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Show HN: RAGsplain – What does your RAG model see before it answers?
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.
- chrisxlucas 1y agosuper 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.
- datafog 1y agoI like the idea of this. When I tried a couple things it didn't work. Either too long or nothing happened after I clicked the 2nd button. Maybe an example page would be nice.
- fredthedeve 1y agoThanks a lot for the feedback! Really appreciate you trying it out. For longer videos, transcription can definitely take a bit... I'm working on moving processing to more powerful servers (currently running off my home machine) For a quick overview on how it works and to get past those initial steps, this demo video of ragsplain might help: https://youtu.be/BwuA_e7Xn74 https://youtu.be/BwuA_e7Xn74