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# 設置 API 密鑰
openai.api_key = 'your-api-key'

# 發起 API 請求
response = openai.Completion.create(
engine="text-davinci-003",
prompt="Translate the following English text to French: 'Hello, how are you?'",
max_tokens=60
)

# 輸出結果
print(response.choices[0].text.strip())

2.4 處理 API 響應

API 響應通常包含生成的文本、請求狀態等信息。你可以通過解析響應對象來獲取所需的數據。

# 獲取生成的文本

generated_text = response.choices[0].text.strip()



# 獲取請求 ID

request_id = response.id



# 獲取請求狀態

status = response.status

3. 實際應用案例

3.1 實時聊天機器人

利用 OpenAI的實時 API，你可以輕松構建一個實時聊天機器人。以下是一個簡單的示例：

import openai



openai.api_key = 'your-api-key'



def chat_with_bot(prompt):

    response = openai.Completion.create(

        engine="text-davinci-003",

        prompt=prompt,

        max_tokens=150

    )

    return response.choices[0].text.strip()



while True:

    user_input = input("You: ")

    if user_input.lower() in ["exit", "quit"]:

        break

    bot_response = chat_with_bot(user_input)

    print(f"Bot: {bot_response}")

3.2 代碼補全工具

OpenAI 的實時 API 還可以用于代碼補全。以下是一個示例，展示如何使用 API 補全 Python代碼：

import openai



openai.api_key = 'your-api-key'



def complete_code(prompt):

    response = openai.Completion.create(

        engine="code-davinci-002",

        prompt=prompt,

        max_tokens=100

    )

    return response.choices[0].text.strip()



code_prompt = """

def fibonacci(n):

    if n <= 0:

        return 0

    elif n == 1:

        return 1

    else:

        return fibonacci(n-1) + fibonacci(n-2)

"""



completed_code = complete_code(code_prompt)

print(completed_code)

4. 性能優化與最佳實踐

4.1 批量處理請求

為了減少延遲并提高吞吐量，建議將多個請求合并為一個批量請求。以下是一個示例：

import openai



openai.api_key = 'your-api-key'



prompts = [

    "Translate the following English text to French: 'Hello, how are you?'",

    "Write a short story about a robot learning to love.",

    "Explain the concept of quantum computing in simple terms."

]



responses = openai.Completion.create(

    engine="text-davinci-003",

    prompt=prompts,

    max_tokens=60

)



for i, response in enumerate(responses.choices):

    print(f"Response {i+1}: {response.text.strip()}")

4.2 錯誤處理與重試機制

在實際應用中，網絡波動或 API 限流可能導致請求失敗。建議實現錯誤處理與重試機制，以提高系統的穩定性。

import openai

import time



openai.api_key = 'your-api-key'



def safe_api_call(prompt, retries=3):

    for i in range(retries):

        try:

            response = openai.Completion.create(

                engine="text-davinci-003",

                prompt=prompt,

                max_tokens=60

            )

            return response.choices[0].text.strip()

        except Exception as e:

            print(f"Attempt {i+1} failed: {e}")

            time.sleep(2 ** i)  # 指數退避

    return "API call failed after retries."



result = safe_api_call("Translate the following English text to French: 'Hello, how are you?'")

print(result)