mirror of
https://github.com/lancedb/lancedb.git
synced 2026-11-13 14:16:54 +00:00
Brendan Clement
1db0d3ca5f
Labels early access features and hides features we aren't documenting yet. **Early access label:** Functions (4 pages, plus the GPU refresh, checkpointing and adaptive execution pages), Secrets (3 pages), Tiered Index Cache, Blob V2, and merge insert, which is labelled for Enterprise only. Two sidebar titles are shorter so the tag fits. **Hidden:** branching, JSON columns and geospatial. - The JSON functions page and the agent branch-experiments tutorial go in `.mintignore`. - `tables/branching` stays reachable but out of the nav, as #4859 left it, because SDK error messages link to it. - Other pages' mentions of these features become draft comments, so they're easy to restore. **Secrets page:** drops references to manual KMS setup, which the control plane handles. It keeps the encryption-at-rest facts, states the Azure value-size limit inline, and points a 501 error to support.
43 lines
2.1 KiB
Plaintext
43 lines
2.1 KiB
Plaintext
---
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title: "Tutorials"
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sidebarTitle: "Overview"
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description: "Worked examples of building with LanceDB, grouped by what they build."
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---
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Every tutorial is one page in the sidebar, grouped by what it builds. The
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documentation explains how a feature works; these show it doing something.
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Examples marked as notebooks live in the
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[vectordb-recipes](https://github.com/lancedb/vectordb-recipes) repository and
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are runnable in Colab; the rest are written up here.
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## Where to start {#start}
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<CardGroup cols={2}>
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<Card title="Search" icon="magnifying-glass" href="/tutorials/search/hybrid-search-beir">
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Vector, multi-vector, hybrid and full-text retrieval.
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</Card>
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<Card title="RAG" icon="robot" href="/tutorials/agents/contextual-rag">
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Retrieval-augmented generation and agent applications.
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</Card>
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<Card title="Feature engineering" icon="wand-magic-sparkles" href="/tutorials/feature-engineering/feature-engineering-101">
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Deriving columns and materialized views.{/* Draft until branching reaches early access: restore "Deriving columns, materialized views, experimenting on branches." */}
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</Card>
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<Card title="Training" icon="graduation-cap" href="/training/object-detection">
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Curating data and training models directly on a table.
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</Card>
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</CardGroup>
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## The features these use {#read-the-docs}
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| Feature | What it covers |
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|:--------|:------------|
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| [Vector search](/search/vector-search) | Similarity search, distance metrics, and tuning it. |
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| [Full-text search](/search/full-text-search) | Keyword search over text columns. |
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| [Hybrid search](/search/hybrid-search) | Keyword and vector search combined. |
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| [Multi-vector search](/search/vector-search) | Several embeddings per document. |
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| [Reranking](/reranking) | Reordering results to improve the top-k. |
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| [Feature engineering](/feature-engineering) | Deriving columns and tables from data already stored. |
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| [Materialized views](/management/materialized-view) | A table defined by a query, brought up to date by each refresh. |
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| [Training](/training/data-loading) | Reading a table into a data loader. |
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