Bump version: 0.37.0-beta.0 → 0.37.1-beta.0

2026-08-28 00:48:40 +00:00 · 2026-07-29 07:11:47 +00:00
114 changed files with 2158 additions and 10196 deletions
@@ -296,18 +296,16 @@ jobs:
          cargo update -p aws-types --precise 1.3.9
          cargo update -p aws-sigv4 --precise 1.3.5
          cargo update -p aws-credential-types --precise 1.2.8
-          # aws-smithy-checksums must stay at or above 0.63.13: OpenDAL's S3
-          # service needs crc-fast ~1.9, and older releases pin it to ~1.3.
-          cargo update -p aws-smithy-checksums --precise 0.63.13
+          cargo update -p aws-smithy-checksums --precise 0.63.9
          cargo update -p aws-smithy-runtime --precise 1.9.3
-          cargo update -p aws-smithy-http --precise 0.62.6
-          cargo update -p aws-smithy-eventstream --precise 0.60.14
+          cargo update -p aws-smithy-http --precise 0.62.4
+          cargo update -p aws-smithy-eventstream --precise 0.60.12
          cargo update -p aws-smithy-http-client --precise 1.1.3
          cargo update -p aws-smithy-observability --precise 0.1.4
          cargo update -p aws-smithy-query --precise 0.60.8
-          cargo update -p aws-smithy-runtime-api --precise 1.9.3
-          cargo update -p aws-smithy-async --precise 1.2.7
-          cargo update -p aws-smithy-types --precise 1.3.6
+          cargo update -p aws-smithy-runtime-api --precise 1.9.1
+          cargo update -p aws-smithy-async --precise 1.2.6
+          cargo update -p aws-smithy-types --precise 1.3.5
          cargo update -p aws-smithy-xml --precise 0.60.11
          cargo update -p home --precise 0.5.9
      - name: cargo +${{ matrix.msrv }} check
@@ -92,8 +92,6 @@ Python bindings changes:
    * Should use `LOOP.run()` to call the corresponding `AsyncTable` method.
 6. Add concrete sync method to `RemoteTable` class in `python/python/lancedb/remote/table.py`.
 7. Add unit test in `python/tests/test_table.py`.
-8. If you added a new public class or module-level function (not just a method on an
-   existing class), expose it in the API reference. See "Python API reference" below.

 TypeScript bindings changes:

@@ -105,33 +103,6 @@ TypeScript bindings changes:
 5. Add test in `nodejs/__test__/table.test.ts`.
 6. Run `npm run docs` to generate TypeScript documentation.

-## Python API reference
-
-`docs/src/python/python.md` is the entire Python API reference. It is maintained by
-hand, and anything not listed there is not rendered at all, so new public classes and
-module-level functions have to be added explicitly. How depends on the module:
-
-* `lancedb.index`, `lancedb.embeddings`, `lancedb.remote`, and `lancedb.rerankers` are
-  rendered by a single directive each, driven by the module's `__all__`. Add the new
-  name to `__all__` and it appears; forget, and it is silently omitted.
-* Everything else (`lancedb`, `lancedb.table`, `lancedb.query`, `lancedb.db`, ...) is
-  listed symbol by symbol. Add a `::: lancedb.<module>.<Name>` line to the matching
-  section, and remember that the page separates synchronous and asynchronous APIs.
-
-Deliberately undocumented: concrete implementations reached through an abstract base
-(`LanceTable`, `LanceDBConnection`, `RemoteDBConnection`), query base classes already
-covered by `inherited_members`, and internal helpers.
-
-Cross-references in docstrings use mkdocstrings syntax, `[text][lancedb.table.Table]`.
-Plain relative links such as `[Table](Table)` do not resolve. To check your work:
-
-```shell
-pip install -r docs/requirements.txt
-cd docs && PYTHONPATH=. mkdocs build
-```
-
-The docs site only builds on pushes to `main`, so this is not covered by PR CI.
-
 ## Review Guidelines

 Please consider the following when reviewing code contributions.
@@ -152,54 +123,3 @@ Please consider the following when reviewing code contributions.
 ### Documentation
 * New features must include updates to the rust documentation comments. Link to
  relevant structs and methods to increase the value of documentation.
-
-## Cursor Cloud specific instructions
-
-The VM snapshot already has the Rust `1.97.0` toolchain (auto-selected by
-`rust-toolchain.toml`), `protoc`, `uv` (on `PATH` via `~/.bashrc`), the Rust
-debug build artifacts, the Python editable extension, and `nodejs/node_modules`.
-The startup update script only refreshes dependencies (`uv sync` for Python and
-`pnpm install` for Node); it deliberately does NOT rebuild the native
-extensions. After changing Rust or PyO3/napi binding code you must rebuild the
-affected binding yourself (see per-binding rebuild commands below).
-
-Non-obvious caveats discovered during setup:
-
-* The documented Python bootstrap `uv run --extra tests --extra dev maturin
-  develop --extras tests,dev` does not work as-is here: `maturin` is not
-  installed as a CLI in the uv environment, and `maturin develop --extras`
-  runs its own dependency resolution that cannot find the prerelease
-  `pylance==9.0.0rc1` (it lacks the extra package index that `uv` uses via
-  `uv.lock`). Because `uv run --extra tests --extra dev` already installs those
-  extras, the working command is:
-  `cd python && uv run --extra tests --extra dev --with maturin maturin develop`
-  (note: `--with maturin`, and no `--extras`). This is the Python binding
-  rebuild command.
-* Rust core, the Python extension (maturin), and the Node addon (napi) all
-  compile into the SHARED `/workspace/target`. Cargo feature unification differs
-  between `maturin develop` and `pnpm build`, so alternating between building
-  the Python and Node bindings forces a full recompile of shared crates
-  (`lancedb`, `datafusion`, `lance-*`) — roughly 6-7 min each way on this
-  4-core VM. Build one binding at a time to avoid the churn.
-* The `_lancedb` release build (triggered when `uv run`/`uv sync` installs the
-  `lancedb` project itself) uses `lto = "fat"` + `opt-level = 3`, needs ~11 GB
-  RAM, and takes ~20 min cold on this VM. To avoid it, the update script uses
-  `uv sync --no-install-project --inexact` (the `--inexact` flag is required so
-  the sync does not uninstall the editable extension). Prefer the debug
-  `maturin develop` (~6 min cold, seconds when warm) for iteration.
-* `cargo check` only produces metadata, so the first `cargo run --example ...`
-  or `cargo test` after a check triggers a large codegen/link compile.
-* Node binding rebuild: `cd nodejs && pnpm build` (napi debug build + `tsc`).
-  The native addon lands at `nodejs/dist/lancedb.linux-x64-gnu.node`.
-
-Verified working (local backend, no cloud credentials needed):
-
-* Rust: `cargo check/clippy --features remote --tests --examples`,
-  `cargo test --features remote -p lancedb --lib`, `cargo run --features remote
-  --example simple`.
-* Python: `cd python && uv run --extra tests pytest python/tests/test_table.py`,
-  `uv run --directory python --extra dev ruff check python`.
-* Node: `cd nodejs && pnpm lint`, `pnpm test __test__/connection.test.ts`.
-
-Java (`java/`) is optional; its integration tests need LanceDB Cloud
-credentials (`LANCEDB_DB`, `LANCEDB_API_KEY`) and were not set up here.
@@ -13,20 +13,20 @@ categories = ["database-implementations"]
 rust-version = "1.91.0"

 [workspace.dependencies]
-lance = { "version" = "=11.0.0-beta.2", default-features = false, "tag" = "v11.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
-lance-core = { "version" = "=11.0.0-beta.2", "tag" = "v11.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
-lance-datagen = { "version" = "=11.0.0-beta.2", "tag" = "v11.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
-lance-file = { "version" = "=11.0.0-beta.2", "tag" = "v11.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
-lance-io = { "version" = "=11.0.0-beta.2", default-features = false, "tag" = "v11.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
-lance-index = { "version" = "=11.0.0-beta.2", "tag" = "v11.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
-lance-linalg = { "version" = "=11.0.0-beta.2", "tag" = "v11.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
-lance-namespace = { "version" = "=11.0.0-beta.2", "tag" = "v11.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
-lance-namespace-impls = { "version" = "=11.0.0-beta.2", default-features = false, "tag" = "v11.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
-lance-table = { "version" = "=11.0.0-beta.2", "tag" = "v11.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
-lance-testing = { "version" = "=11.0.0-beta.2", "tag" = "v11.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
-lance-datafusion = { "version" = "=11.0.0-beta.2", "tag" = "v11.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
-lance-encoding = { "version" = "=11.0.0-beta.2", "tag" = "v11.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
-lance-arrow = { "version" = "=11.0.0-beta.2", "tag" = "v11.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
+lance = { "version" = "=10.0.0-beta.5", default-features = false, "tag" = "v10.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
+lance-core = { "version" = "=10.0.0-beta.5", "tag" = "v10.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
+lance-datagen = { "version" = "=10.0.0-beta.5", "tag" = "v10.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
+lance-file = { "version" = "=10.0.0-beta.5", "tag" = "v10.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
+lance-io = { "version" = "=10.0.0-beta.5", default-features = false, "tag" = "v10.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
+lance-index = { "version" = "=10.0.0-beta.5", "tag" = "v10.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
+lance-linalg = { "version" = "=10.0.0-beta.5", "tag" = "v10.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
+lance-namespace = { "version" = "=10.0.0-beta.5", "tag" = "v10.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
+lance-namespace-impls = { "version" = "=10.0.0-beta.5", default-features = false, "tag" = "v10.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
+lance-table = { "version" = "=10.0.0-beta.5", "tag" = "v10.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
+lance-testing = { "version" = "=10.0.0-beta.5", "tag" = "v10.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
+lance-datafusion = { "version" = "=10.0.0-beta.5", "tag" = "v10.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
+lance-encoding = { "version" = "=10.0.0-beta.5", "tag" = "v10.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
+lance-arrow = { "version" = "=10.0.0-beta.5", "tag" = "v10.0.0-beta.5", "git" = "https://github.com/lance-format/lance.git" }
 ahash = "0.8"
 # Note that this one does not include pyarrow
 arrow = { version = "58.0.0", optional = false }
@@ -51,11 +51,6 @@ plugins:
          paths: [../python/python]
          options:
            docstring_style: numpy
-            docstring_options:
-              # Attributes documented in a `Parameters` section, and pydantic
-              # dataclasses whose `__init__` griffe cannot see statically, both
-              # trip this check. It reports nothing actionable here.
-              warn_unknown_params: false
            heading_level: 3
            show_signature_annotations: true
            show_root_heading: true
@@ -453,16 +453,6 @@ paths:
                    The metric type to use for the index. l2, Cosine, Dot are supported.
                index_type:
                  type: string
-                custom_stop_words:
-                  type: [array, "null"]
-                  items:
-                    type: string
-                  description: |
-                    The custom stop-word list for an FTS index. A non-null
-                    array replaces the language's built-in stop-word list and is only
-                    applied when remove_stop_words is enabled. Null uses the built-in
-                    language list, while an empty array explicitly replaces it with no
-                    stop words.
      responses:
        "200":
          description: Index successfully created
@@ -520,4 +510,4 @@ paths:
        "401":
          $ref: "#/components/responses/unauthorized"
        "404":
-          $ref: "#/components/responses/not_found"
+          $ref: "#/components/responses/not_found"
@@ -1,7 +1,7 @@
 # Contributing to LanceDB Typescript

 This document outlines the process for contributing to LanceDB Typescript.
-For general contribution guidelines, see [CONTRIBUTING.md](https://github.com/lancedb/lancedb/blob/main/CONTRIBUTING.md).
+For general contribution guidelines, see [CONTRIBUTING.md](../CONTRIBUTING.md).

 ## Project layout

@@ -25,27 +25,6 @@ the underlying connection has been closed.

 ## Methods

-### cancelJob()
-
-```ts
-abstract cancelJob(jobId): Promise<boolean>
-```
-
-Request cancellation of a server-side job by id.
-
-Resolves to true if the server accepted the cancellation, false if no
-such job exists. Cancelling an already-terminal job is a no-op success.
-
-#### Parameters
-
-* **jobId**: `string`
-
-#### Returns
-
-`Promise`&lt;`boolean`&gt;
-
-***
-
 ### cloneTable()

 ```ts
@@ -386,26 +365,6 @@ Drop an existing table.

 ***

-### getJob()
-
-```ts
-abstract getJob(jobId): Promise<null | JobDescription>
-```
-
-Describe a single server-side job by id.
-
-Resolves to `null` when the server has no such job.
-
-#### Parameters
-
-* **jobId**: `string`
-
-#### Returns
-
-`Promise`&lt;`null` \| [`JobDescription`](../interfaces/JobDescription.md)&gt;
-
-***
-
 ### isOpen()

 ```ts
@@ -420,62 +379,6 @@ Return true if the connection has not been closed

 ***

-### job()
-
-```ts
-abstract job(jobId): Job
-```
-
-A [Job](Job.md) handle for a server-side job by id.
-
-The handle is constructed without a server round trip; an unknown id
-surfaces when the handle is used. Dropping the handle has no effect on
-the job itself.
-
-#### Parameters
-
-* **jobId**: `string`
-
-#### Returns
-
-[`Job`](Job.md)
-
-***
-
-### jobHistory()
-
-```ts
-abstract jobHistory(jobId?): Promise<Table<any>>
-```
-
-The lifecycle event history of a server-side job, as an Arrow table.
-
-Lists history across all jobs when `jobId` is omitted.
-
-#### Parameters
-
-* **jobId?**: `string`
-
-#### Returns
-
-`Promise`&lt;`Table`&lt;`any`&gt;&gt;
-
-***
-
-### listJobs()
-
-```ts
-abstract listJobs(): Promise<JobInfo[]>
-```
-
-List server-side jobs across the database's tables.
-
-#### Returns
-
-`Promise`&lt;[`JobInfo`](../interfaces/JobInfo.md)[]&gt;
-
-***
-
 ### listNamespaces()

 ```ts
@@ -1,83 +0,0 @@
-[**@lancedb/lancedb**](../README.md) • **Docs**
-
-***
-
-[@lancedb/lancedb](../globals.md) / Job
-
-# Class: Job
-
-A handle to an operation that may still be running.
-
-## Constructors
-
-### new Job()
-
-```ts
-new Job(): Job
-```
-
-#### Returns
-
-[`Job`](Job.md)
-
-## Accessors
-
-### id
-
-```ts
-get id(): null | string
-```
-
-Identifies the operation on the server that is running it. Operations
-that run in this process have no server id. The value is opaque.
-
-#### Returns
-
-`null` \| `string`
-
-## Methods
-
-### cancel()
-
-```ts
-cancel(): Promise<void>
-```
-
-Request cancellation. Cancelling a finished operation is a no-op.
-
-#### Returns
-
-`Promise`&lt;`void`&gt;
-
-***
-
-### status()
-
-```ts
-status(): Promise<string>
-```
-
-The operation's current lifecycle state: "running", "finished",
-"failed", or "cancelled".
-
-A point snapshot; unlike [Job.wait](Job.md#wait) it does not block or reject
-on a terminal failure state. States a newer server reports that this
-client version does not know pass through as-is.
-
-#### Returns
-
-`Promise`&lt;`string`&gt;
-
-***
-
-### wait()
-
-```ts
-wait(): Promise<void>
-```
-
-Wait until the operation reaches a terminal state.
-
-#### Returns
-
-`Promise`&lt;`void`&gt;
@@ -295,29 +295,6 @@ await table.createIndex("my_float_col");

 ***

-### createIndexAsync()
-
-```ts
-abstract createIndexAsync(column, options?): Promise<Job>
-```
-
-Create an index, returning a handle to the indexing job.
-
-The job may already be complete when returned; callers must not assume
-the index exists until [Job.wait](Job.md#wait) resolves.
-
-#### Parameters
-
-* **column**: `string`
-
-* **options?**: `Partial`&lt;[`IndexOptions`](../interfaces/IndexOptions.md)&gt;
-
-#### Returns
-
-`Promise`&lt;[`Job`](Job.md)&gt;
-
-***
-
 ### currentBranch()

 ```ts
@@ -25,7 +25,6 @@
 - [Connection](classes/Connection.md)
 - [HeaderProvider](classes/HeaderProvider.md)
 - [Index](classes/Index.md)
- [Job](classes/Job.md)
 - [MakeArrowTableOptions](classes/MakeArrowTableOptions.md)
 - [MatchQuery](classes/MatchQuery.md)
 - [MergeInsertBuilder](classes/MergeInsertBuilder.md)
@@ -89,9 +88,6 @@
 - [IvfFlatOptions](interfaces/IvfFlatOptions.md)
 - [IvfPqOptions](interfaces/IvfPqOptions.md)
 - [IvfRqOptions](interfaces/IvfRqOptions.md)
- [JobDescription](interfaces/JobDescription.md)
- [JobFailureInfo](interfaces/JobFailureInfo.md)
- [JobInfo](interfaces/JobInfo.md)
 - [ListNamespacesOptions](interfaces/ListNamespacesOptions.md)
 - [ListNamespacesResponse](interfaces/ListNamespacesResponse.md)
 - [LsmWriteSpec](interfaces/LsmWriteSpec.md)
@@ -56,21 +56,6 @@ the experimental FTS V3 format and may introduce breaking changes.

 ***

-### customStopWords?
-
-```ts
-optional customStopWords: string[];
-```
-
-Custom stop words that replace the built-in list for `language`.
-
-This option only affects tokenization when `removeStopWords` is true.
-
-`undefined` keeps the built-in language list. An empty array explicitly
-replaces it with no stop words.
-
-***
-
 ### language?

 ```ts
@@ -1,66 +0,0 @@
-[**@lancedb/lancedb**](../README.md) • **Docs**
-
-***
-
-[@lancedb/lancedb](../globals.md) / JobDescription
-
-# Interface: JobDescription
-
-A described job from `Connection.getJob`.
-
-## Properties
-
-### creationMs
-
-```ts
-creationMs: number;
-```
-
-When the job was created, in milliseconds since the epoch.
-
-***
-
-### failure?
-
-```ts
-optional failure: JobFailureInfo;
-```
-
-Why the job failed, when the job is failed and the server reports a
-reason.
-
-***
-
-### jobId
-
-```ts
-jobId: string;
-```
-
-***
-
-### jobType
-
-```ts
-jobType: string;
-```
-
-***
-
-### specJson?
-
-```ts
-optional specJson: string;
-```
-
-The job-type-specific specification as a JSON string, when present.
-
-***
-
-### state
-
-```ts
-state: string;
-```
-
-Lifecycle state: "running", "finished", "failed", or "cancelled".
@@ -1,33 +0,0 @@
-[**@lancedb/lancedb**](../README.md) • **Docs**
-
-***
-
-[@lancedb/lancedb](../globals.md) / JobFailureInfo
-
-# Interface: JobFailureInfo
-
-The server's account of why a job failed.
-
-## Properties
-
-### message?
-
-```ts
-optional message: string;
-```
-
-***
-
-### phase?
-
-```ts
-optional phase: string;
-```
-
-***
-
-### retryable?
-
-```ts
-optional retryable: boolean;
-```
@@ -1,58 +0,0 @@
-[**@lancedb/lancedb**](../README.md) • **Docs**
-
-***
-
-[@lancedb/lancedb](../globals.md) / JobInfo
-
-# Interface: JobInfo
-
-A row from `Connection.listJobs`: one server-side job.
-
-## Properties
-
-### createdAtMillis
-
-```ts
-createdAtMillis: number;
-```
-
-When the job was created, in milliseconds since the epoch.
-
-***
-
-### jobId
-
-```ts
-jobId: string;
-```
-
-The job id -- what `Connection.getJob` and `Connection.cancelJob`
-accept.
-
-***
-
-### jobType
-
-```ts
-jobType: string;
-```
-
-***
-
-### state
-
-```ts
-state: string;
-```
-
-Lifecycle state: "running", "finished", "failed", or "cancelled".
-
-***
-
-### table
-
-```ts
-table: string;
-```
-
-The table the job runs against, without URI or namespace.
@@ -30,21 +30,6 @@ The tokenizer to use. The default is "simple".

 ***

-### customStopWords?
-
-```ts
-optional customStopWords: string[];
-```
-
-Custom stop words that replace the built-in list for `language`.
-
-This option only affects tokenization when `removeStopWords` is true.
-
-`undefined` keeps the built-in language list. An empty array explicitly
-replaces it with no stop words.
-
-***
-
 ### language?

 ```ts
@@ -26,18 +26,6 @@ is also an [asynchronous API client](#connections-asynchronous).

 ::: lancedb.db.DBConnection

-::: lancedb.Session
-
-## Namespaces (Synchronous)
-
-A namespace-backed connection resolves tables through a
-[Lance namespace](https://lancedb.github.io/lance-namespace/) service instead of
-listing a storage directory.
-
-::: lancedb.connect_namespace
-
-::: lancedb.namespace.LanceNamespaceDBConnection
-
 ## Tables (Synchronous)

 ::: lancedb.table.Table
@@ -46,12 +34,8 @@ listing a storage directory.

 ::: lancedb.table.FragmentSummaryStats

-::: lancedb.table.TableStatistics
-
 ::: lancedb.table.Tags

-::: lancedb.table.Branches
-
 ## Expressions

 Type-safe expression builder for filters and projections. Use these instead
@@ -78,46 +62,29 @@ of raw SQL strings with [where][lancedb.query.LanceQueryBuilder.where] and

 ::: lancedb.query.LanceHybridQueryBuilder

-::: lancedb.query.LanceEmptyQueryBuilder
-
-::: lancedb.query.LanceTakeQueryBuilder
-
-## Full text queries
-
-Structured full text queries can be passed to
-[Table.search][lancedb.table.Table.search] or
-[AsyncTable.search][lancedb.table.AsyncTable.search] in place of a query string,
-and combined with [BooleanQuery][lancedb.query.BooleanQuery].
-
-::: lancedb.query.FullTextQuery
-
-::: lancedb.query.MatchQuery
-
-::: lancedb.query.PhraseQuery
-
-::: lancedb.query.BoostQuery
-
-::: lancedb.query.MultiMatchQuery
-
-::: lancedb.query.BooleanQuery
-
-::: lancedb.query.FullTextOperator
-
-::: lancedb.query.Occur
-
 ## Embeddings

-::: lancedb.embeddings
-    options:
-      show_root_heading: false
-      show_root_toc_entry: false
+::: lancedb.embeddings.registry.EmbeddingFunctionRegistry
+
+::: lancedb.embeddings.base.EmbeddingFunctionConfig
+
+::: lancedb.embeddings.base.EmbeddingFunction
+
+::: lancedb.embeddings.base.TextEmbeddingFunction
+
+::: lancedb.embeddings.sentence_transformers.SentenceTransformerEmbeddings
+
+::: lancedb.embeddings.openai.OpenAIEmbeddings
+
+::: lancedb.embeddings.open_clip.OpenClipEmbeddings

 ## Remote configuration

-::: lancedb.remote
-    options:
-      show_root_heading: false
-      show_root_toc_entry: false
+::: lancedb.remote.ClientConfig
+
+::: lancedb.remote.TimeoutConfig
+
+::: lancedb.remote.RetryConfig

 ## Context

@@ -127,50 +94,11 @@ and combined with [BooleanQuery][lancedb.query.BooleanQuery].

 ## Full text search

-Pass `custom_stop_words` to [lancedb.index.FTS][]:
+Use [lancedb.table.Table.create_fts_index][] for the synchronous API or
+[lancedb.table.AsyncTable.create_index][] with [lancedb.index.FTS][] for the
+asynchronous API.

-```python
-from lancedb.index import FTS
-
-table.create_index(
-    "text",
-    config=FTS(remove_stop_words=True, custom_stop_words=["acme", "internal"]),
-)
-```
-
-The list replaces the built-in stop words and is used only when
-`remove_stop_words=True`:
-
- `custom_stop_words=None` uses the built-in list for `language`.
- `custom_stop_words=[]` removes no words.
- Values are passed through without trimming, lowercasing, or other rewriting.
-
-The same option is available on `lancedb.tokenize(...)` and the deprecated
-[lancedb.table.Table.create_fts_index][] compatibility helper:
-
-```python
-import lancedb
-
-tokens = list(lancedb.tokenize("acme makes searchable data",
-                               custom_stop_words=["acme"]))
-```
-
-::: lancedb.tokenize
-
-::: lancedb.FtsToken
-
-## Blobs
-
-Blob columns store large binary values out of line so they can be read lazily
-instead of being materialized with the rest of the row.
-
-::: lancedb.blob
-
-::: lancedb.BlobType
-
-::: lancedb._blob.BlobFile
-    options:
-      show_root_full_path: false
+::: lancedb.index.FTS

 ## Utilities

@@ -178,14 +106,6 @@ instead of being materialized with the rest of the row.

 ::: lancedb.merge.LanceMergeInsertBuilder

-::: lancedb.otel.instrument_lancedb_metrics
-
-## Exceptions
-
-::: lancedb.exceptions.MissingValueError
-
-::: lancedb.exceptions.MissingColumnError
-
 ## Integrations

 ## Pydantic
@@ -194,30 +114,19 @@ instead of being materialized with the rest of the row.

 ::: lancedb.pydantic.vector

-::: lancedb.pydantic.Vector
-
-::: lancedb.pydantic.MultiVector
-
 ::: lancedb.pydantic.LanceModel

-## PyTorch
-
-::: lancedb.streaming.StreamingDataset
-
-::: lancedb.permutation.permutation_builder
-
-::: lancedb.permutation.PermutationBuilder
-
-::: lancedb.permutation.Permutation
-
-::: lancedb.permutation.Transforms
-
 ## Reranking

-::: lancedb.rerankers
-    options:
-      show_root_heading: false
-      show_root_toc_entry: false
+::: lancedb.rerankers.linear_combination.LinearCombinationReranker
+
+::: lancedb.rerankers.cohere.CohereReranker
+
+::: lancedb.rerankers.colbert.ColbertReranker
+
+::: lancedb.rerankers.cross_encoder.CrossEncoderReranker
+
+::: lancedb.rerankers.openai.OpenaiReranker

 ## Connections (Asynchronous)

@@ -228,12 +137,6 @@ can be used to create, list, or open tables.

 ::: lancedb.db.AsyncConnection

-## Namespaces (Asynchronous)
-
-::: lancedb.connect_namespace_async
-
-::: lancedb.namespace.AsyncLanceNamespaceDBConnection
-
 ## Tables (Asynchronous)

 Table hold your actual data as a collection of records / rows.
@@ -242,20 +145,32 @@ Table hold your actual data as a collection of records / rows.

 ::: lancedb.table.AsyncTags

-::: lancedb.table.AsyncBranches
-
 ## Indices (Asynchronous)

 Indices can be created on a table to speed up queries. This section
 lists the indices that LanceDb supports.

-::: lancedb.index
-    options:
-      show_root_heading: false
-      show_root_toc_entry: false
-      # `lang_mapping` is defined in the module rather than imported, so it is
-      # picked up despite not being in `__all__`. It is an internal lookup table.
-      filters: ["!^_", "!^lang_mapping$"]
+::: lancedb.index.BTree
+
+::: lancedb.index.Bitmap
+
+::: lancedb.index.LabelList
+
+::: lancedb.index.FTS
+
+::: lancedb.index.IvfPq
+
+::: lancedb.index.HnswPq
+
+::: lancedb.index.HnswSq
+
+::: lancedb.index.IvfFlat
+
+::: lancedb.index.IvfSq
+
+::: lancedb.index.IvfRq
+
+::: lancedb.index.HnswFlat

 ::: lancedb.table.IndexStatistics

@@ -283,7 +198,3 @@ rows nearest to a query vector and can be created with the
 ::: lancedb.query.AsyncHybridQuery
    options:
      inherited_members: true
-
-::: lancedb.query.AsyncTakeQuery
-    options:
-      inherited_members: true
@@ -28,7 +28,7 @@
    <properties>
        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
        <arrow.version>15.0.0</arrow.version>
-        <lance-core.version>11.0.0-beta.2</lance-core.version>
+        <lance-core.version>10.0.0-beta.5</lance-core.version>
        <spotless.skip>false</spotless.skip>
        <spotless.version>2.30.0</spotless.version>
        <spotless.java.googlejavaformat.version>1.7</spotless.java.googlejavaformat.version>
@@ -1,7 +1,7 @@
 # Contributing to LanceDB Typescript

 This document outlines the process for contributing to LanceDB Typescript.
-For general contribution guidelines, see [CONTRIBUTING.md](https://github.com/lancedb/lancedb/blob/main/CONTRIBUTING.md).
+For general contribution guidelines, see [CONTRIBUTING.md](../CONTRIBUTING.md).

 ## Project layout

@@ -197,35 +197,6 @@ describe.each([arrow15, arrow16, arrow17, arrow18])(
        expect(table.getChild("d")?.toJSON()).toEqual([9n, 10n, null]);
      });

-      it("will use a provided FixedSizeList schema with typed array values", function () {
-        const schema = new Schema([
-          new Field("text", new Utf8(), false),
-          new Field(
-            "vector",
-            new FixedSizeList(3, new Field("item", new Float32(), false)),
-            false,
-          ),
-        ]);
-
-        const table = makeArrowTable(
-          [
-            {
-              text: "foo",
-              vector: new Float32Array([1, 2, 3]),
-            },
-          ],
-          { schema },
-        );
-
-        expect(table.getChild("text")?.toJSON()).toEqual(["foo"]);
-        expect(
-          table
-            .getChild("vector")
-            ?.toJSON()
-            .map((value) => value.toJSON()),
-        ).toEqual([[1, 2, 3]]);
-      });
-
      it("will assume the column `vector` is FixedSizeList<Float32> by default", async function () {
        const schema = new Schema([
          new Field("a", new Float(Precision.DOUBLE), true),
@@ -170,38 +170,6 @@ describe("remote connection", () => {
    );
  });

-  it("surfaces JSON server errors from remote table operations", async () => {
-    await withMockDatabase(
-      (req, res) => {
-        const path = req.url ?? "";
-        if (path.endsWith("/describe/")) {
-          res.writeHead(200, { "Content-Type": "application/json" }).end(
-            JSON.stringify({
-              name: "broken_table",
-              version: 1,
-              schema: { fields: [] },
-            }),
-          );
-          return;
-        }
-
-        if (path.endsWith("/count_rows/")) {
-          res
-            .writeHead(400, { "Content-Type": "application/json" })
-            .end(JSON.stringify({ error: "count rows failed" }));
-          return;
-        }
-
-        res.writeHead(404).end();
-      },
-      async (db) => {
-        const table = await db.openTable("broken_table");
-
-        await expect(table.countRows()).rejects.toThrow("count rows failed");
-      },
-    );
-  });
-
  it("should pass on requested extra headers", async () => {
    await withMockDatabase(
      (req, res) => {
@@ -258,7 +226,7 @@ describe("remote connection", () => {
    );
  });

-  it("sends FTS options to remote tables", async () => {
+  it("sends the FTS posting block size to remote tables", async () => {
    let createIndexBody: Record<string, unknown> | undefined;

    await withMockDatabase(
@@ -296,11 +264,7 @@ describe("remote connection", () => {
      async (db) => {
        const table = await db.openTable("t");
        await table.createIndex("text", {
-          config: Index.fts({
-            blockSize: 256,
-            removeStopWords: true,
-            customStopWords: ["the"],
-          }),
+          config: Index.fts({ blockSize: 256 }),
        });
      },
    );
@@ -308,7 +272,6 @@ describe("remote connection", () => {
    expect(createIndexBody?.["column"]).toBe("text");
    expect(createIndexBody?.["index_type"]).toBe("FTS");
    expect(createIndexBody?.["block_size"]).toBe(256);
-    expect(createIndexBody?.["custom_stop_words"]).toEqual(["the"]);
  });

  it("diffs and merges remote branches", async () => {
@@ -909,96 +872,3 @@ describe("remote connection", () => {
    });
  });
 });
-
-describe("remote connection jobs surface", () => {
-  it("lists, describes, cancels, and reads history", async () => {
-    const { tableFromArrays, tableToIPC } = await import("apache-arrow");
-    const eventsTable = tableFromArrays({ state: ["created", "succeeded"] });
-    const eventsBody = Buffer.from(tableToIPC(eventsTable, "stream"));
-
-    await withMockDatabase(
-      (req, res) => {
-        let body = "";
-        req.on("data", (chunk) => {
-          body += chunk;
-        });
-        req.on("end", () => {
-          const payload = body.length > 0 ? JSON.parse(body) : {};
-          if (req.url === "/v1/jobs/list") {
-            if (payload["page_token"] === undefined) {
-              res
-                .writeHead(200, { "Content-Type": "application/json" })
-                .end(
-                  '{"jobs": [{"job_id": "job-1", "table": "t1", ' +
-                    '"job_type": "create_index", "state": "in_progress", ' +
-                    '"created_at_millis": 1000}], "page_token": "next"}',
-                );
-            } else {
-              res
-                .writeHead(200, { "Content-Type": "application/json" })
-                .end(
-                  '{"jobs": [{"job_id": "job-2", "table": "t2", ' +
-                    '"job_type": "create_index", "state": "succeeded", ' +
-                    '"created_at_millis": 2000}]}',
-                );
-            }
-          } else if (req.url === "/v1/jobs/describe") {
-            if (payload["job_id"] !== "job-1") {
-              res.writeHead(404).end("no such job");
-              return;
-            }
-            res
-              .writeHead(200, { "Content-Type": "application/json" })
-              .end(
-                '{"job_id": "job-1", "job_type": "create_index", ' +
-                  '"job_state": "FAILED", "creation_ms": 1000, ' +
-                  '"spec": {"column": "vec"}, "failure": {"phase": "execute", ' +
-                  '"message": "worker died", "retryable": true}}',
-              );
-          } else if (req.url === "/v1/jobs/cancel") {
-            if (payload["job_id"] !== "job-1") {
-              res.writeHead(404).end("no such job");
-              return;
-            }
-            res
-              .writeHead(200, { "Content-Type": "application/json" })
-              .end('{"job_id": "job-1"}');
-          } else if (req.url === "/v1/jobs/query_events") {
-            res
-              .writeHead(200, {
-                "Content-Type": "application/vnd.apache.arrow.stream",
-              })
-              .end(eventsBody);
-          } else {
-            res.writeHead(404).end();
-          }
-        });
-      },
-      async (db) => {
-        const jobs = await db.listJobs();
-        expect(jobs.map((job) => job.jobId)).toEqual(["job-1", "job-2"]);
-        expect(jobs[0].state).toEqual("running");
-        expect(jobs[1].state).toEqual("finished");
-
-        const description = await db.getJob("job-1");
-        expect(description?.state).toEqual("failed");
-        expect(JSON.parse(description?.specJson ?? "")).toEqual({
-          column: "vec",
-        });
-        expect(description?.failure?.message).toEqual("worker died");
-        expect(await db.getJob("missing")).toBeNull();
-
-        expect(await db.cancelJob("job-1")).toBe(true);
-        expect(await db.cancelJob("missing")).toBe(false);
-
-        const history = await db.jobHistory("job-1");
-        expect(history.numRows).toEqual(2);
-
-        const job = db.job("job-1");
-        expect(job.id).toEqual("job-1");
-        expect(await job.status()).toEqual("failed");
-        await expect(job.wait()).rejects.toThrow("worker died");
-      },
-    );
-  });
-});
@@ -86,44 +86,6 @@ describe.each([arrow15, arrow16, arrow17, arrow18])(
      await expect(table.countRows()).resolves.toBe(3);
    });

-    it("should support a foreign Float64 vector schema end to end", async () => {
-      const conn = await connect(tmpDir.name);
-      const schema = new arrow.Schema([
-        new arrow.Field("resource_id", new arrow.Int32(), false),
-        new arrow.Field(
-          "vector",
-          new arrow.FixedSizeList(
-            3,
-            new arrow.Field("value", new arrow.Float64(), true),
-          ),
-          false,
-        ),
-      ]);
-      const data = [
-        {
-          // biome-ignore lint/style/useNamingConvention: matches the reported schema
-          resource_id: 0,
-          vector: [0.1, 0.1, 0.1],
-        },
-      ];
-
-      const resources = await conn.createTable("resources", data, { schema });
-
-      const existing = await resources
-        .query()
-        .where("resource_id = 0")
-        .limit(1)
-        .toArray();
-      expect(existing).toHaveLength(1);
-
-      const matched = await resources
-        .search(Float64Array.from(data[0].vector))
-        .limit(1)
-        .toArray();
-      expect(matched).toHaveLength(1);
-      expect(matched[0]["resource_id"]).toBe(0);
-    });
-
    it("should support branches", async () => {
      await table.add([{ id: 1 }]);
      expect(await table.countRows()).toBe(1);
@@ -889,11 +851,7 @@ describe("When creating an index", () => {
  afterEach(() => tmpDir.removeCallback());

  it("should create a vector index on vector columns", async () => {
-    const job = await tbl.createIndexAsync("vec");
-    expect(job.id).toBeNull();
-    await job.wait();
-    // Cancelling a job that already finished succeeds and does nothing.
-    await job.cancel();
+    await tbl.createIndex("vec");

    // check index directory
    const indexDir = path.join(tmpDir.name, "test.lance", "_indices");
@@ -2811,15 +2769,6 @@ describe.each([arrow15, arrow16, arrow17, arrow18])(
  },
 );

-test("tokenize supports custom stop words", async () => {
-  const tokens = await tokenize("the lance data", {
-    stem: false,
-    removeStopWords: true,
-    customStopWords: ["lance"],
-  });
-  expect(tokens.map((token) => token.text)).toEqual(["the", "data"]);
-});
-
 describe("when calling explainPlan", () => {
  let tmpDir: tmp.DirResult;
  let table: Table;
@@ -29,14 +29,8 @@ test("full text search", async () => {
    const tbl = await db.createTable("myVectors", data, { mode: "overwrite" });

    await tbl.createIndex("doc", {
-      config: lancedb.Index.fts({
-        stem: false,
-        removeStopWords: true,
-        customStopWords: ["banana"],
-      }),
+      config: lancedb.Index.fts(),
    });
-    const tokens = await tbl.tokenize("apple banana", { column: "doc" });
-    expect(tokens.map((token) => token.text)).toEqual(["apple"]);

    // --8<-- [start:full_text_search]
    const result = await tbl
@@ -1,7 +1,6 @@
 // SPDX-License-Identifier: Apache-2.0
 // SPDX-FileCopyrightText: Copyright The LanceDB Authors

-import { tableFromIPC } from "apache-arrow";
 import {
  Data,
  SchemaLike,
@@ -21,9 +20,6 @@ import type {
  CreateNamespaceResponse,
  DescribeNamespaceResponse,
  DropNamespaceResponse,
-  Job,
-  JobDescription,
-  JobInfo,
  ListNamespacesResponse,
 } from "./native";
 export type {
@@ -440,40 +436,6 @@ export abstract class Connection {
    newName: string,
    options?: RenameTableOptions,
  ): Promise<void>;
-
-  /**
-   * A {@link Job} handle for a server-side job by id.
-   *
-   * The handle is constructed without a server round trip; an unknown id
-   * surfaces when the handle is used. Dropping the handle has no effect on
-   * the job itself.
-   */
-  abstract job(jobId: string): Job;
-
-  /** List server-side jobs across the database's tables. */
-  abstract listJobs(): Promise<JobInfo[]>;
-
-  /**
-   * Describe a single server-side job by id.
-   *
-   * Resolves to `null` when the server has no such job.
-   */
-  abstract getJob(jobId: string): Promise<JobDescription | null>;
-
-  /**
-   * Request cancellation of a server-side job by id.
-   *
-   * Resolves to true if the server accepted the cancellation, false if no
-   * such job exists. Cancelling an already-terminal job is a no-op success.
-   */
-  abstract cancelJob(jobId: string): Promise<boolean>;
-
-  /**
-   * The lifecycle event history of a server-side job, as an Arrow table.
-   *
-   * Lists history across all jobs when `jobId` is omitted.
-   */
-  abstract jobHistory(jobId?: string): Promise<ArrowTable>;
 }

 /** @hideconstructor */
@@ -760,30 +722,6 @@ export class LocalConnection extends Connection {
      options?.newNamespacePath,
    );
  }
-
-  job(jobId: string): Job {
-    return this.inner.job(jobId);
-  }
-
-  async listJobs(): Promise<JobInfo[]> {
-    return this.inner.listJobs();
-  }
-
-  async getJob(jobId: string): Promise<JobDescription | null> {
-    return this.inner.getJob(jobId);
-  }
-
-  async cancelJob(jobId: string): Promise<boolean> {
-    return this.inner.cancelJob(jobId);
-  }
-
-  async jobHistory(jobId?: string): Promise<ArrowTable> {
-    const buf = await this.inner.jobHistory(jobId);
-    if (buf.length === 0) {
-      return new ArrowTable();
-    }
-    return tableFromIPC(buf);
-  }
 }

 /**
@@ -85,13 +85,7 @@ export {
  RenameTableOptions,
 } from "./connection";

-export {
-  Job,
-  JobDescription,
-  JobFailureInfo,
-  JobInfo,
-  Session,
-} from "./native.js";
+export { Session } from "./native.js";

 export {
  ExecutableQuery,
@@ -200,16 +194,6 @@ export interface TokenizeOptions {
  /** Whether to remove stop words. */
  removeStopWords?: boolean;

-  /**
-   * Custom stop words that replace the built-in list for `language`.
-   *
-   * This option only affects tokenization when `removeStopWords` is true.
-   *
-   * `undefined` keeps the built-in language list. An empty array explicitly
-   * replaces it with no stop words.
-   */
-  customStopWords?: string[];
-
  /** Whether to fold ASCII characters. */
  asciiFolding?: boolean;

@@ -241,7 +225,6 @@ export async function tokenize(
    options?.lowercase,
    options?.stem,
    options?.removeStopWords,
-    options?.customStopWords,
    options?.asciiFolding,
    options?.ngramMinLength,
    options?.ngramMaxLength,
@@ -553,16 +553,6 @@ export interface FtsOptions {
   */
  removeStopWords?: boolean;

-  /**
-   * Custom stop words that replace the built-in list for `language`.
-   *
-   * This option only affects tokenization when `removeStopWords` is true.
-   *
-   * `undefined` keeps the built-in language list. An empty array explicitly
-   * replaces it with no stop words.
-   */
-  customStopWords?: string[];
-
  /**
   * whether to remove punctuation
   */
@@ -765,7 +755,6 @@ export class Index {
        options?.lowercase,
        options?.stem,
        options?.removeStopWords,
-        options?.customStopWords,
        options?.asciiFolding,
        options?.ngramMinLength,
        options?.ngramMaxLength,
@@ -30,7 +30,6 @@ import {
  DropColumnsResult,
  IndexConfig,
  IndexStatistics,
-  Job,
  Branches as NativeBranches,
  OptimizeStats,
  TableStatistics,
@@ -359,17 +358,6 @@ export abstract class Table {
    options?: Partial<IndexOptions>,
  ): Promise<void>;

-  /**
-   * Create an index, returning a handle to the indexing job.
-   *
-   * The job may already be complete when returned; callers must not assume
-   * the index exists until {@link Job.wait} resolves.
-   */
-  abstract createIndexAsync(
-    column: string,
-    options?: Partial<IndexOptions>,
-  ): Promise<Job>;
-
  /**
   * Drop an index from the table.
   *
@@ -952,22 +940,6 @@ export class LocalTable extends Table {
    );
  }

-  async createIndexAsync(
-    column: string,
-    options?: Partial<IndexOptions>,
-  ): Promise<Job> {
-    // biome-ignore lint/suspicious/noExplicitAny: skip
-    const nativeIndex = (options?.config as any)?.inner;
-    return await this.inner.createIndexAsync(
-      nativeIndex,
-      column,
-      options?.replace,
-      options?.waitTimeoutSeconds,
-      options?.name,
-      options?.train,
-    );
-  }
-
  async dropIndex(name: string): Promise<void> {
    await this.inner.dropIndex(name);
  }
@@ -1,12 +1,12 @@
 {
  "name": "@lancedb/lancedb",
-  "version": "0.37.1-beta.0",
+  "version": "0.37.0-beta.0",
  "lockfileVersion": 3,
  "requires": true,
  "packages": {
    "": {
      "name": "@lancedb/lancedb",
-      "version": "0.37.1-beta.0",
+      "version": "0.37.0-beta.0",
      "cpu": [
        "x64",
        "arm64"
@@ -340,69 +340,6 @@ impl Connection {
        self.get_inner()?.drop_all_tables(&ns).await.default_error()
    }

-    /// A `Job` handle for a server-side job by id.
-    ///
-    /// The handle is constructed without a server round trip; an unknown id
-    /// surfaces when the handle is used.
-    #[napi]
-    pub fn job(&self, job_id: String) -> napi::Result<crate::job::Job> {
-        let job = self.get_inner()?.job(job_id).default_error()?;
-        Ok(crate::job::Job::new(job))
-    }
-
-    /// List server-side jobs across the database's tables.
-    #[napi(catch_unwind)]
-    pub async fn list_jobs(&self) -> napi::Result<Vec<crate::job::JobInfo>> {
-        let jobs = self.get_inner()?.list_jobs().await.default_error()?;
-        Ok(jobs.into_iter().map(Into::into).collect())
-    }
-
-    /// Describe a single server-side job by id. `null` when the server has
-    /// no such job.
-    #[napi(catch_unwind)]
-    pub async fn get_job(
-        &self,
-        job_id: String,
-    ) -> napi::Result<Option<crate::job::JobDescription>> {
-        let description = self.get_inner()?.get_job(&job_id).await.default_error()?;
-        Ok(description.map(Into::into))
-    }
-
-    /// Request cancellation of a server-side job by id. Returns true if the
-    /// server accepted the cancellation, false if no such job exists.
-    #[napi(catch_unwind)]
-    pub async fn cancel_job(&self, job_id: String) -> napi::Result<bool> {
-        self.get_inner()?.cancel_job(&job_id).await.default_error()
-    }
-
-    /// The lifecycle event history of a server-side job (all jobs when
-    /// `job_id` is null), as an Arrow IPC stream buffer. Empty when there is
-    /// no history.
-    #[napi(catch_unwind)]
-    pub async fn job_history(&self, job_id: Option<String>) -> napi::Result<Buffer> {
-        let batches = self
-            .get_inner()?
-            .job_history(job_id.as_deref())
-            .await
-            .default_error()?;
-        let Some(first) = batches.first() else {
-            return Ok(Buffer::from(Vec::<u8>::new()));
-        };
-        let mut out = Vec::new();
-        let mut writer = arrow_ipc::writer::StreamWriter::try_new(&mut out, &first.schema())
-            .map_err(|e| napi::Error::from_reason(e.to_string()))?;
-        for batch in &batches {
-            writer
-                .write(batch)
-                .map_err(|e| napi::Error::from_reason(e.to_string()))?;
-        }
-        writer
-            .finish()
-            .map_err(|e| napi::Error::from_reason(e.to_string()))?;
-        drop(writer);
-        Ok(Buffer::from(out))
-    }
-
    #[napi(catch_unwind)]
    /// Describe a namespace and return its properties.
    pub async fn describe_namespace(
@@ -43,7 +43,6 @@ pub fn tokenize(
    lower_case: Option<bool>,
    stem: Option<bool>,
    remove_stop_words: Option<bool>,
-    custom_stop_words: Option<Vec<String>>,
    ascii_folding: Option<bool>,
    ngram_min_length: Option<u32>,
    ngram_max_length: Option<u32>,
@@ -73,7 +72,6 @@ pub fn tokenize(
    if let Some(remove_stop_words) = remove_stop_words {
        opts = opts.remove_stop_words(remove_stop_words);
    }
-    opts = opts.custom_stop_words(custom_stop_words);
    if let Some(ascii_folding) = ascii_folding {
        opts = opts.ascii_folding(ascii_folding);
    }
@@ -224,7 +222,6 @@ impl Index {
        lower_case: Option<bool>,
        stem: Option<bool>,
        remove_stop_words: Option<bool>,
-        custom_stop_words: Option<Vec<String>>,
        ascii_folding: Option<bool>,
        ngram_min_length: Option<u32>,
        ngram_max_length: Option<u32>,
@@ -253,7 +250,6 @@ impl Index {
        if let Some(remove_stop_words) = remove_stop_words {
            opts = opts.remove_stop_words(remove_stop_words);
        }
-        opts = opts.custom_stop_words(custom_stop_words);
        if let Some(ascii_folding) = ascii_folding {
            opts = opts.ascii_folding(ascii_folding);
        }
@@ -1,123 +0,0 @@
-// SPDX-License-Identifier: Apache-2.0
-// SPDX-FileCopyrightText: Copyright The LanceDB Authors
-
-use std::sync::Arc;
-
-use napi_derive::napi;
-
-use crate::error::NapiErrorExt;
-
-/// A handle to an operation that may still be running.
-#[napi]
-pub struct Job {
-    inner: Arc<lancedb::Job>,
-}
-
-impl Job {
-    pub(crate) fn new(inner: lancedb::Job) -> Self {
-        Self {
-            inner: Arc::new(inner),
-        }
-    }
-}
-
-#[napi]
-impl Job {
-    /// Identifies the operation on the server that is running it. Operations
-    /// that run in this process have no server id. The value is opaque.
-    #[napi(getter)]
-    pub fn id(&self) -> Option<String> {
-        self.inner.id().map(str::to_string)
-    }
-
-    /// The operation's current lifecycle state: "running", "finished",
-    /// "failed", or "cancelled".
-    ///
-    /// A point snapshot; unlike {@link Job.wait} it does not block or reject
-    /// on a terminal failure state. States a newer server reports that this
-    /// client version does not know pass through as-is.
-    #[napi(catch_unwind)]
-    pub async fn status(&self) -> napi::Result<String> {
-        self.inner.status().await.default_error()
-    }
-
-    /// Wait until the operation reaches a terminal state.
-    #[napi(catch_unwind)]
-    pub async fn wait(&self) -> napi::Result<()> {
-        self.inner.wait().await.default_error()
-    }
-
-    /// Request cancellation. Cancelling a finished operation is a no-op.
-    #[napi(catch_unwind)]
-    pub async fn cancel(&self) -> napi::Result<()> {
-        self.inner.cancel().await.default_error()
-    }
-}
-
-/// A row from `Connection.listJobs`: one server-side job.
-#[napi(object)]
-pub struct JobInfo {
-    /// The job id -- what `Connection.getJob` and `Connection.cancelJob`
-    /// accept.
-    pub job_id: String,
-    /// The table the job runs against, without URI or namespace.
-    pub table: String,
-    pub job_type: String,
-    /// Lifecycle state: "running", "finished", "failed", or "cancelled".
-    pub state: String,
-    /// When the job was created, in milliseconds since the epoch.
-    pub created_at_millis: i64,
-}
-
-impl From<lancedb::database::JobInfo> for JobInfo {
-    fn from(info: lancedb::database::JobInfo) -> Self {
-        Self {
-            job_id: info.job_id,
-            table: info.table,
-            job_type: info.job_type,
-            state: info.state,
-            created_at_millis: info.created_at_millis,
-        }
-    }
-}
-
-/// The server's account of why a job failed.
-#[napi(object)]
-pub struct JobFailureInfo {
-    pub phase: Option<String>,
-    pub message: Option<String>,
-    pub retryable: Option<bool>,
-}
-
-/// A described job from `Connection.getJob`.
-#[napi(object)]
-pub struct JobDescription {
-    pub job_id: String,
-    pub job_type: String,
-    /// Lifecycle state: "running", "finished", "failed", or "cancelled".
-    pub state: String,
-    /// When the job was created, in milliseconds since the epoch.
-    pub creation_ms: i64,
-    /// The job-type-specific specification as a JSON string, when present.
-    pub spec_json: Option<String>,
-    /// Why the job failed, when the job is failed and the server reports a
-    /// reason.
-    pub failure: Option<JobFailureInfo>,
-}
-
-impl From<lancedb::database::JobDescription> for JobDescription {
-    fn from(description: lancedb::database::JobDescription) -> Self {
-        Self {
-            job_id: description.job_id,
-            job_type: description.job_type,
-            state: description.state,
-            creation_ms: description.creation_ms,
-            spec_json: (!description.spec.is_null()).then(|| description.spec.to_string()),
-            failure: description.failure.map(|failure| JobFailureInfo {
-                phase: failure.phase,
-                message: failure.message,
-                retryable: failure.retryable,
-            }),
-        }
-    }
-}
@@ -11,7 +11,6 @@ mod error;
 mod header;
 mod index;
 mod iterator;
-mod job;
 pub mod merge;
 pub mod otel;
 pub mod permutation;
@@ -168,39 +168,6 @@ impl Table {
        builder.execute().await.default_error()
    }

-    #[napi(catch_unwind)]
-    pub async fn create_index_async(
-        &self,
-        index: Option<&Index>,
-        column: String,
-        replace: Option<bool>,
-        wait_timeout_s: Option<i64>,
-        name: Option<String>,
-        train: Option<bool>,
-    ) -> napi::Result<crate::job::Job> {
-        let lancedb_index = if let Some(index) = index {
-            index.consume()?
-        } else {
-            lancedb::index::Index::Auto
-        };
-        let mut builder = self.inner_ref()?.create_index(&[column], lancedb_index);
-        if let Some(replace) = replace {
-            builder = builder.replace(replace);
-        }
-        if let Some(timeout) = wait_timeout_s {
-            builder =
-                builder.wait_timeout(std::time::Duration::from_secs(timeout.try_into().unwrap()));
-        }
-        if let Some(name) = name {
-            builder = builder.name(name);
-        }
-        if let Some(train) = train {
-            builder = builder.train(train);
-        }
-        let job = builder.execute_async().await.default_error()?;
-        Ok(crate::job::Job::new(job))
-    }
-
    #[napi(catch_unwind)]
    pub async fn drop_index(&self, index_name: String) -> napi::Result<()> {
        self.inner_ref()?
@@ -339,9 +306,7 @@ impl Table {
        let transforms = NewColumnTransform::SqlExpressions(transforms);
        let res = self
            .inner_ref()?
-            .add_columns()
-            .transform(transforms)
-            .execute()
+            .add_columns(transforms, None)
            .await
            .default_error()?;
        Ok(res.into())
@@ -358,9 +323,7 @@ impl Table {
        let transforms = NewColumnTransform::AllNulls(schema);
        let res = self
            .inner_ref()?
-            .add_columns()
-            .transform(transforms)
-            .execute()
+            .add_columns(transforms, None)
            .await
            .default_error()?;
        Ok(res.into())
@@ -26,7 +26,7 @@ lance-namespace-impls.workspace = true
 lance-io.workspace = true
 env_logger.workspace = true
 log.workspace = true
-pyo3 = { version = "0.28", features = ["extension-module", "abi3-py310", "chrono"] }
+pyo3 = { version = "0.28", features = ["extension-module", "abi3-py39", "chrono"] }
 chrono = { version = "0.4", default-features = false, features = ["clock"] }
 pyo3-async-runtimes = { version = "0.28", features = [
    "attributes",
@@ -43,7 +43,7 @@ libc = "0.2"
 [build-dependencies]
 pyo3-build-config = { version = "0.28", features = [
    "extension-module",
-    "abi3-py310",
+    "abi3-py39",
 ] }

 [features]
@@ -20,7 +20,6 @@ from .remote import ClientConfig
 from .remote.db import RemoteDBConnection
 from .expr import Expr, col, lit, func
 from .schema import blob, vector, BlobType
-from .job import AsyncJob, Job
 from .table import AsyncTable, Table
 from .types import BaseTokenizerType
 from ._lancedb import Session
@@ -259,7 +258,6 @@ def tokenize(
    lower_case: bool = True,
    stem: bool = True,
    remove_stop_words: bool = True,
-    custom_stop_words: Optional[List[str]] = None,
    ascii_folding: bool = True,
    ngram_min_length: int = 3,
    ngram_max_length: int = 3,
@@ -267,10 +265,9 @@ def tokenize(
 ) -> Iterable[FtsToken]:
    """Tokenize a full-text search query using an explicit tokenizer.

-    This does not require an FTS index. The tokenizer options match
-    :class:`lancedb.index.FTS`. ``custom_stop_words`` accepts a list of strings.
+    This does not require a table or FTS index. The tokenizer options match
+    :class:`lancedb.index.FTS`.
    """
-
    return _tokenize(
        query,
        base_tokenizer=base_tokenizer,
@@ -279,7 +276,6 @@ def tokenize(
        lower_case=lower_case,
        stem=stem,
        remove_stop_words=remove_stop_words,
-        custom_stop_words=custom_stop_words,
        ascii_folding=ascii_folding,
        ngram_min_length=ngram_min_length,
        ngram_max_length=ngram_max_length,
@@ -501,7 +497,6 @@ __all__ = [
    "connect_namespace",
    "connect_namespace_async",
    "AsyncConnection",
-    "AsyncJob",
    "AsyncLanceNamespaceDBConnection",
    "AsyncTable",
    "FtsToken",
@@ -515,7 +510,6 @@ __all__ = [
    "BlobType",
    "vector",
    "DBConnection",
-    "Job",
    "LanceDBConnection",
    "LanceNamespaceDBConnection",
    "RemoteDBConnection",
@@ -14,10 +14,14 @@ import pyarrow as pa
 from .expr import Expr
 from .schema import blob_v2_column_paths
 from .types import BlobMode, QueryProjection, QueryProjectionSpec
+from .util import get_uri_scheme

 if TYPE_CHECKING:
    from _typeshed import WriteableBuffer

+    from .remote.table import RemoteTable
+    from .table import AsyncTable, Table
+
 BLOB_MODE_TO_HANDLING = {
    "lazy": "blobs_descriptions",
    "bytes": "all_binary",
@@ -100,6 +104,22 @@ def validate_blob_mode(blob_mode: BlobMode) -> None:
        raise ValueError(f"blob_mode must be one of {modes}, got {blob_mode!r}")


+def supports_blob_auto_row_id(table: Table | AsyncTable | RemoteTable) -> bool:
+    """Blob auto row-id applies to native tables, not LanceDB Cloud."""
+    from .remote.table import RemoteTable
+
+    if isinstance(table, RemoteTable):
+        return False
+
+    inner = getattr(table, "_inner", None)
+    if inner is not None:
+        uri = inner.database().uri
+        if isinstance(uri, str) and get_uri_scheme(uri) == "db":
+            return False
+
+    return True
+
+
 def projection_includes_blob_column(
    projection: QueryProjection,
    blob_columns: Iterable[str],
@@ -144,14 +164,16 @@ def v2_projection_needs_row_id(


 def blob_auto_row_id_for_scan(
+    table: Table | AsyncTable | RemoteTable,
    schema: pa.Schema,
    projection: QueryProjection,
    *,
    with_row_id: bool | None,
 ) -> bool:
-    """Auto row-id only applies when the caller said nothing about row ids."""
    if with_row_id is not None:
        return False
+    if not supports_blob_auto_row_id(table):
+        return False
    return v2_projection_needs_row_id(schema, projection, with_row_id=False)


@@ -164,11 +186,6 @@ def finalize_blob_query_table(
 ) -> pa.Table:
    if user_requested_row_id or not blob_auto_row_id:
        return tbl
-    if "_rowid" not in tbl.column_names:
-        # A backend that ignores the row-id request leaves nothing to stash. Hand
-        # back the projection as-is so fetch_blobs raises the error that names the
-        # ways to supply row ids, rather than failing here about a hidden column.
-        return tbl
    return stash_auto_row_ids(tbl, blob_paths)


@@ -59,7 +59,6 @@ def tokenize(
    lower_case: bool = True,
    stem: bool = True,
    remove_stop_words: bool = True,
-    custom_stop_words: Optional[List[str]] = None,
    ascii_folding: bool = True,
    ngram_min_length: int = 3,
    ngram_max_length: int = 3,
@@ -146,13 +145,6 @@ class Connection(object):
        start_after: Optional[str],
        limit: Optional[int],
    ) -> list[str]: ...  # Deprecated: Use list_tables instead
-    def job(self, job_id: str) -> Job: ...
-    async def list_jobs(self) -> List[JobInfo]: ...
-    async def get_job(self, job_id: str) -> Optional[JobDescription]: ...
-    async def cancel_job(self, job_id: str) -> bool: ...
-    async def job_history(
-        self, job_id: Optional[str] = None
-    ) -> List[pa.RecordBatch]: ...
    async def create_table(
        self,
        name: str,
@@ -216,47 +208,6 @@ class BlobFile:
    def read_range(self, offset: int, length: int) -> bytes: ...
    def read_up_to(self, length: int) -> bytes: ...

-class Job:
-    @property
-    def id(self) -> Optional[str]: ...
-    async def status(self) -> str: ...
-    async def wait(self) -> None: ...
-    async def cancel(self) -> None: ...
-
-class JobInfo:
-    @property
-    def job_id(self) -> str: ...
-    @property
-    def table(self) -> str: ...
-    @property
-    def job_type(self) -> str: ...
-    @property
-    def state(self) -> str: ...
-    @property
-    def created_at_millis(self) -> int: ...
-
-class JobFailureInfo:
-    @property
-    def phase(self) -> Optional[str]: ...
-    @property
-    def message(self) -> Optional[str]: ...
-    @property
-    def retryable(self) -> Optional[bool]: ...
-
-class JobDescription:
-    @property
-    def job_id(self) -> str: ...
-    @property
-    def job_type(self) -> str: ...
-    @property
-    def state(self) -> str: ...
-    @property
-    def creation_ms(self) -> int: ...
-    @property
-    def spec_json(self) -> Optional[str]: ...
-    @property
-    def failure(self) -> Optional[JobFailureInfo]: ...
-
 class Table:
    def name(self) -> str: ...
    def __repr__(self) -> str: ...
@@ -296,28 +247,6 @@ class Table:
        name: Optional[str],
        train: Optional[bool],
    ): ...
-    async def create_index_async(
-        self,
-        column: str,
-        index: Union[
-            IvfFlat,
-            IvfSq,
-            IvfPq,
-            HnswPq,
-            HnswSq,
-            HnswFlat,
-            BTree,
-            Bitmap,
-            LabelList,
-            Fm,
-            FTS,
-        ],
-        replace: Optional[bool],
-        wait_timeout: Optional[object],
-        *,
-        name: Optional[str],
-        train: Optional[bool],
-    ) -> Job: ...
    async def list_versions(self) -> List[Dict[str, Any]]: ...
    async def version(self) -> int: ...
    async def checkout(self, version: Union[int, str]): ...
@@ -45,7 +45,6 @@ from lance_namespace.errors import NamespaceNotEmptyError, TableNotFoundError

 from . import __version__
 from ._lancedb import connect as lancedb_connect  # type: ignore
-from .job import AsyncJob, Job
 from .table import (
    AsyncTable,
    LanceTable,
@@ -64,7 +63,6 @@ if TYPE_CHECKING:
    from .pydantic import LanceModel

    from ._lancedb import Connection as LanceDbConnection
-    from ._lancedb import JobDescription, JobInfo
    from .common import DATA, URI
    from .embeddings import EmbeddingFunctionConfig
    from ._lancedb import Session
@@ -180,51 +178,6 @@ class DBConnection(EnforceOverrides):
            "Namespace operations are not supported for this connection type"
        )

-    def namespace_exists(self, namespace_id: List[str]) -> bool:
-        """Check if a namespace exists.
-
-        Parameters
-        ----------
-        namespace_id: List[str]
-            The namespace identifier to check.
-
-        Returns
-        -------
-        bool
-            True if the namespace exists, False otherwise.
-
-        Raises
-        ------
-        NotImplementedError
-            If the connection type does not support namespace operations.
-        """
-        raise NotImplementedError(
-            "Namespace operations are not supported for this connection type"
-        )
-
-    def table_exists(self, table_id: List[str]) -> bool:
-        """Check if a table exists.
-
-        Parameters
-        ----------
-        table_id: List[str]
-            The table identifier to check (full path including namespace
-            segments and table name).
-
-        Returns
-        -------
-        bool
-            True if the table exists, False otherwise.
-
-        Raises
-        ------
-        NotImplementedError
-            If the connection type does not support namespace operations.
-        """
-        raise NotImplementedError(
-            "Namespace operations are not supported for this connection type"
-        )
-
    def list_tables(
        self,
        namespace_path: Optional[List[str]] = None,
@@ -406,7 +359,7 @@ class DBConnection(EnforceOverrides):

        Data is converted to Arrow before being written to disk. For maximum
        control over how data is saved, either provide the PyArrow schema to
-        convert to or else provide a [PyArrow Table][pyarrow.Table] directly.
+        convert to or else provide a [PyArrow Table](pyarrow.Table) directly.

        >>> import pyarrow as pa
        >>> custom_schema = pa.schema([
@@ -610,46 +563,6 @@ class DBConnection(EnforceOverrides):
        """
        raise NotImplementedError("serialize is not supported for this connection type")

-    def job(self, job_id: str) -> Job:
-        """A [Job][lancedb.job.Job] handle for a server-side job by id.
-
-        The handle is constructed without a server round trip; an unknown id
-        surfaces when the handle is used. Dropping the handle has no effect
-        on the job itself.
-        """
-        raise NotImplementedError("job is not supported for this connection type")
-
-    def list_jobs(self) -> List[JobInfo]:
-        """List server-side jobs across the database's tables."""
-        raise NotImplementedError("list_jobs is not supported for this connection type")
-
-    def get_job(self, job_id: str) -> Optional[JobDescription]:
-        """Describe a single server-side job by id.
-
-        Returns None when the server has no such job.
-        """
-        raise NotImplementedError("get_job is not supported for this connection type")
-
-    def cancel_job(self, job_id: str) -> bool:
-        """Request cancellation of a server-side job by id.
-
-        Returns True if the server accepted the cancellation, False if no
-        such job exists. Cancelling an already-terminal job is a no-op
-        success.
-        """
-        raise NotImplementedError(
-            "cancel_job is not supported for this connection type"
-        )
-
-    def job_history(self, job_id: Optional[str] = None) -> List[pa.RecordBatch]:
-        """The lifecycle event history of a server-side job, as Arrow batches.
-
-        Lists history across all jobs when `job_id` is None.
-        """
-        raise NotImplementedError(
-            "job_history is not supported for this connection type"
-        )
-

 class LanceDBConnection(DBConnection):
    """
@@ -707,9 +620,6 @@ class LanceDBConnection(DBConnection):
        self._namespace_client_properties = namespace_client_properties
        if _inner is not None:
            self._conn = _inner
-            # Native-derived wrappers resolve this in their async reconstruction
-            # path so construction never synchronously re-enters LOOP.
-            self._read_consistency_interval = read_consistency_interval
            self._cached_namespace_client = None
            return

@@ -759,14 +669,11 @@ class LanceDBConnection(DBConnection):
        # storage_options.  Also, this class really shouldn't be holding any state
        # beyond _conn.
        self._conn = AsyncConnection(LOOP.run(do_connect()))
-        # Keep property access synchronous so debugger introspection cannot wait on
-        # the background loop while that thread is suspended at a breakpoint.
-        self._read_consistency_interval = read_consistency_interval
        self._cached_namespace_client: Optional[LanceNamespace] = None

    @property
    def read_consistency_interval(self) -> Optional[timedelta]:
-        return self._read_consistency_interval
+        return LOOP.run(self._conn.get_read_consistency_interval())

    @property
    def session(self) -> Optional[Session]:
@@ -777,19 +684,15 @@ class LanceDBConnection(DBConnection):
        return self._conn.uri

    @classmethod
-    def from_inner(
-        cls,
-        inner: LanceDbConnection,
-        read_consistency_interval: Optional[timedelta],
-    ):
-        return cls(
-            None,
-            read_consistency_interval=read_consistency_interval,
-            _inner=inner,
-        )
+    def from_inner(cls, inner: LanceDbConnection):
+        return cls(None, _inner=inner)

    def __repr__(self) -> str:
-        return f"{self.__class__.__name__}(uri={self._conn.uri!r})"
+        val = f"{self.__class__.__name__}(uri={self._conn.uri!r}"
+        if self.read_consistency_interval is not None:
+            val += f", read_consistency_interval={repr(self.read_consistency_interval)}"
+        val += ")"
+        return val

    @override
    def serialize(self) -> str:
@@ -1226,47 +1129,6 @@ class LanceDBConnection(DBConnection):
            )
        )

-    @override
-    def job(self, job_id: str) -> Job:
-        """A [Job][lancedb.job.Job] handle for a server-side job by id.
-
-        The handle is constructed without a server round trip; an unknown id
-        surfaces when the handle is used. Dropping the handle has no effect
-        on the job itself.
-        """
-        return Job(self._conn.job(job_id))
-
-    @override
-    def list_jobs(self) -> List[JobInfo]:
-        """List server-side jobs across the database's tables."""
-        return LOOP.run(self._conn.list_jobs())
-
-    @override
-    def get_job(self, job_id: str) -> Optional[JobDescription]:
-        """Describe a single server-side job by id.
-
-        Returns None when the server has no such job.
-        """
-        return LOOP.run(self._conn.get_job(job_id))
-
-    @override
-    def cancel_job(self, job_id: str) -> bool:
-        """Request cancellation of a server-side job by id.
-
-        Returns True if the server accepted the cancellation, False if no
-        such job exists. Cancelling an already-terminal job is a no-op
-        success.
-        """
-        return LOOP.run(self._conn.cancel_job(job_id))
-
-    @override
-    def job_history(self, job_id: Optional[str] = None) -> List[pa.RecordBatch]:
-        """The lifecycle event history of a server-side job, as Arrow batches.
-
-        Lists history across all jobs when `job_id` is None.
-        """
-        return LOOP.run(self._conn.job_history(job_id))
-
    @override
    def namespace_client(self) -> LanceNamespace:
        """Get the equivalent namespace client for this connection.
@@ -1667,7 +1529,7 @@ class AsyncConnection(object):

        Data is converted to Arrow before being written to disk. For maximum
        control over how data is saved, either provide the PyArrow schema to
-        convert to or else provide a [PyArrow Table][pyarrow.Table] directly.
+        convert to or else provide a [PyArrow Table](pyarrow.Table) directly.

        >>> import pyarrow as pa
        >>> custom_schema = pa.schema([
@@ -1976,43 +1838,6 @@ class AsyncConnection(object):
            namespace_path = []
        await self._inner.drop_all_tables(namespace_path=namespace_path)

-    def job(self, job_id: str) -> AsyncJob:
-        """An [AsyncJob][lancedb.job.AsyncJob] handle for a server-side job
-        by id.
-
-        The handle is constructed without a server round trip; an unknown id
-        surfaces when the handle is used. Dropping the handle has no effect
-        on the job itself.
-        """
-        return AsyncJob(self._inner.job(job_id))
-
-    async def list_jobs(self) -> List[JobInfo]:
-        """List server-side jobs across the database's tables."""
-        return await self._inner.list_jobs()
-
-    async def get_job(self, job_id: str) -> Optional[JobDescription]:
-        """Describe a single server-side job by id.
-
-        Returns None when the server has no such job.
-        """
-        return await self._inner.get_job(job_id)
-
-    async def cancel_job(self, job_id: str) -> bool:
-        """Request cancellation of a server-side job by id.
-
-        Returns True if the server accepted the cancellation, False if no
-        such job exists. Cancelling an already-terminal job is a no-op
-        success.
-        """
-        return await self._inner.cancel_job(job_id)
-
-    async def job_history(self, job_id: Optional[str] = None) -> List[pa.RecordBatch]:
-        """The lifecycle event history of a server-side job, as Arrow batches.
-
-        Lists history across all jobs when `job_id` is None.
-        """
-        return await self._inner.job_history(job_id)
-
    async def namespace_client(self) -> LanceNamespace:
        """Get the equivalent namespace client for this connection.

@@ -21,32 +21,3 @@ from .watsonx import WatsonxEmbeddings
 from .voyageai import VoyageAIEmbeddingFunction
 from .colpali import ColPaliEmbeddings
 from .siglip import SigLipEmbeddings
-
-# The API reference renders this package with a single mkdocstrings directive,
-# which only picks up names listed here. New embedding functions must be added
-# to both the imports above and this list, or they will silently go undocumented.
-__all__ = [
-    "EmbeddingFunction",
-    "EmbeddingFunctionConfig",
-    "TextEmbeddingFunction",
-    "EmbeddingFunctionRegistry",
-    "get_registry",
-    "register",
-    "SentenceTransformerEmbeddings",
-    "OpenAIEmbeddings",
-    "OpenClipEmbeddings",
-    "BedRockText",
-    "CohereEmbeddingFunction",
-    "GeminiText",
-    "GteEmbeddings",
-    "InstructorEmbeddingFunction",
-    "JinaEmbeddings",
-    "OllamaEmbeddings",
-    "TransformersEmbeddingFunction",
-    "ColbertEmbeddings",
-    "VoyageAIEmbeddingFunction",
-    "WatsonxEmbeddings",
-    "ColPaliEmbeddings",
-    "ImageBindEmbeddings",
-    "SigLipEmbeddings",
-]
@@ -21,20 +21,20 @@ class BedRockText(TextEmbeddingFunction):
    """
    Parameters
    ----------
-    name : str, default "amazon.titan-embed-text-v1"
+    name: str, default "amazon.titan-embed-text-v1"
        The model ID of the bedrock model to use. Supported models for are:
        - amazon.titan-embed-text-v1
        - cohere.embed-english-v3
        - cohere.embed-multilingual-v3
-    region : str, default "us-east-1"
+    region: str, default "us-east-1"
        Optional name of the AWS Region in which the service should be called.
-    profile_name : str, default None
+    profile_name: str, default None
        Optional name of the AWS profile to use for calling the Bedrock service.
        If not specified, the default profile will be used.
-    assumed_role : str, default None
+    assumed_role: str, default None
        Optional ARN of an AWS IAM role to assume for calling the Bedrock service.
        If not specified, the current active credentials will be used.
-    role_session_name : str, default "lancedb-embeddings"
+    role_session_name: str, default "lancedb-embeddings"
        Optional name of the AWS IAM role session to use for calling the Bedrock
        service. If not specified, "lancedb-embeddings" name will be used.

@@ -22,7 +22,7 @@ class CohereEmbeddingFunction(TextEmbeddingFunction):

    Parameters
    ----------
-    name : str, default "embed-multilingual-v2.0"
+    name: str, default "embed-multilingual-v2.0"
        The name of the model to use. List of acceptable models:

            * embed-english-v3.0
@@ -33,14 +33,12 @@ class CohereEmbeddingFunction(TextEmbeddingFunction):
            * embed-english-light-v2.0
            * embed-multilingual-v2.0

-    source_input_type : str, default "search_document"
+    source_input_type: str, default "search_document"
        The input type for the source column in the database

-    query_input_type : str, default "search_query"
+    query_input_type: str, default "search_query"
        The input type for the query column in the database

-    Notes
-    -----
    Cohere supports following input types:

    | Input Type               | Description                          |
@@ -44,7 +44,7 @@ class ColPaliEmbeddings(EmbeddingFunction):
        The token pooling strategy to use, by default "hierarchical".
        - "hierarchical": Progressively pools tokens to reduce sequence length.
        - "lambda": A simpler pooling that uses a custom `pooling_func`.
-    pooling_func : typing.Callable, optional
+    pooling_func: typing.Callable, optional
        A function to use for pooling when `pooling_strategy` is "lambda".
    pool_factor : int
        Factor to reduce sequence length if token pooling is enabled (default 2).
@@ -52,7 +52,7 @@ class ColPaliEmbeddings(EmbeddingFunction):
        Quantization configuration for the model. (default None, bitsandbytes needed)
    batch_size : int
        Batch size for processing inputs (default 2).
-    offload_folder : str, optional
+    offload_folder: str, optional
        Folder to offload model weights if using CPU offloading (default None). This is
        useful for large models that do not fit in memory.
    """
@@ -48,16 +48,16 @@ class GeminiText(TextEmbeddingFunction):

    Parameters
    ----------
-    name : str, default "gemini-embedding-001"
+    name: str, default "gemini-embedding-001"
        The name of the model to use. Supported models include:
        - "gemini-embedding-001" (768 dimensions)

        Note: The legacy "models/embedding-001" format is also supported but
        "gemini-embedding-001" is recommended.

-    query_task_type : str, default "retrieval_query"
+    query_task_type: str, default "retrieval_query"
        Sets the task type for the queries.
-    source_task_type : str, default "retrieval_document"
+    source_task_type: str, default "retrieval_document"
        Sets the task type for ingestion.

    Examples
@@ -26,13 +26,13 @@ class GteEmbeddings(TextEmbeddingFunction):

    Parameters
    ----------
-    name : str, default "thenlper/gte-large"
+    name: str, default "thenlper/gte-large"
        The name of the model to use.
-    device : str, default "cpu"
+    device: str, default "cpu"
        Sets the device type for the model.
-    normalize : str, default "True"
+    normalize: str, default "True"
        Controls normalize param in encode function for the transformer.
-    mlx : bool, default False
+    mlx: bool, default False
        Controls which model to use. False for gte-large,True for the mlx version.

    Examples
@@ -35,23 +35,23 @@ class InstructorEmbeddingFunction(TextEmbeddingFunction):

    Parameters
    ----------
-    name : str
+    name: str
        The name of the model to use. Available models are listed at
        https://github.com/xlang-ai/instructor-embedding#model-list;
        The default model is hkunlp/instructor-base
-    batch_size : int, default 32
+    batch_size: int, default 32
        The batch size to use when generating embeddings
-    device : str, default "cpu"
+    device: str, default "cpu"
        The device to use when generating embeddings
-    show_progress_bar : bool, default True
+    show_progress_bar: bool, default True
        Whether to show a progress bar when generating embeddings
-    normalize_embeddings : bool, default True
+    normalize_embeddings: bool, default True
        Whether to normalize the embeddings
-    quantize : bool, default False
+    quantize: bool, default False
        Whether to quantize the model
-    source_instruction : str, default "represent the document for retrieval"
+    source_instruction: str, default "represent the document for retrieval"
        The instruction for the source column
-    query_instruction : str, default "represent the document for retrieving the most
+    query_instruction: str, default "represent the document for retrieving the most
        similar documents"
        The instruction for the query

@@ -101,7 +101,8 @@ class InstructorEmbeddingFunction(TextEmbeddingFunction):

    @weak_lru(maxsize=1)
    def ndims(self):
-        return len(self.generate_embeddings([[self.source_instruction, "foo"]])[0])
+        model = self.get_model()
+        return model.encode("foo").shape[0]

    def compute_query_embeddings(self, query: str, *args, **kwargs) -> List[np.array]:
        return self.generate_embeddings([[self.query_instruction, query]])
@@ -40,10 +40,10 @@ class JinaEmbeddings(EmbeddingFunction):

    Parameters
    ----------
-    name : str, default "jina-clip-v1". Note that some models support both image
+    name: str, default "jina-clip-v1". Note that some models support both image
        and text embeddings and some just text embedding

-    api_key : str, default None
+    api_key: str, default None
        The api key to access Jina API. If you pass None, you can set JINA_API_KEY
        environment variable

@@ -21,13 +21,13 @@ class SentenceTransformerEmbeddings(TextEmbeddingFunction):

    Parameters
    ----------
-    name : str, default "all-MiniLM-L6-v2"
+    name: str, default "all-MiniLM-L6-v2"
        The name of the model to use.
-    device : str, default "cpu"
+    device: str, default "cpu"
        The device to use for the model
-    normalize : bool, default True
+    normalize: bool, default True
        Whether to normalize the embeddings
-    trust_remote_code : bool, default True
+    trust_remote_code: bool, default True
        Whether to trust the remote code
    """

@@ -167,7 +167,7 @@ class VoyageAIEmbeddingFunction(EmbeddingFunction):

    Parameters
    ----------
-    name : str
+    name: str
        The name of the model to use. List of acceptable models:

            * voyage-4 (1024 dims, general-purpose and multilingual retrieval)
@@ -185,7 +185,7 @@ class VoyageAIEmbeddingFunction(EmbeddingFunction):
            * voyage-law-2
            * voyage-code-2

-    output_dimension : int, optional
+    output_dimension: int, optional
        The output dimension for models that support flexible dimensions.
        Currently only voyage-multimodal-3.5 supports this feature.
        Valid options: 256, 512, 1024 (default), 2048.
@@ -23,15 +23,3 @@ class MissingColumnError(KeyError):
        return (
            f"Error: Column '{self.column_name}' does not exist in the DataFrame object"
        )
-
-
-class JobFailedError(RuntimeError):
-    """Exception raised when an asynchronous job reaches the failed state."""
-
-    pass
-
-
-class JobCancelledError(RuntimeError):
-    """Exception raised when an asynchronous job was cancelled."""
-
-    pass
@@ -2,7 +2,7 @@
 # SPDX-FileCopyrightText: Copyright The LanceDB Authors

 from dataclasses import dataclass
-from typing import List, Literal, Optional
+from typing import Literal, Optional

 from ._lancedb import (
    IndexConfig,
@@ -151,11 +151,6 @@ class FTS:
    remove_stop_words : bool, default True
        Whether to remove stop words. Stop words are common words that are often
        removed from text before indexing. For example, in English "the" and "and".
-    custom_stop_words : list of str, optional
-        Custom words replace the built-in language stop words
-        and only take effect when ``remove_stop_words`` is True. ``None`` uses
-        the built-in language list, while an empty list explicitly uses no
-        stop words.
    ascii_folding : bool, default True
        Whether to fold ASCII characters. This converts accented characters to
        their ASCII equivalent. For example, "café" would be converted to "cafe".
@@ -184,7 +179,6 @@ class FTS:
    ngram_max_length: int = 3
    prefix_only: bool = False
    block_size: int = 128
-    custom_stop_words: Optional[List[str]] = None


@dataclass
@@ -219,7 +213,7 @@ class HnswPq:
        distance has a range of (-∞, ∞). If the vectors are normalized (i.e. their
        l2 norm is 1), then dot distance is equivalent to the cosine distance.

-    num_partitions: int, default sqrt(num_rows)
+    num_partitions, default sqrt(num_rows)

        The number of IVF partitions to create.

@@ -228,7 +222,7 @@ class HnswPq:
        will require too much memory. Each partition becomes its own HNSW graph, so
        setting this value higher reduces the peak memory use of training.

-    num_sub_vectors: int, default is vector dimension / 16
+    num_sub_vectors, default is vector dimension / 16

        Number of sub-vectors of PQ.

@@ -244,13 +238,13 @@ class HnswPq:
        If the dimension is not visible by 8 then we use 1 subvector.  This is not
        ideal and will likely result in poor performance.

-    num_bits: int, default 8
+     num_bits: int, default 8
        Number of bits to encode each sub-vector.

        This value controls how much the sub-vectors are compressed.  The more bits
        the more accurate the index but the slower search. Only 4 and 8 are supported.

-    max_iterations: int, default 50
+    max_iterations, default 50

        Max iterations to train kmeans.

@@ -263,7 +257,7 @@ class HnswPq:
        those cases it is unlikely that setting this larger will lead to the index
        converging anyways.

-    sample_rate: int, default 256
+    sample_rate, default 256

        The rate used to calculate the number of training vectors for kmeans.

@@ -279,14 +273,14 @@ class HnswPq:
        Increasing this value might improve the quality of the index but in
        most cases the default should be sufficient.

-    m: int, default 20
+    m, default 20

        The number of neighbors to select for each vector in the HNSW graph.

        This value controls the tradeoff between search speed and accuracy.
        The higher the value the more accurate the search but the slower it will be.

-    ef_construction: int, default 300
+    ef_construction, default 300

        The number of candidates to evaluate during the construction of the HNSW graph.

@@ -297,7 +291,7 @@ class HnswPq:
        This value should be set to a value that is not less than `ef` in the
        search phase.

-    target_partition_size: int, default is 1,048,576
+    target_partition_size, default is 1,048,576

        The target size of each partition.

@@ -351,7 +345,7 @@ class HnswSq:
        distance has a range of (-∞, ∞). If the vectors are normalized (i.e. their
        l2 norm is 1), then dot distance is equivalent to the cosine distance.

-    num_partitions: int, default sqrt(num_rows)
+    num_partitions, default sqrt(num_rows)

        The number of IVF partitions to create.

@@ -360,7 +354,7 @@ class HnswSq:
        will require too much memory. Each partition becomes its own HNSW graph, so
        setting this value higher reduces the peak memory use of training.

-    max_iterations: int, default 50
+    max_iterations, default 50

        Max iterations to train kmeans.

@@ -373,7 +367,7 @@ class HnswSq:
        In those cases it is unlikely that setting this larger will lead to
        the index converging anyways.

-    sample_rate: int, default 256
+    sample_rate, default 256

        The rate used to calculate the number of training vectors for kmeans.

@@ -389,14 +383,14 @@ class HnswSq:
        Increasing this value might improve the quality of the index but in
        most cases the default should be sufficient.

-    m: int, default 20
+    m, default 20

        The number of neighbors to select for each vector in the HNSW graph.

        This value controls the tradeoff between search speed and accuracy.
        The higher the value the more accurate the search but the slower it will be.

-    ef_construction: int, default 300
+    ef_construction, default 300

        The number of candidates to evaluate during the construction of the HNSW graph.

@@ -407,7 +401,7 @@ class HnswSq:
        This value should be set to a value that is not less than `ef` in the search
        phase.

-    target_partition_size: int, default is 1,048,576
+    target_partition_size, default is 1,048,576

        The target size of each partition.

@@ -460,7 +454,7 @@ class HnswFlat:
        distance has a range of (-∞, ∞). If the vectors are normalized (i.e. their
        l2 norm is 1), then dot distance is equivalent to the cosine distance.

-    num_partitions: int, default sqrt(num_rows)
+    num_partitions, default sqrt(num_rows)

        The number of IVF partitions to create.

@@ -470,18 +464,18 @@ class HnswFlat:
        graph, so setting this value higher reduces the peak memory use of
        training.

-    max_iterations: int, default 50
+    max_iterations, default 50

        Max iterations to train kmeans.

        When training an IVF index we use kmeans to calculate the partitions.
        This parameter controls how many iterations of kmeans to run.

-    sample_rate: int, default 256
+    sample_rate, default 256

        The rate used to calculate the number of training vectors for kmeans.

-    m: int, default 20
+    m, default 20

        The number of neighbors to select for each vector in the HNSW graph.

@@ -489,7 +483,7 @@ class HnswFlat:
        The higher the value the more accurate the search but the slower it
        will be.

-    ef_construction: int, default 300
+    ef_construction, default 300

        The number of candidates to evaluate during the construction of the HNSW
        graph.
@@ -501,7 +495,7 @@ class HnswFlat:
        than 500.  This value should be set to a value that is not less than `ef`
        in the search phase.

-    target_partition_size: int, default is 1,048,576
+    target_partition_size, default is 1,048,576

        The target size of each partition.
    """
@@ -605,7 +599,7 @@ class IvfFlat:

        The default value is 256.

-    target_partition_size: int, default is 8192
+    target_partition_size, default is 8192

        The target size of each partition.

@@ -769,7 +763,7 @@ class IvfPq:

        The default value is 256.

-    target_partition_size: int, default is 8192
+    target_partition_size, default is 8192

        The target size of each partition.

@@ -830,7 +824,7 @@ class IvfRq:
    sample_rate: int, default 256
        Controls the number of training vectors: sample_rate * num_partitions.

-    target_partition_size: int, default is 8192
+    target_partition_size, default is 8192
        Target size of each partition.
    """

@@ -845,9 +839,6 @@ class IvfRq:
    accelerator: Optional[str] = None


-# The API reference renders this module with a single mkdocstrings directive,
-# which only picks up names listed here. New public names must be added to this
-# list, or they will silently go undocumented.
 __all__ = [
    "BTree",
    "IvfPq",
@@ -1,105 +0,0 @@
-# SPDX-License-Identifier: Apache-2.0
-# SPDX-FileCopyrightText: Copyright The LanceDB Authors
-
-"""Handles to operations a server may run asynchronously."""
-
-import asyncio
-from datetime import timedelta
-from typing import Optional
-
-from lancedb.background_loop import LOOP
-
-from . import _lancedb
-
-
-class AsyncJob:
-    """A handle to an operation that may still be running.
-
-    The operation may already be complete when the handle is created.
-    """
-
-    def __init__(self, inner: Optional["_lancedb.Job"]):
-        self._inner = inner
-
-    @property
-    def id(self) -> Optional[str]:
-        """Identifies the operation on the server that is running it.
-
-        Returned for correlating with server logs or the jobs API. Operations
-        that run in this process have no server id and return `None`. The value
-        is opaque: parsing it or storing it to resume the job later is not
-        supported.
-        """
-        return self._inner.id if self._inner is not None else None
-
-    async def status(self) -> str:
-        """The operation's current lifecycle state: "running", "finished",
-        "failed", or "cancelled".
-
-        A point snapshot; unlike `wait` it does not block or raise on a
-        terminal failure state. States a newer server reports that this
-        client version does not know pass through as-is.
-        """
-        if self._inner is None:
-            return "finished"
-        return await self._inner.status()
-
-    async def wait(self, timeout: Optional[timedelta] = None):
-        """Wait until the operation reaches a terminal state.
-
-        Raises `JobFailedError` if the operation failed, `JobCancelledError`
-        if it was cancelled, and `TimeoutError` if `timeout` elapses first.
-        """
-        if self._inner is None:
-            return
-        if timeout is None:
-            await self._inner.wait()
-        else:
-            await asyncio.wait_for(self._inner.wait(), timeout.total_seconds())
-
-    async def cancel(self):
-        """Request cancellation. Cancelling a finished operation is a no-op."""
-        if self._inner is None:
-            return
-        await self._inner.cancel()
-
-
-class Job:
-    """Synchronous counterpart of `AsyncJob`."""
-
-    def __init__(self, inner: Optional[AsyncJob]):
-        self._inner = inner
-
-    @property
-    def id(self) -> Optional[str]:
-        """Identifies the operation on the server that is running it.
-
-        See :attr:`AsyncJob.id`.
-        """
-        return self._inner.id if self._inner is not None else None
-
-    def status(self) -> str:
-        """The operation's current lifecycle state: "running", "finished",
-        "failed", or "cancelled".
-
-        See :meth:`AsyncJob.status`.
-        """
-        if self._inner is None:
-            return "finished"
-        return LOOP.run(self._inner.status())
-
-    def wait(self, timeout: Optional[timedelta] = None):
-        """Block until the operation reaches a terminal state.
-
-        Raises `JobFailedError` if the operation failed, `JobCancelledError`
-        if it was cancelled, and `TimeoutError` if `timeout` elapses first.
-        """
-        if self._inner is None:
-            return
-        LOOP.run(self._inner.wait(timeout))
-
-    def cancel(self):
-        """Request cancellation. Cancelling a finished operation is a no-op."""
-        if self._inner is None:
-            return
-        LOOP.run(self._inner.cancel())
@@ -92,10 +92,8 @@ class LanceMergeInsertBuilder(object):
        self._when_not_matched_by_source_delete = True
        if isinstance(condition, Expr):
            self._when_not_matched_by_source_condition_expr = condition._inner
-            self._when_not_matched_by_source_condition = None
-        else:
+        elif condition is not None:
            self._when_not_matched_by_source_condition = condition
-            self._when_not_matched_by_source_condition_expr = None
        return self

    def use_index(self, use_index: bool) -> LanceMergeInsertBuilder:
@@ -38,11 +38,7 @@ from lance_namespace_urllib3_client.models.query_table_request_vector import (
    QueryTableRequestVector,
 )
 from lance_namespace_urllib3_client.models.string_fts_query import StringFtsQuery
-from lance_namespace.errors import (
-    NamespaceNotEmptyError,
-    NamespaceNotFoundError,
-    TableNotFoundError,
-)
+from lance_namespace.errors import NamespaceNotEmptyError, TableNotFoundError
 from lancedb._lancedb import (
    connect_namespace as _connect_namespace,
    connect_namespace_client as _connect_namespace_client,
@@ -57,8 +53,6 @@ from lance_namespace import (
    DropNamespaceResponse,
    ListNamespacesResponse,
    ListTablesResponse,
-    NamespaceExistsRequest,
-    TableExistsRequest,
 )
 from lancedb.table import AsyncTable, LanceTable, Table
 from lancedb.util import validate_table_name
@@ -786,51 +780,6 @@ class LanceNamespaceDBConnection(DBConnection):
        """
        return LOOP.run(self._inner.describe_namespace(namespace_path))

-    @override
-    def namespace_exists(self, namespace_id: List[str]) -> bool:
-        """
-        Check if a namespace exists.
-
-        Parameters
-        ----------
-        namespace_id : List[str]
-            The namespace identifier to check.
-
-        Returns
-        -------
-        bool
-            True if the namespace exists, False otherwise.
-        """
-        request = NamespaceExistsRequest(id=namespace_id)
-        try:
-            self._namespace_client.namespace_exists(request)
-            return True
-        except NamespaceNotFoundError:
-            return False
-
-    @override
-    def table_exists(self, table_id: List[str]) -> bool:
-        """
-        Check if a table exists.
-
-        Parameters
-        ----------
-        table_id : List[str]
-            The table identifier to check (full path including namespace
-            segments and table name).
-
-        Returns
-        -------
-        bool
-            True if the table exists, False otherwise.
-        """
-        request = TableExistsRequest(id=table_id)
-        try:
-            self._namespace_client.table_exists(request)
-            return True
-        except TableNotFoundError:
-            return False
-
    @override
    def list_tables(
        self,
@@ -1284,49 +1233,6 @@ class AsyncLanceNamespaceDBConnection:
        """
        return await self._inner.describe_namespace(namespace_path)

-    async def namespace_exists(self, namespace_id: List[str]) -> bool:
-        """
-        Check if a namespace exists.
-
-        Parameters
-        ----------
-        namespace_id : List[str]
-            The namespace identifier to check.
-
-        Returns
-        -------
-        bool
-            True if the namespace exists, False otherwise.
-        """
-        request = NamespaceExistsRequest(id=namespace_id)
-        try:
-            self._namespace_client.namespace_exists(request)
-            return True
-        except NamespaceNotFoundError:
-            return False
-
-    async def table_exists(self, table_id: List[str]) -> bool:
-        """
-        Check if a table exists.
-
-        Parameters
-        ----------
-        table_id : List[str]
-            The table identifier to check (full path including namespace
-            segments and table name).
-
-        Returns
-        -------
-        bool
-            True if the table exists, False otherwise.
-        """
-        request = TableExistsRequest(id=table_id)
-        try:
-            self._namespace_client.table_exists(request)
-            return True
-        except TableNotFoundError:
-            return False
-
    async def list_tables(
        self,
        namespace_path: Optional[List[str]] = None,
@@ -226,7 +226,7 @@ class PermutationBuilder:

        async def do_execute():
            inner_tbl = await self._async.execute()
-            return await LanceTable.from_inner(inner_tbl)
+            return LanceTable.from_inner(inner_tbl)

        return LOOP.run(do_execute())

@@ -438,8 +438,7 @@ class Permutation:
        _reader: Optional[PermutationReader] = None,
    ):
        """
-        Internal constructor.  Use
-        [from_tables][lancedb.permutation.Permutation.from_tables] instead.
+        Internal constructor.  Use [from_tables](#from_tables) instead.
        """
        assert base_table is not None, "base_table is required"
        assert selection is not None, "selection is required"
@@ -986,9 +985,8 @@ class Permutation:
        types.  Conversion of strings, lists, and structs will require creating python
        objects and this is not zero-copy.

-        For custom formatting, use
-        [with_transform][lancedb.permutation.Permutation.with_transform] which
-        overrides this method.
+        For custom formatting, use [with_transform](#with_transform) which overrides
+        this method.
        """
        assert format is not None, "format is required"
        if format == "python":
@@ -1063,8 +1061,7 @@ class Permutation:
        Note: this method returns a new permutation and does not modify `self`
        It is provided for compatibility with the huggingface Dataset API.

-        Use [with_skip][lancedb.permutation.Permutation.with_skip] instead to
-        avoid confusion.
+        Use [with_skip](#with_skip) instead to avoid confusion.
        """
        return self.with_skip(skip)

@@ -1087,8 +1084,7 @@ class Permutation:
        Note: this method returns a new permutation and does not modify `self`
        It is provided for compatibility with the huggingface Dataset API.

-        Use [with_take][lancedb.permutation.Permutation.with_take] instead to
-        avoid confusion.
+        Use [with_take](#with_take) instead to avoid confusion.
        """
        return self.with_take(limit)

@@ -1111,8 +1107,7 @@ class Permutation:
        Note: this method returns a new permutation and does not modify `self`
        It is provided for compatibility with the huggingface Dataset API.

-        Use [with_repeat][lancedb.permutation.Permutation.with_repeat] instead
-        to avoid confusion.
+        Use [with_repeat](#with_repeat) instead to avoid confusion.
        """
        return self.with_repeat(times)

@@ -52,6 +52,7 @@ from ._blob import (
    finalize_blob_query_table,
    replace_v2_blob_columns_with_bytes,
    replace_v2_blob_columns_with_bytes_sync,
+    supports_blob_auto_row_id,
    validate_blob_mode,
 )
 from .types import BlobMode, QueryProjection
@@ -650,8 +651,7 @@ class Query(pydantic.BaseModel):
    distance_type : Optional[str]
        the distance type to use for vector search

-        This can be l2 (default), cosine and dot.  See
-        [metric definitions](https://lancedb.com/docs/search/vector-search/) for
+        This can be l2 (default), cosine and dot.  See [metric definitions][search] for
        more details.

        If this is not a vector search this will be None.
@@ -664,9 +664,8 @@ class Query(pydantic.BaseModel):

        - A higher number makes search more accurate but also slower.

-        - See discussion in
-          [Querying an ANN Index](https://lancedb.com/docs/indexing/)
-          for tuning advice.
+        - See discussion in [Querying an ANN Index][querying-an-ann-index] for
+          tuning advice.

        Will be None if this is not a vector search.
    refine_factor : Optional[int]
@@ -674,9 +673,8 @@ class Query(pydantic.BaseModel):

        - A higher number makes search more accurate but also slower.

-        - See discussion in
-          [Querying an ANN Index](https://lancedb.com/docs/indexing/)
-          for tuning advice.
+        - See discussion in [Querying an ANN Index][querying-an-ann-index] for
+          tuning advice.

        Will be None if this is not a vector search.
    lower_bound : Optional[float]
@@ -1279,7 +1277,10 @@ class LanceQueryBuilder(ABC):
        return self._with_row_id is True

    def _blob_auto_row_id_enabled(self) -> bool:
+        if not supports_blob_auto_row_id(self._table):
+            return False
        return blob_auto_row_id_for_scan(
+            self._table,
            self._table.schema,
            self._columns,
            with_row_id=self._with_row_id,
@@ -1650,8 +1651,8 @@ class LanceVectorQueryBuilder(LanceQueryBuilder):
        Higher values will yield better recall (more likely to find vectors if
        they exist) at the expense of latency.

-        See discussion in [Querying an ANN Index](https://lancedb.com/docs/indexing/)
-        for tuning advice.
+        See discussion in [Querying an ANN Index][querying-an-ann-index] for
+        tuning advice.

        This method sets both the minimum and maximum number of probes to the same
        value. See `minimum_nprobes` and `maximum_nprobes` for more fine-grained
@@ -1751,8 +1752,8 @@ class LanceVectorQueryBuilder(LanceQueryBuilder):
        As an example, a refine factor of 2 will sample 2x as many vectors as
        requested, re-ranks them, and returns the top half most relevant results.

-        See discussion in [Querying an ANN Index](https://lancedb.com/docs/indexing/)
-        for tuning advice.
+        See discussion in [Querying an ANN Index][querying-an-ann-index] for
+        tuning advice.

        Parameters
        ----------
@@ -2697,7 +2698,7 @@ class LanceHybridQueryBuilder(LanceQueryBuilder):
            self._fts_query.phrase_query(True)
        if self._distance_type:
            self._vector_query.metric(self._distance_type)
-        if self._minimum_nprobes is not None:
+        if self._minimum_nprobes:
            self._vector_query.minimum_nprobes(self._minimum_nprobes)
        if self._maximum_nprobes is not None:
            self._vector_query.maximum_nprobes(self._maximum_nprobes)
@@ -2770,7 +2771,7 @@ class AsyncQueryBase(object):
        )

    async def _maybe_add_blob_row_id(self) -> None:
-        if self._table is None:
+        if self._table is None or not supports_blob_auto_row_id(self._table):
            self._blob_auto_row_id = False
            self._blob_paths = ()
            return
@@ -2778,6 +2779,7 @@ class AsyncQueryBase(object):
        req = self._inner.to_query_request()
        schema = await self._table.schema()
        self._blob_auto_row_id = blob_auto_row_id_for_scan(
+            self._table,
            schema,
            req.select,
            with_row_id=self._with_row_id,
@@ -3029,6 +3031,7 @@ class AsyncQueryBase(object):

        schema = await self._table.schema()
        blob_auto_row_id = blob_auto_row_id_for_scan(
+            self._table,
            schema,
            query.columns,
            with_row_id=self._with_row_id,
@@ -3376,9 +3379,8 @@ class AsyncQuery(AsyncStandardQuery):
        are various ANN search parameters that will let you fine tune your recall
        accuracy vs search latency.

-        Vector searches always have a
-        [limit][lancedb.query.AsyncVectorQuery.limit].  If `limit` has not been
-        called then a default `limit` of 10 will be used.
+        Vector searches always have a [limit][].  If `limit` has not been called then
+        a default `limit` of 10 will be used.

        Typically, a single vector is passed in as the query. However, you can also
        pass in multiple vectors. When multiple vectors are passed in, if the vector
@@ -3509,9 +3511,8 @@ class AsyncFTSQuery(AsyncStandardQuery):
        are various ANN search parameters that will let you fine tune your recall
        accuracy vs search latency.

-        Hybrid searches always have a
-        [limit][lancedb.query.AsyncHybridQuery.limit].  If `limit` has not been
-        called then a default `limit` of 10 will be used.
+        Hybrid searches always have a [limit][].  If `limit` has not been called then
+        a default `limit` of 10 will be used.

        Typically, a single vector is passed in as the query. However, you can also
        pass in multiple vectors.  This can be useful if you want to find the nearest
@@ -3874,9 +3875,10 @@ class AsyncHybridQuery(AsyncStandardQuery, AsyncVectorQueryBase):
        req = fts_query._inner.to_query_request()
        blob_auto_row_id = False
        blob_paths: tuple[str, ...] = ()
-        if self._table is not None:
+        if self._table is not None and supports_blob_auto_row_id(self._table):
            schema = await self._table.schema()
            blob_auto_row_id = blob_auto_row_id_for_scan(
+                self._table,
                schema,
                req.select,
                with_row_id=self._with_row_id,
@@ -11,9 +11,6 @@ from lancedb import __version__
 from .header import HeaderProvider
 from .oauth import OAuthConfig, OAuthFlowType

-# The API reference renders this module with a single mkdocstrings directive,
-# which only picks up names listed here. New public names must be added to this
-# list, or they will silently go undocumented.
 __all__ = [
    "TimeoutConfig",
    "RetryConfig",
@@ -7,7 +7,7 @@ import json
 import logging
 from concurrent.futures import ThreadPoolExecutor
 import sys
-from typing import TYPE_CHECKING, Any, Dict, Iterable, List, Optional, Union
+from typing import Any, Dict, Iterable, List, Optional, Union
 from urllib.parse import urlparse
 import warnings

@@ -23,10 +23,6 @@ import pyarrow as pa

 from ..common import DATA
 from ..db import DBConnection, LOOP
-from ..job import Job
-
-if TYPE_CHECKING:
-    from .._lancedb import JobDescription, JobInfo
 from ..embeddings import EmbeddingFunctionConfig
 from lance_namespace import (
    LanceNamespace,
@@ -419,11 +415,6 @@ class RemoteDBConnection(DBConnection):

        if namespace_path is None:
            namespace_path = []
-        if storage_options is not None:
-            logging.info(
-                "storage_options is ignored in LanceDb Cloud"
-                " (storage is managed; set storage_options on connect() instead)"
-            )
        if index_cache_size is not None:
            logging.info(
                "index_cache_size is ignored in LanceDb Cloud"
@@ -693,47 +684,6 @@ class RemoteDBConnection(DBConnection):
            )
        )

-    @override
-    def job(self, job_id: str) -> Job:
-        """A [Job][lancedb.job.Job] handle for a server-side job by id.
-
-        The handle is constructed without a server round trip; an unknown id
-        surfaces when the handle is used. Dropping the handle has no effect
-        on the job itself.
-        """
-        return Job(self._conn.job(job_id))
-
-    @override
-    def list_jobs(self) -> List["JobInfo"]:
-        """List server-side jobs across the database's tables."""
-        return LOOP.run(self._conn.list_jobs())
-
-    @override
-    def get_job(self, job_id: str) -> Optional["JobDescription"]:
-        """Describe a single server-side job by id.
-
-        Returns None when the server has no such job.
-        """
-        return LOOP.run(self._conn.get_job(job_id))
-
-    @override
-    def cancel_job(self, job_id: str) -> bool:
-        """Request cancellation of a server-side job by id.
-
-        Returns True if the server accepted the cancellation, False if no
-        such job exists. Cancelling an already-terminal job is a no-op
-        success.
-        """
-        return LOOP.run(self._conn.cancel_job(job_id))
-
-    @override
-    def job_history(self, job_id: Optional[str] = None) -> List[pa.RecordBatch]:
-        """The lifecycle event history of a server-side job, as Arrow batches.
-
-        Lists history across all jobs when `job_id` is None.
-        """
-        return LOOP.run(self._conn.job_history(job_id))
-
    @override
    def namespace_client(self) -> LanceNamespace:
        """Get the equivalent namespace client for this connection.
@@ -53,9 +53,9 @@ class RetryError(LanceDBClientError):
    """An error that occurs when the client has exceeded the maximum number of retries.

    The retry strategy can be adjusted by setting the
-    [retry_config][lancedb.remote.ClientConfig.retry_config] in the client
+    [retry_config](lancedb.remote.ClientConfig.retry_config) in the client
    configuration. This is passed in the `client_config` argument of
-    [connect][lancedb.connect] and [connect_async][lancedb.connect_async].
+    [connect](lancedb.connect) and [connect_async](lancedb.connect_async).

    The __cause__ attribute of this exception will be the last exception that
    caused the retry to fail. It will be an
@@ -20,7 +20,6 @@ from typing import (
 import warnings

 from lancedb import __version__
-from lancedb._blob import BlobFile

 from lancedb._lancedb import (
    AddColumnsResult,
@@ -48,7 +47,6 @@ from lancedb.index import (
    IvfSq,
    LabelList,
 )
-from lancedb.job import Job
 from lancedb.remote.db import LOOP
 from lancedb.table import IndexConfigType, KNOWN_METRICS
 import pyarrow as pa
@@ -342,7 +340,6 @@ class RemoteTable(Table):
        lower_case: bool = True,
        stem: bool = True,
        remove_stop_words: bool = True,
-        custom_stop_words: Optional[List[str]] = None,
        ascii_folding: bool = True,
        ngram_min_length: int = 3,
        ngram_max_length: int = 3,
@@ -364,7 +361,6 @@ class RemoteTable(Table):
            lower_case=lower_case,
            stem=stem,
            remove_stop_words=remove_stop_words,
-            custom_stop_words=custom_stop_words,
            ascii_folding=ascii_folding,
            ngram_min_length=ngram_min_length,
            ngram_max_length=ngram_max_length,
@@ -542,34 +538,6 @@ class RemoteTable(Table):
            )
        )

-    def create_index_async(
-        self,
-        column: str,
-        *,
-        config: IndexConfigType,
-        replace: Optional[bool] = None,
-        wait_timeout: Optional[timedelta] = None,
-        name: Optional[str] = None,
-        train: bool = True,
-    ) -> Job:
-        """Create an index, returning a handle to the indexing job.
-
-        The job may already be complete when returned; callers must not assume
-        the index exists until :meth:`Job.wait` returns.
-        """
-        return Job(
-            LOOP.run(
-                self._table.create_index_async(
-                    column,
-                    replace=replace,
-                    config=config,
-                    wait_timeout=wait_timeout,
-                    name=name,
-                    train=train,
-                )
-            )
-        )
-
    def _is_legacy_create_index_call(
        self,
        first_arg: str,
@@ -610,9 +578,8 @@ class RemoteTable(Table):
        progress: Optional[Union[bool, Callable, Any]] = None,
        write_parallelism: Optional[int] = None,
    ) -> AddResult:
-        """Add more data to the [Table][lancedb.table.Table].
-
-        It has the same API signature as the OSS version.
+        """Add more data to the [Table](Table). It has the same API signature as
+        the OSS version.

        Parameters
        ----------
@@ -672,8 +639,7 @@ class RemoteTable(Table):
        fast_search: bool = False,
    ) -> LanceVectorQueryBuilder:
        """Create a search query to find the nearest neighbors
-        of the given query vector. We currently support
-        [vector search](https://lancedb.com/docs/search/vector-search/)
+        of the given query vector. We currently support [vector search][search]

        All query options are defined in
        [LanceVectorQueryBuilder][lancedb.query.LanceVectorQueryBuilder].
@@ -1069,22 +1035,22 @@ class RemoteTable(Table):
        )

    def blob_columns(self) -> list[str]:
-        return LOOP.run(self._table.blob_columns())
+        raise NotImplementedError(
+            "blob_columns() is not yet supported on the LanceDB Cloud"
+        )

-    def fetch_blobs(
-        self, column: str, row_ids: Union[list[int], pa.Table]
-    ) -> pa.LargeBinaryArray:
-        return LOOP.run(self._table.fetch_blobs(column, row_ids))
+    def fetch_blobs(self, column: str, row_ids) -> pa.LargeBinaryArray:
+        raise NotImplementedError("fetch_blobs() is not supported on LanceDB Cloud")

    def fetch_blob_ranges(self, column: str, requests) -> pa.LargeBinaryArray:
        raise NotImplementedError(
            "fetch_blob_ranges() is not supported on LanceDB Cloud"
        )

-    def fetch_blob_files(
-        self, column: str, row_ids: Union[list[int], pa.Table]
-    ) -> "list[Optional[BlobFile]]":
-        return LOOP.run(self._table.fetch_blob_files(column, row_ids))
+    def fetch_blob_files(self, column: str, row_ids):
+        raise NotImplementedError(
+            "fetch_blob_files() is not supported on LanceDB Cloud"
+        )

    def head(self, n=5) -> pa.Table:
        """
@@ -14,9 +14,6 @@ from .answerdotai import AnswerdotaiRerankers
 from .voyageai import VoyageAIReranker
 from .watsonx import WatsonxReranker

-# The API reference renders this module with a single mkdocstrings directive,
-# which only picks up names listed here. New public names must be added to this
-# list, or they will silently go undocumented.
 __all__ = [
    "Reranker",
    "CrossEncoderReranker",
@@ -40,7 +40,6 @@ from ._blob import (
 from .types import BlobMode
 from lancedb.arrow import peek_reader
 from lancedb.background_loop import LOOP, embedding_executor
-from lancedb.job import AsyncJob, Job
 from .dependencies import (
    _check_for_hugging_face,
    _check_for_lance,
@@ -978,24 +977,6 @@ class Table(ABC):
        """
        raise NotImplementedError

-    def create_index_async(
-        self,
-        column: str,
-        *,
-        config: IndexConfigType,
-        replace: Optional[bool] = None,
-        wait_timeout: Optional[timedelta] = None,
-        name: Optional[str] = None,
-        train: bool = True,
-    ) -> Job:
-        """Create an index, returning a handle to the indexing job.
-
-        Takes the same arguments as :meth:`create_index`. The job may already
-        be complete when returned; callers must not assume the index exists
-        until :meth:`Job.wait` returns.
-        """
-        raise NotImplementedError
-
    def drop_index(self, name: str) -> None:
        """
        Drop an index from the table.
@@ -1122,7 +1103,6 @@ class Table(ABC):
        lower_case: bool = True,
        stem: bool = True,
        remove_stop_words: bool = True,
-        custom_stop_words: Optional[List[str]] = None,
        ascii_folding: bool = True,
        ngram_min_length: int = 3,
        ngram_max_length: int = 3,
@@ -1190,9 +1170,6 @@ class Table(ABC):
        remove_stop_words : bool, default True
            Whether to remove stop words. Stop words are common words that are often
            removed from text before indexing. For example, in English "the" and "and".
-        custom_stop_words : list of str, optional
-            Custom words that replace the built-in language stop words. ``None``
-            uses the built-in list; an empty list explicitly uses no stop words.
        ascii_folding : bool, default True
            Whether to fold ASCII characters. This converts accented characters to
            their ASCII equivalent. For example, "café" would be converted to "cafe".
@@ -1230,7 +1207,7 @@ class Table(ABC):
        progress: Optional[Union[bool, Callable, Any]] = None,
        write_parallelism: Optional[int] = None,
    ) -> AddResult:
-        """Add more data to the [Table][lancedb.table.Table].
+        """Add more data to the [Table](Table).

        Parameters
        ----------
@@ -1362,8 +1339,8 @@ class Table(ABC):
        fts_columns: Optional[Union[str, List[str]]] = None,
    ) -> LanceQueryBuilder:
        """Create a search query to find the nearest neighbors
-        of the given query vector. We currently support [vector search](https://lancedb.com/docs/search/vector-search/)
-        and [full-text search](https://lancedb.com/docs/search/full-text-search/).
+        of the given query vector. We currently support [vector search][search]
+        and [full-text search][experimental-full-text-search].

        All query options are defined in
        [LanceQueryBuilder][lancedb.query.LanceQueryBuilder].
@@ -1593,10 +1570,8 @@ class Table(ABC):
        """Open lazy, seekable :class:`~lancedb._blob.BlobFile` handles.

        Prefer this over :meth:`fetch_blobs` for large payloads. ``row_ids`` is
-        a ``list[int]`` or a query ``pyarrow.Table`` carrying row identity via
-        ``_rowid`` or a ``_lance_row_id`` field on the blob descriptor. Null
-        rows are ``None``. Remote tables require LanceDB Cloud server 0.5.0 or
-        newer.
+        a ``list[int]`` or query ``pyarrow.Table`` with ``_rowid`` (or stashed
+        row-id metadata). Null rows are ``None``. Local tables only.
        """

    @abstractmethod
@@ -1799,7 +1774,7 @@ class Table(ABC):
        for faster reads.

        Arguments are passed onto Lance's
-        `lance.dataset.DatasetOptimizer.compact_files`.
+        [compact_files][lance.dataset.DatasetOptimizer.compact_files].
        For most cases, the default should be fine.

        See Also
@@ -1853,8 +1828,6 @@ class Table(ABC):
        retrain: bool, default False
            This parameter is no longer used and is deprecated.

-        Notes
-        -----
        The frequency an application should call optimize is based on the frequency of
        data modifications.  If data is frequently added, deleted, or updated then
        optimize should be run frequently.  A good rule of thumb is to run optimize if
@@ -2009,14 +1982,15 @@ class Table(ABC):
        change permanent you can use the `[Self::restore]` method.

        Any operation that modifies the table will fail while the table is in a checked
-        out state. To return the table to a normal state use
-        `[Self::checkout_latest]`.
+        out state.

        Parameters
        ----------
        version: int | str,
            The version to check out. A version number (`int`) or a tag
            (`str`) can be provided.
+
+        To return the table to a normal state use `[Self::checkout_latest]`
        """

    @abstractmethod
@@ -2182,15 +2156,11 @@ class LanceTable(Table):
        return self.name

    @classmethod
-    async def from_inner(cls, tbl: LanceDBTable):
-        from .db import AsyncConnection, LanceDBConnection
+    def from_inner(cls, tbl: LanceDBTable):
+        from .db import LanceDBConnection

        async_tbl = AsyncTable(tbl)
-        inner_conn = tbl.database()
-        read_consistency_interval = await AsyncConnection(
-            inner_conn
-        ).get_read_consistency_interval()
-        conn = LanceDBConnection.from_inner(inner_conn, read_consistency_interval)
+        conn = LanceDBConnection.from_inner(tbl.database())
        return cls(
            conn,
            async_tbl.name,
@@ -2494,7 +2464,13 @@ class LanceTable(Table):
        return LOOP.run(self._table.count_rows(filter))

    def __repr__(self) -> str:
-        return f"{self.__class__.__name__}(name={self.name!r}, _conn={self._conn!r})"
+        val = f"{self.__class__.__name__}(name={self.name!r}"
+        if self._conn.read_consistency_interval is not None:
+            val += ", read_consistency_interval={!r}".format(
+                self._conn.read_consistency_interval
+            )
+        val += f", _conn={self._conn!r})"
+        return val

    def __str__(self) -> str:
        return self.__repr__()
@@ -2803,34 +2779,6 @@ class LanceTable(Table):
            )
        )

-    def create_index_async(
-        self,
-        column: str,
-        *,
-        config: IndexConfigType,
-        replace: Optional[bool] = None,
-        wait_timeout: Optional[timedelta] = None,
-        name: Optional[str] = None,
-        train: bool = True,
-    ) -> Job:
-        """Create an index, returning a handle to the indexing job.
-
-        The job may already be complete when returned; callers must not assume
-        the index exists until :meth:`Job.wait` returns.
-        """
-        return Job(
-            LOOP.run(
-                self._table.create_index_async(
-                    column,
-                    replace=replace,
-                    config=config,
-                    wait_timeout=wait_timeout,
-                    name=name,
-                    train=train,
-                )
-            )
-        )
-
    def _is_legacy_create_index_call(
        self,
        first_arg: str,
@@ -3107,7 +3055,6 @@ class LanceTable(Table):
        lower_case: bool = True,
        stem: bool = True,
        remove_stop_words: bool = True,
-        custom_stop_words: Optional[List[str]] = None,
        ascii_folding: bool = True,
        ngram_min_length: int = 3,
        ngram_max_length: int = 3,
@@ -3154,7 +3101,6 @@ class LanceTable(Table):
                "lower_case": lower_case,
                "stem": stem,
                "remove_stop_words": remove_stop_words,
-                "custom_stop_words": custom_stop_words,
                "ascii_folding": ascii_folding,
                "ngram_min_length": ngram_min_length,
                "ngram_max_length": ngram_max_length,
@@ -3162,7 +3108,6 @@ class LanceTable(Table):
            }
        else:
            tokenizer_configs = self.infer_tokenizer_configs(tokenizer_name)
-            tokenizer_configs["custom_stop_words"] = custom_stop_words

        config = FTS(block_size=block_size, **tokenizer_configs)

@@ -3435,8 +3380,8 @@ class LanceTable(Table):
        fts_columns: Optional[Union[str, List[str]]] = None,
    ) -> LanceQueryBuilder:
        """Create a search query to find the nearest neighbors
-        of the given query vector. We currently support [vector search](https://lancedb.com/docs/search/vector-search/)
-        and [full-text search](https://lancedb.com/docs/search/full-text-search/).
+        of the given query vector. We currently support [vector search][search]
+        and [full-text search][search].

        Examples
        --------
@@ -3466,9 +3411,8 @@ class LanceTable(Table):
            - *default None*.
            Acceptable types are: list, np.ndarray, PIL.Image.Image

-            - If None then the
-            select/[where][lancedb.query.LanceQueryBuilder.where]/limit clauses
-            are applied to filter the table
+            - If None then the select/[where][sql]/limit clauses are applied
+            to filter the table
        vector_column_name: str, optional
            The name of the vector column to search.

@@ -3862,8 +3806,6 @@ class LanceTable(Table):
        retrain: bool, default False
            This parameter is no longer used and is deprecated.

-        Notes
-        -----
        The frequency an application should call optimize is based on the frequency of
        data modifications.  If data is frequently added, deleted, or updated then
        optimize should be run frequently.  A good rule of thumb is to run optimize if
@@ -4742,7 +4684,7 @@ class AsyncTable:
        Parameters
        ----------
        **kwargs
-            Forwarded to `lance.dataset`.
+            Forwarded to [`lance.dataset`][lance.dataset].

        Returns
        -------
@@ -4918,46 +4860,6 @@ class AsyncTable:
                )
            raise e

-    async def create_index_async(
-        self,
-        column: str,
-        *,
-        replace: Optional[bool] = None,
-        config: Optional[
-            Union[
-                IvfFlat,
-                IvfPq,
-                IvfRq,
-                HnswPq,
-                HnswSq,
-                HnswFlat,
-                BTree,
-                Bitmap,
-                LabelList,
-                Fm,
-                FTS,
-            ]
-        ] = None,
-        wait_timeout: Optional[timedelta] = None,
-        name: Optional[str] = None,
-        train: bool = True,
-    ) -> AsyncJob:
-        """Create an index, returning a handle to the indexing job.
-
-        Takes the same arguments as :meth:`create_index`. The job may already
-        be complete when returned; callers must not assume the index exists
-        until :meth:`AsyncJob.wait` resolves.
-        """
-        job = await self._inner.create_index_async(
-            column,
-            index=config,
-            replace=replace,
-            wait_timeout=wait_timeout,
-            name=name,
-            train=train,
-        )
-        return AsyncJob(job)
-
    async def drop_index(self, name: str) -> None:
        """
        Drop an index from the table.
@@ -5101,7 +5003,7 @@ class AsyncTable:
        progress: Optional[Union[bool, Callable, Any]] = None,
        write_parallelism: Optional[int] = None,
    ) -> AddResult:
-        """Add more data to the [AsyncTable][lancedb.table.AsyncTable].
+        """Add more data to the [Table](Table).

        Parameters
        ----------
@@ -5303,8 +5205,8 @@ class AsyncTable:
        fts_columns: Optional[Union[str, List[str]]] = None,
    ) -> Union[AsyncHybridQuery, AsyncFTSQuery, AsyncVectorQuery]:
        """Create a search query to find the nearest neighbors
-        of the given query vector. We currently support [vector search](https://lancedb.com/docs/search/vector-search/)
-        and [full-text search](https://lancedb.com/docs/search/full-text-search/).
+        of the given query vector. We currently support [vector search][search]
+        and [full-text search][experimental-full-text-search].

        All query options are defined in [AsyncQuery][lancedb.query.AsyncQuery].

@@ -5865,14 +5767,15 @@ class AsyncTable:
        change permanent you can use the `[Self::restore]` method.

        Any operation that modifies the table will fail while the table is in a checked
-        out state. To return the table to a normal state use
-        `[Self::checkout_latest]`.
+        out state.

        Parameters
        ----------
        version: int | str,
            The version to check out. A version number (`int`) or a tag
            (`str`) can be provided.
+
+        To return the table to a normal state use `[Self::checkout_latest]`
        """
        try:
            await self._inner.checkout(version)
@@ -6056,8 +5959,6 @@ class AsyncTable:
        retrain: bool, default False
            This parameter is no longer used and is deprecated.

-        Notes
-        -----
        The frequency an application should call optimize is based on the frequency of
        data modifications.  If data is frequently added, deleted, or updated then
        optimize should be run frequently.  A good rule of thumb is to run optimize if
@@ -6438,8 +6339,6 @@ class Branches:
        dry_run: bool, default False
            When True, only preview. When False, attempt the merge.

-        Notes
-        -----
        A rejected merge returns ``status="rejected"`` instead of raising.
        """
        return LOOP.run(self._table.branches.merge(from_branch, dry_run))
@@ -395,11 +395,6 @@ def _(value: dict):
    )


-@value_to_sql.register(pa.Scalar)
-def _(value: pa.Scalar):
-    return value_to_sql(value.as_py())
-
-
@value_to_sql.register(np.ndarray)
 def _(value: np.ndarray):
    return value_to_sql(value.tolist())
@@ -226,13 +226,13 @@ def test_fetch_blob_ranges_validates_requests():
    table = _blob_table("range_validation", [{"id": 1, "image": b"abc"}])
    row_id = _row_ids_by_id(table)[1]

-    with pytest.raises(ValueError, match="exceeds blob size"):
+    with pytest.raises(RuntimeError, match="exceeds blob size"):
        table.fetch_blob_ranges("image", [(row_id, 2, 2)])

-    with pytest.raises(ValueError, match="offset \\+ length overflowed"):
+    with pytest.raises(RuntimeError, match="offset \\+ length overflowed"):
        table.fetch_blob_ranges("image", [(row_id, 2**64 - 1, 1)])

-    with pytest.raises(ValueError, match="row IDs"):
+    with pytest.raises(ValueError, match="row ids"):
        table.fetch_blob_ranges("image", [(2**64 - 1, 0, 1)])


@@ -2,7 +2,6 @@
 # SPDX-FileCopyrightText: Copyright The LanceDB Authors


-import inspect
 import re
 import sys
 from datetime import timedelta
@@ -63,44 +62,6 @@ def test_basic(tmp_path):
    assert db.open_table("test").name == db["test"].name


-def test_sync_debugger_inspection_does_not_use_background_loop(tmp_path, monkeypatch):
-    from lancedb.background_loop import LOOP
-
-    db = lancedb.connect(tmp_path)
-    table = db.create_table("test", data=[{"id": 1}])
-
-    def fail_run(*args, **kwargs):
-        raise AssertionError("debugger inspection should not use the background loop")
-
-    monkeypatch.setattr(LOOP, "run", fail_run)
-
-    # Debuggers enumerate and evaluate every exposed attribute when expanding a
-    # variable. This must remain safe while their breakpoint suspends LOOP's thread.
-    members = dict(inspect.getmembers(db))
-
-    assert members["uri"] == str(tmp_path)
-    assert members["read_consistency_interval"] is None
-    assert repr(db) == f"LanceDBConnection(uri={str(tmp_path)!r})"
-    assert repr(table) == f"LanceTable(name='test', _conn={db!r})"
-
-
-def test_read_consistency_interval_does_not_use_background_loop(tmp_path, monkeypatch):
-    from lancedb.background_loop import LOOP
-    from lancedb.db import LanceDBConnection
-
-    consistency_interval = timedelta(seconds=5)
-    db = lancedb.connect(tmp_path, read_consistency_interval=consistency_interval)
-    db_from_inner = LanceDBConnection.from_inner(db._inner, consistency_interval)
-
-    def fail_run(*args, **kwargs):
-        raise AssertionError("properties should not use the Python background loop")
-
-    monkeypatch.setattr(LOOP, "run", fail_run)
-
-    assert db.read_consistency_interval == consistency_interval
-    assert db_from_inner.read_consistency_interval == consistency_interval
-
-
 def test_ingest_pd(tmp_path):
    db = lancedb.connect(tmp_path)

@@ -64,23 +64,6 @@ def test_embedding_function(tmp_path):
    assert np.allclose(actual, expected)


-def test_instructor_ndims_uses_instruction():
-    instructor = get_registry().get("instructor").create()
-    model = MagicMock()
-    model.encode.return_value = np.zeros((1, 384))
-
-    with patch.object(type(instructor), "get_model", return_value=model):
-        assert instructor.ndims() == 384
-
-    model.encode.assert_called_once_with(
-        [[instructor.source_instruction, "foo"]],
-        batch_size=instructor.batch_size,
-        show_progress_bar=instructor.show_progress_bar,
-        normalize_embeddings=instructor.normalize_embeddings,
-        device=instructor.device,
-    )
-
-
 def test_embedding_function_variables():
    @register("variable-testing")
    class VariableTestingFunction(TextEmbeddingFunction):
@@ -132,16 +115,34 @@ def test_embedding_function_variables():
    assert func.safe_model_dump()["secret_key"] == "$var:secret"


-def test_openai_variables_survive_metadata_round_trip():
+def test_parse_functions_with_variables():
+    @register("variable-parsing-test")
+    class VariableParsingFunction(TextEmbeddingFunction):
+        api_key: str
+        base_url: Optional[str] = None
+
+        @staticmethod
+        def sensitive_keys():
+            return ["api_key"]
+
+        def ndims(self):
+            return 10
+
+        def generate_embeddings(self, texts):
+            # Mock implementation that just returns random embeddings
+            # In real usage, this would use the api_key to call an API
+            return [np.random.rand(self.ndims()).tolist() for _ in texts]
+
    registry = EmbeddingFunctionRegistry.get_instance()

    registry.set_var("test_api_key", "sk-test-key-12345")
+    registry.set_var("test_base_url", "https://api.example.com")

    conf = EmbeddingFunctionConfig(
        source_column="text",
        vector_column="vector",
-        function=registry.get("openai").create(
-            api_key="$var:test_api_key", base_url="https://api.example.com"
+        function=registry.get("variable-parsing-test").create(
+            api_key="$var:test_api_key", base_url="$var:test_base_url"
        ),
    )

@@ -149,10 +150,7 @@ def test_openai_variables_survive_metadata_round_trip():

    # Create a mock arrow table with the metadata
    schema = pa.schema(
-        [
-            pa.field("text", pa.string()),
-            pa.field("vector", pa.list_(pa.float32(), 1536)),
-        ]
+        [pa.field("text", pa.string()), pa.field("vector", pa.list_(pa.float32(), 10))]
    )
    table = pa.table({"text": [], "vector": []}, schema=schema)
    table = table.replace_schema_metadata(metadata)
@@ -166,15 +164,13 @@ def test_openai_variables_survive_metadata_round_trip():

    assert parsed_func.api_key == "sk-test-key-12345"
    assert parsed_func.base_url == "https://api.example.com"
+
+    embeddings = parsed_func.generate_embeddings(["test text"])
+    assert len(embeddings) == 1
+    assert len(embeddings[0]) == 10
+
    assert parsed_func.safe_model_dump()["api_key"] == "$var:test_api_key"

-    with patch("lancedb.embeddings.openai.attempt_import_or_raise") as import_openai:
-        parsed_func._openai_client
-
-    import_openai.return_value.OpenAI.assert_called_once_with(
-        api_key="sk-test-key-12345", base_url="https://api.example.com"
-    )
-

 def test_embedding_with_bad_results(tmp_path):
    @register("null-embedding")
@@ -219,13 +219,11 @@ def test_create_inverted_index(table, with_position):
        table.create_fts_index(
            "text",
            with_position=with_position,
-            custom_stop_words=["puppy"],
            name="custom_fts_index",
        )
    indices = table.list_indices()
    fts_indices = [i for i in indices if i.index_type == "FTS"]
    assert any(i.name == "custom_fts_index" for i in fts_indices)
-    assert fts_indices[0].index_details["custom_stop_words"] == ["puppy"]


@pytest.mark.parametrize("block_size", [128, 256])
@@ -245,24 +243,6 @@ def test_create_inverted_index_rejects_invalid_block_size(table):
        table.create_index("text", config=FTS(block_size=129))


-def test_custom_stop_words_list(table):
-    table.create_index(
-        "text",
-        config=FTS(stem=False, custom_stop_words=["lance"]),
-    )
-
-    assert table.list_indices()[0].index_details["custom_stop_words"] == ["lance"]
-    tokens = table.tokenize("the lance data", column="text")
-    assert [token.text for token in tokens] == ["the", "data"]
-    empty_tokens = ldb.tokenize("the lance data", stem=False, custom_stop_words=[])
-    assert [token.text for token in empty_tokens] == ["the", "lance", "data"]
-    with pytest.raises(TypeError, match=r"custom_stop_words.*int"):
-        ldb.tokenize(
-            "the lance data",
-            custom_stop_words=["lance", 42],
-        )
-
-
 def test_search_fts(table):
    table.create_fts_index("text")
    results = table.search("puppy").select(["id", "text"]).limit(5).to_list()
@@ -12,7 +12,7 @@ import pyarrow.compute as pc
 import pytest
 import pytest_asyncio

-from lancedb.index import BTree, FTS, IvfPq
+from lancedb.index import FTS
 from lancedb.table import AsyncTable, Table


@@ -99,86 +99,6 @@ async def test_async_hybrid_query_filters(table: AsyncTable):
    assert result["text"].to_pylist() == ["cat", "b"]


-@pytest.mark.asyncio
-async def test_hybrid_query_with_stale_fixed_size_binary_prefilter(
-    tmpdir_factory,
-):
-    tmp_path = str(tmpdir_factory.mktemp("stale_scalar_prefilter"))
-    db = await lancedb.connect_async(tmp_path)
-
-    def fixed_size_binary(value: int) -> bytes:
-        return value.to_bytes(16, byteorder="big")
-
-    num_rows = 1000
-    data = pa.table(
-        {
-            "space_id": pa.array(
-                [fixed_size_binary(i) for i in range(num_rows)],
-                type=pa.binary(16),
-            ),
-            "text": ["book"] * num_rows,
-            "vector": pa.array(
-                [[float(i), float(i)] for i in range(num_rows)],
-                type=pa.list_(pa.float32(), 2),
-            ),
-        }
-    )
-    table = await db.create_table("test", data)
-    await table.create_index(
-        "vector", config=IvfPq(num_partitions=4, num_sub_vectors=2)
-    )
-    await table.create_index("space_id", config=BTree())
-    await table.create_index("text", config=FTS(with_position=False))
-
-    # Advance the search indices without advancing the scalar index. This is the
-    # state that previously let hybrid search use an incomplete scalar prefilter.
-    await table.add(data)
-    lance_dataset = await table.to_lance()
-    lance_dataset.optimize.optimize_indices(index_names=["vector_idx", "text_idx"])
-    await table.checkout_latest()
-
-    scalar_stats = await table.index_stats("space_id_idx")
-    assert scalar_stats is not None
-    assert scalar_stats.num_indexed_rows == num_rows
-    assert scalar_stats.num_unindexed_rows == num_rows
-
-    for index_name in ["vector_idx", "text_idx"]:
-        search_stats = await table.index_stats(index_name)
-        assert search_stats is not None
-        assert search_stats.num_indexed_rows == num_rows * 2
-        assert search_stats.num_unindexed_rows == 0
-
-    matching_ids = [5, 10, 15, 20, 25, 30]
-    literals = [
-        f"arrow_cast(0x{fixed_size_binary(i).hex()}, 'FixedSizeBinary(16)')"
-        for i in matching_ids
-    ]
-    predicate = f"space_id IN ({', '.join(literals)})"
-    expected_ids = sorted(fixed_size_binary(i) for i in matching_ids for _ in range(2))
-
-    vector_query = (
-        table.query().where(predicate).nearest_to([5.0, 5.0]).limit(num_rows * 2)
-    )
-    vector_results = await vector_query.to_arrow()
-    assert sorted(vector_results["space_id"].to_pylist()) == expected_ids
-
-    fts_query = (
-        table.query().where(predicate).nearest_to_text("book").limit(num_rows * 2)
-    )
-    fts_results = await fts_query.to_arrow()
-    assert sorted(fts_results["space_id"].to_pylist()) == expected_ids
-
-    hybrid_results = await (
-        table.query()
-        .where(predicate)
-        .nearest_to([5.0, 5.0])
-        .nearest_to_text("book")
-        .limit(num_rows * 2)
-        .to_arrow()
-    )
-    assert sorted(hybrid_results["space_id"].to_pylist()) == expected_ids
-
-
@pytest.mark.asyncio
 async def test_async_hybrid_query_default_limit(table: AsyncTable):
    # add 10 new rows
@@ -203,19 +123,6 @@ async def test_async_hybrid_query_default_limit(table: AsyncTable):
    assert texts.count("a") == 1


-def test_hybrid_query_minimum_nprobes_zero_raises(sync_table: Table):
-    # minimum_nprobes(0) must raise the same validation error a plain vector
-    # query raises, not silently no-op because 0 is falsy.
-    with pytest.raises(ValueError, match="minimum_nprobes must be greater than 0"):
-        (
-            sync_table.search(query_type="hybrid")
-            .vector([0.0, 0.4])
-            .text("dog")
-            .minimum_nprobes(0)
-            .to_arrow()
-        )
-
-
 def test_hybrid_query_distance_range(sync_table: Table):
    reranker = RRFReranker(return_score="all")
    result = (
@@ -1,33 +0,0 @@
-# SPDX-License-Identifier: Apache-2.0
-# SPDX-FileCopyrightText: Copyright The LanceDB Authors
-
-import re
-import shutil
-import subprocess
-import sys
-
-import lancedb._lancedb as _lancedb
-import pytest
-
-
-@pytest.mark.skipif(sys.platform != "linux", reason="ldd is Linux-specific")
-def test_native_extension_does_not_link_openssl():
-    """OpenSSL-linked wheels abort when imported on RHEL hosts in FIPS mode."""
-    ldd = shutil.which("ldd")
-    if ldd is None:
-        pytest.skip("ldd is not installed")
-
-    result = subprocess.run(
-        [ldd, _lancedb.__file__],
-        check=True,
-        capture_output=True,
-        text=True,
-    )
-    openssl_libraries = re.findall(
-        r"^\s*(lib(?:crypto|ssl)\S*)\s+=>", result.stdout, flags=re.MULTILINE
-    )
-
-    assert not openssl_libraries, (
-        "the LanceDB native extension must use rustls instead of linking OpenSSL: "
-        f"{openssl_libraries}"
-    )
@@ -84,15 +84,6 @@ async def binary_table(db_async):
    )


-@pytest.mark.asyncio
-async def test_create_index_async_returns_done_job(some_table: AsyncTable):
-    job = await some_table.create_index_async("id", config=BTree())
-    assert job.id is None
-    await job.wait()
-    assert len(await some_table.list_indices()) == 1
-    await job.cancel()
-
-
@pytest.mark.asyncio
 async def test_create_scalar_index(some_table: AsyncTable):
    # Can create
@@ -372,31 +363,6 @@ async def test_create_vector_index(some_table: AsyncTable):
    assert stats.num_indices == 1


-@pytest.mark.asyncio
-async def test_create_ivf_index_reports_unsplittable_partitions(db_async):
-    dim = 8
-    num_partitions = 300  # More than 256 selects hierarchical k-means.
-    base_vectors = [[float(row == column) for column in range(dim)] for row in range(5)]
-    vectors = pa.array(base_vectors * 200, pa.list_(pa.float32(), dim))
-    table = await db_async.create_table(
-        "unsplittable_partitions",
-        pa.table({"vector": vectors}),
-    )
-
-    error_pattern = (
-        rf"Cannot create {num_partitions} IVF partitions: k-means could only form"
-    )
-    with pytest.raises(RuntimeError, match=error_pattern):
-        await table.create_index(
-            "vector",
-            config=IvfFlat(
-                distance_type="dot",
-                num_partitions=num_partitions,
-                max_iterations=10,
-            ),
-        )
-
-
@pytest.mark.asyncio
 async def test_create_4bit_ivfpq_index(some_table: AsyncTable):
    # Can create
@@ -18,7 +18,6 @@ Tests verify:
 """

 import copy
-import os
 import shutil
 import sys
 import tempfile
@@ -240,7 +239,7 @@ def create_tracking_namespace(

    dir_props = {f"storage.{k}": v for k, v in storage_options_with_refresh.items()}

-    if os.path.isabs(bucket_name) or bucket_name.startswith("file://"):
+    if bucket_name.startswith("/") or bucket_name.startswith("file://"):
        dir_props["root"] = f"{bucket_name}/namespace_root"
    else:
        dir_props["root"] = f"s3://{bucket_name}/namespace_root"
@@ -768,70 +767,3 @@ def test_namespace_with_schema_only(s3_bucket: str, use_custom: bool):

    # Verify data was added
    assert table.count_rows() == 2
-
-
-@pytest.mark.parametrize("use_custom", [False, True], ids=["DirectoryNS", "CustomNS"])
-def test_namespace_exists(use_custom: bool):
-    """
-    Test namespace_exists returns True for existing and False for non-existent.
-    """
-    temp_dir = tempfile.mkdtemp()
-    try:
-        ns_client, _ = create_tracking_namespace(
-            bucket_name=temp_dir,
-            storage_options={},
-            credential_expires_in_seconds=3600,
-            use_custom=use_custom,
-        )
-        db = LanceNamespaceDBConnection(ns_client)
-
-        namespace_name = f"test_ns_{uuid.uuid4().hex[:8]}"
-        db.create_namespace([namespace_name])
-
-        # Existing namespace should return True
-        assert db.namespace_exists(namespace_id=[namespace_name]) is True
-
-        # Non-existent namespace should return False
-        assert db.namespace_exists(namespace_id=["nonexistent_ns"]) is False
-    finally:
-        shutil.rmtree(temp_dir, ignore_errors=True)
-
-
-@pytest.mark.parametrize("use_custom", [False, True], ids=["DirectoryNS", "CustomNS"])
-def test_table_exists(use_custom: bool):
-    """
-    Test table_exists returns True for existing table and False for non-existent.
-    """
-    temp_dir = tempfile.mkdtemp()
-    try:
-        ns_client, _ = create_tracking_namespace(
-            bucket_name=temp_dir,
-            storage_options={},
-            credential_expires_in_seconds=3600,
-            use_custom=use_custom,
-        )
-        db = LanceNamespaceDBConnection(ns_client)
-
-        namespace_name = f"test_ns_{uuid.uuid4().hex[:8]}"
-        db.create_namespace([namespace_name])
-
-        table_name = f"test_table_{uuid.uuid4().hex}"
-        namespace_path = [namespace_name]
-        schema = pa.schema(
-            [
-                pa.field("id", pa.int64()),
-                pa.field("vector", pa.list_(pa.float32(), 2)),
-                pa.field("text", pa.string()),
-            ]
-        )
-
-        db.create_table(table_name, schema=schema, namespace_path=namespace_path)
-
-        # Existing table should return True
-        table_id = namespace_path + [table_name]
-        assert db.table_exists(table_id=table_id) is True
-
-        # Non-existent table should return False
-        assert db.table_exists(table_id=namespace_path + ["nonexistent_table"]) is False
-    finally:
-        shutil.rmtree(temp_dir, ignore_errors=True)
@@ -1,42 +0,0 @@
-# SPDX-License-Identifier: Apache-2.0
-# SPDX-FileCopyrightText: Copyright The LanceDB Authors
-
-import importlib
-import re
-import sys
-from pathlib import Path
-
-import pytest
-
-
-def test_pyo3_abi_matches_minimum_supported_python():
-    project_dir = Path(__file__).parents[2]
-    pyproject = (project_dir / "pyproject.toml").read_text()
-    cargo_manifest = (project_dir / "Cargo.toml").read_text()
-
-    minimum_python = re.search(
-        r'^requires-python\s*=\s*">=(\d+)\.(\d+)"$', pyproject, re.MULTILINE
-    )
-    assert minimum_python is not None
-
-    major, minor = minimum_python.groups()
-    expected_abi = f"abi3-py{major}{minor}"
-    configured_abis = re.findall(r'"(abi3-py\d+)"', cargo_manifest)
-
-    assert configured_abis == [expected_abi, expected_abi], (
-        "the pyo3 runtime and build ABI features must both match requires-python"
-    )
-
-
-@pytest.mark.skipif(sys.platform != "win32", reason="Windows wheel regression test")
-def test_windows_wheel_tag_and_native_import():
-    project_dir = Path(__file__).parents[2]
-    wheels = list((project_dir.parent / "target" / "wheels").glob("lancedb-*.whl"))
-    if not wheels:
-        pytest.skip("no wheel artifact is available in this development environment")
-
-    assert len(wheels) == 1
-    assert wheels[0].name.endswith("-cp310-abi3-win_amd64.whl")
-
-    native_module = importlib.import_module("lancedb._lancedb")
-    assert Path(native_module.__file__).suffix == ".pyd"
@@ -6,7 +6,6 @@ import math
 import pytest

 from lancedb import DBConnection, Table, connect
-from lancedb.background_loop import LOOP
 from lancedb.permutation import Permutation, Permutations, permutation_builder


@@ -32,25 +31,6 @@ def test_split_random_ratios(mem_db):
    assert 65 <= split_1_count <= 75  # ~70% ± tolerance


-def test_execute_does_not_reenter_background_loop(tmp_path, monkeypatch):
-    import threading
-
-    db = connect(tmp_path)
-    tbl = db.create_table("test_table", pa.table({"x": range(10)}))
-    original_run = LOOP.run
-
-    def fail_on_reentry(future):
-        assert threading.current_thread() is not LOOP.thread
-        return original_run(future)
-
-    monkeypatch.setattr(LOOP, "run", fail_on_reentry)
-
-    permutation_tbl = permutation_builder(tbl).execute()
-
-    assert permutation_tbl.count_rows() == 10
-    assert permutation_tbl._conn.read_consistency_interval is None
-
-
 def test_split_random_counts(mem_db):
    """Test random splitting with absolute counts."""
    tbl = mem_db.create_table(
@@ -35,12 +35,6 @@ def make_mock_http_handler(handler):
    return MockLanceDBHandler


-@pytest.mark.parametrize("db_name", ["a" * 64, "invalid..database"])
-def test_connect_rejects_invalid_cloud_dns_hostname(db_name):
-    with pytest.raises(ValueError, match="DNS labels must contain 1 to 63 bytes"):
-        lancedb.connect(f"db://{db_name}", api_key="fake")
-
-
@contextlib.contextmanager
 def mock_lancedb_connection(handler):
    with http.server.HTTPServer(
@@ -777,7 +771,6 @@ def test_table_create_indices():
                "text",
                wait_timeout=timedelta(seconds=2),
                block_size=256,
-                custom_stop_words=["cloud"],
                name="custom_fts_idx",
            )

@@ -802,7 +795,6 @@ def test_table_create_indices():
        assert "name" in fts_req
        assert fts_req["name"] == "custom_fts_idx"
        assert fts_req["block_size"] == 256
-        assert fts_req["custom_stop_words"] == ["cloud"]

        # Check vector index request has custom name
        vector_req = received_requests[2]
@@ -818,121 +810,6 @@ def test_table_create_indices():
        table.drop_index("custom_fts_idx")


-def test_remote_create_index_async_returns_job():
-    from lancedb.index import BTree
-
-    describe_calls = []
-
-    def handler(request):
-        content_len = int(request.headers.get("Content-Length", 0))
-        body = request.rfile.read(content_len) if content_len > 0 else b""
-        if request.path == "/v1/table/test/create_index/":
-            request.send_response(200)
-            request.send_header("Content-Type", "application/json")
-            request.end_headers()
-            request.wfile.write(b'{"job_id": "job-1"}')
-        elif request.path == "/v1/jobs/describe":
-            assert json.loads(body)["job_id"] == "job-1"
-            describe_calls.append(1)
-            state = "IN_PROGRESS" if len(describe_calls) == 1 else "DONE"
-            request.send_response(200)
-            request.send_header("Content-Type", "application/json")
-            request.end_headers()
-            request.wfile.write(
-                json.dumps(dict(job_id="job-1", job_state=state)).encode()
-            )
-        elif request.path == "/v1/jobs/cancel":
-            assert json.loads(body)["job_id"] == "job-1"
-            request.send_response(200)
-            request.send_header("Content-Type", "application/json")
-            request.end_headers()
-            request.wfile.write(b"{}")
-        elif request.path == "/v1/table/test/create/?mode=create":
-            request.send_response(200)
-            request.send_header("Content-Type", "application/json")
-            request.end_headers()
-            request.wfile.write(b"{}")
-        elif request.path == "/v1/table/test/describe/":
-            request.send_response(200)
-            request.send_header("Content-Type", "application/json")
-            request.end_headers()
-            request.wfile.write(
-                json.dumps(
-                    dict(
-                        version=1,
-                        schema=dict(
-                            fields=[
-                                dict(name="id", type={"type": "int64"}, nullable=False),
-                            ]
-                        ),
-                    )
-                ).encode()
-            )
-        else:
-            request.send_response(404)
-            request.end_headers()
-
-    with mock_lancedb_connection(handler) as db:
-        table = db.create_table("test", [{"id": 1}])
-        job = table.create_index_async("id", config=BTree())
-        assert job.id == "job-1"
-        job.wait(timeout=timedelta(seconds=30))
-        assert len(describe_calls) == 2
-        job.cancel()
-
-
-def test_remote_job_wait_raises_on_failure():
-    from lancedb.exceptions import JobFailedError
-    from lancedb.index import BTree
-
-    def handler(request):
-        content_len = int(request.headers.get("Content-Length", 0))
-        body = request.rfile.read(content_len) if content_len > 0 else b""
-        if request.path == "/v1/table/test/create_index/":
-            request.send_response(200)
-            request.send_header("Content-Type", "application/json")
-            request.end_headers()
-            request.wfile.write(b'{"job_id": "job-2"}')
-        elif request.path == "/v1/jobs/describe":
-            assert json.loads(body)["job_id"] == "job-2"
-            request.send_response(200)
-            request.send_header("Content-Type", "application/json")
-            request.end_headers()
-            request.wfile.write(
-                json.dumps(dict(job_id="job-2", job_state="FAILED")).encode()
-            )
-        elif request.path == "/v1/table/test/create/?mode=create":
-            request.send_response(200)
-            request.send_header("Content-Type", "application/json")
-            request.end_headers()
-            request.wfile.write(b"{}")
-        elif request.path == "/v1/table/test/describe/":
-            request.send_response(200)
-            request.send_header("Content-Type", "application/json")
-            request.end_headers()
-            request.wfile.write(
-                json.dumps(
-                    dict(
-                        version=1,
-                        schema=dict(
-                            fields=[
-                                dict(name="id", type={"type": "int64"}, nullable=False),
-                            ]
-                        ),
-                    )
-                ).encode()
-            )
-        else:
-            request.send_response(404)
-            request.end_headers()
-
-    with mock_lancedb_connection(handler) as db:
-        table = db.create_table("test", [{"id": 1}])
-        job = table.create_index_async("id", config=BTree())
-        with pytest.raises(JobFailedError, match="job-2"):
-            job.wait()
-
-
 def test_remote_create_index_new_api():
    received_requests = []

@@ -1141,7 +1018,7 @@ def query_test_table(query_handler, *, server_version=Version("0.1.0")):
            request.send_header("Content-Type", "application/json")
            request.send_header("phalanx-version", str(server_version))
            request.end_headers()
-            request.wfile.write(b'{"version": 1, "schema": {"fields": []}}')
+            request.wfile.write(b"{}")
        elif request.path == "/v1/table/test/query/":
            content_len = int(request.headers.get("Content-Length"))
            body = request.rfile.read(content_len)
@@ -1979,330 +1856,3 @@ def test_inherited_remote_table_reopens_after_fork():
    finally:
        server.shutdown()
        server_thread.join()
-
-
-BLOB_DESCRIBE_RESPONSE = {
-    "table": "test",
-    "version": 1,
-    "schema": {
-        "fields": [
-            {"name": "id", "type": {"type": "int64"}, "nullable": False},
-            {
-                "name": "image",
-                "type": {
-                    "type": "struct",
-                    "fields": [
-                        {
-                            "name": "data",
-                            "type": {"type": "large_binary"},
-                            "nullable": True,
-                        },
-                        {"name": "uri", "type": {"type": "string"}, "nullable": True},
-                    ],
-                },
-                "nullable": True,
-                "metadata": {
-                    "ARROW:extension:name": "lance.blob.v2",
-                    "ARROW:extension:metadata": "",
-                },
-            },
-        ]
-    },
-}
-
-
-def blob_query_response_table():
-    image_field = pa.field(
-        "image",
-        pa.struct(
-            [
-                pa.field("kind", pa.uint8(), nullable=False),
-                pa.field("position", pa.uint64(), nullable=False),
-                pa.field("size", pa.uint64(), nullable=False),
-                pa.field("blob_id", pa.uint32(), nullable=False),
-                pa.field("blob_uri", pa.string(), nullable=False),
-            ]
-        ),
-        metadata={"lance-encoding:blob": "true"},
-    )
-    images = pa.StructArray.from_arrays(
-        [
-            pa.array([1, 0, 0], type=pa.uint8()),
-            pa.array([0, 0, 0], type=pa.uint64()),
-            pa.array([5, 0, 5], type=pa.uint64()),
-            pa.array([1, 0, 2], type=pa.uint32()),
-            pa.array(["", "", ""], type=pa.string()),
-        ],
-        fields=image_field.type,
-        mask=pa.array([False, True, False]),
-    )
-    return pa.Table.from_arrays(
-        [
-            pa.array([1, 2, 3], type=pa.int64()),
-            images,
-            pa.array([10, 20, 30], type=pa.uint64()),
-        ],
-        schema=pa.schema(
-            [
-                pa.field("id", pa.int64(), nullable=False),
-                image_field,
-                pa.field("_rowid", pa.uint64()),
-            ]
-        ),
-    )
-
-
-@contextlib.contextmanager
-def blob_remote_table(*, server_version=Version("0.5.0")):
-    def handler(request):
-        if request.path == "/v1/table/test/describe/":
-            request.send_response(200)
-            request.send_header("Content-Type", "application/json")
-            request.send_header("phalanx-version", str(server_version))
-            request.end_headers()
-            request.wfile.write(json.dumps(BLOB_DESCRIBE_RESPONSE).encode())
-        elif request.path.startswith("/v1/table/test/blob/image/"):
-            path = request.path.partition("?")[0]
-            row_id = int(path.split("/")[-2])
-            payload = {10: b"alpha", 20: None, 30: b"gamma"}[row_id]
-            if payload is None:
-                request.send_response(204)
-                request.end_headers()
-                return
-            byte_range = request.headers["Range"].removeprefix("bytes=")
-            start_text, end_text = byte_range.split("-", maxsplit=1)
-            start = int(start_text)
-            end = int(end_text) if end_text else len(payload) - 1
-            chunk = payload[start : end + 1]
-            request.send_response(206)
-            request.send_header("Content-Range", f"bytes {start}-{end}/{len(payload)}")
-            request.send_header("Content-Length", str(len(chunk)))
-            request.end_headers()
-            request.wfile.write(chunk)
-        elif request.path == "/v1/table/test/query/":
-            content_len = int(request.headers.get("Content-Length", 0))
-            body = json.loads(request.rfile.read(content_len))
-            assert body["columns"] == ["id", "image"]
-            assert body["with_row_id"] is True
-            response_table = blob_query_response_table()
-            request.send_response(200)
-            request.send_header("Content-Type", "application/vnd.apache.arrow.file")
-            request.end_headers()
-            with pa.ipc.new_file(request.wfile, response_table.schema) as writer:
-                writer.write_table(response_table)
-        elif request.path == "/v1/table/test/fetch_blobs/":
-            content_len = int(request.headers.get("Content-Length", 0))
-            body = json.loads(request.rfile.read(content_len))
-            assert body["column"] == "image"
-            assert body["row_ids"] == [10, 20, 30]
-            response_table = pa.table(
-                {"image": pa.array([b"alpha", None, b"gamma"], type=pa.large_binary())}
-            )
-            request.send_response(200)
-            request.send_header("Content-Type", "application/vnd.apache.arrow.stream")
-            request.end_headers()
-            with pa.ipc.new_stream(request.wfile, response_table.schema) as writer:
-                writer.write_table(response_table)
-        else:
-            request.send_response(404)
-            request.end_headers()
-
-    with mock_lancedb_connection(handler) as db:
-        yield db.open_table("test")
-
-
-def test_remote_blob_columns_and_fetch():
-    with blob_remote_table() as table:
-        assert table.blob_columns() == ["image"]
-        blobs = table.fetch_blobs("image", [10, 20, 30])
-        assert blobs.to_pylist() == [b"alpha", None, b"gamma"]
-
-
-def test_remote_blob_files_are_lazy_seekable_handles():
-    with blob_remote_table() as table:
-        files = table.fetch_blob_files("image", [10, 20, 30])
-
-        assert len(files) == 3
-        alpha, null_row, gamma = files
-        assert null_row is None
-        assert alpha is not None
-        assert gamma is not None
-        assert alpha.size() == 5
-        assert alpha.read_range(1, 3) == b"lph"
-        gamma.seek(2)
-        assert gamma.read() == b"mma"
-
-
-def test_remote_blob_fetch_accepts_query_table():
-    hits = pa.table({"_rowid": pa.array([10, 20, 30], type=pa.uint64())})
-
-    with blob_remote_table() as table:
-        blobs = table.fetch_blobs("image", hits)
-
-    assert blobs.to_pylist() == [b"alpha", None, b"gamma"]
-
-
-def test_remote_blob_query_stashes_row_ids_for_fetch():
-    with blob_remote_table() as table:
-        hits = table.search().select(["id", "image"]).limit(3).to_arrow()
-        assert "_rowid" not in hits.column_names
-        assert "_lance_row_id" in hits.schema.field("image").type.names
-        blobs = table.fetch_blobs("image", hits)
-
-    assert blobs.to_pylist() == [b"alpha", None, b"gamma"]
-
-
-def test_remote_blob_query_survives_a_server_that_ignores_the_row_id_request():
-    def handler(request):
-        if request.path == "/v1/table/test/describe/":
-            request.send_response(200)
-            request.send_header("Content-Type", "application/json")
-            request.send_header("phalanx-version", "0.5.0")
-            request.end_headers()
-            request.wfile.write(json.dumps(BLOB_DESCRIBE_RESPONSE).encode())
-        elif request.path == "/v1/table/test/query/":
-            content_len = int(request.headers.get("Content-Length", 0))
-            assert json.loads(request.rfile.read(content_len))["with_row_id"] is True
-            response_table = blob_query_response_table().drop_columns(["_rowid"])
-            request.send_response(200)
-            request.send_header("Content-Type", "application/vnd.apache.arrow.file")
-            request.end_headers()
-            with pa.ipc.new_file(request.wfile, response_table.schema) as writer:
-                writer.write_table(response_table)
-        else:
-            request.send_response(404)
-            request.end_headers()
-
-    with mock_lancedb_connection(handler) as db:
-        table = db.open_table("test")
-        hits = table.search().select(["id", "image"]).limit(3).to_arrow()
-
-        assert hits.column_names == ["id", "image"]
-        assert "_lance_row_id" not in hits.schema.field("image").type.names
-        with pytest.raises(ValueError, match="pass a list of row ids"):
-            table.fetch_blobs("image", hits)
-
-
-def test_remote_blob_byte_apis_not_supported_on_old_server():
-    with blob_remote_table(server_version=Version("0.1.0")) as table:
-        assert table.blob_columns() == ["image"]
-        with pytest.raises(NotImplementedError, match="not supported"):
-            table.fetch_blobs("image", [1])
-        with pytest.raises(NotImplementedError, match="not supported"):
-            table.fetch_blob_files("image", [1])
-
-
-def test_remote_connection_jobs_surface():
-    from lancedb.exceptions import JobFailedError
-
-    schema = pa.schema([("state", pa.string())])
-    batch = pa.record_batch([pa.array(["created", "done"])], schema=schema)
-    sink = pa.BufferOutputStream()
-    with pa.ipc.new_stream(sink, schema) as writer:
-        writer.write_batch(batch)
-    events_body = sink.getvalue().to_pybytes()
-
-    def handler(request):
-        content_len = int(request.headers.get("Content-Length", 0))
-        body = request.rfile.read(content_len) if content_len > 0 else b""
-        payload = json.loads(body) if body else {}
-        if request.path == "/v1/jobs/list":
-            if payload.get("page_token") is None:
-                rsp = dict(
-                    jobs=[
-                        dict(
-                            job_id="job-1",
-                            table="t1",
-                            job_type="create_index",
-                            state="in_progress",
-                            created_at_millis=1000,
-                        )
-                    ],
-                    page_token="next",
-                )
-            else:
-                assert payload["page_token"] == "next"
-                rsp = dict(
-                    jobs=[
-                        dict(
-                            job_id="job-2",
-                            table="t2",
-                            job_type="create_index",
-                            state="succeeded",
-                            created_at_millis=2000,
-                        )
-                    ]
-                )
-            request.send_response(200)
-            request.send_header("Content-Type", "application/json")
-            request.end_headers()
-            request.wfile.write(json.dumps(rsp).encode())
-        elif request.path == "/v1/jobs/describe":
-            if payload["job_id"] != "job-1":
-                request.send_response(404)
-                request.end_headers()
-                return
-            request.send_response(200)
-            request.send_header("Content-Type", "application/json")
-            request.end_headers()
-            request.wfile.write(
-                json.dumps(
-                    dict(
-                        job_id="job-1",
-                        job_type="create_index",
-                        job_state="FAILED",
-                        creation_ms=1000,
-                        spec=dict(column="vec"),
-                        failure=dict(
-                            phase="execute", message="worker died", retryable=True
-                        ),
-                    )
-                ).encode()
-            )
-        elif request.path == "/v1/jobs/cancel":
-            if payload["job_id"] != "job-1":
-                request.send_response(404)
-                request.end_headers()
-                return
-            request.send_response(200)
-            request.send_header("Content-Type", "application/json")
-            request.end_headers()
-            request.wfile.write(b'{"job_id": "job-1"}')
-        elif request.path == "/v1/jobs/query_events":
-            assert payload["job_id"] == "job-1"
-            request.send_response(200)
-            request.send_header("Content-Type", "application/vnd.apache.arrow.stream")
-            request.end_headers()
-            request.wfile.write(events_body)
-        else:
-            request.send_response(404)
-            request.end_headers()
-
-    with mock_lancedb_connection(handler) as db:
-        jobs = db.list_jobs()
-        assert [job.job_id for job in jobs] == ["job-1", "job-2"]
-        assert jobs[0].state == "running"
-        assert jobs[0].table == "t1"
-        assert jobs[1].state == "finished"
-
-        description = db.get_job("job-1")
-        assert description.job_type == "create_index"
-        assert description.state == "failed"
-        assert json.loads(description.spec_json) == {"column": "vec"}
-        assert description.failure.message == "worker died"
-        assert description.failure.retryable is True
-        assert db.get_job("missing") is None
-
-        assert db.cancel_job("job-1") is True
-        assert db.cancel_job("missing") is False
-
-        batches = db.job_history("job-1")
-        assert len(batches) == 1
-        assert batches[0].num_rows == 2
-        assert batches[0].column("state").to_pylist() == ["created", "done"]
-
-        job = db.job("job-1")
-        assert job.id == "job-1"
-        assert job.status() == "failed"
-        with pytest.raises(JobFailedError, match="worker died"):
-            job.wait(timeout=timedelta(seconds=5))
@@ -2,14 +2,10 @@
 # SPDX-FileCopyrightText: Copyright The LanceDB Authors


-import ctypes
-import gc
 import os
 import sys
 import threading
 import warnings
-import weakref
-from concurrent.futures import ThreadPoolExecutor
 from datetime import date, datetime, timedelta
 from time import sleep
 from typing import List
@@ -102,30 +98,6 @@ def test_basic(mem_db: DBConnection):
    assert table.to_arrow() == expected_data


-def test_search_preserves_nulls_from_sliced_arrow_table(mem_db: DBConnection):
-    data = pa.table(
-        {
-            "id": [0, 1, 2, 3, 4],
-            "score_cn": [None, 22, None, 5, 8],
-            "score_mt": [None, 42, None, 5, 8],
-            "vector": [
-                [20, 19, -1, -1],
-                [41, 38, 22, 42],
-                [10, 10, -1, -1],
-                [5, 5, 5, 5],
-                [8, 8, 8, 8],
-            ],
-        }
-    ).slice(1)
-
-    table = mem_db.create_table("sliced_nullable", data=data)
-    result = table.search([41, 38, 22, 42]).limit(1).to_arrow()
-
-    assert result["id"].to_pylist() == [1]
-    assert result["score_cn"].to_pylist() == [22]
-    assert result["score_mt"].to_pylist() == [42]
-
-
 def test_table_to_pandas_default_matches_arrow(tmp_db: DBConnection):
    pd = pytest.importorskip("pandas")
    data = pa.table({"id": [1, 2], "text": ["one", "two"]})
@@ -462,38 +434,6 @@ def test_add(mem_db: DBConnection):
    _add(table, schema)


-def test_add_releases_arrow_buffers_without_gc(mem_db: DBConnection):
-    """Regression test for https://github.com/lancedb/lancedb/issues/2512."""
-    schema = pa.schema([pa.field("x", pa.int64())])
-    table = mem_db.create_table("test_add_releases_arrow_buffers", schema=schema)
-
-    class BufferOwner:
-        def __init__(self, size: int):
-            self.memory = ctypes.create_string_buffer(size)
-
-    owner_refs = []
-    gc_was_enabled = gc.isenabled()
-    gc.disable()
-    try:
-        for _ in range(3):
-            size = 8 * 1024
-            owner = BufferOwner(size)
-            arrow_buffer = pa.foreign_buffer(
-                ctypes.addressof(owner.memory), size, owner
-            )
-            array = pa.Array.from_buffers(pa.int64(), 1024, [None, arrow_buffer])
-            batch = pa.RecordBatch.from_arrays([array], schema=schema)
-            owner_refs.append(weakref.ref(owner))
-
-            table.add(batch)
-            del batch, array, arrow_buffer, owner
-
-        assert all(owner_ref() is None for owner_ref in owner_refs)
-    finally:
-        if gc_was_enabled:
-            gc.enable()
-
-
 def test_add_write_parallelism(mem_db: DBConnection):
    schema = pa.schema([pa.field("id", pa.int64())])
    table = mem_db.create_table("test", schema=schema)
@@ -1462,15 +1402,6 @@ async def test_async_open_table_with_branch_version(tmp_path):
    assert await pinned.count_rows() == 4  # writable again


-def test_create_index_async_returns_done_job(mem_db: DBConnection):
-    table = mem_db.create_table("job_test", [{"id": i} for i in range(10)])
-    job = table.create_index_async("id", config=BTree())
-    assert job.id is None
-    job.wait()
-    assert len(table.list_indices()) == 1
-    job.cancel()
-
-
@patch("lancedb.table.AsyncTable.create_index")
 def test_create_index_method(mock_create_index, mem_db: DBConnection):
    table = mem_db.create_table(
@@ -1884,33 +1815,6 @@ def test_add_nullable_struct_with_none(mem_db: DBConnection):
    assert result.column("data").to_pylist() == [{"x": 1.0}, None]


-def test_read_mostly_null_list_v2_2_page_boundary(tmp_path):
-    # Regression test for #3194. This row/value count crosses a v2.2 structural
-    # encoding page boundary where Lance 3.0.0 sliced repetition/definition
-    # levels by row offset and decoded child arrays at different lengths.
-    num_rows = 64_885
-    num_values = 217
-    list_type = pa.list_(pa.float32())
-    source = pa.table(
-        {
-            "id": np.arange(num_rows, dtype=np.int64),
-            "coords": pa.array(
-                [[1.0, 2.0, 3.0, 4.0]] * num_values + [None] * (num_rows - num_values),
-                type=list_type,
-            ),
-        }
-    )
-    db = lancedb.connect(
-        tmp_path,
-        storage_options={"new_table_data_storage_version": "2.2"},
-    )
-    table = db.create_table("test_sparse_nullable_list", data=source)
-
-    result = table.search().select(["id", "coords"]).limit(num_rows).to_arrow()
-
-    assert result.equals(source)
-
-
 def test_add_with_integer_embeddings_preserves_casting(mem_db: DBConnection):
    class Schema(LanceModel):
        text: str
@@ -2211,27 +2115,6 @@ def test_delete(mem_db: DBConnection):
    assert table.to_arrow()["id"].to_pylist() == [1]


-def test_concurrent_deletes_are_thread_safe(mem_db: DBConnection):
-    num_workers = 8
-    table = mem_db.create_table(
-        "my_table", data=[{"id": row_id} for row_id in range(num_workers)]
-    )
-    barrier = threading.Barrier(num_workers)
-
-    def delete(row_id: int):
-        barrier.wait()
-        return table.delete(f"id = {row_id}")
-
-    with ThreadPoolExecutor(max_workers=num_workers) as pool:
-        results = list(pool.map(delete, range(num_workers)))
-
-    assert all(result.num_deleted_rows == 1 for result in results)
-    assert sorted(result.version for result in results) == list(
-        range(2, num_workers + 2)
-    )
-    assert table.count_rows() == 0
-
-
 def test_delete_expr(mem_db: DBConnection):
    table = mem_db.create_table(
        "my_table",
@@ -2282,20 +2165,6 @@ def test_update(mem_db: DBConnection):
    assert np.allclose(v, np.array([[1.2, 1.9], [1.1, 1.1]]))


-def test_update_with_arrow_scalar(mem_db: DBConnection):
-    schema = pa.schema({"id": pa.int64(), "vector": pa.list_(pa.float32(), 4)})
-    table = mem_db.create_table("my_table", schema=schema)
-    table.add([{"id": 1, "vector": [1.0, 2.0, 3.0, 4.0]}])
-
-    value = table.search().select(["vector"]).limit(1).to_arrow()["vector"][0]
-    assert isinstance(value, pa.FixedSizeListScalar)
-
-    result = table.update(where="id == 1", values={"vector": value})
-
-    assert result.rows_updated == 1
-    assert table.to_arrow()["vector"].to_pylist() == [[1.0, 2.0, 3.0, 4.0]]
-
-
 def test_update_types(mem_db: DBConnection):
    table = mem_db.create_table(
        "my_table",
@@ -2463,55 +2332,6 @@ def test_merge_insert(mem_db: DBConnection):
        )


-def test_merge_insert_nullable_pandas_into_pydantic_schema(mem_db: DBConnection):
-    # Regression test for https://github.com/lancedb/lancedb/issues/2366
-    pd = pytest.importorskip("pandas")
-
-    class Document(LanceModel):
-        id: int
-        title: str
-        content: str
-
-    table = mem_db.create_table("documents", schema=Document)
-    table.add(
-        pd.DataFrame(
-            {
-                "title": ["Old title", "Unchanged"],
-                "id": [2, 3],
-                "content": ["Old content", "Keep this"],
-            }
-        )
-    )
-
-    # Pandas produces nullable Arrow fields, in an order that differs from the
-    # non-nullable Pydantic schema. This is valid as long as the data has no nulls.
-    new_data = pd.DataFrame(
-        {
-            "title": ["Inserted", "Updated"],
-            "id": [1, 2],
-            "content": ["New row", "New content"],
-        }
-    )
-    result = (
-        table.merge_insert("id")
-        .when_matched_update_all()
-        .when_not_matched_insert_all()
-        .execute(new_data)
-    )
-
-    assert result.num_inserted_rows == 1
-    assert result.num_updated_rows == 1
-    expected = pa.Table.from_pylist(
-        [
-            {"id": 1, "title": "Inserted", "content": "New row"},
-            {"id": 2, "title": "Updated", "content": "New content"},
-            {"id": 3, "title": "Unchanged", "content": "Keep this"},
-        ],
-        schema=Document.to_arrow_schema(),
-    )
-    assert table.to_arrow().sort_by("id") == expected
-
-
 def test_merge_insert_by_source_delete_expr(mem_db: DBConnection):
    table = mem_db.create_table(
        "my_table",
@@ -2535,29 +2355,6 @@ def test_merge_insert_by_source_delete_expr(mem_db: DBConnection):
    assert table.to_arrow().sort_by("a") == expected


-def test_merge_insert_by_source_delete_reconfigure(mem_db: DBConnection):
-    # Calling when_not_matched_by_source_delete() again with no condition must
-    # widen the delete to unconditional, not keep the earlier condition around.
-    table = mem_db.create_table(
-        "my_table",
-        data=pa.table({"a": [1, 2, 3], "b": ["a", "b", "c"]}),
-    )
-    new_data = pa.table({"a": [2, 4], "b": ["x", "z"]})
-
-    merge_insert_res = (
-        table.merge_insert("a")
-        .when_matched_update_all()
-        .when_not_matched_insert_all()
-        .when_not_matched_by_source_delete("a > 2")
-        .when_not_matched_by_source_delete()
-        .execute(new_data)
-    )
-    assert merge_insert_res.num_deleted_rows == 2
-
-    expected = pa.table({"a": [2, 4], "b": ["x", "z"]})
-    assert table.to_arrow().sort_by("a") == expected
-
-
@pytest.mark.asyncio
 async def test_merge_insert_by_source_delete_expr_async(
    mem_db_async: AsyncConnection,
@@ -2612,36 +2409,6 @@ def test_merge_insert_subschema(mem_db: DBConnection, data_format):
    assert table.to_arrow().sort_by("id") == expected


-def test_repeated_partial_merge_insert_with_scalar_index(mem_db: DBConnection):
-    def make_batch(start: int) -> pa.Table:
-        return pa.table(
-            {
-                "id": [f"id-{i:04}" for i in range(start, start + 100)],
-                "category": ["A"] * 100,
-                "value_a": [float(i) for i in range(start, start + 100)],
-                "value_b": [float(i) / 10 for i in range(100)],
-            }
-        )
-
-    table = mem_db.create_table("my_table", data=make_batch(0))
-    table.add(make_batch(100))
-    table.add(make_batch(200))
-    table.create_index("id", config=BTree())
-
-    ids = [f"id-{i:04}" for i in range(100, 200)]
-    for value in (999.0, 888.0):
-        result = (
-            table.merge_insert("id")
-            .when_matched_update_all()
-            .execute(pa.table({"id": ids, "value_a": [value] * 100}))
-        )
-        assert result.num_updated_rows == 100
-
-    actual = table.to_arrow().sort_by("id")
-    assert actual.num_rows == 300
-    assert actual["value_a"].to_pylist()[100:200] == [888.0] * 100
-
-
@pytest.mark.asyncio
 async def test_merge_insert_async(mem_db_async: AsyncConnection):
    data = pa.table({"a": [1, 2, 3], "b": ["a", "b", "c"]})
@@ -3320,6 +3087,9 @@ def test_consistency(tmp_path, consistency_interval):

    db2 = lancedb.connect(tmp_path, read_consistency_interval=consistency_interval)
    table2 = db2.open_table("my_table")
+    if consistency_interval is not None:
+        assert "read_consistency_interval=datetime.timedelta(" in repr(db2)
+        assert "read_consistency_interval=datetime.timedelta(" in repr(table2)
    assert table2.version == table.version

    table.add([{"id": 1}])
@@ -3668,8 +3438,8 @@ def test_create_table_empty_list_no_schema_error(mem_db: DBConnection):
        mem_db.create_table("test_empty_no_schema", data=[])


-def test_create_table_without_data_with_vector_schema(tmp_path):
-    """Test exact scenario from issue #1968.
+def test_add_table_with_empty_embeddings(tmp_path):
+    """Test exact scenario from issue #1968

    Regression test for issue #1968:
    https://github.com/lancedb/lancedb/issues/1968
@@ -3681,9 +3451,6 @@ def test_create_table_without_data_with_vector_schema(tmp_path):
        embedding: Vector(16)

    table = db.create_table("test", schema=MySchema)
-    assert table.count_rows() == 0
-    assert table.schema == MySchema.to_arrow_schema()
-
    table.add(
        [{"text": "bar", "embedding": [0.1] * 16}],
        on_bad_vectors="drop",
@@ -75,22 +75,6 @@ class TestVoyageAIModelRegistration:
        with pytest.raises(ValueError, match="not supported"):
            func.ndims()

-    def test_voyage3_source_embeddings_use_text_api(self, mock_voyageai_client):
-        """Regression test for text table data being sent to the multimodal API."""
-        mock_voyageai_client.tokenize.return_value = [["hello", "world"]]
-        mock_voyageai_client.embed.return_value.embeddings = [[0.1] * 1024]
-
-        registry = get_registry()
-        func = registry.get("voyageai").create(name="voyage-3")
-
-        embeddings = func.compute_source_embeddings("hello world")
-
-        assert embeddings == [[0.1] * 1024]
-        mock_voyageai_client.embed.assert_called_once_with(
-            texts=["hello world"], model="voyage-3", input_type="document"
-        )
-        mock_voyageai_client.multimodal_embed.assert_not_called()
-
    @pytest.mark.parametrize(
        "model_name",
        [
@@ -13,11 +13,7 @@ use crate::{
    runtime::future_into_py,
    table::Table,
 };
-use arrow::{
-    datatypes::Schema,
-    ffi_stream::ArrowArrayStreamReader,
-    pyarrow::{FromPyArrow, ToPyArrow},
-};
+use arrow::{datatypes::Schema, ffi_stream::ArrowArrayStreamReader, pyarrow::FromPyArrow};
 use lancedb::{
    connection::Connection as LanceConnection,
    connection::NamespaceClientPushdownOperation,
@@ -28,7 +24,7 @@ use pyo3::{
    Bound, FromPyObject, Py, PyAny, PyRef, PyResult, Python,
    exceptions::{PyRuntimeError, PyValueError},
    pyclass, pyfunction, pymethods,
-    types::{PyDict, PyDictMethods, PyList, PyListMethods},
+    types::{PyDict, PyDictMethods},
 };

 #[pyclass]
@@ -540,55 +536,6 @@ impl Connection {
            })
        })
    }
-
-    pub fn job(&self, job_id: String) -> PyResult<crate::job::Job> {
-        let inner = self.get_inner()?.clone();
-        Ok(crate::job::Job::new(inner.job(job_id).infer_error()?))
-    }
-
-    pub fn list_jobs(self_: PyRef<'_, Self>) -> PyResult<Bound<'_, PyAny>> {
-        let inner = self_.get_inner()?.clone();
-        future_into_py(self_.py(), async move {
-            let jobs = inner.list_jobs().await.infer_error()?;
-            Ok(jobs
-                .into_iter()
-                .map(crate::job::JobInfo::from)
-                .collect::<Vec<_>>())
-        })
-    }
-
-    pub fn get_job(self_: PyRef<'_, Self>, job_id: String) -> PyResult<Bound<'_, PyAny>> {
-        let inner = self_.get_inner()?.clone();
-        future_into_py(self_.py(), async move {
-            let description = inner.get_job(&job_id).await.infer_error()?;
-            Ok(description.map(crate::job::JobDescription::from))
-        })
-    }
-
-    pub fn cancel_job(self_: PyRef<'_, Self>, job_id: String) -> PyResult<Bound<'_, PyAny>> {
-        let inner = self_.get_inner()?.clone();
-        future_into_py(self_.py(), async move {
-            inner.cancel_job(&job_id).await.infer_error()
-        })
-    }
-
-    #[pyo3(signature = (job_id=None))]
-    pub fn job_history(
-        self_: PyRef<'_, Self>,
-        job_id: Option<String>,
-    ) -> PyResult<Bound<'_, PyAny>> {
-        let inner = self_.get_inner()?.clone();
-        future_into_py(self_.py(), async move {
-            let batches = inner.job_history(job_id.as_deref()).await.infer_error()?;
-            Python::attach(|py| {
-                let list = PyList::empty(py);
-                for batch in batches {
-                    list.append(batch.to_pyarrow(py)?)?;
-                }
-                Ok(list.unbind())
-            })
-        })
-    }
 }

 #[pyfunction]
@@ -102,18 +102,6 @@ impl<T> PythonErrorExt<T> for std::result::Result<T, LanceError> {
                    err.setattr(intern!(py, "__cause__"), cause_err)?;
                    Err(PyErr::from_value(err))
                }),
-                LanceError::JobFailed { .. } => Python::attach(|py| {
-                    let cls = py
-                        .import(intern!(py, "lancedb.exceptions"))?
-                        .getattr(intern!(py, "JobFailedError"))?;
-                    Err(PyErr::from_value(cls.call1((err.to_string(),))?))
-                }),
-                LanceError::JobCancelled { .. } => Python::attach(|py| {
-                    let cls = py
-                        .import(intern!(py, "lancedb.exceptions"))?
-                        .getattr(intern!(py, "JobCancelledError"))?;
-                    Err(PyErr::from_value(cls.call1((err.to_string(),))?))
-                }),
                _ => self.runtime_error(),
            },
        }
@@ -59,8 +59,7 @@ pub fn extract_index_params(source: &Option<Bound<'_, PyAny>>) -> PyResult<Lance
                    .ascii_folding(params.ascii_folding)
                    .ngram_min_length(params.ngram_min_length)
                    .ngram_max_length(params.ngram_max_length)
-                    .ngram_prefix_only(params.prefix_only)
-                    .custom_stop_words(params.custom_stop_words);
+                    .ngram_prefix_only(params.prefix_only);
                let inner_opts = inner_opts
                    .block_size(params.block_size)
                    .map_err(|err| PyValueError::new_err(err.to_string()))?;
@@ -207,7 +206,6 @@ struct FtsParams {
    lower_case: bool,
    stem: bool,
    remove_stop_words: bool,
-    custom_stop_words: Option<Vec<String>>,
    ascii_folding: bool,
    ngram_min_length: u32,
    ngram_max_length: u32,
@@ -1,145 +0,0 @@
-// SPDX-License-Identifier: Apache-2.0
-// SPDX-FileCopyrightText: Copyright The LanceDB Authors
-
-use std::sync::Arc;
-
-use crate::runtime::future_into_py;
-use pyo3::{Bound, PyAny, PyRef, PyResult, pyclass, pymethods};
-
-use crate::error::PythonErrorExt;
-
-#[pyclass]
-pub struct Job {
-    inner: Arc<lancedb::Job>,
-}
-
-impl Job {
-    pub(crate) fn new(inner: lancedb::Job) -> Self {
-        Self {
-            inner: Arc::new(inner),
-        }
-    }
-}
-
-#[pymethods]
-impl Job {
-    #[getter]
-    pub fn id(&self) -> Option<String> {
-        self.inner.id().map(str::to_string)
-    }
-
-    pub fn status(self_: PyRef<'_, Self>) -> PyResult<Bound<'_, PyAny>> {
-        let inner = self_.inner.clone();
-        future_into_py(
-            self_.py(),
-            async move { inner.status().await.infer_error() },
-        )
-    }
-
-    pub fn wait(self_: PyRef<'_, Self>) -> PyResult<Bound<'_, PyAny>> {
-        let inner = self_.inner.clone();
-        future_into_py(self_.py(), async move {
-            inner.wait().await.infer_error()?;
-            Ok(())
-        })
-    }
-
-    pub fn cancel(self_: PyRef<'_, Self>) -> PyResult<Bound<'_, PyAny>> {
-        let inner = self_.inner.clone();
-        future_into_py(self_.py(), async move {
-            inner.cancel().await.infer_error()?;
-            Ok(())
-        })
-    }
-}
-
-/// A row from `Connection.list_jobs`: one server-side job.
-#[pyclass(get_all, skip_from_py_object)]
-#[derive(Clone)]
-pub struct JobInfo {
-    job_id: String,
-    table: String,
-    job_type: String,
-    state: String,
-    created_at_millis: i64,
-}
-
-#[pymethods]
-impl JobInfo {
-    fn __repr__(&self) -> String {
-        format!(
-            "JobInfo(job_id={:?}, table={:?}, job_type={:?}, state={:?}, created_at_millis={})",
-            self.job_id, self.table, self.job_type, self.state, self.created_at_millis
-        )
-    }
-}
-
-impl From<lancedb::database::JobInfo> for JobInfo {
-    fn from(info: lancedb::database::JobInfo) -> Self {
-        Self {
-            job_id: info.job_id,
-            table: info.table,
-            job_type: info.job_type,
-            state: info.state,
-            created_at_millis: info.created_at_millis,
-        }
-    }
-}
-
-/// The server's account of why a job failed.
-#[pyclass(get_all, skip_from_py_object)]
-#[derive(Clone)]
-pub struct JobFailureInfo {
-    phase: Option<String>,
-    message: Option<String>,
-    retryable: Option<bool>,
-}
-
-#[pymethods]
-impl JobFailureInfo {
-    fn __repr__(&self) -> String {
-        format!(
-            "JobFailureInfo(phase={:?}, message={:?}, retryable={:?})",
-            self.phase, self.message, self.retryable
-        )
-    }
-}
-
-/// A described job from `Connection.get_job`.
-#[pyclass(get_all, skip_from_py_object)]
-#[derive(Clone)]
-pub struct JobDescription {
-    job_id: String,
-    job_type: String,
-    state: String,
-    creation_ms: i64,
-    spec_json: Option<String>,
-    failure: Option<JobFailureInfo>,
-}
-
-#[pymethods]
-impl JobDescription {
-    fn __repr__(&self) -> String {
-        format!(
-            "JobDescription(job_id={:?}, job_type={:?}, state={:?}, creation_ms={})",
-            self.job_id, self.job_type, self.state, self.creation_ms
-        )
-    }
-}
-
-impl From<lancedb::database::JobDescription> for JobDescription {
-    fn from(description: lancedb::database::JobDescription) -> Self {
-        Self {
-            job_id: description.job_id,
-            job_type: description.job_type,
-            state: description.state,
-            creation_ms: description.creation_ms,
-            spec_json: (!description.spec.is_null()).then(|| description.spec.to_string()),
-            failure: description.failure.map(|failure| JobFailureInfo {
-                phase: failure.phase,
-                message: failure.message,
-                retryable: failure.retryable,
-            }),
-        }
-    }
-}
@@ -25,7 +25,6 @@ pub mod error;
 pub mod expr;
 pub mod header;
 pub mod index;
-pub mod job;
 pub mod namespace;
 pub mod oauth;
 pub mod otel;
@@ -45,10 +44,6 @@ pub fn _lancedb(_py: Python, m: &Bound<'_, PyModule>) -> PyResult<()> {
    m.add_class::<Connection>()?;
    m.add_class::<Session>()?;
    m.add_class::<Table>()?;
-    m.add_class::<crate::job::Job>()?;
-    m.add_class::<crate::job::JobInfo>()?;
-    m.add_class::<crate::job::JobDescription>()?;
-    m.add_class::<crate::job::JobFailureInfo>()?;
    m.add_class::<PyBlobFile>()?;
    m.add_class::<IndexConfig>()?;
    m.add_class::<Query>()?;
@@ -426,11 +426,9 @@ pub struct PyBlobFile {
 impl PyBlobFile {
    fn read_bytes(self_: PyRef<'_, Self>) -> PyResult<Py<PyBytes>> {
        let inner = self_.inner.clone();
-        let py = self_.py();
-        let bytes = py
-            .detach(move || block_on(async move { inner.read().await }))
+        let bytes = block_on(async move { inner.read().await })
            .map_err(|e| PyRuntimeError::new_err(format!("blob read failed: {e}")))?;
-        Ok(PyBytes::new(py, bytes.as_ref()).unbind())
+        Ok(PyBytes::new(self_.py(), bytes.as_ref()).unbind())
    }

    pub fn read(self_: PyRef<'_, Self>) -> PyResult<Bound<'_, PyAny>> {
@@ -446,32 +444,24 @@ impl PyBlobFile {

    fn close(self_: PyRef<'_, Self>) -> PyResult<()> {
        let inner = self_.inner.clone();
-        self_
-            .py()
-            .detach(move || block_on(async move { inner.close().await }))
+        block_on(async move { inner.close().await })
            .map_err(|e| PyRuntimeError::new_err(format!("blob close failed: {e}")))
    }

    fn is_closed(self_: PyRef<'_, Self>) -> bool {
        let inner = self_.inner.clone();
-        self_
-            .py()
-            .detach(move || block_on(async move { inner.is_closed().await }))
+        block_on(async move { inner.is_closed().await })
    }

    fn seek(self_: PyRef<'_, Self>, position: u64) -> PyResult<()> {
        let inner = self_.inner.clone();
-        self_
-            .py()
-            .detach(move || block_on(async move { inner.seek(position).await }))
+        block_on(async move { inner.seek(position).await })
            .map_err(|e| PyRuntimeError::new_err(format!("blob seek failed: {e}")))
    }

    fn tell(self_: PyRef<'_, Self>) -> PyResult<u64> {
        let inner = self_.inner.clone();
-        self_
-            .py()
-            .detach(move || block_on(async move { inner.tell().await }))
+        block_on(async move { inner.tell().await })
            .map_err(|e| PyRuntimeError::new_err(format!("blob tell failed: {e}")))
    }

@@ -485,20 +475,16 @@ impl PyBlobFile {
            .checked_add(length as u64)
            .ok_or_else(|| PyValueError::new_err("offset + length overflowed"))?;
        let inner = self_.inner.clone();
-        let py = self_.py();
-        let bytes = py
-            .detach(move || block_on(async move { inner.read_range(offset..end).await }))
+        let bytes = block_on(async move { inner.read_range(offset..end).await })
            .map_err(|e| PyRuntimeError::new_err(format!("blob read_range failed: {e}")))?;
-        Ok(PyBytes::new(py, bytes.as_ref()).unbind())
+        Ok(PyBytes::new(self_.py(), bytes.as_ref()).unbind())
    }

    fn read_up_to(self_: PyRef<'_, Self>, length: usize) -> PyResult<Py<PyBytes>> {
        let inner = self_.inner.clone();
-        let py = self_.py();
-        let bytes = py
-            .detach(move || block_on(async move { inner.read_up_to(length).await }))
-            .map_err(|e| PyRuntimeError::new_err(format!("blob read_up_to failed: {e}")))?;
-        Ok(PyBytes::new(py, bytes.as_ref()).unbind())
+        let bytes = block_on(async move { inner.read_up_to(length).await })
+            .map_err(|e| PyRuntimeError::new_err(format!("blob read failed: {e}")))?;
+        Ok(PyBytes::new(self_.py(), bytes.as_ref()).unbind())
    }
 }

@@ -534,7 +520,6 @@ impl From<LanceDbFtsToken> for FtsToken {
    lower_case = true,
    stem = true,
    remove_stop_words = true,
-    custom_stop_words = None,
    ascii_folding = true,
    ngram_min_length = 3,
    ngram_max_length = 3,
@@ -549,7 +534,6 @@ pub fn tokenize(
    lower_case: bool,
    stem: bool,
    remove_stop_words: bool,
-    custom_stop_words: Option<Vec<String>>,
    ascii_folding: bool,
    ngram_min_length: u32,
    ngram_max_length: u32,
@@ -571,8 +555,7 @@ pub fn tokenize(
        .ascii_folding(ascii_folding)
        .ngram_min_length(ngram_min_length)
        .ngram_max_length(ngram_max_length)
-        .ngram_prefix_only(prefix_only)
-        .custom_stop_words(custom_stop_words);
+        .ngram_prefix_only(prefix_only);
    let tokens = lancedb_tokenize(&query, &params).infer_error()?;
    Ok(tokens.into_iter().map(FtsToken::from).collect())
 }
@@ -745,9 +728,6 @@ impl Table {

    #[allow(private_interfaces)]
    pub fn delete(self_: PyRef<'_, Self>, condition: PredicateArg) -> PyResult<Bound<'_, PyAny>> {
-        // Do not hold the Python borrow across the await.  The cloned Rust table
-        // handle is thread-safe and allows deletes on the same Python table to
-        // run concurrently without PyO3 reporting "Already borrowed".
        let inner = self_.inner_ref()?.clone();
        future_into_py(self_.py(), async move {
            let result = match &condition {
@@ -822,37 +802,6 @@ impl Table {
        })
    }

-    #[pyo3(signature = (column, index=None, replace=None, wait_timeout=None, *, name=None, train=None))]
-    pub fn create_index_async<'a>(
-        self_: PyRef<'a, Self>,
-        column: String,
-        index: Option<Bound<'_, PyAny>>,
-        replace: Option<bool>,
-        wait_timeout: Option<Bound<'_, PyAny>>,
-        name: Option<String>,
-        train: Option<bool>,
-    ) -> PyResult<Bound<'a, PyAny>> {
-        let index = extract_index_params(&index)?;
-        let timeout = wait_timeout.map(|t| t.extract::<std::time::Duration>().unwrap());
-        let mut op = self_
-            .inner_ref()?
-            .create_index_with_timeout(&[column], index, timeout);
-        if let Some(replace) = replace {
-            op = op.replace(replace);
-        }
-        if let Some(name) = name {
-            op = op.name(name);
-        }
-        if let Some(train) = train {
-            op = op.train(train);
-        }
-
-        future_into_py(self_.py(), async move {
-            let job = op.execute_async().await.infer_error()?;
-            Ok(crate::job::Job::new(job))
-        })
-    }
-
    pub fn drop_index(self_: PyRef<'_, Self>, index_name: String) -> PyResult<Bound<'_, PyAny>> {
        let inner = self_.inner_ref()?.clone();
        future_into_py(self_.py(), async move {
@@ -1378,12 +1327,7 @@ impl Table {

        let inner = self_.inner_ref()?.clone();
        future_into_py(self_.py(), async move {
-            let result = inner
-                .add_columns()
-                .transform(definitions)
-                .execute()
-                .await
-                .infer_error()?;
+            let result = inner.add_columns(definitions, None).await.infer_error()?;
            Ok(AddColumnsResult::from(result))
        })
    }
@@ -1397,12 +1341,7 @@ impl Table {

        let inner = self_.inner_ref()?.clone();
        future_into_py(self_.py(), async move {
-            let result = inner
-                .add_columns()
-                .transform(transform)
-                .execute()
-                .await
-                .infer_error()?;
+            let result = inner.add_columns(transform, None).await.infer_error()?;
            Ok(AddColumnsResult::from(result))
        })
    }
@@ -1,2 +1,2 @@
 [toolchain]
-channel = "1.97.0"
+channel = "1.95.0"
@@ -49,8 +49,8 @@ lance-namespace = { workspace = true }
 lance-namespace-impls = { workspace = true }
 metrics = { workspace = true, optional = true }
 metrics-util = { workspace = true, optional = true }
-# Pin the GooseFS SDK to the version required by Lance's OpenDAL dependency.
-goosefs-sdk = { version = "=0.1.9", optional = true }
+# Pin the transitive GooseFS SDK until the 0.1.6 compile break is fixed upstream.
+goosefs-sdk = { version = "=0.1.5", optional = true }
 moka = { workspace = true }
 pin-project = { workspace = true }
 tokio = { version = "1.23", features = ["rt-multi-thread", "sync"] }
@@ -75,8 +75,6 @@ reqwest = { version = "0.12.0", default-features = false, features = [
    "http2",
    "json",
    "macos-system-configuration",
-    # Avoid linking OpenSSL into Python wheels, which breaks on FIPS hosts.
-    "rustls-tls-native-roots",
    "stream",
 ], optional = true }
 http = { version = "1", optional = true } # Matching what is in reqwest
@@ -76,12 +76,7 @@ async fn create_table(db: &Connection) -> Result<Table> {

 async fn create_index(table: &Table) -> Result<()> {
    table
-        .create_index(
-            &["doc"],
-            Index::FTS(
-                FtsIndexBuilder::default().custom_stop_words(Some(vec!["example".to_owned()])),
-            ),
-        )
+        .create_index(&["doc"], Index::FTS(FtsIndexBuilder::default()))
        .execute()
        .await?;
    Ok(())
@@ -9,7 +9,6 @@
 //!
 //! Blob tables require Lance file format >= 2.2 and stable row ids at create.

-use std::ops::Range;
 use std::sync::Arc;

 use arrow_array::LargeBinaryArray;
@@ -17,203 +16,11 @@ use arrow_array::builder::LargeBinaryBuilder;
 use arrow_schema::{DataType, Field, Schema};
 use lance::dataset::{BlobRangeRequest as LanceBlobRangeRequest, Dataset, WriteParams};
 use lance_arrow::FieldExt;
-use lance_file::version::LanceFileVersion;
-use lance_io::object_store::ObjectStore;
-use object_store::path::Path;
+use lance_encoding::version::LanceFileVersion;

 use crate::error::{Error, Result};

-/// Seekable handle for one blob value, backed by local storage or a remote
-/// HTTP byte-range endpoint.
-#[derive(Debug)]
-pub struct BlobFile {
-    inner: BlobFileInner,
-}
-
-#[derive(Debug)]
-enum BlobFileInner {
-    Native(lance::dataset::BlobFile),
-    #[cfg(feature = "remote")]
-    Remote(Box<crate::remote::table::blobs::RemoteBlobFile>),
-}
-
-impl From<lance::dataset::BlobFile> for BlobFile {
-    fn from(value: lance::dataset::BlobFile) -> Self {
-        Self {
-            inner: BlobFileInner::Native(value),
-        }
-    }
-}
-
-#[cfg(feature = "remote")]
-impl From<crate::remote::table::blobs::RemoteBlobFile> for BlobFile {
-    fn from(value: crate::remote::table::blobs::RemoteBlobFile) -> Self {
-        Self {
-            inner: BlobFileInner::Remote(Box::new(value)),
-        }
-    }
-}
-
-impl BlobFile {
-    /// Inline reader over a data-file slice.
-    pub fn new_inline(
-        object_store: Arc<ObjectStore>,
-        path: Path,
-        position: u64,
-        size: u64,
-    ) -> Self {
-        lance::dataset::BlobFile::new_inline(object_store, path, position, size).into()
-    }
-
-    /// Dedicated sidecar-file reader.
-    pub fn new_dedicated(object_store: Arc<ObjectStore>, path: Path, size: u64) -> Self {
-        lance::dataset::BlobFile::new_dedicated(object_store, path, size).into()
-    }
-
-    /// Packed reader for a slice in a shared sidecar.
-    pub fn new_packed(
-        object_store: Arc<ObjectStore>,
-        path: Path,
-        position: u64,
-        size: u64,
-    ) -> Self {
-        lance::dataset::BlobFile::new_packed(object_store, path, position, size).into()
-    }
-
-    /// External reader at a resolved object location.
-    pub fn new_external(
-        object_store: Arc<ObjectStore>,
-        path: Path,
-        uri: String,
-        position: u64,
-        size: u64,
-    ) -> Self {
-        lance::dataset::BlobFile::new_external(object_store, path, uri, position, size).into()
-    }
-
-    /// Close the handle.
-    pub async fn close(&self) -> lance_core::Result<()> {
-        match &self.inner {
-            BlobFileInner::Native(file) => file.close().await,
-            #[cfg(feature = "remote")]
-            BlobFileInner::Remote(file) => file.close().await,
-        }
-    }
-
-    /// Whether the handle is closed.
-    pub async fn is_closed(&self) -> bool {
-        match &self.inner {
-            BlobFileInner::Native(file) => file.is_closed().await,
-            #[cfg(feature = "remote")]
-            BlobFileInner::Remote(file) => file.is_closed(),
-        }
-    }
-
-    /// Read a range without moving the cursor.
-    pub async fn read_range(&self, range: Range<u64>) -> lance_core::Result<bytes::Bytes> {
-        match &self.inner {
-            BlobFileInner::Native(file) => file.read_range(range).await,
-            #[cfg(feature = "remote")]
-            BlobFileInner::Remote(file) => file.read_range(range).await,
-        }
-    }
-
-    /// Read ranges without moving the cursor.
-    pub async fn read_ranges(
-        &self,
-        ranges: &[Range<u64>],
-    ) -> lance_core::Result<Vec<bytes::Bytes>> {
-        match &self.inner {
-            BlobFileInner::Native(file) => file.read_ranges(ranges).await,
-            #[cfg(feature = "remote")]
-            BlobFileInner::Remote(file) => file.read_ranges(ranges).await,
-        }
-    }
-
-    /// Read from the cursor to the end.
-    pub async fn read(&self) -> lance_core::Result<bytes::Bytes> {
-        match &self.inner {
-            BlobFileInner::Native(file) => file.read().await,
-            #[cfg(feature = "remote")]
-            BlobFileInner::Remote(file) => file.read().await,
-        }
-    }
-
-    /// Read up to `len` bytes and advance the cursor.
-    pub async fn read_up_to(&self, len: usize) -> lance_core::Result<bytes::Bytes> {
-        match &self.inner {
-            BlobFileInner::Native(file) => file.read_up_to(len).await,
-            #[cfg(feature = "remote")]
-            BlobFileInner::Remote(file) => file.read_up_to(len).await,
-        }
-    }
-
-    /// Move the cursor to `new_cursor`.
-    pub async fn seek(&self, new_cursor: u64) -> lance_core::Result<()> {
-        match &self.inner {
-            BlobFileInner::Native(file) => file.seek(new_cursor).await,
-            #[cfg(feature = "remote")]
-            BlobFileInner::Remote(file) => file.seek(new_cursor).await,
-        }
-    }
-
-    /// Current cursor position.
-    pub async fn tell(&self) -> lance_core::Result<u64> {
-        match &self.inner {
-            BlobFileInner::Native(file) => file.tell().await,
-            #[cfg(feature = "remote")]
-            BlobFileInner::Remote(file) => file.tell().await,
-        }
-    }
-
-    /// Blob length in bytes.
-    pub fn size(&self) -> u64 {
-        match &self.inner {
-            BlobFileInner::Native(file) => file.size(),
-            #[cfg(feature = "remote")]
-            BlobFileInner::Remote(file) => file.size(),
-        }
-    }
-
-    /// Physical byte offset in the data file. `None` on remote handles. The
-    /// Cloud byte-range route does not expose storage layout.
-    pub fn position(&self) -> Option<u64> {
-        match &self.inner {
-            BlobFileInner::Native(file) => Some(file.position()),
-            #[cfg(feature = "remote")]
-            BlobFileInner::Remote(_) => None,
-        }
-    }
-
-    /// Path of the data file holding the blob. `None` on remote handles. The
-    /// Cloud byte-range route does not expose storage layout.
-    pub fn data_path(&self) -> Option<&Path> {
-        match &self.inner {
-            BlobFileInner::Native(file) => Some(file.data_path()),
-            #[cfg(feature = "remote")]
-            BlobFileInner::Remote(_) => None,
-        }
-    }
-
-    /// Native storage layout. `None` on remote handles. The Cloud byte-range
-    /// route does not expose layout.
-    pub fn kind(&self) -> Option<lance_core::datatypes::BlobKind> {
-        match &self.inner {
-            BlobFileInner::Native(file) => Some(file.kind()),
-            #[cfg(feature = "remote")]
-            BlobFileInner::Remote(_) => None,
-        }
-    }
-
-    /// External URI for native handles. Remote handles do not expose storage URIs.
-    pub fn uri(&self) -> Option<&str> {
-        match &self.inner {
-            BlobFileInner::Native(file) => file.uri(),
-            #[cfg(feature = "remote")]
-            BlobFileInner::Remote(_) => None,
-        }
-    }
-}
+pub use lance::dataset::BlobFile;

 /// One row-specific blob range read request.
 ///
@@ -457,10 +264,7 @@ pub(crate) async fn take_blob_files_aligned(

    let handles = dataset.take_blobs(row_ids, column).await?;
    ensure_all_row_ids_resolved(column, row_ids.len(), handles.len())?;
-    Ok(handles
-        .into_iter()
-        .map(|handle| handle.map(Into::into))
-        .collect())
+    Ok(handles)
 }

 #[cfg(test)]
@@ -23,8 +23,8 @@ use crate::connection::create_table::CreateTableBuilder;
 use crate::data::scannable::Scannable;
 use crate::database::listing::ListingDatabase;
 use crate::database::{
-    CloneTableRequest, Database, DatabaseOptions, JobDescription, JobInfo, OpenTableRequest,
-    ReadConsistency, TableNamesRequest,
+    CloneTableRequest, Database, DatabaseOptions, OpenTableRequest, ReadConsistency,
+    TableNamesRequest,
 };
 use crate::embeddings::{EmbeddingRegistry, MemoryRegistry};
 use crate::error::{Error, Result};
@@ -34,7 +34,7 @@ use crate::remote::{
    db::{OPT_REMOTE_API_KEY, OPT_REMOTE_HOST_OVERRIDE, OPT_REMOTE_REGION},
 };
 use lance::io::ObjectStoreParams;
-pub use lance_file::version::LanceFileVersion;
+pub use lance_encoding::version::LanceFileVersion;
 #[cfg(feature = "remote")]
 use lance_io::object_store::StorageOptions;
 use lance_io::object_store::{StorageOptionsAccessor, StorageOptionsProvider};
@@ -456,10 +456,6 @@ impl Connection {
    ///
    /// # Returns
    /// Created [`TableRef`], or [`Error::TableNotFound`] if the table does not exist.
-    /// If the table's storage is present but holds no readable dataset (for example a
-    /// `<name>.lance` directory left behind by an interrupted drop and re-create, which
-    /// [`Self::table_names`] still lists) this returns [`Error::TableCorrupted`]
-    /// instead.
    pub fn open_table(&self, name: impl Into<String>) -> OpenTableBuilder {
        OpenTableBuilder::new(
            self.internal.clone(),
@@ -517,39 +513,6 @@ impl Connection {
        self.internal.read_consistency().await
    }

-    /// A [`crate::job::Job`] handle for a server-side job by id, suitable for
-    /// waiting on or cancelling the job.
-    ///
-    /// The handle is constructed without a server round trip; an unknown id
-    /// surfaces when the handle is used. Only server-backed databases support
-    /// job handles by id.
-    pub fn job(&self, job_id: impl AsRef<str>) -> Result<crate::job::Job> {
-        self.internal.job(job_id.as_ref())
-    }
-
-    /// List server-side jobs across the database's tables.
-    pub async fn list_jobs(&self) -> Result<Vec<JobInfo>> {
-        self.internal.list_jobs().await
-    }
-
-    /// Describe a single server-side job by id. `None` when the server has no
-    /// such job.
-    pub async fn get_job(&self, job_id: impl AsRef<str>) -> Result<Option<JobDescription>> {
-        self.internal.get_job(job_id.as_ref()).await
-    }
-
-    /// Request cancellation of a server-side job by id. Returns true if the
-    /// server accepted the cancellation, false if no such job exists.
-    pub async fn cancel_job(&self, job_id: impl AsRef<str>) -> Result<bool> {
-        self.internal.cancel_job(job_id.as_ref()).await
-    }
-
-    /// The lifecycle event history of a server-side job (all jobs when
-    /// `job_id` is `None`), as recorded Arrow batches.
-    pub async fn job_history(&self, job_id: Option<&str>) -> Result<Vec<RecordBatch>> {
-        self.internal.job_history(job_id).await
-    }
-
    /// Drop a table in the database.
    ///
    /// # Arguments
@@ -202,17 +202,6 @@ mod tests {
        assert_eq!(table.count_rows(None).await.unwrap(), 0);
    }

-    #[tokio::test]
-    async fn create_table_in_named_memory_database() {
-        let db = connect("memory://foo").execute().await.unwrap();
-        let batch = record_batch!(("id", Int64, [1, 2, 3])).unwrap();
-
-        let table = db.create_table("my_table", batch).execute().await.unwrap();
-
-        assert_eq!(table.uri().await.unwrap(), "memory://foo/my_table.lance");
-        assert_eq!(table.count_rows(None).await.unwrap(), 3);
-    }
-
    async fn test_create_table_with_data<T>(data: T)
    where
        T: Scannable + 'static,
@@ -18,8 +18,6 @@ use std::collections::HashMap;
 use std::sync::Arc;
 use std::time::Duration;

-use arrow_array::RecordBatch;
-
 use lance::dataset::ReadParams;
 use lance_namespace::LanceNamespace;
 use lance_namespace::models::{
@@ -202,45 +200,6 @@ pub enum ReadConsistency {
    Strong,
 }

-/// A row from [`Database::list_jobs`]: one server-side job (index build,
-/// compaction, column refresh, ...).
-#[derive(Debug, Clone)]
-pub struct JobInfo {
-    /// The job id -- what [`Database::get_job`] and [`Database::cancel_job`]
-    /// accept.
-    pub job_id: String,
-    /// The table the job runs against, without URI or namespace.
-    pub table: String,
-    pub job_type: String,
-    /// Lifecycle state: "running", "finished", "failed", or "cancelled".
-    pub state: String,
-    /// When the job was created, in milliseconds since the epoch.
-    pub created_at_millis: i64,
-}
-
-/// A described job from [`Database::get_job`]: lifecycle state plus the
-/// job-type-specific specification.
-#[derive(Debug, Clone)]
-pub struct JobDescription {
-    pub job_id: String,
-    pub job_type: String,
-    /// Lifecycle state: "running", "finished", "failed", or "cancelled".
-    pub state: String,
-    /// When the job was created, in milliseconds since the epoch.
-    pub creation_ms: i64,
-    /// The job-type-specific specification. Null when the server omits it.
-    pub spec: serde_json::Value,
-    /// Why the job failed, when the job is failed and the server reports a
-    /// reason.
-    pub failure: Option<crate::error::JobFailure>,
-}
-
-fn job_op_not_supported<T>(what: &str) -> Result<T> {
-    Err(crate::error::Error::NotSupported {
-        message: format!("{} is not supported by this database", what),
-    })
-}
-
 /// The `Database` trait defines the interface for database implementations.
 ///
 /// A database is responsible for managing tables and their metadata.
@@ -286,31 +245,6 @@ pub trait Database:
    ///
    /// See [`CloneTableRequest`] for detailed documentation and examples.
    async fn clone_table(&self, request: CloneTableRequest) -> Result<Arc<dyn BaseTable>>;
-    /// A [`crate::job::Job`] handle for a server-side job by id, suitable for
-    /// waiting on or cancelling the job. The handle is constructed without a
-    /// server round trip; an unknown id surfaces when the handle is used.
-    fn job(&self, _job_id: &str) -> Result<crate::job::Job> {
-        job_op_not_supported("job")
-    }
-    /// List server-side jobs across the database's tables.
-    async fn list_jobs(&self) -> Result<Vec<JobInfo>> {
-        job_op_not_supported("list_jobs")
-    }
-    /// Describe a single job by id. `None` when the server has no such job.
-    async fn get_job(&self, _job_id: &str) -> Result<Option<JobDescription>> {
-        job_op_not_supported("get_job")
-    }
-    /// Request cancellation of a job by id. Returns true if the server
-    /// accepted the cancellation, false if no such job exists. Cancelling an
-    /// already-terminal job is a no-op success.
-    async fn cancel_job(&self, _job_id: &str) -> Result<bool> {
-        job_op_not_supported("cancel_job")
-    }
-    /// The lifecycle event history of a job (all jobs when `job_id` is
-    /// `None`), as recorded Arrow batches.
-    async fn job_history(&self, _job_id: Option<&str>) -> Result<Vec<RecordBatch>> {
-        job_op_not_supported("job_history")
-    }
    /// Open a table in the database
    async fn open_table(&self, request: OpenTableRequest) -> Result<Arc<dyn BaseTable>>;
    /// Rename a table in the database
@@ -12,7 +12,7 @@ use lance::dataset::refs::Ref;
 use lance::dataset::{ReadParams, WriteMode, builder::DatasetBuilder};
 use lance::io::{ObjectStore, ObjectStoreParams, WrappingObjectStore};
 use lance_datafusion::utils::StreamingWriteSource;
-use lance_file::version::LanceFileVersion;
+use lance_encoding::version::LanceFileVersion;
 use lance_io::object_store::{StorageOptionsAccessor, StorageOptionsProvider};
 use lance_table::io::commit::commit_handler_from_url;
 use object_store::local::LocalFileSystem;
@@ -1376,68 +1376,6 @@ mod tests {
        assert!(!tempdir.path().join("__manifest").exists());
    }

-    /// Regression test for https://github.com/lancedb/lancedb/issues/1600.
-    ///
-    /// Opening a table used to create a separate object-store client instead of
-    /// reusing the one that successfully connected to the database.  Repeating
-    /// credential discovery made S3 table opens intermittent, especially in AWS
-    /// Lambda, and the failed open was reported as `TableNotFound`.
-    #[tokio::test]
-    async fn test_open_table_reuses_connection_object_store() {
-        let tempdir = tempdir().unwrap();
-        let uri = tempdir.path().to_str().unwrap();
-        let registry = Arc::new(lance_io::object_store::ObjectStoreRegistry::default());
-        let session = Arc::new(lance::session::Session::new(16, 16, registry.clone()));
-
-        let request = ConnectRequest {
-            uri: uri.to_string(),
-            #[cfg(feature = "remote")]
-            client_config: Default::default(),
-            options: Default::default(),
-            namespace_client_properties: Default::default(),
-            manifest_enabled: false,
-            read_consistency_interval: None,
-            session: Some(session),
-        };
-        let db = ListingDatabase::connect_with_options(&request)
-            .await
-            .unwrap();
-
-        let schema = Arc::new(Schema::new(vec![Field::new("id", DataType::Int32, false)]));
-        db.create_table(CreateTableRequest {
-            name: "test".to_string(),
-            namespace_path: vec![],
-            data: Box::new(RecordBatch::new_empty(schema)) as Box<dyn Scannable>,
-            mode: CreateTableMode::Create,
-            write_options: Default::default(),
-            location: None,
-            namespace_client: None,
-        })
-        .await
-        .unwrap();
-
-        let before_open = registry.stats();
-        for _ in 0..3 {
-            let table = db
-                .open_table(OpenTableRequest {
-                    name: "test".to_string(),
-                    namespace_path: vec![],
-                    index_cache_size: None,
-                    lance_read_params: None,
-                    location: None,
-                    namespace_client: None,
-                    managed_versioning: None,
-                })
-                .await
-                .unwrap();
-            assert_eq!(table.count_rows(None).await.unwrap(), 0);
-        }
-
-        let after_open = registry.stats();
-        assert_eq!(after_open.misses, before_open.misses);
-        assert!(after_open.hits >= before_open.hits + 3);
-    }
-
    #[tokio::test]
    async fn test_clone_table_basic() {
        let (_tempdir, db) = setup_database().await;
@@ -201,7 +201,7 @@ impl LanceNamespaceDatabase {
        &self,
        request: &DbCreateTableRequest,
    ) -> Result<(
-        Option<lance_file::version::LanceFileVersion>,
+        Option<lance_encoding::version::LanceFileVersion>,
        Option<bool>,
        Option<bool>,
    )> {
@@ -214,7 +214,7 @@ impl LanceNamespaceDatabase {

        let storage_version_override = storage_options
            .and_then(|opts| opts.get(OPT_NEW_TABLE_STORAGE_VERSION))
-            .map(|s| s.parse::<lance_file::version::LanceFileVersion>())
+            .map(|s| s.parse::<lance_encoding::version::LanceFileVersion>())
            .transpose()?;

        let v2_manifest_override = storage_options
@@ -11,9 +11,7 @@ use lance_core::{cache::LanceCache, utils::futures::FinallyStreamExt};
 use lance_encoding::decoder::{DecoderPlugins, FilterExpression};
 use lance_file::{
    reader::{FileReader, FileReaderOptions},
-    version::ConcreteFileVersion,
-    versions,
-    writer::FileWriterOptions,
+    writer::{FileWriter, FileWriterOptions},
 };
 use lance_io::{
    ReadBatchParams,
@@ -154,12 +152,8 @@ impl Shuffler {
                    source: None,
                })?;
            let object_writer = object_store.create(&path).await?;
-            let writer = versions::create_writer(
-                ConcreteFileVersion::V2_1,
-                object_writer,
-                schema.clone(),
-                FileWriterOptions::default(),
-            )?;
+            let writer =
+                FileWriter::try_new(object_writer, schema.clone(), FileWriterOptions::default())?;
            file_writers.push(writer);
        }

@@ -264,7 +264,7 @@ pub fn compute_output_schema(
        let field_name = ed
            .dest_column
            .clone()
-            .unwrap_or_else(|| format!("{}_embedding", ed.source_column));
+            .unwrap_or_else(|| format!("{}_embedding", &ed.source_column));

        sb.push(Field::new(
            field_name,
@@ -291,7 +291,7 @@ pub fn compute_embeddings_for_batch(
        let dst_field_name = fld
            .dest_column
            .clone()
-            .unwrap_or_else(|| format!("{}_embedding", fld.source_column));
+            .unwrap_or_else(|| format!("{}_embedding", &fld.source_column));

        let dst_field = Field::new(
            dst_field_name,
@@ -315,7 +315,7 @@ impl<R: RecordBatchReader> WithEmbeddings<R> {
                let field_name = ed
                    .dest_column
                    .clone()
-                    .unwrap_or_else(|| format!("{}_embedding", ed.source_column));
+                    .unwrap_or_else(|| format!("{}_embedding", &ed.source_column));
                Ok(Field::new(
                    field_name,
                    func.dest_type()?.into_owned(),
@@ -1,8 +1,7 @@
 // SPDX-License-Identifier: Apache-2.0
 // SPDX-FileCopyrightText: Copyright The LanceDB Authors

-use std::fmt::{self, Display, Formatter};
-use std::sync::{Arc, PoisonError};
+use std::sync::PoisonError;

 use arrow_schema::ArrowError;
 use datafusion_common::DataFusionError;
@@ -10,46 +9,6 @@ use snafu::Snafu;

 pub(crate) type BoxError = Box<dyn std::error::Error + Send + Sync>;

-/// Why a job failed, to whatever precision the backend provides.
-///
-/// A job run in this process carries the error it failed with in [`Self::source`].
-/// A job run remotely carries whatever the server reported, which older servers
-/// do not report at all. Every field is absent rather than invented when the
-/// backend does not supply it.
-#[derive(Debug, Clone, Default)]
-pub struct JobFailure {
-    /// The stage the job was in, when known.
-    pub phase: Option<String>,
-    /// A human-readable reason, when known.
-    pub message: Option<String>,
-    /// Whether a retry could clear the failure, when known.
-    pub retryable: Option<bool>,
-    /// The error the job failed with, when it ran in this process.
-    pub source: Option<Arc<Error>>,
-}
-
-impl JobFailure {
-    /// A failure whose only known detail is the error that caused it.
-    pub(crate) fn from_source(source: Arc<Error>) -> Self {
-        Self {
-            message: Some(source.to_string()),
-            source: Some(source),
-            ..Default::default()
-        }
-    }
-}
-
-impl Display for JobFailure {
-    fn fmt(&self, f: &mut Formatter<'_>) -> fmt::Result {
-        match (&self.message, &self.phase) {
-            (Some(message), Some(phase)) => write!(f, ": {message} (in {phase})"),
-            (Some(message), None) => write!(f, ": {message}"),
-            (None, Some(phase)) => write!(f, " in {phase}"),
-            (None, None) => Ok(()),
-        }
-    }
-}
-
 #[derive(Debug, Snafu)]
 #[snafu(visibility(pub(crate)))]
 pub enum Error {
@@ -59,10 +18,6 @@ pub enum Error {
    InvalidInput { message: String },
    #[snafu(display("Table '{name}' was not found"))]
    TableNotFound { name: String, source: BoxError },
-    #[snafu(display(
-        "Table '{name}' exists but could not be loaded (it may be corrupt or incomplete): {source}"
-    ))]
-    TableCorrupted { name: String, source: BoxError },
    #[snafu(display("Database '{name}' was not found"))]
    DatabaseNotFound { name: String },
    #[snafu(display("Database '{name}' already exists."))]
@@ -85,13 +40,6 @@ pub enum Error {
    Runtime { message: String },
    #[snafu(display("Timeout error: {message}"))]
    Timeout { message: String },
-    #[snafu(display("Job{} failed{failure}", job_id.as_ref().map(|id| format!(" {id}")).unwrap_or_default()))]
-    JobFailed {
-        job_id: Option<String>,
-        failure: JobFailure,
-    },
-    #[snafu(display("Job{} was cancelled", job_id.as_ref().map(|id| format!(" {id}")).unwrap_or_default()))]
-    JobCancelled { job_id: Option<String> },

    // 3rd party / external errors
    #[snafu(display("object_store error: {source}"))]
@@ -173,9 +121,6 @@ impl From<lance::Error> for Error {
        match source {
            lance::Error::Wrapped { error, .. } => Self::from_box_error(error),
            lance::Error::External { source } => Self::from_box_error(source),
-            lance::Error::InvalidInput { source, .. } => Self::InvalidInput {
-                message: source.to_string(),
-            },
            _ => Self::Lance { source },
        }
    }
@@ -10,7 +10,7 @@ use std::time::Duration;
 use vector::IvfFlatIndexBuilder;

 use crate::index::vector::IvfRqIndexBuilder;
-use crate::{DistanceType, Error, Result, job::Job, table::BaseTable};
+use crate::{DistanceType, Error, Result, table::BaseTable};

 use self::{
    scalar::{BTreeIndexBuilder, BitmapIndexBuilder, FmIndexBuilder, LabelListIndexBuilder},
@@ -305,14 +305,6 @@ impl IndexBuilder {
    pub async fn execute(self) -> Result<()> {
        self.parent.clone().create_index(self).await
    }
-
-    /// Creates the index, returning a [`Job`] tracking the operation.
-    ///
-    /// The job may already be complete when returned, and callers must not
-    /// assume the index exists until [`Job::wait`] resolves.
-    pub async fn execute_async(self) -> Result<Job> {
-        self.parent.clone().create_index_async(self).await
-    }
 }

 #[derive(Debug, Clone, PartialEq, Deserialize)]
@@ -132,14 +132,9 @@ impl ObjectStore for MirroringObjectStore {
        if to.primary_only() {
            self.primary.copy_opts(from, to, options).await
        } else {
-            // The secondary store can be process-local and less durable than the
-            // primary, so a source written by another process may not exist here
-            // or may be evicted before the copy begins.
-            match self.secondary.copy_opts(from, to, options.clone()).await {
-                Ok(()) | Err(Error::NotFound { .. }) => {}
-                Err(err) => return Err(err),
-            }
-            self.primary.copy_opts(from, to, options).await
+            self.secondary.copy_opts(from, to, options.clone()).await?;
+            self.primary.copy_opts(from, to, options).await?;
+            Ok(())
        }
    }
 }
@@ -197,8 +192,7 @@ mod test {
    use futures::TryStreamExt;
    use lance::{dataset::WriteParams, io::ObjectStoreParams};
    use lance_testing::datagen::{BatchGenerator, IncrementingInt32, RandomVector};
-    use object_store::{local::LocalFileSystem, memory::InMemory};
-    use std::time::Duration;
+    use object_store::local::LocalFileSystem;
    use tempfile;

    use crate::{
@@ -207,139 +201,6 @@ mod test {
        table::WriteOptions,
    };

-    #[derive(Debug)]
-    struct EvictBeforeCopyStore {
-        inner: Arc<dyn ObjectStore>,
-    }
-
-    impl std::fmt::Display for EvictBeforeCopyStore {
-        fn fmt(&self, f: &mut Formatter<'_>) -> std::fmt::Result {
-            write!(f, "EvictBeforeCopyStore")
-        }
-    }
-
-    #[async_trait]
-    impl ObjectStore for EvictBeforeCopyStore {
-        async fn put_opts(
-            &self,
-            location: &Path,
-            payload: PutPayload,
-            options: PutOptions,
-        ) -> Result<PutResult> {
-            self.inner.put_opts(location, payload, options).await
-        }
-
-        async fn put_multipart_opts(
-            &self,
-            location: &Path,
-            options: PutMultipartOptions,
-        ) -> Result<Box<dyn MultipartUpload>> {
-            self.inner.put_multipart_opts(location, options).await
-        }
-
-        async fn get_opts(&self, location: &Path, options: GetOptions) -> Result<GetResult> {
-            self.inner.get_opts(location, options).await
-        }
-
-        fn delete_stream(
-            &self,
-            locations: BoxStream<'static, Result<Path>>,
-        ) -> BoxStream<'static, Result<Path>> {
-            self.inner.delete_stream(locations)
-        }
-
-        fn list(&self, prefix: Option<&Path>) -> BoxStream<'static, Result<ObjectMeta>> {
-            self.inner.list(prefix)
-        }
-
-        async fn list_with_delimiter(&self, prefix: Option<&Path>) -> Result<ListResult> {
-            self.inner.list_with_delimiter(prefix).await
-        }
-
-        async fn copy_opts(&self, from: &Path, to: &Path, options: CopyOptions) -> Result<()> {
-            self.inner.delete(from).await?;
-            self.inner.copy_opts(from, to, options).await
-        }
-    }
-
-    #[tokio::test]
-    async fn test_copy_when_source_is_missing_from_secondary() {
-        let primary_dir = tempfile::tempdir().unwrap();
-        let secondary_dir = tempfile::tempdir().unwrap();
-        let primary: Arc<dyn ObjectStore> =
-            Arc::new(LocalFileSystem::new_with_prefix(primary_dir.path()).unwrap());
-        let secondary: Arc<dyn ObjectStore> =
-            Arc::new(LocalFileSystem::new_with_prefix(secondary_dir.path()).unwrap());
-        let store = MirroringObjectStore {
-            primary: primary.clone(),
-            secondary: secondary.clone(),
-        };
-        let staging = Path::from("_versions/1.manifest-staging");
-        let finalized = Path::from("_versions/1.manifest");
-
-        primary
-            .put(&staging, "manifest contents".into())
-            .await
-            .unwrap();
-
-        tokio::time::timeout(Duration::from_secs(5), store.copy(&staging, &finalized))
-            .await
-            .expect("copy should not hang when the secondary source is missing")
-            .unwrap();
-
-        let copied = primary
-            .get(&finalized)
-            .await
-            .unwrap()
-            .bytes()
-            .await
-            .unwrap();
-        assert_eq!(copied, "manifest contents");
-        assert!(matches!(
-            secondary.head(&finalized).await,
-            Err(Error::NotFound { .. })
-        ));
-    }
-
-    #[tokio::test]
-    async fn test_copy_when_secondary_source_disappears_after_head() {
-        let primary: Arc<dyn ObjectStore> = Arc::new(InMemory::new());
-        let secondary_inner: Arc<dyn ObjectStore> = Arc::new(InMemory::new());
-        let secondary: Arc<dyn ObjectStore> = Arc::new(EvictBeforeCopyStore {
-            inner: secondary_inner.clone(),
-        });
-        let store = MirroringObjectStore {
-            primary: primary.clone(),
-            secondary,
-        };
-        let staging = Path::from("_versions/1.manifest-staging");
-        let finalized = Path::from("_versions/1.manifest");
-
-        primary
-            .put(&staging, "manifest contents".into())
-            .await
-            .unwrap();
-        secondary_inner
-            .put(&staging, "manifest contents".into())
-            .await
-            .unwrap();
-
-        store.copy(&staging, &finalized).await.unwrap();
-
-        let copied = primary
-            .get(&finalized)
-            .await
-            .unwrap()
-            .bytes()
-            .await
-            .unwrap();
-        assert_eq!(copied, "manifest contents");
-        assert!(matches!(
-            secondary_inner.head(&finalized).await,
-            Err(Error::NotFound { .. })
-        ));
-    }
-
    // This test is ignored because lance 3.0 introduced LocalWriter optimization
    // that bypasses the object store wrapper for local writes. The mirroring feature
    // still works for remote/cloud storage, but can't be tested with local storage.
@@ -1,182 +0,0 @@
-// SPDX-License-Identifier: Apache-2.0
-// SPDX-FileCopyrightText: Copyright The LanceDB Authors
-
-//! Handles to operations a server may run asynchronously.
-
-use std::sync::Arc;
-
-use async_trait::async_trait;
-use tokio::sync::watch;
-use tokio::task::{AbortHandle, JoinHandle};
-
-use crate::error::{Error, JobFailure, Result};
-
-/// Backend-specific tracking for an asynchronous operation.
-#[async_trait]
-pub(crate) trait JobHandle: Send + Sync {
-    /// Server-assigned id, when the backend has one.
-    fn id(&self) -> Option<&str> {
-        None
-    }
-    async fn status(&self) -> Result<String>;
-    async fn wait(&self) -> Result<()>;
-    async fn cancel(&self) -> Result<()>;
-}
-
-/// A handle to an operation that may still be running.
-///
-/// The operation may already be complete when the handle is created.
-pub struct Job {
-    handle: Option<Box<dyn JobHandle>>,
-}
-
-impl std::fmt::Debug for Job {
-    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
-        f.debug_struct("Job")
-            .field("id", &self.id())
-            .field("done", &self.handle.is_none())
-            .finish()
-    }
-}
-
-impl Job {
-    /// A job whose operation finished before the handle was created.
-    pub(crate) fn new_done() -> Self {
-        Self { handle: None }
-    }
-
-    pub(crate) fn new(handle: Box<dyn JobHandle>) -> Self {
-        Self {
-            handle: Some(handle),
-        }
-    }
-
-    /// A job running as a task in this process.
-    pub(crate) fn spawned(task: JoinHandle<Result<()>>) -> Self {
-        Self::new(Box::new(SpawnedJob::new(task)))
-    }
-
-    /// Identifies the operation on the server that is running it.
-    ///
-    /// Returned for correlating with server logs or the jobs API. Operations
-    /// that run in this process have no server id and return `None`. The
-    /// value is opaque: parsing it or storing it to resume the job later is
-    /// not supported.
-    pub fn id(&self) -> Option<&str> {
-        self.handle.as_ref().and_then(|handle| handle.id())
-    }
-
-    /// The operation's current lifecycle state: "running", "finished",
-    /// "failed", or "cancelled".
-    ///
-    /// A point snapshot; unlike [`Job::wait`] it does not block, raise on a
-    /// terminal failure state, or retry. States a newer server reports that
-    /// this client version does not know pass through as-is.
-    pub async fn status(&self) -> Result<String> {
-        match &self.handle {
-            None => Ok("finished".to_string()),
-            Some(handle) => handle.status().await,
-        }
-    }
-
-    /// Waits until the operation reaches a terminal state.
-    ///
-    /// Returns [`crate::Error::JobFailed`] if the operation failed and
-    /// [`crate::Error::JobCancelled`] if it was cancelled.
-    pub async fn wait(&self) -> Result<()> {
-        match &self.handle {
-            None => Ok(()),
-            Some(handle) => handle.wait().await,
-        }
-    }
-
-    /// Requests cancellation of the operation.
-    ///
-    /// Cancelling an operation that already finished is a no-op.
-    pub async fn cancel(&self) -> Result<()> {
-        match &self.handle {
-            None => Ok(()),
-            Some(handle) => handle.cancel().await,
-        }
-    }
-}
-
-/// How an in-process operation ended. Cloneable so every waiter can be given
-/// the outcome; [`Error`] is not, so failures share one behind an [`Arc`].
-#[derive(Clone)]
-enum Outcome {
-    Succeeded,
-    Failed(Arc<Error>),
-    Cancelled,
-}
-
-impl Outcome {
-    fn into_result(self) -> Result<()> {
-        match self {
-            Self::Succeeded => Ok(()),
-            Self::Failed(source) => Err(Error::JobFailed {
-                job_id: None,
-                failure: JobFailure::from_source(source),
-            }),
-            Self::Cancelled => Err(Error::JobCancelled { job_id: None }),
-        }
-    }
-}
-
-/// Tracks an operation running as a task in this process. A second task
-/// watches the first so that aborting it still produces an outcome, and so
-/// that every caller of `wait` observes the same one.
-struct SpawnedJob {
-    outcome: watch::Receiver<Option<Outcome>>,
-    abort: AbortHandle,
-}
-
-impl SpawnedJob {
-    fn new(task: JoinHandle<Result<()>>) -> Self {
-        let abort = task.abort_handle();
-        let (tx, outcome) = watch::channel(None);
-        tokio::spawn(async move {
-            let outcome = match task.await {
-                Ok(Ok(())) => Outcome::Succeeded,
-                Ok(Err(err)) => Outcome::Failed(Arc::new(err)),
-                Err(err) if err.is_cancelled() => Outcome::Cancelled,
-                Err(err) => Outcome::Failed(Arc::new(Error::Runtime {
-                    message: format!("index job task failed: {err}"),
-                })),
-            };
-            let _ = tx.send(Some(outcome));
-        });
-        Self { outcome, abort }
-    }
-}
-
-#[async_trait]
-impl JobHandle for SpawnedJob {
-    async fn status(&self) -> Result<String> {
-        let label = match &*self.outcome.borrow() {
-            None => "running",
-            Some(Outcome::Succeeded) => "finished",
-            Some(Outcome::Failed(_)) => "failed",
-            Some(Outcome::Cancelled) => "cancelled",
-        };
-        Ok(label.to_string())
-    }
-
-    async fn wait(&self) -> Result<()> {
-        let mut outcome = self.outcome.clone();
-        let settled = outcome
-            .wait_for(|outcome| outcome.is_some())
-            .await
-            .map_err(|_| Error::Runtime {
-                message: "index job outcome was dropped before it completed".to_string(),
-            })?
-            .clone()
-            .expect("wait_for returns once an outcome is set");
-        settled.into_result()
-    }
-
-    async fn cancel(&self) -> Result<()> {
-        self.abort.abort();
-        Ok(())
-    }
-}
@@ -184,7 +184,6 @@ pub mod expr;
 pub mod index;
 pub mod io;
 pub mod ipc;
-pub mod job;
 #[cfg(feature = "metrics-otel")]
 pub mod metrics_otel;
 #[cfg(feature = "polars")]
@@ -204,8 +203,7 @@ use serde::{Deserialize, Serialize};

 pub use blob::{BlobRangeRequest, blob, is_blob};
 pub use connection::{ConnectNamespaceBuilder, Connection};
-pub use error::{Error, JobFailure, Result};
-pub use job::Job;
+pub use error::{Error, Result};
 use lance_index::vector::ApproxMode as LanceApproxMode;
 use lance_linalg::distance::DistanceType as LanceDistanceType;
 /// Re-export of the [`metrics`](https://docs.rs/metrics) crate facade. Enable
@@ -1661,8 +1661,14 @@ mod tests {

    #[tokio::test]
    async fn test_setters_getters() {
+        // TODO: Switch back to memory://foo after https://github.com/lancedb/lancedb/issues/1051
+        // is fixed
+        let tmp_dir = tempdir().unwrap();
+        let dataset_path = tmp_dir.path().join("test.lance");
+        let uri = dataset_path.to_str().unwrap();
+
        let batches = make_test_batches();
-        let conn = connect("memory://foo").execute().await.unwrap();
+        let conn = connect(uri).execute().await.unwrap();
        let table = conn
            .create_table("my_table", batches)
            .execute()
@@ -1757,8 +1763,14 @@ mod tests {

    #[tokio::test]
    async fn test_execute() {
+        // TODO: Switch back to memory://foo after https://github.com/lancedb/lancedb/issues/1051
+        // is fixed
+        let tmp_dir = tempdir().unwrap();
+        let dataset_path = tmp_dir.path().join("test.lance");
+        let uri = dataset_path.to_str().unwrap();
+
        let batches = make_non_empty_batches();
-        let conn = connect("memory://foo").execute().await.unwrap();
+        let conn = connect(uri).execute().await.unwrap();
        let table = conn
            .create_table("my_table", batches)
            .execute()
@@ -1877,8 +1889,14 @@ mod tests {

    #[tokio::test]
    async fn test_select_with_transform() {
+        // TODO: Switch back to memory://foo after https://github.com/lancedb/lancedb/issues/1051
+        // is fixed
+        let tmp_dir = tempdir().unwrap();
+        let dataset_path = tmp_dir.path().join("test.lance");
+        let uri = dataset_path.to_str().unwrap();
+
        let batches = make_non_empty_batches();
-        let conn = connect("memory://foo").execute().await.unwrap();
+        let conn = connect(uri).execute().await.unwrap();
        let table = conn
            .create_table("my_table", batches)
            .execute()
@@ -1975,9 +1993,15 @@ mod tests {

    #[tokio::test]
    async fn test_execute_no_vector() {
+        // TODO: Switch back to memory://foo after https://github.com/lancedb/lancedb/issues/1051
+        // is fixed
+        let tmp_dir = tempdir().unwrap();
+        let dataset_path = tmp_dir.path().join("test.lance");
+        let uri = dataset_path.to_str().unwrap();
+
        // test that it's ok to not specify a query vector (just filter / limit)
        let batches = make_non_empty_batches();
-        let conn = connect("memory://foo").execute().await.unwrap();
+        let conn = connect(uri).execute().await.unwrap();
        let table = conn
            .create_table("my_table", batches)
            .execute()
@@ -8,13 +8,13 @@

 pub(crate) mod client;
 pub(crate) mod db;
-pub(crate) mod job;
 pub mod oauth;
 mod retry;
 pub(crate) mod table;
 pub(crate) mod util;

 const ARROW_STREAM_CONTENT_TYPE: &str = "application/vnd.apache.arrow.stream";
+#[cfg(test)]
 const ARROW_FILE_CONTENT_TYPE: &str = "application/vnd.apache.arrow.file";
 #[cfg(test)]
 const JSON_CONTENT_TYPE: &str = "application/json";
--- a/Show More
+++ b/Show More