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You are here		isthisit.nz Prompting GPT Models to Return JSON
\|	\|	www.imaurer.com Using grammars to constrain llama.cpp output - Ian Maurer's Notes	3.9 parsecs away Travel
\|	\|	How context-free grammars improve accuracy in LLM-based biomedical data extraction pipelines.	3.9 parsecs away Travel
\|	\|	til.simonwillison.net Using OpenAI functions and their Python library for data extraction \| Simon Willison's TILs	1.7 parsecs away Travel
\|	\|	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.	1.7 parsecs away Travel
\|	\|	somehowmanage.com Writing an LLM Agent in 50 Lines of Code (or no Code at All) - Somehow Manage	2.3 parsecs away Travel
\|	\|	One of the most interesting patterns that is emerging from Large Language Models (LLMs) is the idea of agents. If you're like me, you can only truly grok a concept by seeing or writing code for it from scratch, so like many other folks, I decided to try building one from scratch. So what is...	2.3 parsecs away Travel
\|	\|	simonwillison.net Building search-based RAG using Claude, Datasette and Val Town	27.1 parsecs away Travel
\|		Retrieval Augmented Generation (RAG) is a technique for adding extra "knowledge" to systems built on LLMs, allowing them to answer questions against custom information not included in their training data. ...	27.1 parsecs away Travel