import streamlit as st
from huggingface_hub import InferenceClient
import time
import re
import edge_tts
import asyncio
from concurrent.futures import ThreadPoolExecutor
import tempfile
from pydub import AudioSegment

# Initialize Hugging Face InferenceClient
client_hf = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1")

# Define the async function for text-to-speech conversion using Edge TTS
async def text_to_speech_edge(text, language_code):
    voice = {"fr": "fr-FR-RemyMultilingualNeural"}[language_code]
    communicate = edge_tts.Communicate(text, voice)
    with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as tmp_file:
        tmp_path = tmp_file.name
    await communicate.save(tmp_path)
    return tmp_path

# Helper function to run async functions from within Streamlit (synchronous context)
def run_in_threadpool(func, *args, **kwargs):
    loop = asyncio.new_event_loop()
    asyncio.set_event_loop(loop)
    future = asyncio.ensure_future(func(*args, **kwargs))
    return loop.run_until_complete(future)

def concatenate_audio(paths):
    combined = AudioSegment.empty()
    for path in paths:
        audio = AudioSegment.from_mp3(path)
        combined += audio
    combined_path = tempfile.mktemp(suffix=".mp3")
    combined.export(combined_path, format="mp3")
    return combined_path

# Modified function to work with async Edge TTS
def dictee_to_audio_segmented(dictee):
    sentences = segmenter_texte(dictee)
    audio_urls = []
    with ThreadPoolExecutor() as executor:
        for sentence in sentences:
            processed_sentence = replace_punctuation(sentence)
            audio_path = executor.submit(run_in_threadpool, text_to_speech_edge, processed_sentence, "fr").result()
            audio_urls.append(audio_path)
    return audio_urls

def generer_dictee(classe, longueur):
    prompt = f"Créer une dictée pour la classe {classe} d'une longueur d'environ {longueur} mots. Il est important de créer le texte uniquement de la dictée et de ne pas ajouter de consignes ou d'indications supplémentaires."
    generate_kwargs = {
        "temperature": 0.7,
        "max_new_tokens": 1000,
        "top_p": 0.95,
        "repetition_penalty": 1.2,
        "do_sample": True,
    }
    formatted_prompt = f"<s>[INST] {prompt} [/INST]"
    stream = client_hf.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
    dictee = ""
    for response in stream:
        dictee += response.token.text
    dictee = dictee.replace("</s>", "").strip()
    return dictee

def replace_punctuation(text):
    replacements = {
        ".": " point,",
        ",": " virgule.",
        ";": " point-virgule;",
        ":": " deux-points:",
        "!": " point d'exclamation!",
        "?": " point d'interrogation?",
        "-": " tiret-",
        "'": " apostrophe'",
    }
    for key, value in replacements.items():
        text = text.replace(key, value)
    return text

def segmenter_texte(texte):
    sentences = re.split(r'(?<=[.!?]) +', texte)
    return sentences

# Streamlit App Interface
st.title('Générateur de Dictée')

mode = st.radio("Mode:", ["S'entrainer", "Entrainer"])

with st.expander("Paramètres de la dictée"):
    classe = st.selectbox("Classe", ["CP", "CE1", "CE2", "CM1", "CM2", "6ème", "5ème", "4ème", "3ème", "Seconde", "Premiere", "Terminale"], index=2)
    longueur = st.slider("Longueur de la dictée (nombre de mots)", 50, 500, 200)
    
if st.button('Générer la Dictée'):
    with st.spinner("Génération de la dictée en cours..."):
        dictee = generer_dictee(classe, longueur)
        if mode == "S'entrainer":
            audio_urls = dictee_to_audio_segmented(dictee)
            concatenated_audio_path = concatenate_audio(audio_urls)
            st.success("Dictée générée. Utilisez le bouton ci-dessous pour écouter la dictée entière.")
            st.audio(concatenated_audio_path, format='audio/wav', start_time=0)
            with st.expander("Phrases de la Dictée"):
                for idx, url in enumerate(audio_urls, start=1):
                    st.markdown(f"**Phrase {idx}:**")
                    st.audio(url, format='audio/wav')
        elif mode == "Entrainer":
            st.text_area("Voici votre dictée :", dictee, height=300)