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#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

#typescript#ci#ci_cd#cicd#evaluation#evaluation_framework#llm#llm_eval#llm_evaluation#llm_evaluation_framework#llmops#pentesting#prompt_engineering#prompt_testing#prompts#rag#red_teaming#testing#vulnerability_scanners Promptfoo is a tool that helps developers test and improve AI applications using Large Language Models (LLMs). It allows you to **test prompts and models** automatically, **secure your apps** by finding vulnerabilities, and **compare different models** side-by-side. You can use it on your computer or integrate it into your development workflow. This tool helps you make sure your AI apps work well and are secure before you release them. It saves time and ensures quality by using data instead of guessing. https://github.com/promptfoo/promptfoo