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Jack YeandBrendan Clement
47b7babc08
Move the public website pages into `docs/web` beside the SDK, with
shared navigation and executable example sources in `docs/web-tests`.
The combined website is assembled by
[lancedb/docs#355](https://github.com/lancedb/docs/pull/355), with six
Enterprise replacements from
[lancedb/sophon#7681](https://github.com/lancedb/sophon/pull/7681).
This includes Function guidance, runnable Quickstarts, regenerated
snippets, production contact/demo fixes, the legacy SQL route, and the
LeRobot redirect. LeRobot remains attributed to Geneva; all 34 Geneva
pages remain in the docs repository until Function officially launches.
Materialized-view guidance follows the full rebuild refresh introduced
by #4373: local refresh writes the complete result, has no `full`
argument, supports `source_version`, and no longer requires stable row
IDs. Deployment SQL refresh options and stable-ID setup are qualified by
version/configuration. Function input guidance distinguishes ordinary
stored columns from computed inputs supported by newer deployments.
**Validation:** independently accepted local checks include 95 Python
tests (real Enterprise excluded), eight TypeScript tests, Rust
Quickstart, snippet parity, typos, deterministic assembly, Mint
validation and links/anchors/redirects. The combined baseline retains
all 181 production routes and 17 legacy redirects. Examples ran locally
against source-built Python SDK 0.40.0b13; existing GitHub workflows do
not run `docs/web-tests`. New main at `069b2f7d` is 0.41.0b0 and adds
computed Function inputs; that SDK was not exercised by the accepted
tests. Latest prose corrections receive focused site validation.
**Merge/rollout:** merge this and #7681 before #355's combined CI, which
reads producer `main`. This is migration infrastructure: section
overlays, source-owned skills and automatic versioned paired releases
remain follow-ups. The current manual publisher is transitional. Hosted
validation, a supported SDK/Enterprise release pair and a real
Enterprise walkthrough remain pending.
Production Mintlify watches `lancedb/docs:deploy-freeze`, directory
`docs`; preserve that source through review. The separate SDK GitHub
Pages reference workflow rebuilds on main merges.
**Updated-head CI (9a50f8db):**
[Typos](https://github.com/lancedb/lancedb/actions/runs/37654185443/job/112904990558),
[PR
title](https://github.com/lancedb/lancedb/actions/runs/37654179507/job/112904974595)
and
[Aikido](https://app.aikido.dev/featurebranch/scan/215386145?groupId=74229)
pass. Critical findings in the example lockfiles were patched: all Sharp
copies use 0.35.5, protobufjs 7.6.6, tar 7.5.22, quinn-proto 0.11.19,
zerovec 0.11.8 and zerovec-derive 0.11.6. The SDK's product dependencies
are unchanged. The revised lockfiles pass eight TypeScript examples,
HuggingFace decode/resize/crop/rescale/normalize plus AVIF roundtrip,
and Rust Quickstart. Aikido passing does not mean every advisory is
cleared; npm still reports 29 high and five moderate advisories in the
example dependency graph. No scanner bypass or suppression was added.
The Function prose correction passes combined/standalone Mint,
deterministic assembly, routes and assets. The revised 325-file site
checksum is
`175bec06864abb400dd292e667ba93448c0479b8359fd7bf6146afabf9040647`. This
PR remains open for independent review; further merges are on hold.
---------
Co-authored-by: Brendan Clement <brendan.clement@lancedb.com>
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{/* Auto-generated by scripts/mdx_snippets_gen.py. Do not edit manually. */}
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export const RsCreateIndex = "// For this example, `table` is a lancedb::Table with a column named\n// \"vector\" that is a vector column with dimension 128.\n\n// By default, if the column \"vector\" appears to be a vector column,\n// then an IVF_PQ index with reasonable defaults is created.\ntable\n .create_index(&[\"vector\"], Index::Auto)\n .execute()\n .await?;\n// For advanced cases, it is also possible to specifically request an\n// IVF_PQ index and provide custom parameters.\ntable\n .create_index(\n &[\"vector\"],\n Index::IvfPq(\n // Here we specify advanced indexing parameters. In this case\n // we are creating an index that my have better recall than the\n // default but is also larger and slower.\n IvfPqIndexBuilder::default()\n // This overrides the default distance type of l2\n .distance_type(DistanceType::Cosine)\n // With 1000 rows this have been ~31 by default\n .num_partitions(50)\n // With dimension 128 this would have been 8 by default\n .num_sub_vectors(16),\n ),\n )\n .execute()\n .await?;\n";
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export const RsSearch1 = "let query_vector = [1.0; 128];\n// By default the index will find the 10 closest results using default\n// search parameters that give a reasonable tradeoff between accuracy\n// and search latency\nlet mut results = table\n .vector_search(&query_vector)?\n // Note: you should always set the distance_type to match the value used\n // to train the index\n .distance_type(DistanceType::Cosine)\n .execute()\n .await?;\nwhile let Some(batch) = results.try_next().await? {\n println!(\"{:?}\", batch);\n}\n// We can also provide custom search parameters. Here we perform a\n// slower but more accurate search\nlet mut results = table\n .vector_search(&query_vector)?\n .distance_type(DistanceType::Cosine)\n // Override the default of 10 to get more rows\n .limit(15)\n // Override the default of 20 to search more partitions\n .nprobes(30)\n // Override the default of None to apply a refine step\n .refine_factor(1)\n .execute()\n .await?;\nwhile let Some(batch) = results.try_next().await? {\n println!(\"{:?}\", batch);\n}\nOk(())\n";
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