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Show HN: RAGsplain – What does your RAG model see before it answers?

https://www.ragsplain.com/
3•fredthedeve•7h ago
Are your RAG models hallucinating? Maybe the issue isn't the LLM, but the retrieval phase.

I built RAGsplain (ragsplain.com) to help debug this. You upload documents (PDFs, audio, YouTube links), choose a retrieval method (semantic, keyword, or hybrid), and see the exact chunks of context passed to the model — match scores included.

Turns out: when retrieval is bad, even the best model can’t think straight.

It’s open and free to use. Would love feedback from folks building RAG pipelines.

Comments

chrisxlucas•7h ago
super cool.. it's interesting to see the small advancements/features foundational model providers are starting to build in for interpretability/explainability. this is way more clear UX/UI with the % match and excerpt.

DeadliQ – AI-powered deadline tracking for your documents

https://www.deadliq.com
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Unmoved mover

https://en.wikipedia.org/wiki/Unmoved_mover
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Graph Continuous Thought Machines

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https://mcclane.super.site/
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https://twitter.com/TenZorroAI/status/1945224617859113401
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