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softwaredoug.com | ||
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strathweb.com
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| | | | | [AI summary] This blog post introduces the fundamentals of tool calling in Azure OpenAI, explaining how large language models select and invoke application tools to orchestrate workflows. | |
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ollama.com
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| | | | | Ollama now supports streaming responses with tool calling. This enables all chat applications to stream content and also call tools in real time. | |
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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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swethatanamala.github.io
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| | | The authors developed a straightforward application of the Long Short-Term Memory (LSTM) architecture which can solve English to French translation. | ||
