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import streamlit as st
from huggingface_hub import InferenceClient
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")
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
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
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."
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?",
}
for key, value in replacements.items():
text = text.replace(key, value)
return text
def segmenter_texte(texte):
sentences = re.split(r'(?<=[.!?]) +', texte)
return sentences
st.set_page_config(layout="wide")
st.title('Générateur de Dictée')
with st.expander("Paramètres de la dictée", expanded=True):
mode = st.radio("Mode:", ["S'entrainer", "Entrainer"])
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)
col1, col2 = st.columns(2)
with col1:
st.audio(concatenated_audio_path, format='audio/mp3')
with col2:
# Utiliser st.session_state pour conserver la saisie de l'utilisateur
user_input = st.text_area("Écrivez la dictée ici:", value=st.session_state.get('user_input', ''), height=300, key='user_input')
if st.button('Correction'):
st.write("Dictée originale:")
st.text(dictee)
# Ajouter ici la logique de comparaison/correction détaillée si nécessaire
elif mode == "Entrainer":
st.text_area("Voici votre dictée :", dictee, height=300) |