A basic test of OpenAI’s Structured Output feature against financial disclosure reports and a newspaper’s police blotter. Code examples use the Python SDK and pydantic for the schema definition…
Read in full here:
README.openai-structured-output-demo.md
# Extracting financial disclosure reports and police blotter narratives using OpenAI's Structured Output
> **tl;dr** this demo shows how to call OpenAI's [gpt-4o-mini model](https://openai.com/index/gpt-4o-mini-advancing-cost-efficient-intelligence/), provide it with URL of a screenshot of a document, and extract data that follows a schema you define. The results are pretty solid even with little effort in defining the data — and no effort doing data prep. OpenAI's API could be a cost-efficient tool for large scale data gathering projects involving public documents.
OpenAI announced [Structured Outputs for its API](https://openai.com/index/introducing-structured-outputs-in-the-api/), a feature that allows users to specify the fields and schema of extracted data, and guarantees that the JSON output will follow that specification.
For example, given a Congressional financial disclosure report, with assets defined in a table like this:
<img width="859" alt="image" src="https://gist.github.com/user-attachments/assets/e64c7ad1-d7af-4e51-a3f2-5961fde4fac3">show original
extract-basic-financial-disclosure.py
#!/usr/bin/env python3
"""
extract-basic-financial-disclosure.py
Parses and extracts structured data — and lets the model infer the structure by itself —
from the screenshot at the given URL:
https://gist.github.com/user-attachments/assets/9c35e7a4-e6b7-4d5b-a4a2-a62b6ec28504
Full financial disclosure report:show original
extract-financial-disclosure.py
#!/usr/bin/env python3
"""
extract-financial-disclosure.py
Parses and extracts structured data from the screenshot at the given URL:
https://gist.github.com/user-attachments/assets/9c35e7a4-e6b7-4d5b-a4a2-a62b6ec28504
Full financial disclosure report:show original
There are more than three files. show original
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