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refactor: reorgnize all examples/ and test/

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Andy Lee
2025-08-03 22:37:45 -07:00
parent 58556ef44c
commit b0239b6e4d
41 changed files with 127 additions and 1926 deletions
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docs/normalized_embeddings.md
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@@ -72,4 +72,4 @@ Using the wrong distance metric with normalized embeddings can lead to:
- **Incorrect ranking** of search results
- **Suboptimal performance** compared to using the correct metric
For more details on why this happens, see our analysis of [OpenAI embeddings with MIPS](../examples/document_rag.py).
For more details on why this happens, see our analysis in the [embedding detection code](../packages/leann-core/src/leann/api.py) which automatically handles normalized embeddings and MIPS distance metric issues.