Get scores for factual accuracy, context retrieval quality, guideline adherence, tonality, and many more. You can’t improve what you can’t measure. UpTrain continuously monitors your application's performance on multiple evaluation criterions and alerts you in case of any regressions with automatic root cause analysis. UpTrain enables fast and robust experimentation across multiple prompts, model providers, and custom configurations, by calculating quantitative scores for direct comparison and optimal prompt selection. Hallucinations have plagued LLMs since their inception. By quantifying degree of hallucination and quality of retrieved context, UpTrain helps to detect responses with low factual accuracy and prevent them before serving to the end-users. Unleash unparalleled power with a single line of code and tailor every detail as per as your use-case.
Features
- Evaluations to test various aspects of your LLM responses
- Single line of code to run LLM evaluations
- When it comes to AI, there is no one size-fits-all solution
- Single line of code to run LLM evaluations
- When it comes to AI, there is no one size-fits-all solution
- Get scores for factual accuracy, context retrieval quality, guideline adherence, and tonality
Project Samples
