an audio file, loaded from a URL.
const result = await transcriber('https://huggingface.co/datasets/Narsil/asr_dummy/resolve/main/mlk.flac');
// {text: ' I have a dream that one day this nation will rise up and live out the true meaning of its creed.'}

// Create a pipeline for feature extraction, using the full-precision model (fp32)
const pipe = await pipeline('feature-extraction', 'Xenova/all-MiniLM-L6-v2', {
    dtype: "fp32",
});

const transcriber = await pipeline('automatic-speech-recognition', 'Xenova/whisper-tiny.en', {
    revision: 'output_attentions',
});

// Create a pipeline for translation
const translator = await pipeline('translation', 'Xenova/nllb-200-distilled-600M');

// Translate from English to Greek
const result = await translator('I like to walk my dog.', {
    src_lang: 'eng_Latn',
    tgt_lang: 'ell_Grek'
});
// [ { translation_text: 'Μου αρέσει να περπατάω το σκυλί μου.' } ]

// Translate back to English
const result2 = await translator(result[0].translation_text, {
    src_lang: 'ell_Grek',
    tgt_lang: 'eng_Latn'
});
// [ { translation_text: 'I like to walk my dog.' } ]

// Create a pipeline for text2text-generation
const poet = await pipeline('text2text-generation', 'Xenova/LaMini-Flan-T5-783M');
const result = await poet('Write me a love poem about cheese.', {
    max_new_tokens: 200,
    temperature: 0.9,
    repetition_penalty: 2.0,
    no_repeat_ngram_size: 3,
});

Cheese, oh cheese! You're the perfect comfort food.
Your texture so smooth and creamy you can never get old.
With every bite it melts in your mouth like buttery delights
that make me feel right at home with this sweet treat of mine. 

From classic to bold flavor combinations,
I love how versatile you are as an ingredient too?
Cheddar is my go-to for any occasion or mood; 
It adds depth and richness without being overpowering its taste buds alone

import { pipeline, TextStreamer } from "@huggingface/transformers";

// Create a text generation pipeline
const generator = await pipeline(
  "text-generation",
  "onnx-community/Qwen2.5-Coder-0.5B-Instruct",
  { dtype: "q4" },
);

// Define the list of messages
const messages = [
  { role: "system", content: "You are a helpful assistant." },
  { role: "user", content:  "Write a quick sort algorithm." },
];

// Create text streamer
const streamer = new TextStreamer(generator.tokenizer, {
  skip_prompt: true,
  // Optionally, do something with the text (e.g., write to a textbox)
  // callback_function: (text) => { /* Do something with text */ },
})

// Generate a response
const result = await generator(messages, { max_new_tokens: 512, do_sample: false, streamer });