We were working on a RAG-powered app to enable companies to talk to their free-text data safely when we ran into trouble tracking the performance of our models’ responses. So we built these solutions to help us out: Tonic Validate Metrics for benchmarking, and Tonic Validate Logging + the Tonic Validate UI to track performance improvements to help us choose the best system possible. Tonic Validate provides a simple and convenient UI that you can get for free at https://validate.tonic.ai/.
Two key benefits of using the Tonic Validate tools are (1) automatic logging and metrics calculation with just a few lines of code and (2) a simple, convenient UI to help visualize your experiments, iterations, and benchmarking results for your RAG applications.
Our hope is that these packages will become a useful part of the technique layer behind the growing suite of LLM-powered applications and, more importantly, that the open-source packages evolve and thrive with your contributions.
We’re excited to hear what you all think in the comments!
Read our docs here: https://docs.tonic.ai/validate/
Get the open-source Tonic Validate Metrics package at: https://github.com/TonicAI/tvalmetrics
Get the open-source Tonic Validate Logging SDK at: https://github.com/TonicAI/tvallogging
Sign up for the Tonic Validate UI here: https://validate.tonic.ai/
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