import { pipeline, env } from 'https://cdn.jsdelivr.net/npm/@huggingface/transformers@3/dist/transformers.min.js';

// Disable local model file check — always fetch from HuggingFace Hub
env.allowLocalModels = false;

let transcriber = null;

async function loadModel(modelId) {
  transcriber = await pipeline(
    'automatic-speech-recognition',
    modelId,
    {
      device: 'webgpu',
      dtype: 'q4',
      progress_callback: (progress) => {
        self.postMessage({ type: 'model-progress', progress });
      },
    }
  );
  self.postMessage({ type: 'model-ready' });
}

// audioData is a Float32Array of 16kHz mono PCM — decoded in the main thread
// to avoid the missing AudioContext issue in Web Workers.
async function transcribe(audioData, language) {
  if (!transcriber) {
    self.postMessage({ type: 'error', message: 'Model not loaded' });
    return;
  }

  try {
    const result = await transcriber(audioData, {
      return_timestamps: true,
      chunk_length_s: 30,
      stride_length_s: 5,
      language: language || null,
      task: 'transcribe',
    });

    self.postMessage({ type: 'result', text: result.text, chunks: result.chunks || [] });
  } catch (err) {
    self.postMessage({ type: 'error', message: err.message });
  }
}

self.onmessage = async (event) => {
  const { type, modelId, audioData, language } = event.data;

  if (type === 'load') {
    try {
      await loadModel(modelId || 'Xenova/whisper-small');
    } catch (err) {
      self.postMessage({ type: 'error', message: `Failed to load model: ${err.message}` });
    }
  } else if (type === 'transcribe') {
    await transcribe(audioData, language);
  }
};