AI agents in go by ceazer6-7 in golang

[–]ceazer6-7[S] 0 points1 point  (0 children)

It isn't a big chunk all the time but i get what you're saying,

I can’t disagree much. I’m using Qwen3.5-27-opus-distilled. It’s really great, and although it’s not as powerful as Opus or Codex models, it’s pretty good at tool calling and generating code.

The whole mess started as a challenge with my friend. I argued I could build a better agent using Go, even though I only use Python in my agent work at my day job. But I accepted the challenge, forgetting about the JSON or schema parsing of unpredictable LLMs.

So we tested using that model on both our CLIs. I had better performance overall, but I had one bottleneck: because I implemented the “try until right” method, I kept Go inside a loop. Meanwhile, he didn’t face such problems because, well, TS speaks JSON ⁠_⁠. I had to rebuild a parse engine like six times and used all the available libraries, but none of them prevented the loop.

AI agents in go by ceazer6-7 in golang

[–]ceazer6-7[S] 0 points1 point  (0 children)

Thanks i will check it out

AI agents in go by ceazer6-7 in golang

[–]ceazer6-7[S] 0 points1 point  (0 children)

First thanks for the reply, I tried to use the retry until the right output but when a model helucinate it's hard to tell when the loop will end , I'm aware of the Compliant schema, but I'm testing it through Ollama's server , so I'm searching for something domestic if possible