README.md

metadata

license: mit
language:
  - fr

Clone this dataset and go crazy

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})