Datasets:
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})
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