conversation starters

app.py

@@ -1,13 +1,15 @@
 from llama_cpp import Llama
 import gradio as gr
 
+
 llm = Llama.from_pretrained(
 	repo_id="rcarioniporras/model_modelcentric_llama_gguf",
 	filename="unsloth.Q4_K_M.gguf",
 )
 
+
 def predict(message, history):
-    messages = [{"role": "system", "content": "You are a helpful assistant."}]
+    messages = [{"role": "system", "content": "You are a helpful assistant who answers questions in a concise but thorough way. Prioritize clarity and usefulness in all interactions."}]
     for user_message, bot_message in history:
         if user_message:
             messages.append({"role": "user", "content": user_message})
@@ -25,7 +27,15 @@ def predict(message, history):
             response += part
         yield response
 
-demo = gr.ChatInterface(predict)
+conversation_starters = [
+    {"text": "What is object-oriented programming (OOP), and what are its four main principles?"},
+    {"text": "Compare the stack and queue data structures."},
+    {"text": "Simplify the expression 3(x+4)−2(2x−1)."},
+    {"text": "What are some fun facts about space?"}
+]
+
+demo = gr.ChatInterface(predict, examples=conversation_starters, theme="Shivi/calm_seafoam")
+                        
 
 if __name__ == "__main__":
     demo.launch()