npm install openai

// 獲取 OpenAI API Key（請(qǐng)確保此密鑰安全）
const apiKey = 'your_openai_api_key';

// 請(qǐng)求的 API URL
const url = 'https://api.openai.com/v1/chat/completions';

// 定義請(qǐng)求體
const requestBody = {
  model: "gpt-3.5-turbo",  // 可以是 gpt-4 或其他模型
  messages: [
    { role: "system", content: "你是一個(gè)樂(lè)于助人的AI助手。" },
    { role: "user", content: "幫我寫一個(gè)Python計(jì)算兩個(gè)數(shù)之和的函數(shù)。" }
  ],
  temperature: 0.7,  // 控制生成內(nèi)容的隨機(jī)性，范圍 0-1
  max_tokens: 150,   // 控制生成內(nèi)容的最大長(zhǎng)度
};

// 發(fā)送請(qǐng)求到 OpenAI API
fetch(url, {
  method: 'POST',
  headers: {
    'Content-Type': 'application/json',
    'Authorization': `Bearer ${apiKey}`,
  },
  body: JSON.stringify(requestBody),
})
  .then(response => response.json())
  .then(data => {
    console.log(data.choices[0].message.content);  // 輸出生成的內(nèi)容
  })
  .catch(error => {
    console.error('Error:', error);
  });

def add_numbers(a, b):
    return a + b

const generateContent = async (userInput) => {
  const apiKey = 'your_openai_api_key';
  const url = 'https://api.openai.com/v1/chat/completions';
  
  const requestBody = {
    model: "gpt-4",  // 選擇合適的模型
    messages: [
      { role: "system", content: "你是一名專業(yè)的文案編輯。" },
      { role: "user", content: userInput }
    ],
    temperature: 0.6,
    max_tokens: 200,
  };

  try {
    const response = await fetch(url, {
      method: 'POST',
      headers: {
        'Content-Type': 'application/json',
        'Authorization': `Bearer ${apiKey}`,
      },
      body: JSON.stringify(requestBody),
    });

    const data = await response.json();
    console.log(data.choices[0].message.content);  // 輸出生成的文案
  } catch (error) {
    console.error('Error:', error);
  }
};

// 用戶輸入
generateContent("幫我寫一段關(guān)于AI教育工具的產(chǎn)品介紹。");

const chatbotResponse = async (userInput) => {
  const apiKey = 'your_openai_api_key';
  const url = 'https://api.openai.com/v1/chat/completions';
  
  const requestBody = {
    model: "gpt-3.5-turbo",  // 使用 ChatGPT 模型
    messages: [
      { role: "system", content: "你是一個(gè)智能問(wèn)答機(jī)器人，可以回答各種問(wèn)題。" },
      { role: "user", content: userInput }
    ],
    temperature: 0.7,
    max_tokens: 150,
  };

  try {
    const response = await fetch(url, {
      method: 'POST',
      headers: {
        'Content-Type': 'application/json',
        'Authorization': `Bearer ${apiKey}`,
      },
      body: JSON.stringify(requestBody),
    });

    const data = await response.json();
    return data.choices[0].message.content;  // 返回生成的回復(fù)
  } catch (error) {
    console.error('Error:', error);
    return "發(fā)生錯(cuò)誤，請(qǐng)稍后再試。";
  }
};

// 用戶輸入
const userQuery = "如何用Python讀取JSON文件？";
chatbotResponse(userQuery).then(response => {
  console.log(response);  // 輸出問(wèn)答機(jī)器人回復(fù)
});

const batchProcess = async (texts) => {
  const apiKey = 'your_openai_api_key';
  const url = 'https://api.openai.com/v1/chat/completions';

  const responses = [];
  for (const text of texts) {
    const requestBody = {
      model: "gpt-3.5-turbo",
      messages: [
        { role: "user", content: text }
      ],
      temperature: 0.6,
      max_tokens: 100,
    };

    try {
      const response = await fetch(url, {
        method: 'POST',
        headers: {
          'Content-Type': 'application/json',
          'Authorization': `Bearer ${apiKey}`,
        },
        body: JSON.stringify(requestBody),
      });

      const data = await response.json();
      responses.push(data.choices[0].message.content);
    } catch (error) {
      console.error('Error:', error);
      responses.push('錯(cuò)誤：無(wú)法生成回復(fù)');
    }
  }

  return responses;
};

// 批量處理文本
const texts = [
  "幫我總結(jié)這段話的重點(diǎn)：Python是一種非常流行的編程語(yǔ)言。",
  "幫我翻譯這句話：Hello, how are you?",
  "生成一句關(guān)于人工智能未來(lái)發(fā)展的預(yù)測(cè)。"
];

batchProcess(texts).then(responses => {
  console.log(responses.join('\n'));
});