ChatBartender / app.py
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Update app.py
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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)