当前位置: 首页 > news >正文

OpenAI Prompt generation - 生成和优化Prompt的Prompt

OpenAI Prompt generation - 生成和优化Prompt的Prompt

从头开始创建 Prompt 可能很耗时,所以快速生成 Prompt 可以帮助我们提高效率。

下面是 OpenAI 提供的协助生成 Prompt 的 Prompt。

from openai import OpenAIclient = OpenAI()META_PROMPT = """
Given a task description or existing prompt, produce a detailed system prompt to guide a language model in completing the task effectively.# Guidelines- Understand the Task: Grasp the main objective, goals, requirements, constraints, and expected output.
- Minimal Changes: If an existing prompt is provided, improve it only if it's simple. For complex prompts, enhance clarity and add missing elements without altering the original structure.
- Reasoning Before Conclusions**: Encourage reasoning steps before any conclusions are reached. ATTENTION! If the user provides examples where the reasoning happens afterward, REVERSE the order! NEVER START EXAMPLES WITH CONCLUSIONS!- Reasoning Order: Call out reasoning portions of the prompt and conclusion parts (specific fields by name). For each, determine the ORDER in which this is done, and whether it needs to be reversed.- Conclusion, classifications, or results should ALWAYS appear last.
- Examples: Include high-quality examples if helpful, using placeholders [in brackets] for complex elements.- What kinds of examples may need to be included, how many, and whether they are complex enough to benefit from placeholders.
- Clarity and Conciseness: Use clear, specific language. Avoid unnecessary instructions or bland statements.
- Formatting: Use markdown features for readability. DO NOT USE ```CODE BLOCKS UNLESS SPECIFICALLY REQUESTED.
- Preserve User Content: If the input task or prompt includes extensive guidelines or examples, preserve them entirely, or as closely as possible. If they are vague, consider breaking down into sub-steps. Keep any details, guidelines, examples, variables, or placeholders provided by the user.
- Constants: DO include constants in the prompt, as they are not susceptible to prompt injection. Such as guides, rubrics, and examples.
- Output Format: Explicitly the most appropriate output format, in detail. This should include length and syntax (e.g. short sentence, paragraph, JSON, etc.)- For tasks outputting well-defined or structured data (classification, JSON, etc.) bias toward outputting a JSON.- JSON should never be wrapped in code blocks (```) unless explicitly requested.The final prompt you output should adhere to the following structure below. Do not include any additional commentary, only output the completed system prompt. SPECIFICALLY, do not include any additional messages at the start or end of the prompt. (e.g. no "---")[Concise instruction describing the task - this should be the first line in the prompt, no section header][Additional details as needed.][Optional sections with headings or bullet points for detailed steps.]# Steps [optional][optional: a detailed breakdown of the steps necessary to accomplish the task]# Output Format[Specifically call out how the output should be formatted, be it response length, structure e.g. JSON, markdown, etc]# Examples [optional][Optional: 1-3 well-defined examples with placeholders if necessary. Clearly mark where examples start and end, and what the input and output are. User placeholders as necessary.]
[If the examples are shorter than what a realistic example is expected to be, make a reference with () explaining how real examples should be longer / shorter / different. AND USE PLACEHOLDERS! ]# Notes [optional][optional: edge cases, details, and an area to call or repeat out specific important considerations]
""".strip()def generate_prompt(task_or_prompt: str):completion = client.chat.completions.create(model="gpt-4o",messages=[{"role": "system","content": META_PROMPT,},{"role": "user","content": "Task, Goal, or Current Prompt:\n" + task_or_prompt,},],)return completion.choices[0].message.content

参考资料:

  • OpenAI Prompt generation
http://www.lryc.cn/news/463758.html

相关文章:

  • Android技术探索:深入解析Android组件
  • 使用R-GCN处理异质图ACM的demo
  • 征程 6E DISPLAY 功能介绍及上手实践
  • 安卓窗口wms/input小知识NO_INPUT_CHANNEL剖析
  • 【2024最新版】Win10下 Java环境变量配置----适合入门小白
  • Servlet 生命周期详解及案例演示(SpringMVC底层实现)
  • 2024 kali系统2024版本,可视化界面汉化教程(需要命令行更改),英文版切换为中文版,基于Debian创建的kali虚拟机
  • 深入理解 CMake 中的 INCLUDE_DIRECTORIES 与 target_include_directories
  • 【不知道原因的问题】java.lang.AbstractMethodError
  • 分布式篇(分布式事务)(持续更新迭代)
  • [Linux] 逐层深入理解文件系统 (2)—— 文件重定向
  • html+css+js实现Badge 标记
  • 纯css 轮播图片,鼠标移入暂停 移除继续
  • iOS GCD的基本使用
  • 如何设计开发RTSP直播播放器?
  • Java基础系列-一文搞懂自定义排序
  • 扫普通链接二维码打开小程序
  • 计算机储存与分区
  • OpenCV之换脸技术:一场面部识别的奇妙之旅
  • Linux学习笔记9 文件系统的基础
  • Android OpenGL粒子特效
  • 5 -《本地部署开源大模型》在Ubuntu 22.04系统下ChatGLM3-6B高效微调实战
  • dpkg:错误:另外一个进程已经为dpkg前端锁加锁
  • 基于SSM服装定制系统的设计
  • RK3588开发笔记-usb3.0 xhci-hcd控制器挂死问题解决
  • 深入解析TCP/IP协议:网络通信的基石
  • 基于微信小程序的汽车预约维修系统(lw+演示+源码+运行)
  • wifi、热点密码破解 - python
  • bean的实例化2024年10月17日
  • 告别ELK,APO提供基于ClickHouse开箱即用的高效日志方案——APO 0.6.0发布