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Extracting Structured Data From Documents with GPT

Extracting Structured Data From Documents with GPT-4 TurboA reliable approach to getting structured data from Large Language ModelsIbrahim SaidiTowards AI Engineering

Ibrahim Saidi

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Towards AI Engineering

·9 min read·May 2, 2024

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Image generated with DALL·E 3 in ChatGPT.

📚👨🏾‍💻What you’ll learn:

Extracting data from PDF documents using GPT-4 TurboChaining multiple LLM calls

When OpenAI released their GPT-4 Vision, this introduced a layer of advanced AI intelligence, empowering applications with the ability to accurately interpret and analyse visual data such as resumes.

Their latest GPT-4 Turbo with Vision now enables the use of JSON mode and function calling. This means that we no longer have to pray to the AI gods that the LLM returns the correct data.

We simply instruct the LLM to output the data in a particular format. When we need to run our code in production, this idea of structured prompting become

Once we have this unstructured data into native types that are appropriate for a variety of programmatic use cases, the sky is the limit in terms of the type of applications we build.

What we’re building: Resume Parser and Cover Letter Drafter

Suppose you’re prototyping a job search application that leverages AI to automate the job search…

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