使用 ChatCompletions API 生成响应

已完成

OpenAI ChatCompletions API 通常用于生成 AI 模型和平台。 尽管建议使用 响应 API 进行新的项目开发，但可能会遇到 ChatCompletions API 对于跨平台兼容性的代码维护非常有用的方案。

提交命令提示符

ChatCompletions API 使用 JSON 格式的消息对象的集合来封装提示：

completion = openai_client.chat.completions.create(
    model="gpt-4o",  # Your model deployment name
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "When was Microsoft founded?"}
    ]
)

print(completion.choices[0].message.content)

保留对话上下文

与 响应 API 不同， ChatCompletins API 不提供有状态响应跟踪功能。 若要保留对话上下文，必须编写代码以手动跟踪以前的提示和响应。

# Initial messages
conversation_messages=[
    {
        "role": "system",
        "content": "You are a helpful AI assistant that answers questions and provides information."
    }
]

# Add the first user message
conversation_messages.append(
    {"role": "user",
    "content": "When was Microsoft founded?"}
)

# Get a completion
completion = openai_client.chat.completions.create(
    model="gpt-4o",
    messages=conversation_messages
)
assistant_message = completion.choices[0].message.content
print("Assistant:", assistant_text)

# Append the response to the conversation
conversation_messages.append(
    {"role": "assistant", "content": assistant_text}
)

# Add the next user message
conversation_messages.append(
    {"role": "user",
    "content": "Who founded it?"}
)

# Get a completion
completion = openai_client.chat.completions.create(
    model="gpt-4o",
    messages=conversation_messages
)
assistant_message = completion.choices[0].message.content
print("Assistant:", assistant_text)

# and so on...

在实际应用程序中，对话很可能在循环中实现；像这样：

# Initial messages
conversation_messages=[
    {
        "role": "system",
        "content": "You are a helpful AI assistant that answers questions and provides information."
    }
]

# Loop until the user wants to quit
print("Assistant: Enter a prompt (or type 'quit' to exit)")
while True:
    input_text = input('\nYou: ')
    if input_text.lower() == "quit":
        print("Assistant: Goodbye!")
        break

    # Add the user message
    conversation_messages.append(
        {"role": "user",
        "content": input_text}
    )

    # Get a completion
    completion = openai_client.chat.completions.create(
        model="gpt-4o",
        messages=conversation_messages
    )
    assistant_message = completion.choices[0].message.content
    print("\nAssistant:", assistant_message)
    
    # Append the response to the conversation
    conversation_messages.append(
        {"role": "assistant", "content": assistant_message}
    )

此示例的输出如下所示：

Assistant: Enter a prompt (or type 'quit' to exit)

You: When was Microsoft founded?

Assistant: Microsoft was founded on April 4, 1975 in Albuquerque, New Mexico, USA.

You: Who founded it?

Assistant: Microsoft was founded by Bill Gates and Paul Allen.

You: quit

Assistant: Goodbye!

每次新增的用户提示和响应都被添加到对话中，并在每个轮次中提交整个对话历史记录。

虽然 响应 API 的功能并不如 ChatCompletions API 那样全面，但 ChatCompletions API 在生成型 AI 模型生态系统中已得到良好的确立，因此熟悉它是很有益的。