import gradio as gr
from huggingface_hub import InferenceClient
#from sentence_transformers import SentenceTransformer
#import torch
#import numpy as np # import libraries
client = InferenceClient("microsoft/phi-4")
def respond(message, history):
    #context = get_relevent_context(message, top_k=3)
    messages = [{"role": "system", "content": "You are a friendly kpop expert chatbot."}]
    if history:
        messages.extend(history)
    messages.append({"role": "user", "content": message})
    response = client.chat_completion(
        messages,
        max_tokens=10000
    )
    return response['choices'][0]['message']['content'].strip()
chatbot = gr.ChatInterface(respond, type="messages")
title = "Kpop chatbot"
topics = """
Welcone to Kpop song Hunters!!
"""
disclaimer = ""
custom_css = """
.gradio-container { background-color: #FFF5F2 !important; }
.gradio-chat { background-color: #A6B28B !important; }
.chat-interface { background-color: #F5C9B0 !important; }
.chat-message { background-color: #F9F6F3 !important; }
"""

with gr.Blocks(css=custom_css) as demo:
    gr.Markdown("Welcome to K‑Pop Chatbot!")
    gr.ChatInterface(fn=respond, type="messages")
demo.launch()

with gr.Blocks() as chatbot:
    with gr.Row():
        with gr.Column(scale=1):   # ← LEFT COLUMN (sidebar)
            gr.Markdown(title)     # Shows your "# :rocket: Lift Off :rocket: "heading
            gr.Markdown(topics)    # Shows your welcome text & bullet list
        with gr.Column(scale=2):   # ← RIGHT COLUMN (main chat area)
           gr.ChatInterface(
                fn=respond,
                type="messages"
            )
    with gr.Row():
        gr.Markdown(disclaimer)    # Footer disclaimer text
chatbot.launch()