ci: Auto fix CI if bump failed

.bumpversion.toml

@@ -1,5 +1,5 @@
 [tool.bumpversion]
-current_version = "0.23.1"
+current_version = "0.23.1-beta.1"
 parse = """(?x)
     (?P<major>0|[1-9]\\d*)\\.
     (?P<minor>0|[1-9]\\d*)\\.

.github/workflows/codex-autofix-ci.yml

@@ -0,0 +1,297 @@
+name: Codex Autofix CI
+
+on:
+  check_suite:
+    types:
+      - completed
+
+permissions:
+  contents: write
+  pull-requests: write
+  actions: read
+
+concurrency:
+  group: codex-autofix-${{ github.event.check_suite.head_branch }}
+  cancel-in-progress: false
+
+jobs:
+  autofix:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Resolve PR and failing required checks
+        id: ctx
+        env:
+          GH_TOKEN: ${{ secrets.ROBOT_TOKEN }}
+          REPO: ${{ github.repository }}
+          SHA: ${{ github.event.check_suite.head_sha }}
+          HEAD_BRANCH: ${{ github.event.check_suite.head_branch }}
+          MAX_ATTEMPTS: "3"
+        run: |
+          set -euo pipefail
+
+          echo "Repository: $REPO"
+          echo "head_branch: $HEAD_BRANCH"
+          echo "head_sha: $SHA"
+
+          if [[ "$HEAD_BRANCH" != codex/update-lance-* ]]; then
+            echo "Skip: branch '$HEAD_BRANCH' does not match codex/update-lance-*"
+            echo "needs_fix=false" >> "$GITHUB_OUTPUT"
+            exit 0
+          fi
+
+          prs_json="$(gh api -H "Accept: application/vnd.github+json" "repos/$REPO/commits/$SHA/pulls")"
+          pr_json="$(echo "$prs_json" | jq -c '[.[] | select(.state=="open")] | .[0]')"
+          if [[ -z "$pr_json" || "$pr_json" == "null" ]]; then
+            echo "Skip: no open PR found for sha $SHA"
+            echo "needs_fix=false" >> "$GITHUB_OUTPUT"
+            exit 0
+          fi
+
+          pr_number="$(echo "$pr_json" | jq -r '.number')"
+          head_ref="$(echo "$pr_json" | jq -r '.head.ref')"
+          head_repo="$(echo "$pr_json" | jq -r '.head.repo.full_name')"
+          pr_head_sha="$(echo "$pr_json" | jq -r '.head.sha')"
+
+          if [[ "$head_repo" != "$REPO" ]]; then
+            echo "Skip: cross-repo PR ($head_repo != $REPO)"
+            echo "needs_fix=false" >> "$GITHUB_OUTPUT"
+            exit 0
+          fi
+
+          if [[ "$pr_head_sha" != "$SHA" ]]; then
+            echo "Skip: stale check_suite event (pr head sha $pr_head_sha != event sha $SHA)"
+            echo "needs_fix=false" >> "$GITHUB_OUTPUT"
+            exit 0
+          fi
+
+          set +e
+          checks_json="$(gh pr checks "$pr_number" --required --repo "$REPO" --json name,state,bucket,link,workflow)"
+          checks_rc=$?
+          set -e
+
+          if [[ "$checks_rc" -eq 8 ]]; then
+            echo "Skip: required checks still pending"
+            echo "needs_fix=false" >> "$GITHUB_OUTPUT"
+            exit 0
+          fi
+
+          if [[ "$checks_rc" -ne 0 ]]; then
+            echo "Skip: failed to query required checks (exit=$checks_rc)"
+            echo "needs_fix=false" >> "$GITHUB_OUTPUT"
+            exit 0
+          fi
+
+          fail_count="$(echo "$checks_json" | jq '[.[] | select(.bucket=="fail")] | length')"
+          if [[ "$fail_count" -eq 0 ]]; then
+            echo "Skip: no failing required checks"
+            echo "needs_fix=false" >> "$GITHUB_OUTPUT"
+            exit 0
+          fi
+
+          comments_json="$(gh api "repos/$REPO/issues/$pr_number/comments" --paginate)"
+          stopped_count="$(echo "$comments_json" | jq '[.[].body | select(test("<!-- codex-autofix stopped -->"))] | length')"
+          if [[ "$stopped_count" -gt 0 ]]; then
+            echo "Skip: codex-autofix already stopped for this PR"
+            echo "needs_fix=false" >> "$GITHUB_OUTPUT"
+            exit 0
+          fi
+
+          prior_attempts="$(echo "$comments_json" | jq '[.[].body | select(test("<!-- codex-autofix attempt:"))] | length')"
+          attempt="$((prior_attempts + 1))"
+
+          if [[ "$attempt" -gt "$MAX_ATTEMPTS" ]]; then
+            run_url="${GITHUB_SERVER_URL}/${REPO}/actions/runs/${GITHUB_RUN_ID}"
+            comment_file="$(mktemp /tmp/codex-autofix-comment.XXXXXX.md)"
+            {
+              printf '%s\n' '<!-- codex-autofix stopped -->'
+              printf '<!-- codex-autofix attempt: %s -->\n' "$attempt"
+              printf 'Codex autofix stopped: reached max attempts (%s).\n\n' "$MAX_ATTEMPTS"
+              printf -- '- Run: %s\n' "$run_url"
+              printf -- '- head_sha: `%s`\n' "$SHA"
+              printf -- '- head_ref: `%s`\n' "$head_ref"
+            } >"$comment_file"
+            gh pr comment "$pr_number" --repo "$REPO" --body-file "$comment_file"
+            echo "needs_fix=false" >> "$GITHUB_OUTPUT"
+            exit 0
+          fi
+
+          evidence_file="$(mktemp /tmp/codex-autofix-evidence.XXXXXX.txt)"
+          run_url="${GITHUB_SERVER_URL}/${REPO}/actions/runs/${GITHUB_RUN_ID}"
+
+          {
+            echo "PR: #$pr_number"
+            echo "head_ref: $head_ref"
+            echo "head_sha: $SHA"
+            echo "Run: $run_url"
+            echo ""
+            echo "Failing required checks:"
+            echo "$checks_json" | jq -r '.[] | select(.bucket=="fail") | "- \(.name) (\(.workflow // "unknown")): \(.link // "n/a")"'
+            echo ""
+          } > "$evidence_file"
+
+          while IFS= read -r row; do
+            name="$(echo "$row" | jq -r '.name')"
+            link="$(echo "$row" | jq -r '.link // empty')"
+            workflow="$(echo "$row" | jq -r '.workflow // "unknown"')"
+
+            {
+              echo "================================================================================"
+              echo "CHECK: $name"
+              echo "WORKFLOW: $workflow"
+              echo "LINK: ${link:-n/a}"
+            } >> "$evidence_file"
+
+            run_id=""
+            if [[ -n "$link" ]]; then
+              run_id="$(echo "$link" | sed -n 's#.*actions/runs/\\([0-9][0-9]*\\).*#\\1#p' | head -n 1 || true)"
+            fi
+
+            if [[ -z "$run_id" ]]; then
+              echo "LOGS: unavailable (no run id found in link)" >> "$evidence_file"
+              echo "" >> "$evidence_file"
+              continue
+            fi
+
+            echo "LOGS: gh run view $run_id --log-failed (tail -c 20000)" >> "$evidence_file"
+            set +e
+            gh run view "$run_id" --repo "$REPO" --log-failed 2>/dev/null | tail -c 20000 >> "$evidence_file"
+            echo "" >> "$evidence_file"
+            set -e
+          done < <(echo "$checks_json" | jq -c '.[] | select(.bucket=="fail")')
+
+          comment_file="$(mktemp /tmp/codex-autofix-comment.XXXXXX.md)"
+          {
+            printf '<!-- codex-autofix attempt: %s -->\n' "$attempt"
+            printf 'Starting Codex autofix attempt %s.\n\n' "$attempt"
+            printf -- '- Run: %s\n' "$run_url"
+            printf -- '- head_sha: `%s`\n' "$SHA"
+            printf -- '- head_ref: `%s`\n' "$head_ref"
+            printf -- '- Failing required checks: %s\n' "$fail_count"
+          } >"$comment_file"
+          gh pr comment "$pr_number" --repo "$REPO" --body-file "$comment_file"
+
+          {
+            echo "needs_fix=true"
+            echo "pr_number=$pr_number"
+            echo "head_ref=$head_ref"
+            echo "attempt=$attempt"
+            echo "evidence_file=$evidence_file"
+          } >> "$GITHUB_OUTPUT"
+
+      - name: Checkout PR branch
+        if: steps.ctx.outputs.needs_fix == 'true'
+        uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+          ref: ${{ steps.ctx.outputs.head_ref }}
+          token: ${{ secrets.ROBOT_TOKEN }}
+          persist-credentials: true
+
+      - name: Configure git
+        if: steps.ctx.outputs.needs_fix == 'true'
+        run: |
+          git config user.name "lancedb automation"
+          git config user.email "robot@lancedb.com"
+
+      - name: Set up Node.js
+        if: steps.ctx.outputs.needs_fix == 'true'
+        uses: actions/setup-node@v4
+        with:
+          node-version: 20
+
+      - name: Install Codex CLI
+        if: steps.ctx.outputs.needs_fix == 'true'
+        run: npm install -g @openai/codex
+
+      - name: Install Rust toolchain
+        if: steps.ctx.outputs.needs_fix == 'true'
+        uses: dtolnay/rust-toolchain@stable
+        with:
+          toolchain: stable
+          components: clippy, rustfmt
+
+      - name: Install system dependencies
+        if: steps.ctx.outputs.needs_fix == 'true'
+        run: |
+          sudo apt-get update
+          sudo apt-get install -y protobuf-compiler libssl-dev
+
+      - name: Run Codex to fix failing CI
+        if: steps.ctx.outputs.needs_fix == 'true'
+        env:
+          PR_NUMBER: ${{ steps.ctx.outputs.pr_number }}
+          HEAD_REF: ${{ steps.ctx.outputs.head_ref }}
+          ATTEMPT: ${{ steps.ctx.outputs.attempt }}
+          EVIDENCE_FILE: ${{ steps.ctx.outputs.evidence_file }}
+          GITHUB_TOKEN: ${{ secrets.ROBOT_TOKEN }}
+          GH_TOKEN: ${{ secrets.ROBOT_TOKEN }}
+          OPENAI_API_KEY: ${{ secrets.CODEX_TOKEN }}
+        run: |
+          set -euo pipefail
+
+          prompt_file="/tmp/codex-prompt.txt"
+          {
+            printf 'You are running inside the lancedb repository on a GitHub Actions runner.\n'
+            printf 'Your task is to fix failing required CI checks for pull request #%s on branch %s.\n\n' "$PR_NUMBER" "$HEAD_REF"
+            printf 'Goal:\n'
+            printf -- '- Make the smallest change necessary so that all required checks pass.\n\n'
+            printf 'Evidence (generated from GitHub checks and logs):\n'
+            printf '---\n'
+            cat "${EVIDENCE_FILE}"
+            printf '\n---\n\n'
+            printf 'Follow these steps exactly:\n'
+            printf '1. Identify the root cause from the evidence and repository state.\n'
+            printf '2. Make changes to fix the failures.\n'
+            printf '3. Run the relevant local commands that correspond to the failing checks until they succeed.\n'
+            printf '   If unsure, start with:\n'
+            printf '   - cargo fmt --all -- --check\n'
+            printf '   - cargo clippy --profile ci --workspace --tests --all-features -- -D warnings\n'
+            printf '4. Ensure the repository is clean except for intentional changes (git status --short, git diff).\n'
+            printf '5. Create a commit with message "fix: codex autofix (attempt %s)".\n' "$ATTEMPT"
+            printf '6. Push to origin branch "%s" (use --force-with-lease only if required).\n' "$HEAD_REF"
+            printf '7. Print the commands you ran and their results, plus git status --short and git log -1 --oneline.\n\n'
+            printf 'Constraints:\n'
+            printf -- '- Do not create a new pull request.\n'
+            printf -- '- Do not merge.\n'
+            printf -- '- Avoid modifying GitHub workflow files unless strictly required to fix CI for this PR.\n'
+          } >"$prompt_file"
+
+          printenv OPENAI_API_KEY | codex login --with-api-key
+          codex --config shell_environment_policy.ignore_default_excludes=true exec --dangerously-bypass-approvals-and-sandbox "$(cat "$prompt_file")"
+
+      - name: Ensure branch is pushed
+        if: steps.ctx.outputs.needs_fix == 'true'
+        env:
+          HEAD_REF: ${{ steps.ctx.outputs.head_ref }}
+        run: |
+          set -euo pipefail
+          if git diff --quiet && git diff --cached --quiet; then
+            echo "Working tree clean."
+          else
+            git add -A
+            git commit -m "fix: codex autofix (post-run)" || true
+          fi
+          git push origin "HEAD:${HEAD_REF}" --force-with-lease
+
+      - name: Comment result
+        if: steps.ctx.outputs.needs_fix == 'true'
+        env:
+          GH_TOKEN: ${{ secrets.ROBOT_TOKEN }}
+          REPO: ${{ github.repository }}
+          PR_NUMBER: ${{ steps.ctx.outputs.pr_number }}
+          ATTEMPT: ${{ steps.ctx.outputs.attempt }}
+        run: |
+          set -euo pipefail
+          run_url="${GITHUB_SERVER_URL}/${REPO}/actions/runs/${GITHUB_RUN_ID}"
+          sha="$(git rev-parse HEAD)"
+          summary="$(git log -1 --oneline || true)"
+          status="$(git status --short || true)"
+          comment_file="$(mktemp /tmp/codex-autofix-comment.XXXXXX.md)"
+          {
+            printf 'Codex autofix attempt %s finished.\n\n' "$ATTEMPT"
+            printf -- '- Run: %s\n' "$run_url"
+            printf -- '- head_sha: `%s`\n' "$sha"
+            printf -- '- Last commit: %s\n\n' "$summary"
+            printf '```\n%s\n```\n' "$status"
+          } >"$comment_file"
+          gh pr comment "$PR_NUMBER" --repo "$REPO" --body-file "$comment_file"

Cargo.toml

@@ -15,39 +15,39 @@ categories = ["database-implementations"]
 rust-version = "1.78.0"
 
 [workspace.dependencies]
-lance = { "version" = "=2.0.0-beta.7", default-features = false, "tag" = "v2.0.0-beta.7", "git" = "https://github.com/lance-format/lance.git" }
-lance-core = { "version" = "=2.0.0-beta.7", "tag" = "v2.0.0-beta.7", "git" = "https://github.com/lance-format/lance.git" }
-lance-datagen = { "version" = "=2.0.0-beta.7", "tag" = "v2.0.0-beta.7", "git" = "https://github.com/lance-format/lance.git" }
-lance-file = { "version" = "=2.0.0-beta.7", "tag" = "v2.0.0-beta.7", "git" = "https://github.com/lance-format/lance.git" }
-lance-io = { "version" = "=2.0.0-beta.7", default-features = false, "tag" = "v2.0.0-beta.7", "git" = "https://github.com/lance-format/lance.git" }
-lance-index = { "version" = "=2.0.0-beta.7", "tag" = "v2.0.0-beta.7", "git" = "https://github.com/lance-format/lance.git" }
-lance-linalg = { "version" = "=2.0.0-beta.7", "tag" = "v2.0.0-beta.7", "git" = "https://github.com/lance-format/lance.git" }
-lance-namespace = { "version" = "=2.0.0-beta.7", "tag" = "v2.0.0-beta.7", "git" = "https://github.com/lance-format/lance.git" }
-lance-namespace-impls = { "version" = "=2.0.0-beta.7", default-features = false, "tag" = "v2.0.0-beta.7", "git" = "https://github.com/lance-format/lance.git" }
-lance-table = { "version" = "=2.0.0-beta.7", "tag" = "v2.0.0-beta.7", "git" = "https://github.com/lance-format/lance.git" }
-lance-testing = { "version" = "=2.0.0-beta.7", "tag" = "v2.0.0-beta.7", "git" = "https://github.com/lance-format/lance.git" }
-lance-datafusion = { "version" = "=2.0.0-beta.7", "tag" = "v2.0.0-beta.7", "git" = "https://github.com/lance-format/lance.git" }
-lance-encoding = { "version" = "=2.0.0-beta.7", "tag" = "v2.0.0-beta.7", "git" = "https://github.com/lance-format/lance.git" }
-lance-arrow = { "version" = "=2.0.0-beta.7", "tag" = "v2.0.0-beta.7", "git" = "https://github.com/lance-format/lance.git" }
+lance = { "version" = "=1.0.1-beta.1", default-features = false, "tag" = "v1.0.1-beta.1", "git" = "https://github.com/lance-format/lance.git" }
+lance-core = { "version" = "=1.0.1-beta.1", "tag" = "v1.0.1-beta.1", "git" = "https://github.com/lance-format/lance.git" }
+lance-datagen = { "version" = "=1.0.1-beta.1", "tag" = "v1.0.1-beta.1", "git" = "https://github.com/lance-format/lance.git" }
+lance-file = { "version" = "=1.0.1-beta.1", "tag" = "v1.0.1-beta.1", "git" = "https://github.com/lance-format/lance.git" }
+lance-io = { "version" = "=1.0.1-beta.1", default-features = false, "tag" = "v1.0.1-beta.1", "git" = "https://github.com/lance-format/lance.git" }
+lance-index = { "version" = "=1.0.1-beta.1", "tag" = "v1.0.1-beta.1", "git" = "https://github.com/lance-format/lance.git" }
+lance-linalg = { "version" = "=1.0.1-beta.1", "tag" = "v1.0.1-beta.1", "git" = "https://github.com/lance-format/lance.git" }
+lance-namespace = { "version" = "=1.0.1-beta.1", "tag" = "v1.0.1-beta.1", "git" = "https://github.com/lance-format/lance.git" }
+lance-namespace-impls = { "version" = "=1.0.1-beta.1", default-features = false, "tag" = "v1.0.1-beta.1", "git" = "https://github.com/lance-format/lance.git" }
+lance-table = { "version" = "=1.0.1-beta.1", "tag" = "v1.0.1-beta.1", "git" = "https://github.com/lance-format/lance.git" }
+lance-testing = { "version" = "=1.0.1-beta.1", "tag" = "v1.0.1-beta.1", "git" = "https://github.com/lance-format/lance.git" }
+lance-datafusion = { "version" = "=1.0.1-beta.1", "tag" = "v1.0.1-beta.1", "git" = "https://github.com/lance-format/lance.git" }
+lance-encoding = { "version" = "=1.0.1-beta.1", "tag" = "v1.0.1-beta.1", "git" = "https://github.com/lance-format/lance.git" }
+lance-arrow = { "version" = "=1.0.1-beta.1", "tag" = "v1.0.1-beta.1", "git" = "https://github.com/lance-format/lance.git" }
 ahash = "0.8"
 # Note that this one does not include pyarrow
-arrow = { version = "57.2.0", optional = false }
-arrow-array = "57.2.0"
-arrow-data = "57.2.0"
-arrow-ipc = "57.2.0"
-arrow-ord = "57.2.0"
-arrow-schema = "57.2.0"
-arrow-select = "57.2.0"
-arrow-cast = "57.2.0"
+arrow = { version = "56.2", optional = false }
+arrow-array = "56.2"
+arrow-data = "56.2"
+arrow-ipc = "56.2"
+arrow-ord = "56.2"
+arrow-schema = "56.2"
+arrow-select = "56.2"
+arrow-cast = "56.2"
 async-trait = "0"
-datafusion = { version = "51.0.0", default-features = false }
-datafusion-catalog = "51.0.0"
-datafusion-common = { version = "51.0.0", default-features = false }
-datafusion-execution = "51.0.0"
-datafusion-expr = "51.0.0"
-datafusion-physical-plan = "51.0.0"
+datafusion = { version = "50.1", default-features = false }
+datafusion-catalog = "50.1"
+datafusion-common = { version = "50.1", default-features = false }
+datafusion-execution = "50.1"
+datafusion-expr = "50.1"
+datafusion-physical-plan = "50.1"
 env_logger = "0.11"
-half = { "version" = "2.7.1", default-features = false, features = [
+half = { "version" = "2.6.0", default-features = false, features = [
     "num-traits",
 ] }
 futures = "0"
@@ -59,7 +59,7 @@ rand = "0.9"
 snafu = "0.8"
 url = "2"
 num-traits = "0.2"
-regex = "1.12"
+regex = "1.10"
 lazy_static = "1"
 semver = "1.0.25"
 chrono = "0.4"

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 \

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

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)
-
-```

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)

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>0.23.1</version>
+    <version>0.23.1-beta.1</version>
 </dependency>
 ```
 

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%);
 }

java/lancedb-core/pom.xml

@@ -8,7 +8,7 @@
     <parent>
       <groupId>com.lancedb</groupId>
       <artifactId>lancedb-parent</artifactId>
-      <version>0.23.1-final.0</version>
+      <version>0.23.1-beta.1</version>
       <relativePath>../pom.xml</relativePath>
     </parent>
 

java/pom.xml

@@ -6,7 +6,7 @@
 
     <groupId>com.lancedb</groupId>
     <artifactId>lancedb-parent</artifactId>
-    <version>0.23.1-final.0</version>
+    <version>0.23.1-beta.1</version>
     <packaging>pom</packaging>
     <name>${project.artifactId}</name>
     <description>LanceDB Java SDK Parent POM</description>

nodejs/Cargo.toml

@@ -1,7 +1,7 @@
 [package]
 name = "lancedb-nodejs"
 edition.workspace = true
-version = "0.23.1"
+version = "0.23.1-beta.1"
 license.workspace = true
 description.workspace = true
 repository.workspace = true

nodejs/npm/darwin-arm64/package.json

@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-darwin-arm64",
-	"version": "0.23.1",
+	"version": "0.23.1-beta.1",
 	"os": ["darwin"],
 	"cpu": ["arm64"],
 	"main": "lancedb.darwin-arm64.node",

nodejs/npm/darwin-x64/package.json

@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-darwin-x64",
-	"version": "0.23.1",
+	"version": "0.23.1-beta.1",
 	"os": ["darwin"],
 	"cpu": ["x64"],
 	"main": "lancedb.darwin-x64.node",

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

@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-arm64-gnu",
-	"version": "0.23.1",
+	"version": "0.23.1-beta.1",
 	"os": ["linux"],
 	"cpu": ["arm64"],
 	"main": "lancedb.linux-arm64-gnu.node",

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

@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-arm64-musl",
-	"version": "0.23.1",
+	"version": "0.23.1-beta.1",
 	"os": ["linux"],
 	"cpu": ["arm64"],
 	"main": "lancedb.linux-arm64-musl.node",

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

@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-x64-gnu",
-	"version": "0.23.1",
+	"version": "0.23.1-beta.1",
 	"os": ["linux"],
 	"cpu": ["x64"],
 	"main": "lancedb.linux-x64-gnu.node",

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

@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-x64-musl",
-	"version": "0.23.1",
+	"version": "0.23.1-beta.1",
 	"os": ["linux"],
 	"cpu": ["x64"],
 	"main": "lancedb.linux-x64-musl.node",

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

@@ -1,6 +1,6 @@
 {
   "name": "@lancedb/lancedb-win32-arm64-msvc",
-  "version": "0.23.1",
+  "version": "0.23.1-beta.1",
   "os": [
     "win32"
   ],

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

@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-win32-x64-msvc",
-	"version": "0.23.1",
+	"version": "0.23.1-beta.1",
 	"os": ["win32"],
 	"cpu": ["x64"],
 	"main": "lancedb.win32-x64-msvc.node",

nodejs/package-lock.json

@@ -1,12 +1,12 @@
 {
   "name": "@lancedb/lancedb",
-  "version": "0.23.1",
+  "version": "0.23.1-beta.1",
   "lockfileVersion": 3,
   "requires": true,
   "packages": {
     "": {
       "name": "@lancedb/lancedb",
-      "version": "0.23.1",
+      "version": "0.23.1-beta.1",
       "cpu": [
         "x64",
         "arm64"

nodejs/package.json

@@ -11,7 +11,7 @@
     "ann"
   ],
   "private": false,
-  "version": "0.23.1",
+  "version": "0.23.1-beta.1",
   "main": "dist/index.js",
   "exports": {
     ".": "./dist/index.js",

python/.bumpversion.toml

@@ -1,5 +1,5 @@
 [tool.bumpversion]
-current_version = "0.26.1"
+current_version = "0.26.1-beta.1"
 parse = """(?x)
     (?P<major>0|[1-9]\\d*)\\.
     (?P<minor>0|[1-9]\\d*)\\.

python/Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "lancedb-python"
-version = "0.26.1"
+version = "0.26.1-beta.1"
 edition.workspace = true
 description = "Python bindings for LanceDB"
 license.workspace = true
@@ -14,15 +14,15 @@ name = "_lancedb"
 crate-type = ["cdylib"]
 
 [dependencies]
-arrow = { version = "57.2.0", features = ["pyarrow"] }
+arrow = { version = "56.2", features = ["pyarrow"] }
 async-trait = "0.1"
 lancedb = { path = "../rust/lancedb", default-features = false }
 lance-core.workspace = true
 lance-namespace.workspace = true
 lance-io.workspace = true
 env_logger.workspace = true
-pyo3 = { version = "0.26", features = ["extension-module", "abi3-py39"] }
-pyo3-async-runtimes = { version = "0.26", features = [
+pyo3 = { version = "0.25", features = ["extension-module", "abi3-py39"] }
+pyo3-async-runtimes = { version = "0.25", features = [
     "attributes",
     "tokio-runtime",
 ] }
@@ -32,7 +32,7 @@ snafu.workspace = true
 tokio = { version = "1.40", features = ["sync"] }
 
 [build-dependencies]
-pyo3-build-config = { version = "0.26", features = [
+pyo3-build-config = { version = "0.25", features = [
     "extension-module",
     "abi3-py39",
 ] }

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),

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
         -------

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
@@ -45,29 +45,11 @@ 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 = 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):
@@ -88,24 +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.")
 
@@ -119,8 +91,6 @@ def sanitize_multimodal_input(inputs: Union[TEXT, IMAGES]) -> List[Any]:
     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):
@@ -173,16 +143,11 @@ class VoyageAIEmbeddingFunction(EmbeddingFunction):
             * 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
     --------
@@ -210,10 +175,7 @@ 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-3.5",
         "voyage-3.5-lite",
@@ -224,7 +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):
@@ -236,17 +198,6 @@ 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":
@@ -260,17 +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]:
@@ -288,7 +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
             )
@@ -330,7 +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
                 )
@@ -413,7 +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)
@@ -421,7 +364,7 @@ class VoyageAIEmbeddingFunction(EmbeddingFunction):
                     inputs=batch_inputs,
                     model=self.name,
                     input_type=input_type,
-                    **multimodal_kwargs,
+                    **kwargs,
                 )
                 return result.embeddings
 

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)

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(

python/python/tests/test_embeddings_slow.py

@@ -613,133 +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,

python/python/tests/test_remote_db.py

@@ -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}

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

python/src/arrow.rs

@@ -1,4 +1,3 @@
-#![allow(deprecated)]
 // SPDX-License-Identifier: Apache-2.0
 // SPDX-FileCopyrightText: Copyright The LanceDB Authors
 
@@ -11,7 +10,8 @@ use arrow::{
 use futures::stream::StreamExt;
 use lancedb::arrow::SendableRecordBatchStream;
 use pyo3::{
-    exceptions::PyStopAsyncIteration, pyclass, pymethods, Bound, Py, PyAny, PyRef, PyResult, Python,
+    exceptions::PyStopAsyncIteration, pyclass, pymethods, Bound, PyAny, PyObject, PyRef, PyResult,
+    Python,
 };
 use pyo3_async_runtimes::tokio::future_into_py;
 
@@ -36,11 +36,8 @@ impl RecordBatchStream {
 #[pymethods]
 impl RecordBatchStream {
     #[getter]
-    pub fn schema(&self, py: Python) -> PyResult<Py<PyAny>> {
-        (*self.schema)
-            .clone()
-            .into_pyarrow(py)
-            .map(|bound| bound.unbind())
+    pub fn schema(&self, py: Python) -> PyResult<PyObject> {
+        (*self.schema).clone().into_pyarrow(py)
     }
 
     pub fn __aiter__(self_: PyRef<'_, Self>) -> PyRef<'_, Self> {
@@ -56,12 +53,7 @@ impl RecordBatchStream {
                 .next()
                 .await
                 .ok_or_else(|| PyStopAsyncIteration::new_err(""))?;
-            Python::with_gil(|py| {
-                inner_next
-                    .infer_error()?
-                    .to_pyarrow(py)
-                    .map(|bound| bound.unbind())
-            })
+            Python::with_gil(|py| inner_next.infer_error()?.to_pyarrow(py))
         })
     }
 }

python/src/connection.rs

@@ -1,4 +1,3 @@
-#![allow(deprecated)]
 // SPDX-License-Identifier: Apache-2.0
 // SPDX-FileCopyrightText: Copyright The LanceDB Authors
 
@@ -305,7 +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>> {
@@ -327,16 +325,21 @@ impl Connection {
         let inner = self_.get_inner()?.clone();
         let py = self_.py();
         future_into_py(py, async move {
-            use lance_namespace::models::CreateNamespaceRequest;
+            use lance_namespace::models::{create_namespace_request, CreateNamespaceRequest};
+            let mode_enum = mode.and_then(|m| match m.to_lowercase().as_str() {
+                "create" => Some(create_namespace_request::Mode::Create),
+                "exist_ok" => Some(create_namespace_request::Mode::ExistOk),
+                "overwrite" => Some(create_namespace_request::Mode::Overwrite),
+                _ => None,
+            });
             let request = CreateNamespaceRequest {
                 id: if namespace.is_empty() {
                     None
                 } else {
                     Some(namespace)
                 },
-                mode,
+                mode: mode_enum,
                 properties,
-                ..Default::default()
             };
             let response = inner.create_namespace(request).await.infer_error()?;
             Python::with_gil(|py| -> PyResult<Py<PyDict>> {
@@ -357,16 +360,25 @@ impl Connection {
         let inner = self_.get_inner()?.clone();
         let py = self_.py();
         future_into_py(py, async move {
-            use lance_namespace::models::DropNamespaceRequest;
+            use lance_namespace::models::{drop_namespace_request, DropNamespaceRequest};
+            let mode_enum = mode.and_then(|m| match m.to_uppercase().as_str() {
+                "SKIP" => Some(drop_namespace_request::Mode::Skip),
+                "FAIL" => Some(drop_namespace_request::Mode::Fail),
+                _ => None,
+            });
+            let behavior_enum = behavior.and_then(|b| match b.to_uppercase().as_str() {
+                "RESTRICT" => Some(drop_namespace_request::Behavior::Restrict),
+                "CASCADE" => Some(drop_namespace_request::Behavior::Cascade),
+                _ => None,
+            });
             let request = DropNamespaceRequest {
                 id: if namespace.is_empty() {
                     None
                 } else {
                     Some(namespace)
                 },
-                mode,
-                behavior,
-                ..Default::default()
+                mode: mode_enum,
+                behavior: behavior_enum,
             };
             let response = inner.drop_namespace(request).await.infer_error()?;
             Python::with_gil(|py| -> PyResult<Py<PyDict>> {
@@ -393,7 +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>> {
@@ -423,7 +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>> {

python/src/error.rs

@@ -1,4 +1,3 @@
-#![allow(deprecated)]
 // SPDX-License-Identifier: Apache-2.0
 // SPDX-FileCopyrightText: Copyright The LanceDB Authors
 

python/src/header.rs

@@ -1,4 +1,3 @@
-#![allow(deprecated)]
 // SPDX-License-Identifier: Apache-2.0
 // SPDX-FileCopyrightText: Copyright The LanceDB Authors
 

python/src/permutation.rs

@@ -1,4 +1,3 @@
-#![allow(deprecated)]
 // SPDX-License-Identifier: Apache-2.0
 // SPDX-FileCopyrightText: Copyright The LanceDB Authors
 
@@ -282,7 +281,7 @@ impl PyPermutationReader {
         let reader = slf.reader.clone();
         future_into_py(slf.py(), async move {
             let schema = reader.output_schema(selection).await.infer_error()?;
-            Python::with_gil(|py| schema.to_pyarrow(py).map(|b| b.unbind()))
+            Python::with_gil(|py| schema.to_pyarrow(py))
         })
     }
 

python/src/query.rs

@@ -1,4 +1,3 @@
-#![allow(deprecated)]
 // SPDX-License-Identifier: Apache-2.0
 // SPDX-FileCopyrightText: Copyright The LanceDB Authors
 
@@ -217,7 +216,7 @@ impl<'py> IntoPyObject<'py> for PyQueryVectors {
         let py_objs = self
             .0
             .into_iter()
-            .map(|v| v.to_data().into_pyarrow(py).map(|b| b.unbind()))
+            .map(|v| v.to_data().into_pyarrow(py))
             .collect::<Result<Vec<_>, _>>()?;
         PyList::new(py, py_objs)
     }
@@ -454,7 +453,7 @@ impl Query {
         let inner = self_.inner.clone();
         future_into_py(self_.py(), async move {
             let schema = inner.output_schema().await.infer_error()?;
-            Python::with_gil(|py| schema.to_pyarrow(py).map(|b| b.unbind()))
+            Python::with_gil(|py| schema.to_pyarrow(py))
         })
     }
 
@@ -533,7 +532,7 @@ impl TakeQuery {
         let inner = self_.inner.clone();
         future_into_py(self_.py(), async move {
             let schema = inner.output_schema().await.infer_error()?;
-            Python::with_gil(|py| schema.to_pyarrow(py).map(|b| b.unbind()))
+            Python::with_gil(|py| schema.to_pyarrow(py))
         })
     }
 
@@ -628,7 +627,7 @@ impl FTSQuery {
         let inner = self_.inner.clone();
         future_into_py(self_.py(), async move {
             let schema = inner.output_schema().await.infer_error()?;
-            Python::with_gil(|py| schema.to_pyarrow(py).map(|b| b.unbind()))
+            Python::with_gil(|py| schema.to_pyarrow(py))
         })
     }
 
@@ -807,7 +806,7 @@ impl VectorQuery {
         let inner = self_.inner.clone();
         future_into_py(self_.py(), async move {
             let schema = inner.output_schema().await.infer_error()?;
-            Python::with_gil(|py| schema.to_pyarrow(py).map(|b| b.unbind()))
+            Python::with_gil(|py| schema.to_pyarrow(py))
         })
     }
 

python/src/storage_options.rs

@@ -1,4 +1,3 @@
-#![allow(deprecated)]
 // SPDX-License-Identifier: Apache-2.0
 // SPDX-FileCopyrightText: Copyright The LanceDB Authors
 

python/src/table.rs

@@ -1,4 +1,3 @@
-#![allow(deprecated)]
 // SPDX-License-Identifier: Apache-2.0
 // SPDX-FileCopyrightText: Copyright The LanceDB Authors
 use std::{collections::HashMap, sync::Arc};
@@ -288,7 +287,7 @@ impl Table {
         let inner = self_.inner_ref()?.clone();
         future_into_py(self_.py(), async move {
             let schema = inner.schema().await.infer_error()?;
-            Python::with_gil(|py| schema.to_pyarrow(py).map(|b| b.unbind()))
+            Python::with_gil(|py| schema.to_pyarrow(py))
         })
     }
 

rust/lancedb/Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "lancedb"
-version = "0.23.1"
+version = "0.23.1-beta.1"
 edition.workspace = true
 description = "LanceDB: A serverless, low-latency vector database for AI applications"
 license.workspace = true

rust/lancedb/src/connection.rs

@@ -1325,27 +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();

rust/lancedb/src/database/namespace.rs

@@ -9,7 +9,7 @@ use std::sync::Arc;
 use async_trait::async_trait;
 use lance_namespace::{
     models::{
-        CreateNamespaceRequest, CreateNamespaceResponse, DeclareTableRequest,
+        CreateEmptyTableRequest, CreateNamespaceRequest, CreateNamespaceResponse,
         DescribeNamespaceRequest, DescribeNamespaceResponse, DescribeTableRequest,
         DropNamespaceRequest, DropNamespaceResponse, DropTableRequest, ListNamespacesRequest,
         ListNamespacesResponse, ListTablesRequest, ListTablesResponse,
@@ -137,7 +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 +154,6 @@ impl Database for LanceNamespaceDatabase {
         let describe_request = DescribeTableRequest {
             id: Some(table_id.clone()),
             version: None,
-            ..Default::default()
         };
 
         let describe_result = self.namespace.describe_table(describe_request).await;
@@ -173,7 +171,6 @@ 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)
@@ -205,24 +202,29 @@ impl Database for LanceNamespaceDatabase {
         let mut table_id = request.namespace.clone();
         table_id.push(request.name.clone());
 
-        let declare_request = DeclareTableRequest {
+        let create_empty_request = CreateEmptyTableRequest {
             id: Some(table_id.clone()),
             location: None,
-            vend_credentials: None,
-            ..Default::default()
+            properties: if self.storage_options.is_empty() {
+                None
+            } else {
+                Some(self.storage_options.clone())
+            },
         };
 
-        let declare_response = self
+        let create_empty_response = self
             .namespace
-            .declare_table(declare_request)
+            .create_empty_table(create_empty_request)
             .await
             .map_err(|e| Error::Runtime {
-                message: format!("Failed to declare table: {}", e),
+                message: format!("Failed to create empty table: {}", e),
             })?;
 
-        let location = declare_response.location.ok_or_else(|| Error::Runtime {
-            message: "Table location is missing from declare_table response".to_string(),
-        })?;
+        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(),
@@ -279,10 +281,7 @@ 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
@@ -439,7 +438,6 @@ mod tests {
             id: Some(vec!["test_ns".into()]),
             mode: None,
             properties: None,
-            ..Default::default()
         })
         .await
         .expect("Failed to create namespace");
@@ -501,7 +499,6 @@ mod tests {
             id: Some(vec!["test_ns".into()]),
             mode: None,
             properties: None,
-            ..Default::default()
         })
         .await
         .expect("Failed to create namespace");
@@ -566,7 +563,6 @@ mod tests {
             id: Some(vec!["test_ns".into()]),
             mode: None,
             properties: None,
-            ..Default::default()
         })
         .await
         .expect("Failed to create namespace");
@@ -651,7 +647,6 @@ mod tests {
             id: Some(vec!["test_ns".into()]),
             mode: None,
             properties: None,
-            ..Default::default()
         })
         .await
         .expect("Failed to create namespace");
@@ -708,7 +703,6 @@ mod tests {
             id: Some(vec!["test_ns".into()]),
             mode: None,
             properties: None,
-            ..Default::default()
         })
         .await
         .expect("Failed to create namespace");
@@ -790,7 +784,6 @@ mod tests {
             id: Some(vec!["test_ns".into()]),
             mode: None,
             properties: None,
-            ..Default::default()
         })
         .await
         .expect("Failed to create namespace");
@@ -825,7 +818,6 @@ mod tests {
             id: Some(vec!["test_ns".into()]),
             mode: None,
             properties: None,
-            ..Default::default()
         })
         .await
         .expect("Failed to create namespace");

rust/lancedb/src/dataloader/permutation/builder.rs

@@ -8,9 +8,10 @@ use datafusion_execution::{disk_manager::DiskManagerBuilder, runtime_env::Runtim
 use datafusion_expr::col;
 use futures::TryStreamExt;
 use lance_core::ROW_ID;
+use lance_datafusion::exec::SessionContextExt;
 
 use crate::{
-    arrow::{SendableRecordBatchStream, SimpleRecordBatchStream},
+    arrow::{SendableRecordBatchStream, SendableRecordBatchStreamExt, SimpleRecordBatchStream},
     connect,
     database::{CreateTableData, CreateTableRequest, Database},
     dataloader::permutation::{
@@ -177,17 +178,12 @@ impl PermutationBuilder {
                 .build_arc()
                 .unwrap(),
         );
-        let batches = data
+        let df = ctx
+            .read_one_shot(data.into_df_stream())
             .map_err(|e| Error::Other {
                 message: format!("Failed to setup sort by split id: {}", e),
                 source: Some(e.into()),
-            })
-            .try_collect::<Vec<_>>()
-            .await?;
-        let df = ctx.read_batches(batches).map_err(|e| Error::Other {
-            message: format!("Failed to setup sort by split id: {}", e),
-            source: Some(e.into()),
-        })?;
+            })?;
         let df_stream = df
             .sort_by(vec![col(SPLIT_ID_COLUMN)])
             .map_err(|e| Error::Other {

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)),
                     };

rust/lancedb/src/remote/db.rs

@@ -1720,7 +1720,6 @@ mod tests {
                 id: Some(namespace.clone()),
                 mode: None,
                 properties: None,
-                ..Default::default()
             })
             .await
             .expect("Failed to create namespace");
@@ -1747,7 +1746,6 @@ mod tests {
                     id: Some(namespace.clone()),
                     page_token: None,
                     limit: None,
-                    ..Default::default()
                 })
                 .await
                 .expect("Failed to list tables");
@@ -1760,7 +1758,6 @@ mod tests {
                     id: Some(namespace.clone()),
                     page_token: None,
                     limit: None,
-                    ..Default::default()
                 })
                 .await
                 .unwrap();
@@ -1802,7 +1799,6 @@ mod tests {
                 id: Some(namespace.clone()),
                 mode: None,
                 properties: None,
-                ..Default::default()
             })
             .await
             .expect("Failed to create namespace");
@@ -1829,7 +1825,6 @@ mod tests {
                     id: Some(namespace.clone()),
                     page_token: None,
                     limit: None,
-                    ..Default::default()
                 })
                 .await
                 .unwrap();

rust/lancedb/src/remote/table.rs

@@ -1088,17 +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());
             }

rust/lancedb/src/table.rs

@@ -42,8 +42,8 @@ use lance_index::DatasetIndexExt;
 use lance_index::IndexType;
 use lance_io::object_store::LanceNamespaceStorageOptionsProvider;
 use lance_namespace::models::{
-    QueryTableRequest as NsQueryTableRequest, QueryTableRequestColumns,
-    QueryTableRequestFullTextQuery, QueryTableRequestVector, StringFtsQuery,
+    QueryTableRequest as NsQueryTableRequest, QueryTableRequestFullTextQuery,
+    QueryTableRequestVector, StringFtsQuery,
 };
 use lance_namespace::LanceNamespace;
 use lance_table::format::Manifest;
@@ -1411,35 +1411,26 @@ impl Table {
         let projected_plans = plans
             .into_iter()
             .enumerate()
-            .map(
-                |(plan_i, plan)| -> Result<Arc<dyn datafusion_physical_plan::ExecutionPlan>> {
-                    let query_index = datafusion_common::ScalarValue::Int32(Some(plan_i as i32));
-                    let query_index_expr =
-                        datafusion_physical_plan::expressions::Literal::new(query_index);
-                    let query_index_expr = Arc::new(query_index_expr)
-                        as Arc<dyn datafusion_physical_plan::PhysicalExpr>;
-                    let mut projections = vec![(query_index_expr, "query_index".to_string())];
-                    projections.extend_from_slice(&project_all_columns);
-                    let projection =
-                        ProjectionExec::try_new(projections, plan).map_err(|e| Error::Runtime {
-                            message: format!("Failed to build projection plan: {e}"),
-                        })?;
-                    Ok(Arc::new(projection) as Arc<dyn datafusion_physical_plan::ExecutionPlan>)
-                },
-            )
-            .collect::<Result<Vec<_>>>()?;
+            .map(|(plan_i, plan)| {
+                let query_index = datafusion_common::ScalarValue::Int32(Some(plan_i as i32));
+                let query_index_expr =
+                    datafusion_physical_plan::expressions::Literal::new(query_index);
+                let query_index_expr =
+                    Arc::new(query_index_expr) as Arc<dyn datafusion_physical_plan::PhysicalExpr>;
+                let mut projections = vec![(query_index_expr, "query_index".to_string())];
+                projections.extend_from_slice(&project_all_columns);
+                let projection = ProjectionExec::try_new(projections, plan).unwrap();
+                Arc::new(projection) as Arc<dyn datafusion_physical_plan::ExecutionPlan>
+            })
+            .collect::<Vec<_>>();
 
-        let unioned = UnionExec::try_new(projected_plans).map_err(|e| Error::Runtime {
-            message: format!("Failed to union query plans: {e}"),
-        })?;
+        let unioned = Arc::new(UnionExec::new(projected_plans));
         // We require 1 partition in the final output
         let repartitioned = RepartitionExec::try_new(
             unioned,
             datafusion_physical_plan::Partitioning::RoundRobinBatch(1),
         )
-        .map_err(|e| Error::Runtime {
-            message: format!("Failed to repartition query plans: {e}"),
-        })?;
+        .unwrap();
         Ok(Arc::new(repartitioned))
     }
 
@@ -2343,23 +2334,6 @@ impl NativeTable {
 
     /// Convert an AnyQuery to the namespace QueryTableRequest format.
     fn convert_to_namespace_query(&self, query: &AnyQuery) -> Result<NsQueryTableRequest> {
-        let to_namespace_columns =
-            |select: &Select| -> Result<Option<Box<QueryTableRequestColumns>>> {
-                match select {
-                    Select::All => Ok(None),
-                    Select::Columns(cols) => {
-                        let mut columns = QueryTableRequestColumns::new();
-                        columns.column_names = Some(cols.clone());
-                        Ok(Some(Box::new(columns)))
-                    }
-                    Select::Dynamic(_) => Err(Error::NotSupported {
-                        message:
-                            "Dynamic column selection is not supported for server-side queries"
-                                .to_string(),
-                    }),
-                }
-            };
-
         match query {
             AnyQuery::VectorQuery(vq) => {
                 // Extract the query vector(s)
@@ -2371,6 +2345,19 @@ impl NativeTable {
                     None => None,
                 };
 
+                // Convert select to columns list
+                let columns = match &vq.base.select {
+                    Select::All => None,
+                    Select::Columns(cols) => Some(cols.clone()),
+                    Select::Dynamic(_) => {
+                        return Err(Error::NotSupported {
+                            message:
+                                "Dynamic column selection is not supported for server-side queries"
+                                    .to_string(),
+                        });
+                    }
+                };
+
                 // Check for unsupported features
                 if vq.base.reranker.is_some() {
                     return Err(Error::NotSupported {
@@ -2378,8 +2365,6 @@ impl NativeTable {
                     });
                 }
 
-                let columns = to_namespace_columns(&vq.base.select)?;
-
                 // Convert FTS query if present
                 let full_text_query = vq.base.full_text_search.as_ref().map(|fts| {
                     let columns = fts.columns();
@@ -2417,7 +2402,6 @@ impl NativeTable {
                     bypass_vector_index: Some(!vq.use_index),
                     full_text_query,
                     version: None,
-                    ..Default::default()
                 })
             }
             AnyQuery::Query(q) => {
@@ -2435,7 +2419,16 @@ impl NativeTable {
                     .map(|f| self.filter_to_sql(f))
                     .transpose()?;
 
-                let columns = to_namespace_columns(&q.select)?;
+                let columns = match &q.select {
+                    Select::All => None,
+                    Select::Columns(cols) => Some(cols.clone()),
+                    Select::Dynamic(_) => {
+                        return Err(Error::NotSupported {
+                            message: "Dynamic columns are not supported for server-side query"
+                                .to_string(),
+                        });
+                    }
+                };
 
                 // Handle full text search if present
                 let full_text_query = q.full_text_search.as_ref().map(|fts| {
@@ -2479,7 +2472,6 @@ impl NativeTable {
                     fast_search: None,
                     lower_bound: None,
                     upper_bound: None,
-                    ..Default::default()
                 })
             }
         }
@@ -5154,13 +5146,7 @@ mod tests {
         assert_eq!(ns_request.k, 10);
         assert_eq!(ns_request.offset, Some(5));
         assert_eq!(ns_request.filter, Some("id > 0".to_string()));
-        assert_eq!(
-            ns_request
-                .columns
-                .as_ref()
-                .and_then(|cols| cols.column_names.clone()),
-            Some(vec!["id".to_string()])
-        );
+        assert_eq!(ns_request.columns, 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()));
         assert!(ns_request.vector.single_vector.is_some());
@@ -5201,13 +5187,7 @@ mod tests {
         assert_eq!(ns_request.k, 20);
         assert_eq!(ns_request.offset, Some(5));
         assert_eq!(ns_request.filter, Some("id > 5".to_string()));
-        assert_eq!(
-            ns_request
-                .columns
-                .as_ref()
-                .and_then(|cols| cols.column_names.clone()),
-            Some(vec!["id".to_string()])
-        );
+        assert_eq!(ns_request.columns, Some(vec!["id".to_string()]));
         assert_eq!(ns_request.with_row_id, Some(true));
         assert_eq!(ns_request.bypass_vector_index, Some(true));
         assert!(ns_request.vector_column.is_none()); // No vector column for plain queries

rust/lancedb/src/table/dataset.rs

@@ -101,7 +101,6 @@ impl DatasetRef {
                     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,
                 };
 
                 if should_checkout {

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,
     })

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());
-}