From Chaos to Clarity: Engineering Structured OpenAI Outputs

Wrestling with messy AI-generated content is a developer’s nightmare. This guide reveals the exact strategies to harness AI’s power and extract pristine, structured data.

Created by DALL-E

Artificial intelligence models make our work much easier. With these systems, we can build certain structures and prepare automation systems. I wanted to write an article about the problem I had while preparing such a system and share the solution with you.

In the system I developed, I had to get the same output every time. Since these outputs were added to a dataframe, even one missing meant I would get an error. I tried two methods to solve this.

1.Giving Output Format to Prompt

You can try to get this output by specifying the format you want in the prompt you will give to the model. Let’s examine it with an example.

from openai import OpenAI


client = OpenAI(api_key="your_api_key")

prompt = """
   Generate an output in the following format:
    {
        "name": "Person Name",
        "age": Age,
        "job": "Occupation"
    }
    Example output:
    {
        "name": "John Doe",
        "age": 30,
        "job": "Data Scientist"…