import {getSetting} from "@app/settings"

const TRANSCRIPTION_MODEL = "openai/whisper-large-v3-turbo"

// OpenRouter chooses a decoder using the uploaded file's extension, and MediaRecorder's output
// format varies by engine — webm on chromium, mp4 on webkit.
const EXTENSIONS_BY_MIME_TYPE: Record<string, string> = {
  "audio/webm": "webm",
  "audio/ogg": "ogg",
  "audio/mp4": "m4a",
  "audio/mpeg": "mp3",
  "audio/wav": "wav",
}

// Reports how loud the microphone is once per frame, so the caller can show the speaker that we're
// hearing them. Levels follow the waveform's envelope — jumping to each peak, then decaying — since
// the raw root mean square drops to nothing in the gaps between words.
export const startDictation = async (onLevel: (level: number) => void) => {
  const stream = await navigator.mediaDevices.getUserMedia({audio: true})
  const recorder = new MediaRecorder(stream)
  const chunks: Blob[] = []

  recorder.addEventListener("dataavailable", event => chunks.push(event.data))
  recorder.start()

  const context = new AudioContext()
  const analyser = context.createAnalyser()

  analyser.fftSize = 512

  context.createMediaStreamSource(stream).connect(analyser)

  const samples = new Uint8Array(analyser.frequencyBinCount)

  let level = 0

  const measure = () => {
    analyser.getByteTimeDomainData(samples)

    let sumSquares = 0

    for (const sample of samples) {
      sumSquares += ((sample - 128) / 128) ** 2
    }

    level = Math.max(Math.sqrt(sumSquares / samples.length), level * 0.92)

    onLevel(level)

    frame = requestAnimationFrame(measure)
  }

  let frame = requestAnimationFrame(measure)

  return () =>
    new Promise<Blob>(resolve => {
      recorder.addEventListener("stop", () => {
        cancelAnimationFrame(frame)
        context.close()

        for (const track of stream.getTracks()) {
          track.stop()
        }

        resolve(new Blob(chunks, {type: recorder.mimeType}))
      })

      recorder.stop()
    })
}

export const transcribe = async (audio: Blob) => {
  const [mimeType] = audio.type.split(";")
  const body = new FormData()

  body.append("model", TRANSCRIPTION_MODEL)
  body.append("file", audio, `dictation.${EXTENSIONS_BY_MIME_TYPE[mimeType] || "webm"}`)

  const response = await fetch("https://openrouter.ai/api/v1/audio/transcriptions", {
    method: "POST",
    headers: {Authorization: `Bearer ${getSetting("openrouter_key")}`},
    body,
  })

  const {text, error}: {text?: string; error?: {message?: string}} = await response.json()

  if (!response.ok) {
    throw new Error(error?.message || `OpenRouter returned a ${response.status}.`)
  }

  return text?.trim() ?? ""
}