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til.simonwillison.net | ||
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www.markhw.com
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| | | | | [AI summary] This blog post discusses integrating R and Python for seamless data analysis using OpenAI's GPT models to extract information from Wikipedia about film directors' roles in Oscar-winning films. | |
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somehowmanage.com
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| | | | | 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... | |
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isthisit.nz
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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. | |
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www.e4developer.com
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| | | High level introduction to Spring Boot and its popularity. Spring Boot Hello World example and a list of features that make it so successful. | ||
