Audience

Professional users interested in a tool to evaluate, test, and optimize their LLM applications

About DeepEval

DeepEval is a simple-to-use, open source LLM evaluation framework, for evaluating and testing large-language model systems. It is similar to Pytest but specialized for unit testing LLM outputs. DeepEval incorporates the latest research to evaluate LLM outputs based on metrics such as G-Eval, hallucination, answer relevancy, RAGAS, etc., which uses LLMs and various other NLP models that run locally on your machine for evaluation. Whether your application is implemented via RAG or fine-tuning, LangChain, or LlamaIndex, DeepEval has you covered. With it, you can easily determine the optimal hyperparameters to improve your RAG pipeline, prevent prompt drifting, or even transition from OpenAI to hosting your own Llama2 with confidence. The framework supports synthetic dataset generation with advanced evolution techniques and integrates seamlessly with popular frameworks, allowing for efficient benchmarking and optimization of LLM systems.

Pricing

Starting Price:
Free
Free Version:
Free Version available.

Integrations

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Company Information

Confident AI
United States
docs.confident-ai.com

Videos and Screen Captures

DeepEval Screenshot 1
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Product Details

Platforms Supported
Cloud
Training
Documentation
Support
Online

DeepEval Frequently Asked Questions

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DeepEval Product Features