/explore
|
You are here 
|
www.swyx.io | ||
| | | | |
domenic.me
|
|
| | | | | Creating web standards for AI models means wrestling with questions that didn't exist two years ago. Here's what I've learned building the prompt API and its siblings. | |
| | | | |
isthisit.nz
|
|
| | | | | 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.ouseful.info
|
|
| | | | | I finally succumbed and had a look at Google's proposed window.ai browser javascript object in Chrome. To get started (the restarts are superstitious behaviour...): download and install Chrome Canary (you can run this alongside any other Chrome instance; you do not need to log in or register to try out any of the following) enable... | |
| | | | |
www.micahwalter.com
|
|
| | | I've been digging into this new AWS blog post about Model Context Protocol MCP servers and their integration with Amazon Bedrock Agents, and I have to say, I'm... | ||
