"""ElevenLabs Scribe v2 transcription with diarization.

Sends the original MP3 in one request so Scribe keeps unbroken voiceprint
continuity across the whole episode. Cost comes back in response headers
(fiat-cost-before-overages) -- we record it per episode.
"""
import os

import httpx

import config

API = "https://api.elevenlabs.io/v1/speech-to-text"


def transcribe(mp3_path, num_speakers=None):
    """Returns (scribe_json, cost_usd)."""
    num_speakers = num_speakers or config.NUM_SPEAKERS
    key = os.environ["ELEVEN_LABS_API_TOKEN"]
    with open(mp3_path, "rb") as fh:
        r = httpx.post(
            API,
            headers={"xi-api-key": key},
            files={"file": (os.path.basename(mp3_path), fh, "audio/mpeg")},
            data={"model_id": "scribe_v2", "diarize": "true",
                  "num_speakers": str(num_speakers),
                  "timestamps_granularity": "word", "tag_audio_events": "true",
                  "language_code": "eng"},
            timeout=3600,
        )
    r.raise_for_status()
    cost = float(r.headers.get("fiat-cost-before-overages", 0) or 0)
    return r.json(), cost


def words_to_turns(scribe_json):
    """Collapse the word stream into speaker turns.

    Keeps [audio events] inline. A turn boundary is a speaker change.
    Returns [{t, end, spk, text}] with t/end in float seconds.
    """
    turns, cur = [], None
    for w in scribe_json.get("words", []):
        kind, txt, spk = w.get("type"), w.get("text", ""), w.get("speaker_id")
        if kind == "spacing":
            if cur:
                cur["text"] += txt
            continue
        if kind not in ("word", "audio_event"):
            continue
        if cur is None or cur["spk"] != spk:
            cur = {"spk": spk, "t": w["start"], "end": w["end"], "text": txt}
            turns.append(cur)
        else:
            if not cur["text"].endswith(" "):
                cur["text"] += " "
            cur["text"] += txt
            cur["end"] = w["end"]
    for t in turns:
        t["text"] = " ".join(t["text"].split())
    return [t for t in turns if t["text"]]