Update app.py

app.py

@@ -1,29 +1,37 @@
-
 import streamlit as st
-from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM
-
-# Load the pipeline
-model_name = "Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2"
-pipe = pipeline("text-generation", model=model_name)
+from transformers import pipeline
 
-# Optionally load the tokenizer and model directly (not used directly in this example)
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForCausalLM.from_pretrained(model_name)
+# Load the model pipeline
+@st.cache_resource  # Cache the model to avoid reloading
+def load_pipeline():
+    model_name = "Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2"
+    return pipeline("text-generation", model=model_name)
 
-def generate_response(prompt):
-    """Generate a response from the model given a prompt."""
-    response = pipe(prompt, max_length=100, num_return_sequences=1)
-    return response[0]['generated_text']
+pipe = load_pipeline()
 
-# Streamlit Interface
-st.title("AI Chatbot using Hugging Face")
-st.markdown("This app uses the Llama-3.1-8B-Lexi-Uncensored-V2 model to generate responses.")
+# App UI
+st.set_page_config(page_title="Hugging Face Chatbot", layout="centered")
+st.title("🤖 AI Chatbot")
+st.markdown(
+    """
+    Welcome to the **AI Chatbot** powered by Hugging Face's Llama-3.1-8B-Lexi-Uncensored-V2 model. 
+    Enter your message below to get started!
+    """
+)
 
-user_input = st.text_input("Enter your message:", placeholder="Type something here...")
+# Input Box
+user_input = st.text_area(
+    "Your Message", 
+    placeholder="Type your message here...", 
+    height=100
+)
 
+# Generate Button
 if st.button("Generate Response"):
-    if user_input:
-        response = generate_response(user_input)
-        st.text_area("Response:", value=response, height=200)
+    if user_input.strip():
+        with st.spinner("Generating response..."):
+            response = pipe(user_input, max_length=150, num_return_sequences=1)
+            st.text_area("Response", value=response[0]['generated_text'], height=200)
     else:
         st.warning("Please enter a message before clicking the button.")
+