import gradio as gr
from huggingface_hub import InferenceClient
import plotly.express as px

# Inisialisasi client
client = InferenceClient("meta-llama/Meta-Llama-3-8B-Instruct")

# Fungsi untuk menghasilkan plot acak
def random_plot():
    df = px.data.iris()
    fig = px.scatter(df, x="sepal_width", y="sepal_length", color="species",
                    size='petal_length', hover_data=['petal_width'])
    return fig

# Fungsi untuk mencetak data suka/tidak suka
def print_like_dislike(x: gr.LikeData):
    print(x.index, x.value, x.liked)

# Fungsi untuk menambahkan pesan ke riwayat
def add_message(history, message):
    if message["files"]:
        for x in message["files"]:
            history.append(((x,), None))
    if message["text"] is not None:
        history.append((message["text"], None))
    return history, gr.Textbox(value="", interactive=True)

# Fungsi untuk menghubungkan dengan model Llama
def chat_mem(message, chat_history):
    chat_history_role = [{"role": "system", "content": "Anda adalah Chat Bot milik Riswan Nopiyar, yang dirancang untuk membantu menjawab pertanyaan dan memberikan informasi dengan sopan dan akurat dalam bahasa Indonesia. Seluruh percakapan akan dilakukan dalam bahasa Indonesia."}]
    
    if chat_history:
        for user_msg, assistant_msg in chat_history:
            chat_history_role.append({"role": "user", "content": user_msg})
            chat_history_role.append({"role": "assistant", "content": assistant_msg})
    
    chat_history_role.append({"role": "user", "content": message})
    
    if "siapa pembuat" in message.lower() or "siapa pencipta" in message.lower():
        assistant_response = "Chatbot ini dibuat oleh Riswan Nopiyar. Jika Anda memiliki pertanyaan lain atau membutuhkan bantuan lebih lanjut, jangan ragu untuk bertanya."
    else:
        chat_completion = client.chat_completion(
            messages=chat_history_role,
            max_tokens=500,
        )
        assistant_response = chat_completion.choices[0].message.content
    
    chat_history_role.append({"role": "assistant", "content": assistant_response})

    modified = [msg["content"] for msg in chat_history_role]
    chat_history = [(modified[i * 2 + 1], modified[i * 2 + 2]) for i in range(len(modified) // 2)]

    return "", chat_history

fig = random_plot()

# Membuat antarmuka Gradio
with gr.Blocks(fill_height=True) as demo:
    chatbot = gr.Chatbot(
        elem_id="chatbot",
        bubble_full_width=False,
        scale=1,
    )

    chat_input = gr.Textbox(interactive=True,
                            placeholder="Enter message...", show_label=False)

    chat_msg = chat_input.submit(add_message, [chatbot, chat_input], [chatbot, chat_input])
    bot_msg = chat_msg.then(chat_mem, inputs=[chat_input, chatbot], outputs=[chat_input, chatbot], api_name="bot_response")
    bot_msg.then(lambda: gr.Textbox(interactive=True), None, [chat_input])

    chatbot.like(print_like_dislike, None, None)

demo.launch()