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dhariri.com | ||
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blog.adnansiddiqi.me
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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. | |
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blog.martinig.ch
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| | | | | Architecture is an important asset for good programming and the notion of "pattern" is here to help us apply already trusted code architecture solutions to common problems. Jason McDonald has done a wonderful job to group some of them in a document that should be useful to most software developers. Go to his blog to | |
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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.observeinc.com
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| | | Model Context Protocol (MCP) servers are an emerging standard, and we're very excited to make the Observe MCP server available, so you can allow your agents to access your observability data. | ||
