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 ninkovic.dev
Extracting structured information from documents with LLMs
| | isthisit.nz
Prompting GPT Models to Return JSON
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| | August 2024 Update: Now a solved problem. Use Structured Outputs. Large language models (LLMs) return unstructured output. When we prompt them they respond with one large string. This is fine for applications such as ChatGPT, but in others where we want the LLM to return structured data such as lists or key value pairs, a parseable response is needed. In Building A ChatGPT-enhanced Python REPL I used a technique to prompt the LLM to return output in a text format I could parse.
| | blog.adnansiddiqi.me
Introduction to LLM | Adnan's Random bytes
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| | Learn the basics of Large Language Models (LLMs) in this introduction to GenAI series. Discover how LLMs work, their architecture, and practical applications like customer support, content creation, and software development.
| | aisafety.info
What is a shoggoth?
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| | Shoggoths are creatures from the Cthulhu Mythos that are deeply alien and incomprehensible to the human mind. The 'shoggoth with a human mask' has emerged as a meme to illustrate the point that, while large language models (LLMs) are t...
| | til.simonwillison.net
Using OpenAI functions and their Python library for data extraction | Simon Willison's TILs
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| Here's the pattern I figured out for using the openai Python library to extract structured data from text using a single call to the model.