import os
import gradio as gr
from datetime import datetime

# Install and import required packages
try:
    from notion_client import Client
except ImportError:
    os.system('pip install notion-client')
    from notion_client import Client

try:
    from groq import Groq
except ImportError:
    os.system('pip install groq')
    from groq import Groq

# Initialize Groq client with API key
client = Groq(api_key=os.getenv('groq_key'))

# Initialize Notion client
notion = Client(auth=os.getenv("NOTION_API_KEY"))
NOTION_DB_ID = os.getenv("NOTION_DB_ID")

def log_to_notion(name, user_input, bot_response):
    """Logs the conversation to Notion."""
    try:
        notion.pages.create(
            parent={"database_id": NOTION_DB_ID},
            properties={
                "Name": {"title": [{"text": {"content": name}}]},
                "Timestamp": {"date": {"start": datetime.now().isoformat() }},
                "User Input": {"rich_text": [{"text": {"content": user_input}}]},
                "Bot Response": {"rich_text": [{"text": {"content": bot_response}}]},
            },
        )
    except Exception as e:
        print(f"Failed to log to Notion: {e}")

def process_message(message, history):
    """Processes the user message and returns the bot response."""
    messages = [
        {
            "role": "system",
            "content": "你是一個高中數學老師，使用的語言是英文。學生用中文問妳任何字彙，你都可以告訴他那個中文對應的英文和例句，以及在數學上的可能用法以及數學例題和解法。\n說明數學上的可能用法時，先用中文講一遍再用B1程度的英文複述一遍\n"
        }
    ]

    for user_msg, bot_msg in history:
        messages.append({"role": "user", "content": user_msg})
        messages.append({"role": "assistant", "content": bot_msg})

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

    completion = client.chat.completions.create(
        model="llama-3.3-70b-versatile",
        messages=messages,
        temperature=1,
        max_tokens=1024,
        top_p=1,
        stream=True,
        stop=None,
    )

    response_text = ""
    for chunk in completion:
        delta_content = chunk.choices[0].delta.content
        if delta_content is not None:
            response_text += delta_content
            yield response_text

# Create Gradio interface
with gr.Blocks() as demo:
    with gr.Row():
        name_input = gr.Textbox(placeholder="輸入您的名字...", label="Name")
        msg = gr.Textbox(placeholder="輸入您的問題...", label="User Input")

    chatbot = gr.Chatbot(height=600, show_label=False, container=True)
    clear = gr.Button("清除對話")

    def user(name, user_message, history):
        return "", history + [[user_message, None]], name

    def bot(name, history):
        history[-1][1] = ""
        for response in process_message(history[-1][0], history[:-1]):
            history[-1][1] = response
            yield history

        # Log the conversation to Notion
        if name.strip():
            log_to_notion(name, history[-1][0], history[-1][1])

    msg.submit(user, [name_input, msg, chatbot], [msg, chatbot, name_input], queue=False).then(
        bot, [name_input, chatbot], chatbot
    )
    clear.click(lambda: None, None, chatbot, queue=False)

# Launch the app
if __name__ == "__main__":
    demo.queue()
    demo.launch()