Update app.py

app.py

@@ -12,8 +12,6 @@ MAX_CONTEXT_LENGTH = 4096  # Example: Adjust based on your model
 ################################
 # SYSTEM PROMPT (PATIENT ROLE) #
 ################################
-# This is the core text that tells the LLM to behave as the "patient."
-# You can store it in "prompt.txt" or include it directly here as a string.
 nvc_prompt_template = """
 You are now taking on the role of a single user (a “patient”) seeking support for various personal and emotional challenges.
 
@@ -65,8 +63,8 @@ def respond(
 
     # Truncate history to fit within max tokens
     truncated_history = truncate_history(
-        history, 
-        formatted_system_message, 
+        history,
+        formatted_system_message,
         MAX_CONTEXT_LENGTH - max_tokens - 100  # Reserve some space
     )
 
@@ -100,24 +98,15 @@ def respond(
         print(f"An error occurred: {e}")
         yield "I'm sorry, I encountered an error. Please try again."
 
-###################
-# INITIAL MESSAGE #
-###################
-# This is how we make the LLM "start" by playing the role of the user/patient.
-# Essentially, we seed the conversation with an initial user message (from the LLM).
+# OPTIONAL: An initial user message (the LLM "as user") if desired
 initial_user_message = (
-    "I really don’t know where to begin… I feel so overwhelmed lately. "
-    "My neighbors keep playing loud music, I’m arguing with my partner about money, "
-    "and on top of that, two of my friends are in a fight and it’s splitting the group. "
-    "I just feel powerless in all these situations."
+    "I really don’t know where to begin… I feel overwhelmed lately. "
+    "My neighbors keep playing loud music, and I’m arguing with my partner about money. "
+    "Also, two of my friends are fighting, and the group is drifting apart. "
+    "I just feel powerless."
 )
 
 # --- Gradio Interface ---
-def start_conversation():
-    """Creates the initial chat state, so the LLM 'as user' starts talking."""
-    # Return a conversation with a single user message: the LLM’s "patient" message
-    return [("Hi there!", initial_user_message)]
-
 demo = gr.ChatInterface(
     fn=respond,
     additional_inputs=[
@@ -126,11 +115,9 @@ demo = gr.ChatInterface(
         gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
         gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)"),
     ],
-    # We can initialize the conversation so the LLM starts with a 'user' message.
-    # Depending on your version of Gradio, you might set `default_message=...` or
-    # `submit_on_start=True`. Adjust as needed.
-    # Here we use a function that returns an initial conversation state:
-    chatbot = start_conversation()
+    # You can optionally set 'title' or 'description' to show some info in the UI:
+    title="NVC Patient Chatbot",
+    description="This chatbot behaves like a user/patient describing personal challenges."
 )
 
 if __name__ == "__main__":