import gradio as gr
from huggingface_hub import InferenceClient
import json
import os

client = InferenceClient("Qwen/Qwen2.5-72B-Instruct")

def respond(
    message,
    history: list[tuple[str, str]],
    system_message,
    max_tokens,
    temperature,
    top_p,
):
    messages = [{"role": "system", "content": system_message}]

    for val in history:
        if val[0]:
            messages.append({"role": "user", "content": val[0]})
        if val[1]:
            messages.append({"role": "assistant", "content": val[1]})

    messages.append({"role": "user", "content": message})

    response = ""

    for message in client.chat_completion(
        messages,
        max_tokens=max_tokens,
        stream=True,
        temperature=temperature,
        top_p=top_p,
    ):
        token = message.choices[0].delta.content

        response += token
        yield response

def load_rooms():
    if os.path.exists("rooms.json"):
        with open("rooms.json", "r", encoding="utf-8") as f:
            return json.load(f)
    return {}

def save_rooms(rooms):
    with open("rooms.json", "w", encoding="utf-8") as f:
        json.dump(rooms, f, ensure_ascii=False, indent=4)

def create_room(rooms, room_name):
    if room_name not in rooms:
        rooms[room_name] = []
    save_rooms(rooms)
    return rooms

def switch_room(room_name, rooms):
    return rooms.get(room_name, [])

def add_message_to_room(room_name, rooms, message, response):
    if room_name in rooms:
        rooms[room_name].append((message, response))
        save_rooms(rooms)

def chat_interface(room_name, rooms, message, history, system_message, max_tokens, temperature, top_p):
    response = list(respond(message, history, system_message, max_tokens, temperature, top_p))[-1]
    add_message_to_room(room_name, rooms, message, response)
    return response, history + [(message, response)]

def main():
    rooms = load_rooms()
    room_names = list(rooms.keys())
    with gr.Blocks() as demo:
        with gr.Row():
            with gr.Column():
                room_name_dropdown = gr.Dropdown(room_names, label="会話部屋", value=room_names[0] if room_names else None)
                new_room_name = gr.Textbox(label="新しい会話部屋の名前")
                create_room_button = gr.Button("新しい会話部屋を作成")
                create_room_button.click(
                    fn=lambda name, r: (create_room(r, name), name, switch_room(name, r)),
                    inputs=[new_room_name, gr.State(rooms)],
                    outputs=[room_name_dropdown, room_name_dropdown, gr.Chatbot]
                )
                room_name_dropdown.change(
                    fn=lambda name, r: (switch_room(name, r),),
                    inputs=[room_name_dropdown, gr.State(rooms)],
                    outputs=[gr.Chatbot]
                )
            with gr.Column(scale=3):
                chatbot = gr.Chatbot(label="会話")
                message = gr.Textbox(label="メッセージ")
                system_message = gr.Textbox(value="あなたは親切なチャットボットでありQwenというLLMです。", label="システムメッセージ")
                max_tokens = gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="新規トークン最大")
                temperature = gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="温度")
                top_p = gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (核 sampling)")
                submit_button = gr.Button("送信")
                submit_button.click(
                    fn=chat_interface,
                    inputs=[room_name_dropdown, gr.State(rooms), message, chatbot, system_message, max_tokens, temperature, top_p],
                    outputs=[chatbot, chatbot]
                )

    demo.launch()

if __name__ == "__main__":
    main()