from dataclasses import dataclass
from typing import List, Tuple
import os
from openai import OpenAI
import tempfile
from pydub import AudioSegment
import base64
from pathlib import Path
from script_generation import PodScript
@dataclass
class AudioConfig:
    output_path: str = "./src/public/output"
    api_key: str = os.getenv("OPENAI_API_KEY", "")
    model: str = "gpt-4o-mini-tts"
    mocked: bool = False

class ScriptToAudio:
    def __init__(self, config: AudioConfig):
        self._config = config
        self._llm_client = OpenAI(api_key=config.api_key)

    async def _text_to_speech(self, script: PodScript, voice_1: str, voice_2: str) -> Tuple[List[str], str]:
        """Converts the text in the conversation JSON to speech using the specified voices.
        Args:
            conversation_json (Dict): The conversation JSON containing the text to be converted.
            voice_1 (str): The voice for the first speaker.
            voice_2 (str): The voice for the second speaker.
        Returns:
            Tuple[List[str], str]: A tuple containing a list of filenames of the generated audio files and the output directory.
        Raises:
            ValueError: If the conversation JSON is empty or if the voices are invalid.
            RuntimeError: If the text-to-speech conversion fails.
        """
        output_dir = Path(self._create_output_directory())
        filenames = []

        try:
            for i, line in enumerate(script.conversation):
                filename = output_dir / f"output_{i}.wav"
                voice = voice_1 if i % 2 == 0 else voice_2

                tmp_path= await self._generate_audio(line.text, voice)
                os.rename(tmp_path, filename)
                filenames.append(str(filename))

            return filenames, str(output_dir)
        except Exception as e:
            raise RuntimeError(f"Failed to convert text to speech: {e}")


    async def _generate_audio(self, text: str, voice: str) -> str:
        """Generates audio from the given text using the specified voice.
        Args:
            text (str): The input text to be converted to audio.    
            voice (str): The voice to be used for the audio generation.
        Returns:
            str: Astring containing the filename of the generated audio file.
        Raises:
            RuntimeError: If the audio generation fails.
        """
        try:
            with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as tmp_file:

                response = self._llm_client.audio.speech.create(
                    model=self._config.model,
                    voice=voice.lower(),
                    input=text,
                    response_format="wav"
                )
                usage = response 
                tmp_path = tmp_file.name
                with open(tmp_path, "wb") as f:
                    f.write(response.content)
                """ with self._llm_client.audio.speech.with_streaming_response.create(
                    model=self._config.model,
                    voice=voice.lower(),
                    input=text,
                ) as response:
                    response.stream_to_file(tmp_path) """

            return tmp_path
        except Exception as e:
            raise RuntimeError(f"Failed to generate audio: {e}")



    def _create_output_directory(self) -> str:
        """Creates a unique output directory for the generated audio files.
        Returns:
            str: The name of the created output directory.
        Raises:
            RuntimeError: If the directory creation fails.
        """
        random_bytes = os.urandom(8)
        folder_name = base64.urlsafe_b64encode(random_bytes).decode("utf-8")
        final_folder_name = os.path.join(self._config.output_path, folder_name)
        os.makedirs(final_folder_name, exist_ok=True)
        return final_folder_name

    def _combine_audio_files(self, filenames: List[str], output_file: str) -> None:
        """Combines multiple audio files into a single WAV file.
        Args:
            filenames (List[str]): A list of filenames of the audio files to be combined.
            output_file (str): The name of the output WAV file.
        Raises:
            ValueError: If the input filenames list is empty.
            RuntimeError: If the audio file combination fails.
        """
        if not filenames:
            raise ValueError("No input files provided")

        try:
            audio_segments = []

            for filename in filenames:
                audio_segment = AudioSegment.from_mp3(filename)
                audio_segments.append(audio_segment)

            combined = sum(audio_segments, AudioSegment.empty())

            combined.export(output_file, format="wav")

            for filename in filenames:
                os.remove(filename)

        except Exception as e:
            raise RuntimeError(f"Failed to combine audio files: {e}")

    async def run(self, script:PodScript ,voice_1: str, voice_2: str) -> str:
        if self._config.mocked:
            return './articles/mocked_java9_openai_tts.wav'

        try:
            audio_files, folder_name = await self._text_to_speech(
                    script, voice_1, voice_2
            )
            final_output = os.path.join(folder_name, "combined_output.wav")
            self._combine_audio_files(audio_files, final_output)
            return final_output
        except Exception as e:
            raise RuntimeError(f"Failed to convert article to podcast: {e}")