import time
import gradio as gr  # 確認已正確導入 gradio
import os
import requests
import json

# 從 Hugging Face secrets 中讀取 OpenAI API 金鑰
api_key = os.getenv('OPENAI_API_KEY')
if not api_key:
    raise ValueError("請設置 'OPENAI_API_KEY' 環境變數")

# OpenAI API key
openai_api_key = api_key

# 檢查是否為與調酒相關的問題
def is_related_to_bars(message):
    keywords = [
        '調酒', '酒吧', '酒類', 'cocktail', 'bartending', 'bar', 'alcohol', 'drink',  # 調酒相關的關鍵字
        '風味', '口味', '酸', '甜', '苦', '辣', 'flavor', 'taste', 'sour', 'sweet', 'bitter', 'spicy'  # 風味和口味相關的關鍵字
    ]
    return any(keyword in message.lower() for keyword in keywords)

# 回應生成函數，使用 requests 來呼叫 OpenAI API
def response(message, history):
    global conversation_history

    # 檢查問題是否與調酒相關
    if not is_related_to_bars(message):
        print(f"問題與調酒無關: {message}")
        return "抱歉，我只能回答與調酒、酒吧、酒類相關的問題。"  # In Traditional Chinese

    # 呼叫 OpenAI API
    url = "https://api.openai.com/v1/chat/completions"
    headers = {
        "Content-Type": "application/json",
        "Authorization": f"Bearer {openai_api_key}"
    }

    # 設置初始的 prompt_instruction
    prompt_instruction = """
    你是李宗諺的專業小助教，名字叫做 '小李子'，要以專業、冷淡但是非常有禮貌的口氣，與用戶互動並解答問題:
    """
    prompt_to_gpt = prompt_instruction + message

    # 設置請求的數據
    data = {
        "model": "gpt-4o",  # 使用 GPT-4 或 gpt-3.5-turbo
        "messages": [{"role": "system", "content": prompt_to_gpt}],
        "max_tokens": 200  # 控制生成的最大令牌數
    }

    try:
        response = requests.post(url, headers=headers, data=json.dumps(data))
        response.raise_for_status()  # 檢查是否有錯誤
        response_json = response.json()

        # Debugging: 打印 API 回應
        print("API Response:", response_json)

        if 'choices' in response_json and len(response_json['choices']) > 0:
            model_response = response_json['choices'][0]['message']['content']
            return model_response
        else:
            return "Error: No response from the model."
    except Exception as e:
        print(f"API Error: {e}")
        return f"API Error: {e}"

# 初始訊息
def initial_message():
    return "我是你的專業調酒助理 小李子，我只能回答關於調酒的問題。"  # In Traditional Chinese

# 建立 Gradio 聊天界面，並展示初始訊息
def create_demo():
    with gr.Blocks() as demo:
        chatbot = gr.ChatInterface(response, title='Lee Bartender Assistant', textbox=gr.Textbox(placeholder="Ask me about cocktails, bars, or drinks"))
        gr.Markdown(initial_message())  # 初始訊息
    return demo

demo = create_demo()
demo.launch(share=True)