krzysztof/landing_page
1
0
Fork 0
mirror of https://github.com/qdrant/landing_page.git synced 2026-10-12 14:28:31 +02:00
Code Issues Packages Projects Releases Wiki Activity

syntax nitpick

Browse Source
This commit is contained in:
Dylan Couzon
2026-04-24 12:09:44 -04:00
parent cea3fd6092
commit cef9a3e6a7
1 changed files with 2 additions and 2 deletions
Download Patch File Download Diff File Expand all files Collapse all files
qdrant-landing/content/documentation/tutorials-search-engineering/retrieval-quality.md
+2 -2
View File
@@ -29,7 +29,7 @@ Retrieval quality sits on top of embedding quality, measured separately by bench
## Measure ANN Precision with the Web UI ## Measure ANN Precision with the Web UI
Qdrant's Web UI has a Search Quality tab that measures the gap between approximate and exact search without requiring evaluation code. Open the dashboard at `http://localhost:6333/dashboard` (or your cluster's dashboard on Qdrant Cloud), navigate to your collection, open the Search Quality tab, and click **Check Index Quality** to run the comparison. Qdrant's Web UI includes a Search Quality tab that measures the gap between approximate and exact search without writing evaluation code. Open the dashboard at `http://localhost:6333/dashboard` (or your cluster's dashboard on Qdrant Cloud), navigate to your collection, open the Search Quality tab, and click **Check Index Quality** to run the comparison.
![Search Quality tab with default evaluation results](/documentation/tutorials/retrieval-quality/search-quality-tab.png) ![Search Quality tab with default evaluation results](/documentation/tutorials/retrieval-quality/search-quality-tab.png)
@@ -37,7 +37,7 @@ The tab reports average **precision@k** (1.0 = perfect overlap; 0.95+ is typical
## Tuning the HNSW Parameters ## Tuning the HNSW Parameters
HNSW is a hierarchical graph where each node has a set of links to other nodes. The `m` parameter controls the number of edges per node: higher `m` means higher precision at the cost of more memory. The `ef_construct` parameter controls how many neighbors are considered during index building: higher `ef_construct` means higher precision at the cost of longer indexing time. Defaults are `m=16` and `ef_construct=100`. HNSW is a hierarchical graph where each node has a set of links to other nodes. The `m` parameter controls the number of edges per node: higher `m` means higher precision at the cost of more memory. The `ef_construct` parameter controls how many neighbors are considered during index building: higher `ef_construct` means higher precision at the cost of longer indexing time. The defaults are `m=16` and `ef_construct=100`.
For the full list of HNSW parameters, including on-disk storage and precision/memory trade-offs, see [Optimize Performance](/documentation/ops-optimization/optimize/). For the full list of HNSW parameters, including on-disk storage and precision/memory trade-offs, see [Optimize Performance](/documentation/ops-optimization/optimize/).