Bump version: 0.21.0-beta.0 → 0.21.0

2025-12-24 13:59:58 +00:00 · 2025-06-20 05:46:32 +00:00
37 changed files with 351 additions and 571 deletions
--- a/.bumpversion.toml
+++ b/.bumpversion.toml
@@ -1,5 +1,5 @@
 [tool.bumpversion]
-current_version = "0.21.1"
+current_version = "0.21.0"
 parse = """(?x)
    (?P<major>0|[1-9]\\d*)\\.
    (?P<minor>0|[1-9]\\d*)\\.
--- a/Cargo.lock
+++ b/Cargo.lock
--- a/Cargo.toml
+++ b/Cargo.toml
@@ -21,14 +21,14 @@ categories = ["database-implementations"]
 rust-version = "1.78.0"

 [workspace.dependencies]
-lance = { "version" = "=0.31.1", features = ["dynamodb"] }
-lance-io = { "version" = "=0.31.1" }
-lance-index = { "version" = "=0.31.1" }
-lance-linalg = { "version" = "=0.31.1" }
-lance-table = { "version" = "=0.31.1" }
-lance-testing = { "version" = "=0.31.1" }
-lance-datafusion = { "version" = "=0.31.1" }
-lance-encoding = { "version" = "=0.31.1" }
+lance = { "version" = "=0.30.0", "features" = ["dynamodb"] }
+lance-io = "=0.30.0"
+lance-index = "=0.30.0"
+lance-linalg = "=0.30.0"
+lance-table = "=0.30.0"
+lance-testing = "=0.30.0"
+lance-datafusion = "=0.30.0"
+lance-encoding = "=0.30.0"
 # Note that this one does not include pyarrow
 arrow = { version = "55.1", optional = false }
 arrow-array = "55.1"
@@ -39,20 +39,20 @@ arrow-schema = "55.1"
 arrow-arith = "55.1"
 arrow-cast = "55.1"
 async-trait = "0"
-datafusion = { version = "48.0", default-features = false }
-datafusion-catalog = "48.0"
-datafusion-common = { version = "48.0", default-features = false }
-datafusion-execution = "48.0"
-datafusion-expr = "48.0"
-datafusion-physical-plan = "48.0"
+datafusion = { version = "47.0", default-features = false }
+datafusion-catalog = "47.0"
+datafusion-common = { version = "47.0", default-features = false }
+datafusion-execution = "47.0"
+datafusion-expr = "47.0"
+datafusion-physical-plan = "47.0"
 env_logger = "0.11"
-half = { "version" = "2.6.0", default-features = false, features = [
+half = { "version" = "=2.5.0", default-features = false, features = [
    "num-traits",
 ] }
 futures = "0"
 log = "0.4"
 moka = { version = "0.12", features = ["future"] }
-object_store = "0.12.0"
+object_store = "0.11.0"
 pin-project = "1.0.7"
 snafu = "0.8"
 url = "2"
--- a/docs/src/notebooks/Multivector_on_LanceDB.ipynb
+++ b/docs/src/notebooks/Multivector_on_LanceDB.ipynb
@@ -428,7 +428,7 @@
        "\n",
        "**Why?**  \n",
        "Embedding the UFO dataset and ingesting it into LanceDB takes **~2 hours on a T4 GPU**. To save time:  \n",
-        "- **Use the pre-prepared table with index created** (provided below) to proceed directly to **Step 7**: search.  \n",
+        "- **Use the pre-prepared table with index created ** (provided below) to proceed directly to step7: search.  \n",
        "- **Step 5a** contains the full ingestion code for reference (run it only if necessary).  \n",
        "- **Step 6** contains the details on creating the index on the multivector column"
      ]
--- a/java/core/pom.xml
+++ b/java/core/pom.xml
@@ -8,7 +8,7 @@
    <parent>
        <groupId>com.lancedb</groupId>
        <artifactId>lancedb-parent</artifactId>
-        <version>0.21.1-final.0</version>
+        <version>0.21.0-final.0</version>
        <relativePath>../pom.xml</relativePath>
    </parent>

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

    <groupId>com.lancedb</groupId>
    <artifactId>lancedb-parent</artifactId>
-    <version>0.21.1-final.0</version>
+    <version>0.21.0-final.0</version>
    <packaging>pom</packaging>

    <name>LanceDB Parent</name>
--- a/node/package-lock.json
+++ b/node/package-lock.json
@@ -1,12 +1,12 @@
 {
  "name": "vectordb",
-  "version": "0.21.1-beta.1",
+  "version": "0.20.1-beta.2",
  "lockfileVersion": 3,
  "requires": true,
  "packages": {
    "": {
      "name": "vectordb",
-      "version": "0.21.1-beta.1",
+      "version": "0.20.1-beta.2",
      "cpu": [
        "x64",
        "arm64"
@@ -52,11 +52,11 @@
        "uuid": "^9.0.0"
      },
      "optionalDependencies": {
-        "@lancedb/vectordb-darwin-arm64": "0.21.1-beta.1",
-        "@lancedb/vectordb-darwin-x64": "0.21.1-beta.1",
-        "@lancedb/vectordb-linux-arm64-gnu": "0.21.1-beta.1",
-        "@lancedb/vectordb-linux-x64-gnu": "0.21.1-beta.1",
-        "@lancedb/vectordb-win32-x64-msvc": "0.21.1-beta.1"
+        "@lancedb/vectordb-darwin-arm64": "0.20.1-beta.2",
+        "@lancedb/vectordb-darwin-x64": "0.20.1-beta.2",
+        "@lancedb/vectordb-linux-arm64-gnu": "0.20.1-beta.2",
+        "@lancedb/vectordb-linux-x64-gnu": "0.20.1-beta.2",
+        "@lancedb/vectordb-win32-x64-msvc": "0.20.1-beta.2"
      },
      "peerDependencies": {
        "@apache-arrow/ts": "^14.0.2",
@@ -327,9 +327,9 @@
      }
    },
    "node_modules/@lancedb/vectordb-darwin-arm64": {
-      "version": "0.21.1-beta.1",
-      "resolved": "https://registry.npmjs.org/@lancedb/vectordb-darwin-arm64/-/vectordb-darwin-arm64-0.21.1-beta.1.tgz",
-      "integrity": "sha512-D9SOLFb/40E2/9bt82xOti3jogRAaR1UkT2LfGZJw/0wBu8d8/xKjWgfm3d26S5K6in6DWsX1njLxevrFqD5HA==",
+      "version": "0.20.1-beta.2",
+      "resolved": "https://registry.npmjs.org/@lancedb/vectordb-darwin-arm64/-/vectordb-darwin-arm64-0.20.1-beta.2.tgz",
+      "integrity": "sha512-mqi0yI+ZwBTydaDy1FRHAUZwrWS28u6tbHTe1s4uSrmERbVI6PfmoPR+NZWWAp6ZhlseSdl/+yeI4imk11rQSw==",
      "cpu": [
        "arm64"
      ],
@@ -339,9 +339,9 @@
      ]
    },
    "node_modules/@lancedb/vectordb-darwin-x64": {
-      "version": "0.21.1-beta.1",
-      "resolved": "https://registry.npmjs.org/@lancedb/vectordb-darwin-x64/-/vectordb-darwin-x64-0.21.1-beta.1.tgz",
-      "integrity": "sha512-JnZ41aDOJs6LWfI9t/+MnpqsK/Fj9r/hDdZSOjcQquLOcm2eP3NnvEnDvn+1pqWBN6ceqf1avTatPBGnD/yhNA==",
+      "version": "0.20.1-beta.2",
+      "resolved": "https://registry.npmjs.org/@lancedb/vectordb-darwin-x64/-/vectordb-darwin-x64-0.20.1-beta.2.tgz",
+      "integrity": "sha512-m8EYYA8JZIeNsJqQsBDUMu6r31/u7FzpjonJ4Y+CjapVl6UdvI65KUkeL2dYrFao++RuIoaiqcm3e7gRgFZpXQ==",
      "cpu": [
        "x64"
      ],
@@ -351,9 +351,9 @@
      ]
    },
    "node_modules/@lancedb/vectordb-linux-arm64-gnu": {
-      "version": "0.21.1-beta.1",
-      "resolved": "https://registry.npmjs.org/@lancedb/vectordb-linux-arm64-gnu/-/vectordb-linux-arm64-gnu-0.21.1-beta.1.tgz",
-      "integrity": "sha512-Xnw0wYtnfzVUr4DzppJCSx+HZdAHr6sqMC8SdaYNQ9XEjBZE20n5SO2AdBYjejbmONJ7lpGs3ydnLIZ6N40dAQ==",
+      "version": "0.20.1-beta.2",
+      "resolved": "https://registry.npmjs.org/@lancedb/vectordb-linux-arm64-gnu/-/vectordb-linux-arm64-gnu-0.20.1-beta.2.tgz",
+      "integrity": "sha512-3Og2+bk4GlWmMO1Yg2HBfeb5zrOMLaIHD7bEqQ4+6yw4IckAaV+ke05H0tyyqmOVrOQ0LpvtXgD7pPztjm9r9A==",
      "cpu": [
        "arm64"
      ],
@@ -363,9 +363,9 @@
      ]
    },
    "node_modules/@lancedb/vectordb-linux-x64-gnu": {
-      "version": "0.21.1-beta.1",
-      "resolved": "https://registry.npmjs.org/@lancedb/vectordb-linux-x64-gnu/-/vectordb-linux-x64-gnu-0.21.1-beta.1.tgz",
-      "integrity": "sha512-7S7gV13hv9Ho5W1Jat3FYiaMJOjRAwZOol7lKvOhU+sR/tJMEfZIOWAgymoqhAowbMtf+wwLoeKacfybXGET/w==",
+      "version": "0.20.1-beta.2",
+      "resolved": "https://registry.npmjs.org/@lancedb/vectordb-linux-x64-gnu/-/vectordb-linux-x64-gnu-0.20.1-beta.2.tgz",
+      "integrity": "sha512-mwTQyA/FBoU/FkPuvCNBZG3y83gBN+iYoejehBH2HBkLUIcmlsDgSRZ1OQ+f9ijj12EMBCA11tBUPA9zhHzyrw==",
      "cpu": [
        "x64"
      ],
@@ -375,9 +375,9 @@
      ]
    },
    "node_modules/@lancedb/vectordb-win32-x64-msvc": {
-      "version": "0.21.1-beta.1",
-      "resolved": "https://registry.npmjs.org/@lancedb/vectordb-win32-x64-msvc/-/vectordb-win32-x64-msvc-0.21.1-beta.1.tgz",
-      "integrity": "sha512-w6fEQA9IquvJ/GUYfiawRQvvdFD6OU44UW9JWm+FoscUFzdLiV7qmH4QjYEeEXQD7ob83ikFaxXGPTksYXpNOA==",
+      "version": "0.20.1-beta.2",
+      "resolved": "https://registry.npmjs.org/@lancedb/vectordb-win32-x64-msvc/-/vectordb-win32-x64-msvc-0.20.1-beta.2.tgz",
+      "integrity": "sha512-VkjNpqhK3l3uHLLPmox+HrmKPMaZgV+qsGQWx0nfseGnSOEmXAWZWQFe0APVCQ9y0xTypQB0oH7eSOPZv2t4WQ==",
      "cpu": [
        "x64"
      ],
--- a/node/package.json
+++ b/node/package.json
@@ -1,6 +1,6 @@
 {
  "name": "vectordb",
-  "version": "0.21.1",
+  "version": "0.21.0",
  "description": " Serverless, low-latency vector database for AI applications",
  "private": false,
  "main": "dist/index.js",
@@ -89,10 +89,10 @@
    }
  },
  "optionalDependencies": {
-    "@lancedb/vectordb-darwin-x64": "0.21.1",
-    "@lancedb/vectordb-darwin-arm64": "0.21.1",
-    "@lancedb/vectordb-linux-x64-gnu": "0.21.1",
-    "@lancedb/vectordb-linux-arm64-gnu": "0.21.1",
-    "@lancedb/vectordb-win32-x64-msvc": "0.21.1"
+    "@lancedb/vectordb-darwin-x64": "0.21.0",
+    "@lancedb/vectordb-darwin-arm64": "0.21.0",
+    "@lancedb/vectordb-linux-x64-gnu": "0.21.0",
+    "@lancedb/vectordb-linux-arm64-gnu": "0.21.0",
+    "@lancedb/vectordb-win32-x64-msvc": "0.21.0"
  }
 }
--- a/nodejs/Cargo.toml
+++ b/nodejs/Cargo.toml
@@ -1,7 +1,7 @@
 [package]
 name = "lancedb-nodejs"
 edition.workspace = true
-version = "0.21.1"
+version = "0.21.0"
 license.workspace = true
 description.workspace = true
 repository.workspace = true
--- a/nodejs/test/table.test.ts
+++ b/nodejs/test/table.test.ts
@@ -368,9 +368,9 @@ describe("merge insert", () => {
      { a: 4, b: "z" },
    ];

-    const result = (await table.toArrow()).toArray().sort((a, b) => a.a - b.a);
-
-    expect(result.map((row) => ({ ...row }))).toEqual(expected);
+    expect(
+      JSON.parse(JSON.stringify((await table.toArrow()).toArray())),
+    ).toEqual(expected);
  });
  test("conditional update", async () => {
    const newData = [
--- a/nodejs/npm/darwin-arm64/package.json
+++ b/nodejs/npm/darwin-arm64/package.json
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-darwin-arm64",
-	"version": "0.21.1",
+	"version": "0.21.0",
 	"os": ["darwin"],
 	"cpu": ["arm64"],
 	"main": "lancedb.darwin-arm64.node",
--- a/nodejs/npm/darwin-x64/package.json
+++ b/nodejs/npm/darwin-x64/package.json
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-darwin-x64",
-	"version": "0.21.1",
+	"version": "0.21.0",
 	"os": ["darwin"],
 	"cpu": ["x64"],
 	"main": "lancedb.darwin-x64.node",
--- a/nodejs/npm/linux-arm64-gnu/package.json
+++ b/nodejs/npm/linux-arm64-gnu/package.json
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-arm64-gnu",
-	"version": "0.21.1",
+	"version": "0.21.0",
 	"os": ["linux"],
 	"cpu": ["arm64"],
 	"main": "lancedb.linux-arm64-gnu.node",
--- a/nodejs/npm/linux-arm64-musl/package.json
+++ b/nodejs/npm/linux-arm64-musl/package.json
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-arm64-musl",
-	"version": "0.21.1",
+	"version": "0.21.0",
 	"os": ["linux"],
 	"cpu": ["arm64"],
 	"main": "lancedb.linux-arm64-musl.node",
--- a/nodejs/npm/linux-x64-gnu/package.json
+++ b/nodejs/npm/linux-x64-gnu/package.json
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-x64-gnu",
-	"version": "0.21.1",
+	"version": "0.21.0",
 	"os": ["linux"],
 	"cpu": ["x64"],
 	"main": "lancedb.linux-x64-gnu.node",
--- a/nodejs/npm/linux-x64-musl/package.json
+++ b/nodejs/npm/linux-x64-musl/package.json
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-x64-musl",
-	"version": "0.21.1",
+	"version": "0.21.0",
 	"os": ["linux"],
 	"cpu": ["x64"],
 	"main": "lancedb.linux-x64-musl.node",
--- a/nodejs/npm/win32-arm64-msvc/package.json
+++ b/nodejs/npm/win32-arm64-msvc/package.json
@@ -1,6 +1,6 @@
 {
  "name": "@lancedb/lancedb-win32-arm64-msvc",
-  "version": "0.21.1",
+  "version": "0.21.0",
  "os": [
    "win32"
  ],
--- a/nodejs/npm/win32-x64-msvc/package.json
+++ b/nodejs/npm/win32-x64-msvc/package.json
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-win32-x64-msvc",
-	"version": "0.21.1",
+	"version": "0.21.0",
 	"os": ["win32"],
 	"cpu": ["x64"],
 	"main": "lancedb.win32-x64-msvc.node",
--- a/nodejs/package-lock.json
+++ b/nodejs/package-lock.json
@@ -1,12 +1,12 @@
 {
  "name": "@lancedb/lancedb",
-  "version": "0.21.1-beta.1",
+  "version": "0.20.1-beta.2",
  "lockfileVersion": 3,
  "requires": true,
  "packages": {
    "": {
      "name": "@lancedb/lancedb",
-      "version": "0.21.1-beta.1",
+      "version": "0.20.1-beta.2",
      "cpu": [
        "x64",
        "arm64"
--- a/nodejs/package.json
+++ b/nodejs/package.json
@@ -11,7 +11,7 @@
    "ann"
  ],
  "private": false,
-  "version": "0.21.1",
+  "version": "0.21.0",
  "main": "dist/index.js",
  "exports": {
    ".": "./dist/index.js",
--- a/python/.bumpversion.toml
+++ b/python/.bumpversion.toml
@@ -1,5 +1,5 @@
 [tool.bumpversion]
-current_version = "0.24.1"
+current_version = "0.24.0"
 parse = """(?x)
    (?P<major>0|[1-9]\\d*)\\.
    (?P<minor>0|[1-9]\\d*)\\.
--- a/python/Cargo.toml
+++ b/python/Cargo.toml
@@ -1,6 +1,6 @@
 [package]
 name = "lancedb-python"
-version = "0.24.1"
+version = "0.24.0"
 edition.workspace = true
 description = "Python bindings for LanceDB"
 license.workspace = true
--- a/python/pyproject.toml
+++ b/python/pyproject.toml
@@ -85,7 +85,7 @@ embeddings = [
    "boto3>=1.28.57",
    "awscli>=1.29.57",
    "botocore>=1.31.57",
-    "ollama>=0.3.0",
+    "ollama",
    "ibm-watsonx-ai>=1.1.2",
 ]
 azure = ["adlfs>=2024.2.0"]
--- a/python/python/lancedb/embeddings/ollama.py
+++ b/python/python/lancedb/embeddings/ollama.py
@@ -2,15 +2,14 @@
 # SPDX-FileCopyrightText: Copyright The LanceDB Authors

 from functools import cached_property
-from typing import TYPE_CHECKING, List, Optional, Sequence, Union
-
-import numpy as np
+from typing import TYPE_CHECKING, List, Optional, Union

 from ..util import attempt_import_or_raise
 from .base import TextEmbeddingFunction
 from .registry import register

 if TYPE_CHECKING:
+    import numpy as np
    import ollama


@@ -29,21 +28,23 @@ class OllamaEmbeddings(TextEmbeddingFunction):
    keep_alive: Optional[Union[float, str]] = None
    ollama_client_kwargs: Optional[dict] = {}

-    def ndims(self) -> int:
+    def ndims(self):
        return len(self.generate_embeddings(["foo"])[0])

-    def _compute_embedding(self, text: Sequence[str]) -> Sequence[Sequence[float]]:
-        response = self._ollama_client.embed(
-            model=self.name,
-            input=text,
-            options=self.options,
-            keep_alive=self.keep_alive,
+    def _compute_embedding(self, text) -> Union["np.array", None]:
+        return (
+            self._ollama_client.embeddings(
+                model=self.name,
+                prompt=text,
+                options=self.options,
+                keep_alive=self.keep_alive,
+            )["embedding"]
+            or None
        )
-        return response.embeddings

    def generate_embeddings(
-        self, texts: Union[List[str], np.ndarray]
-    ) -> list[Union[np.array, None]]:
+        self, texts: Union[List[str], "np.ndarray"]
+    ) -> list[Union["np.array", None]]:
        """
        Get the embeddings for the given texts

@@ -53,8 +54,8 @@ class OllamaEmbeddings(TextEmbeddingFunction):
            The texts to embed
        """
        # TODO retry, rate limit, token limit
-        embeddings = self._compute_embedding(texts)
-        return list(embeddings)
+        embeddings = [self._compute_embedding(text) for text in texts]
+        return embeddings

    @cached_property
    def _ollama_client(self) -> "ollama.Client":
--- a/python/python/lancedb/query.py
+++ b/python/python/lancedb/query.py
@@ -3042,21 +3042,15 @@ class AsyncHybridQuery(AsyncQueryBase, AsyncVectorQueryBase):
        >>> asyncio.run(doctest_example()) # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
        Vector Search Plan:
        ProjectionExec: expr=[vector@0 as vector, text@3 as text, _distance@2 as _distance]
-          Take: columns="vector, _rowid, _distance, (text)"
-            CoalesceBatchesExec: target_batch_size=1024
-              GlobalLimitExec: skip=0, fetch=10
-                FilterExec: _distance@2 IS NOT NULL
-                  SortExec: TopK(fetch=10), expr=[_distance@2 ASC NULLS LAST], preserve_partitioning=[false]
-                    KNNVectorDistance: metric=l2
-                      LanceScan: uri=..., projection=[vector], row_id=true, row_addr=false, ordered=false
-        <BLANKLINE>
+            Take: columns="vector, _rowid, _distance, (text)"
+                CoalesceBatchesExec: target_batch_size=1024
+                GlobalLimitExec: skip=0, fetch=10
+                    FilterExec: _distance@2 IS NOT NULL
+                    SortExec: TopK(fetch=10), expr=[_distance@2 ASC NULLS LAST], preserve_partitioning=[false]
+                        KNNVectorDistance: metric=l2
+                        LanceScan: uri=..., projection=[vector], row_id=true, row_addr=false, ordered=false
        FTS Search Plan:
-        ProjectionExec: expr=[vector@2 as vector, text@3 as text, _score@1 as _score]
-          Take: columns="_rowid, _score, (vector), (text)"
-            CoalesceBatchesExec: target_batch_size=1024
-              GlobalLimitExec: skip=0, fetch=10
-                MatchQuery: query=hello
-        <BLANKLINE>
+        LanceScan: uri=..., projection=[vector, text], row_id=false, row_addr=false, ordered=true

        Parameters
        ----------
--- a/python/python/lancedb/remote/table.py
+++ b/python/python/lancedb/remote/table.py
@@ -18,7 +18,7 @@ from lancedb._lancedb import (
    UpdateResult,
 )
 from lancedb.embeddings.base import EmbeddingFunctionConfig
-from lancedb.index import FTS, BTree, Bitmap, HnswSq, IvfFlat, IvfPq, LabelList
+from lancedb.index import FTS, BTree, Bitmap, HnswPq, HnswSq, IvfFlat, IvfPq, LabelList
 from lancedb.remote.db import LOOP
 import pyarrow as pa

@@ -89,7 +89,7 @@ class RemoteTable(Table):

    def to_pandas(self):
        """to_pandas() is not yet supported on LanceDB cloud."""
-        raise NotImplementedError("to_pandas() is not yet supported on LanceDB cloud.")
+        return NotImplementedError("to_pandas() is not yet supported on LanceDB cloud.")

    def checkout(self, version: Union[int, str]):
        return LOOP.run(self._table.checkout(version))
@@ -186,8 +186,6 @@ class RemoteTable(Table):
        accelerator: Optional[str] = None,
        index_type="vector",
        wait_timeout: Optional[timedelta] = None,
-        *,
-        num_bits: int = 8,
    ):
        """Create an index on the table.
        Currently, the only parameters that matter are
@@ -222,6 +220,11 @@ class RemoteTable(Table):
        >>> table.create_index("l2", "vector") # doctest: +SKIP
        """

+        if num_partitions is not None:
+            logging.warning(
+                "num_partitions is not supported on LanceDB cloud."
+                "This parameter will be tuned automatically."
+            )
        if num_sub_vectors is not None:
            logging.warning(
                "num_sub_vectors is not supported on LanceDB cloud."
@@ -241,21 +244,13 @@ class RemoteTable(Table):

        index_type = index_type.upper()
        if index_type == "VECTOR" or index_type == "IVF_PQ":
-            config = IvfPq(
-                distance_type=metric,
-                num_partitions=num_partitions,
-                num_sub_vectors=num_sub_vectors,
-                num_bits=num_bits,
-            )
+            config = IvfPq(distance_type=metric)
        elif index_type == "IVF_HNSW_PQ":
-            raise ValueError(
-                "IVF_HNSW_PQ is not supported on LanceDB cloud."
-                "Please use IVF_HNSW_SQ instead."
-            )
+            config = HnswPq(distance_type=metric)
        elif index_type == "IVF_HNSW_SQ":
-            config = HnswSq(distance_type=metric, num_partitions=num_partitions)
+            config = HnswSq(distance_type=metric)
        elif index_type == "IVF_FLAT":
-            config = IvfFlat(distance_type=metric, num_partitions=num_partitions)
+            config = IvfFlat(distance_type=metric)
        else:
            raise ValueError(
                f"Unknown vector index type: {index_type}. Valid options are"
--- a/python/python/tests/test_query.py
+++ b/python/python/tests/test_query.py
@@ -775,82 +775,6 @@ async def test_explain_plan_async(table_async: AsyncTable):
    assert "KNN" in plan


-@pytest.mark.asyncio
-async def test_explain_plan_fts(table_async: AsyncTable):
-    """Test explain plan for FTS queries"""
-    # Create FTS index
-    from lancedb.index import FTS
-
-    await table_async.create_index("text", config=FTS())
-
-    # Test pure FTS query
-    query = await table_async.search("dog", query_type="fts", fts_columns="text")
-    plan = await query.explain_plan()
-    # Should show FTS details (issue #2465 is now fixed)
-    assert "MatchQuery: query=dog" in plan
-    assert "GlobalLimitExec" in plan  # Default limit
-
-    # Test FTS query with limit
-    query_with_limit = await table_async.search(
-        "dog", query_type="fts", fts_columns="text"
-    )
-    plan_with_limit = await query_with_limit.limit(1).explain_plan()
-    assert "MatchQuery: query=dog" in plan_with_limit
-    assert "GlobalLimitExec: skip=0, fetch=1" in plan_with_limit
-
-    # Test FTS query with offset and limit
-    query_with_offset = await table_async.search(
-        "dog", query_type="fts", fts_columns="text"
-    )
-    plan_with_offset = await query_with_offset.offset(1).limit(1).explain_plan()
-    assert "MatchQuery: query=dog" in plan_with_offset
-    assert "GlobalLimitExec: skip=1, fetch=1" in plan_with_offset
-
-
-@pytest.mark.asyncio
-async def test_explain_plan_vector_with_limit_offset(table_async: AsyncTable):
-    """Test explain plan for vector queries with limit and offset"""
-    # Test vector query with limit
-    plan_with_limit = await (
-        table_async.query().nearest_to(pa.array([1, 2])).limit(1).explain_plan()
-    )
-    assert "KNN" in plan_with_limit
-    assert "GlobalLimitExec: skip=0, fetch=1" in plan_with_limit
-
-    # Test vector query with offset and limit
-    plan_with_offset = await (
-        table_async.query()
-        .nearest_to(pa.array([1, 2]))
-        .offset(1)
-        .limit(1)
-        .explain_plan()
-    )
-    assert "KNN" in plan_with_offset
-    assert "GlobalLimitExec: skip=1, fetch=1" in plan_with_offset
-
-
-@pytest.mark.asyncio
-async def test_explain_plan_with_filters(table_async: AsyncTable):
-    """Test explain plan for queries with filters"""
-    # Test vector query with filter
-    plan_with_filter = await (
-        table_async.query().nearest_to(pa.array([1, 2])).where("id = 1").explain_plan()
-    )
-    assert "KNN" in plan_with_filter
-    assert "FilterExec" in plan_with_filter
-
-    # Test FTS query with filter
-    from lancedb.index import FTS
-
-    await table_async.create_index("text", config=FTS())
-    query_fts_filter = await table_async.search(
-        "dog", query_type="fts", fts_columns="text"
-    )
-    plan_fts_filter = await query_fts_filter.where("id = 1").explain_plan()
-    assert "MatchQuery: query=dog" in plan_fts_filter
-    assert "FilterExec: id@" in plan_fts_filter  # Should show filter details
-
-
@pytest.mark.asyncio
 async def test_query_camelcase_async(tmp_path):
    db = await lancedb.connect_async(tmp_path)
--- a/python/python/tests/test_remote_db.py
+++ b/python/python/tests/test_remote_db.py
@@ -210,25 +210,6 @@ async def test_retry_error():
        assert cause.status_code == 429


-def test_table_unimplemented_functions():
-    def handler(request):
-        if request.path == "/v1/table/test/create/?mode=create":
-            request.send_response(200)
-            request.send_header("Content-Type", "application/json")
-            request.end_headers()
-            request.wfile.write(b"{}")
-        else:
-            request.send_response(404)
-            request.end_headers()
-
-    with mock_lancedb_connection(handler) as db:
-        table = db.create_table("test", [{"id": 1}])
-        with pytest.raises(NotImplementedError):
-            table.to_arrow()
-        with pytest.raises(NotImplementedError):
-            table.to_pandas()
-
-
 def test_table_add_in_threadpool():
    def handler(request):
        if request.path == "/v1/table/test/insert/":
--- a/python/src/query.rs
+++ b/python/src/query.rs
@@ -52,7 +52,7 @@ impl FromPyObject<'_> for PyLanceDB<FtsQuery> {
                let operator = ob.getattr("operator")?.extract::<String>()?;
                let prefix_length = ob.getattr("prefix_length")?.extract()?;

-                Ok(Self(
+                Ok(PyLanceDB(
                    MatchQuery::new(query)
                        .with_column(Some(column))
                        .with_boost(boost)
@@ -70,7 +70,7 @@ impl FromPyObject<'_> for PyLanceDB<FtsQuery> {
                let column = ob.getattr("column")?.extract()?;
                let slop = ob.getattr("slop")?.extract()?;

-                Ok(Self(
+                Ok(PyLanceDB(
                    PhraseQuery::new(query)
                        .with_column(Some(column))
                        .with_slop(slop)
@@ -78,10 +78,10 @@ impl FromPyObject<'_> for PyLanceDB<FtsQuery> {
                ))
            }
            "BoostQuery" => {
-                let positive: Self = ob.getattr("positive")?.extract()?;
-                let negative: Self = ob.getattr("negative")?.extract()?;
+                let positive: PyLanceDB<FtsQuery> = ob.getattr("positive")?.extract()?;
+                let negative: PyLanceDB<FtsQuery> = ob.getattr("negative")?.extract()?;
                let negative_boost = ob.getattr("negative_boost")?.extract()?;
-                Ok(Self(
+                Ok(PyLanceDB(
                    BoostQuery::new(positive.0, negative.0, negative_boost).into(),
                ))
            }
@@ -103,17 +103,18 @@ impl FromPyObject<'_> for PyLanceDB<FtsQuery> {
                let op = Operator::try_from(operator.as_str())
                    .map_err(|e| PyValueError::new_err(format!("Invalid operator: {}", e)))?;

-                Ok(Self(q.with_operator(op).into()))
+                Ok(PyLanceDB(q.with_operator(op).into()))
            }
            "BooleanQuery" => {
-                let queries: Vec<(String, Self)> = ob.getattr("queries")?.extract()?;
+                let queries: Vec<(String, PyLanceDB<FtsQuery>)> =
+                    ob.getattr("queries")?.extract()?;
                let mut sub_queries = Vec::with_capacity(queries.len());
                for (occur, q) in queries {
                    let occur = Occur::try_from(occur.as_str())
                        .map_err(|e| PyValueError::new_err(e.to_string()))?;
                    sub_queries.push((occur, q.0));
                }
-                Ok(Self(BooleanQuery::new(sub_queries).into()))
+                Ok(PyLanceDB(BooleanQuery::new(sub_queries).into()))
            }
            name => Err(PyValueError::new_err(format!(
                "Unsupported FTS query type: {}",
@@ -154,8 +155,8 @@ impl<'py> IntoPyObject<'py> for PyLanceDB<FtsQuery> {
                    .call((query.terms, query.column.unwrap()), Some(&kwargs))
            }
            FtsQuery::Boost(query) => {
-                let positive = Self(query.positive.as_ref().clone()).into_pyobject(py)?;
-                let negative = Self(query.negative.as_ref().clone()).into_pyobject(py)?;
+                let positive = PyLanceDB(query.positive.as_ref().clone()).into_pyobject(py)?;
+                let negative = PyLanceDB(query.negative.as_ref().clone()).into_pyobject(py)?;
                let kwargs = PyDict::new(py);
                kwargs.set_item("negative_boost", query.negative_boost)?;
                namespace
@@ -181,13 +182,13 @@ impl<'py> IntoPyObject<'py> for PyLanceDB<FtsQuery> {
                    query.should.len() + query.must.len() + query.must_not.len(),
                );
                for q in query.should {
-                    queries.push((Occur::Should.into(), Self(q).into_pyobject(py)?));
+                    queries.push((Occur::Should.into(), PyLanceDB(q).into_pyobject(py)?));
                }
                for q in query.must {
-                    queries.push((Occur::Must.into(), Self(q).into_pyobject(py)?));
+                    queries.push((Occur::Must.into(), PyLanceDB(q).into_pyobject(py)?));
                }
                for q in query.must_not {
-                    queries.push((Occur::MustNot.into(), Self(q).into_pyobject(py)?));
+                    queries.push((Occur::MustNot.into(), PyLanceDB(q).into_pyobject(py)?));
                }

                namespace
@@ -562,10 +563,7 @@ impl FTSQuery {
    }

    pub fn explain_plan(self_: PyRef<'_, Self>, verbose: bool) -> PyResult<Bound<'_, PyAny>> {
-        let inner = self_
-            .inner
-            .clone()
-            .full_text_search(self_.fts_query.clone());
+        let inner = self_.inner.clone();
        future_into_py(self_.py(), async move {
            inner
                .explain_plan(verbose)
@@ -575,10 +573,7 @@ impl FTSQuery {
    }

    pub fn analyze_plan(self_: PyRef<'_, Self>) -> PyResult<Bound<'_, PyAny>> {
-        let inner = self_
-            .inner
-            .clone()
-            .full_text_search(self_.fts_query.clone());
+        let inner = self_.inner.clone();
        future_into_py(self_.py(), async move {
            inner
                .analyze_plan()
--- a/rust/ffi/node/Cargo.toml
+++ b/rust/ffi/node/Cargo.toml
@@ -1,6 +1,6 @@
 [package]
 name = "lancedb-node"
-version = "0.21.1"
+version = "0.21.0"
 description = "Serverless, low-latency vector database for AI applications"
 license.workspace = true
 edition.workspace = true
--- a/rust/lancedb/Cargo.toml
+++ b/rust/lancedb/Cargo.toml
@@ -1,6 +1,6 @@
 [package]
 name = "lancedb"
-version = "0.21.1"
+version = "0.21.0"
 edition.workspace = true
 description = "LanceDB: A serverless, low-latency vector database for AI applications"
 license.workspace = true
--- a/rust/lancedb/src/catalog/listing.rs
+++ b/rust/lancedb/src/catalog/listing.rs
@@ -105,7 +105,7 @@ impl ListingCatalog {
    }

    async fn open_path(path: &str) -> Result<Self> {
-        let (object_store, base_path) = ObjectStore::from_uri(path).await?;
+        let (object_store, base_path) = ObjectStore::from_uri(path).await.unwrap();
        if object_store.is_local() {
            Self::try_create_dir(path).context(CreateDirSnafu { path })?;
        }
--- a/rust/lancedb/src/io/object_store.rs
+++ b/rust/lancedb/src/io/object_store.rs
@@ -107,7 +107,7 @@ impl ObjectStore for MirroringObjectStore {
        self.primary.delete(location).await
    }

-    fn list(&self, prefix: Option<&Path>) -> BoxStream<'static, Result<ObjectMeta>> {
+    fn list(&self, prefix: Option<&Path>) -> BoxStream<'_, Result<ObjectMeta>> {
        self.primary.list(prefix)
    }

--- a/rust/lancedb/src/io/object_store/io_tracking.rs
+++ b/rust/lancedb/src/io/object_store/io_tracking.rs
@@ -119,7 +119,7 @@ impl ObjectStore for IoTrackingStore {
        let result = self.target.get(location).await;
        if let Ok(result) = &result {
            let num_bytes = result.range.end - result.range.start;
-            self.record_read(num_bytes);
+            self.record_read(num_bytes as u64);
        }
        result
    }
@@ -128,12 +128,12 @@ impl ObjectStore for IoTrackingStore {
        let result = self.target.get_opts(location, options).await;
        if let Ok(result) = &result {
            let num_bytes = result.range.end - result.range.start;
-            self.record_read(num_bytes);
+            self.record_read(num_bytes as u64);
        }
        result
    }

-    async fn get_range(&self, location: &Path, range: std::ops::Range<u64>) -> OSResult<Bytes> {
+    async fn get_range(&self, location: &Path, range: std::ops::Range<usize>) -> OSResult<Bytes> {
        let result = self.target.get_range(location, range).await;
        if let Ok(result) = &result {
            self.record_read(result.len() as u64);
@@ -144,7 +144,7 @@ impl ObjectStore for IoTrackingStore {
    async fn get_ranges(
        &self,
        location: &Path,
-        ranges: &[std::ops::Range<u64>],
+        ranges: &[std::ops::Range<usize>],
    ) -> OSResult<Vec<Bytes>> {
        let result = self.target.get_ranges(location, ranges).await;
        if let Ok(result) = &result {
@@ -170,7 +170,7 @@ impl ObjectStore for IoTrackingStore {
        self.target.delete_stream(locations)
    }

-    fn list(&self, prefix: Option<&Path>) -> BoxStream<'static, OSResult<ObjectMeta>> {
+    fn list(&self, prefix: Option<&Path>) -> BoxStream<'_, OSResult<ObjectMeta>> {
        self.record_read(0);
        self.target.list(prefix)
    }
@@ -179,7 +179,7 @@ impl ObjectStore for IoTrackingStore {
        &self,
        prefix: Option<&Path>,
        offset: &Path,
-    ) -> BoxStream<'static, OSResult<ObjectMeta>> {
+    ) -> BoxStream<'_, OSResult<ObjectMeta>> {
        self.record_read(0);
        self.target.list_with_offset(prefix, offset)
    }
--- a/rust/lancedb/src/remote/table.rs
+++ b/rust/lancedb/src/remote/table.rs
@@ -57,8 +57,6 @@ use crate::{
 };

 const REQUEST_TIMEOUT_HEADER: HeaderName = HeaderName::from_static("x-request-timeout-ms");
-const METRIC_TYPE_KEY: &str = "metric_type";
-const INDEX_TYPE_KEY: &str = "index_type";

 pub struct RemoteTags<'a, S: HttpSend = Sender> {
    inner: &'a RemoteTable<S>,
@@ -999,53 +997,23 @@ impl<S: HttpSend> BaseTable for RemoteTable<S> {
            "column": column
        });

-        match index.index {
+        let (index_type, distance_type) = match index.index {
            // TODO: Should we pass the actual index parameters? SaaS does not
            // yet support them.
-            Index::IvfFlat(index) => {
-                body[INDEX_TYPE_KEY] = serde_json::Value::String("IVF_FLAT".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());
-                }
-            }
-            Index::IvfPq(index) => {
-                body[INDEX_TYPE_KEY] = serde_json::Value::String("IVF_PQ".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::IvfHnswSq(index) => {
-                body[INDEX_TYPE_KEY] = serde_json::Value::String("IVF_HNSW_SQ".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());
-                }
-            }
-            Index::BTree(_) => {
-                body[INDEX_TYPE_KEY] = serde_json::Value::String("BTREE".to_string());
-            }
-            Index::Bitmap(_) => {
-                body[INDEX_TYPE_KEY] = serde_json::Value::String("BITMAP".to_string());
-            }
-            Index::LabelList(_) => {
-                body[INDEX_TYPE_KEY] = serde_json::Value::String("LABEL_LIST".to_string());
-            }
+            Index::IvfFlat(index) => ("IVF_FLAT", Some(index.distance_type)),
+            Index::IvfPq(index) => ("IVF_PQ", Some(index.distance_type)),
+            Index::IvfHnswSq(index) => ("IVF_HNSW_SQ", Some(index.distance_type)),
+            Index::BTree(_) => ("BTREE", None),
+            Index::Bitmap(_) => ("BITMAP", None),
+            Index::LabelList(_) => ("LABEL_LIST", None),
            Index::FTS(fts) => {
-                body[INDEX_TYPE_KEY] = serde_json::Value::String("FTS".to_string());
                let params = serde_json::to_value(&fts).map_err(|e| Error::InvalidInput {
                    message: format!("failed to serialize FTS index params {:?}", e),
                })?;
                for (key, value) in params.as_object().unwrap() {
                    body[key] = value.clone();
                }
+                ("FTS", None)
            }
            Index::Auto => {
                let schema = self.schema().await?;
@@ -1055,11 +1023,9 @@ impl<S: HttpSend> BaseTable for RemoteTable<S> {
                        message: format!("Column {} not found in schema", column),
                    })?;
                if supported_vector_data_type(field.data_type()) {
-                    body[INDEX_TYPE_KEY] = serde_json::Value::String("IVF_PQ".to_string());
-                    body[METRIC_TYPE_KEY] =
-                        serde_json::Value::String(DistanceType::L2.to_string().to_lowercase());
+                    ("IVF_PQ", Some(DistanceType::L2))
                } else if supported_btree_data_type(field.data_type()) {
-                    body[INDEX_TYPE_KEY] = serde_json::Value::String("BTREE".to_string());
+                    ("BTREE", None)
                } else {
                    return Err(Error::NotSupported {
                        message: format!(
@@ -1076,6 +1042,12 @@ impl<S: HttpSend> BaseTable for RemoteTable<S> {
                })
            }
        };
+        body["index_type"] = serde_json::Value::String(index_type.into());
+        if let Some(distance_type) = distance_type {
+            // Phalanx expects this to be lowercase right now.
+            body["metric_type"] =
+                serde_json::Value::String(distance_type.to_string().to_lowercase());
+        }

        let request = request.json(&body);

@@ -1457,12 +1429,11 @@ mod tests {
    use chrono::{DateTime, Utc};
    use futures::{future::BoxFuture, StreamExt, TryFutureExt};
    use lance_index::scalar::inverted::query::MatchQuery;
-    use lance_index::scalar::{FullTextSearchQuery, InvertedIndexParams};
+    use lance_index::scalar::FullTextSearchQuery;
    use reqwest::Body;
    use rstest::rstest;
-    use serde_json::json;

-    use crate::index::vector::{IvfFlatIndexBuilder, IvfHnswSqIndexBuilder};
+    use crate::index::vector::IvfFlatIndexBuilder;
    use crate::remote::db::DEFAULT_SERVER_VERSION;
    use crate::remote::JSON_CONTENT_TYPE;
    use crate::{
@@ -2462,79 +2433,29 @@ mod tests {
        let cases = [
            (
                "IVF_FLAT",
-                json!({
-                    "metric_type": "hamming",
-                }),
+                Some("hamming"),
                Index::IvfFlat(IvfFlatIndexBuilder::default().distance_type(DistanceType::Hamming)),
            ),
-            (
-                "IVF_FLAT",
-                json!({
-                    "metric_type": "hamming",
-                    "num_partitions": 128,
-                }),
-                Index::IvfFlat(
-                    IvfFlatIndexBuilder::default()
-                        .distance_type(DistanceType::Hamming)
-                        .num_partitions(128),
-                ),
-            ),
+            ("IVF_PQ", Some("l2"), Index::IvfPq(Default::default())),
            (
                "IVF_PQ",
-                json!({
-                    "metric_type": "l2",
-                }),
-                Index::IvfPq(Default::default()),
-            ),
-            (
-                "IVF_PQ",
-                json!({
-                    "metric_type": "cosine",
-                    "num_partitions": 128,
-                    "num_bits": 4,
-                }),
-                Index::IvfPq(
-                    IvfPqIndexBuilder::default()
-                        .distance_type(DistanceType::Cosine)
-                        .num_partitions(128)
-                        .num_bits(4),
-                ),
+                Some("cosine"),
+                Index::IvfPq(IvfPqIndexBuilder::default().distance_type(DistanceType::Cosine)),
            ),
            (
                "IVF_HNSW_SQ",
-                json!({
-                    "metric_type": "l2",
-                }),
+                Some("l2"),
                Index::IvfHnswSq(Default::default()),
            ),
-            (
-                "IVF_HNSW_SQ",
-                json!({
-                    "metric_type": "l2",
-                    "num_partitions": 128,
-                }),
-                Index::IvfHnswSq(
-                    IvfHnswSqIndexBuilder::default()
-                        .distance_type(DistanceType::L2)
-                        .num_partitions(128),
-                ),
-            ),
            // HNSW_PQ isn't yet supported on SaaS
-            ("BTREE", json!({}), Index::BTree(Default::default())),
-            ("BITMAP", json!({}), Index::Bitmap(Default::default())),
-            (
-                "LABEL_LIST",
-                json!({}),
-                Index::LabelList(Default::default()),
-            ),
-            (
-                "FTS",
-                serde_json::to_value(InvertedIndexParams::default()).unwrap(),
-                Index::FTS(Default::default()),
-            ),
+            ("BTREE", None, Index::BTree(Default::default())),
+            ("BITMAP", None, Index::Bitmap(Default::default())),
+            ("LABEL_LIST", None, Index::LabelList(Default::default())),
+            ("FTS", None, Index::FTS(Default::default())),
        ];

-        for (index_type, expected_body, index) in cases {
+        for (index_type, distance_type, index) in cases {
+            let params = index.clone();
            let table = Table::new_with_handler("my_table", move |request| {
                assert_eq!(request.method(), "POST");
                assert_eq!(request.url().path(), "/v1/table/my_table/create_index/");
@@ -2544,9 +2465,19 @@ mod tests {
                );
                let body = request.body().unwrap().as_bytes().unwrap();
                let body: serde_json::Value = serde_json::from_slice(body).unwrap();
-                let mut expected_body = expected_body.clone();
-                expected_body["column"] = "a".into();
-                expected_body[INDEX_TYPE_KEY] = index_type.into();
+                let mut expected_body = serde_json::json!({
+                    "column": "a",
+                    "index_type": index_type,
+                });
+                if let Some(distance_type) = distance_type {
+                    expected_body["metric_type"] = distance_type.to_lowercase().into();
+                }
+                if let Index::FTS(fts) = &params {
+                    let params = serde_json::to_value(fts).unwrap();
+                    for (key, value) in params.as_object().unwrap() {
+                        expected_body[key] = value.clone();
+                    }
+                }

                assert_eq!(body, expected_body);

--- a/rust/lancedb/src/table/datafusion.rs
+++ b/rust/lancedb/src/table/datafusion.rs
@@ -392,18 +392,9 @@ pub mod tests {
                } else {
                    expected_line.trim()
                };
-                assert_eq!(
-                    &actual_trimmed[..expected_trimmed.len()],
-                    expected_trimmed,
-                    "\nactual:\n{physical_plan}\nexpected:\n{expected}"
-                );
+                assert_eq!(&actual_trimmed[..expected_trimmed.len()], expected_trimmed);
            }
-            assert_eq!(
-                lines_checked,
-                expected.lines().count(),
-                "\nlines_checked:\n{lines_checked}\nexpected:\n{}",
-                expected.lines().count()
-            );
+            assert_eq!(lines_checked, expected.lines().count());
        }
    }

@@ -486,9 +477,9 @@ pub mod tests {
        TestFixture::check_plan(
            plan,
            "MetadataEraserExec
+             RepartitionExec:...
             CoalesceBatchesExec:...
             FilterExec: i@0 >= 5
-             RepartitionExec:...
             ProjectionExec:...
             LanceScan:...",
        )
--- a/rust/lancedb/src/table/dataset.rs
+++ b/rust/lancedb/src/table/dataset.rs
@@ -129,9 +129,7 @@ impl DatasetRef {
                dataset: ref mut ds,
                ..
            } => {
-                if dataset.manifest().version > ds.manifest().version {
-                    *ds = dataset;
-                }
+                *ds = dataset;
            }
            _ => unreachable!("Dataset should be in latest mode at this point"),
        }