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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.
Deduplicates consecutive repeated Q&A pairs to avoid repetition.
"""
# 1) Get answer from the session-based memory pipeline
answer = run_with_session_memory(message, session_id)
# 2) Deduplicate consecutive identical exchanges
if not history or history[-1]["content"] != answer:
history.append({"role": "user", "content": message})
history.append({"role": "assistant", "content": answer})
# 3) Convert history to message dictionaries for display
message_dicts = []
for msg in history:
message_dicts.append(msg) # Directly append the dictionary
# Return the message dicts and updated history
return message_dicts, history
# Custom CSS for chat interface
my_chat_css = """
.gradio-container {
margin: auto;
}
.user .wrap {
text-align: right !important;
}
.assistant .wrap {
text-align: left !important;
}
"""
# Set up Gradio interface
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."
)
# Launch the Gradio interface
demo.launch()
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