# app.py - ElevenLabs Podcast Dubbing Project
"""
Voices Across Borders - A Multilingual Podcast Audio Dubbing Tool

This Streamlit-based app takes a Spanish podcast/audio file, dubs it in English via ElevenLabs API,
and runs a linguistic and semantic QA using LLMs (in this case, Llama-3-8-B via Groq) to evaluate
translation accuracy and tone. Ideal for showcasing real-world multilingual API deployment.
"""

import streamlit as st
from elevenlabs.client import ElevenLabs
from groq import Groq
from pydub import AudioSegment
from dotenv import load_dotenv
import os
import io

load_dotenv()

# ======CONFIGURATION========
GROQ_API_KEY = os.getenv("GROQ_API_KEY")
ELEVENLABS_API_KEY = os.getenv("ELEVENLABS_API_KEY")

print("GROQ_API_KEY loaded?", bool(GROQ_API_KEY))
print("ELEVENLABS_API_KEY loaded?", bool(ELEVENLABS_API_KEY))

# Initialize ElevenLabs client
client_el = ElevenLabs(api_key=ELEVENLABS_API_KEY)
# Initialize Groq client
client_gr = Groq(api_key=GROQ_API_KEY)

# ======APP LAYOUT========
def transcribe_audio(audio_file):
    print("Transcribing audio...")
    # Transcribe audio using ElevenLabs API
    audio_data = AudioSegment.from_file(audio_file)
    audio_data = audio_data.set_frame_rate(44100).set_channels(1).set_sample_width(2) # Convert to 2 bytes / 16-bit .wav
    audio_buffer = io.BytesIO()
    audio_data.export(audio_buffer, format="wav")
    audio_buffer.seek(0)
    print("Audio converted successfully!")
    with print("✍ Transcribing audio... "):
        transcript = client_el.speech_to_text.convert(
            file = audio_buffer,
            model_id = "scribe_v1"
        )
    return transcript.text

def translate_transcript(transcript):
    print("Translating transcript using Llama-3-8B...")
    completion = client_gr.chat.completions.create(
        model = "llama3-8b-8192",
        messages = [
            {
                "role": "user",
                "content": f"""Translate the following Spanish text to professional English.
                Only return the translation, nothing else. Do not provide any commentary afterward.\n\n{transcript}"""
            }
        ]
    )

    response = completion.choices[0].message.content
    return response

# Helper function for generate_dub
def convert_audio_response(audio, to_wav=False):
    # Handle generator or bytes input
    if isinstance(audio, (bytes, bytearray)):
        audio_bytes = audio
    elif hasattr(audio, '__iter__'):
        audio_bytes = b''.join(audio)
    else:
        raise ValueError("Unsupported audio format.")

    audio_stream = io.BytesIO(audio_bytes)
    audio_stream.seek(0)
    return audio_stream, "audio/mp3"

def generate_dub(translated_text, to_wav=False):
    try:
        audio_data = client_el.text_to_speech.convert(
            text=translated_text,
            voice_id="nPczCjzI2devNBz1zQrb",
            model_id="eleven_multilingual_v2"
        )

        audio_stream, mime_type = convert_audio_response(audio_data, to_wav=to_wav)
        return audio_stream, mime_type

    except Exception as e:
        print(f"ElevenLabs API error: {e}")
        return None, None
        
def run_quality_check(spanish, english):
    qa_prompt = f"""
    Compare the following Spanish source with its English translation.
    - Identify any mistranslations or tone shifts.
    - Rate fluency and accuracy from 1 to 10.
    
    Spanish: {spanish}
    English: {english}

    """

    completion = client_gr.chat.completions.create(
        model = "llama3-8b-8192",
        messages = [
            {
                "role": "user",
                "content": qa_prompt
            }
        ]
    )

    response = completion.choices[0].message.content
    return response

# ======APP LOGIC========
st.title("Voices Across Borders - Multilingual Podcast Dubbing Tool")
st.write("Upload a Spanish podcast audio file for dubbing in English.")
uploaded_file = st.file_uploader("Choose a Spanish audio file", type=["mp3", "wav"])

if uploaded_file:
    transcript = transcribe_audio(uploaded_file)
    st.subheader("📜Transcription")
    st.write(transcript)

    translated = translate_transcript(transcript)
    st.subheader("Translated Text")
    st.write(translated)

    with st.spinner("💿 Generating dub..."):
        dubbed_audio, mime_type = generate_dub(translated)
        if dubbed_audio:
            st.success("Dubbing process completed successfully!")
            dubbed_audio.seek(0)
            st.audio(dubbed_audio, format=mime_type)
            st.download_button(
                label="Download dub",
                data = dubbed_audio,
                file_name = f"dubbed_audio.{mime_type.split('/')[-1]}",
                mime=mime_type
            )
        else:
            st.warning("No audio to play or download.")

    with st.spinner("Running quality check... "):
        qa_result = run_quality_check(transcript, translated)
        if qa_result:
            st.success("Quality check complete!")
    st.markdown("### Quality Check Result")
    st.write(qa_result)