import streamlit as st
from transformers import pipeline

Configuration de la page

st.title("Ray - Mon IA")

Chargement du modèle (mis en cache pour aller vite)

@st .cache_resource
def load_model():
return pipeline("text-generation", model="HuggingFaceTB/SmolLM-135M-Instruct")

chat_ia = load_model()

Initialisation de la mémoire

if "messages" not in st.session_state:
st.session_state.messages = []

Affichage des anciens messages

for message in st.session_state.messages:
with st.chat_message(message["role"]):
st.markdown(message["content"])

Zone de saisie

if prompt := st.chat_input("Dis quelque chose à Ray..."):
st.session_state.messages.append({"role": "user", "content": prompt})
with st.chat_message("user"):
st.markdown(prompt)

# Génération de la réponse
with st.chat_message("assistant"):
    full_prompt = f"Tu es Ray, un assistant poli en français.\nUser: {prompt}\nAssistant:"
    res = chat_ia(full_prompt, max_length=150, do_sample=True)
    reponse = res[0]['generated_text'].split("Assistant:")[-1].strip()
    st.markdown(reponse)
    st.session_state.messages.append({"role": "assistant", "content": reponse})