Project Title

deepeval — The LLM Evaluation Framework for Unit Testing Large-Language Model Systems

Overview

DeepEval is an open-source LLM evaluation framework designed for unit testing large-language model outputs. It specializes in evaluating and testing these models using metrics such as G-Eval, hallucination, answer relevancy, and RAGAS. DeepEval runs locally on your machine, making it a practical tool for developers working with RAG pipelines, chatbots, and AI agents.

Key Features

Specialized for unit testing LLM outputs, similar to Pytest.
Incorporates the latest research for evaluating LLM outputs.
Supports metrics like G-Eval, hallucination, answer relevancy, and RAGAS.
Runs locally on your machine for evaluation.

Use Cases

Evaluating RAG pipelines to determine optimal models and prompts.
Testing chatbots and AI agents for performance and accuracy.
Preventing prompt drifting in agentic workflows.
Transitioning from OpenAI to hosting your own Deepseek R1 with confidence.

Advantages

Simplifies the evaluation process for large-language model systems.
Provides a locally run framework for more control and security.
Offers a platform for comparing iterations and generating testing reports.

Limitations / Considerations

The framework is specialized for LLMs and may not be suitable for other types of model evaluations.
As an open-source project, community support and updates are dependent on contributors.

Pytest: A mature framework for unit testing in Python, not specialized for LLMs but widely used.
LangChain: A framework for building applications with LLMs, offering different functionalities compared to DeepEval.
LlamaIndex: Another tool for working with LLMs, focusing on different aspects than DeepEval.

Basic Information

GitHub: https://github.com/confident-ai/deepeval
Stars: 10,854
License: Unknown
Last Commit: 2025-09-18

📊 Project Information

Project Name: deepeval
GitHub URL: https://github.com/confident-ai/deepeval
Programming Language: Python
⭐ Stars: 10,854
🍴 Forks: 935
📅 Created: 2023-08-10
🔄 Last Updated: 2025-09-18

🏷️ Project Topics

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🎮 Online Demos

Demo GIF

📚 Documentation

deep acyclic graph

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deepeval

Project Description