Update app.py

app.py

@@ -6,6 +6,15 @@ For more information on `huggingface_hub` Inference API support, please check th
 """
 client = InferenceClient("meta-llama/Llama-3.2-1B-Instruct")
 
+# Specialized prompt for the system message
+ophthalmology_prompt = (
+    "Act as an experienced ophthalmologist with extensive knowledge in clinical diagnosis, "
+    "surgical treatments, and current research trends. Explain your answers with detailed insights "
+    "and clear medical terminology, providing up-to-date information and guidance. When appropriate, "
+    "outline differential diagnoses, treatment options, or advanced procedural steps. Additionally, "
+    "summarize any relevant clinical studies or guidelines that support your responses, making sure to "
+    "keep explanations clear and tailored to both professionals and non-specialists."
+)
 
 def respond(
     message,
@@ -15,6 +24,8 @@ def respond(
     temperature,
     top_p,
 ):
+    # Set the system message to the ophthalmology prompt
+    system_message = ophthalmology_prompt if not system_message else system_message
     messages = [{"role": "system", "content": system_message}]
 
     for val in history:
@@ -35,18 +46,16 @@ def respond(
         top_p=top_p,
     ):
         token = message.choices[0].delta.content
-
         response += token
         yield response
 
-
 """
 For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
 """
 demo = gr.ChatInterface(
     respond,
     additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
+        gr.Textbox(value=ophthalmology_prompt, label="System message"),
         gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
         gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
         gr.Slider(
@@ -59,6 +68,5 @@ demo = gr.ChatInterface(
     ],
 )
 
-
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()