Find similar content

#python#evaluation_framework#evaluation_metrics#llm_evaluation#llm_evaluation_framework#llm_evaluation_metrics DeepEval is an open-source tool that makes it easy to test and improve large language model (LLM) applications, much like how Pytest works for regular software, but focused on LLM outputs. It offers over 30 ready-to-use metrics—such as answer relevancy, faithfulness, and hallucination—to check if your LLM is accurate, safe, and reliable. You can test your whole application or just parts of it, and even generate synthetic data for better testing. DeepEval works locally or in the cloud, letting you compare results, share reports, and keep improving your models. This helps you build better, safer, and more trustworthy LLM apps with less effort[1][2][3]. https://github.com/confident-ai/deepeval