# app.py
import gradio as gr
from my_memory_logic import run_with_session_memory

def chat_interface_fn(message, history, session_id):
    """
    Multi-turn chat function for Gradio's ChatInterface.
    'session_id' is used to store conversation across turns.
    """
    # 1) Call run_with_session_memory with user message and session_id
    answer = run_with_session_memory(message, session_id)

    # 2) Append the turn to the 'history' so Gradio UI displays it
    history.append((message, answer))
    
    # 3) Convert into message dicts for ChatInterface
    message_dicts = []
    for user_msg, ai_msg in history:
        message_dicts.append({"role": "user", "content": user_msg})
        message_dicts.append({"role": "assistant", "content": ai_msg})
    return message_dicts, history

# Define custom CSS to align messages
my_chat_css = """
/* Center the container horizontally so there's some margin */
.gradio-container {
  margin: auto;
}

/* Right-align user messages */
.user .wrap {
  text-align: right !important;
}

/* Left-align assistant messages */
.assistant .wrap {
  text-align: left !important;
}
"""

with gr.Blocks(css=my_chat_css) as demo:
    gr.Markdown("### DailyWellnessAI (User on right, Assistant on left)")
    session_id_box = gr.Textbox(label="Session ID", value="abc123", interactive=True)
    
    chat_interface = gr.ChatInterface(
        fn=lambda msg, hist: chat_interface_fn(msg, hist, session_id_box.value),
        title="DailyWellnessAI (Session-based Memory)",
        description="Ask your questions. The session_id determines your stored memory."
    )

demo.launch()