import { pipeline, env } from 'https://cdn.jsdelivr.net/npm/@xenova/transformers@2.17.2';
import * as OpenCC from 'https://cdn.jsdelivr.net/npm/opencc-js@1.0.5/+esm';

env.allowLocalModels = false;

let progressCallback = (progress) => {
    const status = document.getElementById('status');
    if (progress.status === 'progress') {
        status.textContent = `Downloading model... ${progress.file}`;
    } else if (progress.status === 'done') {
        status.textContent = 'Model loaded';
    }
};

env.progress_callback = progressCallback;

const languageSelect = document.getElementById('language');
const engineSelect = document.getElementById('engine');
const recordBtn = document.getElementById('record-btn');
const stopBtn = document.getElementById('stop-btn');
const fileInput = document.getElementById('file-input');
const uploadBtn = document.getElementById('upload-btn');
const output = document.getElementById('output');
const status = document.getElementById('status');
const copyBtn = document.getElementById('copy-btn');

let recognition;
let transcriber = null;
let currentModel = null;

const getModelForLanguage = () => 'Xenova/whisper-small';

const bufferToWav = (buffer, sampleRate = 16000) => {
    const numOfChan = 1;
    const length = buffer.length * 2;
    const bufferArray = new ArrayBuffer(44 + length);
    const view = new DataView(bufferArray);

    const writeString = (view, offset, string) => {
        for (let i = 0; i < string.length; i++) {
            view.setUint8(offset + i, string.charCodeAt(i));
        }
    };

    /* RIFF identifier */
    writeString(view, 0, 'RIFF');
    /* file size - 8 */
    view.setUint32(4, 36 + length, true);
    /* RIFF type */
    writeString(view, 8, 'WAVE');
    /* format chunk identifier */
    writeString(view, 12, 'fmt ');
    /* format chunk length */
    view.setUint32(16, 16, true);
    /* sample format (PCM = 1) */
    view.setUint16(20, 1, true);
    /* channel count */
    view.setUint16(22, numOfChan, true);
    /* sample rate */
    view.setUint32(24, sampleRate, true);
    /* byte rate (sample rate * block align) */
    view.setUint32(28, sampleRate * 2, true);
    /* block align (channel count * bytes per sample) */
    view.setUint16(32, numOfChan * 2, true);
    /* bits per sample */
    view.setUint16(34, 16, true);
    /* data chunk identifier */
    writeString(view, 36, 'data');
    /* chunk length */
    view.setUint32(40, length, true);

    // Convert Float32Array to 16-bit signed PCM
    let offset = 44;
    for (let i = 0; i < buffer.length; i++, offset += 2) {
        let s = Math.max(-1, Math.min(1, buffer[i]));
        view.setInt16(offset, s < 0 ? s * 0x8000 : s * 0x7FFF, true);
    }

    return new Blob([view], { type: 'audio/wav' });
};

fileInput.addEventListener('change', () => {
    uploadBtn.disabled = !fileInput.files.length;
});

const extractAudio = async (file) => {
    status.textContent = `Reading file... (${(file.size / 1024 / 1024).toFixed(1)} MB)`;
    const arrayBuffer = await file.arrayBuffer();
    status.textContent = 'Decoding audio... (page may be briefly unresponsive)';
    await new Promise(r => setTimeout(r, 100));
    const audioContext = new AudioContext({ sampleRate: 16000 });
    const audioBuffer = await new Promise((resolve, reject) => {
        audioContext.decodeAudioData(arrayBuffer, resolve, reject);
    });
    status.textContent = `Audio decoded (${Math.round(audioBuffer.duration)}s)`;
    await audioContext.close();
    return audioBuffer.getChannelData(0);
};

uploadBtn.addEventListener('click', async () => {
    const file = fileInput.files[0];
    if (!file) return;

    uploadBtn.disabled = true;
    output.textContent = '';

    try {
        const selectedLang = languageSelect.value;
        const engine = engineSelect.value;

        status.textContent = 'Processing media file...';
        const audio = await extractAudio(file);

        let text = '';

        if (engine === 'local') {
            const modelName = getModelForLanguage(selectedLang);

            if (!transcriber || currentModel !== modelName) {
                status.textContent = 'Downloading model...';
                transcriber = await pipeline('automatic-speech-recognition', modelName);
                currentModel = modelName;
            }

            status.textContent = 'Transcribing locally...';
            const langCode = selectedLang.split('-')[0];
            const result = await transcriber(audio, {
                language: langCode,
                chunk_length_s: 30,
                stride_length_s: 5,
                return_timestamps: false
            });
            text = result.text;
        } else if (engine === 'server') {
            status.textContent = 'Encoding audio to WAV in browser...';
            const wavBlob = bufferToWav(audio, 16000);

            status.textContent = 'Uploading and transcribing on server...';
            const formData = new FormData();
            formData.append('file', wavBlob, 'audio.wav');
            formData.append('language', selectedLang);

            const response = await fetch('/transcribe', {
                method: 'POST',
                body: formData
            });

            if (!response.ok) {
                const errData = await response.json().catch(() => ({}));
                throw new Error(errData.error || `Server error: ${response.status}`);
            }

            const result = await response.json();
            text = result.text;
        }

        if (selectedLang === 'zh-CN') {
            const converter = OpenCC.Converter({ from: 'tw', to: 'cn' });
            text = converter(text);
        }
        output.textContent = text;
        copyBtn.style.display = 'block';
        status.textContent = 'Complete';
    } catch (err) {
        status.textContent = `Error: ${err.message}`;
    } finally {
        uploadBtn.disabled = false;
    }
});

recordBtn.addEventListener('click', async () => {
    try {
        await navigator.mediaDevices.getUserMedia({ audio: true });

        recognition = new webkitSpeechRecognition();
        recognition.continuous = true;
        recognition.interimResults = true;
        recognition.lang = languageSelect.value;

        let transcript = '';

        recognition.onresult = (event) => {
            let interim = '';
            for (let i = event.resultIndex; i < event.results.length; i++) {
                if (event.results[i].isFinal) {
                    transcript += event.results[i][0].transcript + ' ';
                } else {
                    interim += event.results[i][0].transcript;
                }
            }
            output.textContent = transcript + interim;
            copyBtn.style.display = 'block';
        };

        recognition.start();
        recordBtn.disabled = true;
        stopBtn.disabled = false;
        status.textContent = 'Recording...';

    } catch (err) {
        status.textContent = 'Microphone access denied';
    }
});

stopBtn.addEventListener('click', () => {
    if (recognition) {
        recognition.stop();
        recordBtn.disabled = false;
        stopBtn.disabled = true;
        status.textContent = 'Recording stopped';
    }
});

copyBtn.addEventListener('click', () => {
    navigator.clipboard.writeText(output.textContent);
    status.textContent = 'Copied to clipboard';
});