Bump version: 0.31.0-beta.1 → 0.31.0-beta.2

## Summary
- Bump Lance Rust workspace dependencies from `5.0.0-beta.5` to
`5.1.0-beta.2` using `ci/set_lance_version.py`.
- Update Java `lance-core.version` in `java/pom.xml` to `5.1.0-beta.2`.
- Refresh `Cargo.lock` to match the new Lance tag.

## Verification
- `cargo clippy --workspace --tests --all-features -- -D warnings`
(passes)
- `cargo fmt --all` (passes)

## Triggering Tag
- https://github.com/lance-format/lance/releases/tag/v5.1.0-beta.2

.bumpversion.toml

@@ -1,5 +1,5 @@
 [tool.bumpversion]
-current_version = "0.27.2"
+current_version = "0.28.0-beta.1"
 parse = """(?x)
     (?P<major>0|[1-9]\\d*)\\.
     (?P<minor>0|[1-9]\\d*)\\.

.github/workflows/nodejs.yml

@@ -8,6 +8,7 @@ on:
     paths:
       - Cargo.toml
       - Cargo.lock
+      - rust-toolchain.toml
       - nodejs/**
       - rust/**
       - docs/src/js/**

.github/workflows/python.yml

@@ -8,6 +8,7 @@ on:
     paths:
       - Cargo.toml
       - Cargo.lock
+      - rust-toolchain.toml
       - python/**
       - rust/**
       - .github/workflows/python.yml

.github/workflows/rust.yml

@@ -8,6 +8,7 @@ on:
     paths:
       - Cargo.toml
       - Cargo.lock
+      - rust-toolchain.toml
       - rust/**
       - .github/workflows/rust.yml
 

Cargo.lock

@@ -3072,8 +3072,8 @@ checksum = "42703706b716c37f96a77aea830392ad231f44c9e9a67872fa5548707e11b11c"
 
 [[package]]
 name = "fsst"
-version = "5.0.0-beta.4"
+version = "5.1.0-beta.2"
-source = "git+https://github.com/lance-format/lance.git?tag=v5.0.0-beta.4#d9068e76a301df9e21d7282419f24f61a11375ac"
+source = "git+https://github.com/lance-format/lance.git?tag=v5.1.0-beta.2#df61d95cac9ab579e4bc4ff41d1bd749b24af7f0"
 dependencies = [
  "arrow-array",
  "rand 0.9.2",
@@ -4134,13 +4134,14 @@ dependencies = [
 
 [[package]]
 name = "lance"
-version = "5.0.0-beta.4"
+version = "5.1.0-beta.2"
-source = "git+https://github.com/lance-format/lance.git?tag=v5.0.0-beta.4#d9068e76a301df9e21d7282419f24f61a11375ac"
+source = "git+https://github.com/lance-format/lance.git?tag=v5.1.0-beta.2#df61d95cac9ab579e4bc4ff41d1bd749b24af7f0"
 dependencies = [
  "arrow",
  "arrow-arith",
  "arrow-array",
  "arrow-buffer",
+ "arrow-cast",
  "arrow-ipc",
  "arrow-ord",
  "arrow-row",
@@ -4201,13 +4202,14 @@ dependencies = [
 
 [[package]]
 name = "lance-arrow"
-version = "5.0.0-beta.4"
+version = "5.1.0-beta.2"
-source = "git+https://github.com/lance-format/lance.git?tag=v5.0.0-beta.4#d9068e76a301df9e21d7282419f24f61a11375ac"
+source = "git+https://github.com/lance-format/lance.git?tag=v5.1.0-beta.2#df61d95cac9ab579e4bc4ff41d1bd749b24af7f0"
 dependencies = [
  "arrow-array",
  "arrow-buffer",
  "arrow-cast",
  "arrow-data",
+ "arrow-ipc",
  "arrow-ord",
  "arrow-schema",
  "arrow-select",
@@ -4222,8 +4224,8 @@ dependencies = [
 
 [[package]]
 name = "lance-bitpacking"
-version = "5.0.0-beta.4"
+version = "5.1.0-beta.2"
-source = "git+https://github.com/lance-format/lance.git?tag=v5.0.0-beta.4#d9068e76a301df9e21d7282419f24f61a11375ac"
+source = "git+https://github.com/lance-format/lance.git?tag=v5.1.0-beta.2#df61d95cac9ab579e4bc4ff41d1bd749b24af7f0"
 dependencies = [
  "arrayref",
  "paste",
@@ -4232,8 +4234,8 @@ dependencies = [
 
 [[package]]
 name = "lance-core"
-version = "5.0.0-beta.4"
+version = "5.1.0-beta.2"
-source = "git+https://github.com/lance-format/lance.git?tag=v5.0.0-beta.4#d9068e76a301df9e21d7282419f24f61a11375ac"
+source = "git+https://github.com/lance-format/lance.git?tag=v5.1.0-beta.2#df61d95cac9ab579e4bc4ff41d1bd749b24af7f0"
 dependencies = [
  "arrow-array",
  "arrow-buffer",
@@ -4270,12 +4272,13 @@ dependencies = [
 
 [[package]]
 name = "lance-datafusion"
-version = "5.0.0-beta.4"
+version = "5.1.0-beta.2"
-source = "git+https://github.com/lance-format/lance.git?tag=v5.0.0-beta.4#d9068e76a301df9e21d7282419f24f61a11375ac"
+source = "git+https://github.com/lance-format/lance.git?tag=v5.1.0-beta.2#df61d95cac9ab579e4bc4ff41d1bd749b24af7f0"
 dependencies = [
  "arrow",
  "arrow-array",
  "arrow-buffer",
+ "arrow-cast",
  "arrow-ord",
  "arrow-schema",
  "arrow-select",
@@ -4301,8 +4304,8 @@ dependencies = [
 
 [[package]]
 name = "lance-datagen"
-version = "5.0.0-beta.4"
+version = "5.1.0-beta.2"
-source = "git+https://github.com/lance-format/lance.git?tag=v5.0.0-beta.4#d9068e76a301df9e21d7282419f24f61a11375ac"
+source = "git+https://github.com/lance-format/lance.git?tag=v5.1.0-beta.2#df61d95cac9ab579e4bc4ff41d1bd749b24af7f0"
 dependencies = [
  "arrow",
  "arrow-array",
@@ -4320,8 +4323,8 @@ dependencies = [
 
 [[package]]
 name = "lance-encoding"
-version = "5.0.0-beta.4"
+version = "5.1.0-beta.2"
-source = "git+https://github.com/lance-format/lance.git?tag=v5.0.0-beta.4#d9068e76a301df9e21d7282419f24f61a11375ac"
+source = "git+https://github.com/lance-format/lance.git?tag=v5.1.0-beta.2#df61d95cac9ab579e4bc4ff41d1bd749b24af7f0"
 dependencies = [
  "arrow-arith",
  "arrow-array",
@@ -4358,8 +4361,8 @@ dependencies = [
 
 [[package]]
 name = "lance-file"
-version = "5.0.0-beta.4"
+version = "5.1.0-beta.2"
-source = "git+https://github.com/lance-format/lance.git?tag=v5.0.0-beta.4#d9068e76a301df9e21d7282419f24f61a11375ac"
+source = "git+https://github.com/lance-format/lance.git?tag=v5.1.0-beta.2#df61d95cac9ab579e4bc4ff41d1bd749b24af7f0"
 dependencies = [
  "arrow-arith",
  "arrow-array",
@@ -4391,8 +4394,8 @@ dependencies = [
 
 [[package]]
 name = "lance-index"
-version = "5.0.0-beta.4"
+version = "5.1.0-beta.2"
-source = "git+https://github.com/lance-format/lance.git?tag=v5.0.0-beta.4#d9068e76a301df9e21d7282419f24f61a11375ac"
+source = "git+https://github.com/lance-format/lance.git?tag=v5.1.0-beta.2#df61d95cac9ab579e4bc4ff41d1bd749b24af7f0"
 dependencies = [
  "arrow",
  "arrow-arith",
@@ -4456,8 +4459,8 @@ dependencies = [
 
 [[package]]
 name = "lance-io"
-version = "5.0.0-beta.4"
+version = "5.1.0-beta.2"
-source = "git+https://github.com/lance-format/lance.git?tag=v5.0.0-beta.4#d9068e76a301df9e21d7282419f24f61a11375ac"
+source = "git+https://github.com/lance-format/lance.git?tag=v5.1.0-beta.2#df61d95cac9ab579e4bc4ff41d1bd749b24af7f0"
 dependencies = [
  "arrow",
  "arrow-arith",
@@ -4501,8 +4504,8 @@ dependencies = [
 
 [[package]]
 name = "lance-linalg"
-version = "5.0.0-beta.4"
+version = "5.1.0-beta.2"
-source = "git+https://github.com/lance-format/lance.git?tag=v5.0.0-beta.4#d9068e76a301df9e21d7282419f24f61a11375ac"
+source = "git+https://github.com/lance-format/lance.git?tag=v5.1.0-beta.2#df61d95cac9ab579e4bc4ff41d1bd749b24af7f0"
 dependencies = [
  "arrow-array",
  "arrow-buffer",
@@ -4518,8 +4521,8 @@ dependencies = [
 
 [[package]]
 name = "lance-namespace"
-version = "5.0.0-beta.4"
+version = "5.1.0-beta.2"
-source = "git+https://github.com/lance-format/lance.git?tag=v5.0.0-beta.4#d9068e76a301df9e21d7282419f24f61a11375ac"
+source = "git+https://github.com/lance-format/lance.git?tag=v5.1.0-beta.2#df61d95cac9ab579e4bc4ff41d1bd749b24af7f0"
 dependencies = [
  "arrow",
  "async-trait",
@@ -4532,8 +4535,8 @@ dependencies = [
 
 [[package]]
 name = "lance-namespace-impls"
-version = "5.0.0-beta.4"
+version = "5.1.0-beta.2"
-source = "git+https://github.com/lance-format/lance.git?tag=v5.0.0-beta.4#d9068e76a301df9e21d7282419f24f61a11375ac"
+source = "git+https://github.com/lance-format/lance.git?tag=v5.1.0-beta.2#df61d95cac9ab579e4bc4ff41d1bd749b24af7f0"
 dependencies = [
  "arrow",
  "arrow-ipc",
@@ -4578,8 +4581,8 @@ dependencies = [
 
 [[package]]
 name = "lance-table"
-version = "5.0.0-beta.4"
+version = "5.1.0-beta.2"
-source = "git+https://github.com/lance-format/lance.git?tag=v5.0.0-beta.4#d9068e76a301df9e21d7282419f24f61a11375ac"
+source = "git+https://github.com/lance-format/lance.git?tag=v5.1.0-beta.2#df61d95cac9ab579e4bc4ff41d1bd749b24af7f0"
 dependencies = [
  "arrow",
  "arrow-array",
@@ -4618,8 +4621,8 @@ dependencies = [
 
 [[package]]
 name = "lance-testing"
-version = "5.0.0-beta.4"
+version = "5.1.0-beta.2"
-source = "git+https://github.com/lance-format/lance.git?tag=v5.0.0-beta.4#d9068e76a301df9e21d7282419f24f61a11375ac"
+source = "git+https://github.com/lance-format/lance.git?tag=v5.1.0-beta.2#df61d95cac9ab579e4bc4ff41d1bd749b24af7f0"
 dependencies = [
  "arrow-array",
  "arrow-schema",
@@ -4630,7 +4633,7 @@ dependencies = [
 
 [[package]]
 name = "lancedb"
-version = "0.27.2"
+version = "0.28.0-beta.1"
 dependencies = [
  "ahash",
  "anyhow",
@@ -4712,7 +4715,7 @@ dependencies = [
 
 [[package]]
 name = "lancedb-nodejs"
-version = "0.27.2"
+version = "0.28.0-beta.1"
 dependencies = [
  "arrow-array",
  "arrow-buffer",
@@ -4734,7 +4737,7 @@ dependencies = [
 
 [[package]]
 name = "lancedb-python"
-version = "0.30.2"
+version = "0.31.0-beta.1"
 dependencies = [
  "arrow",
  "async-trait",

Cargo.toml

@@ -15,20 +15,20 @@ categories = ["database-implementations"]
 rust-version = "1.91.0"
 
 [workspace.dependencies]
-lance = { "version" = "=5.0.0-beta.4", default-features = false, "tag" = "v5.0.0-beta.4", "git" = "https://github.com/lance-format/lance.git" }
+lance = { "version" = "=5.1.0-beta.2", default-features = false, "tag" = "v5.1.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
-lance-core = { "version" = "=5.0.0-beta.4", "tag" = "v5.0.0-beta.4", "git" = "https://github.com/lance-format/lance.git" }
+lance-core = { "version" = "=5.1.0-beta.2", "tag" = "v5.1.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
-lance-datagen = { "version" = "=5.0.0-beta.4", "tag" = "v5.0.0-beta.4", "git" = "https://github.com/lance-format/lance.git" }
+lance-datagen = { "version" = "=5.1.0-beta.2", "tag" = "v5.1.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
-lance-file = { "version" = "=5.0.0-beta.4", "tag" = "v5.0.0-beta.4", "git" = "https://github.com/lance-format/lance.git" }
+lance-file = { "version" = "=5.1.0-beta.2", "tag" = "v5.1.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
-lance-io = { "version" = "=5.0.0-beta.4", default-features = false, "tag" = "v5.0.0-beta.4", "git" = "https://github.com/lance-format/lance.git" }
+lance-io = { "version" = "=5.1.0-beta.2", default-features = false, "tag" = "v5.1.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
-lance-index = { "version" = "=5.0.0-beta.4", "tag" = "v5.0.0-beta.4", "git" = "https://github.com/lance-format/lance.git" }
+lance-index = { "version" = "=5.1.0-beta.2", "tag" = "v5.1.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
-lance-linalg = { "version" = "=5.0.0-beta.4", "tag" = "v5.0.0-beta.4", "git" = "https://github.com/lance-format/lance.git" }
+lance-linalg = { "version" = "=5.1.0-beta.2", "tag" = "v5.1.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
-lance-namespace = { "version" = "=5.0.0-beta.4", "tag" = "v5.0.0-beta.4", "git" = "https://github.com/lance-format/lance.git" }
+lance-namespace = { "version" = "=5.1.0-beta.2", "tag" = "v5.1.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
-lance-namespace-impls = { "version" = "=5.0.0-beta.4", default-features = false, "tag" = "v5.0.0-beta.4", "git" = "https://github.com/lance-format/lance.git" }
+lance-namespace-impls = { "version" = "=5.1.0-beta.2", default-features = false, "tag" = "v5.1.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
-lance-table = { "version" = "=5.0.0-beta.4", "tag" = "v5.0.0-beta.4", "git" = "https://github.com/lance-format/lance.git" }
+lance-table = { "version" = "=5.1.0-beta.2", "tag" = "v5.1.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
-lance-testing = { "version" = "=5.0.0-beta.4", "tag" = "v5.0.0-beta.4", "git" = "https://github.com/lance-format/lance.git" }
+lance-testing = { "version" = "=5.1.0-beta.2", "tag" = "v5.1.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
-lance-datafusion = { "version" = "=5.0.0-beta.4", "tag" = "v5.0.0-beta.4", "git" = "https://github.com/lance-format/lance.git" }
+lance-datafusion = { "version" = "=5.1.0-beta.2", "tag" = "v5.1.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
-lance-encoding = { "version" = "=5.0.0-beta.4", "tag" = "v5.0.0-beta.4", "git" = "https://github.com/lance-format/lance.git" }
+lance-encoding = { "version" = "=5.1.0-beta.2", "tag" = "v5.1.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
-lance-arrow = { "version" = "=5.0.0-beta.4", "tag" = "v5.0.0-beta.4", "git" = "https://github.com/lance-format/lance.git" }
+lance-arrow = { "version" = "=5.1.0-beta.2", "tag" = "v5.1.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
 ahash = "0.8"
 # Note that this one does not include pyarrow
 arrow = { version = "57.2", optional = false }

docs/src/java/java.md

@@ -14,7 +14,7 @@ Add the following dependency to your `pom.xml`:
 <dependency>
     <groupId>com.lancedb</groupId>
     <artifactId>lancedb-core</artifactId>
-    <version>0.27.2</version>
+    <version>0.28.0-beta.1</version>
 </dependency>
 ```
 

docs/src/js/interfaces/ClientConfig.md

@@ -53,3 +53,18 @@ optional tlsConfig: TlsConfig;
 ```ts
 optional userAgent: string;
 ```
+
+***
+
+### userId?
+
+```ts
+optional userId: string;
+```
+
+User identifier for tracking purposes.
+
+This is sent as the `x-lancedb-user-id` header in requests to LanceDB Cloud/Enterprise.
+It can be set directly, or via the `LANCEDB_USER_ID` environment variable.
+Alternatively, set `LANCEDB_USER_ID_ENV_KEY` to specify another environment
+variable that contains the user ID value.

java/lancedb-core/pom.xml

@@ -8,7 +8,7 @@
     <parent>
       <groupId>com.lancedb</groupId>
       <artifactId>lancedb-parent</artifactId>
-      <version>0.27.2-final.0</version>
+      <version>0.28.0-beta.1</version>
       <relativePath>../pom.xml</relativePath>
     </parent>
 

java/pom.xml

@@ -6,7 +6,7 @@
 
     <groupId>com.lancedb</groupId>
     <artifactId>lancedb-parent</artifactId>
-    <version>0.27.2-final.0</version>
+    <version>0.28.0-beta.1</version>
     <packaging>pom</packaging>
     <name>${project.artifactId}</name>
     <description>LanceDB Java SDK Parent POM</description>
@@ -28,7 +28,7 @@
     <properties>
         <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
         <arrow.version>15.0.0</arrow.version>
-        <lance-core.version>5.0.0-beta.4</lance-core.version>
+        <lance-core.version>5.1.0-beta.2</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>

nodejs/Cargo.toml

@@ -1,7 +1,7 @@
 [package]
 name = "lancedb-nodejs"
 edition.workspace = true
-version = "0.27.2"
+version = "0.28.0-beta.1"
 license.workspace = true
 description.workspace = true
 repository.workspace = true

nodejs/npm/darwin-arm64/package.json

@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-darwin-arm64",
-	"version": "0.27.2",
+	"version": "0.28.0-beta.1",
 	"os": ["darwin"],
 	"cpu": ["arm64"],
 	"main": "lancedb.darwin-arm64.node",

nodejs/npm/linux-arm64-gnu/package.json

@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-arm64-gnu",
-	"version": "0.27.2",
+	"version": "0.28.0-beta.1",
 	"os": ["linux"],
 	"cpu": ["arm64"],
 	"main": "lancedb.linux-arm64-gnu.node",

nodejs/npm/linux-arm64-musl/package.json

@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-arm64-musl",
-	"version": "0.27.2",
+	"version": "0.28.0-beta.1",
 	"os": ["linux"],
 	"cpu": ["arm64"],
 	"main": "lancedb.linux-arm64-musl.node",

nodejs/npm/linux-x64-gnu/package.json

@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-x64-gnu",
-	"version": "0.27.2",
+	"version": "0.28.0-beta.1",
 	"os": ["linux"],
 	"cpu": ["x64"],
 	"main": "lancedb.linux-x64-gnu.node",

nodejs/npm/linux-x64-musl/package.json

@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-x64-musl",
-	"version": "0.27.2",
+	"version": "0.28.0-beta.1",
 	"os": ["linux"],
 	"cpu": ["x64"],
 	"main": "lancedb.linux-x64-musl.node",

nodejs/npm/win32-arm64-msvc/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@lancedb/lancedb-win32-arm64-msvc",
-  "version": "0.27.2",
+  "version": "0.28.0-beta.1",
   "os": [
     "win32"
   ],

nodejs/npm/win32-x64-msvc/package.json

@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-win32-x64-msvc",
-	"version": "0.27.2",
+	"version": "0.28.0-beta.1",
 	"os": ["win32"],
 	"cpu": ["x64"],
 	"main": "lancedb.win32-x64-msvc.node",

nodejs/package-lock.json

@@ -1,12 +1,12 @@
 {
   "name": "@lancedb/lancedb",
-  "version": "0.27.2",
+  "version": "0.28.0-beta.1",
   "lockfileVersion": 3,
   "requires": true,
   "packages": {
     "": {
       "name": "@lancedb/lancedb",
-      "version": "0.27.2",
+      "version": "0.28.0-beta.1",
       "cpu": [
         "x64",
         "arm64"

nodejs/package.json

@@ -11,7 +11,7 @@
     "ann"
   ],
   "private": false,
-  "version": "0.27.2",
+  "version": "0.28.0-beta.1",
   "main": "dist/index.js",
   "exports": {
     ".": "./dist/index.js",

nodejs/src/remote.rs

@@ -92,6 +92,13 @@ pub struct ClientConfig {
     pub extra_headers: Option<HashMap<String, String>>,
     pub id_delimiter: Option<String>,
     pub tls_config: Option<TlsConfig>,
+    /// User identifier for tracking purposes.
+    ///
+    /// This is sent as the `x-lancedb-user-id` header in requests to LanceDB Cloud/Enterprise.
+    /// It can be set directly, or via the `LANCEDB_USER_ID` environment variable.
+    /// Alternatively, set `LANCEDB_USER_ID_ENV_KEY` to specify another environment
+    /// variable that contains the user ID value.
+    pub user_id: Option<String>,
 }
 
 impl From<TimeoutConfig> for lancedb::remote::TimeoutConfig {
@@ -145,6 +152,7 @@ impl From<ClientConfig> for lancedb::remote::ClientConfig {
             id_delimiter: config.id_delimiter,
             tls_config: config.tls_config.map(Into::into),
             header_provider: None, // the header provider is set separately later
+            user_id: config.user_id,
         }
     }
 }

python/.bumpversion.toml

@@ -1,5 +1,5 @@
 [tool.bumpversion]
-current_version = "0.31.0-beta.0"
+current_version = "0.31.0-beta.2"
 parse = """(?x)
     (?P<major>0|[1-9]\\d*)\\.
     (?P<minor>0|[1-9]\\d*)\\.

python/Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "lancedb-python"
-version = "0.31.0-beta.0"
+version = "0.31.0-beta.2"
 edition.workspace = true
 description = "Python bindings for LanceDB"
 license.workspace = true

python/pyproject.toml

@@ -45,7 +45,7 @@ repository = "https://github.com/lancedb/lancedb"
 
 [project.optional-dependencies]
 pylance = [
-    "pylance>=5.0.0b3",
+    "pylance>=5.0.0b5",
 ]
 tests = [
     "aiohttp>=3.9.0",
@@ -59,7 +59,7 @@ tests = [
     "polars>=0.19, <=1.3.0",
     "tantivy>=0.20.0",
     "pyarrow-stubs>=16.0",
-    "pylance>=5.0.0b3",
+    "pylance>=5.0.0b5",
     "requests>=2.31.0",
     "datafusion>=52,<53",
 ]
@@ -83,7 +83,7 @@ embeddings = [
     "colpali-engine>=0.3.10",
     "huggingface_hub>=0.19.0",
     "InstructorEmbedding>=1.0.1",
-    "google.generativeai>=0.3.0",
+    "google-genai>=1.0.0",
     "boto3>=1.28.57",
     "awscli>=1.44.38",
     "botocore>=1.31.57",

python/python/lancedb/_lancedb.pyi

@@ -151,6 +151,9 @@ class Connection(object):
     async def drop_all_tables(
         self, namespace_path: Optional[List[str]] = None
     ) -> None: ...
+    async def namespace_client_config(
+        self,
+    ) -> Dict[str, Any]: ...
 
 class Table:
     def name(self) -> str: ...

python/python/lancedb/db.py

@@ -23,11 +23,13 @@ from lancedb.embeddings.registry import EmbeddingFunctionRegistry
 from lancedb.common import data_to_reader, sanitize_uri, validate_schema
 from lancedb.background_loop import LOOP
 from lance_namespace import (
+    LanceNamespace,
     ListNamespacesResponse,
     CreateNamespaceResponse,
     DropNamespaceResponse,
     DescribeNamespaceResponse,
     ListTablesResponse,
+    connect as namespace_connect,
 )
 
 from . import __version__
@@ -507,6 +509,26 @@ class DBConnection(EnforceOverrides):
     def uri(self) -> str:
         return self._uri
 
+    def namespace_client(self) -> LanceNamespace:
+        """Get the equivalent namespace client for this connection.
+
+        For native storage connections, this returns a DirectoryNamespace
+        pointing to the same root with the same storage options.
+
+        For namespace connections, this returns the backing namespace client.
+
+        For enterprise (remote) connections, this returns a RestNamespace
+        with the same URI and authentication headers.
+
+        Returns
+        -------
+        LanceNamespace
+            The namespace client for this connection.
+        """
+        raise NotImplementedError(
+            "namespace_client is not supported for this connection type"
+        )
+
 
 class LanceDBConnection(DBConnection):
     """
@@ -1044,6 +1066,20 @@ class LanceDBConnection(DBConnection):
             )
         )
 
+    @override
+    def namespace_client(self) -> LanceNamespace:
+        """Get the equivalent namespace client for this connection.
+
+        Returns a DirectoryNamespace pointing to the same root with the
+        same storage options.
+
+        Returns
+        -------
+        LanceNamespace
+            The namespace client for this connection.
+        """
+        return LOOP.run(self._conn.namespace_client())
+
     @deprecation.deprecated(
         deprecated_in="0.15.1",
         removed_in="0.17",
@@ -1716,6 +1752,25 @@ class AsyncConnection(object):
             namespace_path = []
         await self._inner.drop_all_tables(namespace_path=namespace_path)
 
+    async def namespace_client(self) -> LanceNamespace:
+        """Get the equivalent namespace client for this connection.
+
+        For native storage connections, this returns a DirectoryNamespace
+        pointing to the same root with the same storage options.
+
+        For namespace connections, this returns the backing namespace client.
+
+        For enterprise (remote) connections, this returns a RestNamespace
+        with the same URI and authentication headers.
+
+        Returns
+        -------
+        LanceNamespace
+            The namespace client for this connection.
+        """
+        config = await self._inner.namespace_client_config()
+        return namespace_connect(config["impl"], config["properties"])
+
     @deprecation.deprecated(
         deprecated_in="0.15.1",
         removed_in="0.17",

python/python/lancedb/embeddings/gemini_text.py

@@ -19,10 +19,10 @@ from .utils import TEXT, api_key_not_found_help
 @register("gemini-text")
 class GeminiText(TextEmbeddingFunction):
     """
-    An embedding function that uses the Google's Gemini API. Requires GOOGLE_API_KEY to
+    An embedding function that uses Google's Gemini API. Requires GOOGLE_API_KEY to
     be set.
 
-    https://ai.google.dev/docs/embeddings_guide
+    https://ai.google.dev/gemini-api/docs/embeddings
 
     Supports various tasks types:
     | Task Type               | Description                                            |
@@ -46,9 +46,12 @@ class GeminiText(TextEmbeddingFunction):
 
     Parameters
     ----------
-    name: str, default "models/embedding-001"
+    name: str, default "gemini-embedding-001"
-        The name of the model to use. See the Gemini documentation for a list of
+        The name of the model to use. Supported models include:
-        available models.
+        - "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"
         Sets the task type for the queries.
@@ -77,7 +80,7 @@ class GeminiText(TextEmbeddingFunction):
 
     """
 
-    name: str = "models/embedding-001"
+    name: str = "gemini-embedding-001"
     query_task_type: str = "retrieval_query"
     source_task_type: str = "retrieval_document"
 
@@ -114,23 +117,48 @@ class GeminiText(TextEmbeddingFunction):
         texts: list[str] or np.ndarray (of str)
             The texts to embed
         """
-        if (
+        from google.genai import types
-            kwargs.get("task_type") == "retrieval_document"
-        ):  # Provide a title to use existing API design
-            title = "Embedding of a document"
-            kwargs["title"] = title
 
-        return [
+        task_type = kwargs.get("task_type")
-            self.client.embed_content(model=self.name, content=text, **kwargs)[
+
-                "embedding"
+        # Build content objects for embed_content
-            ]
+        contents = []
-            for text in texts
+        for text in texts:
-        ]
+            if task_type == "retrieval_document":
+                # Provide a title for retrieval_document task
+                contents.append(
+                    {"parts": [{"text": "Embedding of a document"}, {"text": text}]}
+                )
+            else:
+                contents.append({"parts": [{"text": text}]})
+
+        # Build config
+        config_kwargs = {}
+        if task_type:
+            config_kwargs["task_type"] = task_type.upper()  # API expects uppercase
+
+        # Call embed_content for each content
+        embeddings = []
+        for content in contents:
+            config = (
+                types.EmbedContentConfig(**config_kwargs) if config_kwargs else None
+            )
+            response = self.client.models.embed_content(
+                model=self.name,
+                contents=content,
+                config=config,
+            )
+            embeddings.append(response.embeddings[0].values)
+
+        return embeddings
 
     @cached_property
     def client(self):
-        genai = attempt_import_or_raise("google.generativeai", "google.generativeai")
+        attempt_import_or_raise("google.genai", "google-genai")
 
         if not os.environ.get("GOOGLE_API_KEY"):
             api_key_not_found_help("google")
-        return genai
+
+        from google import genai as genai_module
+
+        return genai_module.Client(api_key=os.environ.get("GOOGLE_API_KEY"))

python/python/lancedb/namespace.py

@@ -890,6 +890,20 @@ class LanceNamespaceDBConnection(DBConnection):
             pushdown_operations=self._pushdown_operations,
         )
 
+    @override
+    def namespace_client(self) -> LanceNamespace:
+        """Get the namespace client for this connection.
+
+        For namespace connections, this returns the backing namespace client
+        that was provided during construction.
+
+        Returns
+        -------
+        LanceNamespace
+            The namespace client for this connection.
+        """
+        return self._namespace_client
+
 
 class AsyncLanceNamespaceDBConnection:
     """
@@ -1387,6 +1401,19 @@ class AsyncLanceNamespaceDBConnection:
             page_token=response.page_token,
         )
 
+    async def namespace_client(self) -> LanceNamespace:
+        """Get the namespace client for this connection.
+
+        For namespace connections, this returns the backing namespace client
+        that was provided during construction.
+
+        Returns
+        -------
+        LanceNamespace
+            The namespace client for this connection.
+        """
+        return self._namespace_client
+
 
 def connect_namespace(
     namespace_client_impl: str,

python/python/lancedb/permutation.py

@@ -284,9 +284,8 @@ class Permutations:
         self.permutation_table = permutation_table
 
         if permutation_table.schema.metadata is not None:
-            split_names = permutation_table.schema.metadata.get(
+            raw = permutation_table.schema.metadata.get(b"split_names")
-                b"split_names", None
+            split_names = raw.decode("utf-8") if raw is not None else None
-            ).decode("utf-8")
             if split_names is not None:
                 self.split_names = json.loads(split_names)
                 self.split_dict = {
@@ -460,9 +459,8 @@ class Permutation:
                         f"Cannot create a permutation on split `{split}`"
                         " because no split names are defined in the permutation table"
                     )
-                split_names = permutation_table.schema.metadata.get(
+                raw = permutation_table.schema.metadata.get(b"split_names")
-                    b"split_names", None
+                split_names = raw.decode("utf-8") if raw is not None else None
-                ).decode("utf-8")
                 if split_names is None:
                     raise ValueError(
                         f"Cannot create a permutation on split `{split}`"

python/python/lancedb/pydantic.py

@@ -10,6 +10,7 @@ import sys
 import types
 from abc import ABC, abstractmethod
 from datetime import date, datetime
+from enum import Enum
 from typing import (
     TYPE_CHECKING,
     Any,
@@ -314,6 +315,19 @@ def _pydantic_type_to_arrow_type(tp: Any, field: FieldInfo) -> pa.DataType:
                 return pa.list_(pa.list_(tp.value_arrow_type(), tp.dim()))
             # For regular Vector
             return pa.list_(tp.value_arrow_type(), tp.dim())
+        if _safe_issubclass(tp, Enum):
+            # Map Enum to the Arrow type of its value.
+            # For string-valued enums, use dictionary encoding for efficiency.
+            # For integer enums, use the native type.
+            # Fall back to utf8 for mixed-type or empty enums.
+            value_types = {type(m.value) for m in tp}
+            if len(value_types) == 1:
+                value_type = value_types.pop()
+                if value_type is str:
+                    # Use dictionary encoding for string enums
+                    return pa.dictionary(pa.int32(), pa.utf8())
+                return _py_type_to_arrow_type(value_type, field)
+            return pa.utf8()
     return _py_type_to_arrow_type(tp, field)
 
 

python/python/lancedb/remote/__init__.py

@@ -145,6 +145,33 @@ class TlsConfig:
 
 @dataclass
 class ClientConfig:
+    """Configuration for the LanceDB Cloud HTTP client.
+
+    Attributes
+    ----------
+    user_agent: str
+        User agent string sent with requests.
+    retry_config: RetryConfig
+        Configuration for retrying failed requests.
+    timeout_config: Optional[TimeoutConfig]
+        Configuration for request timeouts.
+    extra_headers: Optional[dict]
+        Additional headers to include in requests.
+    id_delimiter: Optional[str]
+        The delimiter to use when constructing object identifiers.
+    tls_config: Optional[TlsConfig]
+        TLS/mTLS configuration for secure connections.
+    header_provider: Optional[HeaderProvider]
+        Provider for dynamic headers to be added to each request.
+    user_id: Optional[str]
+        User identifier for tracking purposes. This is sent as the
+        `x-lancedb-user-id` header in requests to LanceDB Cloud/Enterprise.
+
+        This can also be set via the `LANCEDB_USER_ID` environment variable.
+        Alternatively, set `LANCEDB_USER_ID_ENV_KEY` to specify another
+        environment variable that contains the user ID value.
+    """
+
     user_agent: str = f"LanceDB-Python-Client/{__version__}"
     retry_config: RetryConfig = field(default_factory=RetryConfig)
     timeout_config: Optional[TimeoutConfig] = field(default_factory=TimeoutConfig)
@@ -152,6 +179,7 @@ class ClientConfig:
     id_delimiter: Optional[str] = None
     tls_config: Optional[TlsConfig] = None
     header_provider: Optional["HeaderProvider"] = None
+    user_id: Optional[str] = None
 
     def __post_init__(self):
         if isinstance(self.retry_config, dict):

python/python/lancedb/remote/db.py

@@ -24,6 +24,7 @@ from ..common import DATA
 from ..db import DBConnection, LOOP
 from ..embeddings import EmbeddingFunctionConfig
 from lance_namespace import (
+    LanceNamespace,
     CreateNamespaceResponse,
     DescribeNamespaceResponse,
     DropNamespaceResponse,
@@ -570,6 +571,19 @@ class RemoteDBConnection(DBConnection):
             )
         )
 
+    @override
+    def namespace_client(self) -> LanceNamespace:
+        """Get the equivalent namespace client for this connection.
+
+        Returns a RestNamespace with the same URI and authentication headers.
+
+        Returns
+        -------
+        LanceNamespace
+            The namespace client for this connection.
+        """
+        return LOOP.run(self._conn.namespace_client())
+
     async def close(self):
         """Close the connection to the database."""
         self._conn.close()

python/python/lancedb/table.py

@@ -270,15 +270,17 @@ def _sanitize_data(
         reader,
         on_bad_vectors=on_bad_vectors,
         fill_value=fill_value,
+        target_schema=target_schema,
+        metadata=metadata,
     )
 
     if target_schema is None:
         target_schema, reader = _infer_target_schema(reader)
 
     if metadata:
-        new_metadata = target_schema.metadata or {}
+        target_schema = target_schema.with_metadata(
-        new_metadata.update(metadata)
+            _merge_metadata(target_schema.metadata, metadata)
-        target_schema = target_schema.with_metadata(new_metadata)
+        )
 
     _validate_schema(target_schema)
     reader = _cast_to_target_schema(reader, target_schema, allow_subschema)
@@ -294,7 +296,7 @@ def _cast_to_target_schema(
     # pa.Table.cast expects field order not to be changed.
     # Lance doesn't care about field order, so we don't need to rearrange fields
     # to match the target schema. We just need to correctly cast the fields.
-    if reader.schema == target_schema:
+    if reader.schema.equals(target_schema, check_metadata=True):
         # Fast path when the schemas are already the same
         return reader
 
@@ -314,7 +316,13 @@ def _cast_to_target_schema(
     def gen():
         for batch in reader:
             # Table but not RecordBatch has cast.
-            yield pa.Table.from_batches([batch]).cast(reordered_schema).to_batches()[0]
+            cast_batches = (
+                pa.Table.from_batches([batch]).cast(reordered_schema).to_batches()
+            )
+            if cast_batches:
+                yield pa.RecordBatch.from_arrays(
+                    cast_batches[0].columns, schema=reordered_schema
+                )
 
     return pa.RecordBatchReader.from_batches(reordered_schema, gen())
 
@@ -332,37 +340,51 @@ def _align_field_types(
         if target_field is None:
             raise ValueError(f"Field '{field.name}' not found in target schema")
         if pa.types.is_struct(target_field.type):
-            new_type = pa.struct(
+            if pa.types.is_struct(field.type):
-                _align_field_types(
+                new_type = pa.struct(
-                    field.type.fields,
+                    _align_field_types(
-                    target_field.type.fields,
+                        field.type.fields,
+                        target_field.type.fields,
+                    )
                 )
-            )
+            else:
+                new_type = target_field.type
         elif pa.types.is_list(target_field.type):
-            new_type = pa.list_(
+            if _is_list_like(field.type):
-                _align_field_types(
+                new_type = pa.list_(
-                    [field.type.value_field],
+                    _align_field_types(
-                    [target_field.type.value_field],
+                        [field.type.value_field],
-                )[0]
+                        [target_field.type.value_field],
-            )
+                    )[0]
+                )
+            else:
+                new_type = target_field.type
         elif pa.types.is_large_list(target_field.type):
-            new_type = pa.large_list(
+            if _is_list_like(field.type):
-                _align_field_types(
+                new_type = pa.large_list(
-                    [field.type.value_field],
+                    _align_field_types(
-                    [target_field.type.value_field],
+                        [field.type.value_field],
-                )[0]
+                        [target_field.type.value_field],
-            )
+                    )[0]
+                )
+            else:
+                new_type = target_field.type
         elif pa.types.is_fixed_size_list(target_field.type):
-            new_type = pa.list_(
+            if _is_list_like(field.type):
-                _align_field_types(
+                new_type = pa.list_(
-                    [field.type.value_field],
+                    _align_field_types(
-                    [target_field.type.value_field],
+                        [field.type.value_field],
-                )[0],
+                        [target_field.type.value_field],
-                target_field.type.list_size,
+                    )[0],
-            )
+                    target_field.type.list_size,
+                )
+            else:
+                new_type = target_field.type
         else:
             new_type = target_field.type
-        new_fields.append(pa.field(field.name, new_type, field.nullable))
+        new_fields.append(
+            pa.field(field.name, new_type, field.nullable, target_field.metadata)
+        )
     return new_fields
 
 
@@ -440,6 +462,7 @@ def sanitize_create_table(
             schema = data.schema
 
     if metadata:
+        metadata = _merge_metadata(schema.metadata, metadata)
         schema = schema.with_metadata(metadata)
         # Need to apply metadata to the data as well
         if isinstance(data, pa.Table):
@@ -492,9 +515,9 @@ def _append_vector_columns(
     vector columns to the table.
     """
     if schema is None:
-        metadata = metadata or {}
+        metadata = _merge_metadata(metadata)
     else:
-        metadata = schema.metadata or metadata or {}
+        metadata = _merge_metadata(schema.metadata, metadata)
     functions = EmbeddingFunctionRegistry.get_instance().parse_functions(metadata)
 
     if not functions:
@@ -3211,43 +3234,157 @@ def _handle_bad_vectors(
     reader: pa.RecordBatchReader,
     on_bad_vectors: Literal["error", "drop", "fill", "null"] = "error",
     fill_value: float = 0.0,
+    target_schema: Optional[pa.Schema] = None,
+    metadata: Optional[dict] = None,
 ) -> pa.RecordBatchReader:
-    vector_columns = []
+    vector_columns = _find_vector_columns(reader.schema, target_schema, metadata)
+    if not vector_columns:
+        return reader
 
-    for field in reader.schema:
+    output_schema = _vector_output_schema(reader.schema, vector_columns)
-        # They can provide a 'vector' column that isn't yet a FSL
-        named_vector_col = (
-            (
-                pa.types.is_list(field.type)
-                or pa.types.is_large_list(field.type)
-                or pa.types.is_fixed_size_list(field.type)
-            )
-            and pa.types.is_floating(field.type.value_type)
-            and field.name == VECTOR_COLUMN_NAME
-        )
-        # TODO: we're making an assumption that fixed size list of 10 or more
-        # is a vector column. This is definitely a bit hacky.
-        likely_vector_col = (
-            pa.types.is_fixed_size_list(field.type)
-            and pa.types.is_floating(field.type.value_type)
-            and (field.type.list_size >= 10)
-        )
-
-        if named_vector_col or likely_vector_col:
-            vector_columns.append(field.name)
 
     def gen():
         for batch in reader:
-            for name in vector_columns:
+            pending_dims = []
+            for vector_column in vector_columns:
+                dim = vector_column["expected_dim"]
+                if target_schema is not None and dim is None:
+                    dim = _infer_vector_dim(batch[vector_column["name"]])
+                    pending_dims.append(vector_column)
                 batch = _handle_bad_vector_column(
                     batch,
-                    vector_column_name=name,
+                    vector_column_name=vector_column["name"],
                     on_bad_vectors=on_bad_vectors,
                     fill_value=fill_value,
+                    expected_dim=dim,
+                    expected_value_type=vector_column["expected_value_type"],
                 )
-            yield batch
+            for vector_column in pending_dims:
+                if vector_column["expected_dim"] is None:
+                    vector_column["expected_dim"] = _infer_vector_dim(
+                        batch[vector_column["name"]]
+                    )
+            if batch.schema.equals(output_schema, check_metadata=True):
+                yield batch
+                continue
 
-    return pa.RecordBatchReader.from_batches(reader.schema, gen())
+            cast_batches = (
+                pa.Table.from_batches([batch]).cast(output_schema).to_batches()
+            )
+            if cast_batches:
+                yield pa.RecordBatch.from_arrays(
+                    cast_batches[0].columns,
+                    schema=output_schema,
+                )
+
+    return pa.RecordBatchReader.from_batches(output_schema, gen())
+
+
+def _find_vector_columns(
+    reader_schema: pa.Schema,
+    target_schema: Optional[pa.Schema],
+    metadata: Optional[dict],
+) -> List[dict]:
+    if target_schema is None:
+        vector_columns = []
+        for field in reader_schema:
+            named_vector_col = (
+                _is_list_like(field.type)
+                and pa.types.is_floating(field.type.value_type)
+                and field.name == VECTOR_COLUMN_NAME
+            )
+            likely_vector_col = (
+                pa.types.is_fixed_size_list(field.type)
+                and pa.types.is_floating(field.type.value_type)
+                and (field.type.list_size >= 10)
+            )
+            if named_vector_col or likely_vector_col:
+                vector_columns.append(
+                    {
+                        "name": field.name,
+                        "expected_dim": None,
+                        "expected_value_type": None,
+                    }
+                )
+        return vector_columns
+
+    reader_column_names = set(reader_schema.names)
+    active_metadata = _merge_metadata(target_schema.metadata, metadata)
+    embedding_function_columns = set(
+        EmbeddingFunctionRegistry.get_instance().parse_functions(active_metadata).keys()
+    )
+    vector_columns = []
+    for field in target_schema:
+        if field.name not in reader_column_names:
+            continue
+        if not _is_list_like(field.type) or not pa.types.is_floating(
+            field.type.value_type
+        ):
+            continue
+
+        reader_field = reader_schema.field(field.name)
+        named_vector_col = (
+            field.name in embedding_function_columns
+            or field.name == VECTOR_COLUMN_NAME
+            or (field.name == "embedding" and pa.types.is_fixed_size_list(field.type))
+        )
+        typed_fixed_vector_col = (
+            pa.types.is_fixed_size_list(reader_field.type)
+            and pa.types.is_floating(reader_field.type.value_type)
+            and reader_field.type.list_size >= 10
+        )
+
+        if named_vector_col or typed_fixed_vector_col:
+            vector_columns.append(
+                {
+                    "name": field.name,
+                    "expected_dim": (
+                        field.type.list_size
+                        if pa.types.is_fixed_size_list(field.type)
+                        else None
+                    ),
+                    "expected_value_type": field.type.value_type,
+                }
+            )
+
+    return vector_columns
+
+
+def _vector_output_schema(
+    reader_schema: pa.Schema,
+    vector_columns: List[dict],
+) -> pa.Schema:
+    columns_by_name = {column["name"]: column for column in vector_columns}
+    fields = []
+    for field in reader_schema:
+        column = columns_by_name.get(field.name)
+        if column is None:
+            output_type = field.type
+        else:
+            output_type = _vector_output_type(field, column)
+        fields.append(pa.field(field.name, output_type, field.nullable, field.metadata))
+    return pa.schema(fields, metadata=reader_schema.metadata)
+
+
+def _vector_output_type(field: pa.Field, vector_column: dict) -> pa.DataType:
+    if not _is_list_like(field.type):
+        return field.type
+
+    if vector_column["expected_value_type"] is not None and (
+        pa.types.is_null(field.type.value_type)
+        or pa.types.is_integer(field.type.value_type)
+        or pa.types.is_unsigned_integer(field.type.value_type)
+    ):
+        return pa.list_(vector_column["expected_value_type"])
+
+    if (
+        vector_column["expected_dim"] is not None
+        and pa.types.is_fixed_size_list(field.type)
+        and field.type.list_size != vector_column["expected_dim"]
+    ):
+        return pa.list_(field.type.value_type)
+
+    return field.type
 
 
 def _handle_bad_vector_column(
@@ -3255,6 +3392,8 @@ def _handle_bad_vector_column(
     vector_column_name: str,
     on_bad_vectors: str = "error",
     fill_value: float = 0.0,
+    expected_dim: Optional[int] = None,
+    expected_value_type: Optional[pa.DataType] = None,
 ) -> pa.RecordBatch:
     """
     Ensure that the vector column exists and has type fixed_size_list(float)
@@ -3271,14 +3410,39 @@ def _handle_bad_vector_column(
     fill_value: float, default 0.0
         The value to use when filling vectors. Only used if on_bad_vectors="fill".
     """
+    position = data.column_names.index(vector_column_name)
     vec_arr = data[vector_column_name]
+    if not _is_list_like(vec_arr.type):
+        return data
 
-    has_nan = has_nan_values(vec_arr)
+    if (
+        expected_dim is not None
+        and pa.types.is_fixed_size_list(vec_arr.type)
+        and vec_arr.type.list_size != expected_dim
+    ):
+        vec_arr = pa.array(vec_arr.to_pylist(), type=pa.list_(vec_arr.type.value_type))
+        data = data.set_column(position, vector_column_name, vec_arr)
 
-    if pa.types.is_fixed_size_list(vec_arr.type):
+    if expected_value_type is not None and (
+        pa.types.is_integer(vec_arr.type.value_type)
+        or pa.types.is_unsigned_integer(vec_arr.type.value_type)
+    ):
+        vec_arr = pa.array(vec_arr.to_pylist(), type=pa.list_(expected_value_type))
+        data = data.set_column(position, vector_column_name, vec_arr)
+
+    if pa.types.is_floating(vec_arr.type.value_type):
+        has_nan = has_nan_values(vec_arr)
+    else:
+        has_nan = pa.array([False] * len(vec_arr))
+
+    if expected_dim is not None:
+        dim = expected_dim
+    elif pa.types.is_fixed_size_list(vec_arr.type):
         dim = vec_arr.type.list_size
     else:
-        dim = _modal_list_size(vec_arr)
+        dim = _infer_vector_dim(vec_arr)
+        if dim is None:
+            return data
     has_wrong_dim = pc.not_equal(pc.list_value_length(vec_arr), dim)
 
     has_bad_vectors = pc.any(has_nan).as_py() or pc.any(has_wrong_dim).as_py()
@@ -3316,13 +3480,12 @@ def _handle_bad_vector_column(
                 )
             vec_arr = pc.if_else(
                 is_bad,
-                pa.scalar([fill_value] * dim),
+                pa.scalar([fill_value] * dim, type=vec_arr.type),
                 vec_arr,
             )
         else:
             raise ValueError(f"Invalid value for on_bad_vectors: {on_bad_vectors}")
 
-    position = data.column_names.index(vector_column_name)
     return data.set_column(position, vector_column_name, vec_arr)
 
 
@@ -3343,6 +3506,28 @@ def has_nan_values(arr: Union[pa.ListArray, pa.ChunkedArray]) -> pa.BooleanArray
     return pc.is_in(indices, has_nan_indices)
 
 
+def _is_list_like(data_type: pa.DataType) -> bool:
+    return (
+        pa.types.is_list(data_type)
+        or pa.types.is_large_list(data_type)
+        or pa.types.is_fixed_size_list(data_type)
+    )
+
+
+def _merge_metadata(*metadata_dicts: Optional[dict]) -> dict:
+    merged = {}
+    for metadata in metadata_dicts:
+        if metadata is None:
+            continue
+        for key, value in metadata.items():
+            if isinstance(key, str):
+                key = key.encode("utf-8")
+            if isinstance(value, str):
+                value = value.encode("utf-8")
+            merged[key] = value
+    return merged
+
+
 def _name_suggests_vector_column(field_name: str) -> bool:
     """Check if a field name indicates a vector column."""
     name_lower = field_name.lower()
@@ -3410,6 +3595,16 @@ def _modal_list_size(arr: Union[pa.ListArray, pa.ChunkedArray]) -> int:
     return pc.mode(pc.list_value_length(arr))[0].as_py()["mode"]
 
 
+def _infer_vector_dim(arr: Union[pa.Array, pa.ChunkedArray]) -> Optional[int]:
+    if not _is_list_like(arr.type):
+        return None
+    lengths = pc.list_value_length(arr)
+    lengths = pc.filter(lengths, pc.greater(lengths, 0))
+    if len(lengths) == 0:
+        return None
+    return pc.mode(lengths)[0].as_py()["mode"]
+
+
 def _validate_schema(schema: pa.Schema):
     """
     Make sure the metadata is valid utf8

python/python/tests/test_db.py

@@ -3,6 +3,7 @@
 
 
 import re
+import sys
 from datetime import timedelta
 import os
 
@@ -1048,3 +1049,59 @@ def test_clone_table_deep_clone_fails(tmp_path):
     source_uri = os.path.join(tmp_path, "source.lance")
     with pytest.raises(Exception, match="Deep clone is not yet implemented"):
         db.clone_table("cloned", source_uri, is_shallow=False)
+
+
+@pytest.mark.skipif(sys.platform == "win32", reason="Namespace client issues")
+def test_namespace_client_native_storage(tmp_path):
+    """Test namespace_client() returns DirectoryNamespace for native storage."""
+    from lance.namespace import DirectoryNamespace
+
+    db = lancedb.connect(tmp_path)
+    ns_client = db.namespace_client()
+
+    assert isinstance(ns_client, DirectoryNamespace)
+    assert str(tmp_path) in ns_client.namespace_id()
+
+
+@pytest.mark.skipif(sys.platform == "win32", reason="Namespace client issues")
+def test_namespace_client_with_storage_options(tmp_path):
+    """Test namespace_client() preserves storage options."""
+    from lance.namespace import DirectoryNamespace
+
+    storage_options = {"timeout": "10s"}
+    db = lancedb.connect(tmp_path, storage_options=storage_options)
+    ns_client = db.namespace_client()
+
+    assert isinstance(ns_client, DirectoryNamespace)
+
+
+@pytest.mark.skipif(sys.platform == "win32", reason="Namespace client issues")
+def test_namespace_client_operations(tmp_path):
+    """Test that namespace_client() returns a functional namespace client."""
+    db = lancedb.connect(tmp_path)
+    ns_client = db.namespace_client()
+
+    # Create a table through the main db connection
+    data = [{"id": 1, "text": "hello", "vector": [1.0, 2.0]}]
+    db.create_table("test_table", data=data)
+
+    # Verify the namespace client can see the table
+    from lance_namespace import ListTablesRequest
+
+    # id=[] means root namespace
+    response = ns_client.list_tables(ListTablesRequest(id=[]))
+    # Tables can be strings or objects with name attribute
+    table_names = [t.name if hasattr(t, "name") else t for t in response.tables]
+    assert "test_table" in table_names
+
+
+@pytest.mark.skipif(sys.platform == "win32", reason="Namespace client issues")
+def test_namespace_client_namespace_connection(tmp_path):
+    """Test namespace_client() returns the backing client for namespace connections."""
+    from lance.namespace import DirectoryNamespace
+
+    db = lancedb.connect_namespace("dir", {"root": str(tmp_path)})
+    ns_client = db.namespace_client()
+
+    assert isinstance(ns_client, DirectoryNamespace)
+    assert str(tmp_path) in ns_client.namespace_id()

python/python/tests/test_permutation.py

@@ -522,6 +522,50 @@ def test_no_split_names(some_table: Table):
     assert permutations[1].num_rows == 500
 
 
+def test_permutations_metadata_without_split_names_key(mem_db: DBConnection):
+    """Regression: schema metadata present but missing split_names key must not crash.
+
+    Previously, `.get(b"split_names", None).decode()` was called unconditionally,
+    so any permutation table whose metadata dict had other keys but no split_names
+    raised AttributeError: 'NoneType' has no attribute 'decode'.
+    """
+    base = mem_db.create_table("base_nosplit", pa.table({"x": range(10)}))
+
+    # Build a permutation-like table that carries some metadata but NOT split_names.
+    raw = pa.table(
+        {
+            "row_id": pa.array(range(10), type=pa.uint64()),
+            "split_id": pa.array([0] * 10, type=pa.uint32()),
+        }
+    ).replace_schema_metadata({b"other_key": b"other_value"})
+    perm_tbl = mem_db.create_table("perm_nosplit", raw)
+
+    permutations = Permutations(base, perm_tbl)
+    assert permutations.split_names == []
+    assert permutations.split_dict == {}
+
+
+def test_from_tables_string_split_missing_names_key(mem_db: DBConnection):
+    """Regression: from_tables() with a string split must raise ValueError, not
+    AttributeError.
+
+    Previously, `.get(b"split_names", None).decode()` crashed with AttributeError
+    when the metadata dict existed but had no split_names key.
+    """
+    base = mem_db.create_table("base_strsplit", pa.table({"x": range(10)}))
+
+    raw = pa.table(
+        {
+            "row_id": pa.array(range(10), type=pa.uint64()),
+            "split_id": pa.array([0] * 10, type=pa.uint32()),
+        }
+    ).replace_schema_metadata({b"other_key": b"other_value"})
+    perm_tbl = mem_db.create_table("perm_strsplit", raw)
+
+    with pytest.raises(ValueError, match="no split names are defined"):
+        Permutation.from_tables(base, perm_tbl, split="train")
+
+
 @pytest.fixture
 def some_perm_table(some_table: Table) -> Table:
     return (

python/python/tests/test_pydantic.py

@@ -3,6 +3,7 @@
 
 import json
 from datetime import date, datetime
+from enum import Enum
 from typing import List, Optional, Tuple
 
 import pyarrow as pa
@@ -673,3 +674,29 @@ async def test_aliases_in_lance_model_async(mem_db_async):
     assert hasattr(model, "name")
     assert hasattr(model, "distance")
     assert model.distance < 0.01
+
+
+def test_enum_types():
+    """Enum fields should map to the Arrow type of their value (issue #1846)."""
+
+    class StrStatus(str, Enum):
+        PENDING = "pending"
+        RUNNING = "running"
+        DONE = "done"
+
+    class IntPriority(int, Enum):
+        LOW = 1
+        MEDIUM = 2
+        HIGH = 3
+
+    class TestModel(pydantic.BaseModel):
+        status: StrStatus
+        priority: IntPriority
+        opt_status: Optional[StrStatus] = None
+
+    schema = pydantic_to_schema(TestModel)
+
+    assert schema.field("status").type == pa.dictionary(pa.int32(), pa.utf8())
+    assert schema.field("priority").type == pa.int64()
+    assert schema.field("opt_status").type == pa.dictionary(pa.int32(), pa.utf8())
+    assert schema.field("opt_status").nullable

python/python/tests/test_table.py

@@ -1049,6 +1049,231 @@ def test_add_with_nans(mem_db: DBConnection):
     assert np.allclose(v, np.array([0.0, 0.0]))
 
 
+def test_add_with_empty_fixed_size_list_drops_bad_rows(mem_db: DBConnection):
+    class Schema(LanceModel):
+        text: str
+        embedding: Vector(16)
+
+    table = mem_db.create_table("test_empty_embeddings", schema=Schema)
+    table.add(
+        [
+            {"text": "hello", "embedding": []},
+            {"text": "bar", "embedding": [0.1] * 16},
+        ],
+        on_bad_vectors="drop",
+    )
+
+    data = table.to_arrow()
+    assert data["text"].to_pylist() == ["bar"]
+    assert np.allclose(data["embedding"].to_pylist()[0], np.array([0.1] * 16))
+
+
+def test_add_with_integer_embeddings_preserves_casting(mem_db: DBConnection):
+    class Schema(LanceModel):
+        text: str
+        embedding: Vector(4)
+
+    table = mem_db.create_table("test_integer_embeddings", schema=Schema)
+    table.add(
+        [{"text": "foo", "embedding": [1, 2, 3, 4]}],
+        on_bad_vectors="drop",
+    )
+
+    assert table.to_arrow()["embedding"].to_pylist() == [[1.0, 2.0, 3.0, 4.0]]
+
+
+def test_on_bad_vectors_does_not_handle_non_vector_fixed_size_lists(
+    mem_db: DBConnection,
+):
+    schema = pa.schema(
+        [
+            pa.field("vector", pa.list_(pa.float32(), 4)),
+            pa.field("bbox", pa.list_(pa.float32(), 4)),
+        ]
+    )
+    table = mem_db.create_table("test_bbox_schema", schema=schema)
+
+    with pytest.raises(RuntimeError, match="FixedSizeListType"):
+        table.add(
+            [{"vector": [1.0, 2.0, 3.0, 4.0], "bbox": [0.0, 1.0]}],
+            on_bad_vectors="drop",
+        )
+
+
+def test_on_bad_vectors_does_not_handle_custom_named_fixed_size_lists(
+    mem_db: DBConnection,
+):
+    schema = pa.schema([pa.field("features", pa.list_(pa.float32(), 16))])
+    table = mem_db.create_table("test_custom_named_fixed_size_vector", schema=schema)
+
+    with pytest.raises(RuntimeError, match="FixedSizeListType"):
+        table.add(
+            [
+                {"features": []},
+                {"features": [0.1] * 16},
+            ],
+            on_bad_vectors="drop",
+        )
+
+
+def test_on_bad_vectors_with_schema_list_vector_still_sanitizes(mem_db: DBConnection):
+    schema = pa.schema([pa.field("vector", pa.list_(pa.float32()))])
+    table = mem_db.create_table("test_schema_list_vector", schema=schema)
+    table.add(
+        [
+            {"vector": [1.0, 2.0]},
+            {"vector": [3.0]},
+            {"vector": [4.0, 5.0]},
+        ],
+        on_bad_vectors="drop",
+    )
+
+    assert table.to_arrow()["vector"].to_pylist() == [[1.0, 2.0], [4.0, 5.0]]
+
+
+def test_on_bad_vectors_handles_typed_custom_fixed_vectors_for_list_schema(
+    mem_db: DBConnection,
+):
+    schema = pa.schema([pa.field("vec", pa.list_(pa.float32()))])
+    table = mem_db.create_table("test_typed_custom_fixed_vector", schema=schema)
+    data = pa.table(
+        {
+            "vec": pa.array(
+                [[float("nan")] * 16, [1.0] * 16],
+                type=pa.list_(pa.float32(), 16),
+            )
+        }
+    )
+
+    table.add(data, on_bad_vectors="drop")
+
+    assert table.to_arrow()["vec"].to_pylist() == [[1.0] * 16]
+
+
+def test_on_bad_vectors_fill_preserves_arrow_nested_vector_type(mem_db: DBConnection):
+    schema = pa.schema([pa.field("vector", pa.list_(pa.float32()))])
+    table = mem_db.create_table("test_fill_arrow_nested_type", schema=schema)
+    data = pa.table(
+        {
+            "vector": pa.array(
+                [[1.0, 2.0], [float("nan"), 3.0]],
+                type=pa.list_(pa.float32(), 2),
+            )
+        }
+    )
+
+    table.add(
+        data,
+        on_bad_vectors="fill",
+        fill_value=0.0,
+    )
+
+    assert table.to_arrow()["vector"].to_pylist() == [[1.0, 2.0], [0.0, 0.0]]
+
+
+@pytest.mark.parametrize(
+    ("table_name", "batch1", "expected"),
+    [
+        (
+            "test_schema_list_vector_empty_prefix",
+            pa.record_batch({"vector": [[], []]}),
+            [[], [], [1.0, 2.0], [3.0, 4.0]],
+        ),
+        (
+            "test_schema_list_vector_all_bad_prefix",
+            pa.record_batch({"vector": [[float("nan")] * 3, [float("nan")] * 3]}),
+            [[1.0, 2.0], [3.0, 4.0]],
+        ),
+    ],
+)
+def test_on_bad_vectors_with_schema_list_vector_ignores_invalid_prefix_batches(
+    mem_db: DBConnection,
+    table_name: str,
+    batch1: pa.RecordBatch,
+    expected: list,
+):
+    schema = pa.schema([pa.field("vector", pa.list_(pa.float32()))])
+    table = mem_db.create_table(table_name, schema=schema)
+    batch2 = pa.record_batch({"vector": [[1.0, 2.0], [3.0, 4.0]]})
+    reader = pa.RecordBatchReader.from_batches(batch1.schema, [batch1, batch2])
+
+    table.add(reader, on_bad_vectors="drop")
+
+    assert table.to_arrow()["vector"].to_pylist() == expected
+
+
+def test_on_bad_vectors_with_multiple_vectors_locks_dim_after_final_drop(
+    mem_db: DBConnection,
+):
+    registry = EmbeddingFunctionRegistry.get_instance()
+    func = MockTextEmbeddingFunction.create()
+    metadata = registry.get_table_metadata(
+        [
+            EmbeddingFunctionConfig(
+                source_column="text1", vector_column="vec1", function=func
+            ),
+            EmbeddingFunctionConfig(
+                source_column="text2", vector_column="vec2", function=func
+            ),
+        ]
+    )
+    schema = pa.schema(
+        [
+            pa.field("vec1", pa.list_(pa.float32())),
+            pa.field("vec2", pa.list_(pa.float32())),
+        ],
+        metadata=metadata,
+    )
+    table = mem_db.create_table("test_multi_vector_dim_lock", schema=schema)
+    batch1 = pa.record_batch(
+        {
+            "vec1": [[1.0, 2.0, 3.0], [10.0, 11.0]],
+            "vec2": [[float("nan"), 0.0], [5.0, 6.0]],
+        }
+    )
+    batch2 = pa.record_batch(
+        {
+            "vec1": [[20.0, 21.0], [30.0, 31.0]],
+            "vec2": [[7.0, 8.0], [9.0, 10.0]],
+        }
+    )
+    reader = pa.RecordBatchReader.from_batches(batch1.schema, [batch1, batch2])
+
+    table.add(reader, on_bad_vectors="drop")
+
+    data = table.to_arrow()
+    assert data["vec1"].to_pylist() == [[10.0, 11.0], [20.0, 21.0], [30.0, 31.0]]
+    assert data["vec2"].to_pylist() == [[5.0, 6.0], [7.0, 8.0], [9.0, 10.0]]
+
+
+def test_on_bad_vectors_does_not_handle_non_vector_list_columns(mem_db: DBConnection):
+    schema = pa.schema([pa.field("embedding_history", pa.list_(pa.float32()))])
+    table = mem_db.create_table("test_non_vector_list_schema", schema=schema)
+    table.add(
+        [
+            {"embedding_history": [1.0, 2.0]},
+            {"embedding_history": [3.0]},
+        ],
+        on_bad_vectors="drop",
+    )
+
+    assert table.to_arrow()["embedding_history"].to_pylist() == [
+        [1.0, 2.0],
+        [3.0],
+    ]
+
+
+def test_on_bad_vectors_all_null_schema_vector_batches_do_not_crash(
+    mem_db: DBConnection,
+):
+    schema = pa.schema([pa.field("vector", pa.list_(pa.float32(), 2), nullable=True)])
+    table = mem_db.create_table("test_all_null_vector_batch", schema=schema)
+
+    table.add([{"vector": None}], on_bad_vectors="drop")
+
+    assert table.to_arrow()["vector"].to_pylist() == [None]
+
+
 def test_restore(mem_db: DBConnection):
     table = mem_db.create_table(
         "my_table",

python/python/tests/test_util.py

@@ -15,8 +15,10 @@ from lancedb.table import (
     _cast_to_target_schema,
     _handle_bad_vectors,
     _into_pyarrow_reader,
-    _sanitize_data,
     _infer_target_schema,
+    _merge_metadata,
+    _sanitize_data,
+    sanitize_create_table,
 )
 import pyarrow as pa
 import pandas as pd
@@ -304,6 +306,117 @@ def test_handle_bad_vectors_noop():
     assert output["vector"] == vector
 
 
+def test_handle_bad_vectors_updates_reader_schema_for_target_schema():
+    data = pa.table({"vector": [[1, 2, 3, 4]]})
+    target_schema = pa.schema([pa.field("vector", pa.list_(pa.float32(), 4))])
+
+    output = _handle_bad_vectors(
+        data.to_reader(),
+        on_bad_vectors="drop",
+        target_schema=target_schema,
+    )
+
+    assert output.schema == pa.schema([pa.field("vector", pa.list_(pa.float32()))])
+    assert output.read_all()["vector"].to_pylist() == [[1.0, 2.0, 3.0, 4.0]]
+
+
+def test_sanitize_data_keeps_target_field_metadata():
+    source_field = pa.field(
+        "vector",
+        pa.list_(pa.float32(), 2),
+        metadata={b"source": b"drop-me"},
+    )
+    target_field = pa.field(
+        "vector",
+        pa.list_(pa.float32(), 2),
+        metadata={b"target": b"keep-me"},
+    )
+    data = pa.table(
+        {"vector": pa.array([[1.0, 2.0]], type=pa.list_(pa.float32(), 2))},
+        schema=pa.schema([source_field]),
+    )
+
+    output = _sanitize_data(
+        data,
+        target_schema=pa.schema([target_field]),
+        on_bad_vectors="drop",
+    ).read_all()
+
+    assert output.schema.field("vector").metadata == {b"target": b"keep-me"}
+
+
+def test_sanitize_data_uses_separate_embedding_metadata_for_bad_vectors():
+    registry = EmbeddingFunctionRegistry.get_instance()
+    conf = EmbeddingFunctionConfig(
+        source_column="text",
+        vector_column="custom_vector",
+        function=MockTextEmbeddingFunction.create(),
+    )
+    metadata = registry.get_table_metadata([conf])
+    schema = pa.schema(
+        {
+            "text": pa.string(),
+            "custom_vector": pa.list_(pa.float32(), 10),
+        },
+        metadata={b"note": b"keep-me"},
+    )
+    data = pa.table(
+        {
+            "text": ["bad", "good"],
+            "custom_vector": [[1.0] * 9, [2.0] * 10],
+        }
+    )
+
+    output = _sanitize_data(
+        data,
+        target_schema=schema,
+        metadata=metadata,
+        on_bad_vectors="drop",
+    ).read_all()
+
+    assert output["text"].to_pylist() == ["good"]
+    assert output.schema.metadata[b"note"] == b"keep-me"
+    assert b"embedding_functions" in output.schema.metadata
+
+
+def test_sanitize_create_table_merges_and_overrides_embedding_metadata():
+    registry = EmbeddingFunctionRegistry.get_instance()
+    old_conf = EmbeddingFunctionConfig(
+        source_column="text",
+        vector_column="old_vector",
+        function=MockTextEmbeddingFunction.create(),
+    )
+    new_conf = EmbeddingFunctionConfig(
+        source_column="text",
+        vector_column="custom_vector",
+        function=MockTextEmbeddingFunction.create(),
+    )
+    metadata = registry.get_table_metadata([new_conf])
+    schema = pa.schema(
+        {
+            "text": pa.string(),
+            "custom_vector": pa.list_(pa.float32(), 10),
+        },
+        metadata=_merge_metadata(
+            {b"note": b"keep-me"},
+            registry.get_table_metadata([old_conf]),
+        ),
+    )
+
+    data, schema = sanitize_create_table(
+        pa.table({"text": ["good"]}),
+        schema,
+        metadata=metadata,
+        on_bad_vectors="drop",
+    )
+
+    assert schema.metadata[b"note"] == b"keep-me"
+    assert b"embedding_functions" in schema.metadata
+    assert data.schema.metadata[b"note"] == b"keep-me"
+    funcs = EmbeddingFunctionRegistry.get_instance().parse_functions(schema.metadata)
+    assert set(funcs.keys()) == {"custom_vector"}
+
+
 class TestModel(lancedb.pydantic.LanceModel):
     a: Optional[int]
     b: Optional[int]

python/src/connection.rs

@@ -474,6 +474,25 @@ impl Connection {
             })
         })
     }
+
+    /// Get the configuration for constructing an equivalent namespace client.
+    /// Returns a dict with:
+    /// - "impl": "dir" for DirectoryNamespace, "rest" for RestNamespace
+    /// - "properties": configuration properties for the namespace
+    #[pyo3(signature = ())]
+    pub fn namespace_client_config(self_: PyRef<'_, Self>) -> PyResult<Bound<'_, PyAny>> {
+        let inner = self_.get_inner()?.clone();
+        let py = self_.py();
+        future_into_py(py, async move {
+            let (impl_type, properties) = inner.namespace_client_config().await.infer_error()?;
+            Python::attach(|py| -> PyResult<Py<PyDict>> {
+                let dict = PyDict::new(py);
+                dict.set_item("impl", impl_type)?;
+                dict.set_item("properties", properties)?;
+                Ok(dict.unbind())
+            })
+        })
+    }
 }
 
 #[pyfunction]
@@ -528,6 +547,7 @@ pub struct PyClientConfig {
     id_delimiter: Option<String>,
     tls_config: Option<PyClientTlsConfig>,
     header_provider: Option<Py<PyAny>>,
+    user_id: Option<String>,
 }
 
 #[derive(FromPyObject)]
@@ -612,6 +632,7 @@ impl From<PyClientConfig> for lancedb::remote::ClientConfig {
             id_delimiter: value.id_delimiter,
             tls_config: value.tls_config.map(Into::into),
             header_provider,
+            user_id: value.user_id,
         }
     }
 }

rust-toolchain.toml

@@ -1,2 +1,2 @@
 [toolchain]
-channel = "1.91.0"
+channel = "1.94.0"

rust/lancedb/Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "lancedb"
-version = "0.27.2"
+version = "0.28.0-beta.1"
 edition.workspace = true
 description = "LanceDB: A serverless, low-latency vector database for AI applications"
 license.workspace = true

rust/lancedb/src/connection.rs

@@ -541,6 +541,16 @@ impl Connection {
         self.internal.namespace_client().await
     }
 
+    /// Get the configuration for constructing an equivalent namespace client.
+    /// Returns (impl_type, properties) where:
+    /// - impl_type: "dir" for DirectoryNamespace, "rest" for RestNamespace
+    /// - properties: configuration properties for the namespace
+    pub async fn namespace_client_config(
+        &self,
+    ) -> Result<(String, std::collections::HashMap<String, String>)> {
+        self.internal.namespace_client_config().await
+    }
+
     /// List tables with pagination support
     pub async fn list_tables(&self, request: ListTablesRequest) -> Result<ListTablesResponse> {
         self.internal.list_tables(request).await

rust/lancedb/src/database.rs

@@ -265,4 +265,13 @@ pub trait Database:
     /// For ListingDatabase, it is the equivalent DirectoryNamespace.
     /// For RemoteDatabase, it is the equivalent RestNamespace.
     async fn namespace_client(&self) -> Result<Arc<dyn LanceNamespace>>;
+
+    /// Get the configuration for constructing an equivalent namespace client.
+    /// Returns (impl_type, properties) where:
+    /// - impl_type: "dir" for DirectoryNamespace, "rest" for RestNamespace
+    /// - properties: configuration properties for the namespace
+    ///
+    /// This is useful for Python bindings where we want to return a Python
+    /// namespace object rather than a Rust trait object.
+    async fn namespace_client_config(&self) -> Result<(String, HashMap<String, String>)>;
 }

rust/lancedb/src/database/listing.rs

@@ -1099,6 +1099,15 @@ impl Database for ListingDatabase {
         })?;
         Ok(Arc::new(namespace) as Arc<dyn lance_namespace::LanceNamespace>)
     }
+
+    async fn namespace_client_config(&self) -> Result<(String, HashMap<String, String>)> {
+        let mut properties = HashMap::new();
+        properties.insert("root".to_string(), self.uri.clone());
+        for (key, value) in &self.storage_options {
+            properties.insert(format!("storage.{}", key), value.clone());
+        }
+        Ok(("dir".to_string(), properties))
+    }
 }
 
 #[cfg(test)]

rust/lancedb/src/database/namespace.rs

@@ -45,6 +45,10 @@ pub struct LanceNamespaceDatabase {
     uri: String,
     // Operations to push down to the namespace server
     pushdown_operations: HashSet<PushdownOperation>,
+    // Namespace implementation type (e.g., "dir", "rest")
+    ns_impl: String,
+    // Namespace properties used to construct the namespace client
+    ns_properties: HashMap<String, String>,
 }
 
 impl LanceNamespaceDatabase {
@@ -74,6 +78,8 @@ impl LanceNamespaceDatabase {
             session,
             uri: format!("namespace://{}", ns_impl),
             pushdown_operations,
+            ns_impl: ns_impl.to_string(),
+            ns_properties,
         })
     }
 }
@@ -345,6 +351,10 @@ impl Database for LanceNamespaceDatabase {
     async fn namespace_client(&self) -> Result<Arc<dyn LanceNamespace>> {
         Ok(self.namespace.clone())
     }
+
+    async fn namespace_client_config(&self) -> Result<(String, HashMap<String, String>)> {
+        Ok((self.ns_impl.clone(), self.ns_properties.clone()))
+    }
 }
 
 #[cfg(test)]

rust/lancedb/src/embeddings/bedrock.rs

@@ -177,6 +177,7 @@ impl BedrockEmbeddingFunction {
                         ))
                         .send()
                         .await
+                        .map_err(Box::new)
                 })
             })
             .unwrap();

rust/lancedb/src/remote/client.rs

@@ -52,6 +52,13 @@ pub struct ClientConfig {
     pub tls_config: Option<TlsConfig>,
     /// Provider for custom headers to be added to each request
     pub header_provider: Option<Arc<dyn HeaderProvider>>,
+    /// User identifier for tracking purposes.
+    ///
+    /// This is sent as the `x-lancedb-user-id` header in requests to LanceDB Cloud/Enterprise.
+    /// It can be set directly, or via the `LANCEDB_USER_ID` environment variable.
+    /// Alternatively, set `LANCEDB_USER_ID_ENV_KEY` to specify another environment
+    /// variable that contains the user ID value.
+    pub user_id: Option<String>,
 }
 
 impl std::fmt::Debug for ClientConfig {
@@ -67,6 +74,7 @@ impl std::fmt::Debug for ClientConfig {
                 "header_provider",
                 &self.header_provider.as_ref().map(|_| "Some(...)"),
             )
+            .field("user_id", &self.user_id)
             .finish()
     }
 }
@@ -81,10 +89,41 @@ impl Default for ClientConfig {
             id_delimiter: None,
             tls_config: None,
             header_provider: None,
+            user_id: None,
         }
     }
 }
 
+impl ClientConfig {
+    /// Resolve the user ID from the config or environment variables.
+    ///
+    /// Resolution order:
+    /// 1. If `user_id` is set in the config, use that value
+    /// 2. If `LANCEDB_USER_ID` environment variable is set, use that value
+    /// 3. If `LANCEDB_USER_ID_ENV_KEY` is set, read the env var it points to
+    /// 4. Otherwise, return None
+    pub fn resolve_user_id(&self) -> Option<String> {
+        if self.user_id.is_some() {
+            return self.user_id.clone();
+        }
+
+        if let Ok(user_id) = std::env::var("LANCEDB_USER_ID")
+            && !user_id.is_empty()
+        {
+            return Some(user_id);
+        }
+
+        if let Ok(env_key) = std::env::var("LANCEDB_USER_ID_ENV_KEY")
+            && let Ok(user_id) = std::env::var(&env_key)
+            && !user_id.is_empty()
+        {
+            return Some(user_id);
+        }
+
+        None
+    }
+}
+
 /// How to handle timeouts for HTTP requests.
 #[derive(Clone, Default, Debug)]
 pub struct TimeoutConfig {
@@ -464,6 +503,15 @@ impl<S: HttpSend> RestfulLanceDbClient<S> {
             );
         }
 
+        if let Some(user_id) = config.resolve_user_id() {
+            headers.insert(
+                HeaderName::from_static("x-lancedb-user-id"),
+                HeaderValue::from_str(&user_id).map_err(|_| Error::InvalidInput {
+                    message: format!("non-ascii user_id '{}' provided", user_id),
+                })?,
+            );
+        }
+
         Ok(headers)
     }
 
@@ -1072,4 +1120,91 @@ mod tests {
             _ => panic!("Expected Runtime error"),
         }
     }
+
+    #[test]
+    fn test_resolve_user_id_direct_value() {
+        let config = ClientConfig {
+            user_id: Some("direct-user-id".to_string()),
+            ..Default::default()
+        };
+        assert_eq!(config.resolve_user_id(), Some("direct-user-id".to_string()));
+    }
+
+    #[test]
+    fn test_resolve_user_id_none() {
+        let config = ClientConfig::default();
+        // Clear env vars that might be set from other tests
+        // SAFETY: This is only called in tests
+        unsafe {
+            std::env::remove_var("LANCEDB_USER_ID");
+            std::env::remove_var("LANCEDB_USER_ID_ENV_KEY");
+        }
+        assert_eq!(config.resolve_user_id(), None);
+    }
+
+    #[test]
+    fn test_resolve_user_id_from_env() {
+        // SAFETY: This is only called in tests
+        unsafe {
+            std::env::set_var("LANCEDB_USER_ID", "env-user-id");
+        }
+        let config = ClientConfig::default();
+        assert_eq!(config.resolve_user_id(), Some("env-user-id".to_string()));
+        // SAFETY: This is only called in tests
+        unsafe {
+            std::env::remove_var("LANCEDB_USER_ID");
+        }
+    }
+
+    #[test]
+    fn test_resolve_user_id_from_env_key() {
+        // SAFETY: This is only called in tests
+        unsafe {
+            std::env::remove_var("LANCEDB_USER_ID");
+            std::env::set_var("LANCEDB_USER_ID_ENV_KEY", "MY_CUSTOM_USER_ID");
+            std::env::set_var("MY_CUSTOM_USER_ID", "custom-env-user-id");
+        }
+        let config = ClientConfig::default();
+        assert_eq!(
+            config.resolve_user_id(),
+            Some("custom-env-user-id".to_string())
+        );
+        // SAFETY: This is only called in tests
+        unsafe {
+            std::env::remove_var("LANCEDB_USER_ID_ENV_KEY");
+            std::env::remove_var("MY_CUSTOM_USER_ID");
+        }
+    }
+
+    #[test]
+    fn test_resolve_user_id_direct_takes_precedence() {
+        // SAFETY: This is only called in tests
+        unsafe {
+            std::env::set_var("LANCEDB_USER_ID", "env-user-id");
+        }
+        let config = ClientConfig {
+            user_id: Some("direct-user-id".to_string()),
+            ..Default::default()
+        };
+        assert_eq!(config.resolve_user_id(), Some("direct-user-id".to_string()));
+        // SAFETY: This is only called in tests
+        unsafe {
+            std::env::remove_var("LANCEDB_USER_ID");
+        }
+    }
+
+    #[test]
+    fn test_resolve_user_id_empty_env_ignored() {
+        // SAFETY: This is only called in tests
+        unsafe {
+            std::env::set_var("LANCEDB_USER_ID", "");
+            std::env::remove_var("LANCEDB_USER_ID_ENV_KEY");
+        }
+        let config = ClientConfig::default();
+        assert_eq!(config.resolve_user_id(), None);
+        // SAFETY: This is only called in tests
+        unsafe {
+            std::env::remove_var("LANCEDB_USER_ID");
+        }
+    }
 }

rust/lancedb/src/remote/db.rs

@@ -777,6 +777,32 @@ impl<S: HttpSend> Database for RemoteDatabase<S> {
         let namespace = builder.build();
         Ok(Arc::new(namespace) as Arc<dyn lance_namespace::LanceNamespace>)
     }
+
+    async fn namespace_client_config(&self) -> Result<(String, HashMap<String, String>)> {
+        let mut properties = HashMap::new();
+        properties.insert("uri".to_string(), self.client.host().to_string());
+        properties.insert("delimiter".to_string(), self.client.id_delimiter.clone());
+        for (key, value) in &self.namespace_headers {
+            properties.insert(format!("header.{}", key), value.clone());
+        }
+        // Add TLS configuration if present
+        if let Some(tls_config) = &self.tls_config {
+            if let Some(cert_file) = &tls_config.cert_file {
+                properties.insert("tls.cert_file".to_string(), cert_file.clone());
+            }
+            if let Some(key_file) = &tls_config.key_file {
+                properties.insert("tls.key_file".to_string(), key_file.clone());
+            }
+            if let Some(ssl_ca_cert) = &tls_config.ssl_ca_cert {
+                properties.insert("tls.ssl_ca_cert".to_string(), ssl_ca_cert.clone());
+            }
+            properties.insert(
+                "tls.assert_hostname".to_string(),
+                tls_config.assert_hostname.to_string(),
+            );
+        }
+        Ok(("rest".to_string(), properties))
+    }
 }
 
 /// RemoteOptions contains a subset of StorageOptions that are compatible with Remote LanceDB connections