import os

import gradio as gr
from openai import OpenAI

SYSTEM_PROMPT = "Ты — Сайга, русскоязычный автоматический ассистент. Ты разговариваешь с людьми и помогаешь им."
BASE_URL = os.getenv("BASE_URL")
API_KEY = os.getenv("API_KEY")
MODEL_NAME = "IlyaGusev/saiga_nemo_12b_gptq_8bit"
CLIENT = OpenAI(base_url=BASE_URL, api_key=API_KEY)


def user(message, history):
    new_history = history + [[message, None]]
    return "", new_history


def bot(
    history,
    system_prompt,
    top_p,
    temp
):
    messages = [{"role": "system", "content": SYSTEM_PROMPT}]

    for user_message, bot_message in history[:-1]:
        messages.append({"role": "user", "content": user_message})
        if bot_message:
            messages.append({"role": "assistant", "content": bot_message})

    last_user_message = history[-1][0]
    messages.append({"role": "user", "content": last_user_message})

    response = CLIENT.chat.completions.create(
        model=MODEL_NAME,
        messages=messages,
        temperature=temp,
        top_p=top_p,
        stream=True,
    )

    partial_text = ""
    for chunk in response:
        content = chunk.choices[0].delta.content
        partial_text += content
        history[-1][1] = partial_text
        yield history


with gr.Blocks(
    theme=gr.themes.Soft()
) as demo:
    favicon = '<img src="https://cdn.midjourney.com/b88e5beb-6324-4820-8504-a1a37a9ba36d/0_1.png" width="48px" style="display: inline">'
    gr.Markdown(
        f"""<h1><center>{favicon}Saiga Nemo 12B GPTQ 8 bit</center></h1>

        This is a demo of a **Russian**-speaking Mistral Nemo based model.

        Это демонстрационная версия [Сайги Немо с 12 миллиардами параметров](https://huggingface.co/IlyaGusev/saiga_nemo_12b).
        """
    )
    with gr.Row():
        with gr.Column(scale=5):
            system_prompt = gr.Textbox(label="Системный промпт", placeholder="", value=SYSTEM_PROMPT, interactive=False)
            chatbot = gr.Chatbot(label="Диалог")
        with gr.Column(min_width=80, scale=1):
            with gr.Tab(label="Параметры генерации"):
                top_p = gr.Slider(
                    minimum=0.0,
                    maximum=1.0,
                    value=0.9,
                    step=0.05,
                    interactive=True,
                    label="Top-p",
                )
                temp = gr.Slider(
                    minimum=0.0,
                    maximum=2.0,
                    value=0.01,
                    step=0.01,
                    interactive=True,
                    label="Температура"
                )
    with gr.Row():
        with gr.Column():
            msg = gr.Textbox(
                label="Отправить сообщение",
                placeholder="Отправить сообщение",
                show_label=False,
            )
        with gr.Column():
            with gr.Row():
                submit = gr.Button("Отправить")
                stop = gr.Button("Остановить")
                clear = gr.Button("Очистить")
    with gr.Row():
        gr.Markdown(
            """ПРЕДУПРЕЖДЕНИЕ: Модель может генерировать фактически или этически некорректные тексты. Мы не несём за это ответственность."""
        )

    # Pressing Enter
    submit_event = msg.submit(
        fn=user,
        inputs=[msg, chatbot],
        outputs=[msg, chatbot],
        queue=False,
    ).success(
        fn=bot,
        inputs=[
            chatbot,
            system_prompt,
            top_p,
            temp
        ],
        outputs=chatbot,
        queue=True,
    )

    # Pressing the button
    submit_click_event = submit.click(
        fn=user,
        inputs=[msg, chatbot],
        outputs=[msg, chatbot],
        queue=False,
    ).success(
        fn=bot,
        inputs=[
            chatbot,
            system_prompt,
            top_p,
            temp
        ],
        outputs=chatbot,
        queue=True,
    )

    # Stop generation
    stop.click(
        fn=None,
        inputs=None,
        outputs=None,
        cancels=[submit_event, submit_click_event],
        queue=False,
    )

    # Clear history
    clear.click(lambda: None, None, chatbot, queue=False)

demo.queue(max_size=128)
demo.launch(show_error=True)