Update app.py

app.py

@@ -37,7 +37,14 @@ body::before {
 
 #keras.config.set_floatx("bfloat16") uncomment to run at half precision.
 gemma_lm = keras_nlp.models.CausalLM.from_preset("hf://sultan-hassan/CosmoGemma_2b_en")
-chat = utils.ChatState(gemma_lm) # adding a chat helper to manage the conversation state (modified version from https://github.com/google-gemini/gemma-cookbook/blob/main/Gemma/Keras_Gemma_2_Quickstart_Chat.ipynb)
+#chat = utils.ChatState(gemma_lm) # adding a chat helper to manage the conversation state (modified version from https://github.com/google-gemini/gemma-cookbook/blob/main/Gemma/Keras_Gemma_2_Quickstart_Chat.ipynb)
+
+examples = [
+    'What are some common methods for model selection in astrophysics?', 
+    'Please list two interesting projects to work on to advance cosmology?',
+    'What is the primary reason for the decline in the number density of luminous quasars at redshifts greater than 5?',
+    'What is the primary goal of calibrating subgrid feedback models in cosmological simulations?',
+]
 
 def launch(message):
 
@@ -52,13 +59,14 @@ def launch(message):
     ind = out.index('\n\nResponse:\n') + len('\n\nResponse:\n')
     return out[ind:]
     
-    # This is to convert QA system to a chatbot
+    # This is to convert QA system to a chatbot by adding history to prompt
     #chat_history = chat.send_message(message) + "\n\n##### History #####\n\n" +  chat.get_history()  
     #return chat_history
 
 iface = gr.Interface(launch,
                      inputs="text",
                      outputs="text",
+                     examples=examples,
                      css=css,
                      title="Hey I am CosmoGemma 👋 I can answer cosmology questions from astroph.CO research articles. Try me :)",
                      description="Gemma_2b_en fine-tuned on QA pairs (~3.5k) generated from Cosmology and Nongalactic Astrophysics articles (arXiv astro-ph.CO) from 2018-2022 and tested on QA pairs (~1k) generated from 2023 articles, scoring over 75% accuracy.")