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title: How to Handle Small Context Window Limits in RAG Systems
description: When building RAG systems on constrained hardware with small context windows, basic chunk retrieval often fails silently — the right chunk is found but never...
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# How to Handle Small Context Window Limits in RAG Systems

**[freeCodeCamp](https://daily.dev/sources/freecodecamp)** · 16 min read · 1 upvotes · 0 comments

## Summary

When building RAG systems on constrained hardware with small context windows, basic chunk retrieval often fails silently — the right chunk is found but never reaches the model because the prompt budget fills up. A hierarchical pattern solves this: use document-level and chunk-level summaries for routing/retrieval, then switch to raw chunks for the final answer, all governed by an explicit token budget. The approach involves indexing chunk summaries, recursively reducing them into document summaries, and at query time searching summaries first before packing raw chunks into a fixed context budget. A debugging trace shows which chunks were included vs. skipped, distinguishing retrieval failures from context-budgeting failures. The pattern is simpler than LangChain's ParentDocumentRetriever or LlamaIndex's Document Summary Index, requires no vector database for the demo, and is especially useful for local models with limited VRAM.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.freecodecamp.org/news/how-to-handle-small-context-window-limits-in-rag-systems>

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---

Tags: [#python](https://daily.dev/tags/python), [#llm](https://daily.dev/tags/llm), [#typescript](https://daily.dev/tags/typescript), [#rag](https://daily.dev/tags/rag)

[View this post on daily.dev](https://daily.dev/posts/how-to-handle-small-context-window-limits-in-rag-systems-wyr4c0z6q)

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