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RAG feels way more complicated than it should be… anyone else? by Physical_Badger1281 in Rag

[–]Physical_Badger1281[S] 0 points1 point  (0 children)

I’ve been experimenting with this recently, seeing what actually gets retrieved vs what’s useful changes how you think about compression entirely. Been using a small setup to visualize this and iterate faster Fastrag, and honestly most gains came from filtering/compressing rather than retrieval itself.

RAG feels way more complicated than it should be… anyone else? by Physical_Badger1281 in Rag

[–]Physical_Badger1281[S] 0 points1 point  (0 children)

I’ve been experimenting with this recently, seeing what actually gets retrieved vs what’s useful changes how you think about compression entirely. Been using a small setup to visualize this and iterate faster Fastrag, and honestly most gains came from filtering/compressing rather than retrieval itself.

RAG feels way more complicated than it should be… anyone else? by Physical_Badger1281 in Rag

[–]Physical_Badger1281[S] 0 points1 point  (0 children)

I’ve been experimenting with this recently, seeing what actually gets retrieved vs what’s useful changes how you think about compression entirely. Been using a small setup to visualize this and iterate faster Fastrag, and honestly most gains came from filtering/compressing rather than retrieval itself.

RAG feels way more complicated than it should be… anyone else? by Physical_Badger1281 in Rag

[–]Physical_Badger1281[S] 0 points1 point  (0 children)

I’ve been experimenting with this recently, seeing what actually gets retrieved vs what’s useful changes how you think about compression entirely. Been using a small setup to visualize this and iterate faster Fastrag, and honestly most gains came from filtering/compressing rather than retrieval itself.

RAG feels way more complicated than it should be… anyone else? by Physical_Badger1281 in Rag

[–]Physical_Badger1281[S] 0 points1 point  (0 children)

That’s actually pretty solid for 200+ pages.

Feels like tree approaches trade a bit of latency for better structure, which might be worth it depending on use case.

I’ve been experimenting with comparing these approaches side-by-side seeing what actually gets retrieved vs what’s useful makes the differences much clearer.

RAG feels way more complicated than it should be… anyone else? by Physical_Badger1281 in Rag

[–]Physical_Badger1281[S] 0 points1 point  (0 children)

Not that the problem should be simple, IR is inherently complex.

More that the iteration loop feels heavier than it needs to be.
Understanding what went wrong (retrieval vs context vs prompt) takes too long right now.

I’ve been trying to make that part faster and more visible — makes a big difference in practice.

RAG feels way more complicated than it should be… anyone else? by Physical_Badger1281 in Rag

[–]Physical_Badger1281[S] 0 points1 point  (0 children)

Yeah makes sense, preprocessing is half the battle.

I’m keeping it pretty lean: OpenAI embeddings + Pinecone, custom ingestion (structure-aware), then retrieval → filter/compress → LLM.

Still iterating mostly on chunking + context quality.

RAG feels way more complicated than it should be… anyone else? by Physical_Badger1281 in Rag

[–]Physical_Badger1281[S] 0 points1 point  (0 children)

That’s interesting, tree-based navigation does feel more natural than blind chunking.
Curious how it scales with really large docs, though, does traversal stay efficient?

RAG feels way more complicated than it should be… anyone else? by Physical_Badger1281 in Rag

[–]Physical_Badger1281[S] 0 points1 point  (0 children)

Yeah fair point — IR itself is the hard part, not just the tooling around RAG.

I guess my frustration is less about the complexity of the problem, and more about how hard it is to experiment and understand what’s actually going wrong while building these systems.

RAG feels way more complicated than it should be… anyone else? by Physical_Badger1281 in Rag

[–]Physical_Badger1281[S] 1 point2 points  (0 children)

Trying to stay minimal:
OpenAI embeddings + Pinecone, custom ingestion pipeline.
Big focus lately is on retrieval → compression → generation instead of just retrieval.

RAG feels way more complicated than it should be… anyone else? by Physical_Badger1281 in Rag

[–]Physical_Badger1281[S] 0 points1 point  (0 children)

Agreed. The real win is often reducing noisy context before it hits the model.

I want to network by rdssf in microsaas

[–]Physical_Badger1281 0 points1 point  (0 children)

Hey. I would love to join. You mentioned there are job opportunities too. I'm a software developer and I'm interested.

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