AI Decision Making — Optimizing Routes

AI decision-making can now be easily trained using the optimization methods available in semantic router. Route score thresholds define whether a route should be chosen. If the score we identify for any given route is higher than the Route.score_threshold, it passes; otherwise, it does not, and either another route is chosen or we return no route. Given that this one score_threshold parameter can define the choice of a route, it's important to get it right — but it's incredibly inefficient to do so manually. Instead, we can use the fit and evaluate methods of our RouteLayer. All we must do is pass a smaller number of (utterance, target route) examples to our methods, and with the fit, we will often see dramatically improved performance within seconds — we will see how to measure that performance gain with evaluation. ⭐ GitHub Repo: https://github.com/aurelio-labs/semantic-router/ 📌 Code: https://github.com/aurelio-labs/semantic-router/blob/main/docs/06-threshold-optimization.ipynb 🔥 Semantic Router Course: https://www.aurelio.ai/course/semantic-router 👋🏼 AI Consulting: https://aurelio.ai 👾 Discord: https://discord.gg/c5QtDB9RAP Twitter: https://twitter.com/jamescalam LinkedIn: https://www.linkedin.com/in/jamescalam/