How do I debug my RAG pipeline stage by stage?

Use tools like mloda: define feature chains with '__' boundaries, run subsets, inspect outputs and evals at each step.

What is mloda and is it production-ready?

mloda is an open-source framework for modular RAG pipelines with swappable plugins and built-in metrics. Core features work; some image bits evolving.

Why not just use end-to-end evaluation for RAG?

It hides inter-stage breaks — one change ripples invisibly. Stage-wise reveals root causes fast.

🤖 AI Dev Tools

I Swapped One Chunk in My RAG Pipeline and Recall Tanked—Here's How Stage-by-Stage Debugging Saved It

Picture this: your RAG pipeline's humming at 0.82 recall. Swap fixed chunks for sentences—bam, down to 0.68. End-to-end metrics scream 'broken,' but won't say where.

theAIcatchup Apr 10, 2026 4 min read

Modular RAG pipeline diagram showing feature chain stages like chunking, dedup, and embedding with evaluation points

⚡ Key Takeaways

End-to-end evals hide bugs; stage-by-stage reveals them surgically. 𝕏
Sentence chunking exposes dedup weaknesses—swap to n-gram for fixes. 𝕏
Modular RAG via feature chains makes pipelines swappable and debuggable like Unix pipes. 𝕏

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#FAISS index #RAG pipelines #Retrieval-Augmented Generation #debugging RAG #mloda #mloda rag_integration #mloda-ai #mlodaAI #modular AI tools #stage-by-stage eval

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Originally reported by dev.to

⚡ Key Takeaways

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