import base64
import os
import tempfile
from typing import Optional

from fastapi import FastAPI, Header, HTTPException
from fastapi.middleware.cors import CORSMiddleware
from pydantic import BaseModel

try:
    from faster_whisper import WhisperModel
except ImportError as exc:  # pragma: no cover
    raise RuntimeError("faster-whisper is required. Install dependencies from requirements.txt") from exc


STT_MODEL = os.getenv("STT_MODEL", "small")
STT_DEVICE = os.getenv("STT_DEVICE", "auto")
STT_COMPUTE_TYPE = os.getenv("STT_COMPUTE_TYPE", "int8")
STT_API_KEY = os.getenv("STT_API_KEY", "").strip()

app = FastAPI(title="Local STT Bridge", version="1.0.0")
app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],
    allow_credentials=False,
    allow_methods=["*"],
    allow_headers=["*"],
)

model = WhisperModel(STT_MODEL, device=STT_DEVICE, compute_type=STT_COMPUTE_TYPE)


class TranscribeRequest(BaseModel):
    audioBase64: str
    mimeType: Optional[str] = "audio/webm"
    captureMode: Optional[str] = "tab"
    model: Optional[str] = None


@app.get("/health")
def health():
    return {
        "ok": True,
        "engine": "faster-whisper",
        "model": STT_MODEL,
        "device": STT_DEVICE,
        "computeType": STT_COMPUTE_TYPE,
    }


@app.post("/transcribe")
def transcribe(payload: TranscribeRequest, x_stt_api_key: Optional[str] = Header(default=None)):
    if STT_API_KEY and x_stt_api_key != STT_API_KEY:
        raise HTTPException(status_code=401, detail="Invalid STT API key")

    try:
        audio_bytes = base64.b64decode(payload.audioBase64)
    except Exception as exc:
        raise HTTPException(status_code=400, detail=f"Invalid base64 audio payload: {exc}") from exc

    suffix = ".webm"
    if payload.mimeType and "mp4" in payload.mimeType:
        suffix = ".mp4"
    elif payload.mimeType and "wav" in payload.mimeType:
        suffix = ".wav"

    with tempfile.NamedTemporaryFile(suffix=suffix, delete=False) as tmp:
        tmp.write(audio_bytes)
        tmp_path = tmp.name

    try:
        segments, info = model.transcribe(
            tmp_path,
            vad_filter=True,
            beam_size=1,
            language=None,
        )
        text = " ".join(segment.text.strip() for segment in segments).strip()
        return {
            "success": True,
            "text": text,
            "language": info.language,
            "duration": info.duration,
        }
    except Exception as exc:
        raise HTTPException(status_code=500, detail=f"Transcription failed: {exc}") from exc
    finally:
        try:
            os.remove(tmp_path)
        except OSError:
            pass