Self-consistency prompts

Imagine you own a store that sells laptops and mobile phones. You start your day with 50 devices in the store, out of which 60% are mobile phones. Throughout the day, three clients visited the store, each of them bought one mobile phone, and one of them bought additionally a laptop. Also, you added to your collection 10 laptops and 5 mobile phones. How many laptops and mobile phones do you have by the end of the day? This problem is defined in the problem_to_solve string, and you will use a self-consistency prompt to solve it.

The OpenAI package and the get_response() function have been pre-loaded for you.

The get_response() function in this exercise employs the max_tokens parameter to help this exercise run faster.

This exercise is part of the course

Prompt Engineering with the OpenAI API

View Course

Exercise instructions

Create the self_consistency_instruction that allows the model to solve the problem with three experts and combine the results with a majority vote.
Create the final prompt by combining the self_consistency_instruction and the problem_to_solve.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

client = OpenAI(api_key="")

# Create the self_consistency instruction
self_consistency_instruction = ____

# Create the problem to solve
problem_to_solve = "If you own a store that sells laptops and mobile phones. You start your day with 50 devices in the store, out of which 60% are mobile phones. Throughout the day, three clients visited the store, each of them bought one mobile phone, and one of them bought additionally a laptop. Also, you added to your collection 10 laptops and 5 mobile phones. How many laptops and mobile phones do you have by the end of the day?"

# Create the final prompt
prompt = ____

response = get_response(prompt)
print(response)

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