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Ragas: artificial intelligence features and setup
An open-source framework for testing and evaluating LLM applications.
Tool by the Otomatzia editorial team · source content checked on
Overview
Ragas is designed to measure language model applications, especially retrieval and answer pipelines, using metrics rather than intuition. You run questions, check faithfulness to sources, and identify answers that are not supported by the documents. Before relying on a score, tailor the question set to your business process, including questions that have no answer in the database. A high score on an artificial test set may hide failures in Hebrew.
Features
- An open-source framework for evaluating LLM applications
- Metrics for source faithfulness and retrieval quality
- Repeatable testing after a pipeline change
Business uses
- Testing a knowledge assistant against questions with known sources
- Identifying answers that are not supported by the retrieved document
Getting started
- Collect questions and source answers after removing identifiers.
- Run an initial evaluation and save it as a baseline.
- Add questions without sources and check that the system avoids guessing.
What to check
- Tailor the test set to your language and documents.
- An average score may hide a single serious failure.
Sources to check next
Vendor features and prices change. Confirm details on the linked official pages before you rely on them.