Keywords AI
Lunary vs Ragas
Compare Lunary and Ragas side by side. Both are tools in the Observability, Prompts & Evals category.
Quick Comparison
| Category | Observability, Prompts & Evals | Observability, Prompts & Evals |
| Pricing | — | Open Source |
| Best For | — | Developers building RAG applications who need specialized evaluation metrics |
| Website | lunary.ai | ragas.io |
| Key Features | — |
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| Use Cases | — |
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When to Choose Lunary vs Ragas
- Evaluating RAG pipeline quality end-to-end
- Measuring retrieval precision and recall
- Testing faithfulness and answer relevance
About Lunary
Lunary is an open-source LLM observability platform for monitoring AI applications in production. It provides request tracing, cost tracking, user analytics, and prompt management with a clean dashboard. Lunary can be self-hosted for data privacy and offers a managed cloud option.
About Ragas
Ragas is an open-source evaluation framework specifically designed for RAG (Retrieval-Augmented Generation) pipelines. It provides metrics for context precision, context recall, faithfulness, and answer relevancy, helping teams measure and improve the quality of their RAG systems. Ragas has become the standard evaluation toolkit for teams building production RAG applications.
What is Observability, Prompts & Evals?
Tools for monitoring LLM applications in production, managing and versioning prompts, and evaluating model outputs. Includes tracing, logging, cost tracking, prompt engineering platforms, automated evaluation frameworks, and human annotation workflows.
Browse all Observability, Prompts & Evals tools →