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About DeepEval

DeepEval is an open-source LLM evaluation framework designed to help developers build and test reliable AI systems. It provides a robust set of tools for evaluating large language models (LLMs) and other AI components, integrating seamlessly into existing development workflows, particularly with Python's Pytest. The framework offers a wide array of research-backed metrics, including advanced techniques like G-Eval, DAGA, and QAG, to provide nuanced and objective scoring for various AI use cases. It supports both single and multi-turn evaluations, handles multi-modal data (text, images, audio), and can even generate synthetic test data to address a lack of real-world examples. DeepEval is built for production-grade standards and integrates with popular AI stacks like OpenAI, LangChain, and Anthropic, making it suitable for enterprises and individual developers focused on ensuring the quality and reliability of their AI applications. For team-wide collaboration and advanced features like regression testing, AI experiments, and online monitoring, DeepEval can be used on Confident AI, a cloud-based LLM evaluation platform developed by the creators of DeepEval.