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to second this, I really want an LLM that can call a REST API like ChatGPT plugins can. What is out there? for this use case, it might be okay if it’s not as i

• grepfru_it 3y ago
  I have used llama2 to do something like this. I build a prompt with a set of opcodes, the llm responds with an opcode and an external system handles the call. Not sure if that is what you are looking for however
  • jes5199 3y ago
    that sounds close, but how much tooling do you have to hand-roll for it?
    • grepfru_it 3y ago
      Well I had the LLM write the tooling for me. In my case I had an air gapped system that based its input on the image of that systems desktop. The LlM wrote the code to capture images from the capture card and determine what window was active. That became an opcode. The llm wrote a function to switch windows using a custom hardware module I wrote (presented as a usb hid keyboard to the remote system). Another opcode. I then had enough opcodes and the necessary code to perform basic actions on a non-networked pc. Then I would have tooling that I mostly built to generate a prompt with the opcodes and have the tooling determine the next steps based on the input and desired output. So I had to hand roll all of the tooling, but the LLM did 80% of that work.
• dragonwriter 3y ago
  > to second this, I really want an LLM that can call a REST API like ChatGPT plugins can. What is out there? That's not really a model feature but a prompting + toolchain feature. Conceptually, there's no reason you couldn't build a parser for the chatGPT plugin description json, the descriptions of existing plugins, and prompt any model wrapped in a tool-using framework to call them. That's all outside of the model itself.