GPT 模型输出仅与您的提示一样好。通过对您想要的内容的明确说明，它将提供您期望的结果。提高 GPT 输出的一些提示包括：

import openaiopenai.api_key = ""res = openai.ChatCompletion.create( model="gpt-3.5-turbo", max_tokens=100, temperature=0.7, messages=[ { "role": "system", "content": """ When I ask to explain something, bring it in a way that teacher would explain it to students in every paragraph. """, }, { "role": "user", "content": """ What is golden globe award and what is the criteria for this award? Summarize them in 2 paragraphs. """, }, ],)

提供示例结果来指导 GPT 模型应如何回答您的问题也很棒。例如，在此代码中，我传递了如何解释情绪，GPT 模型应模仿我的风格。

res = openai.ChatCompletion.create( model="gpt-3.5-turbo", max_tokens=100, temperature=0.7, messages=[ { "role": "system", "content": "Answer in a consistent style.", }, { "role": "user", "content": "Teach me about Love", }, { "role": "assistant", "content": "Love can be sweet, can be sour, can be grand, can be low, and can be anything you want to be", }, { "role": "user", "content": "Teach me about Fear", }, ],)指定完成任务的步骤。 提供有关如何输出以获得最佳输出的详细步骤。详细说明 GPT 模型应如何操作的说明。例如，我们在此代码中放置了带有前缀和翻译的两步指令。

res = openai.ChatCompletion.create( model="gpt-3.5-turbo", max_tokens=100, temperature=0.7, messages= [ { "role": "system", "content": """ Use the following step-by-step instructions to respond to user inputs. step 1 - Explain the question input by the user in 2 paragraphs or less with the prefix "Explanation: ". Step 2 - Translate the Step 1 into Indonesian, with a prefix that says "Translation: ". """, }, { "role": "user", "content":"What is heaven?", }, ])提供参考、链接或引用。如果我们已经有各种问题参考，我们可以将它们用作 GPT 模型的基础来提供输出。提供您认为与您的问题相关的任何参考文献的列表，并将它们传递给系统角色。给 GPT 时间“思考”。提供一个查询，允许 GPT 在急于给出不正确的结果之前详细处理提示。如果我们给助理角色传递错误的结果，并且我们希望 GPT 能够自己批判性地思考，则尤其如此。例如，下面的代码显示了我们如何要求 GPT 模型对用户输入更加严格。

res = openai.ChatCompletion.create( model="gpt-3.5-turbo", max_tokens=100, temperature=0.7, messages= [ { "role": "system", "content": """ Work on your solution to the problem, then compare your solution to the user and evaluate if the solution is correct or not. Only decide if the solution is correct once you have done the problem yourself. """, }, { "role": "user", "content":"1 1 = 3", }, ])使 GPT 使用代码执行来获得精确的结果。 对于更扩展和更复杂的计算，GPT 可能无法按预期工作，因为模型可能会提供不准确的结果。为了缓解这种情况，我们可以要求 GPT 模型编写和运行编码，而不是直接计算它们。这样，GPT 可以依赖代码而不是其计算。例如，我们可以提供如下输入。

res = openai.ChatCompletion.create( model="gpt-3.5-turbo", max_tokens=100, temperature=0.7, messages= [ { "role": "system", "content": """ Write and execute Python code by enclosing it in triple backticks, e.g. ```code goes here```. Use this to perform calculations. """, }, { "role": "user", "content":""" Find all real-valued roots of the following polynomial equation: 2*x**5 - 3*x**8- 2*x**3 - 9*x 11. """, }, ])结论

GPT 模型是目前最好的模型之一，以下是改进 GPT 模型输出的一些最佳实践：