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nastyapash
09877ed06e
* Add RAG Landing Page * fix * fix form, image and links * fix * Content update * shortened file link * update links
40 lines
1.4 KiB
Markdown
40 lines
1.4 KiB
Markdown
---
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title: Why evaluate your RAG application?
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description: The guide will outline both common issues, as well as recommendations to avoid these pitfalls.
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cards:
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- id: 0
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image:
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src: /img/rag-evaluation-guide/integrations/maximize-search.svg
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alt: Maximize search
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description: Lack of Precision
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- id: 1
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image:
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src: /img/rag-evaluation-guide/integrations/enrich-context.svg
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alt: Enrich context
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description: Poor recall
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- id: 2
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image:
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src: /img/rag-evaluation-guide/integrations/avoid-hallucinations.svg
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alt: Avoid hallucinations
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description: “Lost in the middle”
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frameworksTitle: Recommended evaluation frameworks
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frameworksDescription: In the guide, we explore three popular frameworks that can help simplify your evaluation process.
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frameworksCards:
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- id: 0
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image:
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src: /img/rag-evaluation-guide/integrations/ragas.svg
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alt: Ragas logo
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description: Ragas is an open-source framework for evaluating retrieval augmented generation systems.
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- id: 1
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image:
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src: /img/rag-evaluation-guide/integrations/quotient.svg
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alt: Quotient AI logo
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description: Quotient AI is a platform that focuses on building and deploying RAG systems.
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- id: 2
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image:
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src: /img/rag-evaluation-guide/integrations/arize.svg
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alt: Arize logo
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description: Arize Phoenix is a tool designed for monitoring and observability in AI systems, including RAG pipelines.
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sitemapExclude: true
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---
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