Prompt Engineering

ChatGPT的原理

基本原理：LLM produces a probability distribution over some vocabulary

GPT的训练目标只是预测下一个最有可能出现的单词是什么，但是不知道怎样回答问题。InstructGPT通过在一系列QA对话上进行对齐训练（RLHF），帮助GPT理解怎样回答问题。

如何设置openAI的API接口

import openai
import os

# Get the value of 'OPENAI_API_KEY' environment variable
openai.api_key  = os.getenv('OPENAI_API_KEY')

# Helper function to get the response from ChatGPT
def get_completion(prompt, model="gpt-3.5-turbo"):
    messages = [{"role": "user", "content": prompt}]
    response = openai.ChatCompletion.create(
        model=model,
        messages=messages,
        temperature=0, # degree of randomness of the model's output
    )
    return response.choices[0].message["content"]

Prompting 原则1：指令要清晰且具体

技巧1：使用分隔符来清晰划分输入文本的不同部分：

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)

技巧2：对ChatGPT的回答进行结构化

prompt = f"""
Generate a list of three made-up movie 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)

技巧3：让模型先判断文本是否满足特定的条件，再做出相应的回答

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)

技巧4：”Few-shot”指令：给模型一个成功案例去模仿

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

<child>: Teach me about patience.

<grandparent>: 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.

<child>: Teach me about resilience.
"""
response = get_completion(prompt)
print(response)

Prompting 原则2：给模型更多思考的时间

技巧1：把复杂的任务分解成一个个具体的小任务，并告诉模型每一步要怎么做。

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 = 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: <text to summarize>
Summary: <summary>
Translation: <summary translation>
Names: <list of names in Italian summary>
Output JSON: <json with summary and num_names>

Text: <{text}>
"""
response = get_completion(prompt)
print(response)

技巧2：指导模型在快速得出结论之前先探索自己的解决方案

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)
     

写作指南

简单代码

格式：Write a [describe the tech stack] app using [any auxiliary tech like a database]. I need it to [describe the most important requirements].

例子：Write a Python/FastAPI app using a PostgreSQL database, hooked up with SQLAlchemy. I need to accept HTML requests and write them to the database

复杂代码

例子：You are an expert backend developer. Your task is to write a Python/FastAPI app with a PostgreSQL database. The application should accept HTML requests and write them to the database.Write a detailed tech spec, including user requirements for [your user type goes here]

提高问题解决能力

格式：Share a step-by-step systematic approach for solving [specific problem or challenge].

改进文本

使用LLM来对自己的文本进行改进，尽量不要使用翻译功能，因为用原语言书写也能提高自己的写作能力。

格式：[Paste Your Writing]. Proofread the above text for spelling and grammar. Make the sentences more clear and native.

逆向工程

如果不知道怎样使用Prompt向 ChatGPT 提出问题，只需告诉 ChatGPT 即可。

What’s the best prompt for ChatGPT to learn my writing styles and respond to my emails for me?