docs: own every page path, and port the upstream changes

lancedb now holds a page at every path the site publishes, including the twelve
Enterprise ones. Those are real open-source pages -- what the capability is, and
what the embedded form does instead -- rather than blank placeholders, so the
open-source site is complete on its own. sophon becomes an overlay whose page
replaces the one at the same path, which means navigation lives in one place and
the two repositories only have to agree on a path.

That removes the whole class of problem where a page could only be reached from
one of the two trees. The open-source site went from twenty-four dangling
Enterprise links to one, and that one points at the dataset pages the build
repository owns.

Ports four changes that landed on the docs repository after this branch left it:

  #344  indexing and quantization rewritten
  #354  LeRobot native reader
  #361  training/index renamed to training/data-loading and rewritten
  #362  distance metric mismatch falls back to a brute-force scan

None applied as patches, because these files were merged or split here --
quantization into the vector index page, multi-vector into vector search,
performance into four pages. Each was ported by taking the upstream page and
re-applying the restructure on top, which also picked up a correction that would
otherwise have been lost: the stricter brute-force threshold for multi-vector
columns is a Cloud limit, not an Enterprise one.

The upstream LeRobot page linked to a Geneva page that no longer exists; it now
points at the feature-engineering pages that replaced it.
This commit is contained in:
Jack Ye
2026-09-25 15:19:54 -07:00
parent 0913e2a436
commit 70c10e4aa4
34 changed files with 1292 additions and 1103 deletions
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---
title: "Full-text search with SQL"
sidebarTitle: "Full-Text Search"
description: "Running full-text search from SQL, with fuzzy, phrase, boolean and boost queries."
icon: magnifying-glass
keywords: ["fts", "sql", "full text search", "fuzzy", "phrase"]
---
<Badge color="red">Enterprise</Badge>
This page describes a LanceDB Enterprise capability. The embedded form
of LanceDB has no server to provide it -- see
[Architecture](/architecture) for what differs between the two.
Full-text search is available in SQL as the [`fts()`](/sql/functions#fts) table
function, which returns matching rows plus a `_score` column:
```sql
SELECT id, text, _score
FROM fts('my_docs', 'puppy')
ORDER BY _score DESC
LIMIT 5
```
The second argument is a bare query string, or a JSON query object for the
fuzzy, phrase, boolean, boost and multi-match forms.
For a keyword test that needs no score,
[`contains_tokens`](/sql/scalar-functions#contains-tokens) is a predicate usable
directly in `WHERE`, and is accelerated by the full-text index.
The query-builder equivalent is [Full-Text Search](/search/full-text-search).
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---
title: "Connecting a SQL client"
sidebarTitle: "Client Connection"
description: "Reaching the Arrow Flight SQL endpoint from Python or TypeScript."
icon: plug
keywords: ["flight sql", "client", "connect", "arrow"]
---
<Badge color="red">Enterprise</Badge>
This page describes a LanceDB Enterprise capability. The embedded form
of LanceDB has no server to provide it -- see
[Architecture](/architecture) for what differs between the two.
SQL is served over an
[Arrow Flight SQL](https://arrow.apache.org/docs/format/FlightSql.html)
endpoint, so any Flight SQL client reaches it and results arrive as Arrow
record batches.
From Python, the connection runs SQL directly without a separate client:
```python
reader = db.execute_query("SELECT id, text FROM my_docs LIMIT 10")
table = reader.read_all()
```
The TypeScript SDK has no SQL method; use a Flight SQL client. See
[SDKs and SQL](/basics/apis) for the full comparison, and the
[SQL reference](/sql) for the dialect.