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# 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()
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