ChatGPT提示词工程（一）：Guidelines准则

一、说明

这是吴恩达《ChatGPT Prompt Engineering for Developers》的课程笔记系列。
本文是第二讲的内容：Guidelines
课程主讲：Andrew Ng，Isa Fulford
Isa Fulford也是《OpenAI Cookbook》的主要贡献者之一

二、安装环境

1. 下载openai

pip install openai 
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如果是在jupyter notebook上安装，前面需要带英文感叹号（!），之后需要执行bash指令的地方都这样

!pip install openai 
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2. 导入openai，并配置openai api key

import openai
import os

from dotenv import load_dotenv, find_dotenv
_ = load_dotenv(find_dotenv())

openai.api_key = os.getenv('OPENAI_API_KEY')
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这里的OPENAI_API_KEY是设置在环境变量里的值，为你的openai api key
设置环境变量bash指令：

!export OPENAI_API_KEY='sk-...'		
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或者，在代码中直接这样写：

openai.api_key = 'sk-...'    
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3. 辅助函数
调用openai接口

def get_completion(prompt, model="gpt-3.5-turbo"):
    messages = [{"role": "user", "content": prompt}]
    response = openai.ChatCompletion.create(
        model=model,
        messages=messages,
        temperature=0, # this is the degree of randomness of the model's output
    )
    return response.choices[0].message["content"]
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三、Guidelines

准则一：写出明确而具体的说明

方法1：使用分隔符清楚地表示输入的不同部分

分隔符可以是：

 ```,  """,  < >,  <tag> </tag>,  :   
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它可以防止prompt注入，以免给模型产生混乱的理解

例子：

text = f"""
You should express what you want a model to do by \ 
providing instructions that are as clear and \ 
specific as you can possibly make them. \ 
This will guide the model towards the desired output, \ 
and reduce the chances of receiving irrelevant \ 
or incorrect responses. Don't confuse writing a \ 
clear prompt with writing a short prompt. \ 
In many cases, longer prompts provide more clarity \ 
and context for the model, which can lead to \ 
more detailed and relevant outputs.
"""
prompt = f"""
Summarize the text delimited by triple backticks \ 
into a single sentence.
```{text}```
"""
response = get_completion(prompt)
print(response)
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{text} 就是使用符合 ```分隔的内容
以上代码输出的结果为，打印的一句话总结的text的结果：
在这里插入图片描述

方法2：用结构化输出：如直接要求它以HTML或者JSON格式输出

例子：

prompt = f"""
Generate a list of three made-up book titles along \ 
with their authors and genres. 
Provide them in JSON format with the following keys: 
book_id, title, author, genre.
"""
response = get_completion(prompt)
print(response)
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代码中，要求生成三个虚拟的图书，以JSON格式输出，运行结果：
在这里插入图片描述

方法3：请模型检查是否满足条件

要求检查：要求模型先检查是否满足某个条件后，再进行输出，如果条件不满足可以直接告知。
例子：

text_1 = f"""
Making a cup of tea is easy! First, you need to get some \ 
water boiling. While that's happening, \ 
grab a cup and put a tea bag in it. Once the water is \ 
hot enough, just pour it over the tea bag. \ 
Let it sit for a bit so the tea can steep. After a \ 
few minutes, take out the tea bag. If you \ 
like, you can add some sugar or milk to taste. \ 
And that's it! You've got yourself a delicious \ 
cup of tea to enjoy.
"""
prompt = f"""
You will be provided with text delimited by triple quotes. 
If it contains a sequence of instructions, \ 
re-write those instructions in the following format:

Step 1 - ...
Step 2 - …
…
Step N - …

If the text does not contain a sequence of instructions, \ 
then simply write \"No steps provided.\"

\"\"\"{text_1}\"\"\"
"""
response = get_completion(prompt)
print("Completion for Text 1:")
print(response)
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代码中，text的内容是泡一杯茶的步骤，prompt要求模型理解这段内容，告知是否能把它分解成一步一步的步骤的结构，如果能，则按照步骤描述重写，如果不能则给出则返回No steps provided。代码输出结果：
在这里插入图片描述
下面这个例子则给出的是不能分解成步骤的一段话：

text_2 = f"""
The sun is shining brightly today, and the birds are \
singing. It's a beautiful day to go for a \ 
walk in the park. The flowers are blooming, and the \ 
trees are swaying gently in the breeze. People \ 
are out and about, enjoying the lovely weather. \ 
Some are having picnics, while others are playing \ 
games or simply relaxing on the grass. It's a \ 
perfect day to spend time outdoors and appreciate the \ 
beauty of nature.
"""
prompt = f"""
You will be provided with text delimited by triple quotes. 
If it contains a sequence of instructions, \ 
re-write those instructions in the following format:

Step 1 - ...
Step 2 - …
…
Step N - …

If the text does not contain a sequence of instructions, \ 
then simply write \"No steps provided.\"

\"\"\"{text_2}\"\"\"
"""
response = get_completion(prompt)
print("Completion for Text 2:")
print(response)
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在这里插入图片描述

方法4：Prompt中包含少量样本

例子：

prompt = f"""
Your task is to answer in a consistent style.

: Teach me about patience.

: The river that carves the deepest \ 
valley flows from a modest spring; the \ 
grandest symphony originates from a single note; \ 
the most intricate tapestry begins with a solitary thread.

: Teach me about resilience.
"""
response = get_completion(prompt)
print(response)
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代码中，给了一个child和grandparent对话的样本，要求再次按照这个样本给出grandparent的答复，运行结果：
在这里插入图片描述

https://blog.csdn.net/Jay_Xio/article/details/130450026

准则二：给模型一些思考的时间

方法1：指定完成任务所需的步骤

例子：

text = f"""
In a charming village, siblings Jack and Jill set out on \ 
a quest to fetch water from a hilltop \ 
well. As they climbed, singing joyfully, misfortune \ 
struck—Jack tripped on a stone and tumbled \ 
down the hill, with Jill following suit. \ 
Though slightly battered, the pair returned home to \ 
comforting embraces. Despite the mishap, \ 
their adventurous spirits remained undimmed, and they \ 
continued exploring with delight.
"""

prompt_1 = f"""
Perform the following actions: 
1 - Summarize the following text delimited by triple \
backticks with 1 sentence.
2 - Translate the summary into French.
3 - List each name in the French summary.
4 - Output a json object that contains the following \
keys: french_summary, num_names.

Separate your answers with line breaks.

Text:
```{text}```
"""

response = get_completion(prompt_1)
print("Completion for prompt 1:")
print(response)
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代码中，prompt给出模型要执行任务的步骤
步骤1，用一句话总结text内容
步骤2，翻译成法语
步骤3，列出名字
步骤4，以JSON格式输出
执行代码，模型按照这个步骤输出：
在这里插入图片描述

prompt_2 = f"""
Your task is to perform the following actions: 
1 - Summarize the following text delimited by 
  <> with 1 sentence.
2 - Translate the summary into French.
3 - List each name in the French summary.
4 - Output a json object that contains the 
  following keys: french_summary, num_names.

Use the following format:
Text: 
Summary: 
Translation: 
Names: 
Output JSON: 

Text: <{text}>
"""
response = get_completion(prompt_2)
print("\nCompletion
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在这里插入图片描述

方法2：指示模型在匆忙得出结论之前制定出自己的解决方案

prompt = f"""
Determine if the student's solution is correct or not.

Question:
I'm building a solar power installation and I need \
 help working out the financials. 
- Land costs $100 / square foot
- I can buy solar panels for $250 / square foot
- I negotiated a contract for maintenance that will cost \ 
me a flat $100k per year, and an additional $10 / square \
foot
What is the total cost for the first year of operations 
as a function of the number of square feet.

Student's Solution:
Let x be the size of the installation in square feet.
Costs:
1. Land cost: 100x
2. Solar panel cost: 250x
3. Maintenance cost: 100,000 + 100x
Total cost: 100x + 250x + 100,000 + 100x = 450x + 100,000
"""
response = get_completion(prompt)
print(response)
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代码中，要求模型判断学生的结题是否正确，运行结果：
在这里插入图片描述
明显第3部，MainTenance const：应该是 100000 + 10x，而学生给出的是错误的，模型没有判断出这个步骤有误，因为它只判断了 Total cost: 100x + 250x + 100,000 + 100x = 450x + 100,000 是正确的，就给出了正确的结论。

下面的示例，要求模型先自己按照步骤一步一步给出解题步骤，然后再判断学生的解题步骤是否正确：

prompt = f"""
Your task is to determine if the student's solution \
is correct or not.
To solve the problem do the following:
- First, work out your own solution to the problem. 
- Then compare your solution to the student's solution \ 
and evaluate if the student's solution is correct or not. 
Don't decide if the student's solution is correct until 
you have done the problem yourself.

Use the following format:
Question:
```
question here
```
Student's solution:
```
student's solution here
```
Actual solution:
```
steps to work out the solution and your solution here
```
Is the student's solution the same as actual solution \
just calculated:
```
yes or no
```
Student grade:
```
correct or incorrect
```

Question:
```
I'm building a solar power installation and I need help \
working out the financials. 
- Land costs $100 / square foot
- I can buy solar panels for $250 / square foot
- I negotiated a contract for maintenance that will cost \
me a flat $100k per year, and an additional $10 / square \
foot
What is the total cost for the first year of operations \
as a function of the number of square feet.
```
Student's solution:
```
Let x be the size of the installation in square feet.
Costs:
1. Land cost: 100x
2. Solar panel cost: 250x
3. Maintenance cost: 100,000 + 100x
Total cost: 100x + 250x + 100,000 + 100x = 450x + 100,000
```
Actual solution:
"""
response = get_completion(prompt)
print(response)
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运行结果：给出了正确解法，并判断学生的是错误的
在这里插入图片描述