Also here is something fun: Valmis is probably the first AI agent that is able to play real chess with legit moves. We all know LLMs are notoriously terrible at playing chess and always hallucinate moves. So we added a tool to the agent called chess-engine, which basically requires the agent not to rely on text generation to produce moves, but instead to produce each move strictly based on the calculation of a lightweight chess engine built in. And AI can be a great (and sportsmanlike!) chess player.
This is an example I created to show how LLMs can actually do rigorous work. We cannot always trust the output generated (or hallucinated most of the time) by LLMs, but if we add a deterministic tool layer and instruct the model to rely only on the tool's output, we can get more accurate results. In this case, the tool used is a lightweight chess engine.
Looks good, I’ll spin up an instance and give it a try. Btw, does it support multiple users? And the chess engine thing is brilliant, I guess you can extend your logic to other fields, can tools be extended by the end user?