Iterative prompt engineering for few-shot prompts
You are currently working on a project at your content creation company. The project's objective is to develop a text classification model capable of accurately identifying and categorizing different emotions in text, such as happiness, sadness, and fear. In cases where the text does not contain any discernible emotion, you aim for the model to respond with "no explicit emotion."
You decided to use the provided few-shot prompt. However, you've noticed that "Time flies like an arrow" is being incorrectly classified as "surprise." Your objective now is to refine the prompt so that the model correctly classifies this particular example as "no explicit emotion."
The OpenAI package and the get_response() function have been pre-loaded for you.
This exercise is part of the course
ChatGPT Prompt Engineering for Developers
Exercise instructions
- Iteratively refine the
prompt, by refining the examples, to get the output no explicit emotion for the"They sat and ate their meal"example.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
client = OpenAI(api_key="")
# Refine the following prompt
prompt = """
Receiving a promotion at work made me feel on top of the world -> Happiness
The movie's ending left me with a heavy feeling in my chest -> Sadness
Walking alone in the dark alley sent shivers down my spine -> Fear
____
____
They sat and ate their meal ->
"""
response = get_response(prompt)
print(response)