import os
import logging
from fastapi import (
    FastAPI,
    Request,
    Depends,
    HTTPException,
    status,
    UploadFile,
    File,
    Form,
)

from fastapi.responses import StreamingResponse, JSONResponse, FileResponse

from fastapi.middleware.cors import CORSMiddleware
from pydantic import BaseModel

import uuid
import requests
import hashlib
from pathlib import Path
import json

from constants import ERROR_MESSAGES
from utils.utils import (
    decode_token,
    get_current_user,
    get_verified_user,
    get_admin_user,
)
from utils.misc import calculate_sha256

from config import (
    SRC_LOG_LEVELS,
    CACHE_DIR,
    UPLOAD_DIR,
    WHISPER_MODEL,
    WHISPER_MODEL_DIR,
    WHISPER_MODEL_AUTO_UPDATE,
    DEVICE_TYPE,
    AUDIO_STT_OPENAI_API_BASE_URL,
    AUDIO_STT_OPENAI_API_KEY,
    AUDIO_TTS_OPENAI_API_BASE_URL,
    AUDIO_TTS_OPENAI_API_KEY,
    AUDIO_STT_ENGINE,
    AUDIO_STT_MODEL,
    AUDIO_TTS_ENGINE,
    AUDIO_TTS_MODEL,
    AUDIO_TTS_VOICE,
    AppConfig,
)

log = logging.getLogger(__name__)
log.setLevel(SRC_LOG_LEVELS["AUDIO"])

app = FastAPI()
app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)

app.state.config = AppConfig()

app.state.config.STT_OPENAI_API_BASE_URL = AUDIO_STT_OPENAI_API_BASE_URL
app.state.config.STT_OPENAI_API_KEY = AUDIO_STT_OPENAI_API_KEY
app.state.config.STT_ENGINE = AUDIO_STT_ENGINE
app.state.config.STT_MODEL = AUDIO_STT_MODEL

app.state.config.TTS_OPENAI_API_BASE_URL = AUDIO_TTS_OPENAI_API_BASE_URL
app.state.config.TTS_OPENAI_API_KEY = AUDIO_TTS_OPENAI_API_KEY
app.state.config.TTS_ENGINE = AUDIO_TTS_ENGINE
app.state.config.TTS_MODEL = AUDIO_TTS_MODEL
app.state.config.TTS_VOICE = AUDIO_TTS_VOICE

# setting device type for whisper model
whisper_device_type = DEVICE_TYPE if DEVICE_TYPE and DEVICE_TYPE == "cuda" else "cpu"
log.info(f"whisper_device_type: {whisper_device_type}")

SPEECH_CACHE_DIR = Path(CACHE_DIR).joinpath("./audio/speech/")
SPEECH_CACHE_DIR.mkdir(parents=True, exist_ok=True)


class TTSConfigForm(BaseModel):
    OPENAI_API_BASE_URL: str
    OPENAI_API_KEY: str
    ENGINE: str
    MODEL: str
    VOICE: str


class STTConfigForm(BaseModel):
    OPENAI_API_BASE_URL: str
    OPENAI_API_KEY: str
    ENGINE: str
    MODEL: str


class AudioConfigUpdateForm(BaseModel):
    tts: TTSConfigForm
    stt: STTConfigForm


from pydub import AudioSegment
from pydub.utils import mediainfo


def is_mp4_audio(file_path):
    """Check if the given file is an MP4 audio file."""
    if not os.path.isfile(file_path):
        print(f"File not found: {file_path}")
        return False

    info = mediainfo(file_path)
    if (
        info.get("codec_name") == "aac"
        and info.get("codec_type") == "audio"
        and info.get("codec_tag_string") == "mp4a"
    ):
        return True
    return False


def convert_mp4_to_wav(file_path, output_path):
    """Convert MP4 audio file to WAV format."""
    audio = AudioSegment.from_file(file_path, format="mp4")
    audio.export(output_path, format="wav")
    print(f"Converted {file_path} to {output_path}")


@app.get("/config")
async def get_audio_config(user=Depends(get_admin_user)):
    return {
        "tts": {
            "OPENAI_API_BASE_URL": app.state.config.TTS_OPENAI_API_BASE_URL,
            "OPENAI_API_KEY": app.state.config.TTS_OPENAI_API_KEY,
            "ENGINE": app.state.config.TTS_ENGINE,
            "MODEL": app.state.config.TTS_MODEL,
            "VOICE": app.state.config.TTS_VOICE,
        },
        "stt": {
            "OPENAI_API_BASE_URL": app.state.config.STT_OPENAI_API_BASE_URL,
            "OPENAI_API_KEY": app.state.config.STT_OPENAI_API_KEY,
            "ENGINE": app.state.config.STT_ENGINE,
            "MODEL": app.state.config.STT_MODEL,
        },
    }


@app.post("/config/update")
async def update_audio_config(
    form_data: AudioConfigUpdateForm, user=Depends(get_admin_user)
):
    app.state.config.TTS_OPENAI_API_BASE_URL = form_data.tts.OPENAI_API_BASE_URL
    app.state.config.TTS_OPENAI_API_KEY = form_data.tts.OPENAI_API_KEY
    app.state.config.TTS_ENGINE = form_data.tts.ENGINE
    app.state.config.TTS_MODEL = form_data.tts.MODEL
    app.state.config.TTS_VOICE = form_data.tts.VOICE

    app.state.config.STT_OPENAI_API_BASE_URL = form_data.stt.OPENAI_API_BASE_URL
    app.state.config.STT_OPENAI_API_KEY = form_data.stt.OPENAI_API_KEY
    app.state.config.STT_ENGINE = form_data.stt.ENGINE
    app.state.config.STT_MODEL = form_data.stt.MODEL

    return {
        "tts": {
            "OPENAI_API_BASE_URL": app.state.config.TTS_OPENAI_API_BASE_URL,
            "OPENAI_API_KEY": app.state.config.TTS_OPENAI_API_KEY,
            "ENGINE": app.state.config.TTS_ENGINE,
            "MODEL": app.state.config.TTS_MODEL,
            "VOICE": app.state.config.TTS_VOICE,
        },
        "stt": {
            "OPENAI_API_BASE_URL": app.state.config.STT_OPENAI_API_BASE_URL,
            "OPENAI_API_KEY": app.state.config.STT_OPENAI_API_KEY,
            "ENGINE": app.state.config.STT_ENGINE,
            "MODEL": app.state.config.STT_MODEL,
        },
    }


@app.post("/speech")
async def speech(request: Request, user=Depends(get_verified_user)):
    body = await request.body()
    name = hashlib.sha256(body).hexdigest()

    file_path = SPEECH_CACHE_DIR.joinpath(f"{name}.mp3")
    file_body_path = SPEECH_CACHE_DIR.joinpath(f"{name}.json")

    # Check if the file already exists in the cache
    if file_path.is_file():
        return FileResponse(file_path)

    headers = {}
    headers["Authorization"] = f"Bearer {app.state.config.TTS_OPENAI_API_KEY}"
    headers["Content-Type"] = "application/json"

    try:
        body = body.decode("utf-8")
        body = json.loads(body)
        body["model"] = app.state.config.TTS_MODEL
        body = json.dumps(body).encode("utf-8")
    except Exception as e:
        pass

    r = None
    try:
        r = requests.post(
            url=f"{app.state.config.TTS_OPENAI_API_BASE_URL}/audio/speech",
            data=body,
            headers=headers,
            stream=True,
        )

        r.raise_for_status()

        # Save the streaming content to a file
        with open(file_path, "wb") as f:
            for chunk in r.iter_content(chunk_size=8192):
                f.write(chunk)

        with open(file_body_path, "w") as f:
            json.dump(json.loads(body.decode("utf-8")), f)

        # Return the saved file
        return FileResponse(file_path)

    except Exception as e:
        log.exception(e)
        error_detail = "Open WebUI: Server Connection Error"
        if r is not None:
            try:
                res = r.json()
                if "error" in res:
                    error_detail = f"External: {res['error']['message']}"
            except:
                error_detail = f"External: {e}"

        raise HTTPException(
            status_code=r.status_code if r != None else 500,
            detail=error_detail,
        )


@app.post("/transcriptions")
def transcribe(
    file: UploadFile = File(...),
    user=Depends(get_current_user),
):
    log.info(f"file.content_type: {file.content_type}")

    if file.content_type not in ["audio/mpeg", "audio/wav"]:
        raise HTTPException(
            status_code=status.HTTP_400_BAD_REQUEST,
            detail=ERROR_MESSAGES.FILE_NOT_SUPPORTED,
        )

    try:
        ext = file.filename.split(".")[-1]

        id = uuid.uuid4()
        filename = f"{id}.{ext}"

        file_dir = f"{CACHE_DIR}/audio/transcriptions"
        os.makedirs(file_dir, exist_ok=True)
        file_path = f"{file_dir}/{filename}"

        print(filename)

        contents = file.file.read()
        with open(file_path, "wb") as f:
            f.write(contents)
            f.close()

        if app.state.config.STT_ENGINE == "":
            from faster_whisper import WhisperModel

            whisper_kwargs = {
                "model_size_or_path": WHISPER_MODEL,
                "device": whisper_device_type,
                "compute_type": "int8",
                "download_root": WHISPER_MODEL_DIR,
                "local_files_only": not WHISPER_MODEL_AUTO_UPDATE,
            }

            log.debug(f"whisper_kwargs: {whisper_kwargs}")

            try:
                model = WhisperModel(**whisper_kwargs)
            except:
                log.warning(
                    "WhisperModel initialization failed, attempting download with local_files_only=False"
                )
                whisper_kwargs["local_files_only"] = False
                model = WhisperModel(**whisper_kwargs)

            segments, info = model.transcribe(file_path, beam_size=5)
            log.info(
                "Detected language '%s' with probability %f"
                % (info.language, info.language_probability)
            )

            transcript = "".join([segment.text for segment in list(segments)])

            data = {"text": transcript.strip()}

            # save the transcript to a json file
            transcript_file = f"{file_dir}/{id}.json"
            with open(transcript_file, "w") as f:
                json.dump(data, f)

            print(data)

            return data

        elif app.state.config.STT_ENGINE == "openai":
            if is_mp4_audio(file_path):
                print("is_mp4_audio")
                os.rename(file_path, file_path.replace(".wav", ".mp4"))
                # Convert MP4 audio file to WAV format
                convert_mp4_to_wav(file_path.replace(".wav", ".mp4"), file_path)

            headers = {"Authorization": f"Bearer {app.state.config.STT_OPENAI_API_KEY}"}

            files = {"file": (filename, open(file_path, "rb"))}
            data = {"model": app.state.config.STT_MODEL}

            print(files, data)

            r = None
            try:
                r = requests.post(
                    url=f"{app.state.config.STT_OPENAI_API_BASE_URL}/audio/transcriptions",
                    headers=headers,
                    files=files,
                    data=data,
                )

                r.raise_for_status()

                data = r.json()

                # save the transcript to a json file
                transcript_file = f"{file_dir}/{id}.json"
                with open(transcript_file, "w") as f:
                    json.dump(data, f)

                print(data)
                return data
            except Exception as e:
                log.exception(e)
                error_detail = "Open WebUI: Server Connection Error"
                if r is not None:
                    try:
                        res = r.json()
                        if "error" in res:
                            error_detail = f"External: {res['error']['message']}"
                    except:
                        error_detail = f"External: {e}"

                raise HTTPException(
                    status_code=r.status_code if r != None else 500,
                    detail=error_detail,
                )

    except Exception as e:
        log.exception(e)

        raise HTTPException(
            status_code=status.HTTP_400_BAD_REQUEST,
            detail=ERROR_MESSAGES.DEFAULT(e),
        )