3 ms·

Hasn't this been invented already in multiple shapes and forms..? I wrote my own version clai[1] over a year ago which does exactly this, only that it has tools

Hasn't this been invented already in multiple shapes and forms..? I wrote my own version clai[1] over a year ago which does exactly this, only that it has tools support + is multi vendor. [1]: https://github.com/baalimago/clai https://github.com/baalimago/clai

simonw 1y ago
Looks quite similar to my https://llm.datasette.io https://llm.datasette.io tool as well. Honestly though, CLI tools for accessing LLMs (including piping content in and out of them) is such a clearly good idea I'm glad to see more tools implementing the pattern.
- dcre 1y ago
  It's very surprising that it has taken this long to see a first-party CLI like this.
  - simonw 1y ago
    OpenAI have had a bad one for a couple of years. It looks something like this: pip install openai export OPENAI_API_KEY="..." openai api completions.create \ --model gpt-4.1-mini \ --prompt "tell a joke about a fish"
- kristopolous 1y ago
  What is really needed is a usable multiplexed pipeline management and event system. Then you can instrument through metaprogramming. For instance, an alert system could be: "If the threshold goes over 1.0, contact the on-call person through their preferred method" - which may work ... maybe. Or: if any( "check_condition {x}", condition_set ): find_person("on call", right now).contact("preferred") ... the point is to divide everything up into small one-shots, parallelize them, use it as glue/api. Then you get composability. If you can get a framework for coroutines going then it's real game on. The final step is "needs based pulling" which is an inversion of mcp - contextual streams as event based sub-systems. Things are still too slow for this to be not painful but that won't be the case forever. Currently everything is linear. Doesn't have to be ... really doesn't.

3 ms·

Hasn't this been invented already in multiple shapes and forms..? I wrote my own version clai[1] over a year ago which does exactly this, only that it has tools

by baalimago 1y ago

simonw 1y ago
Looks quite similar to my https://llm.datasette.io https://llm.datasette.io tool as well. Honestly though, CLI tools for accessing LLMs (including piping content in and out of them) is such a clearly good idea I'm glad to see more tools implementing the pattern.
- dcre 1y ago
  It's very surprising that it has taken this long to see a first-party CLI like this.
  - simonw 1y ago
    OpenAI have had a bad one for a couple of years. It looks something like this: pip install openai export OPENAI_API_KEY="..." openai api completions.create \ --model gpt-4.1-mini \ --prompt "tell a joke about a fish"
- kristopolous 1y ago
  What is really needed is a usable multiplexed pipeline management and event system. Then you can instrument through metaprogramming. For instance, an alert system could be: "If the threshold goes over 1.0, contact the on-call person through their preferred method" - which may work ... maybe. Or: if any( "check_condition {x}", condition_set ): find_person("on call", right now).contact("preferred") ... the point is to divide everything up into small one-shots, parallelize them, use it as glue/api. Then you get composability. If you can get a framework for coroutines going then it's real game on. The final step is "needs based pulling" which is an inversion of mcp - contextual streams as event based sub-systems. Things are still too slow for this to be not painful but that won't be the case forever. Currently everything is linear. Doesn't have to be ... really doesn't.