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doc: fix broken link and add README (#573)

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Fix broken link to embedding functions

testing: broken link was verified after local docs build to have been
repaired

---------

Co-authored-by: Chang She <chang@lancedb.com>
This commit is contained in:
Chang She
2023-10-16 16:13:07 -07:00
committed by GitHub
parent 1b8cda0941
commit bb01ad5290
3 changed files with 28 additions and 2 deletions
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docs/src/index.md
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@@ -67,7 +67,7 @@ LanceDB's core is written in Rust 🦀 and is built using <a href="https://githu
## Documentation Quick Links
* [`Basic Operations`](basic.md) - basic functionality of LanceDB.
* [`Embedding Functions`](embedding.md) - functions for working with embeddings.
* [`Embedding Functions`](embeddings/index.md) - functions for working with embeddings.
* [`Indexing`](ann_indexes.md) - create vector indexes to speed up queries.
* [`Full text search`](fts.md) - [EXPERIMENTAL] full-text search API
* [`Ecosystem Integrations`](python/integration.md) - integrating LanceDB with python data tooling ecosystem.

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docs/src/search.md
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@@ -4,7 +4,7 @@
In a recommendation system or search engine, you can find similar products from
the one you searched.
In LLM and other AI applications,
each data point can be [presented by the embeddings generated from some models](embedding.md),
each data point can be [presented by the embeddings generated from some models](embeddings/index.md),
it returns the most relevant features.
A search in high-dimensional vector space, is to find `K-Nearest-Neighbors (KNN)` of the query vector.