Handle version number refs

chore: update lance dependency to v2.0.0-beta.3
2026-03-26 10:30:40 +00:00 · 2025-12-22 16:53:16 +08:00 · 2025-12-19 22:04:10 +00:00
81 changed files with 549 additions and 2528 deletions
--- a/.bumpversion.toml
+++ b/.bumpversion.toml
@@ -1,5 +1,5 @@
 [tool.bumpversion]
-current_version = "0.24.1"
+current_version = "0.23.1-beta.1"
 parse = """(?x)
    (?P<major>0|[1-9]\\d*)\\.
    (?P<minor>0|[1-9]\\d*)\\.
--- a/.github/workflows/build_linux_wheel/action.yml
+++ b/.github/workflows/build_linux_wheel/action.yml
@@ -3,7 +3,7 @@ name: build-linux-wheel
 description: "Build a manylinux wheel for lance"
 inputs:
  python-minor-version:
-    description: "10, 11, 12, 13"
+    description: "8, 9, 10, 11, 12"
    required: true
  args:
    description: "--release"
--- a/.github/workflows/build_mac_wheel/action.yml
+++ b/.github/workflows/build_mac_wheel/action.yml
@@ -3,7 +3,7 @@ name: build_wheel
 description: "Build a lance wheel"
 inputs:
  python-minor-version:
-    description: "10, 11, 12, 13"
+    description: "8, 9, 10, 11"
    required: true
  args:
    description: "--release"
--- a/.github/workflows/build_windows_wheel/action.yml
+++ b/.github/workflows/build_windows_wheel/action.yml
@@ -3,7 +3,7 @@ name: build_wheel
 description: "Build a lance wheel"
 inputs:
  python-minor-version:
-    description: "10, 11, 12, 13, 14"
+    description: "8, 9, 10, 11"
    required: true
  args:
    description: "--release"
--- a/.github/workflows/codex-update-lance-dependency.yml
+++ b/.github/workflows/codex-update-lance-dependency.yml
@@ -75,13 +75,6 @@ jobs:
          VERSION="${VERSION#v}"
          BRANCH_NAME="codex/update-lance-${VERSION//[^a-zA-Z0-9]/-}"

-          # Use "chore" for beta/rc versions, "feat" for stable releases
-          if [[ "${VERSION}" == *beta* ]] || [[ "${VERSION}" == *rc* ]]; then
-            COMMIT_TYPE="chore"
-          else
-            COMMIT_TYPE="feat"
-          fi
-
          cat <<EOF >/tmp/codex-prompt.txt
          You are running inside the lancedb repository on a GitHub Actions runner. Update the Lance dependency to version ${VERSION} and prepare a pull request for maintainers to review.

@@ -91,10 +84,10 @@ jobs:
          3. After clippy succeeds, run "cargo fmt --all" to format the workspace.
          4. Ensure the repository is clean except for intentional changes. Inspect "git status --short" and "git diff" to confirm the dependency update and any required fixes.
          5. Create and switch to a new branch named "${BRANCH_NAME}" (replace any duplicated hyphens if necessary).
-          6. Stage all relevant files with "git add -A". Commit using the message "${COMMIT_TYPE}: update lance dependency to v${VERSION}".
+          6. Stage all relevant files with "git add -A". Commit using the message "chore: update lance dependency to v${VERSION}".
          7. Push the branch to origin. If the branch already exists, force-push your changes.
          8. env "GH_TOKEN" is available, use "gh" tools for github related operations like creating pull request.
-          9. Create a pull request targeting "main" with title "${COMMIT_TYPE}: update lance dependency to v${VERSION}". First, write the PR body to /tmp/pr-body.md using a heredoc (cat <<'EOF' > /tmp/pr-body.md). The body should summarize the dependency bump, clippy/fmt verification, and link the triggering tag (${TAG}). Then run "gh pr create --body-file /tmp/pr-body.md".
+          9. Create a pull request targeting "main" with title "chore: update lance dependency to v${VERSION}". In the body, summarize the dependency bump, clippy/fmt verification, and link the triggering tag (${TAG}).
          10. After creating the PR, display the PR URL, "git status --short", and a concise summary of the commands run and their results.

          Constraints:
--- a/.github/workflows/docs.yml
+++ b/.github/workflows/docs.yml
@@ -41,7 +41,7 @@ jobs:
          sudo apt install -y protobuf-compiler libssl-dev
          rustup update && rustup default
      - name: Set up Python
-        uses: actions/setup-python@v6
+        uses: actions/setup-python@v5
        with:
          python-version: "3.10"
          cache: "pip"
--- a/.github/workflows/pypi-publish.yml
+++ b/.github/workflows/pypi-publish.yml
@@ -44,12 +44,12 @@ jobs:
          fetch-depth: 0
          lfs: true
      - name: Set up Python
-        uses: actions/setup-python@v6
+        uses: actions/setup-python@v4
        with:
-          python-version: "3.10"
+          python-version: 3.8
      - uses: ./.github/workflows/build_linux_wheel
        with:
-          python-minor-version: 10
+          python-minor-version: 8
          args: "--release --strip ${{ matrix.config.extra_args }}"
          arm-build: ${{ matrix.config.platform == 'aarch64' }}
          manylinux: ${{ matrix.config.manylinux }}
@@ -74,12 +74,12 @@ jobs:
          fetch-depth: 0
          lfs: true
      - name: Set up Python
-        uses: actions/setup-python@v6
+        uses: actions/setup-python@v4
        with:
-          python-version: "3.13"
+          python-version: 3.12
      - uses: ./.github/workflows/build_mac_wheel
        with:
-          python-minor-version: 10
+          python-minor-version: 8
          args: "--release --strip --target ${{ matrix.config.target }} --features fp16kernels"
      - uses: ./.github/workflows/upload_wheel
        if: startsWith(github.ref, 'refs/tags/python-v')
@@ -95,12 +95,12 @@ jobs:
          fetch-depth: 0
          lfs: true
      - name: Set up Python
-        uses: actions/setup-python@v6
+        uses: actions/setup-python@v4
        with:
-          python-version: "3.13"
+          python-version: 3.12
      - uses: ./.github/workflows/build_windows_wheel
        with:
-          python-minor-version: 10
+          python-minor-version: 8
          args: "--release --strip"
          vcpkg_token: ${{ secrets.VCPKG_GITHUB_PACKAGES }}
      - uses: ./.github/workflows/upload_wheel
--- a/.github/workflows/python.yml
+++ b/.github/workflows/python.yml
@@ -36,9 +36,9 @@ jobs:
          fetch-depth: 0
          lfs: true
      - name: Set up Python
-        uses: actions/setup-python@v6
+        uses: actions/setup-python@v5
        with:
-          python-version: "3.13"
+          python-version: "3.12"
      - name: Install ruff
        run: |
          pip install ruff==0.9.9
@@ -61,9 +61,9 @@ jobs:
          fetch-depth: 0
          lfs: true
      - name: Set up Python
-        uses: actions/setup-python@v6
+        uses: actions/setup-python@v5
        with:
-          python-version: "3.13"
+          python-version: "3.12"
      - name: Install protobuf compiler
        run: |
          sudo apt update
@@ -90,9 +90,9 @@ jobs:
          fetch-depth: 0
          lfs: true
      - name: Set up Python
-        uses: actions/setup-python@v6
+        uses: actions/setup-python@v5
        with:
-          python-version: "3.13"
+          python-version: "3.12"
          cache: "pip"
      - name: Install protobuf
        run: |
@@ -110,7 +110,7 @@ jobs:
    timeout-minutes: 30
    strategy:
      matrix:
-        python-minor-version: ["10", "13"]
+        python-minor-version: ["9", "12"]
    runs-on: "ubuntu-24.04"
    defaults:
      run:
@@ -126,7 +126,7 @@ jobs:
          sudo apt update
          sudo apt install -y protobuf-compiler
      - name: Set up Python
-        uses: actions/setup-python@v6
+        uses: actions/setup-python@v5
        with:
          python-version: 3.${{ matrix.python-minor-version }}
      - uses: ./.github/workflows/build_linux_wheel
@@ -156,9 +156,9 @@ jobs:
          fetch-depth: 0
          lfs: true
      - name: Set up Python
-        uses: actions/setup-python@v6
+        uses: actions/setup-python@v5
        with:
-          python-version: "3.13"
+          python-version: "3.12"
      - uses: ./.github/workflows/build_mac_wheel
        with:
          args: --profile ci
@@ -185,9 +185,9 @@ jobs:
          fetch-depth: 0
          lfs: true
      - name: Set up Python
-        uses: actions/setup-python@v6
+        uses: actions/setup-python@v5
        with:
-          python-version: "3.13"
+          python-version: "3.12"
      - uses: ./.github/workflows/build_windows_wheel
        with:
          args: --profile ci
@@ -212,9 +212,9 @@ jobs:
          sudo apt update
          sudo apt install -y protobuf-compiler
      - name: Set up Python
-        uses: actions/setup-python@v6
+        uses: actions/setup-python@v5
        with:
-          python-version: "3.10"
+          python-version: 3.9
      - name: Install lancedb
        run: |
          pip install "pydantic<2"
--- a/.github/workflows/rust.yml
+++ b/.github/workflows/rust.yml
@@ -48,8 +48,6 @@ jobs:
        run: cargo fmt --all -- --check
      - name: Run clippy
        run: cargo clippy --profile ci --workspace --tests --all-features -- -D warnings
-      - name: Run clippy (without remote feature)
-        run: cargo clippy --profile ci --workspace --tests -- -D warnings

  build-no-lock:
    runs-on: ubuntu-24.04
@@ -169,13 +167,13 @@ jobs:
      - name: Build
        run: |
          $env:VCPKG_ROOT = $env:VCPKG_INSTALLATION_ROOT
-          cargo build --profile ci --features aws,remote --tests --locked --target ${{ matrix.target }}
+          cargo build --profile ci --features remote --tests --locked --target ${{ matrix.target }}
      - name: Run tests
        # Can only run tests when target matches host
        if: ${{ matrix.target == 'x86_64-pc-windows-msvc' }}
        run: |
          $env:VCPKG_ROOT = $env:VCPKG_INSTALLATION_ROOT
-          cargo test --profile ci --features aws,remote --locked
+          cargo test --profile ci --features remote --locked

  msrv:
    # Check the minimum supported Rust version
@@ -183,7 +181,7 @@ jobs:
    runs-on: ubuntu-24.04
    strategy:
      matrix:
-        msrv: ["1.88.0"] # This should match up with rust-version in Cargo.toml
+        msrv: ["1.78.0"] # This should match up with rust-version in Cargo.toml
    env:
      # Need up-to-date compilers for kernels
      CC: clang-18
@@ -214,6 +212,4 @@ jobs:
          cargo update -p aws-sdk-sts --precise 1.51.0
          cargo update -p home --precise 0.5.9
      - name: cargo +${{ matrix.msrv }} check
-        env:
-          RUSTUP_TOOLCHAIN: ${{ matrix.msrv }}
        run: cargo check --profile ci --workspace --tests --benches --all-features
--- a/Cargo.lock
+++ b/Cargo.lock
@@ -1,6 +1,6 @@
 # This file is automatically @generated by Cargo.
 # It is not intended for manual editing.
-version = 4
+version = 3

 [[package]]
 name = "adler2"
@@ -3141,8 +3141,8 @@ checksum = "42703706b716c37f96a77aea830392ad231f44c9e9a67872fa5548707e11b11c"

 [[package]]
 name = "fsst"
-version = "1.0.4"
-source = "git+https://github.com/lance-format/lance.git?tag=v1.0.4#a93eaad1f6909a843cf8aa00d5530359012a7aaa"
+version = "2.0.0-beta.3"
+source = "git+https://github.com/lance-format/lance.git?tag=v2.0.0-beta.3#e6233665e377926ed2a8ceca667bc7a2f23341ae"
 dependencies = [
 "arrow-array",
 "rand 0.9.2",
@@ -4261,7 +4261,7 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "4b0f83760fb341a774ed326568e19f5a863af4a952def8c39f9ab92fd95b88e5"
 dependencies = [
 "equivalent",
- "hashbrown 0.16.0",
+ "hashbrown 0.15.5",
 "serde",
 "serde_core",
 ]
@@ -4478,8 +4478,8 @@ dependencies = [

 [[package]]
 name = "lance"
-version = "1.0.4"
-source = "git+https://github.com/lance-format/lance.git?tag=v1.0.4#a93eaad1f6909a843cf8aa00d5530359012a7aaa"
+version = "2.0.0-beta.3"
+source = "git+https://github.com/lance-format/lance.git?tag=v2.0.0-beta.3#e6233665e377926ed2a8ceca667bc7a2f23341ae"
 dependencies = [
 "arrow",
 "arrow-arith",
@@ -4544,13 +4544,14 @@ dependencies = [

 [[package]]
 name = "lance-arrow"
-version = "1.0.4"
-source = "git+https://github.com/lance-format/lance.git?tag=v1.0.4#a93eaad1f6909a843cf8aa00d5530359012a7aaa"
+version = "2.0.0-beta.3"
+source = "git+https://github.com/lance-format/lance.git?tag=v2.0.0-beta.3#e6233665e377926ed2a8ceca667bc7a2f23341ae"
 dependencies = [
 "arrow-array",
 "arrow-buffer",
 "arrow-cast",
 "arrow-data",
+ "arrow-ord",
 "arrow-schema",
 "arrow-select",
 "bytes",
@@ -4563,8 +4564,8 @@ dependencies = [

 [[package]]
 name = "lance-bitpacking"
-version = "1.0.4"
-source = "git+https://github.com/lance-format/lance.git?tag=v1.0.4#a93eaad1f6909a843cf8aa00d5530359012a7aaa"
+version = "2.0.0-beta.3"
+source = "git+https://github.com/lance-format/lance.git?tag=v2.0.0-beta.3#e6233665e377926ed2a8ceca667bc7a2f23341ae"
 dependencies = [
 "arrayref",
 "paste",
@@ -4573,8 +4574,8 @@ dependencies = [

 [[package]]
 name = "lance-core"
-version = "1.0.4"
-source = "git+https://github.com/lance-format/lance.git?tag=v1.0.4#a93eaad1f6909a843cf8aa00d5530359012a7aaa"
+version = "2.0.0-beta.3"
+source = "git+https://github.com/lance-format/lance.git?tag=v2.0.0-beta.3#e6233665e377926ed2a8ceca667bc7a2f23341ae"
 dependencies = [
 "arrow-array",
 "arrow-buffer",
@@ -4587,6 +4588,7 @@ dependencies = [
 "datafusion-sql",
 "deepsize",
 "futures",
+ "itertools 0.13.0",
 "lance-arrow",
 "libc",
 "log",
@@ -4610,8 +4612,8 @@ dependencies = [

 [[package]]
 name = "lance-datafusion"
-version = "1.0.4"
-source = "git+https://github.com/lance-format/lance.git?tag=v1.0.4#a93eaad1f6909a843cf8aa00d5530359012a7aaa"
+version = "2.0.0-beta.3"
+source = "git+https://github.com/lance-format/lance.git?tag=v2.0.0-beta.3#e6233665e377926ed2a8ceca667bc7a2f23341ae"
 dependencies = [
 "arrow",
 "arrow-array",
@@ -4641,8 +4643,8 @@ dependencies = [

 [[package]]
 name = "lance-datagen"
-version = "1.0.4"
-source = "git+https://github.com/lance-format/lance.git?tag=v1.0.4#a93eaad1f6909a843cf8aa00d5530359012a7aaa"
+version = "2.0.0-beta.3"
+source = "git+https://github.com/lance-format/lance.git?tag=v2.0.0-beta.3#e6233665e377926ed2a8ceca667bc7a2f23341ae"
 dependencies = [
 "arrow",
 "arrow-array",
@@ -4659,8 +4661,8 @@ dependencies = [

 [[package]]
 name = "lance-encoding"
-version = "1.0.4"
-source = "git+https://github.com/lance-format/lance.git?tag=v1.0.4#a93eaad1f6909a843cf8aa00d5530359012a7aaa"
+version = "2.0.0-beta.3"
+source = "git+https://github.com/lance-format/lance.git?tag=v2.0.0-beta.3#e6233665e377926ed2a8ceca667bc7a2f23341ae"
 dependencies = [
 "arrow-arith",
 "arrow-array",
@@ -4697,8 +4699,8 @@ dependencies = [

 [[package]]
 name = "lance-file"
-version = "1.0.4"
-source = "git+https://github.com/lance-format/lance.git?tag=v1.0.4#a93eaad1f6909a843cf8aa00d5530359012a7aaa"
+version = "2.0.0-beta.3"
+source = "git+https://github.com/lance-format/lance.git?tag=v2.0.0-beta.3#e6233665e377926ed2a8ceca667bc7a2f23341ae"
 dependencies = [
 "arrow-arith",
 "arrow-array",
@@ -4730,8 +4732,8 @@ dependencies = [

 [[package]]
 name = "lance-geo"
-version = "1.0.4"
-source = "git+https://github.com/lance-format/lance.git?tag=v1.0.4#a93eaad1f6909a843cf8aa00d5530359012a7aaa"
+version = "2.0.0-beta.3"
+source = "git+https://github.com/lance-format/lance.git?tag=v2.0.0-beta.3#e6233665e377926ed2a8ceca667bc7a2f23341ae"
 dependencies = [
 "datafusion",
 "geo-types",
@@ -4742,8 +4744,8 @@ dependencies = [

 [[package]]
 name = "lance-index"
-version = "1.0.4"
-source = "git+https://github.com/lance-format/lance.git?tag=v1.0.4#a93eaad1f6909a843cf8aa00d5530359012a7aaa"
+version = "2.0.0-beta.3"
+source = "git+https://github.com/lance-format/lance.git?tag=v2.0.0-beta.3#e6233665e377926ed2a8ceca667bc7a2f23341ae"
 dependencies = [
 "arrow",
 "arrow-arith",
@@ -4789,6 +4791,7 @@ dependencies = [
 "prost-types",
 "rand 0.9.2",
 "rand_distr 0.5.1",
+ "rangemap",
 "rayon",
 "roaring",
 "serde",
@@ -4804,8 +4807,8 @@ dependencies = [

 [[package]]
 name = "lance-io"
-version = "1.0.4"
-source = "git+https://github.com/lance-format/lance.git?tag=v1.0.4#a93eaad1f6909a843cf8aa00d5530359012a7aaa"
+version = "2.0.0-beta.3"
+source = "git+https://github.com/lance-format/lance.git?tag=v2.0.0-beta.3#e6233665e377926ed2a8ceca667bc7a2f23341ae"
 dependencies = [
 "arrow",
 "arrow-arith",
@@ -4845,8 +4848,8 @@ dependencies = [

 [[package]]
 name = "lance-linalg"
-version = "1.0.4"
-source = "git+https://github.com/lance-format/lance.git?tag=v1.0.4#a93eaad1f6909a843cf8aa00d5530359012a7aaa"
+version = "2.0.0-beta.3"
+source = "git+https://github.com/lance-format/lance.git?tag=v2.0.0-beta.3#e6233665e377926ed2a8ceca667bc7a2f23341ae"
 dependencies = [
 "arrow-array",
 "arrow-buffer",
@@ -4862,8 +4865,8 @@ dependencies = [

 [[package]]
 name = "lance-namespace"
-version = "1.0.4"
-source = "git+https://github.com/lance-format/lance.git?tag=v1.0.4#a93eaad1f6909a843cf8aa00d5530359012a7aaa"
+version = "2.0.0-beta.3"
+source = "git+https://github.com/lance-format/lance.git?tag=v2.0.0-beta.3#e6233665e377926ed2a8ceca667bc7a2f23341ae"
 dependencies = [
 "arrow",
 "async-trait",
@@ -4875,8 +4878,8 @@ dependencies = [

 [[package]]
 name = "lance-namespace-impls"
-version = "1.0.4"
-source = "git+https://github.com/lance-format/lance.git?tag=v1.0.4#a93eaad1f6909a843cf8aa00d5530359012a7aaa"
+version = "2.0.0-beta.3"
+source = "git+https://github.com/lance-format/lance.git?tag=v2.0.0-beta.3#e6233665e377926ed2a8ceca667bc7a2f23341ae"
 dependencies = [
 "arrow",
 "arrow-ipc",
@@ -4884,7 +4887,6 @@ dependencies = [
 "async-trait",
 "axum",
 "bytes",
- "chrono",
 "futures",
 "lance",
 "lance-core",
@@ -4906,9 +4908,9 @@ dependencies = [

 [[package]]
 name = "lance-namespace-reqwest-client"
-version = "0.4.5"
+version = "0.3.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "a2acdba67f84190067532fce07b51a435dd390d7cdc1129a05003e5cb3274cf0"
+checksum = "00a21b43fe2a373896727b97927adedd2683d2907683f294f62cf8815fbf6a01"
 dependencies = [
 "reqwest",
 "serde",
@@ -4919,8 +4921,8 @@ dependencies = [

 [[package]]
 name = "lance-table"
-version = "1.0.4"
-source = "git+https://github.com/lance-format/lance.git?tag=v1.0.4#a93eaad1f6909a843cf8aa00d5530359012a7aaa"
+version = "2.0.0-beta.3"
+source = "git+https://github.com/lance-format/lance.git?tag=v2.0.0-beta.3#e6233665e377926ed2a8ceca667bc7a2f23341ae"
 dependencies = [
 "arrow",
 "arrow-array",
@@ -4959,8 +4961,8 @@ dependencies = [

 [[package]]
 name = "lance-testing"
-version = "1.0.4"
-source = "git+https://github.com/lance-format/lance.git?tag=v1.0.4#a93eaad1f6909a843cf8aa00d5530359012a7aaa"
+version = "2.0.0-beta.3"
+source = "git+https://github.com/lance-format/lance.git?tag=v2.0.0-beta.3#e6233665e377926ed2a8ceca667bc7a2f23341ae"
 dependencies = [
 "arrow-array",
 "arrow-schema",
@@ -4971,7 +4973,7 @@ dependencies = [

 [[package]]
 name = "lancedb"
-version = "0.24.1"
+version = "0.23.1-beta.1"
 dependencies = [
 "ahash",
 "anyhow",
@@ -5050,7 +5052,7 @@ dependencies = [

 [[package]]
 name = "lancedb-nodejs"
-version = "0.24.1"
+version = "0.23.1-beta.1"
 dependencies = [
 "arrow-array",
 "arrow-ipc",
@@ -5070,7 +5072,7 @@ dependencies = [

 [[package]]
 name = "lancedb-python"
-version = "0.27.1"
+version = "0.26.1-beta.1"
 dependencies = [
 "arrow",
 "async-trait",
@@ -6726,8 +6728,8 @@ version = "0.13.5"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "be769465445e8c1474e9c5dac2018218498557af32d9ed057325ec9a41ae81bf"
 dependencies = [
- "heck 0.5.0",
- "itertools 0.14.0",
+ "heck 0.4.1",
+ "itertools 0.12.1",
 "log",
 "multimap",
 "once_cell",
@@ -6747,7 +6749,7 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "8a56d757972c98b346a9b766e3f02746cde6dd1cd1d1d563472929fdd74bec4d"
 dependencies = [
 "anyhow",
- "itertools 0.14.0",
+ "itertools 0.12.1",
 "proc-macro2",
 "quote",
 "syn 2.0.106",
@@ -8077,7 +8079,7 @@ version = "0.8.9"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "c1c97747dbf44bb1ca44a561ece23508e99cb592e862f22222dcf42f51d1e451"
 dependencies = [
- "heck 0.5.0",
+ "heck 0.4.1",
 "proc-macro2",
 "quote",
 "syn 2.0.106",
--- a/Cargo.toml
+++ b/Cargo.toml
@@ -12,23 +12,23 @@ repository = "https://github.com/lancedb/lancedb"
 description = "Serverless, low-latency vector database for AI applications"
 keywords = ["lancedb", "lance", "database", "vector", "search"]
 categories = ["database-implementations"]
-rust-version = "1.88.0"
+rust-version = "1.78.0"

 [workspace.dependencies]
-lance = { "version" = "=1.0.4", default-features = false, "tag" = "v1.0.4", "git" = "https://github.com/lance-format/lance.git" }
-lance-core = { "version" = "=1.0.4", "tag" = "v1.0.4", "git" = "https://github.com/lance-format/lance.git" }
-lance-datagen = { "version" = "=1.0.4", "tag" = "v1.0.4", "git" = "https://github.com/lance-format/lance.git" }
-lance-file = { "version" = "=1.0.4", "tag" = "v1.0.4", "git" = "https://github.com/lance-format/lance.git" }
-lance-io = { "version" = "=1.0.4", default-features = false, "tag" = "v1.0.4", "git" = "https://github.com/lance-format/lance.git" }
-lance-index = { "version" = "=1.0.4", "tag" = "v1.0.4", "git" = "https://github.com/lance-format/lance.git" }
-lance-linalg = { "version" = "=1.0.4", "tag" = "v1.0.4", "git" = "https://github.com/lance-format/lance.git" }
-lance-namespace = { "version" = "=1.0.4", "tag" = "v1.0.4", "git" = "https://github.com/lance-format/lance.git" }
-lance-namespace-impls = { "version" = "=1.0.4", default-features = false, "tag" = "v1.0.4", "git" = "https://github.com/lance-format/lance.git" }
-lance-table = { "version" = "=1.0.4", "tag" = "v1.0.4", "git" = "https://github.com/lance-format/lance.git" }
-lance-testing = { "version" = "=1.0.4", "tag" = "v1.0.4", "git" = "https://github.com/lance-format/lance.git" }
-lance-datafusion = { "version" = "=1.0.4", "tag" = "v1.0.4", "git" = "https://github.com/lance-format/lance.git" }
-lance-encoding = { "version" = "=1.0.4", "tag" = "v1.0.4", "git" = "https://github.com/lance-format/lance.git" }
-lance-arrow = { "version" = "=1.0.4", "tag" = "v1.0.4", "git" = "https://github.com/lance-format/lance.git" }
+lance = { "version" = "=2.0.0-beta.3", default-features = false, "tag" = "v2.0.0-beta.3", "git" = "https://github.com/lance-format/lance.git" }
+lance-core = { "version" = "=2.0.0-beta.3", "tag" = "v2.0.0-beta.3", "git" = "https://github.com/lance-format/lance.git" }
+lance-datagen = { "version" = "=2.0.0-beta.3", "tag" = "v2.0.0-beta.3", "git" = "https://github.com/lance-format/lance.git" }
+lance-file = { "version" = "=2.0.0-beta.3", "tag" = "v2.0.0-beta.3", "git" = "https://github.com/lance-format/lance.git" }
+lance-io = { "version" = "=2.0.0-beta.3", default-features = false, "tag" = "v2.0.0-beta.3", "git" = "https://github.com/lance-format/lance.git" }
+lance-index = { "version" = "=2.0.0-beta.3", "tag" = "v2.0.0-beta.3", "git" = "https://github.com/lance-format/lance.git" }
+lance-linalg = { "version" = "=2.0.0-beta.3", "tag" = "v2.0.0-beta.3", "git" = "https://github.com/lance-format/lance.git" }
+lance-namespace = { "version" = "=2.0.0-beta.3", "tag" = "v2.0.0-beta.3", "git" = "https://github.com/lance-format/lance.git" }
+lance-namespace-impls = { "version" = "=2.0.0-beta.3", default-features = false, "tag" = "v2.0.0-beta.3", "git" = "https://github.com/lance-format/lance.git" }
+lance-table = { "version" = "=2.0.0-beta.3", "tag" = "v2.0.0-beta.3", "git" = "https://github.com/lance-format/lance.git" }
+lance-testing = { "version" = "=2.0.0-beta.3", "tag" = "v2.0.0-beta.3", "git" = "https://github.com/lance-format/lance.git" }
+lance-datafusion = { "version" = "=2.0.0-beta.3", "tag" = "v2.0.0-beta.3", "git" = "https://github.com/lance-format/lance.git" }
+lance-encoding = { "version" = "=2.0.0-beta.3", "tag" = "v2.0.0-beta.3", "git" = "https://github.com/lance-format/lance.git" }
+lance-arrow = { "version" = "=2.0.0-beta.3", "tag" = "v2.0.0-beta.3", "git" = "https://github.com/lance-format/lance.git" }
 ahash = "0.8"
 # Note that this one does not include pyarrow
 arrow = { version = "56.2", optional = false }
--- a/README.md
+++ b/README.md
@@ -66,7 +66,7 @@ Follow the [Quickstart](https://lancedb.com/docs/quickstart/) doc to set up Lanc
 | Python SDK | https://lancedb.github.io/lancedb/python/python/ |
 | Typescript SDK | https://lancedb.github.io/lancedb/js/globals/ |
 | Rust SDK | https://docs.rs/lancedb/latest/lancedb/index.html |
-| REST API | https://docs.lancedb.com/api-reference/rest |
+| REST API | https://docs.lancedb.com/api-reference/introduction |

 ## **Join Us and Contribute**

--- a/ci/run_with_test_connection.sh
+++ b/ci/run_with_test_connection.sh
@@ -16,7 +16,7 @@ check_command_exists() {
 }

 if [[ ! -e ./lancedb ]]; then
-    if [[ x${SOPHON_READ_TOKEN} != "x" ]]; then
+    if [[ -v SOPHON_READ_TOKEN ]]; then
        INPUT="lancedb-linux-x64"
        gh release \
            --repo lancedb/lancedb \
--- a/docs/mkdocs.yml
+++ b/docs/mkdocs.yml
@@ -11,7 +11,7 @@ watch:
 theme:
  name: "material"
  logo: assets/logo.png
-  favicon: assets/favicon.ico
+  favicon: assets/logo.png
  palette:
    # Palette toggle for light mode
    - scheme: lancedb
@@ -32,6 +32,8 @@ theme:
    - content.tooltips
    - toc.follow
    - navigation.top
+    - navigation.tabs
+    - navigation.tabs.sticky
    - navigation.footer
    - navigation.tracking
    - navigation.instant
@@ -113,13 +115,12 @@ markdown_extensions:
      emoji_index: !!python/name:material.extensions.emoji.twemoji
      emoji_generator: !!python/name:material.extensions.emoji.to_svg
  - markdown.extensions.toc:
-      toc_depth: 3
-      permalink: true
-      permalink_title: Anchor link to this section
+      baselevel: 1
+      permalink: ""

 nav:
-  - Documentation:
-      - SDK Reference: index.md
+  - API reference:
+      - Overview: index.md
      - Python: python/python.md
      - Javascript/TypeScript: js/globals.md
      - Java: java/java.md
--- a/docs/src/assets/favicon.ico
+++ b/docs/src/assets/favicon.ico
--- a/docs/src/embeddings/available_embedding_models/multimodal_embedding_functions/voyageai_multimodal_embedding.md
+++ b/docs/src/embeddings/available_embedding_models/multimodal_embedding_functions/voyageai_multimodal_embedding.md
@@ -1,111 +0,0 @@
-# VoyageAI Embeddings : Multimodal
-
-VoyageAI embeddings can also be used to embed both text and image data, only some of the models support image data and you can check the list
-under [https://docs.voyageai.com/docs/multimodal-embeddings](https://docs.voyageai.com/docs/multimodal-embeddings)
-
-Supported multimodal models:
-
- `voyage-multimodal-3` - 1024 dimensions (text + images)
- `voyage-multimodal-3.5` - Flexible dimensions (256, 512, 1024 default, 2048). Supports text, images, and video.
-
-### Video Support (voyage-multimodal-3.5)
-
-The `voyage-multimodal-3.5` model supports video input through:
- Video URLs (`.mp4`, `.webm`, `.mov`, `.avi`, `.mkv`, `.m4v`, `.gif`)
- Video file paths
-
-Constraints: Max 20MB video size.
-
-Supported parameters (to be passed in `create` method) are:
-
-| Parameter | Type | Default Value           | Description                               |
-|---|---|-------------------------|-------------------------------------------|
-| `name` | `str` | `"voyage-multimodal-3"` | The model ID of the VoyageAI model to use |
-| `output_dimension` | `int` | `None` | Output dimension for voyage-multimodal-3.5. Valid: 256, 512, 1024, 2048 |
-
-Usage Example:
-
-```python
-import base64
-import os
-from io import BytesIO
-
-import requests
-import lancedb
-from lancedb.pydantic import LanceModel, Vector
-from lancedb.embeddings import get_registry
-import pandas as pd
-
-os.environ['VOYAGE_API_KEY'] = 'YOUR_VOYAGE_API_KEY'
-
-db = lancedb.connect(".lancedb")
-func = get_registry().get("voyageai").create(name="voyage-multimodal-3")
-
-
-def image_to_base64(image_bytes: bytes):
-    buffered = BytesIO(image_bytes)
-    img_str = base64.b64encode(buffered.getvalue())
-    return img_str.decode("utf-8")
-
-
-class Images(LanceModel):
-    label: str
-    image_uri: str = func.SourceField()  # image uri as the source
-    image_bytes: str = func.SourceField()  # image bytes base64 encoded as the source
-    vector: Vector(func.ndims()) = func.VectorField()  # vector column
-    vec_from_bytes: Vector(func.ndims()) = func.VectorField()  # Another vector column
-
-
-if "images" in db.table_names():
-    db.drop_table("images")
-table = db.create_table("images", schema=Images)
-labels = ["cat", "cat", "dog", "dog", "horse", "horse"]
-uris = [
-    "http://farm1.staticflickr.com/53/167798175_7c7845bbbd_z.jpg",
-    "http://farm1.staticflickr.com/134/332220238_da527d8140_z.jpg",
-    "http://farm9.staticflickr.com/8387/8602747737_2e5c2a45d4_z.jpg",
-    "http://farm5.staticflickr.com/4092/5017326486_1f46057f5f_z.jpg",
-    "http://farm9.staticflickr.com/8216/8434969557_d37882c42d_z.jpg",
-    "http://farm6.staticflickr.com/5142/5835678453_4f3a4edb45_z.jpg",
-]
-# get each uri as bytes
-images_bytes = [image_to_base64(requests.get(uri).content) for uri in uris]
-table.add(
-    pd.DataFrame({"label": labels, "image_uri": uris, "image_bytes": images_bytes})
-)
-```
-Now we can search using text from both the default vector column and the custom vector column
-```python
-
-# text search
-actual = table.search("man's best friend", "vec_from_bytes").limit(1).to_pydantic(Images)[0]
-print(actual.label) # prints "dog"
-
-frombytes = (
-    table.search("man's best friend", vector_column_name="vec_from_bytes")
-    .limit(1)
-    .to_pydantic(Images)[0]
-)
-print(frombytes.label)
-
-```
-
-Because we're using a multi-modal embedding function, we can also search using images
-
-```python
-# image search
-query_image_uri = "http://farm1.staticflickr.com/200/467715466_ed4a31801f_z.jpg"
-image_bytes = requests.get(query_image_uri).content
-query_image = Image.open(BytesIO(image_bytes))
-actual = table.search(query_image, "vec_from_bytes").limit(1).to_pydantic(Images)[0]
-print(actual.label == "dog")
-
-# image search using a custom vector column
-other = (
-    table.search(query_image, vector_column_name="vec_from_bytes")
-    .limit(1)
-    .to_pydantic(Images)[0]
-)
-print(actual.label)
-
-```
--- a/docs/src/embeddings/available_embedding_models/text_embedding_functions/voyageai_embedding.md
+++ b/docs/src/embeddings/available_embedding_models/text_embedding_functions/voyageai_embedding.md
@@ -1,62 +0,0 @@
-# VoyageAI Embeddings
-
-Voyage AI provides cutting-edge embedding and rerankers.
-
-
-Using voyageai API requires voyageai package, which can be installed using `pip install voyageai`. Voyage AI embeddings are used to generate embeddings for text data. The embeddings can be used for various tasks like semantic search, clustering, and classification.
-You also need to set the `VOYAGE_API_KEY` environment variable to use the VoyageAI API.
-
-Supported models are:
-
-**Voyage-4 Series (Latest)**
-
- voyage-4 (1024 dims, general-purpose and multilingual retrieval, 320K batch tokens)
- voyage-4-lite (1024 dims, optimized for latency and cost, 1M batch tokens)
- voyage-4-large (1024 dims, best retrieval quality, 120K batch tokens)
-
-**Voyage-3 Series**
-
- voyage-3
- voyage-3-lite
-
-**Domain-Specific Models**
-
- voyage-finance-2
- voyage-multilingual-2
- voyage-law-2
- voyage-code-2
-
-
-Supported parameters (to be passed in `create` method) are:
-
-| Parameter | Type | Default Value | Description |
-|---|---|--------|---------|
-| `name` | `str` | `None` | The model ID of the model to use. Supported base models for Text Embeddings: voyage-4, voyage-4-lite, voyage-4-large, voyage-3, voyage-3-lite, voyage-finance-2, voyage-multilingual-2, voyage-law-2, voyage-code-2 |
-| `input_type` | `str` | `None` | Type of the input text. Default to None. Other options: query, document. |
-| `truncation` | `bool` | `True` | Whether to truncate the input texts to fit within the context length. |
-
-
-Usage Example:
-    
-```python
-    import lancedb
-    from lancedb.pydantic import LanceModel, Vector
-    from lancedb.embeddings import EmbeddingFunctionRegistry
-
-    voyageai = EmbeddingFunctionRegistry
-        .get_instance()
-        .get("voyageai")
-        .create(name="voyage-3")
-
-    class TextModel(LanceModel):
-        text: str = voyageai.SourceField()
-        vector: Vector(voyageai.ndims()) =  voyageai.VectorField()
-
-    data = [ { "text": "hello world" },
-            { "text": "goodbye world" }]
-
-    db = lancedb.connect("~/.lancedb")
-    tbl = db.create_table("test", schema=TextModel, mode="overwrite")
-
-    tbl.add(data)
-```
--- a/docs/src/index.md
+++ b/docs/src/index.md
@@ -1,12 +1,8 @@
-# SDK Reference
+# API Reference

-This site contains the API reference for the client SDKs supported by [LanceDB](https://lancedb.com).
+This page contains the API reference for the SDKs supported by the LanceDB team.

 - [Python](python/python.md)
 - [JavaScript/TypeScript](js/globals.md)
 - [Java](java/java.md)
- [Rust](https://docs.rs/lancedb/latest/lancedb/index.html)
-
-!!! info "LanceDB Documentation"
-
-    If you're looking for the full documentation of LanceDB, visit [docs.lancedb.com](https://docs.lancedb.com).
+- [Rust](https://docs.rs/lancedb/latest/lancedb/index.html)
--- a/docs/src/java/java.md
+++ b/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>0.24.1</version>
+    <version>0.23.1-beta.1</version>
 </dependency>
 ```

--- a/docs/src/styles/extra.css
+++ b/docs/src/styles/extra.css
@@ -85,26 +85,17 @@

 /* Header gradient (only header area) */
 .md-header {
-  background: linear-gradient(90deg, #e4d8f8 0%, #F0B7C1 45%, #E55A2B 100%);
+  background: linear-gradient(90deg, #3B2E58 0%, #F0B7C1 45%, #E55A2B 100%);
  box-shadow: inset 0 1px 0 rgba(255,255,255,0.08), 0 1px 0 rgba(0,0,0,0.08);
 }

-/* Improve brand title contrast on the lavender side */
-.md-header__title,
-.md-header__topic,
-.md-header__title .md-ellipsis,
-.md-header__topic .md-ellipsis {
-  color: #2b1b3a;
-  text-shadow: 0 1px 0 rgba(255, 255, 255, 0.25);
-}
-
 /* Same colors as header for tabs (that hold the text) */
 .md-tabs {
-  background: linear-gradient(90deg, #e4d8f8 0%, #F0B7C1 45%, #E55A2B 100%);
+  background: linear-gradient(90deg, #3B2E58 0%, #F0B7C1 45%, #E55A2B 100%);
 }

 /* Dark scheme variant */
 [data-md-color-scheme="slate"] .md-header,
 [data-md-color-scheme="slate"] .md-tabs {
-  background: linear-gradient(90deg, #e4d8f8 0%, #F0B7C1 45%, #E55A2B 100%);
+  background: linear-gradient(90deg, #3B2E58 0%, #F0B7C1 45%, #E55A2B 100%);
 }
--- a/java/lancedb-core/pom.xml
+++ b/java/lancedb-core/pom.xml
@@ -8,7 +8,7 @@
    <parent>
      <groupId>com.lancedb</groupId>
      <artifactId>lancedb-parent</artifactId>
-      <version>0.24.1-final.0</version>
+      <version>0.23.1-beta.1</version>
      <relativePath>../pom.xml</relativePath>
    </parent>

--- a/java/pom.xml
+++ b/java/pom.xml
@@ -6,7 +6,7 @@

    <groupId>com.lancedb</groupId>
    <artifactId>lancedb-parent</artifactId>
-    <version>0.24.1-final.0</version>
+    <version>0.23.1-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>1.0.4</lance-core.version>
+        <lance-core.version>1.0.0-rc.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>
--- a/nodejs/Cargo.toml
+++ b/nodejs/Cargo.toml
@@ -1,7 +1,7 @@
 [package]
 name = "lancedb-nodejs"
 edition.workspace = true
-version = "0.24.1"
+version = "0.23.1-beta.1"
 license.workspace = true
 description.workspace = true
 repository.workspace = true
@@ -36,6 +36,6 @@ aws-lc-rs = "=1.13.0"
 napi-build = "2.1"

 [features]
-default = ["remote", "lancedb/aws", "lancedb/gcs", "lancedb/azure", "lancedb/dynamodb", "lancedb/oss", "lancedb/huggingface"]
+default = ["remote", "lancedb/default"]
 fp16kernels = ["lancedb/fp16kernels"]
 remote = ["lancedb/remote"]
--- a/nodejs/npm/darwin-arm64/package.json
+++ b/nodejs/npm/darwin-arm64/package.json
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-darwin-arm64",
-	"version": "0.24.1",
+	"version": "0.23.1-beta.1",
 	"os": ["darwin"],
 	"cpu": ["arm64"],
 	"main": "lancedb.darwin-arm64.node",
--- a/nodejs/npm/darwin-x64/package.json
+++ b/nodejs/npm/darwin-x64/package.json
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-darwin-x64",
-	"version": "0.24.1",
+	"version": "0.23.1-beta.1",
 	"os": ["darwin"],
 	"cpu": ["x64"],
 	"main": "lancedb.darwin-x64.node",
--- a/nodejs/npm/linux-arm64-gnu/package.json
+++ b/nodejs/npm/linux-arm64-gnu/package.json
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-arm64-gnu",
-	"version": "0.24.1",
+	"version": "0.23.1-beta.1",
 	"os": ["linux"],
 	"cpu": ["arm64"],
 	"main": "lancedb.linux-arm64-gnu.node",
--- a/nodejs/npm/linux-arm64-musl/package.json
+++ b/nodejs/npm/linux-arm64-musl/package.json
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-arm64-musl",
-	"version": "0.24.1",
+	"version": "0.23.1-beta.1",
 	"os": ["linux"],
 	"cpu": ["arm64"],
 	"main": "lancedb.linux-arm64-musl.node",
--- a/nodejs/npm/linux-x64-gnu/package.json
+++ b/nodejs/npm/linux-x64-gnu/package.json
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-x64-gnu",
-	"version": "0.24.1",
+	"version": "0.23.1-beta.1",
 	"os": ["linux"],
 	"cpu": ["x64"],
 	"main": "lancedb.linux-x64-gnu.node",
--- a/nodejs/npm/linux-x64-musl/package.json
+++ b/nodejs/npm/linux-x64-musl/package.json
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-x64-musl",
-	"version": "0.24.1",
+	"version": "0.23.1-beta.1",
 	"os": ["linux"],
 	"cpu": ["x64"],
 	"main": "lancedb.linux-x64-musl.node",
--- a/nodejs/npm/win32-arm64-msvc/package.json
+++ b/nodejs/npm/win32-arm64-msvc/package.json
@@ -1,6 +1,6 @@
 {
  "name": "@lancedb/lancedb-win32-arm64-msvc",
-  "version": "0.24.1",
+  "version": "0.23.1-beta.1",
  "os": [
    "win32"
  ],
--- a/nodejs/npm/win32-x64-msvc/package.json
+++ b/nodejs/npm/win32-x64-msvc/package.json
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-win32-x64-msvc",
-	"version": "0.24.1",
+	"version": "0.23.1-beta.1",
 	"os": ["win32"],
 	"cpu": ["x64"],
 	"main": "lancedb.win32-x64-msvc.node",
--- a/nodejs/package-lock.json
+++ b/nodejs/package-lock.json
@@ -1,12 +1,12 @@
 {
  "name": "@lancedb/lancedb",
-  "version": "0.24.1",
+  "version": "0.23.1-beta.1",
  "lockfileVersion": 3,
  "requires": true,
  "packages": {
    "": {
      "name": "@lancedb/lancedb",
-      "version": "0.24.1",
+      "version": "0.23.1-beta.1",
      "cpu": [
        "x64",
        "arm64"
--- a/nodejs/package.json
+++ b/nodejs/package.json
@@ -11,7 +11,7 @@
    "ann"
  ],
  "private": false,
-  "version": "0.24.1",
+  "version": "0.23.1-beta.1",
  "main": "dist/index.js",
  "exports": {
    ".": "./dist/index.js",
--- a/python/.bumpversion.toml
+++ b/python/.bumpversion.toml
@@ -1,5 +1,5 @@
 [tool.bumpversion]
-current_version = "0.28.0-beta.0"
+current_version = "0.26.1-beta.1"
 parse = """(?x)
    (?P<major>0|[1-9]\\d*)\\.
    (?P<minor>0|[1-9]\\d*)\\.
--- a/python/CONTRIBUTING.md
+++ b/python/CONTRIBUTING.md
@@ -16,7 +16,7 @@ The Python package is a wrapper around the Rust library, `lancedb`. We use

 To set up your development environment, you will need to install the following:

-1. Python 3.10 or later
+1. Python 3.9 or later
 2. Cargo (Rust's package manager). Use [rustup](https://rustup.rs/) to install.
 3. [protoc](https://grpc.io/docs/protoc-installation/) (Protocol Buffers compiler)

--- a/python/Cargo.toml
+++ b/python/Cargo.toml
@@ -1,13 +1,13 @@
 [package]
 name = "lancedb-python"
-version = "0.28.0-beta.0"
+version = "0.26.1-beta.1"
 edition.workspace = true
 description = "Python bindings for LanceDB"
 license.workspace = true
 repository.workspace = true
 keywords.workspace = true
 categories.workspace = true
-rust-version = "1.88.0"
+rust-version = "1.75.0"

 [lib]
 name = "_lancedb"
@@ -21,7 +21,7 @@ lance-core.workspace = true
 lance-namespace.workspace = true
 lance-io.workspace = true
 env_logger.workspace = true
-pyo3 = { version = "0.25", features = ["extension-module", "abi3-py310"] }
+pyo3 = { version = "0.25", features = ["extension-module", "abi3-py39"] }
 pyo3-async-runtimes = { version = "0.25", features = [
    "attributes",
    "tokio-runtime",
@@ -34,10 +34,10 @@ tokio = { version = "1.40", features = ["sync"] }
 [build-dependencies]
 pyo3-build-config = { version = "0.25", features = [
    "extension-module",
-    "abi3-py310",
+    "abi3-py39",
 ] }

 [features]
-default = ["remote",  "lancedb/aws", "lancedb/gcs", "lancedb/azure", "lancedb/dynamodb", "lancedb/oss", "lancedb/huggingface"]
+default = ["remote", "lancedb/default"]
 fp16kernels = ["lancedb/fp16kernels"]
 remote = ["lancedb/remote"]
--- a/python/pyproject.toml
+++ b/python/pyproject.toml
@@ -16,7 +16,7 @@ description = "lancedb"
 authors = [{ name = "LanceDB Devs", email = "dev@lancedb.com" }]
 license = { file = "LICENSE" }
 readme = "README.md"
-requires-python = ">=3.10"
+requires-python = ">=3.9"
 keywords = [
    "data-format",
    "data-science",
@@ -33,10 +33,10 @@ classifiers = [
    "Programming Language :: Python",
    "Programming Language :: Python :: 3",
    "Programming Language :: Python :: 3 :: Only",
+    "Programming Language :: Python :: 3.9",
    "Programming Language :: Python :: 3.10",
    "Programming Language :: Python :: 3.11",
    "Programming Language :: Python :: 3.12",
-    "Programming Language :: Python :: 3.13",
    "Topic :: Scientific/Engineering",
 ]

@@ -137,4 +137,4 @@ include = [
    "python/lancedb/_lancedb.pyi",
 ]
 exclude = ["python/tests/"]
-pythonVersion = "3.13"
+pythonVersion = "3.12"
--- a/python/python/lancedb/init.py
+++ b/python/python/lancedb/init.py
@@ -13,7 +13,6 @@ __version__ = importlib.metadata.version("lancedb")

 from ._lancedb import connect as lancedb_connect
 from .common import URI, sanitize_uri
-from urllib.parse import urlparse
 from .db import AsyncConnection, DBConnection, LanceDBConnection
 from .io import StorageOptionsProvider
 from .remote import ClientConfig
@@ -29,39 +28,6 @@ from .namespace import (
 )


-def _check_s3_bucket_with_dots(
-    uri: str, storage_options: Optional[Dict[str, str]]
-) -> None:
-    """
-    Check if an S3 URI has a bucket name containing dots and warn if no region
-    is specified. S3 buckets with dots cannot use virtual-hosted-style URLs,
-    which breaks automatic region detection.
-
-    See: https://github.com/lancedb/lancedb/issues/1898
-    """
-    if not isinstance(uri, str) or not uri.startswith("s3://"):
-        return
-
-    parsed = urlparse(uri)
-    bucket = parsed.netloc
-
-    if "." not in bucket:
-        return
-
-    # Check if region is provided in storage_options
-    region_keys = {"region", "aws_region"}
-    has_region = storage_options and any(k in storage_options for k in region_keys)
-
-    if not has_region:
-        raise ValueError(
-            f"S3 bucket name '{bucket}' contains dots, which prevents automatic "
-            f"region detection. Please specify the region explicitly via "
-            f"storage_options={{'region': '<your-region>'}} or "
-            f"storage_options={{'aws_region': '<your-region>'}}. "
-            f"See https://github.com/lancedb/lancedb/issues/1898 for details."
-        )
-
-
 def connect(
    uri: URI,
    *,
@@ -155,11 +121,9 @@ def connect(
            storage_options=storage_options,
            **kwargs,
        )
-    _check_s3_bucket_with_dots(str(uri), storage_options)

    if kwargs:
        raise ValueError(f"Unknown keyword arguments: {kwargs}")
-
    return LanceDBConnection(
        uri,
        read_consistency_interval=read_consistency_interval,
@@ -247,8 +211,6 @@ async def connect_async(
    if isinstance(client_config, dict):
        client_config = ClientConfig(**client_config)

-    _check_s3_bucket_with_dots(str(uri), storage_options)
-
    return AsyncConnection(
        await lancedb_connect(
            sanitize_uri(uri),
--- a/python/python/lancedb/_lancedb.pyi
+++ b/python/python/lancedb/_lancedb.pyi
@@ -179,7 +179,6 @@ class Table:
        cleanup_since_ms: Optional[int] = None,
        delete_unverified: Optional[bool] = None,
    ) -> OptimizeStats: ...
-    async def uri(self) -> str: ...
    @property
    def tags(self) -> Tags: ...
    def query(self) -> Query: ...
--- a/python/python/lancedb/background_loop.py
+++ b/python/python/lancedb/background_loop.py
@@ -22,12 +22,7 @@ class BackgroundEventLoop:
        self.thread.start()

    def run(self, future):
-        concurrent_future = asyncio.run_coroutine_threadsafe(future, self.loop)
-        try:
-            return concurrent_future.result()
-        except BaseException:
-            concurrent_future.cancel()
-            raise
+        return asyncio.run_coroutine_threadsafe(future, self.loop).result()


 LOOP = BackgroundEventLoop()
--- a/python/python/lancedb/db.py
+++ b/python/python/lancedb/db.py
@@ -210,8 +210,10 @@ class DBConnection(EnforceOverrides):
        page_token: str, optional
            The token to use for pagination. If not present, start from the beginning.
            Typically, this token is last table name from the previous page.
+            Only supported by LanceDb Cloud.
        limit: int, default 10
            The size of the page to return.
+            Only supported by LanceDb Cloud.

        Returns
        -------
--- a/python/python/lancedb/embeddings/colpali.py
+++ b/python/python/lancedb/embeddings/colpali.py
@@ -275,7 +275,7 @@ class ColPaliEmbeddings(EmbeddingFunction):
        """
        Convert image inputs to PIL Images.
        """
-        PIL_Image = attempt_import_or_raise("PIL.Image", "pillow")
+        PIL = attempt_import_or_raise("PIL", "pillow")
        requests = attempt_import_or_raise("requests", "requests")
        images = self.sanitize_input(images)
        pil_images = []
@@ -285,12 +285,12 @@ class ColPaliEmbeddings(EmbeddingFunction):
                    if image.startswith(("http://", "https://")):
                        response = requests.get(image, timeout=10)
                        response.raise_for_status()
-                        pil_images.append(PIL_Image.open(io.BytesIO(response.content)))
+                        pil_images.append(PIL.Image.open(io.BytesIO(response.content)))
                    else:
-                        with PIL_Image.open(image) as im:
+                        with PIL.Image.open(image) as im:
                            pil_images.append(im.copy())
                elif isinstance(image, bytes):
-                    pil_images.append(PIL_Image.open(io.BytesIO(image)))
+                    pil_images.append(PIL.Image.open(io.BytesIO(image)))
                else:
                    # Assume it's a PIL Image; will raise if invalid
                    pil_images.append(image)
--- a/python/python/lancedb/embeddings/jinaai.py
+++ b/python/python/lancedb/embeddings/jinaai.py
@@ -77,8 +77,8 @@ class JinaEmbeddings(EmbeddingFunction):
            if isinstance(inputs, list):
                inputs = inputs
            else:
-                PIL_Image = attempt_import_or_raise("PIL.Image", "pillow")
-                if isinstance(inputs, PIL_Image.Image):
+                PIL = attempt_import_or_raise("PIL", "pillow")
+                if isinstance(inputs, PIL.Image.Image):
                    inputs = [inputs]
        return inputs

@@ -89,13 +89,13 @@ class JinaEmbeddings(EmbeddingFunction):
        elif isinstance(image, (str, Path)):
            parsed = urlparse.urlparse(image)
            # TODO handle drive letter on windows.
-            PIL_Image = attempt_import_or_raise("PIL.Image", "pillow")
+            PIL = attempt_import_or_raise("PIL", "pillow")
            if parsed.scheme == "file":
-                pil_image = PIL_Image.open(parsed.path)
+                pil_image = PIL.Image.open(parsed.path)
            elif parsed.scheme == "":
-                pil_image = PIL_Image.open(image if os.name == "nt" else parsed.path)
+                pil_image = PIL.Image.open(image if os.name == "nt" else parsed.path)
            elif parsed.scheme.startswith("http"):
-                pil_image = PIL_Image.open(io.BytesIO(url_retrieve(image)))
+                pil_image = PIL.Image.open(io.BytesIO(url_retrieve(image)))
            else:
                raise NotImplementedError("Only local and http(s) urls are supported")
            buffered = io.BytesIO()
@@ -103,9 +103,9 @@ class JinaEmbeddings(EmbeddingFunction):
            image_bytes = buffered.getvalue()
            image_dict = {"image": base64.b64encode(image_bytes).decode("utf-8")}
        else:
-            PIL_Image = attempt_import_or_raise("PIL.Image", "pillow")
+            PIL = attempt_import_or_raise("PIL", "pillow")

-            if isinstance(image, PIL_Image.Image):
+            if isinstance(image, PIL.Image.Image):
                buffered = io.BytesIO()
                image.save(buffered, format="PNG")
                image_bytes = buffered.getvalue()
@@ -136,9 +136,9 @@ class JinaEmbeddings(EmbeddingFunction):
        elif isinstance(query, (Path, bytes)):
            return [self.generate_image_embedding(query)]
        else:
-            PIL_Image = attempt_import_or_raise("PIL.Image", "pillow")
+            PIL = attempt_import_or_raise("PIL", "pillow")

-            if isinstance(query, PIL_Image.Image):
+            if isinstance(query, PIL.Image.Image):
                return [self.generate_image_embedding(query)]
            else:
                raise TypeError(
--- a/python/python/lancedb/embeddings/open_clip.py
+++ b/python/python/lancedb/embeddings/open_clip.py
@@ -71,8 +71,8 @@ class OpenClipEmbeddings(EmbeddingFunction):
        if isinstance(query, str):
            return [self.generate_text_embeddings(query)]
        else:
-            PIL_Image = attempt_import_or_raise("PIL.Image", "pillow")
-            if isinstance(query, PIL_Image.Image):
+            PIL = attempt_import_or_raise("PIL", "pillow")
+            if isinstance(query, PIL.Image.Image):
                return [self.generate_image_embedding(query)]
            else:
                raise TypeError("OpenClip supports str or PIL Image as query")
@@ -145,20 +145,20 @@ class OpenClipEmbeddings(EmbeddingFunction):
            return self._encode_and_normalize_image(image)

    def _to_pil(self, image: Union[str, bytes]):
-        PIL_Image = attempt_import_or_raise("PIL.Image", "pillow")
+        PIL = attempt_import_or_raise("PIL", "pillow")
        if isinstance(image, bytes):
-            return PIL_Image.open(io.BytesIO(image))
-        if isinstance(image, PIL_Image.Image):
+            return PIL.Image.open(io.BytesIO(image))
+        if isinstance(image, PIL.Image.Image):
            return image
        elif isinstance(image, str):
            parsed = urlparse.urlparse(image)
            # TODO handle drive letter on windows.
            if parsed.scheme == "file":
-                return PIL_Image.open(parsed.path)
+                return PIL.Image.open(parsed.path)
            elif parsed.scheme == "":
-                return PIL_Image.open(image if os.name == "nt" else parsed.path)
+                return PIL.Image.open(image if os.name == "nt" else parsed.path)
            elif parsed.scheme.startswith("http"):
-                return PIL_Image.open(io.BytesIO(url_retrieve(image)))
+                return PIL.Image.open(io.BytesIO(url_retrieve(image)))
            else:
                raise NotImplementedError("Only local and http(s) urls are supported")

--- a/python/python/lancedb/embeddings/siglip.py
+++ b/python/python/lancedb/embeddings/siglip.py
@@ -56,8 +56,8 @@ class SigLipEmbeddings(EmbeddingFunction):
        if isinstance(query, str):
            return [self.generate_text_embeddings(query)]
        else:
-            PIL_Image = attempt_import_or_raise("PIL.Image", "pillow")
-            if isinstance(query, PIL_Image.Image):
+            PIL = attempt_import_or_raise("PIL", "pillow")
+            if isinstance(query, PIL.Image.Image):
                return [self.generate_image_embedding(query)]
            else:
                raise TypeError("SigLIP supports str or PIL Image as query")
@@ -127,21 +127,21 @@ class SigLipEmbeddings(EmbeddingFunction):
            return image_features.cpu().detach().numpy().squeeze()

    def _to_pil(self, image: Union[str, bytes, "PIL.Image.Image"]):
-        PIL_Image = attempt_import_or_raise("PIL.Image", "pillow")
-        if isinstance(image, PIL_Image.Image):
+        PIL = attempt_import_or_raise("PIL", "pillow")
+        if isinstance(image, PIL.Image.Image):
            return image.convert("RGB") if image.mode != "RGB" else image
        elif isinstance(image, bytes):
-            return PIL_Image.open(io.BytesIO(image)).convert("RGB")
+            return PIL.Image.open(io.BytesIO(image)).convert("RGB")
        elif isinstance(image, str):
            parsed = urlparse.urlparse(image)
            if parsed.scheme == "file":
-                return PIL_Image.open(parsed.path).convert("RGB")
+                return PIL.Image.open(parsed.path).convert("RGB")
            elif parsed.scheme == "":
                path = image if os.name == "nt" else parsed.path
-                return PIL_Image.open(path).convert("RGB")
+                return PIL.Image.open(path).convert("RGB")
            elif parsed.scheme.startswith("http"):
                image_bytes = url_retrieve(image)
-                return PIL_Image.open(io.BytesIO(image_bytes)).convert("RGB")
+                return PIL.Image.open(io.BytesIO(image_bytes)).convert("RGB")
            else:
                raise NotImplementedError("Only local and http(s) urls are supported")
        else:
--- a/python/python/lancedb/embeddings/voyageai.py
+++ b/python/python/lancedb/embeddings/voyageai.py
@@ -2,7 +2,7 @@
 # SPDX-FileCopyrightText: Copyright The LanceDB Authors
 import base64
 import os
-from typing import ClassVar, TYPE_CHECKING, List, Union, Any, Generator, Optional
+from typing import ClassVar, TYPE_CHECKING, List, Union, Any, Generator

 from pathlib import Path
 from urllib.parse import urlparse
@@ -21,9 +21,6 @@ if TYPE_CHECKING:

 # Token limits for different VoyageAI models
 VOYAGE_TOTAL_TOKEN_LIMITS = {
-    "voyage-4": 320_000,
-    "voyage-4-lite": 1_000_000,
-    "voyage-4-large": 120_000,
    "voyage-context-3": 32_000,
    "voyage-3.5-lite": 1_000_000,
    "voyage-3.5": 320_000,
@@ -48,32 +45,14 @@ def is_valid_url(text):
        return False


-VIDEO_EXTENSIONS = {".mp4", ".webm", ".mov", ".avi", ".mkv", ".m4v", ".gif"}
-
-
-def is_video_url(url: str) -> bool:
-    """Check if URL points to a video file based on extension."""
-    parsed = urlparse(url)
-    path = parsed.path.lower()
-    return any(path.endswith(ext) for ext in VIDEO_EXTENSIONS)
-
-
-def is_video_path(path: Path) -> bool:
-    """Check if file path is a video file based on extension."""
-    return path.suffix.lower() in VIDEO_EXTENSIONS
-
-
 def transform_input(input_data: Union[str, bytes, Path]):
-    PIL_Image = attempt_import_or_raise("PIL.Image", "pillow")
+    PIL = attempt_import_or_raise("PIL", "pillow")
    if isinstance(input_data, str):
        if is_valid_url(input_data):
-            if is_video_url(input_data):
-                content = {"type": "video_url", "video_url": input_data}
-            else:
-                content = {"type": "image_url", "image_url": input_data}
+            content = {"type": "image_url", "image_url": input_data}
        else:
            content = {"type": "text", "text": input_data}
-    elif isinstance(input_data, PIL_Image.Image):
+    elif isinstance(input_data, PIL.Image.Image):
        buffered = BytesIO()
        input_data.save(buffered, format="JPEG")
        img_str = base64.b64encode(buffered.getvalue()).decode("utf-8")
@@ -82,7 +61,7 @@ def transform_input(input_data: Union[str, bytes, Path]):
            "image_base64": "data:image/jpeg;base64," + img_str,
        }
    elif isinstance(input_data, bytes):
-        img = PIL_Image.open(BytesIO(input_data))
+        img = PIL.Image.open(BytesIO(input_data))
        buffered = BytesIO()
        img.save(buffered, format="JPEG")
        img_str = base64.b64encode(buffered.getvalue()).decode("utf-8")
@@ -91,24 +70,14 @@ def transform_input(input_data: Union[str, bytes, Path]):
            "image_base64": "data:image/jpeg;base64," + img_str,
        }
    elif isinstance(input_data, Path):
-        if is_video_path(input_data):
-            # Read video file and encode as base64
-            with open(input_data, "rb") as f:
-                video_bytes = f.read()
-            video_str = base64.b64encode(video_bytes).decode("utf-8")
-            content = {
-                "type": "video_base64",
-                "video_base64": video_str,
-            }
-        else:
-            img = PIL_Image.open(input_data)
-            buffered = BytesIO()
-            img.save(buffered, format="JPEG")
-            img_str = base64.b64encode(buffered.getvalue()).decode("utf-8")
-            content = {
-                "type": "image_base64",
-                "image_base64": "data:image/jpeg;base64," + img_str,
-            }
+        img = PIL.Image.open(input_data)
+        buffered = BytesIO()
+        img.save(buffered, format="JPEG")
+        img_str = base64.b64encode(buffered.getvalue()).decode("utf-8")
+        content = {
+            "type": "image_base64",
+            "image_base64": "data:image/jpeg;base64," + img_str,
+        }
    else:
        raise ValueError("Each input should be either str, bytes, Path or Image.")

@@ -119,11 +88,9 @@ def sanitize_multimodal_input(inputs: Union[TEXT, IMAGES]) -> List[Any]:
    """
    Sanitize the input to the embedding function.
    """
-    PIL_Image = attempt_import_or_raise("PIL.Image", "pillow")
-    if isinstance(inputs, (str, bytes, Path, PIL_Image.Image)):
+    PIL = attempt_import_or_raise("PIL", "pillow")
+    if isinstance(inputs, (str, bytes, Path, PIL.Image.Image)):
        inputs = [inputs]
-    elif isinstance(inputs, list):
-        pass  # Already a list, use as-is
    elif isinstance(inputs, pa.Array):
        inputs = inputs.to_pylist()
    elif isinstance(inputs, pa.ChunkedArray):
@@ -133,7 +100,7 @@ def sanitize_multimodal_input(inputs: Union[TEXT, IMAGES]) -> List[Any]:
            f"Input type {type(inputs)} not allowed with multimodal model."
        )

-    if not all(isinstance(x, (str, bytes, Path, PIL_Image.Image)) for x in inputs):
+    if not all(isinstance(x, (str, bytes, Path, PIL.Image.Image)) for x in inputs):
        raise ValueError("Each input should be either str, bytes, Path or Image.")

    return [transform_input(i) for i in inputs]
@@ -170,25 +137,17 @@ class VoyageAIEmbeddingFunction(EmbeddingFunction):
    name: str
        The name of the model to use. List of acceptable models:

-            * voyage-4 (1024 dims, general-purpose and multilingual retrieval)
-            * voyage-4-lite (1024 dims, optimized for latency and cost)
-            * voyage-4-large (1024 dims, best retrieval quality)
            * voyage-context-3
            * voyage-3.5
            * voyage-3.5-lite
            * voyage-3
            * voyage-3-lite
            * voyage-multimodal-3
-            * voyage-multimodal-3.5
            * voyage-finance-2
            * voyage-multilingual-2
            * voyage-law-2
            * voyage-code-2

-    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.

    Examples
    --------
@@ -216,14 +175,8 @@ class VoyageAIEmbeddingFunction(EmbeddingFunction):
    """

    name: str
-    output_dimension: Optional[int] = None
    client: ClassVar = None
-    _FLEXIBLE_DIM_MODELS: ClassVar[list] = ["voyage-multimodal-3.5"]
-    _VALID_DIMENSIONS: ClassVar[list] = [256, 512, 1024, 2048]
    text_embedding_models: list = [
-        "voyage-4",
-        "voyage-4-lite",
-        "voyage-4-large",
        "voyage-3.5",
        "voyage-3.5-lite",
        "voyage-3",
@@ -233,7 +186,7 @@ class VoyageAIEmbeddingFunction(EmbeddingFunction):
        "voyage-law-2",
        "voyage-code-2",
    ]
-    multimodal_embedding_models: list = ["voyage-multimodal-3", "voyage-multimodal-3.5"]
+    multimodal_embedding_models: list = ["voyage-multimodal-3"]
    contextual_embedding_models: list = ["voyage-context-3"]

    def _is_multimodal_model(self, model_name: str):
@@ -245,25 +198,11 @@ class VoyageAIEmbeddingFunction(EmbeddingFunction):
        return model_name in self.contextual_embedding_models or "context" in model_name

    def ndims(self):
-        # Handle flexible dimension models
-        if self.name in self._FLEXIBLE_DIM_MODELS:
-            if self.output_dimension is not None:
-                if self.output_dimension not in self._VALID_DIMENSIONS:
-                    raise ValueError(
-                        f"Invalid output_dimension {self.output_dimension} "
-                        f"for {self.name}. Valid options: {self._VALID_DIMENSIONS}"
-                    )
-                return self.output_dimension
-            return 1024  # default dimension
-
        if self.name == "voyage-3-lite":
            return 512
        elif self.name == "voyage-code-2":
            return 1536
        elif self.name in [
-            "voyage-4",
-            "voyage-4-lite",
-            "voyage-4-large",
            "voyage-context-3",
            "voyage-3.5",
            "voyage-3.5-lite",
@@ -272,17 +211,12 @@ class VoyageAIEmbeddingFunction(EmbeddingFunction):
            "voyage-finance-2",
            "voyage-multilingual-2",
            "voyage-law-2",
+            "voyage-multimodal-3",
        ]:
            return 1024
        else:
            raise ValueError(f"Model {self.name} not supported")

-    def _get_multimodal_kwargs(self, **kwargs):
-        """Get kwargs for multimodal embed call, including output_dimension if set."""
-        if self.name in self._FLEXIBLE_DIM_MODELS and self.output_dimension is not None:
-            kwargs["output_dimension"] = self.output_dimension
-        return kwargs
-
    def compute_query_embeddings(
        self, query: Union[str, "PIL.Image.Image"], *args, **kwargs
    ) -> List[np.ndarray]:
@@ -300,7 +234,6 @@ class VoyageAIEmbeddingFunction(EmbeddingFunction):
        """
        client = VoyageAIEmbeddingFunction._get_client()
        if self._is_multimodal_model(self.name):
-            kwargs = self._get_multimodal_kwargs(**kwargs)
            result = client.multimodal_embed(
                inputs=[[query]], model=self.name, input_type="query", **kwargs
            )
@@ -342,7 +275,6 @@ class VoyageAIEmbeddingFunction(EmbeddingFunction):
            )
            if has_images:
                # Use non-batched API for images
-                kwargs = self._get_multimodal_kwargs(**kwargs)
                result = client.multimodal_embed(
                    inputs=sanitized, model=self.name, input_type="document", **kwargs
                )
@@ -425,7 +357,6 @@ class VoyageAIEmbeddingFunction(EmbeddingFunction):
            callable: A function that takes a batch of texts and returns embeddings.
        """
        if self._is_multimodal_model(self.name):
-            multimodal_kwargs = self._get_multimodal_kwargs(**kwargs)

            def embed_batch(batch: List[str]) -> List[np.array]:
                batch_inputs = sanitize_multimodal_input(batch)
@@ -433,7 +364,7 @@ class VoyageAIEmbeddingFunction(EmbeddingFunction):
                    inputs=batch_inputs,
                    model=self.name,
                    input_type=input_type,
-                    **multimodal_kwargs,
+                    **kwargs,
                )
                return result.embeddings

--- a/python/python/lancedb/pydantic.py
+++ b/python/python/lancedb/pydantic.py
@@ -275,7 +275,7 @@ def _py_type_to_arrow_type(py_type: Type[Any], field: FieldInfo) -> pa.DataType:
        return pa.timestamp("us", tz=tz)
    elif getattr(py_type, "__origin__", None) in (list, tuple):
        child = py_type.__args__[0]
-        return _pydantic_list_child_to_arrow(child, field)
+        return pa.list_(_py_type_to_arrow_type(child, field))
    raise TypeError(
        f"Converting Pydantic type to Arrow Type: unsupported type {py_type}."
    )
@@ -298,18 +298,12 @@ else:


 def _pydantic_type_to_arrow_type(tp: Any, field: FieldInfo) -> pa.DataType:
-    def _safe_issubclass(candidate: Any, base: type) -> bool:
-        try:
-            return issubclass(candidate, base)
-        except TypeError:
-            return False
-
    if inspect.isclass(tp):
-        if _safe_issubclass(tp, pydantic.BaseModel):
+        if issubclass(tp, pydantic.BaseModel):
            # Struct
            fields = _pydantic_model_to_fields(tp)
            return pa.struct(fields)
-        if _safe_issubclass(tp, FixedSizeListMixin):
+        if issubclass(tp, FixedSizeListMixin):
            if getattr(tp, "is_multi_vector", lambda: False)():
                return pa.list_(pa.list_(tp.value_arrow_type(), tp.dim()))
            # For regular Vector
@@ -317,67 +311,45 @@ def _pydantic_type_to_arrow_type(tp: Any, field: FieldInfo) -> pa.DataType:
    return _py_type_to_arrow_type(tp, field)


-def _pydantic_list_child_to_arrow(child: Any, field: FieldInfo) -> pa.DataType:
-    unwrapped = _unwrap_optional_annotation(child)
-    if unwrapped is not None:
-        return pa.list_(
-            pa.field("item", _pydantic_type_to_arrow_type(unwrapped, field), True)
-        )
-    return pa.list_(_pydantic_type_to_arrow_type(child, field))
-
-
-def _unwrap_optional_annotation(annotation: Any) -> Any | None:
-    if isinstance(annotation, (_GenericAlias, GenericAlias)):
-        origin = annotation.__origin__
-        args = annotation.__args__
-        if origin == Union:
-            non_none = [arg for arg in args if arg is not type(None)]
-            if len(non_none) == 1 and len(non_none) != len(args):
-                return non_none[0]
-    elif sys.version_info >= (3, 10) and isinstance(annotation, types.UnionType):
-        args = annotation.__args__
-        non_none = [arg for arg in args if arg is not type(None)]
-        if len(non_none) == 1 and len(non_none) != len(args):
-            return non_none[0]
-    return None
-
-
 def _pydantic_to_arrow_type(field: FieldInfo) -> pa.DataType:
    """Convert a Pydantic FieldInfo to Arrow DataType"""
-    unwrapped = _unwrap_optional_annotation(field.annotation)
-    if unwrapped is not None:
-        return _pydantic_type_to_arrow_type(unwrapped, field)
    if isinstance(field.annotation, (_GenericAlias, GenericAlias)):
        origin = field.annotation.__origin__
        args = field.annotation.__args__

        if origin is list:
            child = args[0]
-            return _pydantic_list_child_to_arrow(child, field)
+            return pa.list_(_py_type_to_arrow_type(child, field))
+        elif origin == Union:
+            if len(args) == 2 and args[1] is type(None):
+                return _pydantic_type_to_arrow_type(args[0], field)
+    elif sys.version_info >= (3, 10) and isinstance(field.annotation, types.UnionType):
+        args = field.annotation.__args__
+        if len(args) == 2:
+            for typ in args:
+                if typ is type(None):
+                    continue
+                return _py_type_to_arrow_type(typ, field)
    return _pydantic_type_to_arrow_type(field.annotation, field)


 def is_nullable(field: FieldInfo) -> bool:
    """Check if a Pydantic FieldInfo is nullable."""
-    if _unwrap_optional_annotation(field.annotation) is not None:
-        return True
    if isinstance(field.annotation, (_GenericAlias, GenericAlias)):
        origin = field.annotation.__origin__
        args = field.annotation.__args__
        if origin == Union:
-            if any(typ is type(None) for typ in args):
+            if len(args) == 2 and args[1] is type(None):
                return True
    elif sys.version_info >= (3, 10) and isinstance(field.annotation, types.UnionType):
        args = field.annotation.__args__
        for typ in args:
            if typ is type(None):
                return True
-    elif inspect.isclass(field.annotation):
-        try:
-            if issubclass(field.annotation, FixedSizeListMixin):
-                return field.annotation.nullable()
-        except TypeError:
-            return False
+    elif inspect.isclass(field.annotation) and issubclass(
+        field.annotation, FixedSizeListMixin
+    ):
+        return field.annotation.nullable()
    return False


--- a/python/python/lancedb/remote/db.py
+++ b/python/python/lancedb/remote/db.py
@@ -384,7 +384,6 @@ class RemoteDBConnection(DBConnection):
        on_bad_vectors: str = "error",
        fill_value: float = 0.0,
        mode: Optional[str] = None,
-        exist_ok: bool = False,
        embedding_functions: Optional[List[EmbeddingFunctionConfig]] = None,
        *,
        namespace: Optional[List[str]] = None,
@@ -413,12 +412,6 @@ class RemoteDBConnection(DBConnection):
            - pyarrow.Schema

            - [LanceModel][lancedb.pydantic.LanceModel]
-        mode: str, default "create"
-            The mode to use when creating the table.
-            Can be either "create", "overwrite", or "exist_ok".
-        exist_ok: bool, default False
-            If exist_ok is True, and mode is None or "create", mode will be changed
-            to "exist_ok".
        on_bad_vectors: str, default "error"
            What to do if any of the vectors are not the same size or contains NaNs.
            One of "error", "drop", "fill".
@@ -490,11 +483,6 @@ class RemoteDBConnection(DBConnection):
        LanceTable(table4)

        """
-        if exist_ok:
-            if mode == "create":
-                mode = "exist_ok"
-            elif not mode:
-                mode = "exist_ok"
        if namespace is None:
            namespace = []
        validate_table_name(name)
--- a/python/python/lancedb/remote/table.py
+++ b/python/python/lancedb/remote/table.py
@@ -18,17 +18,7 @@ from lancedb._lancedb import (
    UpdateResult,
 )
 from lancedb.embeddings.base import EmbeddingFunctionConfig
-from lancedb.index import (
-    FTS,
-    BTree,
-    Bitmap,
-    HnswSq,
-    IvfFlat,
-    IvfPq,
-    IvfRq,
-    IvfSq,
-    LabelList,
-)
+from lancedb.index import FTS, BTree, Bitmap, HnswSq, IvfFlat, IvfPq, IvfSq, LabelList
 from lancedb.remote.db import LOOP
 import pyarrow as pa

@@ -275,12 +265,6 @@ class RemoteTable(Table):
                num_sub_vectors=num_sub_vectors,
                num_bits=num_bits,
            )
-        elif index_type == "IVF_RQ":
-            config = IvfRq(
-                distance_type=metric,
-                num_partitions=num_partitions,
-                num_bits=num_bits,
-            )
        elif index_type == "IVF_SQ":
            config = IvfSq(distance_type=metric, num_partitions=num_partitions)
        elif index_type == "IVF_HNSW_PQ":
@@ -295,8 +279,7 @@ class RemoteTable(Table):
        else:
            raise ValueError(
                f"Unknown vector index type: {index_type}. Valid options are"
-                " 'IVF_FLAT', 'IVF_PQ', 'IVF_RQ', 'IVF_SQ',"
-                " 'IVF_HNSW_PQ', 'IVF_HNSW_SQ'"
+                " 'IVF_FLAT', 'IVF_SQ', 'IVF_PQ', 'IVF_HNSW_PQ', 'IVF_HNSW_SQ'"
            )

        LOOP.run(
@@ -655,14 +638,6 @@ class RemoteTable(Table):
    def stats(self):
        return LOOP.run(self._table.stats())

-    @property
-    def uri(self) -> str:
-        """The table URI (storage location).
-
-        For remote tables, this fetches the location from the server via describe.
-        """
-        return LOOP.run(self._table.uri())
-
    def take_offsets(self, offsets: list[int]) -> LanceTakeQueryBuilder:
        return LanceTakeQueryBuilder(self._table.take_offsets(offsets))

--- a/python/python/lancedb/table.py
+++ b/python/python/lancedb/table.py
@@ -2218,10 +2218,6 @@ class LanceTable(Table):
    def stats(self) -> TableStatistics:
        return LOOP.run(self._table.stats())

-    @property
-    def uri(self) -> str:
-        return LOOP.run(self._table.uri())
-
    def create_scalar_index(
        self,
        column: str,
@@ -3610,20 +3606,6 @@ class AsyncTable:
        """
        return await self._inner.stats()

-    async def uri(self) -> str:
-        """
-        Get the table URI (storage location).
-
-        For remote tables, this fetches the location from the server via describe.
-        For local tables, this returns the dataset URI.
-
-        Returns
-        -------
-        str
-            The full storage location of the table (e.g., S3/GCS path).
-        """
-        return await self._inner.uri()
-
    async def add(
        self,
        data: DATA,
--- a/python/python/tests/conftest.py
+++ b/python/python/tests/conftest.py
@@ -2,27 +2,12 @@
 # SPDX-FileCopyrightText: Copyright The LanceDB Authors

 from datetime import timedelta
-
 from lancedb.db import AsyncConnection, DBConnection
 import lancedb
 import pytest
 import pytest_asyncio


-def pandas_string_type():
-    """Return the PyArrow string type that pandas uses for string columns.
-
-    pandas 3.0+ uses large_string for string columns, pandas 2.x uses string.
-    """
-    import pandas as pd
-    import pyarrow as pa
-
-    version = tuple(int(x) for x in pd.__version__.split(".")[:2])
-    if version >= (3, 0):
-        return pa.large_utf8()
-    return pa.utf8()
-
-
 # Use an in-memory database for most tests.
@pytest.fixture
 def mem_db() -> DBConnection:
--- a/python/python/tests/test_db.py
+++ b/python/python/tests/test_db.py
@@ -268,8 +268,6 @@ async def test_create_table_from_iterator_async(mem_db_async: lancedb.AsyncConne


 def test_create_exist_ok(tmp_db: lancedb.DBConnection):
-    from conftest import pandas_string_type
-
    data = pd.DataFrame(
        {
            "vector": [[3.1, 4.1], [5.9, 26.5]],
@@ -288,11 +286,10 @@ def test_create_exist_ok(tmp_db: lancedb.DBConnection):
    assert tbl.schema == tbl2.schema
    assert len(tbl) == len(tbl2)

-    # pandas 3.0+ uses large_string, pandas 2.x uses string
    schema = pa.schema(
        [
            pa.field("vector", pa.list_(pa.float32(), list_size=2)),
-            pa.field("item", pandas_string_type()),
+            pa.field("item", pa.utf8()),
            pa.field("price", pa.float64()),
        ]
    )
@@ -302,7 +299,7 @@ def test_create_exist_ok(tmp_db: lancedb.DBConnection):
    bad_schema = pa.schema(
        [
            pa.field("vector", pa.list_(pa.float32(), list_size=2)),
-            pa.field("item", pandas_string_type()),
+            pa.field("item", pa.utf8()),
            pa.field("price", pa.float64()),
            pa.field("extra", pa.float32()),
        ]
@@ -368,8 +365,6 @@ async def test_create_mode_async(tmp_db_async: lancedb.AsyncConnection):

@pytest.mark.asyncio
 async def test_create_exist_ok_async(tmp_db_async: lancedb.AsyncConnection):
-    from conftest import pandas_string_type
-
    data = pd.DataFrame(
        {
            "vector": [[3.1, 4.1], [5.9, 26.5]],
@@ -387,11 +382,10 @@ async def test_create_exist_ok_async(tmp_db_async: lancedb.AsyncConnection):
    assert tbl.name == tbl2.name
    assert await tbl.schema() == await tbl2.schema()

-    # pandas 3.0+ uses large_string, pandas 2.x uses string
    schema = pa.schema(
        [
            pa.field("vector", pa.list_(pa.float32(), list_size=2)),
-            pa.field("item", pandas_string_type()),
+            pa.field("item", pa.utf8()),
            pa.field("price", pa.float64()),
        ]
    )
@@ -601,8 +595,6 @@ def test_open_table_sync(tmp_db: lancedb.DBConnection):

@pytest.mark.asyncio
 async def test_open_table(tmp_path):
-    from conftest import pandas_string_type
-
    db = await lancedb.connect_async(tmp_path)
    data = pd.DataFrame(
        {
@@ -622,11 +614,10 @@ async def test_open_table(tmp_path):
        )
        is not None
    )
-    # pandas 3.0+ uses large_string, pandas 2.x uses string
    assert await tbl.schema() == pa.schema(
        {
            "vector": pa.list_(pa.float32(), list_size=2),
-            "item": pandas_string_type(),
+            "item": pa.utf8(),
            "price": pa.float64(),
        }
    )
--- a/python/python/tests/test_embeddings_slow.py
+++ b/python/python/tests/test_embeddings_slow.py
@@ -517,36 +517,19 @@ def test_ollama_embedding(tmp_path):
@pytest.mark.skipif(
    os.environ.get("VOYAGE_API_KEY") is None, reason="VOYAGE_API_KEY not set"
 )
-@pytest.mark.parametrize(
-    "model_name,expected_dims",
-    [
-        ("voyage-3", 1024),
-        ("voyage-4", 1024),
-        ("voyage-4-lite", 1024),
-        ("voyage-4-large", 1024),
-    ],
-)
-def test_voyageai_embedding_function(model_name, expected_dims, tmp_path):
-    """Integration test for VoyageAI text embedding models with real API calls."""
-    voyageai = get_registry().get("voyageai").create(name=model_name, max_retries=0)
+def test_voyageai_embedding_function():
+    voyageai = get_registry().get("voyageai").create(name="voyage-3", max_retries=0)

    class TextModel(LanceModel):
        text: str = voyageai.SourceField()
        vector: Vector(voyageai.ndims()) = voyageai.VectorField()

    df = pd.DataFrame({"text": ["hello world", "goodbye world"]})
-    db = lancedb.connect(tmp_path)
+    db = lancedb.connect("~/lancedb")
    tbl = db.create_table("test", schema=TextModel, mode="overwrite")

    tbl.add(df)
    assert len(tbl.to_pandas()["vector"][0]) == voyageai.ndims()
-    assert voyageai.ndims() == expected_dims, (
-        f"{model_name} should have {expected_dims} dimensions"
-    )
-
-    # Test search functionality
-    result = tbl.search("hello").limit(1).to_pandas()
-    assert result["text"][0] == "hello world"


@pytest.mark.slow
@@ -630,133 +613,6 @@ def test_voyageai_multimodal_embedding_text_function():
    assert len(tbl.to_pandas()["vector"][0]) == voyageai.ndims()


-@pytest.mark.slow
-@pytest.mark.skipif(
-    os.environ.get("VOYAGE_API_KEY") is None, reason="VOYAGE_API_KEY not set"
-)
-def test_voyageai_multimodal_35_embedding_function():
-    """Test voyage-multimodal-3.5 model with text input."""
-    voyageai = (
-        get_registry()
-        .get("voyageai")
-        .create(name="voyage-multimodal-3.5", max_retries=0)
-    )
-
-    class TextModel(LanceModel):
-        text: str = voyageai.SourceField()
-        vector: Vector(voyageai.ndims()) = voyageai.VectorField()
-
-    df = pd.DataFrame({"text": ["hello world", "goodbye world"]})
-    db = lancedb.connect("~/lancedb")
-    tbl = db.create_table("test_multimodal_35", schema=TextModel, mode="overwrite")
-
-    tbl.add(df)
-    assert len(tbl.to_pandas()["vector"][0]) == voyageai.ndims()
-    assert voyageai.ndims() == 1024
-
-
-@pytest.mark.slow
-@pytest.mark.skipif(
-    os.environ.get("VOYAGE_API_KEY") is None, reason="VOYAGE_API_KEY not set"
-)
-def test_voyageai_multimodal_35_flexible_dimensions():
-    """Test voyage-multimodal-3.5 model with custom output dimension."""
-    voyageai = (
-        get_registry()
-        .get("voyageai")
-        .create(name="voyage-multimodal-3.5", output_dimension=512, max_retries=0)
-    )
-
-    class TextModel(LanceModel):
-        text: str = voyageai.SourceField()
-        vector: Vector(voyageai.ndims()) = voyageai.VectorField()
-
-    assert voyageai.ndims() == 512
-
-    df = pd.DataFrame({"text": ["hello world", "goodbye world"]})
-    db = lancedb.connect("~/lancedb")
-    tbl = db.create_table("test_multimodal_35_dim", schema=TextModel, mode="overwrite")
-
-    tbl.add(df)
-    assert len(tbl.to_pandas()["vector"][0]) == 512
-
-
-@pytest.mark.slow
-@pytest.mark.skipif(
-    os.environ.get("VOYAGE_API_KEY") is None, reason="VOYAGE_API_KEY not set"
-)
-def test_voyageai_multimodal_35_image_embedding():
-    """Test voyage-multimodal-3.5 model with image input."""
-    voyageai = (
-        get_registry()
-        .get("voyageai")
-        .create(name="voyage-multimodal-3.5", max_retries=0)
-    )
-
-    class Images(LanceModel):
-        label: str
-        image_uri: str = voyageai.SourceField()
-        vector: Vector(voyageai.ndims()) = voyageai.VectorField()
-
-    db = lancedb.connect("~/lancedb")
-    table = db.create_table(
-        "test_multimodal_35_images", schema=Images, mode="overwrite"
-    )
-    labels = ["cat", "dog"]
-    uris = [
-        "http://farm1.staticflickr.com/53/167798175_7c7845bbbd_z.jpg",
-        "http://farm9.staticflickr.com/8387/8602747737_2e5c2a45d4_z.jpg",
-    ]
-    table.add(pd.DataFrame({"label": labels, "image_uri": uris}))
-    assert len(table.to_pandas()["vector"][0]) == voyageai.ndims()
-    assert voyageai.ndims() == 1024
-
-
-@pytest.mark.slow
-@pytest.mark.skipif(
-    os.environ.get("VOYAGE_API_KEY") is None, reason="VOYAGE_API_KEY not set"
-)
-@pytest.mark.parametrize("dimension", [256, 512, 1024, 2048])
-def test_voyageai_multimodal_35_all_dimensions(dimension):
-    """Test voyage-multimodal-3.5 model with all valid output dimensions."""
-    voyageai = (
-        get_registry()
-        .get("voyageai")
-        .create(name="voyage-multimodal-3.5", output_dimension=dimension, max_retries=0)
-    )
-
-    assert voyageai.ndims() == dimension
-
-    class TextModel(LanceModel):
-        text: str = voyageai.SourceField()
-        vector: Vector(voyageai.ndims()) = voyageai.VectorField()
-
-    df = pd.DataFrame({"text": ["hello world"]})
-    db = lancedb.connect("~/lancedb")
-    tbl = db.create_table(
-        f"test_multimodal_35_dim_{dimension}", schema=TextModel, mode="overwrite"
-    )
-
-    tbl.add(df)
-    assert len(tbl.to_pandas()["vector"][0]) == dimension
-
-
-@pytest.mark.slow
-@pytest.mark.skipif(
-    os.environ.get("VOYAGE_API_KEY") is None, reason="VOYAGE_API_KEY not set"
-)
-def test_voyageai_multimodal_35_invalid_dimension():
-    """Test voyage-multimodal-3.5 model raises error for invalid output dimension."""
-    with pytest.raises(ValueError, match="Invalid output_dimension"):
-        voyageai = (
-            get_registry()
-            .get("voyageai")
-            .create(name="voyage-multimodal-3.5", output_dimension=999, max_retries=0)
-        )
-        # ndims() is where the validation happens
-        voyageai.ndims()
-
-
@pytest.mark.slow
@pytest.mark.skipif(
    importlib.util.find_spec("colpali_engine") is None,
--- a/python/python/tests/test_namespace_integration.py
+++ b/python/python/tests/test_namespace_integration.py
@@ -26,8 +26,6 @@ import pytest
 from lance_namespace import (
    CreateEmptyTableRequest,
    CreateEmptyTableResponse,
-    DeclareTableRequest,
-    DeclareTableResponse,
    DescribeTableRequest,
    DescribeTableResponse,
    LanceNamespace,
@@ -162,19 +160,6 @@ class TrackingNamespace(LanceNamespace):

        return modified

-    def declare_table(self, request: DeclareTableRequest) -> DeclareTableResponse:
-        """Track declare_table calls and inject rotating credentials."""
-        with self.lock:
-            self.create_call_count += 1
-            count = self.create_call_count
-
-        response = self.inner.declare_table(request)
-        response.storage_options = self._modify_storage_options(
-            response.storage_options, count
-        )
-
-        return response
-
    def create_empty_table(
        self, request: CreateEmptyTableRequest
    ) -> CreateEmptyTableResponse:
--- a/python/python/tests/test_permutation.py
+++ b/python/python/tests/test_permutation.py
@@ -438,15 +438,11 @@ def test_filter_with_splits(mem_db):
    row_count = permutation_tbl.count_rows()
    assert row_count == 67

-    # Verify the permutation table only contains row_id and split_id
-    assert set(permutation_tbl.schema.names) == {"row_id", "split_id"}
-
-    row_ids = permutation_tbl.search(None).to_arrow().to_pydict()["row_id"]
-    data = tbl.take_row_ids(row_ids).to_arrow().to_pydict()
+    data = permutation_tbl.search(None).to_arrow().to_pydict()
    categories = data["category"]

    # All categories should be A or B
-    assert all(cat in ("A", "B") for cat in categories)
+    assert all(cat in ["A", "B"] for cat in categories)


 def test_filter_with_shuffle(mem_db):
--- a/python/python/tests/test_pydantic.py
+++ b/python/python/tests/test_pydantic.py
@@ -2,6 +2,7 @@
 # SPDX-FileCopyrightText: Copyright The LanceDB Authors

 import json
+import sys
 from datetime import date, datetime
 from typing import List, Optional, Tuple

@@ -19,6 +20,10 @@ from pydantic import BaseModel
 from pydantic import Field


+@pytest.mark.skipif(
+    sys.version_info < (3, 9),
+    reason="using native type alias requires python3.9 or higher",
+)
 def test_pydantic_to_arrow():
    class StructModel(pydantic.BaseModel):
        a: str
@@ -78,6 +83,10 @@ def test_pydantic_to_arrow():
    assert schema == expect_schema


+@pytest.mark.skipif(
+    sys.version_info < (3, 10),
+    reason="using | type syntax requires python3.10 or higher",
+)
 def test_optional_types_py310():
    class TestModel(pydantic.BaseModel):
        a: str | None
@@ -96,233 +105,10 @@ def test_optional_types_py310():
    assert schema == expect_schema


-def test_optional_structs():
-    class SplitInfo(pydantic.BaseModel):
-        start_frame: int
-        end_frame: int
-
-    class TestModel(pydantic.BaseModel):
-        id: str
-        split: SplitInfo | None = None
-
-    schema = pydantic_to_schema(TestModel)
-
-    expect_schema = pa.schema(
-        [
-            pa.field("id", pa.utf8(), False),
-            pa.field(
-                "split",
-                pa.struct(
-                    [
-                        pa.field("start_frame", pa.int64(), False),
-                        pa.field("end_frame", pa.int64(), False),
-                    ]
-                ),
-                True,
-            ),
-        ]
-    )
-    assert schema == expect_schema
-
-
-def test_optional_struct_list_py310():
-    class SplitInfo(pydantic.BaseModel):
-        start_frame: int
-        end_frame: int
-
-    class TestModel(pydantic.BaseModel):
-        id: str
-        splits: list[SplitInfo] | None = None
-
-    schema = pydantic_to_schema(TestModel)
-
-    expect_schema = pa.schema(
-        [
-            pa.field("id", pa.utf8(), False),
-            pa.field(
-                "splits",
-                pa.list_(
-                    pa.struct(
-                        [
-                            pa.field("start_frame", pa.int64(), False),
-                            pa.field("end_frame", pa.int64(), False),
-                        ]
-                    )
-                ),
-                True,
-            ),
-        ]
-    )
-    assert schema == expect_schema
-
-
-def test_nested_struct_list():
-    class SplitInfo(pydantic.BaseModel):
-        start_frame: int
-        end_frame: int
-
-    class TestModel(pydantic.BaseModel):
-        id: str
-        splits: list[SplitInfo]
-
-    schema = pydantic_to_schema(TestModel)
-
-    expect_schema = pa.schema(
-        [
-            pa.field("id", pa.utf8(), False),
-            pa.field(
-                "splits",
-                pa.list_(
-                    pa.struct(
-                        [
-                            pa.field("start_frame", pa.int64(), False),
-                            pa.field("end_frame", pa.int64(), False),
-                        ]
-                    )
-                ),
-                False,
-            ),
-        ]
-    )
-    assert schema == expect_schema
-
-
-def test_nested_struct_list_optional():
-    class SplitInfo(pydantic.BaseModel):
-        start_frame: int
-        end_frame: int
-
-    class TestModel(pydantic.BaseModel):
-        id: str
-        splits: Optional[list[SplitInfo]] = None
-
-    schema = pydantic_to_schema(TestModel)
-
-    expect_schema = pa.schema(
-        [
-            pa.field("id", pa.utf8(), False),
-            pa.field(
-                "splits",
-                pa.list_(
-                    pa.struct(
-                        [
-                            pa.field("start_frame", pa.int64(), False),
-                            pa.field("end_frame", pa.int64(), False),
-                        ]
-                    )
-                ),
-                True,
-            ),
-        ]
-    )
-    assert schema == expect_schema
-
-
-def test_nested_struct_list_optional_items():
-    class SplitInfo(pydantic.BaseModel):
-        start_frame: int
-        end_frame: int
-
-    class TestModel(pydantic.BaseModel):
-        id: str
-        splits: list[Optional[SplitInfo]]
-
-    schema = pydantic_to_schema(TestModel)
-
-    expect_schema = pa.schema(
-        [
-            pa.field("id", pa.utf8(), False),
-            pa.field(
-                "splits",
-                pa.list_(
-                    pa.field(
-                        "item",
-                        pa.struct(
-                            [
-                                pa.field("start_frame", pa.int64(), False),
-                                pa.field("end_frame", pa.int64(), False),
-                            ]
-                        ),
-                        True,
-                    )
-                ),
-                False,
-            ),
-        ]
-    )
-    assert schema == expect_schema
-
-
-def test_nested_struct_list_optional_container_and_items():
-    class SplitInfo(pydantic.BaseModel):
-        start_frame: int
-        end_frame: int
-
-    class TestModel(pydantic.BaseModel):
-        id: str
-        splits: Optional[list[Optional[SplitInfo]]] = None
-
-    schema = pydantic_to_schema(TestModel)
-
-    expect_schema = pa.schema(
-        [
-            pa.field("id", pa.utf8(), False),
-            pa.field(
-                "splits",
-                pa.list_(
-                    pa.field(
-                        "item",
-                        pa.struct(
-                            [
-                                pa.field("start_frame", pa.int64(), False),
-                                pa.field("end_frame", pa.int64(), False),
-                            ]
-                        ),
-                        True,
-                    )
-                ),
-                True,
-            ),
-        ]
-    )
-    assert schema == expect_schema
-
-
-def test_nested_struct_list_optional_items_pep604():
-    class SplitInfo(pydantic.BaseModel):
-        start_frame: int
-        end_frame: int
-
-    class TestModel(pydantic.BaseModel):
-        id: str
-        splits: list[SplitInfo | None]
-
-    schema = pydantic_to_schema(TestModel)
-
-    expect_schema = pa.schema(
-        [
-            pa.field("id", pa.utf8(), False),
-            pa.field(
-                "splits",
-                pa.list_(
-                    pa.field(
-                        "item",
-                        pa.struct(
-                            [
-                                pa.field("start_frame", pa.int64(), False),
-                                pa.field("end_frame", pa.int64(), False),
-                            ]
-                        ),
-                        True,
-                    )
-                ),
-                False,
-            ),
-        ]
-    )
-    assert schema == expect_schema
-
-
+@pytest.mark.skipif(
+    sys.version_info > (3, 8),
+    reason="using native type alias requires python3.9 or higher",
+)
 def test_pydantic_to_arrow_py38():
    class StructModel(pydantic.BaseModel):
        a: str
--- a/python/python/tests/test_remote_db.py
+++ b/python/python/tests/test_remote_db.py
@@ -8,7 +8,7 @@ import http.server
 import json
 import threading
 import time
-from unittest.mock import MagicMock, patch
+from unittest.mock import MagicMock
 import uuid
 from packaging.version import Version

@@ -168,42 +168,6 @@ def test_table_len_sync():
        assert len(table) == 1


-def test_create_table_exist_ok():
-    def handler(request):
-        if request.path == "/v1/table/test/create/?mode=exist_ok":
-            request.send_response(200)
-            request.send_header("Content-Type", "application/json")
-            request.end_headers()
-            request.wfile.write(b"{}")
-        else:
-            request.send_response(404)
-            request.end_headers()
-
-    with mock_lancedb_connection(handler) as db:
-        table = db.create_table("test", [{"id": 1}], exist_ok=True)
-        assert table is not None
-
-    with mock_lancedb_connection(handler) as db:
-        table = db.create_table("test", [{"id": 1}], mode="create", exist_ok=True)
-        assert table is not None
-
-
-def test_create_table_exist_ok_with_mode_overwrite():
-    def handler(request):
-        if request.path == "/v1/table/test/create/?mode=overwrite":
-            request.send_response(200)
-            request.send_header("Content-Type", "application/json")
-            request.end_headers()
-            request.wfile.write(b"{}")
-        else:
-            request.send_response(404)
-            request.end_headers()
-
-    with mock_lancedb_connection(handler) as db:
-        table = db.create_table("test", [{"id": 1}], mode="overwrite", exist_ok=True)
-        assert table is not None
-
-
@pytest.mark.asyncio
 async def test_http_error():
    request_id_holder = {"request_id": None}
@@ -1203,22 +1167,3 @@ async def test_header_provider_overrides_static_headers():
        extra_headers={"X-API-Key": "static-key", "X-Extra": "extra-value"},
    ) as db:
        await db.table_names()
-
-
-@pytest.mark.parametrize("exception", [KeyboardInterrupt, SystemExit, GeneratorExit])
-def test_background_loop_cancellation(exception):
-    """Test that BackgroundEventLoop.run() cancels the future on interrupt."""
-    from lancedb.background_loop import BackgroundEventLoop
-
-    mock_future = MagicMock()
-    mock_future.result.side_effect = exception()
-
-    with (
-        patch.object(BackgroundEventLoop, "__init__", return_value=None),
-        patch("asyncio.run_coroutine_threadsafe", return_value=mock_future),
-    ):
-        loop = BackgroundEventLoop()
-        loop.loop = MagicMock()
-        with pytest.raises(exception):
-            loop.run(None)
-        mock_future.cancel.assert_called_once()
--- a/python/python/tests/test_s3_bucket_dots.py
+++ b/python/python/tests/test_s3_bucket_dots.py
@@ -1,68 +0,0 @@
-# SPDX-License-Identifier: Apache-2.0
-# SPDX-FileCopyrightText: Copyright The LanceDB Authors
-
-"""
-Tests for S3 bucket names containing dots.
-
-Related issue: https://github.com/lancedb/lancedb/issues/1898
-
-These tests validate the early error checking for S3 bucket names with dots.
-No actual S3 connection is made - validation happens before connection.
-"""
-
-import pytest
-import lancedb
-
-# Test URIs
-BUCKET_WITH_DOTS = "s3://my.bucket.name/path"
-BUCKET_WITH_DOTS_AND_REGION = ("s3://my.bucket.name", {"region": "us-east-1"})
-BUCKET_WITH_DOTS_AND_AWS_REGION = ("s3://my.bucket.name", {"aws_region": "us-east-1"})
-BUCKET_WITHOUT_DOTS = "s3://my-bucket/path"
-
-
-class TestS3BucketWithDotsSync:
-    """Tests for connect()."""
-
-    def test_bucket_with_dots_requires_region(self):
-        with pytest.raises(ValueError, match="contains dots"):
-            lancedb.connect(BUCKET_WITH_DOTS)
-
-    def test_bucket_with_dots_and_region_passes(self):
-        uri, opts = BUCKET_WITH_DOTS_AND_REGION
-        db = lancedb.connect(uri, storage_options=opts)
-        assert db is not None
-
-    def test_bucket_with_dots_and_aws_region_passes(self):
-        uri, opts = BUCKET_WITH_DOTS_AND_AWS_REGION
-        db = lancedb.connect(uri, storage_options=opts)
-        assert db is not None
-
-    def test_bucket_without_dots_passes(self):
-        db = lancedb.connect(BUCKET_WITHOUT_DOTS)
-        assert db is not None
-
-
-class TestS3BucketWithDotsAsync:
-    """Tests for connect_async()."""
-
-    @pytest.mark.asyncio
-    async def test_bucket_with_dots_requires_region(self):
-        with pytest.raises(ValueError, match="contains dots"):
-            await lancedb.connect_async(BUCKET_WITH_DOTS)
-
-    @pytest.mark.asyncio
-    async def test_bucket_with_dots_and_region_passes(self):
-        uri, opts = BUCKET_WITH_DOTS_AND_REGION
-        db = await lancedb.connect_async(uri, storage_options=opts)
-        assert db is not None
-
-    @pytest.mark.asyncio
-    async def test_bucket_with_dots_and_aws_region_passes(self):
-        uri, opts = BUCKET_WITH_DOTS_AND_AWS_REGION
-        db = await lancedb.connect_async(uri, storage_options=opts)
-        assert db is not None
-
-    @pytest.mark.asyncio
-    async def test_bucket_without_dots_passes(self):
-        db = await lancedb.connect_async(BUCKET_WITHOUT_DOTS)
-        assert db is not None
--- a/python/python/tests/test_table.py
+++ b/python/python/tests/test_table.py
@@ -1967,9 +1967,3 @@ def test_add_table_with_empty_embeddings(tmp_path):
        on_bad_vectors="drop",
    )
    assert table.count_rows() == 1
-
-
-def test_table_uri(tmp_path):
-    db = lancedb.connect(tmp_path)
-    table = db.create_table("my_table", data=[{"x": 0}])
-    assert table.uri == str(tmp_path / "my_table.lance")
--- a/python/python/tests/test_util.py
+++ b/python/python/tests/test_util.py
@@ -528,19 +528,12 @@ def test_sanitize_data(
        else:
            expected_schema = schema
    else:
-        from conftest import pandas_string_type
-
-        # polars uses large_string, pandas 3.0+ uses large_string, others use string
-        if isinstance(data, pl.DataFrame):
-            text_type = pa.large_utf8()
-        elif isinstance(data, pd.DataFrame):
-            text_type = pandas_string_type()
-        else:
-            text_type = pa.string()
        expected_schema = pa.schema(
            {
                "id": pa.int64(),
-                "text": text_type,
+                "text": pa.large_utf8()
+                if isinstance(data, pl.DataFrame)
+                else pa.string(),
                "vector": pa.list_(pa.float32(), 10),
            }
        )
--- a/python/python/tests/test_voyageai_embeddings.py
+++ b/python/python/tests/test_voyageai_embeddings.py
@@ -1,108 +0,0 @@
-# SPDX-License-Identifier: Apache-2.0
-# SPDX-FileCopyrightText: Copyright The LanceDB Authors
-
-"""Unit tests for VoyageAI embedding function.
-
-These tests verify model registration and configuration without requiring API calls.
-"""
-
-import pytest
-from unittest.mock import MagicMock, patch
-
-from lancedb.embeddings import get_registry
-
-
-@pytest.fixture(autouse=True)
-def reset_voyageai_client():
-    """Reset VoyageAI client before and after each test to avoid state pollution."""
-    from lancedb.embeddings.voyageai import VoyageAIEmbeddingFunction
-
-    VoyageAIEmbeddingFunction.client = None
-    yield
-    VoyageAIEmbeddingFunction.client = None
-
-
-class TestVoyageAIModelRegistration:
-    """Tests for VoyageAI model registration and configuration."""
-
-    @pytest.fixture
-    def mock_voyageai_client(self):
-        """Mock VoyageAI client to avoid API calls."""
-        with patch.dict("os.environ", {"VOYAGE_API_KEY": "test-key"}):
-            with patch("lancedb.embeddings.voyageai.attempt_import_or_raise") as mock:
-                mock_client = MagicMock()
-                mock_voyageai = MagicMock()
-                mock_voyageai.Client.return_value = mock_client
-                mock.return_value = mock_voyageai
-                yield mock_client
-
-    def test_voyageai_registered(self):
-        """Test that VoyageAI is registered in the embedding function registry."""
-        registry = get_registry()
-        assert registry.get("voyageai") is not None
-
-    @pytest.mark.parametrize(
-        "model_name,expected_dims",
-        [
-            # Voyage-4 series (all 1024 dims)
-            ("voyage-4", 1024),
-            ("voyage-4-lite", 1024),
-            ("voyage-4-large", 1024),
-            # Voyage-3 series
-            ("voyage-3", 1024),
-            ("voyage-3-lite", 512),
-            # Domain-specific models
-            ("voyage-finance-2", 1024),
-            ("voyage-multilingual-2", 1024),
-            ("voyage-law-2", 1024),
-            ("voyage-code-2", 1536),
-            # Multimodal
-            ("voyage-multimodal-3", 1024),
-        ],
-    )
-    def test_model_dimensions(self, model_name, expected_dims, mock_voyageai_client):
-        """Test that each model returns the correct dimensions."""
-        registry = get_registry()
-        func = registry.get("voyageai").create(name=model_name)
-        assert func.ndims() == expected_dims, (
-            f"Model {model_name} should have {expected_dims} dimensions"
-        )
-
-    def test_unsupported_model_raises_error(self, mock_voyageai_client):
-        """Test that unsupported models raise ValueError."""
-        registry = get_registry()
-        func = registry.get("voyageai").create(name="unsupported-model")
-        with pytest.raises(ValueError, match="not supported"):
-            func.ndims()
-
-    @pytest.mark.parametrize(
-        "model_name",
-        [
-            "voyage-4",
-            "voyage-4-lite",
-            "voyage-4-large",
-        ],
-    )
-    def test_voyage4_models_are_text_models(self, model_name, mock_voyageai_client):
-        """Test that voyage-4 models are classified as text models (not multimodal)."""
-        registry = get_registry()
-        func = registry.get("voyageai").create(name=model_name)
-        assert not func._is_multimodal_model(model_name), (
-            f"{model_name} should be a text model, not multimodal"
-        )
-
-    def test_voyage4_models_in_text_embedding_list(self, mock_voyageai_client):
-        """Test that voyage-4 models are in the text_embedding_models list."""
-        registry = get_registry()
-        func = registry.get("voyageai").create(name="voyage-4")
-        assert "voyage-4" in func.text_embedding_models
-        assert "voyage-4-lite" in func.text_embedding_models
-        assert "voyage-4-large" in func.text_embedding_models
-
-    def test_voyage4_models_not_in_multimodal_list(self, mock_voyageai_client):
-        """Test that voyage-4 models are NOT in the multimodal_embedding_models list."""
-        registry = get_registry()
-        func = registry.get("voyageai").create(name="voyage-4")
-        assert "voyage-4" not in func.multimodal_embedding_models
-        assert "voyage-4-lite" not in func.multimodal_embedding_models
-        assert "voyage-4-large" not in func.multimodal_embedding_models
--- a/python/src/connection.rs
+++ b/python/src/connection.rs
@@ -304,7 +304,6 @@ impl Connection {
                },
                page_token,
                limit: limit.map(|l| l as i32),
-                ..Default::default()
            };
            let response = inner.list_namespaces(request).await.infer_error()?;
            Python::with_gil(|py| -> PyResult<Py<PyDict>> {
@@ -327,12 +326,11 @@ impl Connection {
        let py = self_.py();
        future_into_py(py, async move {
            use lance_namespace::models::CreateNamespaceRequest;
-            // Mode is now a string field
-            let mode_str = mode.and_then(|m| match m.to_lowercase().as_str() {
-                "create" => Some("Create".to_string()),
-                "exist_ok" => Some("ExistOk".to_string()),
-                "overwrite" => Some("Overwrite".to_string()),
-                _ => None,
+            let mode_value = mode.map(|m| match m.to_lowercase().as_str() {
+                "create" => "Create".to_string(),
+                "exist_ok" => "ExistOk".to_string(),
+                "overwrite" => "Overwrite".to_string(),
+                _ => m,
            });
            let request = CreateNamespaceRequest {
                id: if namespace.is_empty() {
@@ -340,9 +338,8 @@ impl Connection {
                } else {
                    Some(namespace)
                },
-                mode: mode_str,
+                mode: mode_value,
                properties,
-                ..Default::default()
            };
            let response = inner.create_namespace(request).await.infer_error()?;
            Python::with_gil(|py| -> PyResult<Py<PyDict>> {
@@ -364,16 +361,15 @@ impl Connection {
        let py = self_.py();
        future_into_py(py, async move {
            use lance_namespace::models::DropNamespaceRequest;
-            // Mode and Behavior are now string fields
-            let mode_str = mode.and_then(|m| match m.to_uppercase().as_str() {
-                "SKIP" => Some("Skip".to_string()),
-                "FAIL" => Some("Fail".to_string()),
-                _ => None,
+            let mode_value = mode.map(|m| match m.to_uppercase().as_str() {
+                "SKIP" => "Skip".to_string(),
+                "FAIL" => "Fail".to_string(),
+                _ => m,
            });
-            let behavior_str = behavior.and_then(|b| match b.to_uppercase().as_str() {
-                "RESTRICT" => Some("Restrict".to_string()),
-                "CASCADE" => Some("Cascade".to_string()),
-                _ => None,
+            let behavior_value = behavior.map(|b| match b.to_uppercase().as_str() {
+                "RESTRICT" => "Restrict".to_string(),
+                "CASCADE" => "Cascade".to_string(),
+                _ => b,
            });
            let request = DropNamespaceRequest {
                id: if namespace.is_empty() {
@@ -381,9 +377,8 @@ impl Connection {
                } else {
                    Some(namespace)
                },
-                mode: mode_str,
-                behavior: behavior_str,
-                ..Default::default()
+                mode: mode_value,
+                behavior: behavior_value,
            };
            let response = inner.drop_namespace(request).await.infer_error()?;
            Python::with_gil(|py| -> PyResult<Py<PyDict>> {
@@ -410,7 +405,6 @@ impl Connection {
                } else {
                    Some(namespace)
                },
-                ..Default::default()
            };
            let response = inner.describe_namespace(request).await.infer_error()?;
            Python::with_gil(|py| -> PyResult<Py<PyDict>> {
@@ -440,7 +434,6 @@ impl Connection {
                },
                page_token,
                limit: limit.map(|l| l as i32),
-                ..Default::default()
            };
            let response = inner.list_tables(request).await.infer_error()?;
            Python::with_gil(|py| -> PyResult<Py<PyDict>> {
--- a/python/src/table.rs
+++ b/python/src/table.rs
@@ -497,11 +497,6 @@ impl Table {
        })
    }

-    pub fn uri(self_: PyRef<'_, Self>) -> PyResult<Bound<'_, PyAny>> {
-        let inner = self_.inner_ref()?.clone();
-        future_into_py(self_.py(), async move { inner.uri().await.infer_error() })
-    }
-
    pub fn __repr__(&self) -> String {
        match &self.inner {
            None => format!("ClosedTable({})", self.name),
--- a/rust/lancedb/Cargo.toml
+++ b/rust/lancedb/Cargo.toml
@@ -1,6 +1,6 @@
 [package]
 name = "lancedb"
-version = "0.24.1"
+version = "0.23.1-beta.1"
 edition.workspace = true
 description = "LanceDB: A serverless, low-latency vector database for AI applications"
 license.workspace = true
@@ -104,16 +104,11 @@ test-log = "0.2"


 [features]
-default = []
+default = ["aws", "gcs", "azure", "dynamodb", "oss"]
 aws = ["lance/aws", "lance-io/aws", "lance-namespace-impls/dir-aws"]
 oss = ["lance/oss", "lance-io/oss", "lance-namespace-impls/dir-oss"]
 gcs = ["lance/gcp", "lance-io/gcp", "lance-namespace-impls/dir-gcp"]
 azure = ["lance/azure", "lance-io/azure", "lance-namespace-impls/dir-azure"]
-huggingface = [
-    "lance/huggingface",
-    "lance-io/huggingface",
-    "lance-namespace-impls/dir-huggingface",
-]
 dynamodb = ["lance/dynamodb", "aws"]
 remote = ["dep:reqwest", "dep:http", "lance-namespace-impls/rest", "lance-namespace-impls/rest-adapter"]
 fp16kernels = ["lance-linalg/fp16kernels"]
@@ -153,6 +148,3 @@ name = "ivf_pq"
 [[example]]
 name = "hybrid_search"
 required-features = ["sentence-transformers"]
-
-[package.metadata.docs.rs]
-all-features = true
--- a/rust/lancedb/src/connection.rs
+++ b/rust/lancedb/src/connection.rs
@@ -36,42 +36,10 @@ use crate::remote::{
 };
 use crate::table::{TableDefinition, WriteOptions};
 use crate::Table;
-use lance::io::ObjectStoreParams;
 pub use lance_encoding::version::LanceFileVersion;
 #[cfg(feature = "remote")]
 use lance_io::object_store::StorageOptions;
-use lance_io::object_store::{StorageOptionsAccessor, StorageOptionsProvider};
-
-fn merge_storage_options(
-    store_params: &mut ObjectStoreParams,
-    pairs: impl IntoIterator<Item = (String, String)>,
-) {
-    let mut options = store_params.storage_options().cloned().unwrap_or_default();
-    for (key, value) in pairs {
-        options.insert(key, value);
-    }
-    let provider = store_params
-        .storage_options_accessor
-        .as_ref()
-        .and_then(|accessor| accessor.provider().cloned());
-    let accessor = if let Some(provider) = provider {
-        StorageOptionsAccessor::with_initial_and_provider(options, provider)
-    } else {
-        StorageOptionsAccessor::with_static_options(options)
-    };
-    store_params.storage_options_accessor = Some(Arc::new(accessor));
-}
-
-fn set_storage_options_provider(
-    store_params: &mut ObjectStoreParams,
-    provider: Arc<dyn StorageOptionsProvider>,
-) {
-    let accessor = match store_params.storage_options().cloned() {
-        Some(options) => StorageOptionsAccessor::with_initial_and_provider(options, provider),
-        None => StorageOptionsAccessor::with_provider(provider),
-    };
-    store_params.storage_options_accessor = Some(Arc::new(accessor));
-}
+use lance_io::object_store::StorageOptionsProvider;

 /// A builder for configuring a [`Connection::table_names`] operation
 pub struct TableNamesBuilder {
@@ -251,36 +219,8 @@ impl CreateTableBuilder<false> {
    /// Execute the create table operation
    pub async fn execute(self) -> Result<Table> {
        let parent = self.parent.clone();
-        let embedding_registry = self.embedding_registry.clone();
-        let request = self.into_request()?;
-        Ok(Table::new_with_embedding_registry(
-            parent.create_table(request).await?,
-            parent,
-            embedding_registry,
-        ))
-    }
-
-    fn into_request(self) -> Result<CreateTableRequest> {
-        if self.embeddings.is_empty() {
-            return Ok(self.request);
-        }
-
-        let CreateTableData::Empty(table_def) = self.request.data else {
-            unreachable!("CreateTableBuilder<false> should always have Empty data")
-        };
-
-        let schema = table_def.schema.clone();
-        let empty_batch = arrow_array::RecordBatch::new_empty(schema.clone());
-
-        let reader = Box::new(std::iter::once(Ok(empty_batch)).collect::<Vec<_>>());
-        let reader = arrow_array::RecordBatchIterator::new(reader.into_iter(), schema);
-        let with_embeddings = WithEmbeddings::new(reader, self.embeddings);
-        let table_definition = with_embeddings.table_definition()?;
-
-        Ok(CreateTableRequest {
-            data: CreateTableData::Empty(table_definition),
-            ..self.request
-        })
+        let table = parent.create_table(self.request).await?;
+        Ok(Table::new(table, parent))
    }
 }

@@ -306,14 +246,16 @@ impl<const HAS_DATA: bool> CreateTableBuilder<HAS_DATA> {
    ///
    /// See available options at <https://lancedb.com/docs/storage/>
    pub fn storage_option(mut self, key: impl Into<String>, value: impl Into<String>) -> Self {
-        let store_params = self
+        let store_options = self
            .request
            .write_options
            .lance_write_params
            .get_or_insert(Default::default())
            .store_params
+            .get_or_insert(Default::default())
+            .storage_options
            .get_or_insert(Default::default());
-        merge_storage_options(store_params, [(key.into(), value.into())]);
+        store_options.insert(key.into(), value.into());
        self
    }

@@ -327,17 +269,19 @@ impl<const HAS_DATA: bool> CreateTableBuilder<HAS_DATA> {
        mut self,
        pairs: impl IntoIterator<Item = (impl Into<String>, impl Into<String>)>,
    ) -> Self {
-        let store_params = self
+        let store_options = self
            .request
            .write_options
            .lance_write_params
            .get_or_insert(Default::default())
            .store_params
+            .get_or_insert(Default::default())
+            .storage_options
            .get_or_insert(Default::default());
-        let updates = pairs
-            .into_iter()
-            .map(|(key, value)| (key.into(), value.into()));
-        merge_storage_options(store_params, updates);
+
+        for (key, value) in pairs {
+            store_options.insert(key.into(), value.into());
+        }
        self
    }

@@ -374,21 +318,23 @@ impl<const HAS_DATA: bool> CreateTableBuilder<HAS_DATA> {
    /// This has no effect in LanceDB Cloud.
    #[deprecated(since = "0.15.1", note = "Use `database_options` instead")]
    pub fn enable_v2_manifest_paths(mut self, use_v2_manifest_paths: bool) -> Self {
-        let store_params = self
+        let storage_options = self
            .request
            .write_options
            .lance_write_params
            .get_or_insert_with(Default::default)
            .store_params
+            .get_or_insert_with(Default::default)
+            .storage_options
            .get_or_insert_with(Default::default);
-        let value = if use_v2_manifest_paths {
-            "true".to_string()
-        } else {
-            "false".to_string()
-        };
-        merge_storage_options(
-            store_params,
-            [(OPT_NEW_TABLE_V2_MANIFEST_PATHS.to_string(), value)],
+
+        storage_options.insert(
+            OPT_NEW_TABLE_V2_MANIFEST_PATHS.to_string(),
+            if use_v2_manifest_paths {
+                "true".to_string()
+            } else {
+                "false".to_string()
+            },
        );
        self
    }
@@ -398,19 +344,19 @@ impl<const HAS_DATA: bool> CreateTableBuilder<HAS_DATA> {
    /// The default is `LanceFileVersion::Stable`.
    #[deprecated(since = "0.15.1", note = "Use `database_options` instead")]
    pub fn data_storage_version(mut self, data_storage_version: LanceFileVersion) -> Self {
-        let store_params = self
+        let storage_options = self
            .request
            .write_options
            .lance_write_params
            .get_or_insert_with(Default::default)
            .store_params
+            .get_or_insert_with(Default::default)
+            .storage_options
            .get_or_insert_with(Default::default);
-        merge_storage_options(
-            store_params,
-            [(
-                OPT_NEW_TABLE_STORAGE_VERSION.to_string(),
-                data_storage_version.to_string(),
-            )],
+
+        storage_options.insert(
+            OPT_NEW_TABLE_STORAGE_VERSION.to_string(),
+            data_storage_version.to_string(),
        );
        self
    }
@@ -435,14 +381,13 @@ impl<const HAS_DATA: bool> CreateTableBuilder<HAS_DATA> {
    /// This allows tables to automatically refresh cloud storage credentials
    /// when they expire, enabling long-running operations on remote storage.
    pub fn storage_options_provider(mut self, provider: Arc<dyn StorageOptionsProvider>) -> Self {
-        let store_params = self
-            .request
+        self.request
            .write_options
            .lance_write_params
            .get_or_insert(Default::default())
            .store_params
-            .get_or_insert(Default::default());
-        set_storage_options_provider(store_params, provider);
+            .get_or_insert(Default::default())
+            .storage_options_provider = Some(provider);
        self
    }
 }
@@ -505,13 +450,15 @@ impl OpenTableBuilder {
    ///
    /// See available options at <https://lancedb.com/docs/storage/>
    pub fn storage_option(mut self, key: impl Into<String>, value: impl Into<String>) -> Self {
-        let store_params = self
+        let storage_options = self
            .request
            .lance_read_params
            .get_or_insert(Default::default())
            .store_options
+            .get_or_insert(Default::default())
+            .storage_options
            .get_or_insert(Default::default());
-        merge_storage_options(store_params, [(key.into(), value.into())]);
+        storage_options.insert(key.into(), value.into());
        self
    }

@@ -525,16 +472,18 @@ impl OpenTableBuilder {
        mut self,
        pairs: impl IntoIterator<Item = (impl Into<String>, impl Into<String>)>,
    ) -> Self {
-        let store_params = self
+        let storage_options = self
            .request
            .lance_read_params
            .get_or_insert(Default::default())
            .store_options
+            .get_or_insert(Default::default())
+            .storage_options
            .get_or_insert(Default::default());
-        let updates = pairs
-            .into_iter()
-            .map(|(key, value)| (key.into(), value.into()));
-        merge_storage_options(store_params, updates);
+
+        for (key, value) in pairs {
+            storage_options.insert(key.into(), value.into());
+        }
        self
    }

@@ -558,13 +507,12 @@ impl OpenTableBuilder {
    /// This allows tables to automatically refresh cloud storage credentials
    /// when they expire, enabling long-running operations on remote storage.
    pub fn storage_options_provider(mut self, provider: Arc<dyn StorageOptionsProvider>) -> Self {
-        let store_params = self
-            .request
+        self.request
            .lance_read_params
            .get_or_insert(Default::default())
            .store_options
-            .get_or_insert(Default::default());
-        set_storage_options_provider(store_params, provider);
+            .get_or_insert(Default::default())
+            .storage_options_provider = Some(provider);
        self
    }

@@ -920,10 +868,6 @@ pub struct ConnectBuilder {
    embedding_registry: Option<Arc<dyn EmbeddingRegistry>>,
 }

-#[cfg(feature = "remote")]
-const ENV_VARS_TO_STORAGE_OPTS: [(&str, &str); 1] =
-    [("AZURE_STORAGE_ACCOUNT_NAME", "azure_storage_account_name")];
-
 impl ConnectBuilder {
    /// Create a new [`ConnectOptions`] with the given database URI.
    pub fn new(uri: &str) -> Self {
@@ -1107,27 +1051,11 @@ impl ConnectBuilder {
        self
    }

-    #[cfg(feature = "remote")]
-    fn apply_env_defaults(
-        env_var_to_remote_storage_option: &[(&str, &str)],
-        options: &mut HashMap<String, String>,
-    ) {
-        for (env_key, opt_key) in env_var_to_remote_storage_option {
-            if let Ok(env_value) = std::env::var(env_key) {
-                if !options.contains_key(*opt_key) {
-                    options.insert((*opt_key).to_string(), env_value);
-                }
-            }
-        }
-    }
-
    #[cfg(feature = "remote")]
    fn execute_remote(self) -> Result<Connection> {
        use crate::remote::db::RemoteDatabaseOptions;

-        let mut merged_options = self.request.options.clone();
-        Self::apply_env_defaults(&ENV_VARS_TO_STORAGE_OPTS, &mut merged_options);
-        let options = RemoteDatabaseOptions::parse_from_map(&merged_options)?;
+        let options = RemoteDatabaseOptions::parse_from_map(&self.request.options)?;

        let region = options.region.ok_or_else(|| Error::InvalidInput {
            message: "A region is required when connecting to LanceDb Cloud".to_string(),
@@ -1349,6 +1277,8 @@ mod test_utils {

 #[cfg(test)]
 mod tests {
+    use std::fs::create_dir_all;
+
    use crate::database::listing::{ListingDatabaseOptions, NewTableConfig};
    use crate::query::QueryBase;
    use crate::query::{ExecutableQuery, QueryExecutionOptions};
@@ -1372,23 +1302,6 @@ mod tests {
        assert_eq!(tc.connection.uri(), tc.uri);
    }

-    #[cfg(feature = "remote")]
-    #[test]
-    fn test_apply_env_defaults() {
-        let env_key = "TEST_APPLY_ENV_DEFAULTS_ENVIRONMENT_VARIABLE_ENV_KEY";
-        let env_val = "TEST_APPLY_ENV_DEFAULTS_ENVIRONMENT_VARIABLE_ENV_VAL";
-        let opts_key = "test_apply_env_defaults_environment_variable_opts_key";
-        std::env::set_var(env_key, env_val);
-
-        let mut options = HashMap::new();
-        ConnectBuilder::apply_env_defaults(&[(env_key, opts_key)], &mut options);
-        assert_eq!(Some(&env_val.to_string()), options.get(opts_key));
-
-        options.insert(opts_key.to_string(), "EXPLICIT-VALUE".to_string());
-        ConnectBuilder::apply_env_defaults(&[(env_key, opts_key)], &mut options);
-        assert_eq!(Some(&"EXPLICIT-VALUE".to_string()), options.get(opts_key));
-    }
-
    #[cfg(not(windows))]
    #[tokio::test]
    async fn test_connect_relative() {
@@ -1412,27 +1325,25 @@ mod tests {

    #[tokio::test]
    async fn test_table_names() {
-        let tc = new_test_connection().await.unwrap();
-        let db = tc.connection;
-        let schema = Arc::new(Schema::new(vec![Field::new("x", DataType::Int32, false)]));
+        let tmp_dir = tempdir().unwrap();
        let mut names = Vec::with_capacity(100);
        for _ in 0..100 {
-            let name = uuid::Uuid::new_v4().to_string();
+            let mut name = uuid::Uuid::new_v4().to_string();
            names.push(name.clone());
-            db.create_empty_table(name, schema.clone())
-                .execute()
-                .await
-                .unwrap();
+            name.push_str(".lance");
+            create_dir_all(tmp_dir.path().join(&name)).unwrap();
        }
        names.sort();
-        let tables = db.table_names().limit(100).execute().await.unwrap();
+
+        let uri = tmp_dir.path().to_str().unwrap();
+        let db = connect(uri).execute().await.unwrap();
+        let tables = db.table_names().execute().await.unwrap();

        assert_eq!(tables, names);

        let tables = db
            .table_names()
            .start_after(&names[30])
-            .limit(100)
            .execute()
            .await
            .unwrap();
@@ -1613,27 +1524,18 @@ mod tests {

    #[tokio::test]
    async fn drop_table() {
-        let tc = new_test_connection().await.unwrap();
-        let db = tc.connection;
+        let tmp_dir = tempdir().unwrap();

-        if tc.is_remote {
-            // All the typical endpoints such as s3:///, file-object-store:///, etc. treat drop_table
-            // as idempotent.
-            assert!(db.drop_table("invalid_table", &[]).await.is_ok());
-        } else {
-            // The behavior of drop_table when using a file:/// endpoint differs from all other
-            // object providers, in that it returns an error when deleting a non-existent table.
-            assert!(matches!(
-                db.drop_table("invalid_table", &[]).await,
-                Err(crate::Error::TableNotFound { .. }),
-            ));
-        }
+        let uri = tmp_dir.path().to_str().unwrap();
+        let db = connect(uri).execute().await.unwrap();

-        let schema = Arc::new(Schema::new(vec![Field::new("x", DataType::Int32, false)]));
-        db.create_empty_table("table1", schema.clone())
-            .execute()
-            .await
-            .unwrap();
+        // drop non-exist table
+        assert!(matches!(
+            db.drop_table("invalid_table", &[]).await,
+            Err(crate::Error::TableNotFound { .. }),
+        ));
+
+        create_dir_all(tmp_dir.path().join("table1.lance")).unwrap();
        db.drop_table("table1", &[]).await.unwrap();

        let tables = db.table_names().execute().await.unwrap();
@@ -1720,128 +1622,4 @@ mod tests {
        let cloned_count = cloned_table.count_rows(None).await.unwrap();
        assert_eq!(source_count, cloned_count);
    }
-
-    #[tokio::test]
-    async fn test_create_empty_table_with_embeddings() {
-        use crate::embeddings::{EmbeddingDefinition, EmbeddingFunction};
-        use arrow_array::{
-            Array, FixedSizeListArray, Float32Array, RecordBatch, RecordBatchIterator, StringArray,
-        };
-        use std::borrow::Cow;
-
-        #[derive(Debug, Clone)]
-        struct MockEmbedding {
-            dim: usize,
-        }
-
-        impl EmbeddingFunction for MockEmbedding {
-            fn name(&self) -> &str {
-                "test_embedding"
-            }
-
-            fn source_type(&self) -> Result<Cow<'_, DataType>> {
-                Ok(Cow::Owned(DataType::Utf8))
-            }
-
-            fn dest_type(&self) -> Result<Cow<'_, DataType>> {
-                Ok(Cow::Owned(DataType::new_fixed_size_list(
-                    DataType::Float32,
-                    self.dim as i32,
-                    true,
-                )))
-            }
-
-            fn compute_source_embeddings(&self, source: Arc<dyn Array>) -> Result<Arc<dyn Array>> {
-                let len = source.len();
-                let values = vec![1.0f32; len * self.dim];
-                let values = Arc::new(Float32Array::from(values));
-                let field = Arc::new(Field::new("item", DataType::Float32, true));
-                Ok(Arc::new(FixedSizeListArray::new(
-                    field,
-                    self.dim as i32,
-                    values,
-                    None,
-                )))
-            }
-
-            fn compute_query_embeddings(&self, _input: Arc<dyn Array>) -> Result<Arc<dyn Array>> {
-                unimplemented!()
-            }
-        }
-
-        let tmp_dir = tempdir().unwrap();
-        let uri = tmp_dir.path().to_str().unwrap();
-        let db = connect(uri).execute().await.unwrap();
-
-        let embed_func = Arc::new(MockEmbedding { dim: 128 });
-        db.embedding_registry()
-            .register("test_embedding", embed_func.clone())
-            .unwrap();
-
-        let schema = Arc::new(Schema::new(vec![Field::new("name", DataType::Utf8, true)]));
-        let ed = EmbeddingDefinition {
-            source_column: "name".to_owned(),
-            dest_column: Some("name_embedding".to_owned()),
-            embedding_name: "test_embedding".to_owned(),
-        };
-
-        let table = db
-            .create_empty_table("test", schema)
-            .mode(CreateTableMode::Overwrite)
-            .add_embedding(ed)
-            .unwrap()
-            .execute()
-            .await
-            .unwrap();
-
-        let table_schema = table.schema().await.unwrap();
-        assert!(table_schema.column_with_name("name").is_some());
-        assert!(table_schema.column_with_name("name_embedding").is_some());
-
-        let embedding_field = table_schema.field_with_name("name_embedding").unwrap();
-        assert_eq!(
-            embedding_field.data_type(),
-            &DataType::new_fixed_size_list(DataType::Float32, 128, true)
-        );
-
-        let input_schema = Arc::new(Schema::new(vec![Field::new("name", DataType::Utf8, true)]));
-        let input_batch = RecordBatch::try_new(
-            input_schema.clone(),
-            vec![Arc::new(StringArray::from(vec![
-                Some("Alice"),
-                Some("Bob"),
-                Some("Charlie"),
-            ]))],
-        )
-        .unwrap();
-
-        let input_reader = Box::new(RecordBatchIterator::new(
-            vec![Ok(input_batch)].into_iter(),
-            input_schema,
-        ));
-
-        table.add(input_reader).execute().await.unwrap();
-
-        let results = table
-            .query()
-            .execute()
-            .await
-            .unwrap()
-            .try_collect::<Vec<_>>()
-            .await
-            .unwrap();
-
-        assert_eq!(results.len(), 1);
-        let batch = &results[0];
-        assert_eq!(batch.num_rows(), 3);
-        assert!(batch.column_by_name("name_embedding").is_some());
-
-        let embedding_col = batch
-            .column_by_name("name_embedding")
-            .unwrap()
-            .as_any()
-            .downcast_ref::<FixedSizeListArray>()
-            .unwrap();
-        assert_eq!(embedding_col.len(), 3);
-    }
 }
--- a/rust/lancedb/src/database/listing.rs
+++ b/rust/lancedb/src/database/listing.rs
@@ -12,7 +12,7 @@ use lance::dataset::{builder::DatasetBuilder, ReadParams, WriteMode};
 use lance::io::{ObjectStore, ObjectStoreParams, WrappingObjectStore};
 use lance_datafusion::utils::StreamingWriteSource;
 use lance_encoding::version::LanceFileVersion;
-use lance_io::object_store::{StorageOptionsAccessor, StorageOptionsProvider};
+use lance_io::object_store::StorageOptionsProvider;
 use lance_table::io::commit::commit_handler_from_url;
 use object_store::local::LocalFileSystem;
 use snafu::ResultExt;
@@ -356,13 +356,7 @@ impl ListingDatabase {
                    .clone()
                    .unwrap_or_else(|| Arc::new(lance::session::Session::default()));
                let os_params = ObjectStoreParams {
-                    storage_options_accessor: if options.storage_options.is_empty() {
-                        None
-                    } else {
-                        Some(Arc::new(StorageOptionsAccessor::with_static_options(
-                            options.storage_options.clone(),
-                        )))
-                    },
+                    storage_options: Some(options.storage_options.clone()),
                    ..Default::default()
                };
                let (object_store, base_path) = ObjectStore::from_uri_and_params(
@@ -469,20 +463,9 @@ impl ListingDatabase {
        validate_table_name(name)?;

        let mut uri = self.uri.clone();
-        // If the URI does not end with a path separator, add one
-        // Use forward slash for URIs (http://, s3://, gs://, file://, etc.)
-        // Use platform-specific separator for local paths without scheme
-        let has_scheme = uri.contains("://");
-        let ends_with_separator = uri.ends_with('/') || uri.ends_with('\\');
-
-        if !ends_with_separator {
-            if has_scheme {
-                // URIs always use forward slash
-                uri.push('/');
-            } else {
-                // Local path without scheme - use platform separator
-                uri.push(std::path::MAIN_SEPARATOR);
-            }
+        // If the URI does not end with a slash, add one
+        if !uri.ends_with('/') {
+            uri.push('/');
        }
        // Append the table name with the lance file extension
        uri.push_str(&format!("{}.{}", name, LANCE_FILE_EXTENSION));
@@ -498,13 +481,7 @@ impl ListingDatabase {

    async fn drop_tables(&self, names: Vec<String>) -> Result<()> {
        let object_store_params = ObjectStoreParams {
-            storage_options_accessor: if self.storage_options.is_empty() {
-                None
-            } else {
-                Some(Arc::new(StorageOptionsAccessor::with_static_options(
-                    self.storage_options.clone(),
-                )))
-            },
+            storage_options: Some(self.storage_options.clone()),
            ..Default::default()
        };
        let mut uri = self.uri.clone();
@@ -553,7 +530,7 @@ impl ListingDatabase {
            .lance_write_params
            .as_ref()
            .and_then(|p| p.store_params.as_ref())
-            .and_then(|sp| sp.storage_options());
+            .and_then(|sp| sp.storage_options.as_ref());

        let storage_version_override = storage_options
            .and_then(|opts| opts.get(OPT_NEW_TABLE_STORAGE_VERSION))
@@ -604,20 +581,21 @@ impl ListingDatabase {
        // will cause a new connection to be created, and that connection will
        // be dropped from the cache when python GCs the table object, which
        // confounds reuse across tables.
-        if !self.storage_options.is_empty() || self.storage_options_provider.is_some() {
-            let store_params = write_params
+        if !self.storage_options.is_empty() {
+            let storage_options = write_params
                .store_params
+                .get_or_insert_with(Default::default)
+                .storage_options
                .get_or_insert_with(Default::default);
-            let mut storage_options = store_params.storage_options().cloned().unwrap_or_default();
-            if !self.storage_options.is_empty() {
-                self.inherit_storage_options(&mut storage_options);
-            }
-            let accessor = if let Some(ref provider) = self.storage_options_provider {
-                StorageOptionsAccessor::with_initial_and_provider(storage_options, provider.clone())
-            } else {
-                StorageOptionsAccessor::with_static_options(storage_options)
-            };
-            store_params.storage_options_accessor = Some(Arc::new(accessor));
+            self.inherit_storage_options(storage_options);
+        }
+
+        // Set storage options provider if available
+        if self.storage_options_provider.is_some() {
+            write_params
+                .store_params
+                .get_or_insert_with(Default::default)
+                .storage_options_provider = self.storage_options_provider.clone();
        }

        write_params.data_storage_version = self
@@ -903,13 +881,7 @@ impl Database for ListingDatabase {
        validate_table_name(&request.target_table_name)?;

        let storage_params = ObjectStoreParams {
-            storage_options_accessor: if self.storage_options.is_empty() {
-                None
-            } else {
-                Some(Arc::new(StorageOptionsAccessor::with_static_options(
-                    self.storage_options.clone(),
-                )))
-            },
+            storage_options: Some(self.storage_options.clone()),
            ..Default::default()
        };
        let read_params = ReadParams {
@@ -973,28 +945,25 @@ impl Database for ListingDatabase {
        // will cause a new connection to be created, and that connection will
        // be dropped from the cache when python GCs the table object, which
        // confounds reuse across tables.
-        if !self.storage_options.is_empty() || self.storage_options_provider.is_some() {
-            let store_params = request
+        if !self.storage_options.is_empty() {
+            let storage_options = request
                .lance_read_params
                .get_or_insert_with(Default::default)
                .store_options
+                .get_or_insert_with(Default::default)
+                .storage_options
                .get_or_insert_with(Default::default);
-            let mut storage_options = store_params.storage_options().cloned().unwrap_or_default();
-            if !self.storage_options.is_empty() {
-                self.inherit_storage_options(&mut storage_options);
-            }
-            // Preserve request-level provider if no connection-level provider exists
-            let request_provider = store_params
-                .storage_options_accessor
-                .as_ref()
-                .and_then(|a| a.provider().cloned());
-            let provider = self.storage_options_provider.clone().or(request_provider);
-            let accessor = if let Some(provider) = provider {
-                StorageOptionsAccessor::with_initial_and_provider(storage_options, provider)
-            } else {
-                StorageOptionsAccessor::with_static_options(storage_options)
-            };
-            store_params.storage_options_accessor = Some(Arc::new(accessor));
+            self.inherit_storage_options(storage_options);
+        }
+
+        // Set storage options provider if available
+        if self.storage_options_provider.is_some() {
+            request
+                .lance_read_params
+                .get_or_insert_with(Default::default)
+                .store_options
+                .get_or_insert_with(Default::default)
+                .storage_options_provider = self.storage_options_provider.clone();
        }

        // Some ReadParams are exposed in the OpenTableBuilder, but we also
@@ -1102,7 +1071,6 @@ mod tests {
    use crate::table::{Table, TableDefinition};
    use arrow_array::{Int32Array, RecordBatch, StringArray};
    use arrow_schema::{DataType, Field, Schema};
-    use std::path::PathBuf;
    use tempfile::tempdir;

    async fn setup_database() -> (tempfile::TempDir, ListingDatabase) {
@@ -1901,9 +1869,7 @@ mod tests {
        let write_options = WriteOptions {
            lance_write_params: Some(lance::dataset::WriteParams {
                store_params: Some(lance::io::ObjectStoreParams {
-                    storage_options_accessor: Some(Arc::new(
-                        StorageOptionsAccessor::with_static_options(storage_options),
-                    )),
+                    storage_options: Some(storage_options),
                    ..Default::default()
                }),
                ..Default::default()
@@ -1977,9 +1943,7 @@ mod tests {
        let write_options = WriteOptions {
            lance_write_params: Some(lance::dataset::WriteParams {
                store_params: Some(lance::io::ObjectStoreParams {
-                    storage_options_accessor: Some(Arc::new(
-                        StorageOptionsAccessor::with_static_options(storage_options),
-                    )),
+                    storage_options: Some(storage_options),
                    ..Default::default()
                }),
                ..Default::default()
@@ -2082,19 +2046,6 @@ mod tests {
        assert_eq!(db_options.new_table_config.enable_stable_row_ids, None);
    }

-    #[tokio::test]
-    async fn test_table_uri() {
-        let (_tempdir, db) = setup_database().await;
-
-        let mut pb = PathBuf::new();
-        pb.push(db.uri.clone());
-        pb.push("test.lance");
-
-        let expected = pb.to_str().unwrap();
-        let uri = db.table_uri("test").ok().unwrap();
-        assert_eq!(uri, expected);
-    }
-
    #[tokio::test]
    async fn test_namespace_client() {
        let (_tempdir, db) = setup_database().await;
--- a/rust/lancedb/src/database/namespace.rs
+++ b/rust/lancedb/src/database/namespace.rs
@@ -10,14 +10,13 @@ use async_trait::async_trait;
 use lance_namespace::{
    models::{
        CreateEmptyTableRequest, CreateNamespaceRequest, CreateNamespaceResponse,
-        DeclareTableRequest, DescribeNamespaceRequest, DescribeNamespaceResponse,
-        DescribeTableRequest, DropNamespaceRequest, DropNamespaceResponse, DropTableRequest,
-        ListNamespacesRequest, ListNamespacesResponse, ListTablesRequest, ListTablesResponse,
+        DescribeNamespaceRequest, DescribeNamespaceResponse, DescribeTableRequest,
+        DropNamespaceRequest, DropNamespaceResponse, DropTableRequest, ListNamespacesRequest,
+        ListNamespacesResponse, ListTablesRequest, ListTablesResponse,
    },
    LanceNamespace,
 };
 use lance_namespace_impls::ConnectBuilder;
-use log::warn;

 use crate::database::ReadConsistency;
 use crate::error::{Error, Result};
@@ -138,7 +137,6 @@ impl Database for LanceNamespaceDatabase {
            id: Some(request.namespace),
            page_token: request.start_after,
            limit: request.limit.map(|l| l as i32),
-            ..Default::default()
        };

        let response = self.namespace.list_tables(ns_request).await?;
@@ -155,7 +153,8 @@ impl Database for LanceNamespaceDatabase {
        table_id.push(request.name.clone());
        let describe_request = DescribeTableRequest {
            id: Some(table_id.clone()),
-            ..Default::default()
+            version: None,
+            with_table_uri: None,
        };

        let describe_result = self.namespace.describe_table(describe_request).await;
@@ -173,7 +172,6 @@ impl Database for LanceNamespaceDatabase {
                    // Drop the existing table - must succeed
                    let drop_request = DropTableRequest {
                        id: Some(table_id.clone()),
-                        ..Default::default()
                    };
                    self.namespace
                        .drop_table(drop_request)
@@ -205,53 +203,29 @@ impl Database for LanceNamespaceDatabase {
        let mut table_id = request.namespace.clone();
        table_id.push(request.name.clone());

-        // Try declare_table first, falling back to create_empty_table for backwards
-        // compatibility with older namespace clients that don't support declare_table
-        let declare_request = DeclareTableRequest {
+        let create_empty_request = CreateEmptyTableRequest {
            id: Some(table_id.clone()),
-            ..Default::default()
+            location: None,
+            properties: if self.storage_options.is_empty() {
+                None
+            } else {
+                Some(self.storage_options.clone())
+            },
        };

-        let location = match self.namespace.declare_table(declare_request).await {
-            Ok(response) => response.location.ok_or_else(|| Error::Runtime {
-                message: "Table location is missing from declare_table response".to_string(),
-            })?,
-            Err(e) => {
-                // Check if the error is "not supported" and try create_empty_table as fallback
-                let err_str = e.to_string().to_lowercase();
-                if err_str.contains("not supported") || err_str.contains("not implemented") {
-                    warn!(
-                        "declare_table is not supported by the namespace client, \
-                        falling back to deprecated create_empty_table. \
-                        create_empty_table is deprecated and will be removed in Lance 3.0.0. \
-                        Please upgrade your namespace client to support declare_table."
-                    );
-                    #[allow(deprecated)]
-                    let create_empty_request = CreateEmptyTableRequest {
-                        id: Some(table_id.clone()),
-                        ..Default::default()
-                    };
+        let create_empty_response = self
+            .namespace
+            .create_empty_table(create_empty_request)
+            .await
+            .map_err(|e| Error::Runtime {
+                message: format!("Failed to create empty table: {}", e),
+            })?;

-                    #[allow(deprecated)]
-                    let create_response = self
-                        .namespace
-                        .create_empty_table(create_empty_request)
-                        .await
-                        .map_err(|e| Error::Runtime {
-                            message: format!("Failed to create empty table: {}", e),
-                        })?;
-
-                    create_response.location.ok_or_else(|| Error::Runtime {
-                        message: "Table location is missing from create_empty_table response"
-                            .to_string(),
-                    })?
-                } else {
-                    return Err(Error::Runtime {
-                        message: format!("Failed to declare table: {}", e),
-                    });
-                }
-            }
-        };
+        let location = create_empty_response
+            .location
+            .ok_or_else(|| Error::Runtime {
+                message: "Table location is missing from create_empty_table response".to_string(),
+            })?;

        let native_table = NativeTable::create_from_namespace(
            self.namespace.clone(),
@@ -308,10 +282,7 @@ impl Database for LanceNamespaceDatabase {
        let mut table_id = namespace.to_vec();
        table_id.push(name.to_string());

-        let drop_request = DropTableRequest {
-            id: Some(table_id),
-            ..Default::default()
-        };
+        let drop_request = DropTableRequest { id: Some(table_id) };
        self.namespace
            .drop_table(drop_request)
            .await
@@ -466,7 +437,8 @@ mod tests {
        // Create a child namespace first
        conn.create_namespace(CreateNamespaceRequest {
            id: Some(vec!["test_ns".into()]),
-            ..Default::default()
+            mode: None,
+            properties: None,
        })
        .await
        .expect("Failed to create namespace");
@@ -526,7 +498,8 @@ mod tests {
        // Create a child namespace first
        conn.create_namespace(CreateNamespaceRequest {
            id: Some(vec!["test_ns".into()]),
-            ..Default::default()
+            mode: None,
+            properties: None,
        })
        .await
        .expect("Failed to create namespace");
@@ -589,7 +562,8 @@ mod tests {
        // Create a child namespace first
        conn.create_namespace(CreateNamespaceRequest {
            id: Some(vec!["test_ns".into()]),
-            ..Default::default()
+            mode: None,
+            properties: None,
        })
        .await
        .expect("Failed to create namespace");
@@ -672,7 +646,8 @@ mod tests {
        // Create a child namespace first
        conn.create_namespace(CreateNamespaceRequest {
            id: Some(vec!["test_ns".into()]),
-            ..Default::default()
+            mode: None,
+            properties: None,
        })
        .await
        .expect("Failed to create namespace");
@@ -727,7 +702,8 @@ mod tests {
        // Create a child namespace first
        conn.create_namespace(CreateNamespaceRequest {
            id: Some(vec!["test_ns".into()]),
-            ..Default::default()
+            mode: None,
+            properties: None,
        })
        .await
        .expect("Failed to create namespace");
@@ -807,7 +783,8 @@ mod tests {
        // Create a child namespace first
        conn.create_namespace(CreateNamespaceRequest {
            id: Some(vec!["test_ns".into()]),
-            ..Default::default()
+            mode: None,
+            properties: None,
        })
        .await
        .expect("Failed to create namespace");
@@ -840,7 +817,8 @@ mod tests {
        // Create a child namespace first
        conn.create_namespace(CreateNamespaceRequest {
            id: Some(vec!["test_ns".into()]),
-            ..Default::default()
+            mode: None,
+            properties: None,
        })
        .await
        .expect("Failed to create namespace");
--- a/rust/lancedb/src/dataloader/permutation/builder.rs
+++ b/rust/lancedb/src/dataloader/permutation/builder.rs
@@ -19,7 +19,7 @@ use crate::{
        split::{SplitStrategy, Splitter, SPLIT_ID_COLUMN},
        util::{rename_column, TemporaryDirectory},
    },
-    query::{ExecutableQuery, QueryBase, Select},
+    query::{ExecutableQuery, QueryBase},
    Error, Result, Table,
 };

@@ -27,8 +27,6 @@ pub const SRC_ROW_ID_COL: &str = "row_id";

 pub const SPLIT_NAMES_CONFIG_KEY: &str = "split_names";

-pub const DEFAULT_MEMORY_LIMIT: usize = 100 * 1024 * 1024;
-
 /// Where to store the permutation table
 #[derive(Debug, Clone, Default)]
 enum PermutationDestination {
@@ -169,20 +167,10 @@ impl PermutationBuilder {
        &self,
        data: SendableRecordBatchStream,
    ) -> Result<SendableRecordBatchStream> {
-        let memory_limit = std::env::var("LANCEDB_PERM_BUILDER_MEMORY_LIMIT")
-            .unwrap_or_else(|_| DEFAULT_MEMORY_LIMIT.to_string())
-            .parse::<usize>()
-            .unwrap_or_else(|_| {
-                log::error!(
-                    "Failed to parse LANCEDB_PERM_BUILDER_MEMORY_LIMIT, using default: {}",
-                    DEFAULT_MEMORY_LIMIT
-                );
-                DEFAULT_MEMORY_LIMIT
-            });
        let ctx = SessionContext::new_with_config_rt(
            SessionConfig::default(),
            RuntimeEnvBuilder::new()
-                .with_memory_limit(memory_limit, 1.0)
+                .with_memory_limit(100 * 1024 * 1024, 1.0)
                .with_disk_manager_builder(
                    DiskManagerBuilder::default()
                        .with_mode(self.config.temp_dir.to_disk_manager_mode()),
@@ -244,7 +232,7 @@ impl PermutationBuilder {
    /// Builds the permutation table and stores it in the given database.
    pub async fn build(self) -> Result<Table> {
        // First pass, apply filter and load row ids
-        let mut rows = self.base_table.query().select(Select::columns(&[ROW_ID]));
+        let mut rows = self.base_table.query().with_row_id();

        if let Some(filter) = &self.config.filter {
            rows = rows.only_if(filter);
@@ -333,47 +321,6 @@ mod tests {

    use super::*;

-    #[tokio::test]
-    async fn test_permutation_table_only_stores_row_id_and_split_id() {
-        let temp_dir = tempfile::tempdir().unwrap();
-
-        let db = connect(temp_dir.path().to_str().unwrap())
-            .execute()
-            .await
-            .unwrap();
-
-        let initial_data = lance_datagen::gen_batch()
-            .col("col_a", lance_datagen::array::step::<Int32Type>())
-            .col("col_b", lance_datagen::array::step::<Int32Type>())
-            .into_ldb_stream(RowCount::from(100), BatchCount::from(10));
-        let data_table = db
-            .create_table_streaming("base_tbl", initial_data)
-            .execute()
-            .await
-            .unwrap();
-
-        let permutation_table = PermutationBuilder::new(data_table.clone())
-            .with_split_strategy(
-                SplitStrategy::Sequential {
-                    sizes: SplitSizes::Percentages(vec![0.5, 0.5]),
-                },
-                None,
-            )
-            .with_filter("col_a > 57".to_string())
-            .build()
-            .await
-            .unwrap();
-
-        let schema = permutation_table.schema().await.unwrap();
-        let field_names: Vec<&str> = schema.fields().iter().map(|f| f.name().as_str()).collect();
-        assert_eq!(
-            field_names,
-            vec!["row_id", "split_id"],
-            "Permutation table should only contain row_id and split_id columns, but found: {:?}",
-            field_names,
-        );
-    }
-
    #[tokio::test]
    async fn test_permutation_builder() {
        let temp_dir = tempfile::tempdir().unwrap();
@@ -405,6 +352,8 @@ mod tests {
            .await
            .unwrap();

+        println!("permutation_table: {:?}", permutation_table);
+
        // Potentially brittle seed-dependent values below
        assert_eq!(permutation_table.count_rows(None).await.unwrap(), 330);
        assert_eq!(
--- a/rust/lancedb/src/dataloader/permutation/shuffle.rs
+++ b/rust/lancedb/src/dataloader/permutation/shuffle.rs
@@ -171,7 +171,7 @@ impl Shuffler {
            // This is kind of an annoying limitation but if we allow runt clumps from batches then
            // clumps will get unaligned and we will mess up the clumps when we do the in-memory
            // shuffle step.  If this is a problem we can probably figure out a better way to do this.
-            if !is_last && !(batch.num_rows() as u64).is_multiple_of(clump_size) {
+            if !is_last && batch.num_rows() as u64 % clump_size != 0 {
                return Err(Error::Runtime {
                    message: format!(
                        "Expected batch size ({}) to be divisible by clump size ({})",
--- a/rust/lancedb/src/dataloader/permutation/split.rs
+++ b/rust/lancedb/src/dataloader/permutation/split.rs
@@ -1,9 +1,12 @@
 // SPDX-License-Identifier: Apache-2.0
 // SPDX-FileCopyrightText: Copyright The LanceDB Authors

-use std::sync::{
-    atomic::{AtomicBool, AtomicU64, AtomicUsize, Ordering},
-    Arc,
+use std::{
+    iter,
+    sync::{
+        atomic::{AtomicBool, AtomicU64, AtomicUsize, Ordering},
+        Arc,
+    },
 };

 use arrow_array::{Array, BooleanArray, RecordBatch, UInt64Array};
@@ -12,8 +15,6 @@ use datafusion_common::hash_utils::create_hashes;
 use futures::{StreamExt, TryStreamExt};
 use lance_arrow::SchemaExt;

-use lance_core::ROW_ID;
-
 use crate::{
    arrow::{SendableRecordBatchStream, SimpleRecordBatchStream},
    dataloader::{
@@ -157,7 +158,7 @@ impl Splitter {
                remaining_in_split
            };

-            split_ids.extend(std::iter::repeat_n(split_id as u64, rows_to_add as usize));
+            split_ids.extend(iter::repeat(split_id as u64).take(rows_to_add as usize));
            if done {
                // Quit early if we've run out of splits
                break;
@@ -362,15 +363,11 @@ impl Splitter {

    pub fn project(&self, query: Query) -> Query {
        match &self.strategy {
-            SplitStrategy::Calculated { calculation } => query.select(Select::Dynamic(vec![
-                (SPLIT_ID_COLUMN.to_string(), calculation.clone()),
-                (ROW_ID.to_string(), ROW_ID.to_string()),
-            ])),
-            SplitStrategy::Hash { columns, .. } => {
-                let mut cols = columns.clone();
-                cols.push(ROW_ID.to_string());
-                query.select(Select::Columns(cols))
-            }
+            SplitStrategy::Calculated { calculation } => query.select(Select::Dynamic(vec![(
+                SPLIT_ID_COLUMN.to_string(),
+                calculation.clone(),
+            )])),
+            SplitStrategy::Hash { columns, .. } => query.select(Select::Columns(columns.clone())),
            _ => query,
        }
    }
@@ -665,7 +662,7 @@ mod tests {
        assert_eq!(split_batch.num_rows(), total_split_sizes as usize);
        let mut expected = Vec::with_capacity(total_split_sizes as usize);
        for (i, size) in expected_split_sizes.iter().enumerate() {
-            expected.extend(std::iter::repeat_n(i as u64, *size as usize));
+            expected.extend(iter::repeat(i as u64).take(*size as usize));
        }
        let expected = Arc::new(UInt64Array::from(expected)) as Arc<dyn Array>;

--- a/rust/lancedb/src/embeddings.rs
+++ b/rust/lancedb/src/embeddings.rs
@@ -120,13 +120,8 @@ impl MemoryRegistry {
 }

 /// A record batch reader that has embeddings applied to it
-///
-/// This is a wrapper around another record batch reader that applies embedding functions
-/// when reading from the record batch.
-///
-/// When multiple embedding functions are defined, they are computed in parallel using
-/// scoped threads to improve performance. For a single embedding function, computation
-/// is done inline without threading overhead.
+/// This is a wrapper around another record batch reader that applies an embedding function
+/// when reading from the record batch
 pub struct WithEmbeddings<R: RecordBatchReader> {
    inner: R,
    embeddings: Vec<(EmbeddingDefinition, Arc<dyn EmbeddingFunction>)>,
@@ -240,48 +235,6 @@ impl<R: RecordBatchReader> WithEmbeddings<R> {
            column_definitions,
        })
    }
-
-    fn compute_embeddings_parallel(&self, batch: &RecordBatch) -> Result<Vec<Arc<dyn Array>>> {
-        if self.embeddings.len() == 1 {
-            let (fld, func) = &self.embeddings[0];
-            let src_column =
-                batch
-                    .column_by_name(&fld.source_column)
-                    .ok_or_else(|| Error::InvalidInput {
-                        message: format!("Source column '{}' not found", fld.source_column),
-                    })?;
-            return Ok(vec![func.compute_source_embeddings(src_column.clone())?]);
-        }
-
-        // Parallel path: multiple embeddings
-        std::thread::scope(|s| {
-            let handles: Vec<_> = self
-                .embeddings
-                .iter()
-                .map(|(fld, func)| {
-                    let src_column = batch.column_by_name(&fld.source_column).ok_or_else(|| {
-                        Error::InvalidInput {
-                            message: format!("Source column '{}' not found", fld.source_column),
-                        }
-                    })?;
-
-                    let handle =
-                        s.spawn(move || func.compute_source_embeddings(src_column.clone()));
-
-                    Ok(handle)
-                })
-                .collect::<Result<_>>()?;
-
-            handles
-                .into_iter()
-                .map(|h| {
-                    h.join().map_err(|e| Error::Runtime {
-                        message: format!("Thread panicked during embedding computation: {:?}", e),
-                    })?
-                })
-                .collect()
-        })
-    }
 }

 impl<R: RecordBatchReader> Iterator for MaybeEmbedded<R> {
@@ -309,19 +262,19 @@ impl<R: RecordBatchReader> Iterator for WithEmbeddings<R> {
    fn next(&mut self) -> Option<Self::Item> {
        let batch = self.inner.next()?;
        match batch {
-            Ok(batch) => {
-                let embeddings = match self.compute_embeddings_parallel(&batch) {
-                    Ok(emb) => emb,
-                    Err(e) => {
-                        return Some(Err(arrow_schema::ArrowError::ComputeError(format!(
-                            "Error computing embedding: {}",
-                            e
-                        ))))
-                    }
-                };
-
-                let mut batch = batch;
-                for ((fld, _), embedding) in self.embeddings.iter().zip(embeddings.iter()) {
+            Ok(mut batch) => {
+                // todo: parallelize this
+                for (fld, func) in self.embeddings.iter() {
+                    let src_column = batch.column_by_name(&fld.source_column).unwrap();
+                    let embedding = match func.compute_source_embeddings(src_column.clone()) {
+                        Ok(embedding) => embedding,
+                        Err(e) => {
+                            return Some(Err(arrow_schema::ArrowError::ComputeError(format!(
+                                "Error computing embedding: {}",
+                                e
+                            ))))
+                        }
+                    };
                    let dst_field_name = fld
                        .dest_column
                        .clone()
@@ -333,7 +286,7 @@ impl<R: RecordBatchReader> Iterator for WithEmbeddings<R> {
                        embedding.nulls().is_some(),
                    );

-                    match batch.try_with_column(dst_field.clone(), embedding.clone()) {
+                    match batch.try_with_column(dst_field.clone(), embedding) {
                        Ok(b) => batch = b,
                        Err(e) => return Some(Err(e)),
                    };
--- a/rust/lancedb/src/index/vector.rs
+++ b/rust/lancedb/src/index/vector.rs
@@ -297,10 +297,10 @@ impl IvfPqIndexBuilder {
 }

 pub(crate) fn suggested_num_sub_vectors(dim: u32) -> u32 {
-    if dim.is_multiple_of(16) {
+    if dim % 16 == 0 {
        // Should be more aggressive than this default.
        dim / 16
-    } else if dim.is_multiple_of(8) {
+    } else if dim % 8 == 0 {
        dim / 8
    } else {
        log::warn!(
--- a/rust/lancedb/src/lib.rs
+++ b/rust/lancedb/src/lib.rs
@@ -25,14 +25,13 @@
 //!
 //! ## Crate Features
 //!
-//! - `aws` - Enable AWS S3 object store support.
-//! - `dynamodb` - Enable DynamoDB manifest store support.
-//! - `azure` - Enable Azure Blob Storage object store support.
-//! - `gcs` - Enable Google Cloud Storage object store support.
-//! - `oss` - Enable Alibaba Cloud OSS object store support.
-//! - `remote` - Enable remote client to connect to LanceDB cloud.
-//! - `huggingface` - Enable HuggingFace Hub integration for loading datasets from the Hub.
-//! - `fp16kernels` - Enable FP16 kernels for faster vector search on CPU.
+//! ### Experimental Features
+//!
+//! These features are not enabled by default.  They are experimental or in-development features that
+//! are not yet ready to be released.
+//!
+//! - `remote` - Enable remote client to connect to LanceDB cloud.  This is not yet fully implemented
+//!   and should not be enabled.
 //!
 //! ### Quick Start
 //!
@@ -51,15 +50,17 @@
 //! - `s3://bucket/path/to/database` or `gs://bucket/path/to/database` - database on cloud object store
 //! - `db://dbname` - Lance Cloud
 //!
-//! You can also use [`ConnectBuilder`] to configure the connection to the database.
+//! You can also use [`ConnectOptions`] to configure the connection to the database.
 //!
 //! ```rust
+//! use object_store::aws::AwsCredential;
 //! # tokio::runtime::Runtime::new().unwrap().block_on(async {
 //! let db = lancedb::connect("data/sample-lancedb")
-//!     .storage_options([
-//!         ("aws_access_key_id", "some_key"),
-//!         ("aws_secret_access_key", "some_secret"),
-//!     ])
+//!     .aws_creds(AwsCredential {
+//!         key_id: "some_key".to_string(),
+//!         secret_key: "some_secret".to_string(),
+//!         token: None,
+//!     })
 //!     .execute()
 //!     .await
 //!     .unwrap();
--- a/rust/lancedb/src/remote/db.rs
+++ b/rust/lancedb/src/remote/db.rs
@@ -1718,7 +1718,8 @@ mod tests {
            let namespace = vec!["test_ns".to_string()];
            conn.create_namespace(CreateNamespaceRequest {
                id: Some(namespace.clone()),
-                ..Default::default()
+                mode: None,
+                properties: None,
            })
            .await
            .expect("Failed to create namespace");
@@ -1743,7 +1744,8 @@ mod tests {
            let list_response = conn
                .list_tables(ListTablesRequest {
                    id: Some(namespace.clone()),
-                    ..Default::default()
+                    page_token: None,
+                    limit: None,
                })
                .await
                .expect("Failed to list tables");
@@ -1754,7 +1756,8 @@ mod tests {
            let list_response = namespace_client
                .list_tables(ListTablesRequest {
                    id: Some(namespace.clone()),
-                    ..Default::default()
+                    page_token: None,
+                    limit: None,
                })
                .await
                .unwrap();
@@ -1794,7 +1797,8 @@ mod tests {
            let namespace = vec!["multi_table_ns".to_string()];
            conn.create_namespace(CreateNamespaceRequest {
                id: Some(namespace.clone()),
-                ..Default::default()
+                mode: None,
+                properties: None,
            })
            .await
            .expect("Failed to create namespace");
@@ -1819,7 +1823,8 @@ mod tests {
            let list_response = conn
                .list_tables(ListTablesRequest {
                    id: Some(namespace.clone()),
-                    ..Default::default()
+                    page_token: None,
+                    limit: None,
                })
                .await
                .unwrap();
--- a/rust/lancedb/src/remote/table.rs
+++ b/rust/lancedb/src/remote/table.rs
@@ -204,7 +204,6 @@ pub struct RemoteTable<S: HttpSend = Sender> {
    server_version: ServerVersion,

    version: RwLock<Option<u64>>,
-    location: RwLock<Option<String>>,
 }

 impl<S: HttpSend> RemoteTable<S> {
@@ -222,7 +221,6 @@ impl<S: HttpSend> RemoteTable<S> {
            identifier,
            server_version,
            version: RwLock::new(None),
-            location: RwLock::new(None),
        }
    }

@@ -641,7 +639,6 @@ impl<S: HttpSend> RemoteTable<S> {
 struct TableDescription {
    version: u64,
    schema: JsonSchema,
-    location: Option<String>,
 }

 impl<S: HttpSend> std::fmt::Display for RemoteTable<S> {
@@ -670,7 +667,6 @@ mod test_utils {
                identifier: name,
                server_version: version.map(ServerVersion).unwrap_or_default(),
                version: RwLock::new(None),
-                location: RwLock::new(None),
            }
        }
    }
@@ -1092,17 +1088,6 @@ impl<S: HttpSend> BaseTable for RemoteTable<S> {
                    body["num_partitions"] = serde_json::Value::Number(num_partitions.into());
                }
            }
-            Index::IvfRq(index) => {
-                body[INDEX_TYPE_KEY] = serde_json::Value::String("IVF_RQ".to_string());
-                body[METRIC_TYPE_KEY] =
-                    serde_json::Value::String(index.distance_type.to_string().to_lowercase());
-                if let Some(num_partitions) = index.num_partitions {
-                    body["num_partitions"] = serde_json::Value::Number(num_partitions.into());
-                }
-                if let Some(num_bits) = index.num_bits {
-                    body["num_bits"] = serde_json::Value::Number(num_bits.into());
-                }
-            }
            Index::BTree(_) => {
                body[INDEX_TYPE_KEY] = serde_json::Value::String("BTREE".to_string());
            }
@@ -1465,28 +1450,8 @@ impl<S: HttpSend> BaseTable for RemoteTable<S> {
            message: "table_definition is not supported on LanceDB cloud.".into(),
        })
    }
-    async fn uri(&self) -> Result<String> {
-        // Check if we already have the location cached
-        {
-            let location = self.location.read().await;
-            if let Some(ref loc) = *location {
-                return Ok(loc.clone());
-            }
-        }
-
-        // Fetch from server via describe
-        let description = self.describe().await?;
-        let location = description.location.ok_or_else(|| Error::NotSupported {
-            message: "Table URI not supported by the server".into(),
-        })?;
-
-        // Cache the location for future use
-        {
-            let mut cached_location = self.location.write().await;
-            *cached_location = Some(location.clone());
-        }
-
-        Ok(location)
+    fn dataset_uri(&self) -> &str {
+        "NOT_SUPPORTED"
    }

    async fn storage_options(&self) -> Option<HashMap<String, String>> {
@@ -3356,69 +3321,4 @@ mod tests {
        let result = table.drop_columns(&["old_col1", "old_col2"]).await.unwrap();
        assert_eq!(result.version, 5);
    }
-
-    #[tokio::test]
-    async fn test_uri() {
-        let table = Table::new_with_handler("my_table", |request| {
-            assert_eq!(request.method(), "POST");
-            assert_eq!(request.url().path(), "/v1/table/my_table/describe/");
-
-            http::Response::builder()
-                .status(200)
-                .body(r#"{"version": 1, "schema": {"fields": []}, "location": "s3://bucket/path/to/table"}"#)
-                .unwrap()
-        });
-
-        let uri = table.uri().await.unwrap();
-        assert_eq!(uri, "s3://bucket/path/to/table");
-    }
-
-    #[tokio::test]
-    async fn test_uri_missing_location() {
-        let table = Table::new_with_handler("my_table", |request| {
-            assert_eq!(request.method(), "POST");
-            assert_eq!(request.url().path(), "/v1/table/my_table/describe/");
-
-            // Server returns response without location field
-            http::Response::builder()
-                .status(200)
-                .body(r#"{"version": 1, "schema": {"fields": []}}"#)
-                .unwrap()
-        });
-
-        let result = table.uri().await;
-        assert!(result.is_err());
-        assert!(matches!(&result, Err(Error::NotSupported { .. })));
-    }
-
-    #[tokio::test]
-    async fn test_uri_caching() {
-        use std::sync::atomic::{AtomicUsize, Ordering};
-        use std::sync::Arc;
-
-        let call_count = Arc::new(AtomicUsize::new(0));
-        let call_count_clone = call_count.clone();
-
-        let table = Table::new_with_handler("my_table", move |request| {
-            assert_eq!(request.url().path(), "/v1/table/my_table/describe/");
-            call_count_clone.fetch_add(1, Ordering::SeqCst);
-
-            http::Response::builder()
-                .status(200)
-                .body(
-                    r#"{"version": 1, "schema": {"fields": []}, "location": "gs://bucket/table"}"#,
-                )
-                .unwrap()
-        });
-
-        // First call should fetch from server
-        let uri1 = table.uri().await.unwrap();
-        assert_eq!(uri1, "gs://bucket/table");
-        assert_eq!(call_count.load(Ordering::SeqCst), 1);
-
-        // Second call should use cached value
-        let uri2 = table.uri().await.unwrap();
-        assert_eq!(uri2, "gs://bucket/table");
-        assert_eq!(call_count.load(Ordering::SeqCst), 1); // Still 1, no new call
-    }
 }
--- a/rust/lancedb/src/table.rs
+++ b/rust/lancedb/src/table.rs
@@ -40,7 +40,7 @@ use lance_index::vector::pq::PQBuildParams;
 use lance_index::vector::sq::builder::SQBuildParams;
 use lance_index::DatasetIndexExt;
 use lance_index::IndexType;
-use lance_io::object_store::{LanceNamespaceStorageOptionsProvider, StorageOptionsAccessor};
+use lance_io::object_store::LanceNamespaceStorageOptionsProvider;
 use lance_namespace::models::{
    QueryTableRequest as NsQueryTableRequest, QueryTableRequestColumns,
    QueryTableRequestFullTextQuery, QueryTableRequestVector, StringFtsQuery,
@@ -79,11 +79,10 @@ use self::merge::MergeInsertBuilder;

 pub mod datafusion;
 pub(crate) mod dataset;
-pub mod delete;
 pub mod merge;
+
 use crate::index::waiter::wait_for_index;
 pub use chrono::Duration;
-pub use delete::DeleteResult;
 use futures::future::{join_all, Either};
 pub use lance::dataset::optimize::CompactionOptions;
 pub use lance::dataset::refs::{TagContents, Tags as LanceTags};
@@ -447,6 +446,15 @@ pub struct AddResult {
    pub version: u64,
 }

+#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize, Default)]
+pub struct DeleteResult {
+    // The commit version associated with the operation.
+    // A version of `0` indicates compatibility with legacy servers that do not return
+    /// a commit version.
+    #[serde(default)]
+    pub version: u64,
+}
+
 #[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize, Default)]
 pub struct MergeResult {
    // The commit version associated with the operation.
@@ -600,8 +608,8 @@ pub trait BaseTable: std::fmt::Display + std::fmt::Debug + Send + Sync {
    async fn list_versions(&self) -> Result<Vec<Version>>;
    /// Get the table definition.
    async fn table_definition(&self) -> Result<TableDefinition>;
-    /// Get the table URI (storage location)
-    async fn uri(&self) -> Result<String>;
+    /// Get the table URI
+    fn dataset_uri(&self) -> &str;
    /// Get the storage options used when opening this table, if any.
    async fn storage_options(&self) -> Option<HashMap<String, String>>;
    /// Poll until the columns are fully indexed. Will return Error::Timeout if the columns
@@ -1309,12 +1317,11 @@ impl Table {
        self.inner.list_indices().await
    }

-    /// Get the table URI (storage location)
+    /// Get the underlying dataset URI
    ///
-    /// Returns the full storage location of the table (e.g., S3/GCS path).
-    /// For remote tables, this fetches the location from the server via describe.
-    pub async fn uri(&self) -> Result<String> {
-        self.inner.uri().await
+    /// Warning: This is an internal API and the return value is subject to change.
+    pub fn dataset_uri(&self) -> &str {
+        self.inner.dataset_uri()
    }

    /// Get the storage options used when opening this table, if any.
@@ -1658,14 +1665,18 @@ impl NativeTable {

        // Use DatasetBuilder::from_namespace which automatically fetches location
        // and storage options from the namespace
-        let builder = DatasetBuilder::from_namespace(namespace_client.clone(), table_id)
-            .await
-            .map_err(|e| match e {
-                lance::Error::Namespace { source, .. } => Error::Runtime {
-                    message: format!("Failed to get table info from namespace: {:?}", source),
-                },
-                source => Error::Lance { source },
-            })?;
+        let builder = DatasetBuilder::from_namespace(
+            namespace_client.clone(),
+            table_id,
+            false, // Don't ignore namespace storage options
+        )
+        .await
+        .map_err(|e| match e {
+            lance::Error::Namespace { source, .. } => Error::Runtime {
+                message: format!("Failed to get table info from namespace: {:?}", source),
+            },
+            source => Error::Lance { source },
+        })?;

        let dataset = builder
            .with_read_params(params)
@@ -1869,13 +1880,7 @@ impl NativeTable {
        let store_params = params
            .store_params
            .get_or_insert_with(ObjectStoreParams::default);
-        let accessor = match store_params.storage_options().cloned() {
-            Some(options) => {
-                StorageOptionsAccessor::with_initial_and_provider(options, storage_options_provider)
-            }
-            None => StorageOptionsAccessor::with_provider(storage_options_provider),
-        };
-        store_params.storage_options_accessor = Some(Arc::new(accessor));
+        store_params.storage_options_provider = Some(storage_options_provider);

        // Patch the params if we have a write store wrapper
        let params = match write_store_wrapper.clone() {
@@ -2051,7 +2056,7 @@ impl NativeTable {
            return provided;
        }
        let suggested = suggested_num_sub_vectors(dim);
-        if num_bits.is_some_and(|num_bits| num_bits == 4) && !suggested.is_multiple_of(2) {
+        if num_bits.is_some_and(|num_bits| num_bits == 4) && suggested % 2 != 0 {
            // num_sub_vectors must be even when 4 bits are used
            suggested + 1
        } else {
@@ -2399,7 +2404,7 @@ impl NativeTable {
                    with_row_id: Some(vq.base.with_row_id),
                    bypass_vector_index: Some(!vq.use_index),
                    full_text_query,
-                    ..Default::default()
+                    version: None,
                })
            }
            AnyQuery::Query(q) => {
@@ -2461,11 +2466,18 @@ impl NativeTable {
                    columns,
                    prefilter: Some(q.prefilter),
                    offset: q.offset.map(|o| o as i32),
+                    ef: None,
+                    refine_factor: None,
+                    distance_type: None,
+                    nprobes: None,
                    vector_column: None, // No vector column for plain queries
                    with_row_id: Some(q.with_row_id),
                    bypass_vector_index: Some(true), // No vector index for plain queries
                    full_text_query,
-                    ..Default::default()
+                    version: None,
+                    fast_search: None,
+                    lower_bound: None,
+                    upper_bound: None,
                })
            }
        }
@@ -3070,8 +3082,11 @@ impl BaseTable for NativeTable {

    /// Delete rows from the table
    async fn delete(&self, predicate: &str) -> Result<DeleteResult> {
-        // Delegate to the submodule implementation
-        delete::execute_delete(self, predicate).await
+        let mut dataset = self.dataset.get_mut().await?;
+        dataset.delete(predicate).await?;
+        Ok(DeleteResult {
+            version: dataset.version().version,
+        })
    }

    async fn tags(&self) -> Result<Box<dyn Tags + '_>> {
@@ -3215,8 +3230,8 @@ impl BaseTable for NativeTable {
        Ok(results.into_iter().flatten().collect())
    }

-    async fn uri(&self) -> Result<String> {
-        Ok(self.uri.clone())
+    fn dataset_uri(&self) -> &str {
+        self.uri.as_str()
    }

    async fn storage_options(&self) -> Option<HashMap<String, String>> {
@@ -3224,7 +3239,7 @@ impl BaseTable for NativeTable {
            .get()
            .await
            .ok()
-            .and_then(|dataset| dataset.initial_storage_options().cloned())
+            .and_then(|dataset| dataset.storage_options().cloned())
    }

    async fn index_stats(&self, index_name: &str) -> Result<Option<IndexStatistics>> {
@@ -3389,6 +3404,7 @@ pub struct FragmentSummaryStats {
 #[cfg(test)]
 #[allow(deprecated)]
 mod tests {
+    use std::iter;
    use std::sync::atomic::{AtomicBool, Ordering};
    use std::sync::Arc;
    use std::time::Duration;
@@ -4005,7 +4021,7 @@ mod tests {
                schema.clone(),
                vec![
                    Arc::new(Int32Array::from_iter_values(offset..(offset + 10))),
-                    Arc::new(Int32Array::from_iter_values(std::iter::repeat_n(age, 10))),
+                    Arc::new(Int32Array::from_iter_values(iter::repeat(age).take(10))),
                ],
            )],
            schema,
@@ -5140,8 +5156,8 @@ mod tests {
            ns_request
                .columns
                .as_ref()
-                .and_then(|c| c.column_names.as_ref()),
-            Some(&vec!["id".to_string()])
+                .and_then(|c| c.column_names.clone()),
+            Some(vec!["id".to_string()])
        );
        assert_eq!(ns_request.vector_column, Some("vector".to_string()));
        assert_eq!(ns_request.distance_type, Some("l2".to_string()));
@@ -5187,8 +5203,8 @@ mod tests {
            ns_request
                .columns
                .as_ref()
-                .and_then(|c| c.column_names.as_ref()),
-            Some(&vec!["id".to_string()])
+                .and_then(|c| c.column_names.clone()),
+            Some(vec!["id".to_string()])
        );
        assert_eq!(ns_request.with_row_id, Some(true));
        assert_eq!(ns_request.bypass_vector_index, Some(true));
--- a/rust/lancedb/src/table/dataset.rs
+++ b/rust/lancedb/src/table/dataset.rs
@@ -100,7 +100,8 @@ impl DatasetRef {
                let should_checkout = match &target_ref {
                    refs::Ref::Version(_, Some(target_ver)) => version != target_ver,
                    refs::Ref::Version(_, None) => true, // No specific version, always checkout
-                    refs::Ref::Tag(_) => true,           // Always checkout for tags
+                    refs::Ref::VersionNumber(target_ver) => version != target_ver,
+                    refs::Ref::Tag(_) => true, // Always checkout for tags
                };

                if should_checkout {
--- a/rust/lancedb/src/table/delete.rs
+++ b/rust/lancedb/src/table/delete.rs
@@ -1,161 +0,0 @@
-// SPDX-License-Identifier: Apache-2.0
-// SPDX-FileCopyrightText: Copyright The LanceDB Authors
-use serde::{Deserialize, Serialize};
-
-use super::NativeTable;
-use crate::Result;
-
-#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize, Default)]
-pub struct DeleteResult {
-    // The commit version associated with the operation.
-    // A version of `0` indicates compatibility with legacy servers that do not return
-    /// a commit version.
-    #[serde(default)]
-    pub version: u64,
-}
-
-/// Internal implementation of the delete logic
-///
-/// This logic was moved from NativeTable::delete to keep table.rs clean.
-pub(crate) async fn execute_delete(table: &NativeTable, predicate: &str) -> Result<DeleteResult> {
-    // We access the dataset from the table. Since this is in the same module hierarchy (super),
-    // and 'dataset' is pub(crate), we can access it.
-    let mut dataset = table.dataset.get_mut().await?;
-
-    // Perform the actual delete on the Lance dataset
-    dataset.delete(predicate).await?;
-
-    // Return the result with the new version
-    Ok(DeleteResult {
-        version: dataset.version().version,
-    })
-}
-
-#[cfg(test)]
-mod tests {
-    use crate::connect;
-    use arrow_array::{record_batch, Int32Array, RecordBatch, RecordBatchIterator};
-    use arrow_schema::{DataType, Field, Schema};
-    use std::sync::Arc;
-
-    use crate::query::ExecutableQuery;
-    use futures::TryStreamExt;
-    #[tokio::test]
-    async fn test_delete_simple() {
-        let conn = connect("memory://").execute().await.unwrap();
-
-        // 1. Create a table with values 0 to 9
-        let schema = Arc::new(Schema::new(vec![Field::new("i", DataType::Int32, false)]));
-        let batch = RecordBatch::try_new(
-            schema.clone(),
-            vec![Arc::new(Int32Array::from_iter_values(0..10))],
-        )
-        .unwrap();
-
-        let table = conn
-            .create_table(
-                "test_delete",
-                RecordBatchIterator::new(vec![Ok(batch)], schema),
-            )
-            .execute()
-            .await
-            .unwrap();
-
-        // 2. Verify initial state
-        assert_eq!(table.count_rows(None).await.unwrap(), 10);
-
-        // 3. Execute Delete (removes values > 5)
-        table.delete("i > 5").await.unwrap();
-
-        // 4. Verify results
-        assert_eq!(table.count_rows(None).await.unwrap(), 6); // 0, 1, 2, 3, 4, 5 remain
-
-        // 5. Verify specific data consistency
-        let batches = table
-            .query()
-            .execute()
-            .await
-            .unwrap()
-            .try_collect::<Vec<_>>()
-            .await
-            .unwrap();
-        let batch = &batches[0];
-        let array = batch
-            .column(0)
-            .as_any()
-            .downcast_ref::<Int32Array>()
-            .unwrap();
-
-        // Ensure no value > 5 exists
-        for val in array.iter() {
-            assert!(val.unwrap() <= 5);
-        }
-    }
-    #[tokio::test]
-    async fn rows_removed_schema_same() {
-        let conn = connect("memory://").execute().await.unwrap();
-        let batch = record_batch!(
-            ("id", Int32, [1, 2, 3, 4, 5]),
-            ("name", Utf8, ["a", "b", "c", "d", "e"])
-        )
-        .unwrap();
-        let original_schema = batch.schema();
-
-        let table = conn
-            .create_table(
-                "test_delete_all",
-                RecordBatchIterator::new(vec![Ok(batch)], original_schema.clone()),
-            )
-            .execute()
-            .await
-            .unwrap();
-
-        table.delete("true").await.unwrap();
-
-        assert_eq!(table.count_rows(None).await.unwrap(), 0);
-
-        let current_schema = table.schema().await.unwrap();
-        //check if the original schema is the same as current
-        assert_eq!(current_schema, original_schema);
-    }
-
-    #[tokio::test]
-    async fn test_delete_false_increments_version() {
-        let conn = connect("memory://").execute().await.unwrap();
-
-        // Create a table with 5 rows
-        let batch = record_batch!(("id", Int32, [1, 2, 3, 4, 5])).unwrap();
-
-        let schema = batch.schema();
-
-        let table = conn
-            .create_table(
-                "test_delete_noop",
-                RecordBatchIterator::new(vec![Ok(batch)], schema),
-            )
-            .execute()
-            .await
-            .unwrap();
-
-        // Capture the initial state (Rows = 5, Version = 1)
-        let initial_rows = table.count_rows(None).await.unwrap();
-        let initial_version = table.version().await.unwrap();
-
-        assert_eq!(initial_rows, 5);
-        table.delete("false").await.unwrap();
-
-        // Rows should still be 5
-        let current_rows = table.count_rows(None).await.unwrap();
-        assert_eq!(
-            current_rows, initial_rows,
-            "Data should not change when predicate is false"
-        );
-
-        // version check
-        let current_version = table.version().await.unwrap();
-        assert!(
-            current_version > initial_version,
-            "Table version must increment after delete operation"
-        );
-    }
-}
--- a/rust/lancedb/src/test_utils/connection.rs
+++ b/rust/lancedb/src/test_utils/connection.rs
@@ -5,19 +5,16 @@

 use regex::Regex;
 use std::env;
-use std::process::Stdio;
-use tokio::io::{AsyncBufReadExt, BufReader};
-use tokio::process::{Child, ChildStdout, Command};
-use tokio::sync::mpsc;
+use std::io::{BufRead, BufReader};
+use std::process::{Child, ChildStdout, Command, Stdio};

 use crate::{connect, Connection};
-use anyhow::{anyhow, bail, Result};
+use anyhow::{bail, Result};
 use tempfile::{tempdir, TempDir};

 pub struct TestConnection {
    pub uri: String,
    pub connection: Connection,
-    pub is_remote: bool,
    _temp_dir: Option<TempDir>,
    _process: Option<TestProcess>,
 }
@@ -40,56 +37,6 @@ pub async fn new_test_connection() -> Result<TestConnection> {
    }
 }

-async fn spawn_stdout_reader(
-    mut stdout: BufReader<ChildStdout>,
-    port_sender: mpsc::Sender<anyhow::Result<String>>,
-) -> tokio::task::JoinHandle<()> {
-    let print_stdout = env::var("PRINT_LANCEDB_TEST_CONNECTION_SCRIPT_OUTPUT").is_ok();
-    tokio::spawn(async move {
-        let mut line = String::new();
-        let re = Regex::new(r"Query node now listening on 0.0.0.0:(.*)").unwrap();
-        loop {
-            line.clear();
-            let result = stdout.read_line(&mut line).await;
-            if let Err(err) = result {
-                port_sender
-                    .send(Err(anyhow!(
-                        "error while reading from process output: {}",
-                        err
-                    )))
-                    .await
-                    .unwrap();
-                return;
-            } else if result.unwrap() == 0 {
-                port_sender
-                    .send(Err(anyhow!(
-                        " hit EOF before reading port from process output."
-                    )))
-                    .await
-                    .unwrap();
-                return;
-            }
-            if re.is_match(&line) {
-                let caps = re.captures(&line).unwrap();
-                port_sender.send(Ok(caps[1].to_string())).await.unwrap();
-                break;
-            }
-        }
-        loop {
-            line.clear();
-            match stdout.read_line(&mut line).await {
-                Err(_) => return,
-                Ok(0) => return,
-                Ok(_size) => {
-                    if print_stdout {
-                        print!("{}", line);
-                    }
-                }
-            }
-        }
-    })
-}
-
 async fn new_remote_connection(script_path: &str) -> Result<TestConnection> {
    let temp_dir = tempdir()?;
    let data_path = temp_dir.path().to_str().unwrap().to_string();
@@ -110,25 +57,38 @@ async fn new_remote_connection(script_path: &str) -> Result<TestConnection> {
        child: child_result.unwrap(),
    };
    let stdout = BufReader::new(process.child.stdout.take().unwrap());
-    let (port_sender, mut port_receiver) = mpsc::channel(5);
-    let _reader = spawn_stdout_reader(stdout, port_sender).await;
-    let port = match port_receiver.recv().await {
-        None => bail!("Unable to determine the port number used by the phalanx process we spawned, because the reader thread was closed too soon."),
-        Some(Err(err)) => bail!("Unable to determine the port number used by the phalanx process we spawned, because of an error, {}", err),
-        Some(Ok(port)) => port,
-    };
+    let port = read_process_port(stdout)?;
    let uri = "db://test";
    let host_override = format!("http://localhost:{}", port);
    let connection = create_new_connection(uri, &host_override).await?;
    Ok(TestConnection {
        uri: uri.to_string(),
        connection,
-        is_remote: true,
        _temp_dir: Some(temp_dir),
        _process: Some(process),
    })
 }

+fn read_process_port(mut stdout: BufReader<ChildStdout>) -> Result<String> {
+    let mut line = String::new();
+    let re = Regex::new(r"Query node now listening on 0.0.0.0:(.*)").unwrap();
+    loop {
+        let result = stdout.read_line(&mut line);
+        if let Err(err) = result {
+            bail!(format!(
+                "read_process_port: error while reading from process output: {}",
+                err
+            ));
+        } else if result.unwrap() == 0 {
+            bail!("read_process_port: hit EOF before reading port from process output.");
+        }
+        if re.is_match(&line) {
+            let caps = re.captures(&line).unwrap();
+            return Ok(caps[1].to_string());
+        }
+    }
+}
+
 #[cfg(feature = "remote")]
 async fn create_new_connection(uri: &str, host_override: &str) -> crate::error::Result<Connection> {
    connect(uri)
@@ -154,7 +114,6 @@ async fn new_local_connection() -> Result<TestConnection> {
    Ok(TestConnection {
        uri: uri.to_string(),
        connection,
-        is_remote: false,
        _temp_dir: Some(temp_dir),
        _process: None,
    })
--- a/rust/lancedb/tests/embedding_registry_test.rs
+++ b/rust/lancedb/tests/embedding_registry_test.rs
@@ -4,6 +4,7 @@
 use std::{
    borrow::Cow,
    collections::{HashMap, HashSet},
+    iter::repeat,
    sync::Arc,
 };

@@ -267,10 +268,9 @@ fn create_some_records() -> Result<impl IntoArrow> {
            schema.clone(),
            vec![
                Arc::new(Int32Array::from_iter_values(0..TOTAL as i32)),
-                Arc::new(StringArray::from_iter(std::iter::repeat_n(
-                    Some("hello world".to_string()),
-                    TOTAL,
-                ))),
+                Arc::new(StringArray::from_iter(
+                    repeat(Some("hello world".to_string())).take(TOTAL),
+                )),
            ],
        )
        .unwrap()]
--- a/rust/lancedb/tests/embeddings_parallel_test.rs
+++ b/rust/lancedb/tests/embeddings_parallel_test.rs
@@ -1,253 +0,0 @@
-// SPDX-License-Identifier: Apache-2.0
-// SPDX-FileCopyrightText: Copyright The LanceDB Authors
-
-use std::{
-    borrow::Cow,
-    sync::{
-        atomic::{AtomicUsize, Ordering},
-        Arc,
-    },
-    time::Duration,
-};
-
-use arrow::buffer::NullBuffer;
-use arrow_array::{
-    Array, FixedSizeListArray, Float32Array, RecordBatch, RecordBatchIterator, StringArray,
-};
-use arrow_schema::{DataType, Field, Schema};
-use lancedb::{
-    embeddings::{EmbeddingDefinition, EmbeddingFunction, MaybeEmbedded, WithEmbeddings},
-    Error, Result,
-};
-
-#[derive(Debug)]
-struct SlowMockEmbed {
-    name: String,
-    dim: usize,
-    delay_ms: u64,
-    call_count: Arc<AtomicUsize>,
-}
-
-impl SlowMockEmbed {
-    pub fn new(name: String, dim: usize, delay_ms: u64) -> Self {
-        Self {
-            name,
-            dim,
-            delay_ms,
-            call_count: Arc::new(AtomicUsize::new(0)),
-        }
-    }
-
-    pub fn get_call_count(&self) -> usize {
-        self.call_count.load(Ordering::SeqCst)
-    }
-}
-
-impl EmbeddingFunction for SlowMockEmbed {
-    fn name(&self) -> &str {
-        &self.name
-    }
-
-    fn source_type(&self) -> Result<Cow<'_, DataType>> {
-        Ok(Cow::Owned(DataType::Utf8))
-    }
-
-    fn dest_type(&self) -> Result<Cow<'_, DataType>> {
-        Ok(Cow::Owned(DataType::new_fixed_size_list(
-            DataType::Float32,
-            self.dim as _,
-            true,
-        )))
-    }
-
-    fn compute_source_embeddings(&self, source: Arc<dyn Array>) -> Result<Arc<dyn Array>> {
-        // Simulate slow embedding computation
-        std::thread::sleep(Duration::from_millis(self.delay_ms));
-        self.call_count.fetch_add(1, Ordering::SeqCst);
-
-        let len = source.len();
-        let inner = Arc::new(Float32Array::from(vec![Some(1.0); len * self.dim]));
-        let field = Field::new("item", inner.data_type().clone(), false);
-        let arr = FixedSizeListArray::new(
-            Arc::new(field),
-            self.dim as _,
-            inner,
-            Some(NullBuffer::new_valid(len)),
-        );
-
-        Ok(Arc::new(arr))
-    }
-
-    fn compute_query_embeddings(&self, _input: Arc<dyn Array>) -> Result<Arc<dyn Array>> {
-        unimplemented!()
-    }
-}
-
-fn create_test_batch() -> Result<RecordBatch> {
-    let schema = Arc::new(Schema::new(vec![Field::new("text", DataType::Utf8, false)]));
-    let text = StringArray::from(vec!["hello", "world"]);
-    RecordBatch::try_new(schema, vec![Arc::new(text)]).map_err(|e| Error::Runtime {
-        message: format!("Failed to create test batch: {}", e),
-    })
-}
-
-#[test]
-fn test_single_embedding_fast_path() {
-    // Single embedding should execute without spawning threads
-    let batch = create_test_batch().unwrap();
-    let schema = batch.schema();
-
-    let embed = Arc::new(SlowMockEmbed::new("test".to_string(), 2, 10));
-    let embedding_def = EmbeddingDefinition::new("text", "test", Some("embedding"));
-
-    let reader = RecordBatchIterator::new(vec![Ok(batch)], schema);
-    let embeddings = vec![(embedding_def, embed.clone() as Arc<dyn EmbeddingFunction>)];
-    let mut with_embeddings = WithEmbeddings::new(reader, embeddings);
-
-    let result = with_embeddings.next().unwrap().unwrap();
-    assert!(result.column_by_name("embedding").is_some());
-    assert_eq!(embed.get_call_count(), 1);
-}
-
-#[test]
-fn test_multiple_embeddings_parallel() {
-    // Multiple embeddings should execute in parallel
-    let batch = create_test_batch().unwrap();
-    let schema = batch.schema();
-
-    let embed1 = Arc::new(SlowMockEmbed::new("embed1".to_string(), 2, 100));
-    let embed2 = Arc::new(SlowMockEmbed::new("embed2".to_string(), 3, 100));
-    let embed3 = Arc::new(SlowMockEmbed::new("embed3".to_string(), 4, 100));
-
-    let def1 = EmbeddingDefinition::new("text", "embed1", Some("emb1"));
-    let def2 = EmbeddingDefinition::new("text", "embed2", Some("emb2"));
-    let def3 = EmbeddingDefinition::new("text", "embed3", Some("emb3"));
-
-    let reader = RecordBatchIterator::new(vec![Ok(batch)], schema);
-    let embeddings = vec![
-        (def1, embed1.clone() as Arc<dyn EmbeddingFunction>),
-        (def2, embed2.clone() as Arc<dyn EmbeddingFunction>),
-        (def3, embed3.clone() as Arc<dyn EmbeddingFunction>),
-    ];
-    let mut with_embeddings = WithEmbeddings::new(reader, embeddings);
-
-    let result = with_embeddings.next().unwrap().unwrap();
-
-    // Verify all embedding columns are present
-    assert!(result.column_by_name("emb1").is_some());
-    assert!(result.column_by_name("emb2").is_some());
-    assert!(result.column_by_name("emb3").is_some());
-
-    // Verify all embeddings were computed
-    assert_eq!(embed1.get_call_count(), 1);
-    assert_eq!(embed2.get_call_count(), 1);
-    assert_eq!(embed3.get_call_count(), 1);
-}
-
-#[test]
-fn test_embedding_column_order_preserved() {
-    // Verify that embedding columns are added in the same order as definitions
-    let batch = create_test_batch().unwrap();
-    let schema = batch.schema();
-
-    let embed1 = Arc::new(SlowMockEmbed::new("embed1".to_string(), 2, 10));
-    let embed2 = Arc::new(SlowMockEmbed::new("embed2".to_string(), 3, 10));
-    let embed3 = Arc::new(SlowMockEmbed::new("embed3".to_string(), 4, 10));
-
-    let def1 = EmbeddingDefinition::new("text", "embed1", Some("first"));
-    let def2 = EmbeddingDefinition::new("text", "embed2", Some("second"));
-    let def3 = EmbeddingDefinition::new("text", "embed3", Some("third"));
-
-    let reader = RecordBatchIterator::new(vec![Ok(batch)], schema);
-    let embeddings = vec![
-        (def1, embed1 as Arc<dyn EmbeddingFunction>),
-        (def2, embed2 as Arc<dyn EmbeddingFunction>),
-        (def3, embed3 as Arc<dyn EmbeddingFunction>),
-    ];
-    let mut with_embeddings = WithEmbeddings::new(reader, embeddings);
-
-    let result = with_embeddings.next().unwrap().unwrap();
-    let result_schema = result.schema();
-
-    // Original column is first
-    assert_eq!(result_schema.field(0).name(), "text");
-    // Embedding columns follow in order
-    assert_eq!(result_schema.field(1).name(), "first");
-    assert_eq!(result_schema.field(2).name(), "second");
-    assert_eq!(result_schema.field(3).name(), "third");
-}
-
-#[test]
-fn test_embedding_error_propagation() {
-    // Test that errors from embedding computation are properly propagated
-    #[derive(Debug)]
-    struct FailingEmbed {
-        name: String,
-    }
-
-    impl EmbeddingFunction for FailingEmbed {
-        fn name(&self) -> &str {
-            &self.name
-        }
-
-        fn source_type(&self) -> Result<Cow<'_, DataType>> {
-            Ok(Cow::Owned(DataType::Utf8))
-        }
-
-        fn dest_type(&self) -> Result<Cow<'_, DataType>> {
-            Ok(Cow::Owned(DataType::new_fixed_size_list(
-                DataType::Float32,
-                2,
-                true,
-            )))
-        }
-
-        fn compute_source_embeddings(&self, _source: Arc<dyn Array>) -> Result<Arc<dyn Array>> {
-            Err(Error::Runtime {
-                message: "Intentional failure".to_string(),
-            })
-        }
-
-        fn compute_query_embeddings(&self, _input: Arc<dyn Array>) -> Result<Arc<dyn Array>> {
-            unimplemented!()
-        }
-    }
-
-    let batch = create_test_batch().unwrap();
-    let schema = batch.schema();
-
-    let embed = Arc::new(FailingEmbed {
-        name: "failing".to_string(),
-    });
-    let def = EmbeddingDefinition::new("text", "failing", Some("emb"));
-
-    let reader = RecordBatchIterator::new(vec![Ok(batch)], schema);
-    let embeddings = vec![(def, embed as Arc<dyn EmbeddingFunction>)];
-    let mut with_embeddings = WithEmbeddings::new(reader, embeddings);
-
-    let result = with_embeddings.next().unwrap();
-    assert!(result.is_err());
-    let err_msg = format!("{}", result.err().unwrap());
-    assert!(err_msg.contains("Intentional failure"));
-}
-
-#[test]
-fn test_maybe_embedded_with_no_embeddings() {
-    // Test that MaybeEmbedded::No variant works correctly
-    let batch = create_test_batch().unwrap();
-    let schema = batch.schema();
-
-    let reader = RecordBatchIterator::new(vec![Ok(batch.clone())], schema.clone());
-    let table_def = lancedb::table::TableDefinition {
-        schema: schema.clone(),
-        column_definitions: vec![lancedb::table::ColumnDefinition {
-            kind: lancedb::table::ColumnKind::Physical,
-        }],
-    };
-
-    let mut maybe_embedded = MaybeEmbedded::try_new(reader, table_def, None).unwrap();
-
-    let result = maybe_embedded.next().unwrap().unwrap();
-    assert_eq!(result.num_columns(), 1);
-    assert_eq!(result.column(0).as_ref(), batch.column(0).as_ref());
-}
Author	SHA1	Message	Date
BubbleCal	929c683a6e	Handle version number refs	2025-12-22 16:53:16 +08:00
lancedb automation	e2794d1a29	chore: update lance dependency to v2.0.0-beta.3	2025-12-19 22:04:10 +00:00