ChatGPT Prompt Engineering for Developers


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Prompting Principles

Principle 1: Write clear and specific instructions

Tactic 1: Use delimiters to clearly indicate distinct parts of the input

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 single backticks \ 
into a single sentence.
response = get_completion(prompt)

Tactic 2: Ask for a structured output

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)

Tactic 3: Ask the model to check whether conditions are satisfied

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.\"

response = get_completion(prompt)
print("Completion for Text 1:")

Tactic 4: "Few-shot" prompting

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)

Principle 2: Give the model time to “think”

Tactic 1: Specify the steps required to complete a task

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.
# example 1
prompt_1 = f"""
Perform the following actions: 
1 - Summarize the following text delimited by single \
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.


response = get_completion(prompt_1)
print("Completion for prompt 1:")

Tactic 2: Instruct the model to work out its own solution before rushing to a conclusion

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 including the final total. 
- 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 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

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 \
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.
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)

Remark: Model Limitations: Hallucinations - Quality and Safety for LLM ApplicationsQuality and Safety for LLM Applications
Whylogs help logs the data, as well as profiling and monitoring the data issue with LLM.

In the note, we will cover

Data Leakage
Refusals and Prompt Injections
Passive and a...

Other use-cases

  • Summarization - Prompt LLM to summarise, we can also specify the focus or specific information in the context
  • Inferring - Prompt LLM to classify, extract information, do the sentiment, identify emotions, and etc.
  • Transforming - Prompt LLM to be a translator from one language to another, convert the tone of the language, format the conversation, spellcheck or grammar check
  • Expanding - Automate reply email

#llm #chatgpt #prompting #deeplearning-ai