app.py

from transformers import pipeline, AutoTokenizer, AutoModelForSeq2SeqLM
import gradio as gr
import joblib
import soundfile as sf
import nemo.collections.asr as nemo_asr


pipe = pipeline("text-generation", model="greykingreys/bart_CHATbotOrangeMoney_model")

asr_canary = nemo_asr.models.ASRModel.from_pretrained("nvidia/canary-1b-flash")
narrator_fr = pipeline("text-to-speech", model="facebook/mms-tts-fra")

tokenizer = AutoTokenizer.from_pretrained("greykingreys/bart_CHATbotOrangeMoney_model")
model = AutoModelForSeq2SeqLM.from_pretrained("greykingreys/bart_CHATbotOrangeMoney_model")

# Fonction
def chat(prompt):
    inputs = tokenizer(prompt, return_tensors="pt", truncation=True, padding="max_length", max_length=512)
    outputs = model.generate(
        input_ids=inputs["input_ids"],
        attention_mask=inputs["attention_mask"],
        max_length=512,
        num_beams=5,
        do_sample=True,
        temperature=0.9
    )
    return tokenizer.decode(outputs[0], skip_special_tokens=True)

def vocal(audio):
    transcriptions = asr_canary.transcribe([audio], source_lang = 'fr', target_lang =  "fr")
    text = transcriptions[0].text
    text = chat(text)
    narrated_text = narrator_fr(text)
    sf.write("narrated_audio3.wav", narrated_text["audio"][0], narrated_text["sampling_rate"])
    return text, 'narrated_audio3.wav'


# Configuration de l'interface Gradio
site = gr.Blocks(theme='NoCrypt/miku')


chatbot = gr.Interface(
    fn = chat,
    inputs=gr.Textbox(lines=2, placeholder="Posez-moi une question sur OM..."),
    outputs=gr.Textbox(lines = 12, label= 'Reponse'),
    title="Chatbot d'assistance Orange Money",
    description="Un chatbot qui vous assiste dans vos activitez avec le service orange money",
    examples=[
        ["Comment consulter mon solde sur Orange Money"],
        ["Comment recharger de credit un compte avec Orange money"],
        ["comment activer mon compte"]
    ]
)

vocalbot = gr.Interface(fn = vocal,
                     inputs = gr.Audio(sources="microphone",
                    type="filepath"),
                     outputs = [
                         gr.Textbox(lines = 7, label = 'text'),
                         gr.Audio(label= 'audio')
                     ],
                     title = "audio d'assistance Orange Money",
                     description = "Vous etes pressé, utiliser l'interface audio pour votre assistance Orange Money"
                    )

with site:
    gr.TabbedInterface(
        [chatbot,
         vocalbot,],
        ["Assistance en ecrit",
         "Assitance en audio"],)

site.launch()