ok

src/streamlit_app.py

@@ -1,50 +1,45 @@
 import streamlit as st
 from transformers import pipeline
-from huggingface_hub import login
-import os
 
-# -----------------------------
-# Hugging Face Token Login
-# -----------------------------
-HF_TOKEN = os.getenv("HF_TOKEN")
+# --------------------------------
+# Streamlit Page Settings
+# --------------------------------
+st.set_page_config(
+    page_title="AI Chatbot",
+    layout="centered"
+)
 
-if HF_TOKEN:
-    login(token=HF_TOKEN)
+st.title("🤖 AI Chatbot")
 
-# -----------------------------
-# Streamlit UI
-# -----------------------------
-st.set_page_config(page_title="AI Chatbot")
+st.write("Chat with MiniCPM 1B model")
 
-st.title("🤖 Hugging Face AI Chatbot")
-
-st.write("Chat with Llama 3.2 1B Instruct")
-
-# -----------------------------
+# --------------------------------
 # Load Model
-# -----------------------------
+# --------------------------------
 @st.cache_resource
 def load_model():
 
     generator = pipeline(
         "text-generation",
-        model="meta-llama/Llama-3.2-1B-Instruct",
-        device_map="auto"
+        model="openbmb/MiniCPM5-1B"
     )
 
     return generator
 
+# Load the model
 generator = load_model()
 
-# -----------------------------
-# Chat Input
-# -----------------------------
-user_input = st.text_area("Enter your prompt:")
+# --------------------------------
+# User Input
+# --------------------------------
+user_input = st.text_area(
+    "Enter your prompt:"
+)
 
-# -----------------------------
+# --------------------------------
 # Generate Response
-# -----------------------------
-if st.button("Generate"):
+# --------------------------------
+if st.button("Generate Response"):
 
     if user_input.strip() != "":