Evaluate LLM-based RAG Applications with automated test set generation
🐢 Open-Source Evaluation & Testing library for LLM Agents - Giskard-AI/giskard-oss
Evaluate LLM-based RAG Applications with automated test set generation launched on April 11, 2024 with 13 votes, #1,030 of 4,347 launches that month and more than 75% of that year's launches. The site was still online in September 2026, 2 years on.
In plain words
This tool automatically generates test sets to evaluate retrieval-augmented generation (RAG) applications that use large language models. It's designed for developers and data scientists building RAG systems who need to validate performance without manually creating test cases. The automation of test set generation stands out as the primary feature, helping teams assess their applications more efficiently.
written from the facts on this page · September 2026
Does a similar job
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Ragas – Open-source library for evals and testing RAG systems2024 · github.com · ▲15Ragas is an open-source library designed for evaluating and testing RAG (Retrieval-Augmented Generation) and other LLM applications. It offers a diverse set of metrics and methods, including synthetic test data generation, to help you assess your RAG applications. Ragas was initially developed to address our own needs for evaluating RAG chatbots last year. ### Problems Ragas Can Solve: - How can you select the best components for your RAG, such as the retriever, reranker, and LLM? - How can you create a test dataset without incurring significant expenses and time? We believe there's a need…
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