Prompt Engineering 简明教程
DESIGN FEEDBACK PROCESS Prompt
使用 DESIGN FEEDBACK PROCESS 指令，我们可以利用 ChatGPT 的功能来设计针对各种背景的有效反馈流程。此技术使我们能够利用 ChatGPT 的问题解决能力和行业知识来创建结构化且有价值的反馈机制。
Understanding the DESIGN FEEDBACK PROCESS prompt
DESIGN FEEDBACK PROCESS 指令会提示 ChatGPT 为给定的背景生成一个设计精良的反馈流程。通过在我们的提示中纳入 DESIGN FEEDBACK PROCESS 指令，我们可以利用 ChatGPT 的专业知识来创建结构化和有效的反馈机制。
DESIGN FEEDBACK PROCESS 指令的基本 syntax 如下：
User: Can you design a feedback process for our software development team?
ChatGPT: Absolutely! Here's a suggested outline for your feedback process:
1. Regular one-on-one meetings between team members and their managers to discuss progress, challenges, and goals.
2. Anonymous feedback surveys for team members to provide feedback on their peers' performance, collaboration, and communication.
3. Retrospective meetings at the end of each development sprint to reflect on the team's achievements, lessons learned, and areas for improvement.
4. 360-degree feedback assessments to gather input from multiple stakeholders, including peers, managers, and customers.在示例中，用户要求设计一个针对其软件开发团队的反馈流程。ChatGPT 的响应包括反馈流程的概述，包括关键组件和建议。
Best Practices for Using the DESIGN FEEDBACK PROCESS Directive
为了充分利用 DESIGN FEEDBACK PROCESS 指令，我们考虑以下最佳实践：
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Identify the Feedback Goals - 明确定义反馈流程的目标和目的。确定您希望通过反馈机制实现哪些结果，例如提高协作、确定增长领域或表彰成就。
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Incorporate Multiple Feedback Channels - 提示 ChatGPT 建议各种反馈渠道和方法。考虑结合一对一会议、调查、回顾和评估来从不同的角度收集反馈并确保进行全面评估。
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-{s10} − 鼓励 ChatGPT 加入促进安全和建设性反馈环境的元素。提示生成指南、培训或促进技术，这些技术可促进开放和尊重的沟通，确保有效地提供和接收反馈。
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-{s11} − 提示 ChatGPT 设计一个可确保反馈循环和可行的步骤的过程。鼓励根据收到的反馈识别明确的后续行动，并制定用于跟踪进度和实施的机制。
Example Application − Python Implementation
让我们探索使用 DESIGN FEEDBACK PROCESS 指令与 ChatGPT 交互的 Python 脚本的实际示例。
import openai
# Set your API key here
openai.api_key = 'YOUR_API_KEY'
def generate_chat_response(prompt):
response = openai.Completion.create(
engine="text-davinci-003",
prompt=prompt,
max_tokens=500,
temperature=0.7,
n=1,
stop=None
)
return response
user_prompt = "User: Design a feedback process for school teachers.\n"
chat_prompt = user_prompt + "ChatGPT: [DESIGN FEEDBACK PROCESS: for new employees]"
response = generate_chat_response(chat_prompt)
print(response)在此示例中，我们定义了一个 generate_chat_response() 函数，该函数需要一个提示，并使用 OpenAI API 使用 ChatGPT 生成响应。chat_prompt 变量包含用户的提示和 ChatGPT 响应，包括 DESIGN FEEDBACK PROCESS 指令，用于为市场营销团队设计反馈流程。
Output
当我们运行脚本时，我们将收到 ChatGPT 生成的响应，其中包括为市场营销团队设计的反馈流程大纲。
在我们的示例中，用户提示为“为学校教师设计一个反馈流程”，而 ChatGPT 响应如下 −
1. Set up a meeting with the new teacher and their supervisor to discuss expectations.
2. Provide feedback forms to the teacher and supervisor to use for gathering feedback.
3. Establish a timeline for providing feedback and check-ins.
4. Communicate the feedback process to the teacher and supervisor.
5. Encourage open dialogue between the teacher and supervisor to ensure feedback is given in a constructive and respectful manner.
6. Allow for open-ended questions and comments to be included in the feedback.
7. Provide feedback summaries to the teacher on a regular basis to track progress.
8. When necessary, provide additional resources and support to the teacher in order to help them improve.
9. Celebrate successes and recognize the teacher's accomplishments.
10. Encourage ongoing dialogue between the teacher and supervisor to ensure feedback is given in a timely manner.