import os
import subprocess
from datetime import datetime
import gradio as gr

# 自動檢查並安裝必要的套件
def install_and_import(package):
    try:
        __import__(package)
    except ImportError:
        subprocess.check_call(["pip", "install", package])

# 安裝依賴
install_and_import("notion-client")
install_and_import("gradio")
install_and_import("groq")

from notion_client import Client
from groq import Groq

# 從環境變數中提取 Notion API Key 和資料庫 ID
NOTION_API_KEY = os.getenv("NOTION_API_KEY")
NOTION_DB_ID = os.getenv("NOTION_DB_ID")

if not NOTION_API_KEY or not NOTION_DB_ID:
    raise ValueError("請設置 NOTION_API_KEY 和 NOTION_DB_ID 環境變數！")

# 初始化 Notion 客戶端
notion = Client(auth=NOTION_API_KEY)

# 設定 Groq 的 API Key
groq_key = os.getenv("groq_key")
if not groq_key:
    raise ValueError("groq_key 環境變數未設置！")

client = Groq(api_key=groq_key)

# 定義 Chatbot 類
class SimpleChatBot:
    def __init__(self):
        self.initial_prompt = [
            {
                "role": "system",
                "content": "你是一個英文老師，會教我背單字，並用蘇格拉底問答引導我，引導時請用繁體中文 zhTW"
            }
        ]

    def get_response(self, message, chat_history):
        messages = self.initial_prompt + chat_history
        messages.append({"role": "user", "content": message})

        # 使用 groq 的 chat.completions API 生成回應
        completion = client.chat.completions.create(
            model="llama3-8b-8192",
            messages=messages,
            temperature=1,
            max_tokens=1024,
            top_p=1,
            stream=False,
        )

        # 修正：正確提取 completion 的內容
        response_content = completion.choices[0].message.content
        return response_content

chatbot = SimpleChatBot()

# 記錄聊天內容到 Notion 資料庫
def log_to_notion(user_name, user_message, bot_response):
    try:
        timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
        notion.pages.create(
            parent={"database_id": NOTION_DB_ID},
            properties={
                "Timestamp": {"date": {"start": timestamp}},
                "Name": {"title": [{"text": {"content": user_name or "Anonymous"}}]},
                "User Input": {"rich_text": [{"text": {"content": user_message}}]},
                "Bot Response": {"rich_text": [{"text": {"content": bot_response}}]},
            },
        )
        print("Logged to Notion successfully.")
    except Exception as e:
        print(f"Error logging to Notion: {e}")

# 定義回應邏輯
def respond(name, message, chat_history):
    chat_history = [{"role": entry["role"], "content": entry["content"]} for entry in chat_history]
    response = chatbot.get_response(message, chat_history)
    chat_history.append({"role": "user", "content": message})
    chat_history.append({"role": "assistant", "content": response})

    # 記錄到 Notion
    log_to_notion(name, message, response)

    return chat_history, ""

# 定義用於存儲用戶名字的狀態
def set_name(name):
    return name

# 建立 Gradio 界面
with gr.Blocks(title="簡單的Gradio聊天機器人") as demo:
    gr.Markdown("# 簡單的Gradio聊天機器人")
    
    # 用戶名稱輸入框
    with gr.Row():
        name_input = gr.Textbox(placeholder="輸入你的名字（僅需填寫一次）", label="你的名字", interactive=True)
        name_button = gr.Button("確認名字")
    
    # 聊天區
    chatbot_interface = gr.Chatbot(type="messages")
    with gr.Row():
        user_input = gr.Textbox(placeholder="輸入訊息...", label="你的訊息")
        send_button = gr.Button("發送")
    
    # 狀態保持，用於存儲用戶名稱
    user_name = gr.State()

    # 事件綁定
    name_button.click(set_name, inputs=[name_input], outputs=[user_name])
    send_button.click(
        respond, 
        inputs=[user_name, user_input, chatbot_interface], 
        outputs=[chatbot_interface, user_input]
    )
    
    demo.launch(share=True)