fix(node): accept Arrow metadata across JavaScript realms (#3904 )

## Summary - accept genuine Arrow metadata maps created in another JavaScript realm - validate every metadata entry and clone it into a local Map - cover an Arrow 15 VM-realm table through the public fromDataToBuffer boundary - retain structural typing for nested and dictionary Arrow data ## Root cause The sanitizer used a local-realm instanceof Map check for schema and field metadata. A genuine Map created in another JavaScript realm has the required internal Map state but fails that identity check, so fromDataToBuffer rejected the foreign table before serializing its rows. ## Scope This fixes the distinct JavaScript-realm sanitizer failure identified during review. It does not establish the cause of the S3/compaction panic reported in #1525, so that issue remains open. ## Validation - pnpm test --runInBand (707 passed, 5 skipped) - pnpm test --runInBand __test__/arrow.test.ts (189 passed) - pnpm build - pnpm lint - pnpm run docs Related to #1525  --------- Co-authored-by: Gatefixer <313497061+lancedb-gatefixer[bot]@users.noreply.github.com> Co-authored-by: Xuanwo <github@xuanwo.io>
feat(python): accept expressions in update filters (#3876 )
2026-08-27 16:38:31 +00:00 · 2026-08-27 23:35:02 +08:00 · 2026-08-27 20:28:21 +08:00 · 2026-08-27 17:10:51 +08:00 · 2026-08-27 15:47:18 +08:00 · 2026-08-27 13:42:30 +08:00
111 changed files with 6654 additions and 1114 deletions
@@ -1,5 +1,5 @@
 [tool.bumpversion]
-current_version = "0.38.0-beta.7"
+current_version = "0.38.0-beta.11"
 parse = """(?x)
    (?P<major>0|[1-9]\\d*)\\.
    (?P<minor>0|[1-9]\\d*)\\.
@@ -3455,8 +3455,8 @@ checksum = "42703706b716c37f96a77aea830392ad231f44c9e9a67872fa5548707e11b11c"

 [[package]]
 name = "fsst"
-version = "11.0.0-beta.22"
-source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
+version = "12.0.0-beta.2"
+source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
 dependencies = [
 "arrow-array",
 "rand 0.9.5",
@@ -4815,8 +4815,8 @@ checksum = "e037a2e1d8d5fdbd49b16a4ea09d5d6401c1f29eca5ff29d03d3824dba16256a"

 [[package]]
 name = "lance"
-version = "11.0.0-beta.22"
-source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
+version = "12.0.0-beta.2"
+source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
 dependencies = [
 "arc-swap",
 "arrow",
@@ -4888,8 +4888,8 @@ dependencies = [

 [[package]]
 name = "lance-arrow"
-version = "11.0.0-beta.22"
-source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
+version = "12.0.0-beta.2"
+source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
 dependencies = [
 "arrow-array",
 "arrow-buffer",
@@ -4911,7 +4911,7 @@ dependencies = [
 [[package]]
 name = "lance-arrow-scalar"
 version = "58.0.0"
-source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
+source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
 dependencies = [
 "arrow-array",
 "arrow-buffer",
@@ -4925,7 +4925,7 @@ dependencies = [
 [[package]]
 name = "lance-arrow-stats"
 version = "58.0.0"
-source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
+source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
 dependencies = [
 "arrow-array",
 "arrow-schema",
@@ -4934,8 +4934,8 @@ dependencies = [

 [[package]]
 name = "lance-bitpacking"
-version = "11.0.0-beta.22"
-source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
+version = "12.0.0-beta.2"
+source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
 dependencies = [
 "arrayref",
 "crunchy",
@@ -4945,8 +4945,8 @@ dependencies = [

 [[package]]
 name = "lance-core"
-version = "11.0.0-beta.22"
-source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
+version = "12.0.0-beta.2"
+source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
 dependencies = [
 "arrow-array",
 "arrow-buffer",
@@ -4983,8 +4983,8 @@ dependencies = [

 [[package]]
 name = "lance-datafusion"
-version = "11.0.0-beta.22"
-source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
+version = "12.0.0-beta.2"
+source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
 dependencies = [
 "arrow",
 "arrow-array",
@@ -5013,8 +5013,8 @@ dependencies = [

 [[package]]
 name = "lance-datagen"
-version = "11.0.0-beta.22"
-source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
+version = "12.0.0-beta.2"
+source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
 dependencies = [
 "arrow",
 "arrow-array",
@@ -5031,8 +5031,8 @@ dependencies = [

 [[package]]
 name = "lance-derive"
-version = "11.0.0-beta.22"
-source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
+version = "12.0.0-beta.2"
+source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
 dependencies = [
 "proc-macro2",
 "quote",
@@ -5041,8 +5041,8 @@ dependencies = [

 [[package]]
 name = "lance-encoding"
-version = "11.0.0-beta.22"
-source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
+version = "12.0.0-beta.2"
+source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
 dependencies = [
 "arrow-arith",
 "arrow-array",
@@ -5075,8 +5075,8 @@ dependencies = [

 [[package]]
 name = "lance-file"
-version = "11.0.0-beta.22"
-source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
+version = "12.0.0-beta.2"
+source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
 dependencies = [
 "arrow-arith",
 "arrow-array",
@@ -5107,8 +5107,8 @@ dependencies = [

 [[package]]
 name = "lance-index"
-version = "11.0.0-beta.22"
-source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
+version = "12.0.0-beta.2"
+source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
 dependencies = [
 "arc-swap",
 "arrow",
@@ -5172,8 +5172,8 @@ dependencies = [

 [[package]]
 name = "lance-index-core"
-version = "11.0.0-beta.22"
-source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
+version = "12.0.0-beta.2"
+source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
 dependencies = [
 "arrow-array",
 "arrow-schema",
@@ -5195,8 +5195,8 @@ dependencies = [

 [[package]]
 name = "lance-io"
-version = "11.0.0-beta.22"
-source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
+version = "12.0.0-beta.2"
+source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
 dependencies = [
 "arrow",
 "arrow-array",
@@ -5236,8 +5236,8 @@ dependencies = [

 [[package]]
 name = "lance-linalg"
-version = "11.0.0-beta.22"
-source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
+version = "12.0.0-beta.2"
+source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
 dependencies = [
 "arrow-array",
 "arrow-schema",
@@ -5251,8 +5251,8 @@ dependencies = [

 [[package]]
 name = "lance-namespace"
-version = "11.0.0-beta.22"
-source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
+version = "12.0.0-beta.2"
+source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
 dependencies = [
 "arrow",
 "async-trait",
@@ -5264,8 +5264,8 @@ dependencies = [

 [[package]]
 name = "lance-namespace-impls"
-version = "11.0.0-beta.22"
-source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
+version = "12.0.0-beta.2"
+source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
 dependencies = [
 "arrow",
 "arrow-ipc",
@@ -5318,8 +5318,8 @@ dependencies = [

 [[package]]
 name = "lance-select"
-version = "11.0.0-beta.22"
-source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
+version = "12.0.0-beta.2"
+source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
 dependencies = [
 "arrow-array",
 "arrow-buffer",
@@ -5333,8 +5333,8 @@ dependencies = [

 [[package]]
 name = "lance-table"
-version = "11.0.0-beta.22"
-source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
+version = "12.0.0-beta.2"
+source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
 dependencies = [
 "arrow",
 "arrow-array",
@@ -5374,8 +5374,8 @@ dependencies = [

 [[package]]
 name = "lance-testing"
-version = "11.0.0-beta.22"
-source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
+version = "12.0.0-beta.2"
+source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
 dependencies = [
 "arrow-array",
 "arrow-schema",
@@ -5388,8 +5388,8 @@ dependencies = [

 [[package]]
 name = "lance-tokenizer"
-version = "11.0.0-beta.22"
-source = "git+https://github.com/lance-format/lance.git?tag=v11.0.0-beta.22#ea3cb4d799c468232735e9bcb43959487aca5c20"
+version = "12.0.0-beta.2"
+source = "git+https://github.com/lance-format/lance.git?tag=v12.0.0-beta.2#dafa4642658d996b3e31dde91e02f72db7860d7e"
 dependencies = [
 "frostem",
 "icu_segmenter",
@@ -5402,7 +5402,7 @@ dependencies = [

 [[package]]
 name = "lancedb"
-version = "0.38.0-beta.7"
+version = "0.38.0-beta.11"
 dependencies = [
 "ahash",
 "anyhow",
@@ -5490,7 +5490,7 @@ dependencies = [

 [[package]]
 name = "lancedb-nodejs"
-version = "0.38.0-beta.7"
+version = "0.38.0-beta.11"
 dependencies = [
 "arrow-array",
 "arrow-buffer",
@@ -5515,7 +5515,7 @@ dependencies = [

 [[package]]
 name = "lancedb-python"
-version = "0.38.0-beta.7"
+version = "0.38.0-beta.11"
 dependencies = [
 "arrow",
 "async-trait",
@@ -13,20 +13,20 @@ categories = ["database-implementations"]
 rust-version = "1.91.0"

 [workspace.dependencies]
-lance = { "version" = "=11.0.0-beta.22", default-features = false, "tag" = "v11.0.0-beta.22", "git" = "https://github.com/lance-format/lance.git" }
-lance-core = { "version" = "=11.0.0-beta.22", "tag" = "v11.0.0-beta.22", "git" = "https://github.com/lance-format/lance.git" }
-lance-datagen = { "version" = "=11.0.0-beta.22", "tag" = "v11.0.0-beta.22", "git" = "https://github.com/lance-format/lance.git" }
-lance-file = { "version" = "=11.0.0-beta.22", "tag" = "v11.0.0-beta.22", "git" = "https://github.com/lance-format/lance.git" }
-lance-io = { "version" = "=11.0.0-beta.22", default-features = false, "tag" = "v11.0.0-beta.22", "git" = "https://github.com/lance-format/lance.git" }
-lance-index = { "version" = "=11.0.0-beta.22", "tag" = "v11.0.0-beta.22", "git" = "https://github.com/lance-format/lance.git" }
-lance-linalg = { "version" = "=11.0.0-beta.22", "tag" = "v11.0.0-beta.22", "git" = "https://github.com/lance-format/lance.git" }
-lance-namespace = { "version" = "=11.0.0-beta.22", "tag" = "v11.0.0-beta.22", "git" = "https://github.com/lance-format/lance.git" }
-lance-namespace-impls = { "version" = "=11.0.0-beta.22", default-features = false, "tag" = "v11.0.0-beta.22", "git" = "https://github.com/lance-format/lance.git" }
-lance-table = { "version" = "=11.0.0-beta.22", "tag" = "v11.0.0-beta.22", "git" = "https://github.com/lance-format/lance.git" }
-lance-testing = { "version" = "=11.0.0-beta.22", "tag" = "v11.0.0-beta.22", "git" = "https://github.com/lance-format/lance.git" }
-lance-datafusion = { "version" = "=11.0.0-beta.22", "tag" = "v11.0.0-beta.22", "git" = "https://github.com/lance-format/lance.git" }
-lance-encoding = { "version" = "=11.0.0-beta.22", "tag" = "v11.0.0-beta.22", "git" = "https://github.com/lance-format/lance.git" }
-lance-arrow = { "version" = "=11.0.0-beta.22", "tag" = "v11.0.0-beta.22", "git" = "https://github.com/lance-format/lance.git" }
+lance = { "version" = "=12.0.0-beta.2", default-features = false, "tag" = "v12.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
+lance-core = { "version" = "=12.0.0-beta.2", "tag" = "v12.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
+lance-datagen = { "version" = "=12.0.0-beta.2", "tag" = "v12.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
+lance-file = { "version" = "=12.0.0-beta.2", "tag" = "v12.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
+lance-io = { "version" = "=12.0.0-beta.2", default-features = false, "tag" = "v12.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
+lance-index = { "version" = "=12.0.0-beta.2", "tag" = "v12.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
+lance-linalg = { "version" = "=12.0.0-beta.2", "tag" = "v12.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
+lance-namespace = { "version" = "=12.0.0-beta.2", "tag" = "v12.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
+lance-namespace-impls = { "version" = "=12.0.0-beta.2", default-features = false, "tag" = "v12.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
+lance-table = { "version" = "=12.0.0-beta.2", "tag" = "v12.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
+lance-testing = { "version" = "=12.0.0-beta.2", "tag" = "v12.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
+lance-datafusion = { "version" = "=12.0.0-beta.2", "tag" = "v12.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
+lance-encoding = { "version" = "=12.0.0-beta.2", "tag" = "v12.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
+lance-arrow = { "version" = "=12.0.0-beta.2", "tag" = "v12.0.0-beta.2", "git" = "https://github.com/lance-format/lance.git" }
 lancedb = { path = "rust/lancedb", default-features = false }
 ahash = "0.8"
 # Note that this one does not include pyarrow
@@ -14,7 +14,7 @@ Add the following dependency to your `pom.xml`:
 <dependency>
    <groupId>com.lancedb</groupId>
    <artifactId>lancedb-core</artifactId>
-    <version>0.38.0-beta.7</version>
+    <version>0.38.0-beta.11</version>
 </dependency>
 ```

@@ -0,0 +1,518 @@
+[**@lancedb/lancedb**](../README.md) • **Docs**
+
+***
+
+[@lancedb/lancedb](../globals.md) / AutoQuery
+
+# Class: AutoQuery
+
+A builder for automatic string searches.
+
+Automatic search determines whether to use full-text or vector search from
+the table revision selected for each execution. This builder exposes the
+common operations supported by both query families.
+
+## Extends
+
+- `StandardQueryBase`&lt;`NativeQuery` \| `NativeVectorQuery`&gt;
+
+## Properties
+
+### inner
+
+```ts
+protected inner: Query | VectorQuery | Promise<Query | VectorQuery>;
+```
+
+#### Inherited from
+
+`StandardQueryBase.inner`
+
+## Methods
+
+### analyzePlan()
+
+```ts
+analyzePlan(distributedMetrics?): Promise<string>
+```
+
+Executes the query and returns the physical query plan annotated with runtime metrics.
+
+This is useful for debugging and performance analysis, as it shows how the query was executed
+and includes metrics such as elapsed time, rows processed, and I/O statistics.
+
+#### Parameters
+
+* **distributedMetrics?**: [`AnalyzePlanDistributedMetrics`](../type-aliases/AnalyzePlanDistributedMetrics.md)
+    How distributed worker metrics are displayed for remote query plans.
+    Defaults to `"aggregate"`.
+
+#### Returns
+
+`Promise`&lt;`string`&gt;
+
+A query execution plan with runtime metrics for each step.
+
+#### Example
+
+```ts
+import * as lancedb from "@lancedb/lancedb"
+
+const db = await lancedb.connect("./.lancedb");
+const table = await db.createTable("my_table", [
+  { vector: [1.1, 0.9], id: "1" },
+]);
+
+const plan = await table.query().nearestTo([0.5, 0.2]).analyzePlan();
+
+Example output (with runtime metrics inlined):
+AnalyzeExec verbose=true, metrics=[]
+ ProjectionExec: expr=[id@3 as id, vector@0 as vector, _distance@2 as _distance], metrics=[output_rows=1, elapsed_compute=3.292µs]
+  Take: columns="vector, _rowid, _distance, (id)", metrics=[output_rows=1, elapsed_compute=66.001µs, batches_processed=1, bytes_read=8, iops=1, requests=1]
+   CoalesceBatchesExec: target_batch_size=1024, metrics=[output_rows=1, elapsed_compute=3.333µs]
+    GlobalLimitExec: skip=0, fetch=10, metrics=[output_rows=1, elapsed_compute=167ns]
+     FilterExec: _distance@2 IS NOT NULL, metrics=[output_rows=1, elapsed_compute=8.542µs]
+      SortExec: TopK(fetch=10), expr=[_distance@2 ASC NULLS LAST], metrics=[output_rows=1, elapsed_compute=63.25µs, row_replacements=1]
+       KNNVectorDistance: metric=l2, metrics=[output_rows=1, elapsed_compute=114.333µs, output_batches=1]
+        LanceScan: uri=/path/to/data, projection=[vector], row_id=true, row_addr=false, ordered=false, metrics=[output_rows=1, elapsed_compute=103.626µs, bytes_read=549, iops=2, requests=2]
+```
+
+#### Inherited from
+
+`StandardQueryBase.analyzePlan`
+
+***
+
+### execute()
+
+```ts
+protected execute(options?): AsyncGenerator<RecordBatch<any>, void, unknown>
+```
+
+Execute the query and return the results as an
+
+#### Parameters
+
+* **options?**: `Partial`&lt;[`QueryExecutionOptions`](../interfaces/QueryExecutionOptions.md)&gt;
+
+#### Returns
+
+`AsyncGenerator`&lt;`RecordBatch`&lt;`any`&gt;, `void`, `unknown`&gt;
+
+#### See
+
+ - AsyncIterator
+of
+ - RecordBatch.
+
+By default, LanceDb will use many threads to calculate results and, when
+the result set is large, multiple batches will be processed at one time.
+This readahead is limited however and backpressure will be applied if this
+stream is consumed slowly (this constrains the maximum memory used by a
+single query)
+
+#### Inherited from
+
+`StandardQueryBase.execute`
+
+***
+
+### explainPlan()
+
+```ts
+explainPlan(verbose): Promise<string>
+```
+
+Generates an explanation of the query execution plan.
+
+#### Parameters
+
+* **verbose**: `boolean` = `false`
+    If true, provides a more detailed explanation. Defaults to false.
+
+#### Returns
+
+`Promise`&lt;`string`&gt;
+
+A Promise that resolves to a string containing the query execution plan explanation.
+
+#### Example
+
+```ts
+import * as lancedb from "@lancedb/lancedb"
+const db = await lancedb.connect("./.lancedb");
+const table = await db.createTable("my_table", [
+  { vector: [1.1, 0.9], id: "1" },
+]);
+const plan = await table.query().nearestTo([0.5, 0.2]).explainPlan();
+```
+
+#### Inherited from
+
+`StandardQueryBase.explainPlan`
+
+***
+
+### fastSearch()
+
+```ts
+fastSearch(): this
+```
+
+Skip searching un-indexed data. This can make search faster, but will miss
+any data that is not yet indexed.
+
+Use [Table#optimize](Table.md#optimize) to index all un-indexed data.
+
+#### Returns
+
+`this`
+
+#### Inherited from
+
+`StandardQueryBase.fastSearch`
+
+***
+
+### ~~filter()~~
+
+```ts
+filter(predicate): this
+```
+
+A filter statement to be applied to this query.
+
+#### Parameters
+
+* **predicate**: `string`
+
+#### Returns
+
+`this`
+
+#### See
+
+where
+
+#### Deprecated
+
+Use `where` instead
+
+#### Inherited from
+
+`StandardQueryBase.filter`
+
+***
+
+### fullTextSearch()
+
+```ts
+fullTextSearch(query, options?): this
+```
+
+#### Parameters
+
+* **query**: `string` \| [`FullTextQuery`](../interfaces/FullTextQuery.md)
+
+* **options?**: `Partial`&lt;[`FullTextSearchOptions`](../interfaces/FullTextSearchOptions.md)&gt;
+
+#### Returns
+
+`this`
+
+#### Inherited from
+
+`StandardQueryBase.fullTextSearch`
+
+***
+
+### limit()
+
+```ts
+limit(limit): this
+```
+
+Set the maximum number of results to return.
+
+By default, a plain search has no limit.  If this method is not
+called then every valid row from the table will be returned.
+
+#### Parameters
+
+* **limit**: `number`
+
+#### Returns
+
+`this`
+
+#### Inherited from
+
+`StandardQueryBase.limit`
+
+***
+
+### offset()
+
+```ts
+offset(offset): this
+```
+
+Set the number of rows to skip before returning results.
+
+This is useful for pagination.
+
+#### Parameters
+
+* **offset**: `number`
+
+#### Returns
+
+`this`
+
+#### Inherited from
+
+`StandardQueryBase.offset`
+
+***
+
+### orderBy()
+
+```ts
+orderBy(ordering): this
+```
+
+Sort the results by the specified column(s).
+
+#### Parameters
+
+* **ordering**: [`ColumnOrdering`](../interfaces/ColumnOrdering.md) \| [`ColumnOrdering`](../interfaces/ColumnOrdering.md)[]
+
+#### Returns
+
+`this`
+
+This query builder.
+
+#### Inherited from
+
+`StandardQueryBase.orderBy`
+
+***
+
+### outputSchema()
+
+```ts
+outputSchema(): Promise<Schema<any>>
+```
+
+Returns the schema of the output that will be returned by this query.
+
+This can be used to inspect the types and names of the columns that will be
+returned by the query before executing it.
+
+#### Returns
+
+`Promise`&lt;`Schema`&lt;`any`&gt;&gt;
+
+An Arrow Schema describing the output columns.
+
+#### Inherited from
+
+`StandardQueryBase.outputSchema`
+
+***
+
+### select()
+
+```ts
+select(columns): this
+```
+
+Return only the specified columns.
+
+By default a query will return all columns from the table.  However, this can have
+a very significant impact on latency.  LanceDb stores data in a columnar fashion.  This
+means we can finely tune our I/O to select exactly the columns we need.
+
+As a best practice you should always limit queries to the columns that you need.  If you
+pass in an array of column names then only those columns will be returned.
+
+You can also use this method to create new "dynamic" columns based on your existing columns.
+For example, you may not care about "a" or "b" but instead simply want "a + b".  This is often
+seen in the SELECT clause of an SQL query (e.g. `SELECT a+b FROM my_table`).
+
+To create dynamic columns you can pass in a Map<string, string>.  A column will be returned
+for each entry in the map.  The key provides the name of the column.  The value is
+an SQL string used to specify how the column is calculated.
+
+For example, an SQL query might state `SELECT a + b AS combined, c`.  The equivalent
+input to this method would be:
+
+#### Parameters
+
+* **columns**: `string` \| `string`[] \| `Record`&lt;`string`, `string`&gt; \| `Map`&lt;`string`, `string`&gt;
+
+#### Returns
+
+`this`
+
+#### Example
+
+```ts
+new Map([["combined", "a + b"], ["c", "c"]])
+
+Columns will always be returned in the order given, even if that order is different than
+the order used when adding the data.
+
+Note that you can pass in a `Record<string, string>` (e.g. an object literal). This method
+uses `Object.entries` which should preserve the insertion order of the object.  However,
+object insertion order is easy to get wrong and `Map` is more foolproof.
+```
+
+#### Inherited from
+
+`StandardQueryBase.select`
+
+***
+
+### toArray()
+
+```ts
+toArray(options?): Promise<any[]>
+```
+
+Collect the results as an array of objects.
+
+#### Parameters
+
+* **options?**: `Partial`&lt;[`QueryExecutionOptions`](../interfaces/QueryExecutionOptions.md)&gt;
+
+#### Returns
+
+`Promise`&lt;`any`[]&gt;
+
+#### Inherited from
+
+`StandardQueryBase.toArray`
+
+***
+
+### toArrow()
+
+```ts
+toArrow(options?): Promise<Table<any>>
+```
+
+Collect the results as an Arrow
+
+#### Parameters
+
+* **options?**: `Partial`&lt;[`QueryExecutionOptions`](../interfaces/QueryExecutionOptions.md)&gt;
+
+#### Returns
+
+`Promise`&lt;`Table`&lt;`any`&gt;&gt;
+
+#### See
+
+ArrowTable.
+
+#### Inherited from
+
+`StandardQueryBase.toArrow`
+
+***
+
+### useLsm()
+
+```ts
+useLsm(enable): this
+```
+
+Control MemWAL read routing for this query.
+
+By default (unset), when the table carries a MemWAL write spec (see
+[Table#setLsmWriteSpec](Table.md#setlsmwritespec)), reads are routed through the LSM scanner so
+they also return data written via the `mergeInsert` LSM path that has not yet
+been compacted into the base table (the active/frozen in-memory memtables and
+the flushed generations), deduplicated by primary key; a table without a spec
+reads the base table.
+
+#### Parameters
+
+* **enable**: `boolean`
+    `true` forces the LSM scanner and errors if the table has no
+    MemWAL write spec. `false` bypasses the MemWAL and reads the base table only,
+    even when a spec is present.
+    Note: the LSM scanner does not support every query shape (e.g. reranking,
+    hybrid search, `orderBy`). On a MemWAL table those shapes error unless
+    `useLsm(false)` is set, because a base-only read would silently exclude
+    un-compacted MemWAL data.
+
+#### Returns
+
+`this`
+
+#### Inherited from
+
+`StandardQueryBase.useLsm`
+
+***
+
+### where()
+
+```ts
+where(predicate): this
+```
+
+A filter statement to be applied to this query.
+
+The filter should be supplied as an SQL query string.  For example:
+
+#### Parameters
+
+* **predicate**: `string`
+
+#### Returns
+
+`this`
+
+#### Example
+
+```ts
+x > 10
+y > 0 AND y < 100
+x > 5 OR y = 'test'
+
+Filtering performance can often be improved by creating a scalar index
+on the filter column(s).
+
+Calling this multiple times combines the filters with a logical AND rather
+than replacing the previous filter.
+```
+
+#### Inherited from
+
+`StandardQueryBase.where`
+
+***
+
+### withRowId()
+
+```ts
+withRowId(): this
+```
+
+Whether to return the row id in the results.
+
+This column can be used to match results between different queries. For
+example, to match results from a full text search and a vector search in
+order to perform hybrid search.
+
+#### Returns
+
+`this`
+
+#### Inherited from
+
+`StandardQueryBase.withRowId`
@@ -942,7 +942,7 @@ Get the schema of the table.
 abstract search(
   query,
   queryType?,
-   ftsColumns?): Query | VectorQuery
+   ftsColumns?): Query | VectorQuery | AutoQuery
 ```

 Create a search query to find the nearest neighbors
@@ -964,7 +964,7 @@ of the given query

 #### Returns

-[`Query`](Query.md) \| [`VectorQuery`](VectorQuery.md)
+[`Query`](Query.md) \| [`VectorQuery`](VectorQuery.md) \| [`AutoQuery`](AutoQuery.md)

 ***

@@ -1292,6 +1292,18 @@ abstract updateFieldMetadata(updates): Promise<UpdateFieldMetadataResult>

 Update per-field (column) metadata.

+The following keys are treated specially, by convention, and should be
+used when appropriate:
+
+- `lancedb:description`: for a human-readable description of a field.
+- `lancedb:tag:<name>`: for a user-defined key-value tag, where the suffix
+  names the tag category; e.g. `lancedb:tag:model: "clip"`.
+- `lancedb:logical-column`: for a column grouping; e.g. `feature_v1` and
+  `feature_v2` might be in the same logical column.
+- `lancedb:status`: for status options (`production`, `candidate`,
+  `deprecated`, `archived`) to designate the current life cycle state of
+  this column.
+
 #### Parameters

 * **updates**: [`FieldMetadataUpdate`](../interfaces/FieldMetadataUpdate.md)[]
@@ -18,6 +18,7 @@

 ## Classes

+- [AutoQuery](classes/AutoQuery.md)
 - [BooleanQuery](classes/BooleanQuery.md)
 - [BoostQuery](classes/BoostQuery.md)
 - [BranchContents](classes/BranchContents.md)
@@ -17,7 +17,8 @@ metadata: Record<string, null | string>;
 ```

 Metadata key/value pairs. Merged into the field's existing metadata by
-default; a value of `null` deletes that key.
+default; a value of `null` deletes that key. See
+[Table.updateFieldMetadata](../classes/Table.md#updatefieldmetadata) for the conventional `lancedb:*` keys.

 ***

@@ -10,16 +10,12 @@
 function getRegistry(): EmbeddingFunctionRegistry
 ```

-Utility function to get the global instance of the registry
+Get the global embedding function registry.
+
+LanceDB built-in providers are initialized when this public API is first
+used, so importing the root package does not change automatic search
+selection for tables without embedding metadata.

 ## Returns

 [`EmbeddingFunctionRegistry`](../classes/EmbeddingFunctionRegistry.md)
-
-`EmbeddingFunctionRegistry` The global instance of the registry
-
-## Example
-
-```ts
-const registry = getRegistry();
-const openai = registry.get("openai").create();
@@ -159,6 +159,8 @@ and combined with [BooleanQuery][lancedb.query.BooleanQuery].

 ::: lancedb.query.FullTextOperator

+::: lancedb.query.DocumentGranularity
+
 ::: lancedb.query.Occur

 ## Embeddings
@@ -8,7 +8,7 @@
    <parent>
      <groupId>com.lancedb</groupId>
      <artifactId>lancedb-parent</artifactId>
-      <version>0.38.0-beta.7</version>
+      <version>0.38.0-beta.11</version>
      <relativePath>../pom.xml</relativePath>
    </parent>

@@ -6,7 +6,7 @@

    <groupId>com.lancedb</groupId>
    <artifactId>lancedb-parent</artifactId>
-    <version>0.38.0-beta.7</version>
+    <version>0.38.0-beta.11</version>
    <packaging>pom</packaging>
    <name>${project.artifactId}</name>
    <description>LanceDB Java SDK Parent POM</description>
@@ -28,7 +28,7 @@
    <properties>
        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
        <arrow.version>15.0.0</arrow.version>
-        <lance-core.version>11.0.0-beta.22</lance-core.version>
+        <lance-core.version>12.0.0-beta.2</lance-core.version>
        <spotless.skip>false</spotless.skip>
        <spotless.version>2.30.0</spotless.version>
        <spotless.java.googlejavaformat.version>1.7</spotless.java.googlejavaformat.version>
@@ -1,7 +1,7 @@
 [package]
 name = "lancedb-nodejs"
 edition.workspace = true
-version = "0.38.0-beta.7"
+version = "0.38.0-beta.11"
 publish = false
 license.workspace = true
 description.workspace = true
@@ -1,11 +1,16 @@
 // SPDX-License-Identifier: Apache-2.0
 // SPDX-FileCopyrightText: Copyright The LanceDB Authors
+import * as fs from "node:fs";
+import * as vm from "node:vm";
 import * as arrow15 from "apache-arrow-15";
 import * as arrow16 from "apache-arrow-16";
 import * as arrow17 from "apache-arrow-17";
 import * as arrow18 from "apache-arrow-18";

 import {
+  Field as CurrentField,
+  LargeBinary as CurrentLargeBinary,
+  Schema as CurrentSchema,
  Vector as CurrentVector,
  convertToTable,
  tableFromIPC as currentTableFromIPC,
@@ -36,6 +41,59 @@ function sampleRecords(): Array<Record<string, any>> {
    },
  ];
 }
+
+it("serializes an Arrow Table created in another JavaScript realm", async () => {
+  const context = vm.createContext({
+    TextDecoder,
+    TextEncoder,
+    console,
+    setTimeout,
+    clearTimeout,
+  });
+  vm.runInContext(
+    fs.readFileSync(
+      require.resolve("apache-arrow-15/Arrow.es2015.min"),
+      "utf8",
+    ),
+    context,
+  );
+  const foreignTable: unknown = vm.runInContext(
+    "Arrow.tableFromArrays({ id: new Int32Array([1, 2, 3]), text: ['foo', 'bar', 'baz'] })",
+    context,
+  );
+
+  const foreignMetadata = (
+    foreignTable as { schema: { metadata: Map<string, string> } }
+  ).schema.metadata;
+  expect(foreignMetadata).not.toBeInstanceOf(Map);
+
+  const buf = await fromDataToBuffer(
+    foreignTable as Parameters<typeof fromDataToBuffer>[0],
+  );
+  const actual = currentTableFromIPC(buf);
+
+  expect(actual.numRows).toBe(3);
+  expect(actual.getChild("id")?.toJSON()).toEqual([1, 2, 3]);
+  expect(actual.getChild("text")?.toJSON()).toEqual(["foo", "bar", "baz"]);
+});
+
+it("preserves field metadata from a provided schema", async function () {
+  const jsonMetadata = new Map([["ARROW:extension:name", "lance.json"]]);
+  const schema = new CurrentSchema([
+    new CurrentField("meta", new CurrentLargeBinary(), true, jsonMetadata),
+  ]);
+
+  const table = makeArrowTable(
+    [{ meta: Buffer.from(JSON.stringify({ source: "test" })) }],
+    { schema },
+  );
+
+  expect(table.schema.fields[0].metadata).toEqual(jsonMetadata);
+
+  const roundTripped = currentTableFromIPC(await fromTableToBuffer(table));
+  expect(roundTripped.schema.fields[0].metadata).toEqual(jsonMetadata);
+});
+
 describe.each([arrow15, arrow16, arrow17, arrow18])(
  "Arrow",
  (
@@ -187,6 +187,58 @@ describe("embedding functions", () => {
    const vector0 = JSON.parse(JSON.stringify(arr[0].vector));
    expect(vector0).toEqual([1, 2, 3]);
  });
+  it("should append multiple Python embeddings with the same alias", async () => {
+    @register("python-mock")
+    // biome-ignore lint/correctness/noUnusedVariables: the decorator registers this class
+    class MockEmbeddingFunction extends EmbeddingFunction<string> {
+      ndims() {
+        return 3;
+      }
+      embeddingDataType(): Float {
+        return new Float32();
+      }
+      async computeQueryEmbeddings(_data: string) {
+        return [1, 2, 3];
+      }
+      async computeSourceEmbeddings(data: string[]) {
+        return data.map((value) =>
+          value === "hello world" ? [1, 2, 3] : [4, 5, 6],
+        );
+      }
+    }
+
+    const metadata = new Map([
+      [
+        "embedding_functions",
+        '[{"source_column":"text1","vector_column":"vector1","name":"python-mock","model":{}},{"source_column":"text2","vector_column":"vector2","name":"python-mock","model":{}}]',
+      ],
+    ]);
+    const schema = new Schema(
+      [
+        new Field("text1", new Utf8(), true),
+        new Field("text2", new Utf8(), true),
+        new Field(
+          "vector1",
+          new FixedSizeList(3, new Field("item", new Float32(), true)),
+          true,
+        ),
+        new Field(
+          "vector2",
+          new FixedSizeList(3, new Field("item", new Float32(), true)),
+          true,
+        ),
+      ],
+      metadata,
+    );
+
+    const db = await connect(tmpDir.name);
+    const table = await db.createEmptyTable("test", schema);
+    await table.add([{ text1: "hello world", text2: "goodbye world" }]);
+
+    const rows = await table.query().toArray();
+    expect(JSON.parse(JSON.stringify(rows[0].vector1))).toEqual([1, 2, 3]);
+    expect(JSON.parse(JSON.stringify(rows[0].vector2))).toEqual([4, 5, 6]);
+  });

  it("should append generated vectors to a non-nullable schema", async () => {
    @register("non_nullable_schema_test")
@@ -0,0 +1,95 @@
+// SPDX-License-Identifier: Apache-2.0
+// SPDX-FileCopyrightText: Copyright The LanceDB Authors
+
+import { execFileSync } from "node:child_process";
+import { resolve } from "node:path";
+
+import type { OpenAIEmbeddingFunction } from "../lancedb/embedding/openai";
+import type { EmbeddingFunctionRegistry } from "../lancedb/embedding/registry";
+
+type EmbeddingModule = typeof import("../lancedb/embedding");
+type OpenAIModule = typeof import("../lancedb/embedding/openai");
+type RegistryModule = typeof import("../lancedb/embedding/registry");
+
+describe("embedding function registry", () => {
+  const registries: EmbeddingFunctionRegistry[] = [];
+
+  afterEach(() => {
+    for (const registry of registries) {
+      registry.reset();
+    }
+    registries.length = 0;
+  });
+
+  it("defers built-in providers until the public registry API is used", () => {
+    jest.isolateModules(() => {
+      const embedding = require("../lancedb/embedding") as EmbeddingModule;
+      const { getRegistry: getInternalRegistry } =
+        require("../lancedb/embedding/registry") as RegistryModule;
+      const registry = getInternalRegistry();
+      registries.push(registry);
+
+      expect(registry.length()).toBe(0);
+      expect(embedding.getRegistry()).toBe(registry);
+      expect(registry.get("openai")).toBeDefined();
+      expect(registry.get("huggingface")).toBeDefined();
+    });
+  });
+
+  it("preserves automatic FTS search in a fresh process", () => {
+    execFileSync(
+      process.execPath,
+      [resolve(__dirname, "fixtures", "auto_fts_search.cjs")],
+      { stdio: "pipe" },
+    );
+  });
+
+  it("shares registrations across duplicated provider module graphs", () => {
+    let registeringRegistry: EmbeddingFunctionRegistry | undefined;
+    let latestOpenAIConstructor: typeof OpenAIEmbeddingFunction | undefined;
+
+    jest.isolateModules(() => {
+      require("../lancedb/embedding/openai");
+      const { getRegistry } =
+        require("../lancedb/embedding/registry") as RegistryModule;
+      registeringRegistry = getRegistry();
+      registries.push(registeringRegistry);
+      expect(registeringRegistry.get("openai")).toBeDefined();
+    });
+
+    expect(() => {
+      jest.isolateModules(() => {
+        const { OpenAIEmbeddingFunction } =
+          require("../lancedb/embedding/openai") as OpenAIModule;
+        latestOpenAIConstructor = OpenAIEmbeddingFunction;
+        const { getRegistry } =
+          require("../lancedb/embedding/registry") as RegistryModule;
+        registries.push(getRegistry());
+      });
+    }).not.toThrow();
+
+    const previousApiKey = process.env.OPENAI_API_KEY;
+    process.env.OPENAI_API_KEY = "test";
+    try {
+      const latestOpenAI = registeringRegistry!
+        .get<OpenAIEmbeddingFunction>("openai")!
+        .create();
+      expect(latestOpenAI).toBeInstanceOf(latestOpenAIConstructor!);
+    } finally {
+      if (previousApiKey === undefined) {
+        delete process.env.OPENAI_API_KEY;
+      } else {
+        process.env.OPENAI_API_KEY = previousApiKey;
+      }
+    }
+
+    jest.isolateModules(() => {
+      const { getRegistry } =
+        require("../lancedb/embedding") as EmbeddingModule;
+      const publicRegistry = getRegistry();
+      registries.push(publicRegistry);
+      expect(publicRegistry).toBe(registeringRegistry);
+      expect(publicRegistry.get("openai")).toBeDefined();
+    });
+  });
+});
@@ -0,0 +1,33 @@
+// SPDX-License-Identifier: Apache-2.0
+// SPDX-FileCopyrightText: Copyright The LanceDB Authors
+
+const assert = require("node:assert/strict");
+const tmp = require("tmp");
+const { connect, embedding, Index } = require("../../dist");
+const { getRegistry } = require("../../dist/embedding/registry");
+
+async function main() {
+  assert.equal(typeof embedding.getRegistry, "function");
+  assert.equal(getRegistry().length(), 0);
+  assert.equal(embedding.getRegistry(), getRegistry());
+  assert.equal(getRegistry().length(), 2);
+
+  const dir = tmp.dirSync({ unsafeCleanup: true });
+  let db;
+  try {
+    db = await connect(dir.name);
+    const table = await db.createTable("docs", [{ text: "hello world" }]);
+    await table.createIndex("text", { config: Index.fts() });
+
+    const rows = await table.search("hello").toArray();
+    assert.equal(rows[0].text, "hello world");
+  } finally {
+    db?.close();
+    dir.removeCallback();
+  }
+}
+
+main().catch((error) => {
+  console.error(error);
+  process.exitCode = 1;
+});
@@ -11,10 +11,13 @@ import * as arrow17 from "apache-arrow-17";
 import * as arrow18 from "apache-arrow-18";

 import {
+  AutoQuery,
  Connection,
  MatchQuery,
  PhraseQuery,
+  Query,
  Table,
+  VectorQuery,
  connect,
  tokenize,
 } from "../lancedb";
@@ -682,6 +685,56 @@ describe.each([arrow15, arrow16, arrow17, arrow18])(
  },
 );

+// https://github.com/lancedb/lancedb/issues/1963
+it("should query documents with LangChain PDF metadata", async () => {
+  const tmpDir = tmp.dirSync({ unsafeCleanup: true });
+  try {
+    const db = await connect(tmpDir.name);
+    const documents = [
+      {
+        text: "first page",
+        vector: [1, 0],
+        source: "first.pdf",
+        loc: { pageNumber: 1, lines: { from: 1, to: 12 } },
+        pdf: {
+          version: "1.10.100",
+          info: {
+            format: "PDF 1.7",
+            producer: "pdf.js",
+            creator: "Writer",
+          },
+          totalPages: 2,
+        },
+      },
+      {
+        text: "second page",
+        vector: [0, 1],
+        source: "second.pdf",
+        loc: { pageNumber: 2, lines: { from: 13, to: 24 } },
+        pdf: {
+          version: "1.10.100",
+          info: {
+            format: "PDF 1.7",
+            producer: "pdf.js",
+            creator: "Writer",
+          },
+          totalPages: 2,
+        },
+      },
+    ];
+    const documentsTable = await db.createTable("documents", documents);
+
+    const results = await documentsTable.query().toArray();
+
+    expect(results).toHaveLength(2);
+    expect(results[0].source).toBe("first.pdf");
+    expect(results[0].pdf.info.producer).toBe("pdf.js");
+    expect(results[1].loc.pageNumber).toBe(2);
+  } finally {
+    tmpDir.removeCallback();
+  }
+});
+
 describe("merge insert", () => {
  let tmpDir: tmp.DirResult;
  let table: Table;
@@ -1777,6 +1830,194 @@ describe("Read consistency interval", () => {
  });
 });

+describe("automatic search schema consistency", () => {
+  let tmpDir: tmp.DirResult;
+
+  class SchemaRefreshEmbedding extends EmbeddingFunction<string> {
+    ndims() {
+      return 2;
+    }
+
+    embeddingDataType() {
+      return new Float32();
+    }
+
+    async computeSourceEmbeddings(data: string[]) {
+      return data.map((value) => [value.length, 1]);
+    }
+
+    async computeQueryEmbeddings(value: string) {
+      return [value.length, 1];
+    }
+  }
+
+  function embeddingSchema() {
+    const func = new SchemaRefreshEmbedding();
+    return LanceSchema({
+      text: func.sourceField(new Utf8()),
+      vector: func.vectorField(),
+    });
+  }
+
+  beforeEach(() => {
+    getRegistry().reset();
+    register("schema-refresh")(SchemaRefreshEmbedding);
+    tmpDir = tmp.dirSync({ unsafeCleanup: true });
+  });
+
+  afterEach(() => {
+    getRegistry().reset();
+    tmpDir.removeCallback();
+  });
+
+  it("uses the schema refreshed from another connection", async () => {
+    const first = await connect(tmpDir.name, { readConsistencyInterval: 0 });
+    const second = await connect(tmpDir.name, { readConsistencyInterval: 0 });
+
+    try {
+      const stale = await first.createTable("docs", [{ text: "before" }], {
+        schema: embeddingSchema(),
+      });
+      const replacement = await second.createTable(
+        "docs",
+        [{ text: "after hello" }],
+        { mode: "overwrite" },
+      );
+      await replacement.createIndex("text", { config: Index.fts() });
+
+      const search = stale.search("hello");
+      expect(search).toBeInstanceOf(AutoQuery);
+      expect(search).not.toBeInstanceOf(Query);
+      expect(search).not.toBeInstanceOf(VectorQuery);
+      expect("nprobes" in search).toBe(false);
+
+      const rows = await search.toArray();
+      expect(rows[0].text).toBe("after hello");
+      expect((await stale.schema()).metadata.has("embedding_functions")).toBe(
+        false,
+      );
+    } finally {
+      first.close();
+      second.close();
+    }
+  });
+
+  it("tracks embedding metadata across checkout and restore", async () => {
+    const first = await connect(tmpDir.name, { readConsistencyInterval: 0 });
+    const second = await connect(tmpDir.name, { readConsistencyInterval: 0 });
+
+    try {
+      await first.createTable("docs", [{ text: "before" }], {
+        schema: embeddingSchema(),
+      });
+      const table = await second.createTable(
+        "docs",
+        [{ text: "after hello" }],
+        { mode: "overwrite" },
+      );
+      await table.createIndex("text", { config: Index.fts() });
+
+      await table.checkout(1);
+      expect((await table.search("before").toArray())[0].text).toBe("before");
+
+      await table.checkoutLatest();
+      expect((await table.search("hello").toArray())[0].text).toBe(
+        "after hello",
+      );
+
+      await table.checkout(1);
+      await table.restore();
+      expect((await table.search("before").toArray())[0].text).toBe("before");
+    } finally {
+      first.close();
+      second.close();
+    }
+  });
+
+  it("pins automatic search while computing an embedding", async () => {
+    let markStarted!: () => void;
+    let releaseEmbedding!: () => void;
+    const started = new Promise<void>((resolve) => {
+      markStarted = resolve;
+    });
+    const released = new Promise<void>((resolve) => {
+      releaseEmbedding = resolve;
+    });
+
+    class BlockingEmbedding extends SchemaRefreshEmbedding {
+      async computeQueryEmbeddings(value: string) {
+        markStarted();
+        await released;
+        return [value.length, 1];
+      }
+    }
+
+    register("schema-refresh-blocking")(BlockingEmbedding);
+    const func = new BlockingEmbedding();
+    const schema = LanceSchema({
+      text: func.sourceField(new Utf8()),
+      vector: func.vectorField(),
+    });
+    const first = await connect(tmpDir.name, { readConsistencyInterval: 0 });
+    const second = await connect(tmpDir.name, { readConsistencyInterval: 0 });
+
+    try {
+      const table = await first.createTable(
+        "docs",
+        [{ text: "hello before" }],
+        { schema },
+      );
+      const pending = table.search("hello").toArray();
+      await started;
+
+      const replacement = await second.createTable(
+        "docs",
+        [{ text: "hello after" }],
+        { mode: "overwrite" },
+      );
+      await replacement.createIndex("text", { config: Index.fts() });
+      releaseEmbedding();
+
+      expect((await pending)[0].text).toBe("hello before");
+    } finally {
+      releaseEmbedding();
+      first.close();
+      second.close();
+    }
+  });
+
+  it("refreshes a reused automatic search for every execution", async () => {
+    const first = await connect(tmpDir.name, { readConsistencyInterval: 0 });
+    const second = await connect(tmpDir.name, { readConsistencyInterval: 0 });
+
+    try {
+      const table = await first.createTable("docs", [
+        { text: "hello before", marker: "before" },
+      ]);
+      await table.createIndex("text", { config: Index.fts() });
+      const search = table.search("hello").select(["text"]);
+
+      const before = (await search.toArray())[0];
+      expect(before.text).toBe("hello before");
+      expect(before.marker).toBeUndefined();
+
+      const replacement = await second.createTable(
+        "docs",
+        [{ text: "hello after", marker: "after" }],
+        { mode: "overwrite" },
+      );
+      await replacement.createIndex("text", { config: Index.fts() });
+
+      const after = (await search.toArray())[0];
+      expect(after.text).toBe("hello after");
+      expect(after.marker).toBeUndefined();
+    } finally {
+      first.close();
+      second.close();
+    }
+  });
+});
+
 describe("schema evolution", function () {
  let tmpDir: tmp.DirResult;
  beforeEach(() => {
@@ -2344,7 +2585,24 @@ describe.each([arrow15, arrow16, arrow17, arrow18])(
      );
    });

-    test("full text search if no embedding function provided", async () => {
+    test("full text search if only an unrelated embedding function is registered", async () => {
+      register("unused")(
+        class extends EmbeddingFunction<string> {
+          ndims() {
+            return 3;
+          }
+          embeddingDataType() {
+            return new Float32();
+          }
+          async computeQueryEmbeddings(_data: string) {
+            return [1, 2, 3];
+          }
+          async computeSourceEmbeddings(data: string[]) {
+            return data.map(() => [1, 2, 3]);
+          }
+        },
+      );
+
      const db = await connect(tmpDir.name);
      const data = [
        { text: "hello world", vector: [0.1, 0.2, 0.3] },
@@ -2366,6 +2624,306 @@ describe.each([arrow15, arrow16, arrow17, arrow18])(
      expect(results2[0].text).toBe(data[1].text);
    });

+    test("auto search stays consistent with the active revision", async () => {
+      let initCalls = 0;
+      let queryCalls = 0;
+      let markStarted!: () => void;
+      const started = new Promise<void>((resolve) => {
+        markStarted = resolve;
+      });
+      let releaseEmbedding!: () => void;
+      const embeddingReleased = new Promise<void>((resolve) => {
+        releaseEmbedding = resolve;
+      });
+
+      @register("refresh-test")
+      class TestEmbedding extends EmbeddingFunction<string> {
+        async init() {
+          initCalls += 1;
+        }
+        ndims() {
+          return 1;
+        }
+        embeddingDataType() {
+          return new arrow.Float32();
+        }
+        async computeQueryEmbeddings(value: string) {
+          queryCalls += 1;
+          if (value === "blocked") {
+            markStarted();
+            await embeddingReleased;
+          }
+          return value === "greetings" ? [0.1] : [0.2];
+        }
+        async computeSourceEmbeddings(values: string[]) {
+          return values.map((value) =>
+            value === "hello world" ? [0.1] : [0.2],
+          );
+        }
+      }
+
+      const writer = await connect(tmpDir.name);
+      await writer.createTable("test", [{ text: "plain", vector: [0.0] }]);
+      const reader = await connect(tmpDir.name, {
+        readConsistencyInterval: 0,
+      });
+      const tracked = await reader.openTable("test");
+      type SnapshotCountingNative = {
+        querySnapshot: () => Promise<unknown>;
+      };
+      const native = (tracked as unknown as { inner: SnapshotCountingNative })
+        .inner;
+      const querySnapshot = native.querySnapshot.bind(native);
+      let snapshotCalls = 0;
+      native.querySnapshot = async () => {
+        snapshotCalls += 1;
+        return await querySnapshot();
+      };
+      const autoQuery = tracked.search("greetings").select(["text"]).limit(1);
+
+      const func = new TestEmbedding();
+      const schema = LanceSchema({
+        text: func.sourceField(new arrow.Utf8()),
+        vector: func.vectorField(),
+      });
+      const data = [{ text: "hello world" }, { text: "goodbye world" }];
+      await writer.createTable("test", data, { mode: "overwrite", schema });
+      const baselineInitCalls = initCalls;
+
+      expect(
+        (await tracked.schema()).metadata.get("embedding_functions"),
+      ).toBeDefined();
+      const results = await autoQuery.toArray();
+      expect(results[0].text).toBe(data[0].text);
+      expect(initCalls).toBe(baselineInitCalls + 1);
+      expect(queryCalls).toBe(1);
+      expect(snapshotCalls).toBe(1);
+
+      const repeatedResults = await autoQuery.toArray();
+      expect(repeatedResults[0].text).toBe(data[0].text);
+      expect(initCalls).toBe(baselineInitCalls + 1);
+      expect(queryCalls).toBe(1);
+      expect(snapshotCalls).toBe(2);
+
+      const pending = tracked
+        .search("blocked")
+        .select(["text"])
+        .limit(1)
+        .toArray();
+      await started;
+
+      const ftsData = [
+        { text: "greetings from full text", vector: [0.0] },
+        { text: "blocked from full text", vector: [0.0] },
+      ];
+      const ftsTable = await writer.createTable("test", ftsData, {
+        mode: "overwrite",
+      });
+      await ftsTable.createIndex("text", { config: Index.fts() });
+      releaseEmbedding();
+
+      const pendingResults = await pending;
+      expect(pendingResults[0].text).toBe(data[1].text);
+
+      expect(
+        (await tracked.schema()).metadata.get("embedding_functions"),
+      ).toBeUndefined();
+      const ftsResults = await autoQuery.toArray();
+      expect(ftsResults[0].text).toBe(ftsData[0].text);
+    });
+
+    test("auto search keeps newer preparation during a revision race", async () => {
+      let aCalls = 0;
+      let bCalls = 0;
+      let markAStarted!: () => void;
+      const aStarted = new Promise<void>((resolve) => {
+        markAStarted = resolve;
+      });
+      let releaseA!: () => void;
+      const aReleased = new Promise<void>((resolve) => {
+        releaseA = resolve;
+      });
+      let markBStarted!: () => void;
+      const bStarted = new Promise<void>((resolve) => {
+        markBStarted = resolve;
+      });
+      let releaseB!: () => void;
+      const bReleased = new Promise<void>((resolve) => {
+        releaseB = resolve;
+      });
+
+      @register("race-a")
+      class EmbeddingA extends EmbeddingFunction<string> {
+        ndims() {
+          return 1;
+        }
+        embeddingDataType() {
+          return new arrow.Float32();
+        }
+        async computeQueryEmbeddings() {
+          aCalls += 1;
+          markAStarted();
+          await aReleased;
+          return [0.1];
+        }
+        async computeSourceEmbeddings(values: string[]) {
+          return values.map(() => [0.1]);
+        }
+      }
+
+      @register("race-b")
+      class EmbeddingB extends EmbeddingFunction<string> {
+        ndims() {
+          return 1;
+        }
+        embeddingDataType() {
+          return new arrow.Float32();
+        }
+        async computeQueryEmbeddings() {
+          bCalls += 1;
+          markBStarted();
+          await bReleased;
+          return [0.2];
+        }
+        async computeSourceEmbeddings(values: string[]) {
+          return values.map(() => [0.2]);
+        }
+      }
+
+      const writer = await connect(tmpDir.name);
+      const embeddingA = new EmbeddingA();
+      const schemaA = LanceSchema({
+        text: embeddingA.sourceField(new arrow.Utf8()),
+        vector: embeddingA.vectorField(),
+      });
+      await writer.createTable("race", [{ text: "revision a" }], {
+        schema: schemaA,
+      });
+      const reader = await connect(tmpDir.name, {
+        readConsistencyInterval: 0,
+      });
+      const tracked = await reader.openTable("race");
+      const query = tracked.search("query");
+
+      const first = query.toArray();
+      await aStarted;
+
+      const embeddingB = new EmbeddingB();
+      const schemaB = LanceSchema({
+        text: embeddingB.sourceField(new arrow.Utf8()),
+        vector: embeddingB.vectorField(),
+      });
+      await writer.createTable("race", [{ text: "revision b" }], {
+        mode: "overwrite",
+        schema: schemaB,
+      });
+      const second = query.toArray();
+      await bStarted;
+
+      releaseA();
+      releaseB();
+      await Promise.all([first, second]);
+      expect(aCalls).toBe(1);
+      expect(bCalls).toBe(1);
+    });
+
+    test("stale FTS routing keeps newer vector preparation", async () => {
+      let vectorCalls = 0;
+      let markVectorStarted!: () => void;
+      const vectorStarted = new Promise<void>((resolve) => {
+        markVectorStarted = resolve;
+      });
+      let releaseVector!: () => void;
+      const vectorReleased = new Promise<void>((resolve) => {
+        releaseVector = resolve;
+      });
+
+      @register("stale-fts-race")
+      class RaceEmbedding extends EmbeddingFunction<string> {
+        ndims() {
+          return 1;
+        }
+        embeddingDataType() {
+          return new arrow.Float32();
+        }
+        async computeQueryEmbeddings() {
+          vectorCalls += 1;
+          markVectorStarted();
+          await vectorReleased;
+          return [0.1];
+        }
+        async computeSourceEmbeddings(values: string[]) {
+          return values.map(() => [0.1]);
+        }
+      }
+
+      const writer = await connect(tmpDir.name);
+      const ftsTable = await writer.createTable("stale_fts", [
+        { text: "hello", vector: [0.0] },
+      ]);
+      await ftsTable.createIndex("text", { config: Index.fts() });
+
+      const reader = await connect(tmpDir.name, {
+        readConsistencyInterval: 0,
+      });
+      const tracked = await reader.openTable("stale_fts");
+      type Snapshot = {
+        schema: () => Promise<Buffer>;
+      };
+      type NativeWithSnapshot = {
+        querySnapshot: () => Promise<Snapshot>;
+      };
+      const native = (tracked as unknown as { inner: NativeWithSnapshot })
+        .inner;
+      const querySnapshot = native.querySnapshot.bind(native);
+      let snapshotCalls = 0;
+      let markStaleSchemaStarted!: () => void;
+      const staleSchemaStarted = new Promise<void>((resolve) => {
+        markStaleSchemaStarted = resolve;
+      });
+      let releaseStaleSchema!: () => void;
+      const staleSchemaReleased = new Promise<void>((resolve) => {
+        releaseStaleSchema = resolve;
+      });
+      native.querySnapshot = async () => {
+        const snapshot = await querySnapshot();
+        snapshotCalls += 1;
+        if (snapshotCalls === 1) {
+          const schema = snapshot.schema.bind(snapshot);
+          snapshot.schema = async () => {
+            markStaleSchemaStarted();
+            await staleSchemaReleased;
+            return await schema();
+          };
+        }
+        return snapshot;
+      };
+
+      const query = tracked.search("hello");
+      const staleFtsExecution = query.toArray();
+      await staleSchemaStarted;
+
+      const embedding = new RaceEmbedding();
+      const vectorSchema = LanceSchema({
+        text: embedding.sourceField(new arrow.Utf8()),
+        vector: embedding.vectorField(),
+      });
+      await writer.createTable("stale_fts", [{ text: "hello" }], {
+        mode: "overwrite",
+        schema: vectorSchema,
+      });
+
+      const vectorExecution = query.toArray();
+      await vectorStarted;
+      releaseStaleSchema();
+      await staleFtsExecution;
+      releaseVector();
+      await vectorExecution;
+
+      await query.toArray();
+      expect(vectorCalls).toBe(1);
+    });
+
    test("tokenizes FTS queries by column or index name", async () => {
      const db = await connect(tmpDir.name);
      const data = [
@@ -2916,6 +3474,30 @@ describe("column name options", () => {
    expect(results[1].query_index).toBe(1);
  });

+  test("observes promised additional vectors while the query is pending", async () => {
+    const initialVector = new Promise<number[]>(() => undefined);
+    const query = table.query().nearestTo(initialVector);
+    const unhandled: unknown[] = [];
+    const onUnhandled = (reason: unknown) => unhandled.push(reason);
+    process.on("unhandledRejection", onUnhandled);
+
+    try {
+      query.addQueryVector(Promise.reject(new Error("extra vector failed")));
+      await new Promise<void>((resolve) => setImmediate(resolve));
+      expect(unhandled).toEqual([]);
+
+      const rejectedQuery = table
+        .query()
+        .nearestTo([0.1, 0.2])
+        .addQueryVector(Promise.reject(new Error("consumed vector failed")));
+      await expect(rejectedQuery.toArray()).rejects.toThrow(
+        "consumed vector failed",
+      );
+    } finally {
+      process.off("unhandledRejection", onUnhandled);
+    }
+  });
+
  test("index and search multivectors", async () => {
    const db = await connect(tmpDir.name);
    const data = [];
@@ -2979,6 +3561,27 @@ describe("when creating an empty table", () => {
    expect((actualSchema.fields[1].type as Float64).precision).toBe(2);
  });

+  it("can add and query JSON data", async () => {
+    const schema = new Schema([
+      new Field("id", new Int32(), true),
+      new Field(
+        "meta",
+        new Utf8(),
+        true,
+        new Map([["ARROW:extension:name", "arrow.json"]]),
+      ),
+    ]);
+    const table = await con.createEmptyTable("json", schema);
+    const meta = JSON.stringify({ x: 1 });
+
+    await table.add([{ id: 1, meta }]);
+
+    const rows = await table.query().toArray();
+    expect(rows).toHaveLength(1);
+    expect(rows[0].id).toBe(1);
+    expect(rows[0].meta).toBe(meta);
+  });
+
  it("can create an empty table from schema that specifies field types by name", async () => {
    const schemaLike = {
      fields: [
@@ -170,7 +170,7 @@ test("basic table examples", async () => {
    // --8<-- [end:create_index]

    // --8<-- [start:delete_rows]
-    await tbl.delete('item = "fizz"');
+    await tbl.delete("item = 'fizz'");
    // --8<-- [end:delete_rows]

    // --8<-- [start:drop_table]
@@ -72,8 +72,7 @@ export type FieldLike =
    };

 export type DataLike =
-  // biome-ignore lint/suspicious/noExplicitAny: <explanation>
-  | import("apache-arrow").Data<Struct<any>>
+  | import("apache-arrow").Data
  | {
      // biome-ignore lint/suspicious/noExplicitAny: <explanation>
      type: any;
@@ -82,6 +81,7 @@ export type DataLike =
      stride: number;
      nullable: boolean;
      children: DataLike[];
+      dictionary?: { data: readonly DataLike[] };
      get nullCount(): number;
      // biome-ignore lint/suspicious/noExplicitAny: <explanation>
      values: Buffers<any>[BufferType.DATA];
@@ -4,7 +4,15 @@
 import { Field, Schema } from "../arrow";
 import { sanitizeType } from "../sanitize";
 import { EmbeddingFunction } from "./embedding_function";
-import { EmbeddingFunctionConfig, getRegistry } from "./registry";
+import {
+  EmbeddingFunctionConfig,
+  EmbeddingFunctionRegistry,
+  getRegistry as getGlobalRegistry,
+  registerBuiltIn,
+} from "./registry";
+
+type OpenAIModule = typeof import("./openai");
+type TransformersModule = typeof import("./transformers");

 export {
  FieldOptions,
@@ -14,7 +22,39 @@ export {
  EmbeddingFunctionConstructor,
 } from "./embedding_function";

-export * from "./registry";
+export {
+  EmbeddingFunctionRegistry,
+  parseEmbeddingMetadata,
+  register,
+} from "./registry";
+export type {
+  CreateReturnType,
+  EmbeddingFunctionConfig,
+  EmbeddingFunctionCreate,
+  EmbeddingMetadataEntry,
+  ResolvedEmbeddingFunctionConfig,
+} from "./registry";
+
+function initializeBuiltInProviders() {
+  const { OpenAIEmbeddingFunction } = require("./openai") as OpenAIModule;
+  const { TransformersEmbeddingFunction } =
+    require("./transformers") as TransformersModule;
+
+  registerBuiltIn("openai", OpenAIEmbeddingFunction);
+  registerBuiltIn("huggingface", TransformersEmbeddingFunction);
+}
+
+/**
+ * Get the global embedding function registry.
+ *
+ * LanceDB built-in providers are initialized when this public API is first
+ * used, so importing the root package does not change automatic search
+ * selection for tables without embedding metadata.
+ */
+export function getRegistry(): EmbeddingFunctionRegistry {
+  initializeBuiltInProviders();
+  return getGlobalRegistry();
+}

 /**
 * Create a schema with embedding functions.
@@ -5,14 +5,13 @@ import type OpenAI from "openai";
 import type { EmbeddingCreateParams } from "openai/resources/index";
 import { Float, Float32 } from "../arrow";
 import { EmbeddingFunction } from "./embedding_function";
-import { register } from "./registry";
+import { registerBuiltIn } from "./registry";

 export type OpenAIOptions = {
  apiKey: string;
  model: EmbeddingCreateParams["model"];
 };

-@register("openai")
 export class OpenAIEmbeddingFunction extends EmbeddingFunction<
  string,
  Partial<OpenAIOptions>
@@ -100,3 +99,5 @@ export class OpenAIEmbeddingFunction extends EmbeddingFunction<
    return response.data[0].embedding;
  }
 }
+
+registerBuiltIn("openai", OpenAIEmbeddingFunction);
@@ -7,6 +7,10 @@ import {
 } from "./embedding_function";
 import "reflect-metadata";

+const builtInFunctionsKey = Symbol.for(
+  "@lancedb/lancedb::embedding-built-in-functions::v1",
+);
+
 export type CreateReturnType<T> = T extends { init: () => Promise<void> }
  ? Promise<T>
  : T;
@@ -59,6 +63,15 @@ export class EmbeddingFunctionRegistry {
    };
  }

+  /** @ignore */
+  setBuiltIn<
+    T extends EmbeddingFunctionConstructor = EmbeddingFunctionConstructor,
+  >(name: string, ctor: T): T {
+    this.#functions.set(name, ctor);
+    Reflect.defineMetadata("lancedb::embedding::name", name, ctor);
+    return ctor;
+  }
+
  get<T extends EmbeddingFunction<unknown>>(
    name: string,
  ): EmbeddingFunctionCreate<T> | undefined;
@@ -96,6 +109,7 @@ export class EmbeddingFunctionRegistry {
   */
  reset(this: EmbeddingFunctionRegistry) {
    this.#functions.clear();
+    getBuiltInFunctions(this).clear();
  }

  /**
@@ -183,12 +197,56 @@ export class EmbeddingFunctionRegistry {
  }
 }

-const _REGISTRY = new EmbeddingFunctionRegistry();
+function getBuiltInFunctions(registry: EmbeddingFunctionRegistry): Set<string> {
+  const registryWithBuiltIns = registry as EmbeddingFunctionRegistry & {
+    [key: symbol]: Set<string> | undefined;
+  };
+  let builtInFunctions = registryWithBuiltIns[builtInFunctionsKey];
+  if (builtInFunctions === undefined) {
+    builtInFunctions = new Set<string>();
+    registryWithBuiltIns[builtInFunctionsKey] = builtInFunctions;
+  }
+  return builtInFunctions;
+}
+
+// Server bundlers can load the side-effect embedding entry points and the public
+// embedding API from separate module graphs. Keep their registry shared.
+const registryKey = Symbol.for(
+  "@lancedb/lancedb::embedding-function-registry::v1",
+);
+const registryGlobal = globalThis as typeof globalThis & {
+  [key: symbol]: EmbeddingFunctionRegistry | undefined;
+};
+
+function getGlobalRegistry(): EmbeddingFunctionRegistry {
+  const existingRegistry = registryGlobal[registryKey];
+  if (existingRegistry !== undefined) {
+    return existingRegistry;
+  }
+  const registry = new EmbeddingFunctionRegistry();
+  registryGlobal[registryKey] = registry;
+  return registry;
+}
+
+const _REGISTRY = getGlobalRegistry();

 export function register(name?: string) {
  return _REGISTRY.register(name);
 }

+/** @ignore */
+export function registerBuiltIn<
+  T extends EmbeddingFunctionConstructor = EmbeddingFunctionConstructor,
+>(name: string, ctor: T): T {
+  const builtInFunctions = getBuiltInFunctions(_REGISTRY);
+  if (builtInFunctions.has(name)) {
+    return _REGISTRY.setBuiltIn(name, ctor);
+  }
+  _REGISTRY.register(name)(ctor);
+  builtInFunctions.add(name);
+  return ctor;
+}
+
 /**
 * Utility function to get the global instance of the registry
 * @returns `EmbeddingFunctionRegistry` The global instance of the registry
@@ -3,7 +3,7 @@

 import { Float, Float32 } from "../arrow";
 import { EmbeddingFunction } from "./embedding_function";
-import { register } from "./registry";
+import { registerBuiltIn } from "./registry";

 export type XenovaTransformerOptions = {
  /** The wasm compatible model to use */
@@ -31,7 +31,6 @@ export type XenovaTransformerOptions = {
  };
 };

-@register("huggingface")
 export class TransformersEmbeddingFunction extends EmbeddingFunction<
  string,
  Partial<XenovaTransformerOptions>
@@ -158,6 +157,8 @@ export class TransformersEmbeddingFunction extends EmbeddingFunction<
  }
 }

+registerBuiltIn("huggingface", TransformersEmbeddingFunction);
+
 const tensorDiv = (
  src: import("@huggingface/transformers").Tensor,
  divBy: number,
@@ -103,6 +103,7 @@ export {
 } from "./native.js";

 export {
+  AutoQuery,
  ExecutableQuery,
  Query,
  QueryBase,
@@ -100,6 +100,29 @@ export interface FullTextSearchOptions {
  columns?: string | string[];
 }

+function nearestToNative(
+  inner: NativeQuery,
+  vector: Awaited<IntoVector>,
+): NativeVectorQuery {
+  const raw = Array.isArray(vector) ? null : extractVectorBuffer(vector);
+  if (raw) {
+    return inner.nearestToRaw(raw.data, raw.dtype);
+  }
+  return inner.nearestTo(Float32Array.from(vector as number[]));
+}
+
+function addQueryVectorToNative(
+  inner: NativeVectorQuery,
+  vector: Awaited<IntoVector>,
+) {
+  const raw = Array.isArray(vector) ? null : extractVectorBuffer(vector);
+  if (raw) {
+    inner.addQueryVectorRaw(raw.data, raw.dtype);
+  } else {
+    inner.addQueryVector(Float32Array.from(vector as number[]));
+  }
+}
+
 /** Common methods supported by all query types
 *
 * @see {@link Query}
@@ -111,13 +134,15 @@ export class QueryBase<
  NativeQueryType extends NativeQuery | NativeVectorQuery | NativeTakeQuery,
 > implements AsyncIterable<RecordBatch>
 {
+  protected inner!: NativeQueryType | Promise<NativeQueryType>;
+
  /**
   * @hidden
   */
-  protected constructor(
-    protected inner: NativeQueryType | Promise<NativeQueryType>,
-  ) {
-    // intentionally empty
+  protected constructor(inner?: NativeQueryType | Promise<NativeQueryType>) {
+    if (inner !== undefined) {
+      this.inner = inner;
+    }
  }

  // call a function on the inner (either a promise or the actual object)
@@ -135,6 +160,15 @@ export class QueryBase<
    }
  }

+  /**
+   * Return the native query used by the next terminal operation.
+   *
+   * @hidden
+   */
+  protected async getInner(): Promise<NativeQueryType> {
+    return this.inner;
+  }
+
  /**
   * Return only the specified columns.
   *
@@ -207,16 +241,11 @@ export class QueryBase<
  /**
   * @hidden
   */
-  protected nativeExecute(
+  protected async nativeExecute(
    options?: Partial<QueryExecutionOptions>,
  ): Promise<NativeBatchIterator> {
-    if (this.inner instanceof Promise) {
-      return this.inner.then((inner) =>
-        inner.execute(options?.maxBatchLength, options?.timeoutMs),
-      );
-    } else {
-      return this.inner.execute(options?.maxBatchLength, options?.timeoutMs);
-    }
+    const inner = await this.getInner();
+    return inner.execute(options?.maxBatchLength, options?.timeoutMs);
  }

  /**
@@ -245,12 +274,7 @@ export class QueryBase<
  /** Collect the results as an Arrow @see {@link ArrowTable}. */
  async toArrow(options?: Partial<QueryExecutionOptions>): Promise<ArrowTable> {
    const batches = [];
-    let inner;
-    if (this.inner instanceof Promise) {
-      inner = await this.inner;
-    } else {
-      inner = this.inner;
-    }
+    const inner = await this.getInner();
    for await (const batch of new RecordBatchIterable(inner, options)) {
      batches.push(batch);
    }
@@ -279,11 +303,8 @@ export class QueryBase<
   * @returns A Promise that resolves to a string containing the query execution plan explanation.
   */
  async explainPlan(verbose = false): Promise<string> {
-    if (this.inner instanceof Promise) {
-      return this.inner.then((inner) => inner.explainPlan(verbose));
-    } else {
-      return this.inner.explainPlan(verbose);
-    }
+    const inner = await this.getInner();
+    return inner.explainPlan(verbose);
  }

  /**
@@ -321,13 +342,8 @@ export class QueryBase<
    distributedMetrics?: AnalyzePlanDistributedMetrics,
  ): Promise<string> {
    const distributedMetricsMode = distributedMetrics ?? "aggregate";
-    if (this.inner instanceof Promise) {
-      return this.inner.then((inner) =>
-        inner.analyzePlan(distributedMetricsMode),
-      );
-    } else {
-      return this.inner.analyzePlan(distributedMetricsMode);
-    }
+    const inner = await this.getInner();
+    return inner.analyzePlan(distributedMetricsMode);
  }

  /**
@@ -339,12 +355,8 @@ export class QueryBase<
   * @returns An Arrow Schema describing the output columns.
   */
  async outputSchema(): Promise<import("./arrow").Schema> {
-    let schemaBuffer: Buffer;
-    if (this.inner instanceof Promise) {
-      schemaBuffer = await this.inner.then((inner) => inner.outputSchema());
-    } else {
-      schemaBuffer = await this.inner.outputSchema();
-    }
+    const inner = await this.getInner();
+    const schemaBuffer = await inner.outputSchema();
    const schema = tableFromIPC(schemaBuffer).schema;
    return schema;
  }
@@ -356,7 +368,7 @@ export class StandardQueryBase<
  extends QueryBase<NativeQueryType>
  implements ExecutableQuery
 {
-  constructor(inner: NativeQueryType | Promise<NativeQueryType>) {
+  constructor(inner?: NativeQueryType | Promise<NativeQueryType>) {
    super(inner);
  }

@@ -510,6 +522,13 @@ export class VectorQuery extends StandardQueryBase<NativeVectorQuery> {
    super(inner);
  }

+  /**
+   * @hidden
+   */
+  protected doVectorCall(fn: (inner: NativeVectorQuery) => void) {
+    super.doCall(fn);
+  }
+
  /**
   * Set the number of partitions to search (probe)
   *
@@ -537,7 +556,7 @@ export class VectorQuery extends StandardQueryBase<NativeVectorQuery> {
   * the minimum and maximum to the same value.
   */
  nprobes(nprobes: number): VectorQuery {
-    super.doCall((inner) => inner.nprobes(nprobes));
+    this.doVectorCall((inner) => inner.nprobes(nprobes));

    return this;
  }
@@ -551,7 +570,7 @@ export class VectorQuery extends StandardQueryBase<NativeVectorQuery> {
   * but will also increase latency.
   */
  minimumNprobes(minimumNprobes: number): VectorQuery {
-    super.doCall((inner) => inner.minimumNprobes(minimumNprobes));
+    this.doVectorCall((inner) => inner.minimumNprobes(minimumNprobes));
    return this;
  }

@@ -565,7 +584,7 @@ export class VectorQuery extends StandardQueryBase<NativeVectorQuery> {
   * potential false negatives.
   */
  maximumNprobes(maximumNprobes: number): VectorQuery {
-    super.doCall((inner) => inner.maximumNprobes(maximumNprobes));
+    this.doVectorCall((inner) => inner.maximumNprobes(maximumNprobes));
    return this;
  }

@@ -578,7 +597,7 @@ export class VectorQuery extends StandardQueryBase<NativeVectorQuery> {
   * `undefined` means no lower or upper bound.
   */
  distanceRange(lowerBound?: number, upperBound?: number): VectorQuery {
-    super.doCall((inner) => inner.distanceRange(lowerBound, upperBound));
+    this.doVectorCall((inner) => inner.distanceRange(lowerBound, upperBound));
    return this;
  }

@@ -592,7 +611,7 @@ export class VectorQuery extends StandardQueryBase<NativeVectorQuery> {
   * also increase the latency of your query. The default value is 1.5*limit.
   */
  ef(ef: number): VectorQuery {
-    super.doCall((inner) => inner.ef(ef));
+    this.doVectorCall((inner) => inner.ef(ef));
    return this;
  }

@@ -606,7 +625,7 @@ export class VectorQuery extends StandardQueryBase<NativeVectorQuery> {
   * whose data type is a fixed-size-list of floats.
   */
  column(column: string): VectorQuery {
-    super.doCall((inner) => inner.column(column));
+    this.doVectorCall((inner) => inner.column(column));
    return this;
  }

@@ -627,7 +646,7 @@ export class VectorQuery extends StandardQueryBase<NativeVectorQuery> {
  distanceType(
    distanceType: Required<IvfPqOptions>["distanceType"],
  ): VectorQuery {
-    super.doCall((inner) => inner.distanceType(distanceType));
+    this.doVectorCall((inner) => inner.distanceType(distanceType));
    return this;
  }

@@ -661,7 +680,7 @@ export class VectorQuery extends StandardQueryBase<NativeVectorQuery> {
   * distance between the query vector and the actual uncompressed vector.
   */
  refineFactor(refineFactor: number): VectorQuery {
-    super.doCall((inner) => inner.refineFactor(refineFactor));
+    this.doVectorCall((inner) => inner.refineFactor(refineFactor));
    return this;
  }

@@ -686,7 +705,7 @@ export class VectorQuery extends StandardQueryBase<NativeVectorQuery> {
   * factor can often help restore some of the results lost by post filtering.
   */
  postfilter(): VectorQuery {
-    super.doCall((inner) => inner.postfilter());
+    this.doVectorCall((inner) => inner.postfilter());
    return this;
  }

@@ -700,7 +719,7 @@ export class VectorQuery extends StandardQueryBase<NativeVectorQuery> {
   * calculate your recall to select an appropriate value for nprobes.
   */
  bypassVectorIndex(): VectorQuery {
-    super.doCall((inner) => inner.bypassVectorIndex());
+    this.doVectorCall((inner) => inner.bypassVectorIndex());
    return this;
  }

@@ -708,43 +727,39 @@ export class VectorQuery extends StandardQueryBase<NativeVectorQuery> {
   * Add a query vector to the search
   *
   * This method can be called multiple times to add multiple query vectors
-   * to the search. If multiple query vectors are added, then they will be searched
-   * in parallel, and the results will be concatenated. A column called `query_index`
-   * will be added to indicate the index of the query vector that produced the result.
-   *
-   * Performance wise, this is equivalent to running multiple queries concurrently.
+   * to the search. A column called `query_index` will be added to indicate the index
+   * of the query vector that produced the result. Flat searches share one table scan
+   * across the query vectors, avoiding the scan and memory amplification of running
+   * multiple queries concurrently. Indexed searches may still perform per-vector
+   * index work.
   */
  addQueryVector(vector: IntoVector): VectorQuery {
    if (vector instanceof Promise) {
+      // Observe the promise as soon as it is accepted. The existing native
+      // query may still be pending, and delaying observation until it resolves
+      // can otherwise surface a fast rejection as unhandled.
+      const settledVector = vector.then(
+        (value) => ({ status: "fulfilled" as const, value }),
+        (reason) => ({ status: "rejected" as const, reason }),
+      );
      const res = (async () => {
-        try {
-          const v = await vector;
-          // biome-ignore lint/suspicious/noExplicitAny: we need to get the `inner`, but js has no package scoping
-          const value: any = this.addQueryVector(v);
-          const inner = value.inner as
-            | NativeVectorQuery
-            | Promise<NativeVectorQuery>;
-          return inner;
-        } catch (e) {
-          return Promise.reject(e);
+        const inner = await this.getInner();
+        const outcome = await settledVector;
+        if (outcome.status === "rejected") {
+          throw outcome.reason;
        }
+        addQueryVectorToNative(inner, outcome.value);
+        return inner;
      })();
      return new VectorQuery(res);
    } else {
-      super.doCall((inner) => {
-        const raw = Array.isArray(vector) ? null : extractVectorBuffer(vector);
-        if (raw) {
-          inner.addQueryVectorRaw(raw.data, raw.dtype);
-        } else {
-          inner.addQueryVector(Float32Array.from(vector as number[]));
-        }
-      });
+      this.doVectorCall((inner) => addQueryVectorToNative(inner, vector));
      return this;
    }
  }

  rerank(reranker: Reranker): VectorQuery {
-    super.doCall((inner) =>
+    this.doVectorCall((inner) =>
      inner.rerank(async (args) => {
        const vecResults = await fromBufferToRecordBatch(args.vecResults);
        const ftsResults = await fromBufferToRecordBatch(args.ftsResults);
@@ -763,6 +778,71 @@ export class VectorQuery extends StandardQueryBase<NativeVectorQuery> {
  }
 }

+/**
+ * Create a string query whose vector/FTS routing is resolved against the active
+ * table schema when the query executes.
+ *
+ * @hidden
+ */
+export function createAutoQuery(
+  table: NativeTable,
+  query: string,
+  columns: string[] | null,
+  getVector: (metadata: string) => Promise<Awaited<IntoVector>>,
+): AutoQuery {
+  type RouteSnapshot = {
+    table: NativeTable;
+    embeddingMetadata: string | undefined;
+  };
+  type CachedPreparation = {
+    metadata: string;
+    vector: Promise<Awaited<IntoVector>>;
+  };
+
+  let cachedPreparation: CachedPreparation | undefined;
+
+  const snapshotRoute = async (): Promise<RouteSnapshot> => {
+    const snapshot = await table.querySnapshot();
+    const schema = tableFromIPC(await snapshot.schema()).schema;
+    return {
+      table: snapshot,
+      embeddingMetadata: schema.metadata.get("embedding_functions"),
+    };
+  };
+
+  const createInner = async (): Promise<NativeQuery | NativeVectorQuery> => {
+    const route = await snapshotRoute();
+    if (route.embeddingMetadata === undefined) {
+      const inner = route.table.query();
+      inner.fullTextSearch({ query, columns });
+      return inner;
+    }
+
+    const metadata = route.embeddingMetadata;
+    if (cachedPreparation?.metadata !== metadata) {
+      cachedPreparation = {
+        metadata,
+        vector: Promise.resolve().then(() => getVector(metadata)),
+      };
+    }
+
+    const preparation = cachedPreparation;
+    let vector: Awaited<IntoVector>;
+    try {
+      vector = await preparation.vector;
+    } catch (error) {
+      if (cachedPreparation === preparation) {
+        cachedPreparation = undefined;
+      }
+      throw error;
+    }
+
+    return nearestToNative(route.table.query(), vector);
+  };
+
+  return new AutoQuery(createInner);
+}
+
 /**
 * A query that returns a subset of the rows in the table.
 *
@@ -788,6 +868,51 @@ export class TakeQuery extends QueryBase<NativeTakeQuery> {
  }
 }

+/**
+ * A builder for automatic string searches.
+ *
+ * Automatic search determines whether to use full-text or vector search from
+ * the table revision selected for each execution. This builder exposes the
+ * common operations supported by both query families.
+ *
+ * @hideconstructor
+ */
+export class AutoQuery extends StandardQueryBase<
+  NativeQuery | NativeVectorQuery
+> {
+  private readonly calls: Array<
+    (inner: NativeQuery | NativeVectorQuery) => void
+  > = [];
+
+  /** @hidden */
+  constructor(
+    private readonly createInner: () => Promise<
+      NativeQuery | NativeVectorQuery
+    >,
+  ) {
+    super();
+  }
+
+  /** @hidden */
+  protected override doCall(
+    fn: (inner: NativeQuery | NativeVectorQuery) => void,
+  ) {
+    this.calls.push(fn);
+  }
+
+  /** @hidden */
+  protected override async getInner(): Promise<
+    NativeQuery | NativeVectorQuery
+  > {
+    const calls = [...this.calls];
+    const inner = await this.createInner();
+    for (const call of calls) {
+      call(inner);
+    }
+    return inner;
+  }
+}
+
 /** A builder for LanceDB queries.
 *
 * @see {@link Table#query}, {@link Table#search}
@@ -840,45 +965,19 @@ export class Query extends StandardQueryBase<NativeQuery> {
   * a default `limit` of 10 will be used.  @see {@link Query#limit}
   */
  nearestTo(vector: IntoVector): VectorQuery {
-    const callNearestTo = (
-      inner: NativeQuery,
-      resolved: Float32Array | Float64Array | Uint8Array | number[],
-    ): NativeVectorQuery => {
-      const raw = Array.isArray(resolved)
-        ? null
-        : extractVectorBuffer(resolved);
-      if (raw) {
-        return inner.nearestToRaw(raw.data, raw.dtype);
-      }
-      return inner.nearestTo(Float32Array.from(resolved as number[]));
-    };
-
-    if (this.inner instanceof Promise) {
-      const nativeQuery = this.inner.then(async (inner) => {
-        const resolved = vector instanceof Promise ? await vector : vector;
-        return callNearestTo(inner, resolved);
-      });
+    const inner = this.inner;
+    if (inner instanceof Promise) {
+      const nativeQuery = inner.then(async (resolvedInner) =>
+        nearestToNative(resolvedInner, await vector),
+      );
      return new VectorQuery(nativeQuery);
    }
    if (vector instanceof Promise) {
-      const res = (async () => {
-        try {
-          const v = await vector;
-          // biome-ignore lint/suspicious/noExplicitAny: we need to get the `inner`, but js has no package scoping
-          const value: any = this.nearestTo(v);
-          const inner = value.inner as
-            | NativeVectorQuery
-            | Promise<NativeVectorQuery>;
-          return inner;
-        } catch (e) {
-          return Promise.reject(e);
-        }
-      })();
-      return new VectorQuery(res);
-    } else {
-      const vectorQuery = callNearestTo(this.inner, vector);
-      return new VectorQuery(vectorQuery);
+      return new VectorQuery(
+        vector.then((resolvedVector) => nearestToNative(inner, resolvedVector)),
+      );
    }
+    return new VectorQuery(nearestToNative(inner, vector));
  }

  nearestToText(query: string | FullTextQuery, columns?: string[]): Query {
@@ -94,17 +94,24 @@ export function sanitizeMetadata(
  if (metadataLike === undefined || metadataLike === null) {
    return undefined;
  }
-  if (!(metadataLike instanceof Map)) {
+
+  let entries: IterableIterator<[unknown, unknown]>;
+  try {
+    entries = Map.prototype.entries.call(metadataLike);
+  } catch {
    throw Error("Expected metadata, if present, to be a Map<string, string>");
  }
-  for (const item of metadataLike) {
-    if (typeof item[0] !== "string" || typeof item[1] !== "string") {
+
+  const metadata = new Map<string, string>();
+  for (const [key, value] of entries) {
+    if (typeof key !== "string" || typeof value !== "string") {
      throw Error(
        "Expected metadata, if present, to be a Map<string, string> but it had non-string keys or values",
      );
    }
+    metadata.set(key, value);
  }
-  return metadataLike as Map<string, string>;
+  return metadata;
 }

 export function sanitizeInt(typeLike: object) {
@@ -406,10 +406,11 @@ function matchingFields(fields: Field[], tree: FieldTree): Field[] {
          field.name,
          new Struct(matchingFields(struct.children, value)),
          field.nullable,
+          field.metadata,
        ),
      );
    } else {
-      matches.push(new Field(field.name, value as DataType, field.nullable));
+      matches.push(field);
    }
  }
  return matches;
@@ -43,10 +43,12 @@ import {
  Table as _NativeTable,
 } from "./native";
 import {
+  AutoQuery,
  FullTextQuery,
  Query,
  TakeQuery,
  VectorQuery,
+  createAutoQuery,
  instanceOfFullTextQuery,
 } from "./query";
 import { sanitizeType } from "./sanitize";
@@ -523,7 +525,7 @@ export abstract class Table {
    query: string | IntoVector | MultiVector | FullTextQuery,
    queryType?: string,
    ftsColumns?: string | string[],
-  ): VectorQuery | Query;
+  ): VectorQuery | Query | AutoQuery;
  /**
   * Search the table with a given query vector.
   *
@@ -628,6 +630,18 @@ export abstract class Table {

  /**
   * Update per-field (column) metadata.
+   *
+   * The following keys are treated specially, by convention, and should be
+   * used when appropriate:
+   *
+   * - `lancedb:description`: for a human-readable description of a field.
+   * - `lancedb:tag:<name>`: for a user-defined key-value tag, where the suffix
+   *   names the tag category; e.g. `lancedb:tag:model: "clip"`.
+   * - `lancedb:logical-column`: for a column grouping; e.g. `feature_v1` and
+   *   `feature_v2` might be in the same logical column.
+   * - `lancedb:status`: for status options (`production`, `candidate`,
+   *   `deprecated`, `archived`) to designate the current life cycle state of
+   *   this column.
   * @param {FieldMetadataUpdate[]} updates One or more per-field updates. Each
   * update's metadata is merged into the field's existing metadata by default;
   * a value of `null` deletes that key, and `replace: true` swaps the whole map.
@@ -975,10 +989,11 @@ export class LocalTable extends Table {
    return this.inner.display();
  }

-  private async getEmbeddingFunctions(): Promise<
-    Map<string, EmbeddingFunctionConfig>
-  > {
-    const schema = await this.schema();
+  private async getEmbeddingFunctions(
+    inner: _NativeTable = this.inner,
+  ): Promise<Map<string, EmbeddingFunctionConfig>> {
+    const schemaBuf = await inner.schema();
+    const schema = tableFromIPC(schemaBuf).schema;
    const registry = getRegistry();
    return registry.parseFunctions(schema.metadata);
  }
@@ -1160,7 +1175,7 @@ export class LocalTable extends Table {
    query: string | IntoVector | MultiVector | FullTextQuery,
    queryType: string = "auto",
    ftsColumns?: string | string[],
-  ): VectorQuery | Query {
+  ): VectorQuery | Query | AutoQuery {
    if (typeof query !== "string" && !instanceOfFullTextQuery(query)) {
      if (queryType === "fts") {
        throw new Error("Cannot perform full text search on a vector query");
@@ -1175,14 +1190,28 @@ export class LocalTable extends Table {
      });
    }

-    // The query type is auto or vector
-    // fall back to full text search if no embedding functions are defined and the query is a string
-    if (
-      queryType === "auto" &&
-      (getRegistry().length() === 0 || instanceOfFullTextQuery(query))
-    ) {
-      return this.query().fullTextSearch(query, {
-        columns: ftsColumns,
+    if (queryType === "auto") {
+      if (instanceOfFullTextQuery(query)) {
+        return this.query().fullTextSearch(query, {
+          columns: ftsColumns,
+        });
+      }
+
+      const columns =
+        typeof ftsColumns === "string" ? [ftsColumns] : (ftsColumns ?? null);
+      return createAutoQuery(this.inner, query, columns, async (metadata) => {
+        const functions = await getRegistry().parseFunctions(
+          new Map([["embedding_functions", metadata]]),
+        );
+        // TODO: Support multiple embedding functions
+        const embeddingFunc: EmbeddingFunctionConfig | undefined = functions
+          .values()
+          .next().value;
+        // The route only calls this callback when embedding metadata exists.
+        // parseFunctions either yields a provider or reports malformed metadata.
+        if (!embeddingFunc)
+          throw new Error("Invalid embedding function metadata");
+        return await embeddingFunc.function.computeQueryEmbeddings(query);
      });
    }

@@ -1538,7 +1567,8 @@ export interface FieldMetadataUpdate {
  path: string;
  /**
   * Metadata key/value pairs. Merged into the field's existing metadata by
-   * default; a value of `null` deletes that key.
+   * default; a value of `null` deletes that key. See
+   * {@link Table.updateFieldMetadata} for the conventional `lancedb:*` keys.
   */
  metadata: Record<string, string | null>;
  /** If true, replace the field's entire metadata map instead of merging. */
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-darwin-arm64",
-	"version": "0.38.0-beta.7",
+	"version": "0.38.0-beta.11",
 	"os": ["darwin"],
 	"cpu": ["arm64"],
 	"main": "lancedb.darwin-arm64.node",
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-arm64-gnu",
-	"version": "0.38.0-beta.7",
+	"version": "0.38.0-beta.11",
 	"os": ["linux"],
 	"cpu": ["arm64"],
 	"main": "lancedb.linux-arm64-gnu.node",
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-arm64-musl",
-	"version": "0.38.0-beta.7",
+	"version": "0.38.0-beta.11",
 	"os": ["linux"],
 	"cpu": ["arm64"],
 	"main": "lancedb.linux-arm64-musl.node",
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-x64-gnu",
-	"version": "0.38.0-beta.7",
+	"version": "0.38.0-beta.11",
 	"os": ["linux"],
 	"cpu": ["x64"],
 	"main": "lancedb.linux-x64-gnu.node",
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-linux-x64-musl",
-	"version": "0.38.0-beta.7",
+	"version": "0.38.0-beta.11",
 	"os": ["linux"],
 	"cpu": ["x64"],
 	"main": "lancedb.linux-x64-musl.node",
@@ -1,6 +1,6 @@
 {
  "name": "@lancedb/lancedb-win32-arm64-msvc",
-  "version": "0.38.0-beta.7",
+  "version": "0.38.0-beta.11",
  "os": [
    "win32"
  ],
@@ -1,6 +1,6 @@
 {
 	"name": "@lancedb/lancedb-win32-x64-msvc",
-	"version": "0.38.0-beta.7",
+	"version": "0.38.0-beta.11",
 	"os": ["win32"],
 	"cpu": ["x64"],
 	"main": "lancedb.win32-x64-msvc.node",
@@ -1,12 +1,12 @@
 {
  "name": "@lancedb/lancedb",
-  "version": "0.38.0-beta.7",
+  "version": "0.38.0-beta.11",
  "lockfileVersion": 3,
  "requires": true,
  "packages": {
    "": {
      "name": "@lancedb/lancedb",
-      "version": "0.38.0-beta.7",
+      "version": "0.38.0-beta.11",
      "cpu": [
        "x64",
        "arm64"
@@ -11,7 +11,7 @@
    "ann"
  ],
  "private": false,
-  "version": "0.38.0-beta.7",
+  "version": "0.38.0-beta.11",
  "main": "dist/index.js",
  "exports": {
    ".": "./dist/index.js",
@@ -278,6 +278,13 @@ impl Table {
        Ok(Query::new(self.inner_ref()?.query()))
    }

+    /// Return a read-only table handle pinned to the current query revision.
+    #[napi(catch_unwind)]
+    pub async fn query_snapshot(&self) -> napi::Result<Self> {
+        let snapshot = self.inner_ref()?.query_snapshot().await.default_error()?;
+        Ok(Self::new(snapshot))
+    }
+
    #[napi(catch_unwind)]
    pub fn take_offsets(&self, offsets: Vec<i64>) -> napi::Result<TakeQuery> {
        Ok(TakeQuery::new(
@@ -554,6 +561,12 @@ impl Table {
            .default_error()
    }

+    #[napi(catch_unwind)]
+    pub async fn checkout_current(&self) -> napi::Result<Self> {
+        let table = self.inner_ref()?.checkout_current().await.default_error()?;
+        Ok(Self::new(table))
+    }
+
    #[napi(catch_unwind)]
    pub async fn checkout(&self, version: i64) -> napi::Result<()> {
        self.inner_ref()?
@@ -1,6 +1,6 @@
 [package]
 name = "lancedb-python"
-version = "0.38.0-beta.7"
+version = "0.38.0-beta.11"
 publish = false
 edition.workspace = true
 description = "Python bindings for LanceDB"
@@ -101,9 +101,12 @@ azure = ["adlfs>=2024.2.0"]
 [tool.maturin]
 python-source = "python"
 module-name = "lancedb._lancedb"
+# uv installs the project as an editable package before `uv run`, so keep that
+# bootstrap build consistent with `maturin develop`.
+editable-profile = "dev"

 [build-system]
-requires = ["maturin>=1.9.4"]
+requires = ["maturin>=1.10"]
 build-backend = "maturin"

 [tool.ruff.lint]
@@ -179,6 +179,18 @@ def connect(
    ...     },
    ... )

+    For Azure Blob Storage, credentials can be passed directly without setting
+    environment variables:
+
+    >>> azure_storage_options = {
+    ...     "account_name": "some-account",
+    ...     "account_key": "some-key",
+    ... }
+    >>> db = lancedb.connect(  # doctest: +SKIP
+    ...     "az://my-container/my-database",
+    ...     storage_options=azure_storage_options,
+    ... )
+
    For tests and temporary data, use an in-memory database:

    >>> db = lancedb.connect("memory://")
@@ -465,6 +477,10 @@ async def connect_async(
    --------

    >>> import lancedb
+    >>> azure_storage_options = {
+    ...     "account_name": "some-account",
+    ...     "account_key": "some-key",
+    ... }
    >>> async def doctest_example():
    ...     # For a local directory, provide a path to the database
    ...     db = await lancedb.connect_async("~/.lancedb")
@@ -472,6 +488,11 @@ async def connect_async(
    ...     db = await lancedb.connect_async("s3://my-bucket/lancedb",
    ...                                      storage_options={
    ...                                          "aws_access_key_id": "***"})
+    ...     # Azure credentials can also be passed directly
+    ...     db = await lancedb.connect_async(
+    ...         "az://my-container/my-database",
+    ...         storage_options=azure_storage_options,
+    ...     )
    ...     # For tests and temporary data, use an in-memory database
    ...     db = await lancedb.connect_async("memory://")
    ...     # Connect to LanceDB cloud
@@ -270,7 +270,8 @@ def _iter_projection_pairs(
            if isinstance(expr, str):
                yield name, expr
            elif isinstance(expr, Expr):
-                yield name, expr.to_sql()
+                source = expr._column_name()
+                yield name, source if source is not None else expr.to_sql()
        return
    for column in projection:
        if isinstance(column, str):
@@ -280,7 +281,8 @@ def _iter_projection_pairs(
            if isinstance(expr, str):
                yield name, expr
            elif isinstance(expr, Expr):
-                yield name, expr.to_sql()
+                source = expr._column_name()
+                yield name, source if source is not None else expr.to_sql()


 def _set_blob_column(tbl: pa.Table, output_name: str, blobs: pa.Array) -> pa.Table:
@@ -87,6 +87,7 @@ class PyExpr:
    def contains(self, substr: "PyExpr") -> "PyExpr": ...
    def isin(self, values: List["PyExpr"]) -> "PyExpr": ...
    def cast(self, data_type: pa.DataType) -> "PyExpr": ...
+    def column_name(self) -> Optional[str]: ...
    def to_sql(self) -> str: ...

 def expr_col(name: str) -> PyExpr: ...
@@ -283,6 +284,7 @@ class Table:
        mode: Literal["append", "overwrite"],
        progress: Optional[Any] = None,
        write_parallelism: Optional[int] = None,
+        allow_external_blob_outside_bases: bool = False,
    ) -> AddResult: ...
    async def update(
        self, updates: Dict[str, str], where: Optional[str]
@@ -607,6 +609,7 @@ class PyQueryRequest:
    filter: Optional[Union[str, bytes]]
    full_text_search: Optional[FullTextQuery]
    select: Optional[Union[str, List[str]]]
+    select_source_columns: Optional[Dict[str, str]]
    fast_search: Optional[bool]
    with_row_id: Optional[bool]
    use_lsm: Optional[bool]
@@ -249,6 +249,10 @@ class Expr:

    # ── utilities ────────────────────────────────────────────────────────────

+    def _column_name(self) -> str | None:
+        """Return the source name when this is a bare column expression."""
+        return self._inner.column_name()
+
    def to_sql(self) -> str:
        """Render the expression as a SQL string (useful for debugging)."""
        return self._inner.to_sql()
@@ -312,7 +316,7 @@ def func(name: str, *args: ExprLike) -> Expr:
    --------
    >>> from lancedb.expr import col, func
    >>> func("lower", col("name"))
-    Expr(lower(name))
+    Expr(lower(`name`))
    """
    inner_args = [_coerce(a)._inner for a in args]
    return Expr(expr_func(name, inner_args))
@@ -4,7 +4,7 @@
 """Canonical Function values exchanged with LanceDB Enterprise services.

 These immutable models contain client/wire state only. Catalog persistence,
-environment bake, secret resolution, and execution are owned by Sophon.
+environment bake, and execution are owned by Sophon.
 ``RefreshColumnResult`` is also the backend-neutral result of a local
 expression-backed refresh job.
 """
@@ -25,7 +25,6 @@ import re
 import sys
 import textwrap
 import types
-import uuid
 from collections.abc import Mapping
 from datetime import date, datetime
 from typing import (
@@ -223,13 +222,14 @@ class PythonEnvironmentSpec(_RemoteValue):

    kind: str
    packages: tuple[str, ...] = ()
+    channels: tuple[str, ...] = ()
    path: Optional[str] = None
    modules: tuple[str, ...] = ()
    image: Optional[str] = None


 class PythonRuntimeSpec(_RemoteValue):
-    """Remote runtime definition with non-secret environment values.
+    """Remote runtime definition with environment values.

    V1 supports ``kind="python"``. Newer runtime kinds remain readable, while
    their unknown payload fields are intentionally not retained by the client.
@@ -268,7 +268,6 @@ class FunctionVersion(_RemoteValue):
    runtime: PythonRuntimeSpec
    runtime_digest: str
    environment_digest: str
-    required_secrets: tuple[str, ...] = ()
    created_at: str

    def __call__(self, **inputs: Any) -> FunctionApplication:
@@ -276,7 +275,7 @@ class FunctionVersion(_RemoteValue):

        Every input must be a direct [lancedb.col][lancedb.expr.col]
        reference. The returned application is immutable and retains a
-        named-struct output as one sibling group, so every row's sibling values
+        named-struct output as one binding, so every row's sibling values
        come from one logical Function evaluation. Map result fields to table
        columns with
        [FunctionApplication.rename][lancedb.functions.FunctionApplication.rename],
@@ -326,22 +325,16 @@ class FunctionVersion(_RemoteValue):
            function=FunctionVersionRef(name=self.name, version=self.version),
            inputs=tuple(bindings),
            output=self.signature.output,
-            group_id=f"fg_{uuid.uuid4().hex}",
        )


 class FunctionRegistrationRequest(_RemoteValue):
-    """Stable remote registration envelope produced by :func:`udf`.
-
-    Only secret names are represented. Secret values are resolved inside the
-    remote service and have no client request field.
-    """
+    """Stable remote registration envelope produced by :func:`udf`."""

    name: str
    artifact: FunctionArtifactRequest
    signature: FunctionSignature
    runtime: PythonRuntimeSpec
-    required_secrets: tuple[str, ...] = ()


 class FunctionVersionRef(_OpenRemoteValue):
@@ -370,7 +363,7 @@ class ApplicationInput(_OpenRemoteValue):
 class FunctionApplication(_OpenRemoteValue):
    """Immutable pre-declaration application of an exact Function version.

-    A named-struct output remains one grouped application through table
+    A named-struct output remains one application through table
    declaration and execution.
    [FunctionApplication.rename][lancedb.functions.FunctionApplication.rename]
    records the result-field to table-column mapping without splitting sibling
@@ -380,7 +373,6 @@ class FunctionApplication(_OpenRemoteValue):
    function: FunctionVersionRef
    inputs: tuple[ApplicationInput, ...]
    output: FunctionOutput
-    group_id: str
    columns: Mapping[str, str] = Field(default_factory=dict)

    def _known_dict(self) -> dict[str, Any]:
@@ -452,12 +444,10 @@ class OutputMapping(_RemoteValue):


 class FunctionBinding(_RemoteValue):
-    """Immutable grouped binding persisted by the Enterprise table service."""
+    """Immutable Function binding persisted by the Enterprise table service."""

    binding_id: str
-    revision: _UInt64
    function: FunctionVersionRef
-    group_id: str
    inputs: tuple[InputBinding, ...]
    outputs: tuple[OutputMapping, ...]
    input_schema: Optional[Mapping[str, Any]] = None
@@ -489,7 +479,6 @@ class RefreshColumnResult(_RemoteValue):


 _FUNCTION_NAME = re.compile(r"^[A-Za-z_][A-Za-z0-9_.-]*$")
-_SECRET_NAME = re.compile(r"^[A-Za-z_][A-Za-z0-9_]*$")


 _GRAMMAR_PRIMITIVES = (
@@ -920,33 +909,32 @@ class UdfDefinition:
        output_schema: Optional[pa.DataType | pa.Field | pa.Schema],
        pip: tuple[str, ...],
        env: Mapping[str, str],
-        secrets: tuple[str, ...],
        python_version: Optional[str],
+        conda: tuple[str, ...] = (),
+        conda_channels: tuple[str, ...] = (),
    ):
        function_name = name or function.__name__
        if not _FUNCTION_NAME.fullmatch(function_name):
            raise ValueError(f"invalid Function name: {function_name!r}")
-        packages = tuple(sorted(set(pip)))
+        if pip and conda:
+            raise ValueError("a Function environment is pip or conda, not both")
+        if conda_channels and not conda:
+            raise ValueError("conda_channels requires conda packages")
+        packages = tuple(sorted(set(conda if conda else pip)))
        if any(not package or package != package.strip() for package in packages):
-            raise ValueError("pip requirements must be non-empty and trimmed")
+            raise ValueError("package requirements must be non-empty and trimmed")
+        if conda:
+            environment_spec = PythonEnvironmentSpec(
+                kind="conda", packages=packages, channels=tuple(conda_channels)
+            )
+        else:
+            environment_spec = PythonEnvironmentSpec(kind="pip", packages=packages)
        environment = dict(env)
        if any(
            not isinstance(key, str) or not isinstance(value, str)
            for key, value in environment.items()
        ):
            raise TypeError("Function env keys and values must be strings")
-        required_secrets = tuple(sorted(set(secrets)))
-        invalid_secrets = [
-            secret for secret in required_secrets if not _SECRET_NAME.fullmatch(secret)
-        ]
-        if invalid_secrets:
-            raise ValueError(f"invalid Function secret names: {invalid_secrets!r}")
-        overlap = set(environment) & set(required_secrets)
-        if overlap:
-            raise ValueError(
-                f"Function env and secret names must be disjoint: {sorted(overlap)!r}"
-            )
-
        signature = _infer_signature(function, input_schema, output_schema)
        source = _package_source(function)
        digest = f"sha256:{hashlib.sha256(source).hexdigest()}"
@@ -954,7 +942,7 @@ class UdfDefinition:
            kind="python",
            python_version=python_version
            or f"{sys.version_info.major}.{sys.version_info.minor}",
-            environment=PythonEnvironmentSpec(kind="pip", packages=packages),
+            environment=environment_spec,
            env=environment,
        )
        self._function = function
@@ -975,7 +963,6 @@ class UdfDefinition:
            ),
            signature=signature,
            runtime=runtime,
-            required_secrets=required_secrets,
        )
        functools.update_wrapper(self, function)

@@ -1001,8 +988,9 @@ def udf(
    output_schema: Optional[pa.DataType | pa.Field | pa.Schema] = None,
    pip: tuple[str, ...] | list[str] = (),
    env: Optional[Mapping[str, str]] = None,
-    secrets: tuple[str, ...] | list[str] = (),
    python_version: Optional[str] = None,
+    conda: tuple[str, ...] | list[str] = (),
+    conda_channels: tuple[str, ...] | list[str] = (),
 ) -> Callable[[Callable[..., Any]], UdfDefinition]: ...


@@ -1014,8 +1002,9 @@ def udf(
    output_schema: Optional[pa.DataType | pa.Field | pa.Schema] = None,
    pip: tuple[str, ...] | list[str] = (),
    env: Optional[Mapping[str, str]] = None,
-    secrets: tuple[str, ...] | list[str] = (),
    python_version: Optional[str] = None,
+    conda: tuple[str, ...] | list[str] = (),
+    conda_channels: tuple[str, ...] | list[str] = (),
 ):
    """Prepare a scalar Python callable for remote Function registration.

@@ -1038,11 +1027,12 @@ def udf(
        provided together with ``input_schema``.
    pip : sequence of str, optional
        Pip requirements for the remote environment.
+    conda : sequence of str, optional
+        Conda packages for the remote environment, instead of ``pip``.
+    conda_channels : sequence of str, optional
+        Conda channels in priority order; requires ``conda``.
    env : mapping of str to str, optional
-        Non-secret environment variables. Use ``secrets`` for credentials.
-    secrets : sequence of str, optional
-        Names of secrets resolved by the remote service. Secret values are not
-        accepted by this API or included in the registration request.
+        Environment variables included in the Function definition.
    python_version : str, optional
        Remote Python major/minor version. Defaults to the client version.

@@ -1064,7 +1054,7 @@ def udf(
    Examples
    --------
    >>> from lancedb import udf
-    >>> @udf(pip=["numpy==2.2.0"], secrets=["MODEL_TOKEN"])
+    >>> @udf(pip=["numpy==2.2.0"])
    ... def score(value: float) -> float:
    ...     return value * 2
    >>> score(1.5)
@@ -1079,8 +1069,9 @@ def udf(
            output_schema=output_schema,
            pip=tuple(pip),
            env={} if env is None else env,
-            secrets=tuple(secrets),
            python_version=python_version,
+            conda=tuple(conda),
+            conda_channels=tuple(conda_channels),
        )

    if function is None:
@@ -7,6 +7,7 @@ from typing import List, Literal, Optional
 from ._lancedb import (
    IndexConfig,
 )
+from .query import DocumentGranularity
 from .types import BaseTokenizerType

 lang_mapping = {
@@ -121,6 +122,11 @@ class FTS:

    >>> config = FTS(block_size=256)

+    Create an index that treats each deepest-list element as one document:
+
+    >>> from lancedb.query import DocumentGranularity
+    >>> config = FTS(document_granularity=DocumentGranularity.LIST_ELEMENT)
+
    Attributes
    ----------
    with_position : bool, default False
@@ -172,6 +178,11 @@ class FTS:
        roughly half of the available CPU cores. The effective value is
        limited by the available compute capacity. This build-only setting is
        not persisted with the index and does not apply to remote tables.
+    document_granularity : DocumentGranularity, default ROW
+        ``ROW`` treats the selected text in one table row as one document.
+        ``LIST_ELEMENT`` treats each element of the deepest list on the indexed
+        field path as one document and returns its physical coordinates in
+        ``_doc_index`` for matching queries.

    Notes
    -----
@@ -196,6 +207,7 @@ class FTS:
    custom_stop_words: Optional[List[str]] = None
    memory_limit: Optional[int] = None
    num_workers: Optional[int] = None
+    document_granularity: DocumentGranularity = DocumentGranularity.ROW


@dataclass
@@ -167,6 +167,12 @@ def _projection_to_scanner_kwargs(columns: QueryProjection) -> Dict[str, Any]:
    return {"columns": projection}


+def _query_request_projection(req: "PyQueryRequest") -> QueryProjection:
+    if req.select_source_columns is not None:
+        return req.select_source_columns
+    return req.select
+
+
 def _scanner_kwargs_for_query(
    query: Query,
    blob_mode: BlobMode,
@@ -375,6 +381,13 @@ class FullTextOperator(str, Enum):
    OR = "OR"


+class DocumentGranularity(str, Enum):
+    """The unit treated as one full-text-search document."""
+
+    ROW = "row"
+    LIST_ELEMENT = "list_element"
+
+
 class Occur(str, Enum):
    SHOULD = "SHOULD"
    MUST = "MUST"
@@ -478,6 +491,10 @@ class MatchQuery(FullTextQuery):
    prefix_length : int, optional
        The number of beginning characters being unchanged for fuzzy matching.
        This is useful to achieve prefix matching.
+    document_granularity : DocumentGranularity, optional
+        Explicitly select row or deepest-list-element documents. If omitted,
+        the indexed granularity is inferred. When both granularities are indexed
+        for the field, this must be specified. With no index, row granularity is used.
    """

    query: str
@@ -487,6 +504,9 @@ class MatchQuery(FullTextQuery):
    max_expansions: int = pydantic.Field(50, kw_only=True)
    operator: FullTextOperator = pydantic.Field(FullTextOperator.OR, kw_only=True)
    prefix_length: int = pydantic.Field(0, kw_only=True)
+    document_granularity: Optional[DocumentGranularity] = pydantic.Field(
+        None, kw_only=True
+    )

    def query_type(self) -> FullTextQueryType:
        return FullTextQueryType.MATCH
@@ -503,11 +523,20 @@ class PhraseQuery(FullTextQuery):
        The query string to match against.
    column : str
        The name of the column to match against.
+    slop : int, default 0
+        The maximum number of intervening positions permitted in the phrase.
+    document_granularity : DocumentGranularity, optional
+        Explicitly select row or deepest-list-element documents. If omitted,
+        the indexed granularity is inferred. When both granularities are indexed
+        for the field, this must be specified. With no index, row granularity is used.
    """

    query: str
    column: str
    slop: int = pydantic.Field(0, kw_only=True)
+    document_granularity: Optional[DocumentGranularity] = pydantic.Field(
+        None, kw_only=True
+    )

    def query_type(self) -> FullTextQueryType:
        return FullTextQueryType.MATCH_PHRASE
@@ -2776,15 +2805,16 @@ class AsyncQueryBase(object):

        req = self._inner.to_query_request()
        schema = await self._table.schema()
+        projection = _query_request_projection(req)
        self._blob_auto_row_id = blob_auto_row_id_for_scan(
            schema,
-            req.select,
+            projection,
            with_row_id=self._with_row_id,
        )
        if not self._blob_auto_row_id:
            self._blob_paths = ()
            return
-        self._blob_paths = tuple(blob_v2_projection_sources(schema, req.select).keys())
+        self._blob_paths = tuple(blob_v2_projection_sources(schema, projection).keys())
        self._inner.with_row_id()

    def select(self, columns: Union[List[str], dict[str, str]]) -> Self:
@@ -3378,9 +3408,10 @@ class AsyncQuery(AsyncStandardQuery):
        pass in multiple vectors. When multiple vectors are passed in, if the vector
        column is with multivector type, then the vectors will be treated as a single
        query. Or the vectors will be treated as multiple queries, this can be useful
-        if you want to find the nearest vectors to multiple query vectors.
-        This is not expected to be faster than making multiple queries concurrently;
-        it is just a convenience method. If multiple vectors are passed in then
+        if you want to find the nearest vectors to multiple query vectors. Flat
+        searches share one table scan across the query vectors, avoiding the scan
+        and memory amplification of making multiple queries concurrently. If
+        multiple vectors are passed in then
        an additional column `query_index` will be added to the results. This column
        will contain the index of the query vector that the result is nearest to.
        """
@@ -3509,8 +3540,8 @@ class AsyncFTSQuery(AsyncStandardQuery):

        Typically, a single vector is passed in as the query. However, you can also
        pass in multiple vectors.  This can be useful if you want to find the nearest
-        vectors to multiple query vectors. This is not expected to be faster than
-        making multiple queries concurrently; it is just a convenience method.
+        vectors to multiple query vectors. Flat searches share one table scan across
+        the query vectors instead of issuing concurrent full scans.
        If multiple vectors are passed in then an additional column `query_index`
        will be added to the results.  This column will contain the index of the
        query vector that the result is nearest to.
@@ -3870,14 +3901,15 @@ class AsyncHybridQuery(AsyncStandardQuery, AsyncVectorQueryBase):
        blob_paths: tuple[str, ...] = ()
        if self._table is not None:
            schema = await self._table.schema()
+            projection = _query_request_projection(req)
            blob_auto_row_id = blob_auto_row_id_for_scan(
                schema,
-                req.select,
+                projection,
                with_row_id=self._with_row_id,
            )
            if blob_auto_row_id:
                blob_paths = tuple(
-                    blob_v2_projection_sources(schema, req.select).keys()
+                    blob_v2_projection_sources(schema, projection).keys()
                )
        self._blob_auto_row_id = blob_auto_row_id
        self._blob_paths = blob_paths
@@ -36,6 +36,7 @@ from lancedb._lancedb import (
    UpdateResult,
 )
 from lancedb.embeddings.base import EmbeddingFunctionConfig
+from lancedb.expr import Expr
 from lancedb.index import (
    FTS,
    BTree,
@@ -61,6 +62,7 @@ from lancedb.table import _normalize_progress

 from ..query import (
    AnalyzePlanDistributedMetrics,
+    DocumentGranularity,
    LanceQueryBuilder,
    LanceTakeQueryBuilder,
    LanceVectorQueryBuilder,
@@ -349,6 +351,7 @@ class RemoteTable(Table):
        ngram_max_length: int = 3,
        prefix_only: bool = False,
        block_size: int = 128,
+        document_granularity: DocumentGranularity = DocumentGranularity.ROW,
        name: Optional[str] = None,
    ):
        """Create a full-text search index on a column.
@@ -371,6 +374,7 @@ class RemoteTable(Table):
            ngram_max_length=ngram_max_length,
            prefix_only=prefix_only,
            block_size=block_size,
+            document_granularity=document_granularity,
        )
        LOOP.run(
            self._table.create_index(
@@ -610,6 +614,7 @@ class RemoteTable(Table):
        fill_value: float = 0.0,
        progress: Optional[Union[bool, Callable, Any]] = None,
        write_parallelism: Optional[int] = None,
+        allow_external_blob_outside_bases: bool = False,
    ) -> AddResult:
        """Add more data to the [Table][lancedb.table.Table].

@@ -642,6 +647,8 @@ class RemoteTable(Table):
            data in flight. Defaults to an estimate based on the data size,
            capped at the number of CPU cores. Lower this if bulk ingestion is
            using too much memory.
+        allow_external_blob_outside_bases: bool, default False
+            Not supported on LanceDB Cloud. Setting this raises.

        Returns
        -------
@@ -658,6 +665,7 @@ class RemoteTable(Table):
                    fill_value=fill_value,
                    progress=progress,
                    write_parallelism=write_parallelism,
+                    allow_external_blob_outside_bases=allow_external_blob_outside_bases,
                )
            )
        finally:
@@ -856,7 +864,7 @@ class RemoteTable(Table):

    def update(
        self,
-        where: Optional[str] = None,
+        where: Optional[Union[str, Expr]] = None,
        values: Optional[dict] = None,
        *,
        values_sql: Optional[Dict[str, str]] = None,
@@ -867,9 +875,11 @@ class RemoteTable(Table):

        Parameters
        ----------
-        where: str, optional
-            The SQL where clause to use when updating rows. For example, 'x = 2'
-            or 'x IN (1, 2, 3)'. The filter must not be empty, or it will error.
+        where: str or [Expr][lancedb.expr.Expr], optional
+            The filter condition. Can be a SQL string or a type-safe
+            [Expr][lancedb.expr.Expr] built with [col][lancedb.expr.col] and
+            [lit][lancedb.expr.lit]. The filter must not be empty, or it will
+            error.
        values: dict, optional
            The values to update. The keys are the column names and the values
            are the values to set.
@@ -85,6 +85,7 @@ from .query import (
    AsyncQuery,
    AsyncTakeQuery,
    AsyncVectorQuery,
+    DocumentGranularity,
    FullTextQuery,
    LanceEmptyQueryBuilder,
    LanceFtsQueryBuilder,
@@ -1168,6 +1169,7 @@ class Table(ABC):
        ngram_max_length: int = 3,
        prefix_only: bool = False,
        block_size: int = 128,
+        document_granularity: DocumentGranularity = DocumentGranularity.ROW,
        wait_timeout: Optional[timedelta] = None,
        name: Optional[str] = None,
    ):
@@ -1246,6 +1248,11 @@ class Table(ABC):
            The number of documents per compressed posting block. Must be 128
            or 256. A value of 256 uses the experimental FTS V3 format and
            may introduce breaking changes.
+        document_granularity: DocumentGranularity, default ROW
+            ``ROW`` treats the selected text in one table row as one document.
+            ``LIST_ELEMENT`` treats each element of the deepest list on the field
+            path as one document and returns its physical coordinates in
+            ``_doc_index`` for matching queries.
        wait_timeout: timedelta, optional
            The timeout to wait if indexing is asynchronous.
        name: str, optional
@@ -1269,6 +1276,7 @@ class Table(ABC):
        fill_value: float = 0.0,
        progress: Optional[Union[bool, Callable, Any]] = None,
        write_parallelism: Optional[int] = None,
+        allow_external_blob_outside_bases: bool = False,
    ) -> AddResult:
        """Add more data to the [Table][lancedb.table.Table].

@@ -1320,6 +1328,10 @@ class Table(ABC):
            data in flight. Defaults to an estimate based on the data size,
            capped at the number of CPU cores. Lower this if bulk ingestion is
            using too much memory.
+        allow_external_blob_outside_bases: bool, default False
+            Store blob URIs that sit outside registered blob bases. The row
+            keeps a reference, so the object has to stay readable. Local
+            tables only.

        Returns
        -------
@@ -1732,7 +1744,7 @@ class Table(ABC):
    @abstractmethod
    def update(
        self,
-        where: Optional[str] = None,
+        where: Optional[Union[str, Expr]] = None,
        values: Optional[dict] = None,
        *,
        values_sql: Optional[Dict[str, str]] = None,
@@ -1747,9 +1759,11 @@ class Table(ABC):

        Parameters
        ----------
-        where: str, optional
-            The SQL where clause to use when updating rows. For example, 'x = 2'
-            or 'x IN (1, 2, 3)'. The filter must not be empty, or it will error.
+        where: str or [Expr][lancedb.expr.Expr], optional
+            The filter condition. Can be a SQL string or a type-safe
+            [Expr][lancedb.expr.Expr] built with [col][lancedb.expr.col] and
+            [lit][lancedb.expr.lit]. The filter must not be empty, or it will
+            error.
        values: dict, optional
            The values to update. The keys are the column names and the values
            are the values to set.
@@ -1767,6 +1781,7 @@ class Table(ABC):
        Examples
        --------
        >>> import lancedb
+        >>> from lancedb.expr import col
        >>> import pandas as pd
        >>> data = pd.DataFrame({"x": [1, 2, 3], "vector": [[1.0, 2], [3, 4], [5, 6]]})
        >>> db = lancedb.connect("./.lancedb")
@@ -1776,7 +1791,7 @@ class Table(ABC):
        0  1  [1.0, 2.0]
        1  2  [3.0, 4.0]
        2  3  [5.0, 6.0]
-        >>> table.update(where="x = 2", values={"vector": [10.0, 10]})
+        >>> table.update(where=col("x") == 2, values={"vector": [10.0, 10]})
        UpdateResult(rows_updated=1, version=2)
        >>> table.to_pandas()
           x        vector
@@ -1972,7 +1987,7 @@ class Table(ABC):
            A mapping with one ``FunctionApplication`` value keeps its scalar
            or named-struct result in the named table column. A bare
            named-struct application expands its ordered result fields as one
-            atomic sibling group; aliases come from ``rename(columns=...)``.
+            atomic binding; aliases come from ``rename(columns=...)``.
            Function columns are supported only on LanceDB Cloud and
            Enterprise.
        computed: Dict[str, str], optional
@@ -2115,12 +2130,25 @@ class Table(ABC):
        ----------
        updates : dict
            One or more dicts, each with:
+
            - "path": str — dot-path to the field (e.g. "embedding" or "a.b.c").
            - "metadata": dict[str, str | None] — keys to set; a value of ``None``
              deletes that key.
            - "replace": bool, optional — replace the field's whole metadata map
              instead of merging (default False).

+            The following keys are treated specially, by convention, and should
+            be used when appropriate:
+
+            - "lancedb:description": for a human-readable description of a field.
+            - ``"lancedb:tag:<name>"`` for a user-defined key-value tag, where the
+                suffix names the tag category; e.g. "lancedb:tag:model": "clip".
+            - "lancedb:logical-column" for a column grouping; e.g. "feature_v1"
+                and "feature_v2" might be in the same logical column.
+            - "lancedb:status" for status options ("production", "candidate",
+                "deprecated", "archived") to designate the current life cycle
+                state of this column.
+
        Returns
        -------
        UpdateFieldMetadataResult
@@ -3268,6 +3296,7 @@ class LanceTable(Table):
        ngram_max_length: int = 3,
        prefix_only: bool = False,
        block_size: int = 128,
+        document_granularity: DocumentGranularity = DocumentGranularity.ROW,
        name: Optional[str] = None,
    ):
        """Create a full-text search index on a column.
@@ -3319,7 +3348,11 @@ class LanceTable(Table):
            tokenizer_configs = self.infer_tokenizer_configs(tokenizer_name)
            tokenizer_configs["custom_stop_words"] = custom_stop_words

-        config = FTS(block_size=block_size, **tokenizer_configs)
+        config = FTS(
+            block_size=block_size,
+            document_granularity=document_granularity,
+            **tokenizer_configs,
+        )

        try:
            LOOP.run(
@@ -3409,6 +3442,7 @@ class LanceTable(Table):
        fill_value: float = 0.0,
        progress: Optional[Union[bool, Callable, Any]] = None,
        write_parallelism: Optional[int] = None,
+        allow_external_blob_outside_bases: bool = False,
    ) -> AddResult:
        """Add data to the table.
        If vector columns are missing and the table
@@ -3436,6 +3470,9 @@ class LanceTable(Table):
            data in flight. Defaults to an estimate based on the data size,
            capped at the number of CPU cores. Lower this if bulk ingestion is
            using too much memory.
+        allow_external_blob_outside_bases: bool, default False
+            Allow blob URIs outside registered bases. See :meth:`Table.add`.
+            Local tables only.

        Returns
        -------
@@ -3452,6 +3489,7 @@ class LanceTable(Table):
                    fill_value=fill_value,
                    progress=progress,
                    write_parallelism=write_parallelism,
+                    allow_external_blob_outside_bases=allow_external_blob_outside_bases,
                )
            )
        finally:
@@ -3806,7 +3844,7 @@ class LanceTable(Table):

    def update(
        self,
-        where: Optional[str] = None,
+        where: Optional[Union[str, Expr]] = None,
        values: Optional[dict] = None,
        *,
        values_sql: Optional[Dict[str, str]] = None,
@@ -3817,9 +3855,11 @@ class LanceTable(Table):

        Parameters
        ----------
-        where: str, optional
-            The SQL where clause to use when updating rows. For example, 'x = 2'
-            or 'x IN (1, 2, 3)'. The filter must not be empty, or it will error.
+        where: str or [Expr][lancedb.expr.Expr], optional
+            The filter condition. Can be a SQL string or a type-safe
+            [Expr][lancedb.expr.Expr] built with [col][lancedb.expr.col] and
+            [lit][lancedb.expr.lit]. The filter must not be empty, or it will
+            error.
        values: dict, optional
            The values to update. The keys are the column names and the values
            are the values to set.
@@ -3837,6 +3877,7 @@ class LanceTable(Table):
        Examples
        --------
        >>> import lancedb
+        >>> from lancedb.expr import col
        >>> import pandas as pd
        >>> data = pd.DataFrame({"x": [1, 2, 3], "vector": [[1.0, 2], [3, 4], [5, 6]]})
        >>> db = lancedb.connect("./.lancedb")
@@ -3846,7 +3887,7 @@ class LanceTable(Table):
        0  1  [1.0, 2.0]
        1  2  [3.0, 4.0]
        2  3  [5.0, 6.0]
-        >>> table.update(where="x = 2", values={"vector": [10.0, 10]})
+        >>> table.update(where=col("x") == 2, values={"vector": [10.0, 10]})
        UpdateResult(rows_updated=1, version=2)
        >>> table.to_pandas()
           x        vector
@@ -5365,6 +5406,7 @@ class AsyncTable:
        fill_value: Optional[float] = None,
        progress: Optional[Union[bool, Callable, Any]] = None,
        write_parallelism: Optional[int] = None,
+        allow_external_blob_outside_bases: bool = False,
    ) -> AddResult:
        """Add more data to the [AsyncTable][lancedb.table.AsyncTable].

@@ -5395,6 +5437,9 @@ class AsyncTable:
            data in flight. Defaults to an estimate based on the data size,
            capped at the number of CPU cores. Lower this if bulk ingestion is
            using too much memory.
+        allow_external_blob_outside_bases: bool, default False
+            Allow blob URIs outside registered bases. See :meth:`Table.add`.
+            Local tables only.

        """
        schema = await self.schema()
@@ -5431,6 +5476,7 @@ class AsyncTable:
                mode or "append",
                progress=progress,
                write_parallelism=write_parallelism,
+                allow_external_blob_outside_bases=allow_external_blob_outside_bases,
            )
        except RuntimeError as e:
            if "Cast error" in str(e):
@@ -5955,7 +6001,7 @@ class AsyncTable:
        self,
        updates: Optional[Dict[str, Any]] = None,
        *,
-        where: Optional[str] = None,
+        where: Optional[Union[str, Expr]] = None,
        updates_sql: Optional[Dict[str, str]] = None,
    ) -> UpdateResult:
        """
@@ -5970,9 +6016,11 @@ class AsyncTable:
            The updates to apply.  The keys should be the name of the column to
            update.  The values should be the new values to assign.  This is
            required unless updates_sql is supplied.
-        where: str, optional
-            An SQL filter that controls which rows are updated. For example, 'x = 2'
-            or 'x IN (1, 2, 3)'.  Only rows that satisfy this filter will be udpated.
+        where: str or [Expr][lancedb.expr.Expr], optional
+            The filter condition. Can be a SQL string or a type-safe
+            [Expr][lancedb.expr.Expr] built with [col][lancedb.expr.col] and
+            [lit][lancedb.expr.lit]. Only rows that satisfy this filter will
+            be updated.
        updates_sql: dict, optional
            The updates to apply, expressed as SQL expression strings.  The keys should
            be column names. The values should be SQL expressions.  These can be SQL
@@ -5990,13 +6038,14 @@ class AsyncTable:
        --------
        >>> import asyncio
        >>> import lancedb
+        >>> from lancedb.expr import col
        >>> import pandas as pd
        >>> async def demo_update():
        ...     data = pd.DataFrame({"x": [1, 2], "vector": [[1, 2], [3, 4]]})
        ...     db = await lancedb.connect_async("./.lancedb")
        ...     table = await db.create_table("my_table", data)
        ...     # x is [1, 2], vector is [[1, 2], [3, 4]]
-        ...     await table.update({"vector": [10, 10]}, where="x = 2")
+        ...     await table.update({"vector": [10, 10]}, where=col("x") == 2)
        ...     # x is [1, 2], vector is [[1, 2], [10, 10]]
        ...     await table.update(updates_sql={"x": "x + 1"})
        ...     # x is [2, 3], vector is [[1, 2], [10, 10]]
@@ -6010,7 +6059,8 @@ class AsyncTable:
        if updates is not None:
            updates_sql = {k: value_to_sql(v) for k, v in updates.items()}

-        return await self._inner.update(updates_sql, where)
+        predicate = where.to_sql() if isinstance(where, Expr) else where
+        return await self._inner.update(updates_sql, predicate)

    async def add_columns(
        self,
@@ -6038,7 +6088,7 @@ class AsyncTable:
            A mapping with one ``FunctionApplication`` value keeps its scalar
            or named-struct result in the named table column. A bare
            named-struct application expands its ordered result fields as one
-            atomic sibling group; aliases come from ``rename(columns=...)``.
+            atomic binding; aliases come from ``rename(columns=...)``.
            Function columns are supported only on LanceDB Cloud and
            Enterprise.
        computed: Dict[str, str], optional
@@ -6075,7 +6125,7 @@ class AsyncTable:
                isinstance(value, FunctionApplication) for value in transforms.values()
            ):
                raise ValueError(
-                    "one add_columns call declares exactly one Function sibling group"
+                    "one add_columns call declares exactly one Function binding"
                )
            function_output_name, function_application = next(iter(transforms.items()))

@@ -105,7 +105,7 @@ def test_quickstart(tmp_path):
    tbl.create_index(num_sub_vectors=1)
    # --8<-- [end:create_index]
    # --8<-- [start:delete_rows]
-    tbl.delete('item = "fizz"')
+    tbl.delete("item = 'fizz'")
    # --8<-- [end:delete_rows]
    # --8<-- [start:drop_table]
    db.drop_table("my_table")
@@ -201,7 +201,7 @@ async def test_quickstart_async(tmp_path):
    await tbl.create_index("vector")
    # --8<-- [end:create_index_async]
    # --8<-- [start:delete_rows_async]
-    await tbl.delete('item = "fizz"')
+    await tbl.delete("item = 'fizz'")
    # --8<-- [end:delete_rows_async]
    # --8<-- [start:drop_table_async]
    await db.drop_table("my_table_async")
@@ -266,7 +266,7 @@ def test_table():
    tbl.add(pydantic_model_items)
    # --8<-- [end:add_table_from_pydantic]
    # --8<-- [start:delete_row]
-    tbl.delete('item = "fizz"')
+    tbl.delete("item = 'fizz'")
    # --8<-- [end:delete_row]
    # --8<-- [start:delete_specific_row]
    data = [
@@ -538,7 +538,7 @@ async def test_table_async():
    await async_tbl.add(pydantic_model_items)
    # --8<-- [end:add_table_async_from_pydantic]
    # --8<-- [start:delete_row_async]
-    await async_tbl.delete('item = "fizz"')
+    await async_tbl.delete("item = 'fizz'")
    # --8<-- [end:delete_row_async]
    # --8<-- [start:delete_specific_row_async]
    data = [
@@ -8,7 +8,12 @@ import pyarrow.compute as pc
 import pytest

 import lancedb
-from lancedb._blob import read_row_ids_from_hits, stash_auto_row_ids
+from lancedb._blob import (
+    blob_v2_projection_sources,
+    read_row_ids_from_hits,
+    stash_auto_row_ids,
+)
+from lancedb.expr import col
 from lancedb.index import FTS
 from lancedb.schema import blob_column_paths, blob_v2_column_paths

@@ -70,6 +75,14 @@ def test_blob_v2_column_paths_include_list_children():
    ]


+def test_blob_v2_projection_sources_use_typed_column_name():
+    schema = pa.schema([lancedb.blob("blob")])
+
+    assert blob_v2_projection_sources(schema, {"blob_alias": col("blob")}) == {
+        "blob_alias": "blob"
+    }
+
+
 def _legacy_v1_table(name):
    db = lancedb.connect("memory:///")
    schema = pa.schema(
@@ -166,6 +179,20 @@ async def test_async_table_to_pandas_descriptions_mode_omits_row_id():
    assert set(descriptor.keys()) == {"kind", "position", "size", "blob_id", "blob_uri"}


+@pytest.mark.asyncio
+async def test_async_typed_blob_projection_preserves_source_column():
+    db = await lancedb.connect_async("memory:///typed_blob_projection")
+    schema = pa.schema([pa.field("id", pa.int64()), lancedb.blob("blob")])
+    table = await db.create_table("typed_blob_projection", schema=schema)
+    await table.add([{"id": 1, "blob": b"alpha"}])
+
+    hits = await table.query().select({"blob_alias": col("blob")}).to_arrow()
+
+    assert "_lance_row_id" in hits.schema.field("blob_alias").type.names
+    blobs = await table.fetch_blobs("blob", hits)
+    assert blobs.to_pylist() == [b"alpha"]
+
+
 def test_fetch_blobs_round_trip():
    table = _blob_table(
        "round_trip",
@@ -403,6 +430,50 @@ async def test_blob_v2_hybrid_fetch_blobs_async():
    assert {blobs[i].as_py() for i in range(len(blobs))} == {b"alpha", b"beta"}


+@pytest.mark.asyncio
+async def test_async_hybrid_typed_blob_projection_preserves_source_column():
+    db = await lancedb.connect_async("memory:///hybrid_typed_blob")
+    schema = pa.schema(
+        [
+            pa.field("id", pa.int64()),
+            pa.field("text", pa.utf8()),
+            pa.field("vector", pa.list_(pa.float32(), list_size=2)),
+            lancedb.blob("blob"),
+        ]
+    )
+    table = await db.create_table("hybrid_typed_blob", schema=schema)
+    await table.add(
+        [
+            {
+                "id": 1,
+                "text": "hello alpha",
+                "vector": [1.0, 0.0],
+                "blob": b"alpha",
+            },
+            {
+                "id": 2,
+                "text": "hello beta",
+                "vector": [0.9, 0.1],
+                "blob": b"beta",
+            },
+        ]
+    )
+    await table.create_index("text", config=FTS(with_position=False))
+
+    hits = await (
+        table.query()
+        .nearest_to([1.0, 0.0])
+        .nearest_to_text("hello")
+        .select({"blob_alias": col("blob")})
+        .limit(2)
+        .to_arrow()
+    )
+
+    assert "_lance_row_id" in hits.schema.field("blob_alias").type.names
+    blobs = await table.fetch_blobs("blob", hits)
+    assert {blobs[i].as_py() for i in range(len(blobs))} == {b"alpha", b"beta"}
+
+
 def test_blob_file_seek_read_and_read_range():
    payload = _identifiable_payload(1024)
    table = _blob_table("seek_read", [{"id": 1, "image": payload}])
@@ -617,3 +688,71 @@ def test_fetch_blobs_nested_path_survives_sort_after_query():
 def _identifiable_payload(size: int) -> bytes:
    block = 256
    return b"".join(bytes([i % 256]) * block for i in range(size // block))
+
+
+def _external_uri_blob_array(uris):
+    blob_type = lancedb.blob("image").type
+    storage_type = blob_type.storage_type
+    child_names = [field.name for field in storage_type]
+    assert "uri" in child_names, "blob layout no longer has a uri child"
+    children = [
+        pa.array(uris if field.name == "uri" else [None] * len(uris), type=field.type)
+        for field in storage_type
+    ]
+    storage = pa.StructArray.from_arrays(children, fields=list(storage_type))
+    return pa.ExtensionArray.from_storage(blob_type, storage)
+
+
+def _external_uri_table_and_rows(name, uris):
+    db = lancedb.connect("memory:///")
+    schema = pa.schema([pa.field("id", pa.int64()), lancedb.blob("image")])
+    table = db.create_table(name, schema=schema)
+    rows = pa.Table.from_arrays(
+        [
+            pa.array(range(len(uris)), type=pa.int64()),
+            _external_uri_blob_array(uris),
+        ],
+        schema=schema,
+    )
+    return table, rows
+
+
+def test_add_external_uri_struct_round_trips_with_flag(tmp_path):
+    payload = b"external-uri-bytes"
+    blob_path = tmp_path / "payload.bin"
+    blob_path.write_bytes(payload)
+
+    table, rows = _external_uri_table_and_rows("external_struct", [blob_path.as_uri()])
+    table.add(rows, allow_external_blob_outside_bases=True)
+
+    hits = table.search().to_arrow()
+    blobs = table.fetch_blobs("image", hits)
+    assert blobs[0].as_py() == payload
+
+
+def test_add_external_uri_without_flag_raises(tmp_path):
+    blob_path = tmp_path / "payload.bin"
+    blob_path.write_bytes(b"unreachable")
+
+    table, rows = _external_uri_table_and_rows("external_no_flag", [blob_path.as_uri()])
+    with pytest.raises(ValueError, match="allow_external_blob_outside_bases"):
+        table.add(rows)
+    assert table.count_rows() == 0
+
+
+def test_add_external_uri_string_round_trips_with_flag(tmp_path):
+    payload = b"external-uri-bytes"
+    blob_path = tmp_path / "payload.bin"
+    blob_path.write_bytes(payload)
+
+    db = lancedb.connect("memory:///")
+    schema = pa.schema([pa.field("id", pa.int64()), lancedb.blob("image")])
+    table = db.create_table("external_string", schema=schema)
+    table.add(
+        [{"id": 1, "image": blob_path.as_uri()}],
+        allow_external_blob_outside_bases=True,
+    )
+
+    hits = table.search().to_arrow()
+    blobs = table.fetch_blobs("image", hits)
+    assert blobs[0].as_py() == payload
@@ -52,7 +52,7 @@ class TestExprConstruction:
    def test_func(self):
        e = func("lower", col("name"))
        assert isinstance(e, Expr)
-        assert e.to_sql() == "lower(name)"
+        assert e.to_sql() == "lower(`name`)"

    def test_func_unknown_raises(self):
        with pytest.raises(Exception):
@@ -115,7 +115,7 @@ class TestExprOperators:
    def test_and_operator(self):
        e = (col("age") > lit(18)) & (col("status") == lit("active"))
        assert isinstance(e, Expr)
-        assert e.to_sql() == "((age > 18) AND (status = 'active'))"
+        assert e.to_sql() == "((age > 18) AND (`status` = 'active'))"

    def test_or_operator(self):
        e = (col("a") == lit(1)) | (col("b") == lit(2))
@@ -166,7 +166,7 @@ class TestExprOperators:
    def test_coerce_plain_str(self):
        e = col("name") == "alice"
        assert isinstance(e, Expr)
-        assert e.to_sql() == "(name = 'alice')"
+        assert e.to_sql() == "(`name` = 'alice')"

    def test_reflexive_comparisons(self):
        # 10 < col("age") swaps to col("age") > 10
@@ -198,85 +198,85 @@ class TestExprBytesLiteral:

    def test_bytes_equality_expr_sql(self):
        e = col("data") == lit(b"\xca\xfe")
-        assert e.to_sql() == "(data = X'CAFE')"
+        assert e.to_sql() == "(`data` = X'CAFE')"

    def test_bytes_ne_expr_sql(self):
        e = col("data") != lit(b"\xff")
-        assert e.to_sql() == "(data <> X'FF')"
+        assert e.to_sql() == "(`data` <> X'FF')"

    def test_bytes_compound_expr_sql(self):
        e = (col("data") == lit(b"\x01")) & (col("id") > lit(5))
-        assert e.to_sql() == "((data = X'01') AND (id > 5))"
+        assert e.to_sql() == "((`data` = X'01') AND (id > 5))"

    def test_bytes_in_function_call(self):
        # Regression test: binary literals inside scalar function calls
        # used to fail because DataFusion's unparser does not support Binary
        # scalars.  Now handled via a placeholder-substitution rewrite.
        e = func("contains", col("data"), lit(b"\xff"))
-        assert e.to_sql() == "contains(data, X'FF')"
+        assert e.to_sql() == "contains(`data`, X'FF')"

    def test_bytes_in_not(self):
        e = ~(col("data") == lit(b"\xff"))
-        assert e.to_sql() == "NOT (data = X'FF')"
+        assert e.to_sql() == "NOT (`data` = X'FF')"


 class TestExprStringMethods:
    def test_lower(self):
        e = col("name").lower()
        assert isinstance(e, Expr)
-        assert e.to_sql() == "lower(name)"
+        assert e.to_sql() == "lower(`name`)"

    def test_upper(self):
        e = col("name").upper()
        assert isinstance(e, Expr)
-        assert e.to_sql() == "upper(name)"
+        assert e.to_sql() == "upper(`name`)"

    def test_contains(self):
        e = col("text").contains(lit("hello"))
        assert isinstance(e, Expr)
-        assert e.to_sql() == "contains(text, 'hello')"
+        assert e.to_sql() == "contains(`text`, 'hello')"

    def test_contains_with_str_coerce(self):
        e = col("text").contains("hello")
        assert isinstance(e, Expr)
-        assert e.to_sql() == "contains(text, 'hello')"
+        assert e.to_sql() == "contains(`text`, 'hello')"

    def test_chained_lower_eq(self):
        e = col("name").lower() == lit("alice")
        assert isinstance(e, Expr)
-        assert e.to_sql() == "(lower(name) = 'alice')"
+        assert e.to_sql() == "(lower(`name`) = 'alice')"


 class TestExprCast:
    def test_cast_string(self):
        e = col("id").cast("string")
        assert isinstance(e, Expr)
-        assert e.to_sql() == "CAST(id AS VARCHAR)"
+        assert e.to_sql() == "arrow_cast(id, 'Utf8')"

    def test_cast_int32(self):
        e = col("score").cast("int32")
        assert isinstance(e, Expr)
-        assert e.to_sql() == "CAST(score AS INTEGER)"
+        assert e.to_sql() == "arrow_cast(score, 'Int32')"

    def test_cast_float64(self):
        e = col("val").cast("float64")
        assert isinstance(e, Expr)
-        assert e.to_sql() == "CAST(val AS DOUBLE)"
+        assert e.to_sql() == "arrow_cast(val, 'Float64')"

    def test_cast_pyarrow_type(self):
        e = col("score").cast(pa.int32())
        assert isinstance(e, Expr)
-        assert e.to_sql() == "CAST(score AS INTEGER)"
+        assert e.to_sql() == "arrow_cast(score, 'Int32')"

    def test_cast_pyarrow_float64(self):
        e = col("val").cast(pa.float64())
        assert isinstance(e, Expr)
-        assert e.to_sql() == "CAST(val AS DOUBLE)"
+        assert e.to_sql() == "arrow_cast(val, 'Float64')"

    def test_cast_pyarrow_string(self):
        e = col("id").cast(pa.string())
        assert isinstance(e, Expr)
-        assert e.to_sql() == "CAST(id AS VARCHAR)"
+        assert e.to_sql() == "arrow_cast(id, 'Utf8')"

    def test_cast_pyarrow_and_string_equivalent(self):
        # pa.int32() and "int32" should produce equivalent SQL
@@ -597,14 +597,14 @@ class TestExprIsin:
    def test_isin_strs(self):
        assert (
            col("status").isin(["active", "pending"]).to_sql()
-            == "status IN ('active', 'pending')"
+            == "`status` IN ('active', 'pending')"
        )

    def test_isin_coerces_and_mixes(self):
        assert col("id").isin([lit(1), 2]).to_sql() == "id IN (1, 2)"

    def test_isin_empty(self):
-        assert col("id").isin([]).to_sql() == "id IN ()"
+        assert col("id").isin([]).to_sql() == "false"

    def test_isin_filter(self, simple_table):
        result = simple_table.search().where(col("id").isin([1, 3, 5])).to_arrow()
@@ -37,21 +37,6 @@ def job_result(name: str) -> dict:
    return json.loads(fixture(name))["result"]


-def assert_no_secret_values(value):
-    if isinstance(value, dict):
-        for key, child in value.items():
-            assert key not in {
-                "secret_value",
-                "secret_values",
-                "resolved_secret",
-                "resolved_secrets",
-            }
-            assert_no_secret_values(child)
-    elif isinstance(value, list):
-        for child in value:
-            assert_no_secret_values(child)
-
-
 def test_public_function_values_are_in_api_reference():
    docs = Path(__file__).parents[3] / "docs" / "src" / "python" / "python.md"
    rendered = docs.read_text()
@@ -109,7 +94,6 @@ def test_function_version_identity_is_immutable_and_exact():
    version = FunctionVersion.from_json(json.dumps(value))
    assert version.name == "embed"
    assert version.version == "fv_01K3EXACT"
-    assert version.required_secrets == ("HF_TOKEN",)

    with pytest.raises((TypeError, ValueError)):
        version.version = "fv_changed"
@@ -121,7 +105,7 @@ def test_function_version_identity_is_immutable_and_exact():
    assert FunctionVersion(**changed) != version


-def test_function_version_binds_named_columns_as_one_immutable_group():
+def test_function_version_binds_named_columns_as_one_immutable_application():
    version = FunctionVersion.from_json(
        json.dumps(job_result("remote_function_job.json"))
    )
@@ -131,13 +115,10 @@ def test_function_version_binds_named_columns_as_one_immutable_group():
    assert application.function.name == version.name
    assert application.function.version == version.version
    assert application.output is version.signature.output
-    assert application.group_id.startswith("fg_")
    assert [
        (value.parameter, value.kind, value.value["path"])
        for value in application.inputs
    ] == [("text", "column", "documents.body")]
-    with pytest.raises((TypeError, ValueError)):
-        application.group_id = "fg_changed"


 def test_function_version_binding_validates_names_and_direct_columns():
@@ -156,7 +137,7 @@ def test_function_version_binding_validates_names_and_direct_columns():
 def test_function_version_keeps_named_struct_outputs_in_one_application():
    value = job_result("remote_function_job.json")
    value["name"] = "text_features"
-    value["version"] = "fv_grouped"
+    value["version"] = "fv_multi_output"
    value["signature"] = {
        "inputs": [
            {"name": "title", "arrow_type": "utf8", "nullable": True},
@@ -221,7 +202,6 @@ def test_function_application_uses_rename_columns_only():
    assert application.columns["normalized_text"] == "search_text"
    assert renamed.columns["normalized_text"] == "body_normalized"
    assert renamed.function == application.function
-    assert renamed.group_id == application.group_id
    assert not hasattr(application, "rename_outputs")
    with pytest.raises(TypeError, match="immutable"):
        renamed.columns["normalized_text"] = "changed"
@@ -242,7 +222,6 @@ def test_function_application_uses_rename_columns_only():

 def test_binding_and_refresh_result_keep_stable_remote_fields():
    binding = FunctionBinding.from_json(fixture("remote_function_binding.json"))
-    assert binding.revision == 3
    assert binding.function.version == "fv_01K3TEXT"
    assert [output.output_ordinal for output in binding.outputs] == [0, 1]
    assert binding.input_schema is not None
@@ -297,15 +276,6 @@ def test_refresh_result_rejects_non_u64_values(field):
        RefreshColumnResult.from_json(json.dumps(value))


-def test_canonical_client_values_contain_secret_names_only():
-    version = FunctionVersion.from_json(
-        json.dumps(job_result("remote_function_job.json"))
-    )
-    canonical = json.loads(version.to_canonical_json())
-    assert canonical["required_secrets"] == ["HF_TOKEN"]
-    assert_no_secret_values(canonical)
-
-
 class _FunctionDeclarationInner:
    def __init__(self):
        self.calls = []
@@ -322,7 +292,7 @@ def known_application() -> FunctionApplication:


@pytest.mark.asyncio
-async def test_add_columns_routes_struct_as_one_and_grouped_expansion_atomically():
+async def test_add_columns_routes_struct_as_one_and_multi_output_binding_atomically():
    inner = _FunctionDeclarationInner()
    table = AsyncTable(inner)
    application = known_application()
@@ -343,12 +313,12 @@ async def test_add_columns_routes_struct_as_one_and_grouped_expansion_atomically


@pytest.mark.asyncio
-async def test_add_columns_rejects_mixed_groups_and_unknown_newer_application():
+async def test_add_columns_rejects_multiple_bindings_and_unknown_newer_application():
    inner = _FunctionDeclarationInner()
    table = AsyncTable(inner)
    application = known_application()

-    with pytest.raises(ValueError, match="exactly one Function sibling group"):
+    with pytest.raises(ValueError, match="exactly one Function binding"):
        await table.add_columns({"a": application, "b": application})

    future = json.loads(fixture("remote_function_application.json"))
@@ -376,7 +346,6 @@ def test_rename_requires_named_struct_and_keeps_partial_mapping_immutable():
                    "arrow_type": "list<float32>",
                    "nullable": False,
                },
-                "group_id": "fg_scalar",
            }
        )
    )
@@ -39,28 +39,12 @@ FIXTURES = (
@udf(
    pip=["numpy>=2"],
    env={"MODE": "test"},
-    secrets=["API_TOKEN"],
    python_version="3.12",
 )
 def normalize_score(value: float) -> float:
    return value / 100.0


-def _assert_no_secret_values(value):
-    if isinstance(value, dict):
-        for key, child in value.items():
-            assert key not in {
-                "secret_value",
-                "secret_values",
-                "resolved_secret",
-                "resolved_secrets",
-            }
-            _assert_no_secret_values(child)
-    elif isinstance(value, list):
-        for child in value:
-            _assert_no_secret_values(child)
-
-
 def test_scalar_udf_matches_shared_registration_golden_and_remains_callable():
    assert isinstance(normalize_score, UdfDefinition)
    assert normalize_score(25.0) == 0.25
@@ -75,8 +59,6 @@ def test_scalar_udf_matches_shared_registration_golden_and_remains_callable():
        "kind": "scalar_to_arrow_batch",
        "version": 1,
    }
-    assert request["required_secrets"] == ["API_TOKEN"]
-    _assert_no_secret_values(request)


 def _run_packaged(definition, *args):
@@ -87,6 +69,26 @@ def _run_packaged(definition, *args):
    return namespace[definition.registration_request.artifact.entrypoint](*args)


+def test_udf_conda_environment():
+    @udf(conda=["scipy", "numpy"], conda_channels=["conda-forge", "defaults"])
+    def halve(value: float) -> float:
+        return value / 2
+
+    request = json.loads(halve.registration_request.to_canonical_json())
+    assert request["runtime"]["environment"] == {
+        "kind": "conda",
+        "packages": ["numpy", "scipy"],
+        "channels": ["conda-forge", "defaults"],
+    }
+    pip_request = json.loads(normalize_score.registration_request.to_canonical_json())
+    assert "channels" not in pip_request["runtime"]["environment"]
+
+    with pytest.raises(ValueError, match="not both"):
+        udf(name="both", pip=["numpy"], conda=["numpy"])(lambda value: value)
+    with pytest.raises(ValueError, match="requires conda"):
+        udf(name="channels", conda_channels=["conda-forge"])(lambda value: value)
+
+
 def test_udf_packages_attribute_access_and_body_imports():
    @udf
    def word_norm(body: str) -> float:
@@ -370,7 +372,6 @@ def test_udf_recursion_versus_a_rebound_module_name(tmp_path):
        output_schema=None,
        pip=(),
        env={},
-        secrets=(),
        python_version=None,
    )
    with pytest.raises(ValueError, match="binds that name to another value"):
@@ -525,14 +526,6 @@ def test_annotation_and_explicit_schema_validation_fail_closed():
            return value


-def test_environment_rejects_secret_value_overlap():
-    with pytest.raises(ValueError, match="must be disjoint"):
-
-        @udf(env={"TOKEN": "plaintext"}, secrets=["TOKEN"])
-        def overlapping(value: int) -> int:
-            return value
-
-
 def test_local_function_catalog_operations_are_not_supported(tmp_path):
    db = lancedb.connect(tmp_path)
    message = "Function catalog operations are not supported by this database"
@@ -569,7 +562,6 @@ def _mock_remote_function_catalog():
                    "runtime": body["runtime"],
                    "runtime_digest": "sha256:runtime",
                    "environment_digest": "sha256:environment",
-                    "required_secrets": body.get("required_secrets", []),
                    "created_at": "2026-08-21T00:00:00Z",
                }
                response = {"job_id": "job-register"}
@@ -628,7 +620,6 @@ def test_remote_registration_job_and_exact_version_reopen_round_trip():
    assert create_request == json.loads(
        normalize_score.registration_request.to_canonical_json()
    )
-    _assert_no_secret_values(create_request)


 def test_blocking_remote_registration_returns_function_version():
@@ -25,6 +25,7 @@ from lancedb.db import DBConnection
 from lancedb.index import FTS
 from lancedb.query import (
    BoostQuery,
+    DocumentGranularity,
    MatchQuery,
    MultiMatchQuery,
    PhraseQuery,
@@ -245,6 +246,55 @@ def test_create_inverted_index_rejects_invalid_block_size(table):
        table.create_index("text", config=FTS(block_size=129))


+def test_list_element_document_granularity(tmp_path):
+    docs_type = pa.list_(pa.struct([pa.field("content", pa.string())]))
+    docs = pa.array(
+        [
+            [
+                {"content": "alpha beta"},
+                None,
+                {"content": ""},
+                {"content": "the and"},
+                {"content": "alpha beta"},
+            ]
+        ],
+        type=docs_type,
+    )
+    table = ldb.connect(tmp_path).create_table(
+        "list_element_docs", pa.table({"id": [0], "docs": docs})
+    )
+    row_table = ldb.connect(tmp_path).create_table(
+        "row_docs", pa.table({"id": [0], "docs": docs})
+    )
+    row_table.create_index("docs.content", config=FTS())
+    row_result = row_table.search(MatchQuery("alpha", "docs.content")).to_arrow()
+    assert row_result.num_rows == 1
+    assert "_doc_index" not in row_result.column_names
+
+    granularity = DocumentGranularity.LIST_ELEMENT
+    table.create_index(
+        "docs.content",
+        config=FTS(with_position=True, document_granularity=granularity),
+    )
+    assert table.list_indices()[0].columns == ["docs.content"]
+
+    def coordinates(query):
+        result = table.search(query).limit(10).to_arrow()
+        doc_index_type = result.schema.field("_doc_index").type
+        assert pa.types.is_list(doc_index_type)
+        assert doc_index_type.value_type == pa.uint32()
+        return sorted(result["_doc_index"].to_pylist())
+
+    assert coordinates(
+        MatchQuery("alpha", "docs.content", document_granularity=granularity)
+    ) == [[0], [4]]
+    assert coordinates(
+        PhraseQuery("alpha beta", "docs.content", document_granularity=granularity)
+    ) == [[0], [4]]
+    assert coordinates(MatchQuery("alpha", "docs.content")) == [[0], [4]]
+    assert FTS().document_granularity is DocumentGranularity.ROW
+
+
 def test_create_inverted_index_respects_build_memory_limit(table):
    with pytest.raises(ValueError, match="exceeds worker memory limit"):
        table.create_index(
@@ -1089,6 +1139,20 @@ def test_fts_query_to_json():
    )
    assert json_str == expected

+    # Test MatchQuery with list-element document granularity
+    match_query = MatchQuery(
+        "hello world",
+        "text",
+        document_granularity=DocumentGranularity.LIST_ELEMENT,
+    )
+    json_str = match_query.to_json()
+    expected = (
+        '{"match":{"column":"text","terms":"hello world","boost":1.0,'
+        '"fuzziness":0,"max_expansions":50,"operator":"Or","prefix_length":0,'
+        '"document_granularity":"list_element"}}'
+    )
+    assert json_str == expected
+
    # Test MatchQuery with options
    match_query = MatchQuery("puppy", "text", fuzziness=2, boost=1.5, prefix_length=3)
    json_str = match_query.to_json()
@@ -1098,6 +1162,19 @@ def test_fts_query_to_json():
    )
    assert json_str == expected

+    # Test PhraseQuery with list-element document granularity
+    phrase_query = PhraseQuery(
+        "quick brown fox",
+        "title",
+        document_granularity=DocumentGranularity.LIST_ELEMENT,
+    )
+    json_str = phrase_query.to_json()
+    expected = (
+        '{"phrase":{"column":"title","terms":"quick brown fox","slop":0,'
+        '"document_granularity":"list_element"}}'
+    )
+    assert json_str == expected
+
    # Test PhraseQuery
    phrase_query = PhraseQuery("quick brown fox", "title")
    json_str = phrase_query.to_json()
@@ -675,6 +675,21 @@ def test_distance_range(table: lancedb.table.Table):
    assert res["_distance"].to_pylist() == [min_dist, max_dist]


+@pytest.mark.parametrize("expression", ["1 - _distance", "1.0 - _distance"])
+def test_select_arithmetic_with_distance(table, expression):
+    result = (
+        table.search([10, 10])
+        .select({"similarity": expression, "_distance": "_distance"})
+        .distance_type("cosine")
+        .to_arrow()
+    )
+
+    assert result.schema.field("similarity").type == pa.float32()
+    assert result["similarity"].to_pylist() == pytest.approx(
+        [1 - distance for distance in result["_distance"].to_pylist()]
+    )
+
+
@pytest.mark.asyncio
 async def test_distance_range_async(table_async: AsyncTable):
    q = [0, 0]
@@ -897,6 +912,23 @@ def test_query_builder_batches(table):
    assert rs_list["id"][1] == 2


+def test_batch_vector_query_shares_filtered_flat_scan(table):
+    query = (
+        table.search([[1.0, 2.0], [3.0, 4.0]])
+        .where("id > 0", prefilter=True)
+        .limit(1)
+        .select(["id"])
+    )
+
+    plan = query.explain_plan(verbose=True)
+    assert "KNNVectorDistance: queries=2" in plan
+    assert "UnionExec" not in plan
+
+    results = query.to_arrow()
+    assert len(results) == 2
+    assert results["query_index"].to_pylist() == [0, 1]
+
+
 def test_dynamic_projection(table):
    rs = (
        LanceVectorQueryBuilder(table, [0, 0], "vector")
@@ -1618,6 +1618,49 @@ def test_query_sync_fts():
        )


+def test_query_sync_fts_document_granularity():
+    from lancedb.query import DocumentGranularity, MatchQuery
+
+    def handler(body):
+        assert body == {
+            "full_text_query": {
+                "query": {
+                    "match": {
+                        "column": "docs.content",
+                        "terms": "alpha",
+                        "boost": 1.0,
+                        "fuzziness": 0,
+                        "max_expansions": 50,
+                        "operator": "Or",
+                        "prefix_length": 0,
+                        "document_granularity": "list_element",
+                    }
+                }
+            },
+            "k": 10,
+            "prefilter": True,
+            "vector": [],
+            "version": None,
+        }
+        return pa.table(
+            {
+                "id": [1, 1],
+                "_doc_index": pa.array([[0], [4]], type=pa.list_(pa.uint32())),
+            }
+        )
+
+    with query_test_table(handler, server_version=Version("0.6.0")) as table:
+        result = table.search(
+            MatchQuery(
+                "alpha",
+                "docs.content",
+                document_granularity=DocumentGranularity.LIST_ELEMENT,
+            )
+        ).to_arrow()
+
+    assert result["_doc_index"].to_pylist() == [[0], [4]]
+
+
 def test_query_sync_hybrid():
    def handler(body):
        if "full_text_query" in body:
@@ -4,6 +4,7 @@

 import asyncio
 import copy
+from concurrent.futures import ThreadPoolExecutor
 from datetime import timedelta
 import threading

@@ -86,6 +87,25 @@ def test_s3_lifecycle(s3_bucket: str):
    asyncio.run(test())


+@pytest.mark.s3_test
+def test_concurrent_open_table(s3_bucket: str):
+    uri = f"s3://{s3_bucket}/test_concurrent_open_table"
+    db = lancedb.connect(uri, storage_options=copy.copy(CONFIG))
+    db.create_table("test", pa.table({"x": [1, 2, 3]}))
+
+    num_workers = 32
+    barrier = threading.Barrier(num_workers)
+
+    def open_and_count(_):
+        barrier.wait()
+        return db.open_table("test").count_rows()
+
+    with ThreadPoolExecutor(max_workers=num_workers) as pool:
+        row_counts = list(pool.map(open_and_count, range(num_workers)))
+
+    assert row_counts == [3] * num_workers
+
+
@pytest.fixture()
 def kms_key():
    kms = get_boto3_client("kms", endpoint_url=CONFIG["aws_endpoint"])
@@ -11,6 +11,7 @@ import warnings
 import weakref
 from concurrent.futures import ThreadPoolExecutor
 from datetime import date, datetime, timedelta
+from decimal import Decimal
 from time import sleep
 from typing import List
 from unittest.mock import patch
@@ -336,6 +337,21 @@ async def test_update_async(mem_db_async: AsyncConnection):
    assert await table.count_rows("id == 10") == 1


+@pytest.mark.asyncio
+async def test_update_expr_filter_literals_async(mem_db_async: AsyncConnection):
+    values = ["5", "4.66e-84", "it's"]
+    table = await mem_db_async.create_table(
+        "update_expr_literals",
+        data=[{"field": value, "result": "original"} for value in values],
+    )
+
+    for value in values:
+        update_res = await table.update({"result": value}, where=col("field") == value)
+        assert update_res.rows_updated == 1
+
+    assert (await table.to_arrow())["result"].to_pylist() == values
+
+
 def test_create_table(mem_db: DBConnection):
    schema = pa.schema(
        {
@@ -2343,6 +2359,148 @@ def test_update(mem_db: DBConnection):
    assert np.allclose(v, np.array([[1.2, 1.9], [1.1, 1.1]]))


+def test_update_expr_filter_literals(mem_db: DBConnection):
+    values = ["5", "4.66e-84", "it's"]
+    table = mem_db.create_table(
+        "update_expr_literals",
+        data=[{"field": value, "result": "original"} for value in values],
+    )
+
+    for value in values:
+        update_res = table.update(where=col("field") == value, values={"result": value})
+        assert update_res.rows_updated == 1
+
+    assert table.to_arrow()["result"].to_pylist() == values
+
+
+def test_update_expr_filter_preserves_typed_semantics(mem_db: DBConnection):
+    low = Decimal("1.234567890123456789")
+    high = Decimal("1.234567890123456790")
+    decimal_schema = pa.schema(
+        [("val", pa.decimal128(19, 18)), ("result", pa.string())]
+    )
+    decimal_table = mem_db.create_table(
+        "update_expr_decimal",
+        pa.table(
+            {"val": [low, high], "result": ["old", "old"]},
+            schema=decimal_schema,
+        ),
+    )
+    predicate = col("val") < lit(high)
+    assert decimal_table.search().where(predicate).to_arrow().num_rows == 1
+    result = decimal_table.update(where=predicate, values={"result": "new"})
+    assert result.rows_updated == 1
+
+    keyword_table = mem_db.create_table(
+        "update_expr_keyword", [{"null": 1, "result": "old"}]
+    )
+    predicate = col("null") == 1
+    assert keyword_table.search().where(predicate).to_arrow().num_rows == 1
+    result = keyword_table.update(where=predicate, values={"result": "new"})
+    assert result.rows_updated == 1
+
+    empty_in_table = mem_db.create_table(
+        "update_expr_empty_in", [{"id": 1, "result": "old"}]
+    )
+    predicate = col("id").isin([])
+    assert empty_in_table.search().where(predicate).to_arrow().num_rows == 0
+    result = empty_in_table.update(where=predicate, values={"result": "new"})
+    assert result.rows_updated == 0
+
+    marker = "__lancedb_binary_placeholder_0__"
+    binary_schema = pa.schema(
+        [("payload", pa.binary()), ("text", pa.string()), ("result", pa.string())]
+    )
+    binary_table = mem_db.create_table(
+        "update_expr_binary",
+        pa.table(
+            {
+                "payload": [b"\x01", b"\x02"],
+                "text": ["other", marker],
+                "result": ["old", "old"],
+            },
+            schema=binary_schema,
+        ),
+    )
+    predicate = (col("payload") == lit(b"\x01")) | (col("text") == marker)
+    assert binary_table.search().where(predicate).to_arrow().num_rows == 2
+    result = binary_table.update(where=predicate, values={"result": "new"})
+    assert result.rows_updated == 2
+
+    nonfinite_table = mem_db.create_table(
+        "update_expr_nonfinite",
+        [{"x": 1.0, "result": "old"}, {"x": 2.0, "result": "old"}],
+    )
+    predicate = col("x") < float("inf")
+    assert nonfinite_table.search().where(predicate).to_arrow().num_rows == 2
+    result = nonfinite_table.update(where=predicate, values={"result": "new"})
+    assert result.rows_updated == 2
+
+    float16_table = mem_db.create_table(
+        "update_expr_float16",
+        [{"x": 1.0, "result": "old"}, {"x": 3.0, "result": "old"}],
+    )
+    predicate = col("x").cast(pa.float16()) < 2.0
+    assert float16_table.search().where(predicate).to_arrow().num_rows == 1
+    result = float16_table.update(where=predicate, values={"result": "new"})
+    assert result.rows_updated == 1
+
+    string_cast_table = mem_db.create_table(
+        "update_expr_string_cast",
+        [{"x": 1, "result": "old"}, {"x": 2, "result": "old"}],
+    )
+    predicate = col("x").cast("string") == "1"
+    assert string_cast_table.search().where(predicate).to_arrow().num_rows == 1
+    result = string_cast_table.update(where=predicate, values={"result": "new"})
+    assert result.rows_updated == 1
+
+    quoted_identifier_schema = pa.schema(
+        [("payload", pa.binary()), ("odd'name", pa.int64()), ("result", pa.string())]
+    )
+    quoted_identifier_table = mem_db.create_table(
+        "update_expr_quoted_identifier",
+        pa.table(
+            {"payload": [b"\x01"], "odd'name": [1], "result": ["old"]},
+            schema=quoted_identifier_schema,
+        ),
+    )
+    predicate = (col("payload") == lit(b"\x01")) & (col("odd'name") == 1)
+    assert quoted_identifier_table.search().where(predicate).to_arrow().num_rows == 1
+    result = quoted_identifier_table.update(where=predicate, values={"result": "new"})
+    assert result.rows_updated == 1
+
+    decimal256_schema = pa.schema(
+        [("val", pa.decimal256(40, 2)), ("result", pa.string())]
+    )
+    decimal256_table = mem_db.create_table(
+        "update_expr_decimal256",
+        pa.table(
+            {
+                "val": [Decimal("1.00"), Decimal("3.00")],
+                "result": ["old", "old"],
+            },
+            schema=decimal256_schema,
+        ),
+    )
+    predicate = col("val") < lit(Decimal("2.00")).cast(pa.decimal256(40, 2))
+    assert decimal256_table.search().where(predicate).to_arrow().num_rows == 1
+    result = decimal256_table.update(where=predicate, values={"result": "new"})
+    assert result.rows_updated == 1
+
+    binary_empty_table = mem_db.create_table(
+        "update_expr_binary_empty",
+        pa.table(
+            {"payload": [b"\x01", b"\x02"], "result": ["old", "old"]},
+            schema=pa.schema([("payload", pa.binary()), ("result", pa.string())]),
+        ),
+    )
+    predicate = (col("payload") == lit(b"\x01")).isin([])
+    assert binary_empty_table.search().where(predicate).to_arrow().num_rows == 0
+    assert predicate.to_sql() == "false"
+    result = binary_empty_table.update(where=predicate, values={"result": "new"})
+    assert result.rows_updated == 0
+
+
 def test_update_with_arrow_scalar(mem_db: DBConnection):
    schema = pa.schema({"id": pa.int64(), "vector": pa.list_(pa.float32(), 4)})
    table = mem_db.create_table("my_table", schema=schema)
@@ -130,6 +130,14 @@ impl PyExpr {

    // ── utilities ────────────────────────────────────────────────────────────

+    /// Return the referenced column name for a bare column expression.
+    fn column_name(&self) -> Option<String> {
+        match &self.0 {
+            DfExpr::Column(column) if column.relation.is_none() => Some(column.name.clone()),
+            _ => None,
+        }
+    }
+
    /// Render the expression as a SQL string (useful for debugging).
    fn to_sql(&self) -> PyResult<String> {
        lancedb::expr::expr_to_sql_string(&self.0).map_err(|e| PyValueError::new_err(e.to_string()))
@@ -8,7 +8,7 @@ use lancedb::index::vector::{
 };
 use lancedb::index::{
    Index as LanceDbIndex,
-    scalar::{BTreeIndexBuilder, FmIndexBuilder, FtsIndexBuilder},
+    scalar::{BTreeIndexBuilder, DocumentGranularity, FmIndexBuilder, FtsIndexBuilder},
 };
 use pyo3::IntoPyObject;
 use pyo3::types::PyStringMethods;
@@ -60,7 +60,11 @@ pub fn extract_index_params(source: &Option<Bound<'_, PyAny>>) -> PyResult<Lance
                    .ngram_min_length(params.ngram_min_length)
                    .ngram_max_length(params.ngram_max_length)
                    .ngram_prefix_only(params.prefix_only)
-                    .custom_stop_words(params.custom_stop_words);
+                    .custom_stop_words(params.custom_stop_words)
+                    .document_granularity(
+                        DocumentGranularity::try_from(params.document_granularity.as_str())
+                            .map_err(|err| PyValueError::new_err(err.to_string()))?,
+                    );
                if let Some(memory_limit) = params.memory_limit {
                    inner_opts = inner_opts.memory_limit_mb(memory_limit);
                }
@@ -221,6 +225,7 @@ struct FtsParams {
    block_size: usize,
    memory_limit: Option<u64>,
    num_workers: Option<usize>,
+    document_granularity: String,
 }

 #[derive(FromPyObject)]
@@ -481,6 +486,7 @@ mod tests {
    block_size = 128
    memory_limit = 2048
    num_workers = 7
+    document_granularity = 'row'

 config = FTS()",
                None,
@@ -1,6 +1,7 @@
 // SPDX-License-Identifier: Apache-2.0
 // SPDX-FileCopyrightText: Copyright The LanceDB Authors

+use std::collections::HashMap;
 use std::sync::Arc;
 use std::time::Duration;

@@ -16,8 +17,8 @@ use arrow::pyarrow::FromPyArrow;
 use arrow::pyarrow::IntoPyArrow;
 use arrow::pyarrow::ToPyArrow;
 use lancedb::index::scalar::{
-    BooleanQuery, BoostQuery, FtsQuery, FullTextSearchQuery, MatchQuery, MultiMatchQuery, Occur,
-    Operator, PhraseQuery,
+    BooleanQuery, BoostQuery, DocumentGranularity, FtsQuery, FullTextSearchQuery, MatchQuery,
+    MultiMatchQuery, Occur, Operator, PhraseQuery,
 };
 use lancedb::query::AnalyzePlanDistributedMetrics;
 use lancedb::query::QueryBase;
@@ -76,8 +77,16 @@ impl<'a, 'py> FromPyObject<'a, 'py> for PyLanceDB<FtsQuery> {
                let max_expansions = ob.getattr("max_expansions")?.extract()?;
                let operator = ob.getattr("operator")?.extract::<String>()?;
                let prefix_length = ob.getattr("prefix_length")?.extract()?;
+                let document_granularity = ob
+                    .getattr("document_granularity")?
+                    .extract::<Option<String>>()?
+                    .map(|value| {
+                        DocumentGranularity::try_from(value.as_str())
+                            .map_err(|err| PyValueError::new_err(err.to_string()))
+                    })
+                    .transpose()?;

-                Ok(Self(
+                let mut query =
                    MatchQuery::new(query)
                        .with_column(Some(column))
                        .with_boost(boost)
@@ -86,21 +95,32 @@ impl<'a, 'py> FromPyObject<'a, 'py> for PyLanceDB<FtsQuery> {
                        .with_operator(Operator::try_from(operator.as_str()).map_err(|e| {
                            PyValueError::new_err(format!("Invalid operator: {}", e))
                        })?)
-                        .with_prefix_length(prefix_length)
-                        .into(),
-                ))
+                        .with_prefix_length(prefix_length);
+                if let Some(document_granularity) = document_granularity {
+                    query = query.with_document_granularity(document_granularity);
+                }
+                Ok(Self(query.into()))
            }
            "PhraseQuery" => {
                let query = ob.getattr("query")?.extract()?;
                let column = ob.getattr("column")?.extract()?;
                let slop = ob.getattr("slop")?.extract()?;
+                let document_granularity = ob
+                    .getattr("document_granularity")?
+                    .extract::<Option<String>>()?
+                    .map(|value| {
+                        DocumentGranularity::try_from(value.as_str())
+                            .map_err(|err| PyValueError::new_err(err.to_string()))
+                    })
+                    .transpose()?;

-                Ok(Self(
-                    PhraseQuery::new(query)
-                        .with_column(Some(column))
-                        .with_slop(slop)
-                        .into(),
-                ))
+                let mut query = PhraseQuery::new(query)
+                    .with_column(Some(column))
+                    .with_slop(slop);
+                if let Some(document_granularity) = document_granularity {
+                    query = query.with_document_granularity(document_granularity);
+                }
+                Ok(Self(query.into()))
            }
            "BoostQuery" => {
                let positive: Self = ob.getattr("positive")?.extract()?;
@@ -167,6 +187,13 @@ impl<'py> IntoPyObject<'py> for PyLanceDB<FtsQuery> {
                kwargs.set_item("max_expansions", query.max_expansions)?;
                kwargs.set_item::<_, &str>("operator", query.operator.into())?;
                kwargs.set_item("prefix_length", query.prefix_length)?;
+                if let Some(document_granularity) = query.document_granularity {
+                    let value = match document_granularity {
+                        DocumentGranularity::Row => "row",
+                        DocumentGranularity::ListElement => "list_element",
+                    };
+                    kwargs.set_item("document_granularity", value)?;
+                }
                namespace
                    .getattr(intern!(py, "MatchQuery"))?
                    .call((query.terms, query.column.unwrap()), Some(&kwargs))
@@ -174,6 +201,13 @@ impl<'py> IntoPyObject<'py> for PyLanceDB<FtsQuery> {
            FtsQuery::Phrase(query) => {
                let kwargs = PyDict::new(py);
                kwargs.set_item("slop", query.slop)?;
+                if let Some(document_granularity) = query.document_granularity {
+                    let value = match document_granularity {
+                        DocumentGranularity::Row => "row",
+                        DocumentGranularity::ListElement => "list_element",
+                    };
+                    kwargs.set_item("document_granularity", value)?;
+                }
                namespace
                    .getattr(intern!(py, "PhraseQuery"))?
                    .call((query.terms, query.column.unwrap()), Some(&kwargs))
@@ -292,6 +326,7 @@ pub struct PyQueryRequest {
    pub filter: Option<PyQueryFilter>,
    pub full_text_search: Option<PyLanceDB<FtsQuery>>,
    pub select: PySelect,
+    pub select_source_columns: Option<HashMap<String, String>>,
    pub fast_search: Option<bool>,
    pub with_row_id: Option<bool>,
    pub use_lsm: Option<bool>,
@@ -322,6 +357,7 @@ impl From<AnyQuery> for PyQueryRequest {
                full_text_search: query_request
                    .full_text_search
                    .map(|fts| PyLanceDB(fts.query)),
+                select_source_columns: PySelect::source_columns(&query_request.select),
                select: PySelect(query_request.select),
                fast_search: Some(query_request.fast_search),
                with_row_id: Some(query_request.with_row_id),
@@ -347,6 +383,7 @@ impl From<AnyQuery> for PyQueryRequest {
                offset: vector_query.base.offset,
                filter: vector_query.base.filter.map(PyQueryFilter),
                full_text_search: None,
+                select_source_columns: PySelect::source_columns(&vector_query.base.select),
                select: PySelect(vector_query.base.select),
                fast_search: Some(vector_query.base.fast_search),
                with_row_id: Some(vector_query.base.with_row_id),
@@ -379,6 +416,25 @@ impl From<AnyQuery> for PyQueryRequest {
 #[derive(Clone)]
 pub struct PySelect(Select);

+impl PySelect {
+    fn source_columns(select: &Select) -> Option<HashMap<String, String>> {
+        match select {
+            Select::Expr(pairs) => Some(
+                pairs
+                    .iter()
+                    .filter_map(|(output, expr)| match expr {
+                        lancedb::expr::DfExpr::Column(column) if column.relation.is_none() => {
+                            Some((output.clone(), column.name.clone()))
+                        }
+                        _ => None,
+                    })
+                    .collect(),
+            ),
+            _ => None,
+        }
+    }
+}
+
 impl<'py> IntoPyObject<'py> for PySelect {
    type Target = PyAny;
    type Output = Bound<'py, Self::Target>;
@@ -780,15 +780,19 @@ impl Table {
        })
    }

-    #[pyo3(signature = (data, mode, progress=None, write_parallelism=None))]
+    #[pyo3(signature = (data, mode, progress=None, write_parallelism=None, allow_external_blob_outside_bases=false))]
    pub fn add<'a>(
        self_: PyRef<'a, Self>,
        data: PyScannable,
        mode: String,
        progress: Option<Py<PyAny>>,
        write_parallelism: Option<usize>,
+        allow_external_blob_outside_bases: bool,
    ) -> PyResult<Bound<'a, PyAny>> {
-        let mut op = self_.inner_ref()?.add(data);
+        let mut op = self_
+            .inner_ref()?
+            .add(data)
+            .allow_external_blob_outside_bases(allow_external_blob_outside_bases);
        if mode == "append" {
            op = op.mode(AddDataMode::Append);
        } else if mode == "overwrite" {
@@ -1,6 +1,6 @@
 [package]
 name = "lancedb"
-version = "0.38.0-beta.7"
+version = "0.38.0-beta.11"
 edition.workspace = true
 description = "LanceDB: A serverless, low-latency vector database for AI applications"
 license.workspace = true
@@ -1476,7 +1476,7 @@ mod tests {
    use crate::table::{AnyQuery, WriteOptions};
    use arrow_array::{Int32Array, RecordBatch, StringArray};
    use arrow_schema::{DataType, Field, Schema, SchemaRef};
-    use futures::{TryStreamExt, stream::once};
+    use futures::{TryStreamExt, future::try_join_all, stream::once};
    use std::path::PathBuf;
    use std::sync::Arc;
    use std::time::Duration;
@@ -1614,6 +1614,59 @@ mod tests {
        );
    }

+    #[tokio::test]
+    async fn test_concurrent_open_table_reuses_connection_object_store() {
+        let tempdir = tempdir().unwrap();
+        let uri = tempdir.path().to_str().unwrap();
+        let session = Arc::new(lance::session::Session::default());
+        let request = ConnectRequest {
+            uri: uri.to_string(),
+            #[cfg(feature = "remote")]
+            client_config: Default::default(),
+            options: Default::default(),
+            namespace_client_properties: Default::default(),
+            manifest_enabled: false,
+            read_consistency_interval: None,
+            session: Some(session.clone()),
+        };
+        let db = ListingDatabase::connect_with_options(&request)
+            .await
+            .unwrap();
+        let schema = Arc::new(Schema::new(vec![Field::new("id", DataType::Int32, false)]));
+        db.create_table(CreateTableRequest {
+            name: "test".to_string(),
+            namespace_path: vec![],
+            data: Box::new(RecordBatch::new_empty(schema)) as Box<dyn Scannable>,
+            mode: CreateTableMode::Create,
+            write_options: Default::default(),
+            location: None,
+            namespace_client: None,
+        })
+        .await
+        .unwrap();
+
+        let before = session.store_registry().stats();
+        let opened_tables = try_join_all((0..32).map(|_| {
+            db.open_table(OpenTableRequest {
+                name: "test".to_string(),
+                namespace_path: vec![],
+                index_cache_size: None,
+                lance_read_params: None,
+                location: None,
+                namespace_client: None,
+                managed_versioning: None,
+            })
+        }))
+        .await
+        .unwrap();
+        let after = session.store_registry().stats();
+
+        assert_eq!(opened_tables.len(), 32);
+        assert_eq!(after.misses, before.misses);
+        assert_eq!(after.active_stores, before.active_stores);
+        assert!(after.hits >= before.hits + 32);
+    }
+
    #[tokio::test]
    async fn test_listing_database_root_ops_do_not_create_manifest() {
        let tempdir = tempdir().unwrap();
@@ -19,6 +19,7 @@

 mod sql;

+pub(crate) use sql::canonicalize_sql_predicate;
 pub use sql::expr_to_sql_string;

 use std::sync::Arc;
@@ -156,7 +157,7 @@ mod tests {
        use datafusion_common::ScalarValue;
        let expr = col("data").eq(lit(ScalarValue::Binary(Some(vec![0xca, 0xfe]))));
        let sql = expr_to_sql_string(&expr).unwrap();
-        assert_eq!(sql, "(data = X'CAFE')");
+        assert_eq!(sql, "(`data` = X'CAFE')");
    }

    #[test]
@@ -166,7 +167,7 @@ mod tests {
        let int_expr = col("id").gt(lit(5i64));
        let combined = bin_expr.and(int_expr);
        let sql = expr_to_sql_string(&combined).unwrap();
-        assert_eq!(sql, "((data = X'01') AND (id > 5))");
+        assert_eq!(sql, "((`data` = X'01') AND (id > 5))");
    }

    #[test]
@@ -184,7 +185,7 @@ mod tests {
        // serialized correctly (regression test for placeholder rewrite path).
        let expr = contains(col("data"), lit(ScalarValue::Binary(Some(vec![0xff]))));
        let sql = expr_to_sql_string(&expr).unwrap();
-        assert_eq!(sql, "contains(data, X'FF')");
+        assert_eq!(sql, "contains(`data`, X'FF')");
    }

    #[test]
@@ -195,7 +196,7 @@ mod tests {
            .eq(lit(ScalarValue::Binary(Some(vec![0xab, 0xcd]))))
            .not();
        let sql = expr_to_sql_string(&expr).unwrap();
-        assert_eq!(sql, "NOT (data = X'ABCD')");
+        assert_eq!(sql, "NOT (`data` = X'ABCD')");
    }

    #[test]
@@ -205,6 +206,122 @@ mod tests {
        assert!(sql.contains("IN"), "expected IN in: {}", sql);
    }

+    #[test]
+    fn test_empty_is_in() {
+        let expr = is_in(col("id"), vec![]);
+        assert_eq!(expr_to_sql_string(&expr).unwrap(), "false");
+    }
+
+    #[test]
+    fn test_empty_is_in_discards_binary_children() {
+        use datafusion_common::ScalarValue;
+
+        let expr = is_in(
+            col("payload").eq(lit(ScalarValue::Binary(Some(vec![0x01])))),
+            vec![],
+        );
+        assert_eq!(expr_to_sql_string(&expr).unwrap(), "false");
+    }
+
+    #[test]
+    fn test_keyword_identifier() {
+        let expr = col("null").eq(lit(1i64));
+        assert_eq!(expr_to_sql_string(&expr).unwrap(), "(`null` = 1)");
+    }
+
+    #[test]
+    fn test_decimal_literal_preserves_type() {
+        use datafusion_common::ScalarValue;
+
+        let expr = col("val").lt(lit(ScalarValue::Decimal128(
+            Some(1_234_567_890_123_456_790),
+            19,
+            18,
+        )));
+        let sql = expr_to_sql_string(&expr).unwrap();
+        assert_eq!(
+            sql,
+            "(val < arrow_cast('1.234567890123456790', 'Decimal128(19, 18)'))"
+        );
+    }
+
+    #[test]
+    fn test_non_finite_float_literal_preserves_type() {
+        let expr = col("x").lt(lit(f64::INFINITY));
+        assert_eq!(
+            expr_to_sql_string(&expr).unwrap(),
+            "(x < arrow_cast('inf', 'Float64'))"
+        );
+    }
+
+    #[test]
+    fn test_cast_uses_arrow_type_name() {
+        let string = expr_cast(col("x"), DataType::Utf8);
+        assert_eq!(
+            expr_to_sql_string(&string).unwrap(),
+            "arrow_cast(x, 'Utf8')"
+        );
+
+        let int32 = expr_cast(col("x"), DataType::Int32);
+        assert_eq!(
+            expr_to_sql_string(&int32).unwrap(),
+            "arrow_cast(x, 'Int32')"
+        );
+
+        let expr = expr_cast(col("x"), DataType::Float16).lt(lit(2.0));
+        assert_eq!(
+            expr_to_sql_string(&expr).unwrap(),
+            "(arrow_cast(x, 'Float16') < 2.0)"
+        );
+
+        let decimal = expr_cast(lit("2.00"), DataType::Decimal256(40, 2));
+        assert_eq!(
+            expr_to_sql_string(&decimal).unwrap(),
+            "arrow_cast('2.00', 'Decimal256(40, 2)')"
+        );
+    }
+
+    #[test]
+    fn test_binary_placeholder_does_not_rewrite_user_string() {
+        use datafusion_common::ScalarValue;
+
+        let marker = "__lancedb_binary_placeholder_0__";
+        let expr = col("payload")
+            .eq(lit(ScalarValue::Binary(Some(vec![0x01]))))
+            .or(col("text").eq(lit(marker)));
+        assert_eq!(
+            expr_to_sql_string(&expr).unwrap(),
+            "((payload = X'01') OR (`text` = '__lancedb_binary_placeholder_0__'))"
+        );
+    }
+
+    #[test]
+    fn test_binary_binding_skips_quoted_identifiers() {
+        use datafusion_common::ScalarValue;
+
+        let expr = col("payload")
+            .eq(lit(ScalarValue::Binary(Some(vec![0x01]))))
+            .and(col("odd'name").eq(lit(1i64)))
+            .and(col("odd`'name").eq(lit(2i64)));
+        assert_eq!(
+            expr_to_sql_string(&expr).unwrap(),
+            "(((payload = X'01') AND (`odd'name` = 1)) AND (`odd``'name` = 2))"
+        );
+    }
+
+    #[test]
+    fn test_binary_placeholder_collision_search_is_linear() {
+        use datafusion_common::ScalarValue;
+
+        let collision_shaped = format!("__lancedb_binary_placeholder_0__{}", "_".repeat(64_000));
+        let expr = col("payload")
+            .eq(lit(ScalarValue::Binary(Some(vec![0x01]))))
+            .and(col("text").eq(lit(collision_shaped.clone())));
+        let sql = expr_to_sql_string(&expr).unwrap();
+        assert!(sql.contains("X'01'"));
+        assert!(sql.contains(&format!("'{collision_shaped}'")));
+    }
+
    #[test]
    fn test_multiple_binary_literals() {
        use datafusion_common::ScalarValue;
@@ -1,10 +1,27 @@
 // SPDX-License-Identifier: Apache-2.0
 // SPDX-FileCopyrightText: Copyright The LanceDB Authors

+use std::{
+    any::TypeId,
+    collections::{HashMap, HashSet},
+};
+
+use arrow_array::types::{
+    Decimal32Type, Decimal64Type, Decimal128Type, Decimal256Type, DecimalType,
+};
+use arrow_schema::DataType;
 use datafusion_common::ScalarValue;
 use datafusion_common::tree_node::{Transformed, TreeNode, TreeNodeRecursion};
 use datafusion_expr::Expr;
-use datafusion_sql::unparser::{self, dialect::Dialect};
+use datafusion_functions::core::expr_fn::{
+    arrow_cast as datafusion_arrow_cast, arrow_try_cast as datafusion_arrow_try_cast,
+};
+use datafusion_sql::sqlparser::{
+    dialect::{Dialect as SqlParserDialect, GenericDialect},
+    keywords::ALL_KEYWORDS,
+    tokenizer::{Token, Tokenizer},
+};
+use datafusion_sql::unparser::{self, dialect::Dialect as UnparserDialect};

 /// Unparser dialect that matches the quoting style expected by the Lance SQL
 /// parser.  Lance uses backtick (`` ` ``) as the only delimited-identifier
@@ -19,17 +36,74 @@ use datafusion_sql::unparser::{self, dialect::Dialect};
 ///   lower-case by the SQL parser, which would break case-sensitive schemas).
 struct LanceSqlDialect;

-impl Dialect for LanceSqlDialect {
+impl UnparserDialect for LanceSqlDialect {
    fn identifier_quote_style(&self, identifier: &str) -> Option<char> {
-        let needs_quote = identifier.chars().any(|c| c.is_ascii_uppercase())
-            || !identifier
-                .chars()
-                .enumerate()
-                .all(|(i, c)| c == '_' || c.is_ascii_alphabetic() || (i > 0 && c.is_ascii_digit()));
+        let identifier_upper = identifier.to_ascii_uppercase();
+        let needs_quote =
+            (identifier_upper != "ID" && ALL_KEYWORDS.contains(&identifier_upper.as_str()))
+                || identifier.chars().any(|c| c.is_ascii_uppercase())
+                || !identifier.chars().enumerate().all(|(i, c)| {
+                    c == '_' || c.is_ascii_alphabetic() || (i > 0 && c.is_ascii_digit())
+                });
        if needs_quote { Some('`') } else { None }
    }
 }

+/// Lance's tokenizer dialect with SQL-standard double-quoted identifiers added.
+///
+/// Keep this deliberately small: Lance's parser wraps `GenericDialect` and
+/// delegates only identifier recognition, leaving every other dialect option at
+/// its default. In particular, `/*! ... */` remains an ordinary block comment.
+#[derive(Debug, Default)]
+struct PredicateDialect(GenericDialect);
+
+impl SqlParserDialect for PredicateDialect {
+    fn dialect(&self) -> TypeId {
+        self.0.dialect()
+    }
+
+    fn is_identifier_start(&self, ch: char) -> bool {
+        self.0.is_identifier_start(ch)
+    }
+
+    fn is_identifier_part(&self, ch: char) -> bool {
+        self.0.is_identifier_part(ch)
+    }
+
+    fn is_delimited_identifier_start(&self, ch: char) -> bool {
+        ch == '"' || ch == '`'
+    }
+}
+
+/// Canonicalize a raw SQL predicate for Lance's parser.
+///
+/// Lance wraps [`GenericDialect`] for identifier recognition while retaining the
+/// default dialect behavior for every other lexical option. [`PredicateDialect`]
+/// mirrors that contract and additionally recognizes `"` as an identifier
+/// delimiter, allowing this function to rewrite only those identifier tokens.
+pub fn canonicalize_sql_predicate(predicate: &str) -> crate::Result<String> {
+    let dialect = PredicateDialect::default();
+    let tokens = Tokenizer::new(&dialect, predicate)
+        .with_unescape(false)
+        .tokenize()
+        .map_err(|err| crate::Error::InvalidInput {
+            message: format!("invalid SQL predicate: {err}"),
+        })?;
+
+    Ok(tokens
+        .into_iter()
+        .map(|token| match token {
+            Token::Word(word) if word.quote_style == Some('"') => {
+                // with_unescape(false) retains doubled double quotes. Decode
+                // those before escaping any backticks for Lance's delimiter.
+                let identifier = word.value.replace("\"\"", "\"").replace('`', "``");
+                format!("`{identifier}`")
+            }
+            other => other.to_string(),
+        })
+        .collect())
+}
+
 /// Prefix for placeholder strings inserted in place of binary literals.  Chosen
 /// to be extremely unlikely to occur in user data.
 const BINARY_PLACEHOLDER_PREFIX: &str = "__lancedb_binary_placeholder_";
@@ -39,24 +113,128 @@ fn bytes_to_hex_sql(bytes: &[u8]) -> String {
    format!("X'{hex}'")
 }

-/// Returns true if *expr* contains a `Binary` or `LargeBinary` scalar literal
-/// anywhere in its subtree.  DataFusion's SQL unparser cannot serialize those
-/// variants, so we route such expressions through a placeholder-substitution
-/// path that emits SQL `X'...'` byte-string literals.
-fn has_binary_literal(expr: &Expr) -> bool {
-    let mut found = false;
+fn string_literals(expr: &Expr) -> HashSet<String> {
+    let mut literals = HashSet::new();
    let _ = expr.apply(&mut |e: &Expr| {
-        if matches!(
-            e,
-            Expr::Literal(ScalarValue::Binary(_) | ScalarValue::LargeBinary(_), _)
-        ) {
-            found = true;
-            Ok(TreeNodeRecursion::Stop)
-        } else {
-            Ok(TreeNodeRecursion::Continue)
+        if let Expr::Literal(
+            ScalarValue::Utf8(Some(value))
+            | ScalarValue::LargeUtf8(Some(value))
+            | ScalarValue::Utf8View(Some(value)),
+            _,
+        ) = e
+        {
+            literals.insert(value.clone());
        }
+        Ok(TreeNodeRecursion::Continue)
    });
-    found
+    literals
+}
+
+fn typed_string_literal(value: String, data_type: DataType) -> Expr {
+    datafusion_arrow_cast(
+        Expr::Literal(ScalarValue::Utf8(Some(value)), None),
+        Expr::Literal(ScalarValue::Utf8(Some(data_type.to_string())), None),
+    )
+}
+
+fn next_binary_placeholder(user_strings: &HashSet<String>, next_id: &mut usize) -> String {
+    loop {
+        let placeholder = format!("{BINARY_PLACEHOLDER_PREFIX}{}__", *next_id);
+        *next_id += 1;
+        if !user_strings.contains(&placeholder) {
+            return placeholder;
+        }
+    }
+}
+
+fn bind_binary_literals(
+    sql: &str,
+    mut bindings: HashMap<String, Vec<u8>>,
+) -> crate::Result<String> {
+    let bytes = sql.as_bytes();
+    let mut output = Vec::with_capacity(bytes.len());
+    let mut index = 0;
+
+    // Walk SQL string tokens once. Placeholders are plain, unescaped string
+    // literals, so this remains linear even when user strings are large or
+    // deliberately resemble the placeholder prefix.
+    while index < bytes.len() {
+        if bytes[index] == b'`' {
+            let identifier_start = index;
+            index += 1;
+            let mut identifier_end = None;
+            while index < bytes.len() {
+                if bytes[index] == b'`' {
+                    if index + 1 < bytes.len() && bytes[index + 1] == b'`' {
+                        index += 2;
+                    } else {
+                        index += 1;
+                        identifier_end = Some(index);
+                        break;
+                    }
+                } else {
+                    index += 1;
+                }
+            }
+
+            let Some(identifier_end) = identifier_end else {
+                return Err(crate::Error::InvalidInput {
+                    message: "unterminated identifier while binding binary literal".to_string(),
+                });
+            };
+            output.extend_from_slice(&bytes[identifier_start..identifier_end]);
+            continue;
+        }
+
+        if bytes[index] != b'\'' {
+            output.push(bytes[index]);
+            index += 1;
+            continue;
+        }
+
+        let literal_start = index;
+        index += 1;
+        let content_start = index;
+        let mut escaped = false;
+        let mut content_end = None;
+        while index < bytes.len() {
+            if bytes[index] == b'\'' {
+                if index + 1 < bytes.len() && bytes[index + 1] == b'\'' {
+                    escaped = true;
+                    index += 2;
+                } else {
+                    content_end = Some(index);
+                    index += 1;
+                    break;
+                }
+            } else {
+                index += 1;
+            }
+        }
+
+        let Some(content_end) = content_end else {
+            return Err(crate::Error::InvalidInput {
+                message: "unterminated string while binding binary literal".to_string(),
+            });
+        };
+
+        let placeholder = &sql[content_start..content_end];
+        if !escaped && let Some(value) = bindings.remove(placeholder) {
+            output.extend_from_slice(bytes_to_hex_sql(&value).as_bytes());
+        } else {
+            output.extend_from_slice(&bytes[literal_start..index]);
+        }
+    }
+
+    if !bindings.is_empty() {
+        return Err(crate::Error::InvalidInput {
+            message: "failed to bind binary literal while serializing expression".to_string(),
+        });
+    }
+
+    String::from_utf8(output).map_err(|e| crate::Error::InvalidInput {
+        message: format!("failed to bind binary literal: {e}"),
+    })
 }

 fn run_unparser(expr: &Expr) -> crate::Result<String> {
@@ -69,25 +247,37 @@ fn run_unparser(expr: &Expr) -> crate::Result<String> {
 }

 pub fn expr_to_sql_string(expr: &Expr) -> crate::Result<String> {
-    // Fast path: no binary literals — DataFusion's unparser handles everything.
-    if !has_binary_literal(expr) {
-        return run_unparser(expr);
-    }
-
-    // Slow path: DataFusion's unparser cannot serialize `Binary`/`LargeBinary`
-    // scalars, so we rewrite each one to a unique string-literal placeholder,
-    // let the unparser do the rest of the work, then substitute the SQL
-    // `X'...'` byte-string literal back in.  This keeps the operator/function
-    // serialization logic centralized in DataFusion and works for every
-    // expression node type the unparser supports.
-    let mut bindings: Vec<Vec<u8>> = Vec::new();
+    // DataFusion's unparser needs a few adaptations before its SQL can be
+    // reparsed by Lance without changing the typed expression's semantics:
+    //
+    // * decimal literals need an explicit cast to preserve precision and scale;
+    // * casts need exact Arrow type names rather than SQL type aliases;
+    // * an empty IN list is valid in DataFusion but invalid SQL;
+    // * binary literals are unsupported by the unparser and need placeholders.
+    // Eliminate empty membership expressions before visiting their children.
+    // Otherwise a discarded binary child could leave behind a stale binding.
    let rewritten = expr
        .clone()
+        .transform(|e: Expr| match e {
+            Expr::InList(in_list) if in_list.list.is_empty() => Ok(Transformed::yes(
+                Expr::Literal(ScalarValue::Boolean(Some(in_list.negated)), None),
+            )),
+            other => Ok(Transformed::no(other)),
+        })
+        .map_err(|e| crate::Error::InvalidInput {
+            message: format!("failed to rewrite expression: {e}"),
+        })?
+        .data;
+
+    let user_strings = string_literals(&rewritten);
+    let mut next_placeholder_id = 0;
+    let mut binary_bindings = HashMap::new();
+    let rewritten = rewritten
        .transform(|e: Expr| match e {
            Expr::Literal(ScalarValue::Binary(Some(bytes)), m)
            | Expr::Literal(ScalarValue::LargeBinary(Some(bytes)), m) => {
-                let placeholder = format!("{}{}__", BINARY_PLACEHOLDER_PREFIX, bindings.len());
-                bindings.push(bytes);
+                let placeholder = next_binary_placeholder(&user_strings, &mut next_placeholder_id);
+                binary_bindings.insert(placeholder.clone(), bytes);
                Ok(Transformed::yes(Expr::Literal(
                    ScalarValue::Utf8(Some(placeholder)),
                    m,
@@ -97,6 +287,57 @@ pub fn expr_to_sql_string(expr: &Expr) -> crate::Result<String> {
            | Expr::Literal(ScalarValue::LargeBinary(None), m) => {
                Ok(Transformed::yes(Expr::Literal(ScalarValue::Null, m)))
            }
+            Expr::Literal(ScalarValue::Decimal32(Some(value), precision, scale), _m) => {
+                let value = Decimal32Type::format_decimal(value, precision, scale);
+                Ok(Transformed::yes(typed_string_literal(
+                    value,
+                    DataType::Decimal32(precision, scale),
+                )))
+            }
+            Expr::Literal(ScalarValue::Decimal64(Some(value), precision, scale), _m) => {
+                let value = Decimal64Type::format_decimal(value, precision, scale);
+                Ok(Transformed::yes(typed_string_literal(
+                    value,
+                    DataType::Decimal64(precision, scale),
+                )))
+            }
+            Expr::Literal(ScalarValue::Decimal128(Some(value), precision, scale), _m) => {
+                let value = Decimal128Type::format_decimal(value, precision, scale);
+                Ok(Transformed::yes(typed_string_literal(
+                    value,
+                    DataType::Decimal128(precision, scale),
+                )))
+            }
+            Expr::Literal(ScalarValue::Decimal256(Some(value), precision, scale), _m) => {
+                let value = Decimal256Type::format_decimal(value, precision, scale);
+                Ok(Transformed::yes(typed_string_literal(
+                    value,
+                    DataType::Decimal256(precision, scale),
+                )))
+            }
+            Expr::Literal(ScalarValue::Float16(Some(value)), _m) if !value.is_finite() => Ok(
+                Transformed::yes(typed_string_literal(value.to_string(), DataType::Float16)),
+            ),
+            Expr::Literal(ScalarValue::Float32(Some(value)), _m) if !value.is_finite() => Ok(
+                Transformed::yes(typed_string_literal(value.to_string(), DataType::Float32)),
+            ),
+            Expr::Literal(ScalarValue::Float64(Some(value)), _m) if !value.is_finite() => Ok(
+                Transformed::yes(typed_string_literal(value.to_string(), DataType::Float64)),
+            ),
+            Expr::Cast(cast) => Ok(Transformed::yes(datafusion_arrow_cast(
+                *cast.expr,
+                Expr::Literal(
+                    ScalarValue::Utf8(Some(cast.field.data_type().to_string())),
+                    None,
+                ),
+            ))),
+            Expr::TryCast(cast) => Ok(Transformed::yes(datafusion_arrow_try_cast(
+                *cast.expr,
+                Expr::Literal(
+                    ScalarValue::Utf8(Some(cast.field.data_type().to_string())),
+                    None,
+                ),
+            ))),
            other => Ok(Transformed::no(other)),
        })
        .map_err(|e| crate::Error::InvalidInput {
@@ -104,12 +345,58 @@ pub fn expr_to_sql_string(expr: &Expr) -> crate::Result<String> {
        })?
        .data;

-    let mut sql = run_unparser(&rewritten)?;
-    for (i, bytes) in bindings.iter().enumerate() {
-        // The unparser quotes string literals with single quotes, so the
-        // placeholder appears as `'__lancedb_binary_placeholder_<i>__'`.
-        let quoted = format!("'{}{}__'", BINARY_PLACEHOLDER_PREFIX, i);
-        sql = sql.replace(&quoted, &bytes_to_hex_sql(bytes));
+    let sql = run_unparser(&rewritten)?;
+    if binary_bindings.is_empty() {
+        Ok(sql)
+    } else {
+        bind_binary_literals(&sql, binary_bindings)
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::canonicalize_sql_predicate;
+
+    #[test]
+    fn normalizes_double_quoted_identifiers() {
+        assert_eq!(
+            canonicalize_sql_predicate(r#""PartyAbbrev" = 'D'"#).unwrap(),
+            "`PartyAbbrev` = 'D'"
+        );
+        assert_eq!(
+            canonicalize_sql_predicate(r#""MetaData"."userId" = 5"#).unwrap(),
+            "`MetaData`.`userId` = 5"
+        );
+        assert_eq!(
+            canonicalize_sql_predicate(r#""a""b" = 1"#).unwrap(),
+            "`a\"b` = 1"
+        );
+    }
+
+    #[test]
+    fn preserves_quotes_inside_literals_and_backticks() {
+        let filter = r#"name = 'Alice "Ace"' AND `quoted"field` = 1"#;
+        assert_eq!(canonicalize_sql_predicate(filter).unwrap(), filter);
+    }
+
+    #[test]
+    fn preserves_literals_and_comments_using_lance_dialect_rules() {
+        let predicate = r#"path = '\' AND "PartyAbbrev" = 'D' -- unmatched " in comment"#;
+        assert_eq!(
+            canonicalize_sql_predicate(predicate).unwrap(),
+            r#"path = '\' AND `PartyAbbrev` = 'D' -- unmatched " in comment"#
+        );
+
+        let predicate = r#"id = 1 /* unmatched " in block comment */"#;
+        assert_eq!(canonicalize_sql_predicate(predicate).unwrap(), predicate);
+
+        let predicate = r#"id = 1 /*! OR "PartyAbbrev" = 'D' */"#;
+        assert_eq!(canonicalize_sql_predicate(predicate).unwrap(), predicate);
+    }
+
+    #[test]
+    fn rejects_unterminated_double_quoted_identifier() {
+        let error = canonicalize_sql_predicate(r#""PartyAbbrev = 'D'"#).unwrap_err();
+        assert!(matches!(error, crate::Error::InvalidInput { .. }));
    }
-    Ok(sql)
 }
@@ -5,7 +5,7 @@
 //! backend-neutral terminal result of a computed-column refresh.
 //!
 //! This module contains client/wire values only. Catalog persistence,
-//! environment bake, secret resolution, and execution are owned by Sophon.
+//! environment bake, and execution are owned by Sophon.

 use std::collections::BTreeMap;

@@ -186,6 +186,9 @@ pub struct PythonEnvironmentSpec {
    pub kind: String,
    #[serde(default, skip_serializing_if = "Vec::is_empty")]
    pub packages: Vec<String>,
+    /// Conda channels in priority order; conda environments only.
+    #[serde(default, skip_serializing_if = "Vec::is_empty")]
+    pub channels: Vec<String>,
    #[serde(default, skip_serializing_if = "Option::is_none")]
    pub path: Option<String>,
    #[serde(default, skip_serializing_if = "Vec::is_empty")]
@@ -195,9 +198,6 @@ pub struct PythonEnvironmentSpec {
 }

 /// Reproducible Python runtime definition understood by Sophon.
-///
-/// `env` contains non-secret values. Secret values have no client model;
-/// [`FunctionVersion::required_secrets`] contains names only.
 #[derive(Debug, Clone, PartialEq, Eq)]
 #[non_exhaustive]
 pub enum PythonRuntimeSpec {
@@ -239,7 +239,7 @@ impl PythonRuntimeSpec {
        }
    }

-    /// Non-secret environment variables, or `None` for an unknown kind.
+    /// Environment variables, or `None` for an unknown kind.
    pub fn env(&self) -> Option<&BTreeMap<String, String>> {
        match self {
            Self::Python { env, .. } => Some(env),
@@ -324,8 +324,6 @@ pub struct FunctionVersion {
    runtime: PythonRuntimeSpec,
    runtime_digest: String,
    environment_digest: String,
-    #[serde(default, skip_serializing_if = "Vec::is_empty")]
-    required_secrets: Vec<String>,
    created_at: String,
 }

@@ -358,11 +356,6 @@ impl FunctionVersion {
        &self.environment_digest
    }

-    /// Required secret names. Resolved values exist only inside Sophon.
-    pub fn required_secrets(&self) -> &[String] {
-        &self.required_secrets
-    }
-
    pub fn created_at(&self) -> &str {
        &self.created_at
    }
@@ -404,18 +397,12 @@ pub struct FunctionArtifactRequest {
 }

 /// Stable request envelope for remote immutable Function registration.
-///
-/// Secret values deliberately have no field in this model. The only secret
-/// material the client may send is the ordered set of names Sophon resolves
-/// inside the remote runtime.
 #[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
 pub struct FunctionRegistrationRequest {
    pub name: String,
    pub artifact: FunctionArtifactRequest,
    pub signature: FunctionSignature,
    pub runtime: PythonRuntimeSpec,
-    #[serde(default, skip_serializing_if = "Vec::is_empty")]
-    pub required_secrets: Vec<String>,
 }

 impl_json!(FunctionRegistrationRequest);
@@ -446,7 +433,6 @@ pub struct FunctionApplication {
    function: FunctionVersionRef,
    inputs: Vec<ApplicationInput>,
    output: FunctionOutput,
-    group_id: String,
    #[serde(default, skip_serializing_if = "BTreeMap::is_empty")]
    columns: BTreeMap<String, String>,
    #[serde(default, flatten, skip_serializing)]
@@ -468,10 +454,6 @@ impl FunctionApplication {
        &self.output
    }

-    pub fn group_id(&self) -> &str {
-        &self.group_id
-    }
-
    pub fn columns(&self) -> &BTreeMap<String, String> {
        &self.columns
    }
@@ -513,7 +495,7 @@ pub struct InputBinding {
    pub nullable: bool,
 }

-/// Ordered result-field to table-field mapping for a grouped binding.
+/// Ordered result-field to table-field mapping for a Function binding.
 ///
 /// Assignment state is not part of the Slice 1 client contract. During the
 /// NULL transition there is no public Lance cell-flag identifier to persist.
@@ -527,20 +509,18 @@ pub struct OutputMapping {
    pub nullable: bool,
 }

-/// Immutable grouped binding persisted by the Enterprise table service.
+/// Immutable Function binding persisted by the Enterprise table service.
 #[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
 pub struct FunctionBinding {
    binding_id: String,
-    revision: u64,
    function: FunctionVersionRef,
-    group_id: String,
    inputs: Vec<InputBinding>,
    outputs: Vec<OutputMapping>,
    /// Exact Arrow schema presented to the Function, encoded with the Lance
    /// Namespace Arrow JSON representation.
    #[serde(default, skip_serializing_if = "Option::is_none")]
    input_schema: Option<Value>,
-    /// Exact physical Arrow schema of the grouped table outputs.
+    /// Exact physical Arrow schema of the binding's table outputs.
    #[serde(default, skip_serializing_if = "Option::is_none")]
    output_schema: Option<Value>,
 }
@@ -550,18 +530,10 @@ impl FunctionBinding {
        &self.binding_id
    }

-    pub fn revision(&self) -> u64 {
-        self.revision
-    }
-
    pub fn function(&self) -> &FunctionVersionRef {
        &self.function
    }

-    pub fn group_id(&self) -> &str {
-        &self.group_id
-    }
-
    pub fn inputs(&self) -> &[InputBinding] {
        &self.inputs
    }
@@ -614,3 +586,26 @@ impl RefreshColumnResult {
 }

 impl_json!(RefreshColumnResult);
+
+#[cfg(test)]
+mod conda_environment_tests {
+    use super::PythonEnvironmentSpec;
+
+    #[test]
+    fn conda_channels_round_trip_and_pip_stays_bare() {
+        let conda: PythonEnvironmentSpec = serde_json::from_str(
+            r#"{"kind":"conda","packages":["numpy"],"channels":["conda-forge"]}"#,
+        )
+        .unwrap();
+        assert_eq!(conda.channels, ["conda-forge"]);
+        assert!(
+            serde_json::to_string(&conda)
+                .unwrap()
+                .contains(r#""channels":["conda-forge"]"#)
+        );
+
+        let pip: PythonEnvironmentSpec =
+            serde_json::from_str(r#"{"kind":"pip","packages":["numpy"]}"#).unwrap();
+        assert!(!serde_json::to_string(&pip).unwrap().contains("channels"));
+    }
+}
@@ -63,4 +63,5 @@ pub struct FmIndexBuilder {}
 pub use lance_index::scalar::FullTextSearchQuery;
 pub use lance_index::scalar::InvertedIndexParams as FtsIndexBuilder;
 pub use lance_index::scalar::InvertedIndexParams;
+pub use lance_index::scalar::inverted::DocumentGranularity;
 pub use lance_index::scalar::inverted::query::*;
@@ -10,7 +10,7 @@ use lance::io::WrappingObjectStore;
 use object_store::{
    CopyOptions, Error, GetOptions, GetResult, ListResult, MultipartUpload, ObjectMeta,
    ObjectStore, ObjectStoreExt, PutMultipartOptions, PutOptions, PutPayload, PutResult, Result,
-    UploadPart, path::Path,
+    UploadPart, list::PaginatedListStore, path::Path,
 };

 use async_trait::async_trait;
@@ -187,6 +187,14 @@ impl WrappingObjectStore for MirroringObjectStoreWrapper {
            secondary: self.secondary.clone(),
        })
    }
+
+    fn wrap_paginated(
+        &self,
+        _store_prefix: &str,
+        original: Arc<dyn PaginatedListStore>,
+    ) -> Option<Arc<dyn PaginatedListStore>> {
+        Some(original)
+    }
 }

 // windows pathing can't be simply concatenated
@@ -12,7 +12,7 @@ use lance::io::WrappingObjectStore;
 use object_store::{
    CopyOptions, GetOptions, GetResult, ListResult, MultipartUpload, ObjectMeta, ObjectStore,
    PutMultipartOptions, PutOptions, PutPayload, PutResult, RenameOptions, Result as OSResult,
-    UploadPart, path::Path,
+    UploadPart, list::PaginatedListStore, path::Path,
 };

 #[derive(Debug, Default)]
@@ -57,6 +57,14 @@ impl WrappingObjectStore for IoStatsHolder {
            stats: self.0.clone(),
        })
    }
+
+    fn wrap_paginated(
+        &self,
+        _store_prefix: &str,
+        original: Arc<dyn PaginatedListStore>,
+    ) -> Option<Arc<dyn PaginatedListStore>> {
+        Some(original)
+    }
 }

 impl IoTrackingStore {
@@ -47,6 +47,10 @@ impl TerminalResult {
        }
    }

+    pub(crate) fn value(&self) -> Option<&Value> {
+        self.value.as_ref()
+    }
+
    fn decode<T: DeserializeOwned>(self) -> Result<T> {
        let value = self.value.ok_or_else(|| match &self.request_id {
            Some(request_id) => Error::Http {
@@ -170,6 +170,15 @@ pub(crate) fn plan(
    filter: Option<&str>,
    limit: Option<u64>,
 ) -> Result<(MaterializedViewDefinition, Vec<ArrowField>, Lineage)> {
+    let filter = filter
+        .map(crate::expr::canonicalize_sql_predicate)
+        .transpose()
+        .map_err(|err| match err {
+            Error::InvalidInput { message } => Error::InvalidInput {
+                message: format!("invalid view filter: {message}"),
+            },
+            err => err,
+        })?;
    let projections: Vec<(String, String)> = if projections.is_empty() {
        source_schema
            .fields()
@@ -274,7 +283,7 @@ pub(crate) fn plan(
        declared.push(output);
    }

-    if let Some(filter) = filter {
+    if let Some(filter) = filter.as_deref() {
        let expr = planner
            .parse_filter(filter)
            .map_err(|e| Error::InvalidInput {
@@ -314,7 +323,7 @@ pub(crate) fn plan(
            .into_iter()
            .map(|(output, expression)| ViewProjection { output, expression })
            .collect(),
-        filter: filter.map(String::from),
+        filter,
        limit,
        inputs,
    };
@@ -46,8 +46,9 @@ use lance_table::format::Fragment;
 use serde::{Deserialize, Serialize};

 use super::{
-    INCARNATION_META_KEY, MaterializedViewDefinition, REFRESHED_AT_MS_META_KEY,
-    SOURCE_ROW_ID_COLUMN, SOURCE_VERSION_META_KEY,
+    DEFINITION_META_KEY, INCARNATION_META_KEY, MaterializedViewDefinition,
+    REFRESHED_AT_MS_META_KEY, SOURCE_ROW_ID_COLUMN, SOURCE_VERSION_META_KEY,
+    definition_to_metadata,
 };
 use crate::database::OpenTableRequest;
 use crate::table::{NativeTable, NativeTableExt, Table};
@@ -197,8 +198,28 @@ pub(crate) async fn execute_refresh(
            ),
        });
    }
+    let definition_changed =
+        definition.filter != replanned.filter || definition.inputs != replanned.inputs;
    let definition = &replanned;

+    // A watermark written for a legacy raw filter certifies the rows that
+    // filter produced, not the canonical predicate above. Rebuild instead of
+    // accepting or advancing it, and persist the migrated definition in the
+    // same metadata commit that certifies the replacement rows.
+    if definition_changed {
+        return rebuild(
+            view_native,
+            &view_ds,
+            &source_ds,
+            source_version,
+            source_ts,
+            definition,
+            true,
+            expected_incarnation,
+        )
+        .await;
+    }
+
    let metadata = &view_ds.schema().metadata;
    let watermark: Option<u64> = metadata
        .get(SOURCE_VERSION_META_KEY)
@@ -257,6 +278,7 @@ pub(crate) async fn execute_refresh(
                        source_version,
                        source_ts,
                        definition,
+                        false,
                        expected_incarnation,
                    )
                    .await
@@ -271,6 +293,7 @@ pub(crate) async fn execute_refresh(
                source_version,
                source_ts,
                definition,
+                false,
                expected_incarnation,
            )
            .await
@@ -683,6 +706,7 @@ async fn incremental(
            view_ds.clone(),
            source_version,
            source_ts,
+            None,
            expected_incarnation,
        )
        .await?;
@@ -704,6 +728,7 @@ async fn incremental(
            published,
            source_version,
            source_ts,
+            None,
            expected_incarnation,
        )
        .await?;
@@ -775,6 +800,7 @@ async fn incremental(
            published,
            source_version,
            source_ts,
+            None,
            expected_incarnation,
        )
        .await?;
@@ -824,12 +850,14 @@ async fn incremental(
        appended,
        source_version,
        source_ts,
+        None,
        expected_incarnation,
    )
    .await?;
    Ok(Some(result))
 }

+#[allow(clippy::too_many_arguments)]
 async fn rebuild(
    view_native: &NativeTable,
    view_ds: &Dataset,
@@ -837,6 +865,7 @@ async fn rebuild(
    source_version: u64,
    source_ts: u128,
    definition: &MaterializedViewDefinition,
+    persist_definition: bool,
    expected_incarnation: Option<&str>,
 ) -> Result<RefreshMaterializedViewResult> {
    let rows_written = Arc::new(AtomicU64::new(0));
@@ -867,6 +896,7 @@ async fn rebuild(
        replaced,
        source_version,
        source_ts,
+        persist_definition.then_some(definition),
        expected_incarnation,
    )
    .await?;
@@ -981,6 +1011,7 @@ async fn stamp_watermark(
    mut dataset: Dataset,
    source_version: u64,
    source_ts: u128,
+    definition: Option<&MaterializedViewDefinition>,
    expected_incarnation: Option<&str>,
 ) -> Result<u64> {
    ensure_incarnation(&dataset, expected_incarnation, dataset.uri()).await?;
@@ -993,27 +1024,32 @@ async fn stamp_watermark(
        .get(INCARNATION_META_KEY)
        .cloned()
        .unwrap_or_else(|| uuid::Uuid::new_v4().to_string());
-    dataset
-        .update_schema_metadata([
-            (INCARNATION_META_KEY.to_string(), Some(incarnation)),
-            (
-                SOURCE_VERSION_META_KEY.to_string(),
-                Some(source_version.to_string()),
-            ),
-            (
-                SOURCE_VERSION_TS_META_KEY.to_string(),
-                Some(source_ts.to_string()),
-            ),
-            (
-                REFRESHED_AT_MS_META_KEY.to_string(),
-                Some(now_ms().to_string()),
-            ),
-            (
-                VIEW_VERSION_META_KEY.to_string(),
-                Some(predicted.to_string()),
-            ),
-        ])
-        .await?;
+    let mut metadata = vec![(INCARNATION_META_KEY.to_string(), Some(incarnation))];
+    if let Some(definition) = definition {
+        metadata.push((
+            DEFINITION_META_KEY.to_string(),
+            Some(definition_to_metadata(definition)?),
+        ));
+    }
+    metadata.extend([
+        (
+            SOURCE_VERSION_META_KEY.to_string(),
+            Some(source_version.to_string()),
+        ),
+        (
+            SOURCE_VERSION_TS_META_KEY.to_string(),
+            Some(source_ts.to_string()),
+        ),
+        (
+            REFRESHED_AT_MS_META_KEY.to_string(),
+            Some(now_ms().to_string()),
+        ),
+        (
+            VIEW_VERSION_META_KEY.to_string(),
+            Some(predicted.to_string()),
+        ),
+    ]);
+    dataset.update_schema_metadata(metadata).await?;
    let actual = dataset.version().version;
    if actual != predicted {
        return Err(Error::Runtime {
@@ -1585,6 +1621,106 @@ mod tests {
        assert_eq!(read(view.table(), "x").await, vec![20, 40]);
    }

+    #[tokio::test]
+    async fn test_mixed_case_filter_is_canonicalized_for_lineage_and_refresh() {
+        let conn = connect("memory://").execute().await.unwrap();
+        let batch = record_batch!(
+            ("id", Int32, [1, 2, 3]),
+            ("PartyAbbrev", Utf8, ["D", "R", "D"])
+        )
+        .unwrap();
+        conn.create_table("src", batch)
+            .write_options(crate::materialized_view::tests::stable_row_ids())
+            .execute()
+            .await
+            .unwrap();
+        conn.create_materialized_view("democrats", "src")
+            .select([("id", "id")])
+            .only_if(r#""PartyAbbrev" = 'D'"#)
+            .execute()
+            .await
+            .unwrap();
+
+        // Reopen from schema metadata so these assertions cover the stored
+        // predicate and lineage, not only the declaration-time handle.
+        let view = conn.open_materialized_view("democrats").await.unwrap();
+        assert_eq!(
+            view.definition().filter.as_deref(),
+            Some("`PartyAbbrev` = 'D'")
+        );
+        assert_eq!(view.definition().inputs, ["PartyAbbrev", "id"]);
+
+        let result = view.refresh().execute().await.unwrap();
+        assert_eq!(result.rows_written, 2);
+        assert_eq!(read(view.table(), "id").await, vec![1, 3]);
+    }
+
+    #[tokio::test]
+    async fn test_legacy_raw_filter_rebuilds_and_persists_canonical_definition() {
+        let conn = connect("memory://").execute().await.unwrap();
+        let batch = record_batch!(
+            ("id", Int32, [1, 2, 3]),
+            ("PartyAbbrev", Utf8, ["D", "R", "D"])
+        )
+        .unwrap();
+        conn.create_table("legacy_src", batch)
+            .write_options(crate::materialized_view::tests::stable_row_ids())
+            .execute()
+            .await
+            .unwrap();
+        let view = conn
+            .create_materialized_view("legacy_view", "legacy_src")
+            .select([("id", "id")])
+            .only_if(r#""PartyAbbrev" = 'X'"#)
+            .execute()
+            .await
+            .unwrap();
+        assert_eq!(view.refresh().execute().await.unwrap().rows_written, 0);
+
+        // Model a definition and up-to-date watermark written before filter
+        // canonicalization was applied to materialized views.
+        let mut legacy = view.definition().clone();
+        legacy.filter = Some(r#""PartyAbbrev" = 'D'"#.into());
+        legacy.inputs = vec!["id".into()];
+        let native = view.table().as_native().unwrap();
+        let mut dataset = native.dataset.get().await.unwrap().as_ref().clone();
+        let predicted = dataset.version().version + 1;
+        dataset
+            .update_schema_metadata([
+                (
+                    DEFINITION_META_KEY.to_string(),
+                    Some(definition_to_metadata(&legacy).unwrap()),
+                ),
+                (
+                    VIEW_VERSION_META_KEY.to_string(),
+                    Some(predicted.to_string()),
+                ),
+            ])
+            .await
+            .unwrap();
+        native.dataset.update(dataset);
+
+        let reopened = conn.open_materialized_view("legacy_view").await.unwrap();
+        let result = reopened.refresh().execute().await.unwrap();
+        assert_eq!(result.mode, RefreshMode::Rebuild);
+        assert_eq!(result.rows_written, 2);
+        assert_eq!(read(reopened.table(), "id").await, vec![1, 3]);
+
+        // A fresh handle proves the migration was stored alongside the new
+        // watermark and therefore happens only once.
+        let migrated = conn.open_materialized_view("legacy_view").await.unwrap();
+        assert_eq!(
+            migrated.definition().filter.as_deref(),
+            Some("`PartyAbbrev` = 'D'")
+        );
+        assert_eq!(migrated.definition().inputs, ["PartyAbbrev", "id"]);
+        assert_eq!(
+            migrated.refresh().execute().await.unwrap().mode,
+            RefreshMode::NoOp
+        );
+        assert_eq!(read(migrated.table(), "id").await, vec![1, 3]);
+    }
+
    #[tokio::test]
    async fn test_append_refreshes_incrementally() {
        let (_conn, source, view) = refreshed_doubled(vec![1, 2]).await;
@@ -2767,7 +2903,7 @@ mod tests {
        let stale = view_native.dataset.get().await.unwrap().as_ref().clone();
        view.table().delete("x = 1").await.unwrap();

-        let err = stamp_watermark(view_native, stale, 99, 99, None).await;
+        let err = stamp_watermark(view_native, stale, 99, 99, None, None).await;
        assert!(err.is_err());

        let result = view.refresh().execute().await.unwrap();
@@ -399,6 +399,9 @@ pub trait QueryBase {
    /// x > 5 OR y = 'test'
    /// ```
    ///
+    /// Identifiers may be delimited with SQL-standard double quotes or
+    /// backticks. String literals must use single quotes.
+    ///
    /// Filtering performance can often be improved by creating a scalar index
    /// on the filter column(s).
    ///
@@ -913,6 +916,17 @@ impl QueryRequest {
    /// use different representations) the error is recorded and surfaced later
    /// by [`Self::check_filter`].
    pub(crate) fn add_filter(&mut self, new: QueryFilter) {
+        let new = match new {
+            QueryFilter::Sql(filter) => match crate::expr::canonicalize_sql_predicate(&filter) {
+                Ok(filter) => QueryFilter::Sql(filter),
+                Err(err) => {
+                    self.filter_error = Some(err.to_string());
+                    return;
+                }
+            },
+            other => other,
+        };
+
        self.filter = Some(match self.filter.take() {
            None => new,
            Some(existing) => match and_filters(existing, new) {
@@ -1174,12 +1188,12 @@ impl VectorQuery {

    /// Add another query vector to the search.
    ///
-    /// Multiple searches will be dispatched as part of the query.
-    /// This is a convenience method for adding multiple query vectors
-    /// to the search. It is not expected to be faster than issuing
-    /// multiple queries concurrently.
+    /// Multiple searches will be dispatched as a batch. Flat searches share
+    /// one table scan across the query vectors, avoiding the scan and memory
+    /// amplification of issuing the searches concurrently. Indexed searches
+    /// may still perform per-vector index work.
    ///
-    /// The output data will contain an additional columns `query_index` which
+    /// The output data will contain an additional column `query_index` which
    /// will contain the index of the query vector that was used to generate the
    /// result.
    pub fn add_query_vector(mut self, vector: impl IntoQueryVector) -> Result<Self> {
@@ -1646,10 +1660,14 @@ mod tests {
    use std::{collections::HashSet, sync::Arc};

    use super::*;
-    use arrow::{array::downcast_array, compute::concat_batches, datatypes::Int32Type};
+    use arrow::{
+        array::downcast_array,
+        compute::concat_batches,
+        datatypes::{Int32Type, UInt8Type},
+    };
    use arrow_array::{
-        FixedSizeListArray, Float32Array, Int32Array, RecordBatch, StringArray, cast::AsArray,
-        types::Float32Type,
+        FixedSizeListArray, Float32Array, Int32Array, RecordBatch, RecordBatchIterator,
+        StringArray, cast::AsArray, types::Float32Type,
    };
    use arrow_schema::{DataType, Field as ArrowField, Schema as ArrowSchema};
    use futures::{StreamExt, TryStreamExt};
@@ -1774,11 +1792,14 @@ mod tests {
            .postfilter();
        let result = query.execute().await;
        let mut stream = result.expect("should have result");
-        // should only have one batch
+        let mut num_rows = 0;
        while let Some(batch) = stream.next().await {
-            // post filter should have removed some rows
-            assert!(batch.expect("should be Ok").num_rows() < 10);
+            let batch = batch.expect("should be Ok");
+            let ids: &Int32Array = batch["id"].as_primitive();
+            assert!(ids.iter().all(|id| id.unwrap() % 2 == 0));
+            num_rows += batch.num_rows();
        }
+        assert!(num_rows <= 10);

        let query = table
            .query()
@@ -1875,6 +1896,157 @@ mod tests {
        query.execute().await.unwrap();
    }

+    #[tokio::test]
+    async fn test_double_quoted_predicates_across_table_operations() {
+        let tmp_dir = tempdir().unwrap();
+        let dataset_path = tmp_dir.path().join("test.lance");
+        let uri = dataset_path.to_str().unwrap();
+        let schema = Arc::new(ArrowSchema::new(vec![
+            ArrowField::new("id", DataType::Int32, false),
+            ArrowField::new("PartyAbbrev", DataType::Utf8, false),
+            ArrowField::new("path", DataType::Utf8, false),
+        ]));
+        let batch = RecordBatch::try_new(
+            schema.clone(),
+            vec![
+                Arc::new(Int32Array::from(vec![1, 2, 3, 4])),
+                Arc::new(StringArray::from(vec!["D", "R", "R", "D"])),
+                Arc::new(StringArray::from(vec!["\\", "\\", "x", "x"])),
+            ],
+        )
+        .unwrap();
+
+        let conn = connect(uri).execute().await.unwrap();
+        let table = conn.create_table("parties", batch).execute().await.unwrap();
+        let batches = table
+            .query()
+            .only_if(r#""PartyAbbrev" = 'D'"#)
+            .execute()
+            .await
+            .unwrap()
+            .try_collect::<Vec<_>>()
+            .await
+            .unwrap();
+
+        assert_eq!(batches.iter().map(RecordBatch::num_rows).sum::<usize>(), 2);
+        assert_eq!(
+            table
+                .count_rows(Some(r#""PartyAbbrev" = 'D'"#.to_string()))
+                .await
+                .unwrap(),
+            2
+        );
+
+        // Public BaseTable dispatch cannot bypass canonicalization.
+        let query = AnyQuery::Query(QueryRequest {
+            filter: Some(QueryFilter::Sql(r#""PartyAbbrev" = 'D'"#.to_string())),
+            ..Default::default()
+        });
+        let batches = table
+            .base_table()
+            .query(&query, Default::default())
+            .await
+            .unwrap()
+            .try_collect::<Vec<_>>()
+            .await
+            .unwrap();
+        assert_eq!(batches.iter().map(RecordBatch::num_rows).sum::<usize>(), 2);
+        assert_eq!(
+            table
+                .base_table()
+                .count_rows(Some(crate::table::Filter::Sql(
+                    r#""PartyAbbrev" = 'D'"#.to_string(),
+                )))
+                .await
+                .unwrap(),
+            2
+        );
+
+        for predicate in [
+            r#"id = 1 -- unmatched " in a valid SQL comment"#,
+            r#"id = 1 /* unmatched " in a valid SQL comment */"#,
+            r#"id = 1 /*! OR "PartyAbbrev" = 'D' */"#,
+            r#"path = '\' AND "PartyAbbrev" = 'D'"#,
+        ] {
+            let batches = table
+                .query()
+                .only_if(predicate)
+                .execute()
+                .await
+                .unwrap()
+                .try_collect::<Vec<_>>()
+                .await
+                .unwrap();
+            assert_eq!(batches.iter().map(RecordBatch::num_rows).sum::<usize>(), 1);
+        }
+
+        // The same canonical predicate contract applies to both merge filters.
+        let source = RecordBatch::try_new(
+            schema.clone(),
+            vec![
+                Arc::new(Int32Array::from(vec![1, 2, 3])),
+                Arc::new(StringArray::from(vec!["D", "R", "R"])),
+                Arc::new(StringArray::from(vec!["\\", "\\", "x"])),
+            ],
+        )
+        .unwrap();
+        let mut merge = table.merge_insert(&["id"]);
+        merge.when_not_matched_by_source_delete(Some(r#""PartyAbbrev" = 'D'"#.to_string()));
+        let result = table
+            .base_table()
+            .merge_insert(
+                merge,
+                Box::new(RecordBatchIterator::new(vec![Ok(source)], schema.clone())),
+            )
+            .await
+            .unwrap();
+        assert_eq!(result.num_deleted_rows, 1);
+
+        let source = RecordBatch::try_new(
+            schema.clone(),
+            vec![
+                Arc::new(Int32Array::from(vec![1, 2, 3])),
+                Arc::new(StringArray::from(vec!["U", "U", "U"])),
+                Arc::new(StringArray::from(vec!["\\", "\\", "x"])),
+            ],
+        )
+        .unwrap();
+        let mut merge = table.merge_insert(&["id"]);
+        merge.when_matched_update_all(Some(r#"target."PartyAbbrev" = 'D'"#.to_string()));
+        merge
+            .execute(Box::new(RecordBatchIterator::new(vec![Ok(source)], schema)))
+            .await
+            .unwrap();
+        assert_eq!(
+            table
+                .count_rows(Some(r#""PartyAbbrev" = 'U'"#.to_string()))
+                .await
+                .unwrap(),
+            1
+        );
+
+        let update = table
+            .update()
+            .only_if(r#""PartyAbbrev" = 'R'"#)
+            .column("PartyAbbrev", "'X'");
+        table.base_table().update(update).await.unwrap();
+        assert_eq!(
+            table
+                .count_rows(Some(r#""PartyAbbrev" = 'X'"#.to_string()))
+                .await
+                .unwrap(),
+            2
+        );
+
+        let result = table
+            .base_table()
+            .delete(crate::table::Predicate::String(r#""PartyAbbrev" = 'X'"#))
+            .await
+            .unwrap();
+        assert_eq!(result.num_deleted_rows, 2);
+        assert_eq!(table.count_rows(None).await.unwrap(), 1);
+    }
+
    #[tokio::test]
    async fn test_select_with_transform() {
        let batches = make_non_empty_batches();
@@ -2331,7 +2503,8 @@ mod tests {
            .limit(1);

        let plan = query.explain_plan(true).await.unwrap();
-        assert!(plan.contains("UnionExec"));
+        assert!(plan.contains("KNNVectorDistance: queries=2"));
+        assert!(!plan.contains("UnionExec"));

        let results = query
            .execute()
@@ -2346,6 +2519,100 @@ mod tests {
        // We don't guarantee order.
        assert!(query_index.values().contains(&0));
        assert!(query_index.values().contains(&1));
+
+        // Batch KNN does not support a per-query offset, so offset queries keep
+        // the legacy per-vector plan to preserve their result semantics.
+        let offset_query = table
+            .query()
+            .nearest_to(&[0.1, 0.2, 0.3, 0.4])
+            .unwrap()
+            .add_query_vector(&[0.5, 0.6, 0.7, 0.8])
+            .unwrap()
+            .limit(1)
+            .offset(1);
+        assert!(
+            offset_query
+                .explain_plan(true)
+                .await
+                .unwrap()
+                .contains("UnionExec")
+        );
+        let offset_results = offset_query
+            .execute()
+            .await
+            .unwrap()
+            .try_collect::<Vec<_>>()
+            .await
+            .unwrap();
+        assert_eq!(
+            offset_results
+                .iter()
+                .map(RecordBatch::num_rows)
+                .sum::<usize>(),
+            2
+        );
+    }
+
+    #[tokio::test]
+    async fn test_multiple_binary_query_vectors() {
+        let vectors = FixedSizeListArray::from_iter_primitive::<UInt8Type, _, _>(
+            vec![
+                Some(vec![Some(0), Some(0)]),
+                Some(vec![Some(255), Some(255)]),
+            ],
+            2,
+        );
+        let schema = Arc::new(ArrowSchema::new(vec![
+            ArrowField::new("id", DataType::Int32, false),
+            ArrowField::new("vector", vectors.data_type().clone(), false),
+        ]));
+        let batch = RecordBatch::try_new(
+            schema,
+            vec![Arc::new(Int32Array::from(vec![0, 1])), Arc::new(vectors)],
+        )
+        .unwrap();
+
+        let conn = connect("memory://").execute().await.unwrap();
+        let table = conn
+            .create_table("binary_batch", batch)
+            .execute()
+            .await
+            .unwrap();
+        let query = table
+            .query()
+            .nearest_to(&[0.0, 0.0])
+            .unwrap()
+            .add_query_vector(&[255.0, 255.0])
+            .unwrap()
+            .distance_type(DistanceType::Hamming)
+            .limit(1);
+
+        // Binary queries retain the per-vector plan because Lance's binary
+        // nearest path requires primitive UInt8 query arrays.
+        assert!(
+            query
+                .explain_plan(true)
+                .await
+                .unwrap()
+                .contains("UnionExec")
+        );
+
+        let results = query
+            .execute()
+            .await
+            .unwrap()
+            .try_collect::<Vec<_>>()
+            .await
+            .unwrap();
+        let results = concat_batches(&results[0].schema(), &results).unwrap();
+        assert_eq!(results.num_rows(), 2);
+
+        let ids = results["id"].as_primitive::<Int32Type>();
+        assert!(ids.values().contains(&0));
+        assert!(ids.values().contains(&1));
+        let query_index = results["query_index"].as_primitive::<Int32Type>();
+        assert!(query_index.values().contains(&0));
+        assert!(query_index.values().contains(&1));
    }

    #[tokio::test]
@@ -87,6 +87,10 @@ impl ServerVersion {
    pub fn support_blobs(&self) -> bool {
        self.0 >= semver::Version::new(0, 5, 0)
    }
+
+    pub fn support_fts_document_granularity(&self) -> bool {
+        self.0 >= semver::Version::new(0, 6, 0)
+    }
 }

 pub const OPT_REMOTE_PREFIX: &str = "remote_database_";
@@ -6,6 +6,7 @@
 use std::ops::Range;
 use std::sync::Arc;
 use std::sync::atomic::{AtomicBool, Ordering};
+use std::time::Duration;

 use arrow_array::{Array, LargeBinaryArray};
 use arrow_schema::DataType;
@@ -20,7 +21,7 @@ use crate::error::Result;
 use crate::remote::client::{HttpSend, RequestResultExt, RestfulLanceDbClient};
 use crate::table::BaseTable;

-use super::{FreshnessHeaders, RemoteTable};
+use super::{FreshnessHeaders, FreshnessState, RemoteTable, freshness_headers_snapshot};

 #[derive(Debug, Clone, Copy)]
 enum RangeRequestMode {
@@ -43,7 +44,10 @@ struct TableBlobRangeRequester<S: HttpSend> {
    path: String,
    version: Option<u64>,
    branch: Option<String>,
-    freshness: FreshnessHeaders,
+    freshness: Arc<std::sync::Mutex<FreshnessState>>,
+    parent_freshness: Arc<std::sync::Mutex<FreshnessState>>,
+    parent_freshness_request: FreshnessHeaders,
+    read_consistency_interval: Option<Duration>,
 }

 #[async_trait::async_trait]
@@ -53,8 +57,9 @@ impl<S: HttpSend> BlobRangeRequester for TableBlobRangeRequester<S> {
        range_header: &str,
        mode: RangeRequestMode,
    ) -> Result<(String, Response)> {
-        let mut request = self
-            .freshness
+        let freshness_request =
+            freshness_headers_snapshot(&self.freshness, self.read_consistency_interval);
+        let mut request = freshness_request
            .apply(self.client.get(&self.path))
            .header(header::RANGE, range_header);
        if let Some(version) = self.version {
@@ -71,6 +76,9 @@ impl<S: HttpSend> BlobRangeRequester for TableBlobRangeRequester<S> {
            return Ok((request_id, response));
        }
        let response = self.client.check_response(&request_id, response).await?;
+        freshness_request.observe_headers(&self.freshness, response.headers());
+        self.parent_freshness_request
+            .observe_headers(&self.parent_freshness, response.headers());
        Ok((request_id, response))
    }
 }
@@ -361,18 +369,21 @@ impl<S: HttpSend> RemoteTable<S> {
                message: "fetch_blobs is not supported on this LanceDB Cloud server".into(),
            });
        }
-        let version = self.current_version().await;
+        let read_snapshot = self.snapshot_read_state().await;
        let mut body = serde_json::json!({
-            "version": version,
+            "version": read_snapshot.version,
            "column": column,
            "row_ids": row_ids,
        });
        self.apply_branch_body(&mut body);

        let request = self
-            .post_read(&format!("/v1/table/{}/fetch_blobs/", self.identifier))
+            .client
+            .post(&format!("/v1/table/{}/fetch_blobs/", self.identifier))
            .json(&body);
-        let (request_id, response) = self.send(request, true).await?;
+        let (request_id, response) = self
+            .send_with_freshness(request, true, read_snapshot.freshness)
+            .await?;
        let mut stream = self.read_arrow_response(&request_id, response).await?;

        let mut blob_chunks: Vec<Arc<dyn Array>> = Vec::new();
@@ -448,8 +459,7 @@ impl<S: HttpSend> RemoteTable<S> {
            });
        }

-        let version = self.current_version().await;
-        let freshness = self.snapshot_freshness_headers();
+        let read_snapshot = self.snapshot_read_state().await;
        let encoded_column = urlencoding::encode(column);
        let requesters = row_ids
            .iter()
@@ -461,9 +471,12 @@ impl<S: HttpSend> RemoteTable<S> {
                let requester: Arc<dyn BlobRangeRequester> = Arc::new(TableBlobRangeRequester {
                    client: self.client.clone(),
                    path,
-                    version,
+                    version: read_snapshot.version,
                    branch: self.branch.clone(),
-                    freshness,
+                    freshness: Arc::new(std::sync::Mutex::new(read_snapshot.freshness_state)),
+                    parent_freshness: self.freshness.clone(),
+                    parent_freshness_request: read_snapshot.freshness,
+                    read_consistency_interval: self.client.read_consistency_interval,
                });
                requester
            })
@@ -685,6 +698,46 @@ mod tests {
        assert!(requests.lock().unwrap().contains(&"bytes=5-11".to_string()));
    }

+    #[tokio::test]
+    async fn remote_blob_file_keeps_the_open_timeline_after_parent_checkout() {
+        let range_requests = Arc::new(StdMutex::new(Vec::new()));
+        let captured = range_requests.clone();
+        let table = RemoteTable::new_mock(
+            "my_table".to_string(),
+            move |request| match request.url().path() {
+                "/v1/table/my_table/describe/" => http::Response::builder()
+                    .status(200)
+                    .body(r#"{"version":5,"schema":{"fields":[]}}"#.as_bytes().to_vec())
+                    .unwrap(),
+                "/v1/table/my_table/blob/image/10/bytes" => {
+                    captured.lock().unwrap().push((
+                        request.url().query().unwrap_or_default().to_string(),
+                        request.headers().clone(),
+                    ));
+                    range_response(&request, PAYLOAD)
+                }
+                path => panic!("unexpected path: {path}"),
+            },
+            Some(Version::new(0, 5, 0)),
+        );
+
+        table.checkout(5).await.unwrap();
+        let file = table
+            .fetch_blob_files_impl("image", &[10])
+            .await
+            .unwrap()
+            .pop()
+            .flatten()
+            .unwrap();
+        table.checkout_latest().await.unwrap();
+        file.read_range(5..12).await.unwrap();
+
+        let requests = range_requests.lock().unwrap();
+        let (query, headers) = requests.last().unwrap();
+        assert!(query.contains("version=5"));
+        assert!(!headers.contains_key("x-lancedb-min-timestamp"));
+    }
+
    #[tokio::test]
    async fn remote_blob_file_reuses_sequential_response_until_seek() {
        let requests = Arc::new(StdMutex::new(Vec::new()));
@@ -24,7 +24,10 @@ use lance::io::exec::utils::InstrumentedRecordBatchStreamAdapter;
 use crate::Error;
 use crate::remote::ARROW_STREAM_CONTENT_TYPE;
 use crate::remote::client::{HttpSend, RestfulLanceDbClient, Sender};
-use crate::remote::table::{MergeInsertRequest, REQUEST_TIMEOUT_HEADER, RemoteTable};
+use crate::remote::table::{
+    FreshnessHeaders, FreshnessState, MergeInsertRequest, REQUEST_TIMEOUT_HEADER, RemoteTable,
+    freshness_headers_snapshot,
+};
 use crate::table::datafusion::insert::COUNT_SCHEMA;
 use crate::table::write_progress::WriteProgressTracker;
 use crate::table::{AddResult, MergeResult};
@@ -54,6 +57,38 @@ pub enum WriteResult {
    Merge(MergeResult),
 }

+#[derive(Debug, Clone, Default)]
+struct WriteFreshness {
+    state: Option<Arc<Mutex<FreshnessState>>>,
+    read_consistency_interval: Option<Duration>,
+}
+
+impl WriteFreshness {
+    fn prepare(
+        &self,
+        request: reqwest::RequestBuilder,
+    ) -> (reqwest::RequestBuilder, Option<FreshnessHeaders>) {
+        match &self.state {
+            Some(state) => {
+                let freshness_request =
+                    freshness_headers_snapshot(state, self.read_consistency_interval);
+                (freshness_request.apply(request), Some(freshness_request))
+            }
+            None => (request, None),
+        }
+    }
+
+    fn observe(
+        &self,
+        freshness_request: Option<FreshnessHeaders>,
+        headers: &reqwest::header::HeaderMap,
+    ) {
+        if let (Some(state), Some(freshness_request)) = (&self.state, freshness_request) {
+            freshness_request.observe_headers(state, headers);
+        }
+    }
+}
+
 /// ExecutionPlan for streaming a write (add or merge_insert) to a remote
 /// LanceDB table.
 ///
@@ -71,6 +106,7 @@ pub struct RemoteWriteExec<S: HttpSend = Sender> {
    table_name: String,
    identifier: String,
    client: RestfulLanceDbClient<S>,
+    freshness: WriteFreshness,
    input: Arc<dyn ExecutionPlan>,
    op: WriteOp,
    properties: Arc<PlanProperties>,
@@ -170,6 +206,7 @@ impl<S: HttpSend + 'static> RemoteWriteExec<S> {
            table_name,
            identifier,
            client,
+            freshness: WriteFreshness::default(),
            input,
            op,
            properties: Arc::new(properties),
@@ -183,6 +220,18 @@ impl<S: HttpSend + 'static> RemoteWriteExec<S> {
        }
    }

+    pub(super) fn with_freshness(
+        mut self,
+        state: Arc<Mutex<FreshnessState>>,
+        read_consistency_interval: Option<Duration>,
+    ) -> Self {
+        self.freshness = WriteFreshness {
+            state: Some(state),
+            read_consistency_interval,
+        };
+        self
+    }
+
    /// Get the add result after execution, if this exec ran an insert.
    pub fn add_result(&self) -> Option<AddResult> {
        match self
@@ -285,6 +334,7 @@ impl<S: HttpSend + 'static> RemoteWriteExec<S> {
 /// each threading the same handful of arguments.
 struct PartRequestCtx<'a, S: HttpSend> {
    client: &'a RestfulLanceDbClient<S>,
+    freshness: &'a WriteFreshness,
    identifier: &'a str,
    table_name: &'a str,
    upload_id: &'a str,
@@ -352,7 +402,11 @@ impl<S: HttpSend + 'static> PartRequestCtx<'_, S> {
    }

    /// Build the `/insert` request for a single multipart part.
-    fn build_part_request(&self, part_id: &str, body: reqwest::Body) -> reqwest::RequestBuilder {
+    fn build_part_request(
+        &self,
+        part_id: &str,
+        body: reqwest::Body,
+    ) -> (reqwest::RequestBuilder, Option<FreshnessHeaders>) {
        let mut request = self
            .client
            .post(&format!("/v1/table/{}/insert/", self.identifier))
@@ -368,12 +422,16 @@ impl<S: HttpSend + 'static> PartRequestCtx<'_, S> {
        if let Some(b) = self.branch {
            request = request.query(&[("branch", b)]);
        }
-        request.body(body)
+        self.freshness.prepare(request.body(body))
    }

    /// Send a single part's request and drain the response, mapping HTTP and
    /// table-not-found errors into `DataFusionError`.
-    async fn send_part_request(&self, request: reqwest::RequestBuilder) -> DataFusionResult<()> {
+    async fn send_part_request(
+        &self,
+        request: reqwest::RequestBuilder,
+        freshness_request: Option<FreshnessHeaders>,
+    ) -> DataFusionResult<()> {
        let (request_id, response) = self
            .client
            .send(request)
@@ -388,6 +446,8 @@ impl<S: HttpSend + 'static> PartRequestCtx<'_, S> {
            .check_response(&request_id, response)
            .await
            .map_err(|e| DataFusionError::External(Box::new(e)))?;
+        self.freshness
+            .observe(freshness_request, response.headers());
        response.bytes().await.map_err(|e| {
            DataFusionError::External(Box::new(Error::Http {
                source: Box::new(e),
@@ -419,7 +479,7 @@ impl<S: HttpSend + 'static> PartRequestCtx<'_, S> {
        let body = reqwest::Body::wrap_stream(chunk_rx);

        let part_id = uuid::Uuid::new_v4().to_string();
-        let request = self.build_part_request(&part_id, body);
+        let (request, freshness_request) = self.build_part_request(&part_id, body);

        // Measured from just before the request is sent, matching the window the
        // client read timeout applies to the upload.
@@ -495,7 +555,7 @@ impl<S: HttpSend + 'static> PartRequestCtx<'_, S> {
            Ok::<bool, DataFusionError>(input_ended)
        };

-        let send = self.send_part_request(request);
+        let send = self.send_part_request(request, freshness_request);

        // `join!` rather than `tokio::spawn`: the producer borrows `input` (and
        // `schema`), so it cannot satisfy the `'static` bound a spawned task
@@ -569,7 +629,7 @@ impl<S: HttpSend + 'static> ExecutionPlan for RemoteWriteExec<S> {
        // Building a fresh exec (with a new, empty `result`) is what makes the
        // outer rescannable retry loop work: `reset_state()` clears the captured
        // result so a re-execution starts clean.
-        Ok(Arc::new(Self::new_inner(
+        let mut exec = Self::new_inner(
            self.table_name.clone(),
            self.identifier.clone(),
            self.client.clone(),
@@ -580,7 +640,9 @@ impl<S: HttpSend + 'static> ExecutionPlan for RemoteWriteExec<S> {
            self.branch.clone(),
            self.max_bytes_per_request,
            self.max_request_duration,
-        )))
+        );
+        exec.freshness = self.freshness.clone();
+        Ok(Arc::new(exec))
    }

    fn execute(
@@ -613,6 +675,7 @@ impl<S: HttpSend + 'static> ExecutionPlan for RemoteWriteExec<S> {
                &self.metrics,
            ));
        let client = self.client.clone();
+        let freshness = self.freshness.clone();
        let identifier = self.identifier.clone();
        let op = self.op.clone();
        let result_slot = self.result.clone();
@@ -634,6 +697,7 @@ impl<S: HttpSend + 'static> ExecutionPlan for RemoteWriteExec<S> {
                let overwrite = matches!(op, WriteOp::Insert { overwrite: true });
                let ctx = PartRequestCtx {
                    client: &client,
+                    freshness: &freshness,
                    identifier: &identifier,
                    table_name: &table_name,
                    upload_id,
@@ -688,7 +752,7 @@ impl<S: HttpSend + 'static> ExecutionPlan for RemoteWriteExec<S> {

            let (error_tx, mut error_rx) = tokio::sync::oneshot::channel();
            let body = Self::stream_as_http_body(input_stream, error_tx, tracker)?;
-            let request = request.body(body);
+            let (request, freshness_request) = freshness.prepare(request.body(body));

            let result: DataFusionResult<(String, _)> = async {
                let (request_id, response) = client
@@ -708,6 +772,7 @@ impl<S: HttpSend + 'static> ExecutionPlan for RemoteWriteExec<S> {
                    .check_response(&request_id, response)
                    .await
                    .map_err(|e| DataFusionError::External(Box::new(e)))?;
+                freshness.observe(freshness_request, response.headers());

                Ok((request_id, response))
            }
@@ -59,7 +59,9 @@ use crate::index::{IndexConfig, IndexStatisticsImpl, IndexType};
 use crate::job::Job;
 use crate::query::{IntoQueryVector, Query, QueryExecutionOptions, TakeQuery, VectorQuery};
 use crate::table::datafusion::insert::InsertExec;
-use crate::utils::{PatchReadParam, PatchWriteParam, resolve_arrow_field_path};
+use crate::utils::{
+    PatchReadParam, PatchWriteParam, public_fts_field_path_by_id, resolve_arrow_field_path,
+};

 use self::dataset::DatasetConsistencyWrapper;
 use self::merge::MergeInsertBuilder;
@@ -560,6 +562,13 @@ pub trait BaseTable: std::fmt::Display + std::fmt::Debug + Send + Sync {
    fn id(&self) -> &str;
    /// Get the arrow [Schema] of the table.
    async fn schema(&self) -> Result<SchemaRef>;
+    /// Create a read-only handle pinned to the table's current active revision.
+    ///
+    /// The returned handle is independent from later refreshes or checkouts on
+    /// this handle.  This is used by bindings that must prepare client-side
+    /// query state from the same revision that the query will execute against.
+    #[doc(hidden)]
+    async fn query_snapshot(&self) -> Result<Arc<dyn BaseTable>>;
    /// Count the number of rows in this table.
    async fn count_rows(&self, filter: Option<Filter>) -> Result<usize>;
    /// Create a physical plan for the query.
@@ -751,7 +760,7 @@ pub trait BaseTable: std::fmt::Display + std::fmt::Debug + Send + Sync {
            message: "computed columns are not supported on this table type".into(),
        })
    }
-    /// Declare one immutable registered-Function output group.
+    /// Declare one immutable registered-Function binding.
    async fn add_function_columns(
        &self,
        _application: &crate::function::FunctionApplication,
@@ -785,6 +794,12 @@ pub trait BaseTable: std::fmt::Display + std::fmt::Debug + Send + Sync {
    async fn drop_columns(&self, columns: &[&str]) -> Result<DropColumnsResult>;
    /// Get the version of the table.
    async fn version(&self) -> Result<u64>;
+    /// Return a new table handle pinned to the exact revision currently visible.
+    async fn checkout_current(&self) -> Result<Arc<dyn BaseTable>> {
+        Err(Error::NotSupported {
+            message: "checkout_current is not supported on this table type".into(),
+        })
+    }
    /// Checkout a specific version of the table.
    async fn checkout(&self, version: u64) -> Result<()>;
    /// Checkout a table version referenced by a tag.
@@ -1133,13 +1148,26 @@ impl Table {
        self.inner.schema().await
    }

+    /// Create a read-only handle pinned to the current active revision.
+    #[doc(hidden)]
+    pub async fn query_snapshot(&self) -> Result<Self> {
+        Ok(Self {
+            inner: self.inner.query_snapshot().await?,
+            database: self.database.clone(),
+            embedding_registry: self.embedding_registry.clone(),
+        })
+    }
+
    /// Count the number of rows in this dataset.
    ///
    /// # Arguments
    ///
    /// * `filter` if present, only count rows matching the filter
    pub async fn count_rows(&self, filter: Option<String>) -> Result<usize> {
-        self.inner.count_rows(filter.map(Filter::Sql)).await
+        let filter = filter
+            .map(|predicate| crate::expr::canonicalize_sql_predicate(&predicate).map(Filter::Sql))
+            .transpose()?;
+        self.inner.count_rows(filter).await
    }

    /// Names of the blob v2 columns in this table, in declaration order.
@@ -1339,7 +1367,13 @@ impl Table {
    /// # });
    /// ```
    pub async fn delete(&self, predicate: impl Into<Predicate<'_>>) -> Result<DeleteResult> {
-        self.inner.delete(predicate.into()).await
+        match predicate.into() {
+            Predicate::String(predicate) => {
+                let predicate = crate::expr::canonicalize_sql_predicate(predicate)?;
+                self.inner.delete(Predicate::String(&predicate)).await
+            }
+            predicate @ Predicate::Expr(_) => self.inner.delete(predicate).await,
+        }
    }

    /// Create an index on the provided column(s).
@@ -1752,7 +1786,23 @@ impl Table {
        self.inner.alter_columns(alterations).await
    }

-    /// Update per-field metadata (merges by default).
+    /// Update per-field (column) metadata.
+    ///
+    /// Each [`FieldMetadataUpdate`] is merged into the field's existing metadata
+    /// by default; use [`FieldMetadataUpdate::remove`] to delete a key, or
+    /// [`FieldMetadataUpdate::replace`] to swap the field's entire metadata map.
+    ///
+    /// The following keys are treated specially, by convention, and should be
+    /// used when appropriate:
+    ///
+    /// - `lancedb:description`: for a human-readable description of a field.
+    /// - `lancedb:tag:<name>`: for a user-defined key-value tag, where the suffix
+    ///   names the tag category; e.g. `lancedb:tag:model: "clip"`.
+    /// - `lancedb:logical-column`: for a column grouping; e.g. `feature_v1` and
+    ///   `feature_v2` might be in the same logical column.
+    /// - `lancedb:status`: for status options (`production`, `candidate`,
+    ///   `deprecated`, `archived`) to designate the current life cycle state of
+    ///   this column.
    pub async fn update_field_metadata(
        &self,
        updates: &[FieldMetadataUpdate],
@@ -1944,6 +1994,20 @@ impl Table {
        self.inner.version().await
    }

+    /// Return a new table handle pinned to the exact revision currently visible.
+    ///
+    /// This is used when asynchronous preparation must remain consistent with
+    /// the revision used for a later read.
+    #[doc(hidden)]
+    pub async fn checkout_current(&self) -> Result<Self> {
+        let inner = self.inner.checkout_current().await?;
+        Ok(Self {
+            inner,
+            database: self.database.clone(),
+            embedding_registry: self.embedding_registry.clone(),
+        })
+    }
+
    /// Checks out a specific version of the Table
    ///
    /// Any read operation on the table will now access the data at the checked out version.
@@ -3039,10 +3103,33 @@ impl BaseTable for NativeTable {
        &self.id
    }

+    async fn query_snapshot(&self) -> Result<Arc<dyn BaseTable>> {
+        let snapshot = self.dataset.new_query_snapshot().await?;
+        let mut table = self.with_dataset(snapshot);
+        // QueryTable requests do not carry a revision. A pinned snapshot must
+        // execute locally until the namespace API can accept that revision.
+        table
+            .pushdown_operations
+            .remove(&NamespaceClientPushdownOperation::QueryTable);
+        Ok(Arc::new(table))
+    }
+
    async fn version(&self) -> Result<u64> {
        Ok(self.dataset.get().await?.version().version)
    }

+    async fn checkout_current(&self) -> Result<Arc<dyn BaseTable>> {
+        let current = self.dataset.get().await?;
+        let dataset = dataset::DatasetConsistencyWrapper::new_time_travel(
+            current.as_ref().clone(),
+            self.read_consistency_interval,
+        );
+        Ok(Arc::new(Self {
+            dataset,
+            ..self.clone()
+        }))
+    }
+
    async fn checkout(&self, version: u64) -> Result<()> {
        self.dataset.as_time_travel(version).await
    }
@@ -3161,7 +3248,10 @@ impl BaseTable for NativeTable {
        let dataset = self.dataset.get().await?;
        match filter {
            None => Ok(dataset.count_rows(None).await?),
-            Some(Filter::Sql(sql)) => Ok(dataset.count_rows(Some(sql)).await?),
+            Some(Filter::Sql(sql)) => {
+                let sql = crate::expr::canonicalize_sql_predicate(&sql)?;
+                Ok(dataset.count_rows(Some(sql)).await?)
+            }
            Some(Filter::Datafusion(_)) => Err(Error::NotSupported {
                message: "Datafusion filters are not yet supported".to_string(),
            }),
@@ -3208,7 +3298,7 @@ impl BaseTable for NativeTable {

        let output = add.into_plan(&table_schema, &table_def)?;

-        let lance_params = output
+        let mut lance_params = output
            .write_options
            .lance_write_params
            .unwrap_or(WriteParams {
@@ -3218,6 +3308,9 @@ impl BaseTable for NativeTable {
                },
                ..Default::default()
            });
+        if output.allow_external_blob_outside_bases {
+            lance_params.allow_external_blob_outside_bases = true;
+        }

        // Repartition for write parallelism if beneficial.
        let plan = if num_partitions > 1 {
@@ -3496,7 +3589,14 @@ impl BaseTable for NativeTable {
                let field_ids = idx_desc.field_ids();
                let mut columns = Vec::with_capacity(field_ids.len());
                for field_id in field_ids {
-                    let field_path = match dataset.schema().field_path(*field_id as i32) {
+                    let field_path = match if index_type == crate::index::IndexType::FTS {
+                        public_fts_field_path_by_id(dataset.schema(), *field_id as i32)
+                    } else {
+                        dataset
+                            .schema()
+                            .field_path(*field_id as i32)
+                            .map_err(Into::into)
+                    } {
                        Ok(field_path) => field_path,
                        Err(e) => {
                            log::warn!(
@@ -4083,6 +4183,14 @@ mod tests {
                parent_list_calls: self.parent_list_calls.clone(),
            })
        }
+
+        fn wrap_paginated(
+            &self,
+            _store_prefix: &str,
+            _original: Arc<dyn object_store::list::PaginatedListStore>,
+        ) -> Option<Arc<dyn object_store::list::PaginatedListStore>> {
+            None
+        }
    }

    #[tokio::test]
@@ -4186,6 +4294,14 @@ mod tests {
            self.called.store(true, Ordering::Relaxed);
            original
        }
+
+        fn wrap_paginated(
+            &self,
+            _store_prefix: &str,
+            original: Arc<dyn object_store::list::PaginatedListStore>,
+        ) -> Option<Arc<dyn object_store::list::PaginatedListStore>> {
+            Some(original)
+        }
    }

    #[tokio::test]
@@ -88,7 +88,7 @@ impl AddColumnsBuilder {
    }

    /// Declare every field of a named-struct Function result as one atomic
-    /// sibling group. Result-field aliases come from
+    /// binding. Result-field aliases come from
    /// [`FunctionApplication::columns`](crate::function::FunctionApplication::columns).
    ///
    /// ```
@@ -60,6 +60,7 @@ pub struct AddDataBuilder {
    pub(crate) embedding_registry: Option<Arc<dyn EmbeddingRegistry>>,
    pub(crate) progress_callback: Option<ProgressCallback>,
    pub(crate) write_parallelism: Option<usize>,
+    pub(crate) allow_external_blob_outside_bases: bool,
 }

 impl std::fmt::Debug for AddDataBuilder {
@@ -87,6 +88,7 @@ impl AddDataBuilder {
            embedding_registry,
            progress_callback: None,
            write_parallelism: None,
+            allow_external_blob_outside_bases: false,
        }
    }

@@ -141,6 +143,16 @@ impl AddDataBuilder {
        self
    }

+    /// Store blob URIs that sit outside registered blob bases.
+    ///
+    /// The row keeps a reference, so the object has to stay readable.
+    /// [`crate::table::Table::fetch_blobs`] reads from that location.
+    /// Defaults to `false`. Local tables only.
+    pub fn allow_external_blob_outside_bases(mut self, allow: bool) -> Self {
+        self.allow_external_blob_outside_bases = allow;
+        self
+    }
+
    pub async fn execute(self) -> Result<AddResult> {
        if self.write_parallelism.map(|p| p == 0).unwrap_or(false) {
            return Err(Error::InvalidInput {
@@ -199,6 +211,7 @@ impl AddDataBuilder {
            write_options: self.write_options,
            mode: self.mode,
            tracker,
+            allow_external_blob_outside_bases: self.allow_external_blob_outside_bases,
        })
    }
 }
@@ -212,6 +225,7 @@ pub struct PreprocessingOutput {
    pub write_options: WriteOptions,
    pub mode: AddDataMode,
    pub tracker: Option<Arc<WriteProgressTracker>>,
+    pub allow_external_blob_outside_bases: bool,
 }

 /// Check that the input schema is valid for insert.
@@ -13,7 +13,7 @@
 //! self-describing -- both are derived from the expression, so a caller writes
 //! neither -- while a kind resolved through a registry cannot be typed without
 //! consulting it. Registered Functions use an exact remote version plus a
-//! schema-level grouped binding; unknown newer kinds remain readable and fail
+//! schema-level Function binding; unknown newer kinds remain readable and fail
 //! closed before mutation.
 //!
 //! [`computed_columns`] and [`computed_column_from_field`] read declarations
@@ -46,16 +46,16 @@ pub const EXPRESSION_META_KEY: &str = "computed_column.expression";
 /// Field metadata key holding the column's inputs, as a JSON array of names.
 pub const INPUTS_META_KEY: &str = "computed_column.inputs";

-/// Field metadata key holding the grouped Function binding identity.
+/// Field metadata key holding the Function binding identity.
 pub const FUNCTION_BINDING_ID_META_KEY: &str = "computed_column.function.binding_id";

 /// Field metadata key holding this sibling's ordered Function output ordinal.
 pub const FUNCTION_OUTPUT_ORDINAL_META_KEY: &str = "computed_column.function.output_ordinal";

-/// Schema metadata key holding all immutable grouped Function bindings.
+/// Schema metadata key holding all immutable Function bindings.
 pub const FUNCTION_BINDINGS_META_KEY: &str = "lancedb::function_bindings";

-/// Version of the schema-level grouped Function binding envelope.
+/// Version of the schema-level Function binding envelope.
 pub const FUNCTION_BINDINGS_VERSION: u32 = 1;

 /// Value of [`KIND_META_KEY`] for a column defined by a SQL expression.
@@ -81,7 +81,7 @@ pub enum ComputedColumnKind {
        /// The expression.
        expression: String,
    },
-    /// One physical output in an immutable grouped registered-Function
+    /// One physical output in an immutable registered-Function
    /// binding. The full binding lives in schema metadata.
    Function {
        /// Shared immutable binding identity.
@@ -159,7 +159,7 @@ struct FunctionBindingEnvelope {
    bindings: Vec<Value>,
 }

-/// Encode immutable grouped bindings for schema-level persistence.
+/// Encode immutable Function bindings for schema-level persistence.
 pub fn function_bindings_metadata(bindings: &[FunctionBinding]) -> Result<String> {
    let bindings = bindings
        .iter()
@@ -177,7 +177,7 @@ pub fn function_bindings_metadata(bindings: &[FunctionBinding]) -> Result<String
    })
 }

-/// Decode known grouped Function bindings without rewriting their raw schema
+/// Decode known Function bindings without rewriting their raw schema
 /// metadata. Unknown envelope versions fail closed.
 pub fn function_bindings(schema: &ArrowSchema) -> Result<Vec<FunctionBinding>> {
    let Some(envelope) = function_binding_envelope(schema)? else {
@@ -238,21 +238,15 @@ pub(crate) fn ensure_supported_function_metadata(schema: &ArrowSchema) -> Result
                message: format!("duplicate Function binding '{}'", binding.binding_id()),
            });
        }
-        if binding.revision() == 0 || binding.outputs().is_empty() {
+        if binding.outputs().is_empty() {
            return Err(Error::InvalidInput {
-                message: format!(
-                    "Function binding '{}' has no immutable revision or outputs",
-                    binding.binding_id()
-                ),
+                message: format!("Function binding '{}' has no outputs", binding.binding_id()),
            });
        }
-        if binding.function().name.is_empty()
-            || binding.function().version.is_empty()
-            || binding.group_id().is_empty()
-        {
+        if binding.function().name.is_empty() || binding.function().version.is_empty() {
            return Err(Error::InvalidInput {
                message: format!(
-                    "Function binding '{}' has no exact version or group identity",
+                    "Function binding '{}' has no exact version",
                    binding.binding_id()
                ),
            });
@@ -493,9 +487,7 @@ fn ensure_known_binding_shape(value: &Value) -> Result<()> {
        value,
        &[
            "binding_id",
-            "revision",
            "function",
-            "group_id",
            "inputs",
            "outputs",
            "input_schema",
@@ -786,12 +778,9 @@ pub(crate) fn plan_function_application(
            message: "Function application contains fields from a newer contract".into(),
        });
    }
-    if application.function().name.is_empty()
-        || application.function().version.is_empty()
-        || application.group_id().is_empty()
-    {
+    if application.function().name.is_empty() || application.function().version.is_empty() {
        return Err(invalid_function(
-            "Function application requires an exact version and group identity",
+            "Function application requires an exact version",
        ));
    }

@@ -2261,7 +2250,6 @@ mod tests {
                    {{"name":"normalized_text","arrow_type":"utf8","nullable":false}},
                    {{"name":"token_count","arrow_type":"int64","nullable":false}}
                ]}},
-                "group_id":"fg_exact",
                "columns":{columns}
            }}"#
        ))
@@ -2442,8 +2430,7 @@ mod tests {
            r#"{
                "function":{"name":"f","version":"fv"},
                "inputs":[{"parameter":"title","kind":"future_source","value":{"path":"title"}}],
-                "output":{"kind":"scalar","arrow_type":"int64","nullable":false},
-                "group_id":"fg"
+                "output":{"kind":"scalar","arrow_type":"int64","nullable":false}
            }"#,
        )
        .unwrap();
@@ -2456,7 +2443,6 @@ mod tests {
                "function":{"name":"f","version":"fv"},
                "inputs":[],
                "output":{"kind":"scalar","arrow_type":"int64","nullable":false},
-                "group_id":"fg",
                "future_declaration":{"mode":"managed"}
            }"#,
        )
@@ -2470,8 +2456,7 @@ mod tests {
            r#"{
                "function":{"name":"f","version":"fv"},
                "inputs":[],
-                "output":{"kind":"scalar","arrow_type":"int64","nullable":false,"assignment":"cell_flag"},
-                "group_id":"fg"
+                "output":{"kind":"scalar","arrow_type":"int64","nullable":false,"assignment":"cell_flag"}
            }"#,
        )
        .unwrap();
@@ -28,8 +28,9 @@ pub(super) type PreparedIndex = (String, Box<dyn lance::index::IndexParams>, Ind
 use crate::index::Index;
 use crate::index::vector::{VectorIndex, suggested_num_sub_vectors};
 use crate::utils::{
-    supported_bitmap_data_type, supported_btree_data_type, supported_fm_data_type,
-    supported_fts_data_type, supported_label_list_data_type, supported_vector_data_type,
+    resolve_lance_fts_field_path, supported_bitmap_data_type, supported_btree_data_type,
+    supported_fm_data_type, supported_fts_data_type, supported_label_list_data_type,
+    supported_vector_data_type,
 };

 use super::NativeTable;
@@ -122,7 +123,20 @@ impl NativeTable {
        }
        self.dataset.ensure_mutable()?;
        let dataset = self.dataset.get().await?;
-        let (column, field) = Self::resolve_index_field(dataset.schema(), &opts.columns[0])?;
+        let (column, field) = if let Index::FTS(params) = &opts.index {
+            let resolved = resolve_lance_fts_field_path(dataset.schema(), &opts.columns[0])?;
+            if params.get_document_granularity().is_list_element() && resolved.list_depth == 0 {
+                return Err(Error::InvalidInput {
+                    message: format!(
+                        "FTS field path '{}' has no List layer and cannot use ListElement document granularity",
+                        resolved.canonical_path
+                    ),
+                });
+            }
+            (resolved.canonical_path, resolved.field)
+        } else {
+            Self::resolve_index_field(dataset.schema(), &opts.columns[0])?
+        };
        let params = self.make_index_params(&field, opts.index.clone()).await?;
        let index_type = self.get_index_type_for_field(&field, &opts.index);
        Ok((column, params, index_type))
@@ -436,7 +450,7 @@ mod tests {
    use crate::connection::ConnectBuilder;
    use crate::index::Index;
    use crate::index::scalar::{
-        BTreeIndexBuilder, BitmapIndexBuilder, FmIndexBuilder, FtsIndexBuilder,
+        BTreeIndexBuilder, BitmapIndexBuilder, DocumentGranularity, FmIndexBuilder, FtsIndexBuilder,
    };
    use crate::index::vector::{
        IvfHnswFlatIndexBuilder, IvfHnswPqIndexBuilder, IvfHnswSqIndexBuilder,
@@ -553,6 +567,38 @@ mod tests {
        job.cancel().await.unwrap();
    }

+    #[tokio::test]
+    async fn test_execute_async_validates_fts_input_before_starting_job() {
+        let conn = connect("memory://").execute().await.unwrap();
+        let batch =
+            record_batch!(("id", Int32, [1, 2]), ("text", Utf8, ["alpha", "beta"])).unwrap();
+        let table = conn.create_table("t", batch).execute().await.unwrap();
+
+        let missing = table
+            .create_index(&["missing"], Index::FTS(FtsIndexBuilder::default()))
+            .execute_async()
+            .await;
+        assert!(missing.is_err());
+
+        let invalid_type = table
+            .create_index(&["id"], Index::FTS(FtsIndexBuilder::default()))
+            .execute_async()
+            .await;
+        assert!(invalid_type.is_err());
+
+        let invalid_granularity = table
+            .create_index(
+                &["text"],
+                Index::FTS(
+                    FtsIndexBuilder::default()
+                        .document_granularity(DocumentGranularity::ListElement),
+                ),
+            )
+            .execute_async()
+            .await;
+        assert!(invalid_granularity.is_err());
+    }
+
    /// Concurrent waiters, and a wait issued after the job settled, all
    /// succeed once the build does.
    #[tokio::test]
@@ -7,7 +7,7 @@

 use std::sync::Arc;

-use arrow_schema::{DataType, Field, FieldRef};
+use arrow_schema::{DataType, Field, FieldRef, Fields};
 use datafusion::functions::core::{get_field, named_struct};
 use datafusion_common::ScalarValue;
 use datafusion_common::config::ConfigOptions;
@@ -35,8 +35,9 @@ pub(super) fn coerce_blob_expr(
        });
    };

-    let input_struct_children = match input_field.data_type() {
-        DataType::Binary | DataType::LargeBinary | DataType::BinaryView => None,
+    let input_shape = match input_field.data_type() {
+        DataType::Binary | DataType::LargeBinary | DataType::BinaryView => BlobInputShape::Bytes,
+        DataType::Utf8 | DataType::LargeUtf8 | DataType::Utf8View => BlobInputShape::String,
        DataType::Struct(children) => {
            if !children
                .iter()
@@ -49,13 +50,15 @@ pub(super) fn coerce_blob_expr(
                    ),
                });
            }
-            Some(children)
+            BlobInputShape::Struct(children)
        }
        other => {
            return Err(Error::InvalidInput {
                message: format!(
                    "cannot coerce column '{}' with type {} into a blob v2 struct. \
-                     expected Binary, LargeBinary, BinaryView, or a Struct with a 'data' or 'uri' child",
+                     expected binary bytes (Binary, LargeBinary, BinaryView), \
+                     strings (Utf8, LargeUtf8, Utf8View), \
+                     or a Struct with a 'data' or 'uri' child",
                    table_field.name(),
                    other,
                ),
@@ -69,9 +72,8 @@ pub(super) fn coerce_blob_expr(
            declared.name().as_str(),
        ))));

-        let value: Arc<dyn PhysicalExpr> = match input_struct_children {
-            // Raw binary lands in `data` and everything else is a typed null.
-            None => {
+        let value: Arc<dyn PhysicalExpr> = match &input_shape {
+            BlobInputShape::Bytes => {
                if declared.name() == "data" {
                    Arc::new(CastExpr::new(
                        input_expr.clone(),
@@ -82,30 +84,43 @@ pub(super) fn coerce_blob_expr(
                    typed_null(declared.data_type())?
                }
            }
-            Some(children) => match children.iter().find(|c| c.name() == declared.name()) {
-                Some(child) => {
-                    let field_expr: Arc<dyn PhysicalExpr> = Arc::new(ScalarFunctionExpr::new(
-                        &format!("get_field({})", declared.name()),
-                        get_field(),
-                        vec![
-                            input_expr.clone(),
-                            Arc::new(Literal::new(ScalarValue::from(declared.name().as_str()))),
-                        ],
-                        Arc::new(child.as_ref().clone()),
-                        config.clone(),
-                    ));
-                    if child.data_type() == declared.data_type() {
-                        field_expr
-                    } else {
-                        Arc::new(CastExpr::new(
-                            field_expr,
-                            declared.data_type().clone(),
-                            None,
-                        ))
-                    }
+            BlobInputShape::String => {
+                if declared.name() == "uri" {
+                    Arc::new(CastExpr::new(
+                        input_expr.clone(),
+                        declared.data_type().clone(),
+                        None,
+                    ))
+                } else {
+                    typed_null(declared.data_type())?
                }
-                None => typed_null(declared.data_type())?,
-            },
+            }
+            BlobInputShape::Struct(children) => {
+                match children.iter().find(|c| c.name() == declared.name()) {
+                    Some(child) => {
+                        let field_expr: Arc<dyn PhysicalExpr> = Arc::new(ScalarFunctionExpr::new(
+                            &format!("get_field({})", declared.name()),
+                            get_field(),
+                            vec![
+                                input_expr.clone(),
+                                Arc::new(Literal::new(ScalarValue::from(declared.name().as_str()))),
+                            ],
+                            Arc::new(child.as_ref().clone()),
+                            config.clone(),
+                        ));
+                        if child.data_type() == declared.data_type() {
+                            field_expr
+                        } else {
+                            Arc::new(CastExpr::new(
+                                field_expr,
+                                declared.data_type().clone(),
+                                None,
+                            ))
+                        }
+                    }
+                    None => typed_null(declared.data_type())?,
+                }
+            }
        };
        ns_args.push(value);
    }
@@ -120,6 +135,12 @@ pub(super) fn coerce_blob_expr(
    Ok((expr, table_field.clone()))
 }

+enum BlobInputShape<'a> {
+    Bytes,
+    String,
+    Struct(&'a Fields),
+}
+
 fn typed_null(data_type: &DataType) -> Result<Arc<dyn PhysicalExpr>> {
    let scalar = ScalarValue::try_from(data_type).map_err(|e| Error::InvalidInput {
        message: format!("cannot build null literal for blob child type {data_type}: {e}"),
@@ -134,7 +155,7 @@ mod tests {
    use crate::blob::blob;
    use arrow_array::{
        Array, ArrayRef, BinaryArray, BinaryViewArray, Int32Array, Int64Array, LargeBinaryArray,
-        RecordBatch, StringArray, StructArray, UInt8Array, UInt64Array,
+        RecordBatch, StringArray, StringViewArray, StructArray, UInt8Array, UInt64Array,
    };
    use arrow_schema::Schema;
    use datafusion::prelude::SessionContext;
@@ -436,14 +457,78 @@ mod tests {
    #[tokio::test]
    async fn unsupported_input_type_is_rejected_with_column_name() {
        let batch = batch_with_image(
-            Field::new("image", DataType::Utf8, true),
-            Arc::new(StringArray::from(vec!["not bytes"])),
+            Field::new("image", DataType::Int64, true),
+            Arc::new(Int64Array::from(vec![42])),
        );
        let err = coerce_err(batch, &blob_table_schema()).await;
        assert!(matches!(err, Error::InvalidInput { .. }), "got {err:?}");
        assert!(err.to_string().contains("image"));
    }

+    #[tokio::test]
+    async fn utf8_string_coerces_to_uri_child() {
+        let batch = batch_with_image(
+            Field::new("image", DataType::Utf8, true),
+            Arc::new(StringArray::from(vec![Some("s3://bucket/key"), None])),
+        );
+        let coerced = coerce(batch, &blob_table_schema()).await;
+        let image = image_struct(&coerced);
+        let uri: &StringArray = image
+            .column_by_name("uri")
+            .unwrap()
+            .as_any()
+            .downcast_ref()
+            .unwrap();
+        assert_eq!(uri.value(0), "s3://bucket/key");
+        assert!(image.column_by_name("data").unwrap().is_null(0));
+        assert!(uri.is_null(1));
+    }
+
+    #[tokio::test]
+    async fn large_utf8_string_coerces_into_four_child_blob_layout() {
+        use arrow_array::LargeStringArray;
+
+        let table_schema = Schema::new(vec![
+            Field::new("id", DataType::Int64, false),
+            wide_blob_field("image"),
+        ]);
+        let batch = batch_with_image(
+            Field::new("image", DataType::LargeUtf8, true),
+            Arc::new(LargeStringArray::from(vec!["file:///tmp/blob.bin"])),
+        );
+        let coerced = coerce(batch, &table_schema).await;
+        let image = image_struct(&coerced);
+        assert_eq!(image.num_columns(), 4);
+        let uri: &StringArray = image
+            .column_by_name("uri")
+            .unwrap()
+            .as_any()
+            .downcast_ref()
+            .unwrap();
+        assert_eq!(uri.value(0), "file:///tmp/blob.bin");
+        assert!(image.column_by_name("data").unwrap().is_null(0));
+        assert!(image.column_by_name("position").unwrap().is_null(0));
+        assert!(image.column_by_name("size").unwrap().is_null(0));
+    }
+
+    #[tokio::test]
+    async fn utf8_view_string_coerces_to_uri_child() {
+        let batch = batch_with_image(
+            Field::new("image", DataType::Utf8View, true),
+            Arc::new(StringViewArray::from(vec![Some("s3://bucket/view-key")])),
+        );
+        let coerced = coerce(batch, &blob_table_schema()).await;
+        let image = image_struct(&coerced);
+        let uri: &StringArray = image
+            .column_by_name("uri")
+            .unwrap()
+            .as_any()
+            .downcast_ref()
+            .unwrap();
+        assert_eq!(uri.value(0), "s3://bucket/view-key");
+        assert!(image.column_by_name("data").unwrap().is_null(0));
+    }
+
    #[tokio::test]
    async fn blob_metadata_survives_cast_of_sibling_column() {
        let batch = RecordBatch::try_new(
@@ -32,6 +32,10 @@ struct DatasetState {
    /// `Some(version)` = pinned to a specific version (time travel),
    /// `None` = tracking latest.
    pinned_version: Option<u64>,
+    /// Whether the pin is an internal query snapshot rather than user-visible
+    /// time travel. Query snapshots remain read-only but preserve MemWAL read
+    /// semantics.
+    query_snapshot: bool,
 }

 #[derive(Debug, Clone)]
@@ -70,6 +74,7 @@ impl DatasetConsistencyWrapper {
            state: Arc::new(Mutex::new(DatasetState {
                dataset,
                pinned_version: None,
+                query_snapshot: false,
            })),
            consistency,
            shard_writer: Arc::new(ShardWriterCache::default()),
@@ -93,6 +98,36 @@ impl DatasetConsistencyWrapper {
        wrapper
    }

+    /// Create an independent read-only wrapper pinned to the current dataset
+    /// while retaining this wrapper's live MemWAL read context.
+    pub async fn new_query_snapshot(&self) -> Result<Self> {
+        // Apply the configured consistency policy before taking the snapshot.
+        // The returned dataset is intentionally discarded: a checkout may race
+        // after this await, so the dataset and its pin provenance must instead
+        // be cloned together from one authoritative state sample below.
+        self.get().await?;
+
+        let (dataset, query_snapshot) = {
+            let state = self.state.lock()?;
+            // Preserve user time travel so the MemWAL safety guard still sees
+            // it. Latest and already-internal snapshots remain internal pins.
+            (
+                state.dataset.clone(),
+                state.query_snapshot || state.pinned_version.is_none(),
+            )
+        };
+        let version = dataset.version().version;
+        Ok(Self {
+            state: Arc::new(Mutex::new(DatasetState {
+                dataset,
+                pinned_version: Some(version),
+                query_snapshot,
+            })),
+            consistency: ConsistencyMode::Lazy,
+            shard_writer: self.shard_writer.clone(),
+        })
+    }
+
    /// The MemWAL `ShardWriter` cache co-located with this dataset.
    pub(crate) fn shard_writer(&self) -> &Arc<ShardWriterCache> {
        &self.shard_writer
@@ -169,6 +204,7 @@ impl DatasetConsistencyWrapper {
        let mut state = self.state.lock()?;
        state.dataset = Arc::new(new_dataset);
        state.pinned_version = None;
+        state.query_snapshot = false;
        drop(state);
        if let ConsistencyMode::Eventual(bg_cache) = &self.consistency {
            bg_cache.invalidate();
@@ -202,10 +238,10 @@ impl DatasetConsistencyWrapper {

    /// Returns the version, if in time travel mode, or None otherwise.
    pub fn time_travel_version(&self) -> Option<u64> {
-        self.state
-            .lock()
-            .unwrap_or_else(|e| e.into_inner())
-            .pinned_version
+        let state = self.state.lock().unwrap_or_else(|e| e.into_inner());
+        (!state.query_snapshot)
+            .then_some(state.pinned_version)
+            .flatten()
    }

    /// Convert into a wrapper in latest version mode.
@@ -225,6 +261,7 @@ impl DatasetConsistencyWrapper {
        if state.pinned_version.is_some() {
            state.dataset = Arc::new(new_dataset);
            state.pinned_version = None;
+            state.query_snapshot = false;
        }
        drop(state);
        if let ConsistencyMode::Eventual(bg_cache) = &self.consistency {
@@ -260,6 +297,7 @@ impl DatasetConsistencyWrapper {
        let mut state = self.state.lock()?;
        state.dataset = Arc::new(new_dataset);
        state.pinned_version = Some(version_value);
+        state.query_snapshot = false;
        Ok(())
    }

@@ -461,6 +499,29 @@ mod tests {
        assert_eq!(wrapper.time_travel_version(), Some(1));
    }

+    #[tokio::test]
+    async fn test_query_snapshot_samples_dataset_and_pin_together() {
+        let dir = tempfile::tempdir().unwrap();
+        let uri = dir.path().to_str().unwrap();
+        let ds = create_test_dataset(uri).await;
+
+        let wrapper = DatasetConsistencyWrapper::new_latest(ds, None);
+        wrapper.as_time_travel(1u64).await.unwrap();
+        let stale_time_travel_dataset = wrapper.get().await.unwrap();
+
+        append_to_dataset(uri).await;
+        wrapper.as_latest().await.unwrap();
+
+        let snapshot = wrapper.new_query_snapshot().await.unwrap();
+        let snapshot_dataset = snapshot.get().await.unwrap();
+        assert_eq!(snapshot_dataset.version().version, 2);
+        assert_ne!(
+            snapshot_dataset.version().version,
+            stale_time_travel_dataset.version().version
+        );
+        assert_eq!(snapshot.time_travel_version(), None);
+    }
+
    #[tokio::test]
    async fn test_as_latest_from_time_travel() {
        let dir = tempfile::tempdir().unwrap();
@@ -31,8 +31,9 @@ pub(crate) async fn execute_delete(
    table.dataset.ensure_mutable()?;
    match predicate {
        Predicate::String(s) => {
+            let predicate = crate::expr::canonicalize_sql_predicate(s)?;
            let mut dataset = (*table.dataset.get().await?).clone();
-            let delete_result = dataset.delete(s).boxed().await?;
+            let delete_result = dataset.delete(&predicate).boxed().await?;
            let num_deleted_rows = delete_result.num_deleted_rows;
            let version = dataset.version().version;
            table.dataset.update(dataset);
@@ -220,9 +220,32 @@ impl MergeInsertBuilder {
    ///
    /// Returns version and statistics about the merge operation including the number of rows
    /// inserted, updated, and deleted.
-    pub async fn execute(self, new_data: Box<dyn RecordBatchReader + Send>) -> Result<MergeResult> {
+    pub async fn execute(
+        mut self,
+        new_data: Box<dyn RecordBatchReader + Send>,
+    ) -> Result<MergeResult> {
+        self.canonicalize_filters()?;
        self.table.clone().merge_insert(self, new_data).await
    }
+
+    pub(crate) fn canonicalize_filters(&mut self) -> Result<()> {
+        self.when_matched_update_all_filt =
+            canonicalize_merge_filter(self.when_matched_update_all_filt.take())?;
+        self.when_not_matched_by_source_delete_filt =
+            canonicalize_merge_filter(self.when_not_matched_by_source_delete_filt.take())?;
+        Ok(())
+    }
+}
+
+fn canonicalize_merge_filter(filter: Option<MergeFilter>) -> Result<Option<MergeFilter>> {
+    filter
+        .map(|filter| match filter {
+            MergeFilter::Sql(predicate) => {
+                crate::expr::canonicalize_sql_predicate(&predicate).map(MergeFilter::Sql)
+            }
+            filter @ MergeFilter::Expr(_) => Ok(filter),
+        })
+        .transpose()
 }

 /// Internal implementation of the merge insert logic
@@ -230,9 +253,10 @@ impl MergeInsertBuilder {
 /// This logic was moved from NativeTable::merge_insert to keep table.rs clean.
 pub(crate) async fn execute_merge_insert(
    table: &NativeTable,
-    params: MergeInsertBuilder,
+    mut params: MergeInsertBuilder,
    new_data: Box<dyn RecordBatchReader + Send>,
 ) -> Result<MergeResult> {
+    params.canonicalize_filters()?;
    super::computed_columns::ensure_no_function_bindings_for_mutation(
        table.schema().await?.as_ref(),
        "merge_insert",
@@ -1056,6 +1080,44 @@ mod lsm_tests {
        );
    }

+    #[tokio::test]
+    async fn query_snapshot_preserves_lsm_read_semantics() {
+        let dir = tempdir().unwrap();
+        let table = id_value_table(&dir).await;
+        table
+            .set_lsm_write_spec(LsmWriteSpec::unsharded())
+            .await
+            .unwrap();
+        lsm_upsert(&table, vec![4, 5]).await;
+
+        let snapshot = table.query_snapshot().await.unwrap();
+        let rows = collect_id_value(snapshot.query().execute().await.unwrap()).await;
+        assert_eq!(
+            rows.iter().map(|(id, _)| *id).collect::<Vec<_>>(),
+            vec![1, 2, 3, 4, 5]
+        );
+    }
+
+    #[tokio::test]
+    async fn query_snapshot_preserves_time_travel_lsm_guard() {
+        let dir = tempdir().unwrap();
+        let table = id_value_table(&dir).await;
+        table
+            .set_lsm_write_spec(LsmWriteSpec::unsharded())
+            .await
+            .unwrap();
+        lsm_upsert(&table, vec![4]).await;
+
+        let version = table.version().await.unwrap();
+        table.checkout(version).await.unwrap();
+        let direct_error = table.query().execute().await.err().unwrap();
+        assert!(matches!(direct_error, Error::NotSupported { .. }));
+
+        let snapshot = table.query_snapshot().await.unwrap();
+        let snapshot_error = snapshot.query().execute().await.err().unwrap();
+        assert!(matches!(snapshot_error, Error::NotSupported { .. }));
+    }
+
    #[tokio::test]
    async fn lsm_read_dedup_newest_wins() {
        let dir = tempdir().unwrap();
@@ -17,11 +17,11 @@ use arrow::array::{AsArray, FixedSizeListBuilder, Float32Builder};
 use arrow::datatypes::{Float32Type, UInt8Type};
 use arrow_array::Array;
 use arrow_schema::{DataType, Schema};
+use datafusion_common::{Column, DataFusionError, SchemaError};
 use datafusion_physical_plan::ExecutionPlan;
 use datafusion_physical_plan::projection::ProjectionExec;
 use datafusion_physical_plan::repartition::RepartitionExec;
 use datafusion_physical_plan::union::UnionExec;
-use futures::future::try_join_all;
 use lance::dataset::mem_wal::DatasetMemWalExt;
 use lance::dataset::scanner::DatasetRecordBatchStream;
 use lance::dataset::scanner::Scanner;
@@ -45,6 +45,22 @@ impl AnyQuery {
            Self::VectorQuery(query) => &query.base,
        }
    }
+
+    fn base_mut(&mut self) -> &mut QueryRequest {
+        match self {
+            Self::Query(query) => query,
+            Self::VectorQuery(query) => &mut query.base,
+        }
+    }
+
+    /// Canonicalize any raw SQL filter immediately before backend dispatch.
+    pub(crate) fn canonicalized(&self) -> Result<Self> {
+        let mut query = self.clone();
+        if let Some(QueryFilter::Sql(predicate)) = &mut query.base_mut().filter {
+            *predicate = crate::expr::canonicalize_sql_predicate(predicate)?;
+        }
+        Ok(query)
+    }
 }

 //Decide between namespace or local
@@ -53,15 +69,16 @@ pub async fn execute_query(
    query: &AnyQuery,
    options: QueryExecutionOptions,
 ) -> Result<DatasetRecordBatchStream> {
+    let query = query.canonicalized()?;
    // QueryTable pushdown runs the query server-side, but only on the main
    // branch: the namespace request carries no branch yet, so a branch handle
    // must fall through to local execution.
-    if can_execute_namespace_query(table, query).await?
+    if can_execute_namespace_query(table, &query).await?
        && let Some(ref namespace_client) = table.namespace_client
    {
-        return execute_namespace_query(table, namespace_client.clone(), query, options).await;
+        return execute_namespace_query(table, namespace_client.clone(), &query, options).await;
    }
-    execute_generic_query(table, query, options).await
+    execute_generic_query(table, &query, options).await
 }

 async fn can_execute_namespace_query(table: &NativeTable, query: &AnyQuery) -> Result<bool> {
@@ -136,9 +153,10 @@ pub async fn create_plan(
    query: &AnyQuery,
    options: QueryExecutionOptions,
 ) -> Result<Arc<dyn ExecutionPlan>> {
+    let query = query.canonicalized()?;
    let query = match query {
-        AnyQuery::VectorQuery(query) => query.clone(),
-        AnyQuery::Query(query) => VectorQueryRequest::from_plain_query(query.clone()),
+        AnyQuery::VectorQuery(query) => query,
+        AnyQuery::Query(query) => VectorQueryRequest::from_plain_query(query),
    };
    query.base.check_filter()?;

@@ -170,26 +188,48 @@ pub async fn create_plan(
    let mut column = query.column.clone();

    let mut query_vector = query.query_vector.first().cloned();
+    let mut is_batch_query = false;
    if query.query_vector.len() > 1 {
        if column.is_none() {
            // Infer a vector column with the same dimension of the query vector.
-            let arrow_schema = Schema::from(ds_ref.schema());
+            let arrow_schema = Schema::from(schema);
            column = Some(default_vector_column(
                &arrow_schema,
                Some(query.query_vector[0].len() as i32),
            )?);
        }
        let vector_field = schema.field(column.as_ref().unwrap()).unwrap();
-        if let DataType::List(_) = vector_field.data_type() {
-            // Multivector handling: concatenate into FixedSizeList<FixedSizeList<_>>
+        let (_, element_type) =
+            lance::index::vector::utils::get_vector_type(schema, column.as_ref().unwrap())?;
+        let is_binary = matches!(element_type, DataType::UInt8);
+        if matches!(vector_field.data_type(), DataType::List(_))
+            || (query.base.offset.unwrap_or(0) == 0 && !is_binary)
+        {
+            // Lance distinguishes these cases from the vector column type: a
+            // list-like query against a List column is one multivector query,
+            // while the same query against a FixedSizeList column is a batch of
+            // independent queries. The batch path shares a single flat scan and
+            // bounds retained candidate data instead of running one scan per
+            // query vector.
            let vectors = query
                .query_vector
                .iter()
                .map(|arr| arr.as_ref())
                .collect::<Vec<_>>();
            let dim = vectors[0].len();
+            if let Some((query_index, actual_dim)) = vectors
+                .iter()
+                .enumerate()
+                .find_map(|(index, vector)| (vector.len() != dim).then_some((index, vector.len())))
+            {
+                return Err(Error::InvalidInput {
+                    message: format!(
+                        "query vector at index {query_index} has dimension {actual_dim}, expected {dim}"
+                    ),
+                });
+            }
            let mut fsl_builder = FixedSizeListBuilder::with_capacity(
-                Float32Builder::with_capacity(dim),
+                Float32Builder::with_capacity(dim * vectors.len()),
                dim as i32,
                vectors.len(),
            );
@@ -200,8 +240,12 @@ pub async fn create_plan(
                fsl_builder.append(true);
            }
            query_vector = Some(Arc::new(fsl_builder.finish()));
+            is_batch_query = !matches!(vector_field.data_type(), DataType::List(_));
        } else {
-            // Multiple query vectors: create a plan for each and union them
+            // Lance's batch path has no per-query offset, and its binary path
+            // requires primitive UInt8 queries rather than a fixed-size list.
+            // Keep the prior plan shape for these cases so offsets are applied
+            // per query and binary query vectors retain their primitive shape.
            let query_vecs = query.query_vector.clone();
            let plan_futures = query_vecs
                .into_iter()
@@ -214,7 +258,7 @@ pub async fn create_plan(
                    }
                })
                .collect::<Vec<_>>();
-            let plans = try_join_all(plan_futures).await?;
+            let plans = futures::future::try_join_all(plan_futures).await?;
            return create_multi_vector_plan(plans);
        }
    }
@@ -225,7 +269,7 @@ pub async fn create_plan(
        let column = if let Some(col) = column {
            col
        } else {
-            let arrow_schema = Schema::from(ds_ref.schema());
+            let arrow_schema = Schema::from(schema);
            default_vector_column(&arrow_schema, Some(query_vector.len() as i32))?
        };

@@ -251,10 +295,14 @@ pub async fn create_plan(
        }
    }

-    scanner.limit(
-        query.base.limit.map(|limit| limit as i64),
-        query.base.offset.map(|offset| offset as i64),
-    )?;
+    // For a batch query, `nearest` already applies k to each query vector.
+    // Adding Scanner's global limit would truncate the combined result to k rows.
+    if !is_batch_query {
+        scanner.limit(
+            query.base.limit.map(|limit| limit as i64),
+            query.base.offset.map(|offset| offset as i64),
+        )?;
+    }

    if let Some(ef) = query.ef {
        scanner.ef(ef);
@@ -327,7 +375,97 @@ pub async fn create_plan(
        scanner.order_by(Some(order_by.clone()))?;
    }

-    Ok(scanner.create_plan().await?)
+    scanner
+        .create_plan()
+        .await
+        .map_err(|error| enrich_lance_field_not_found(error, schema))
+}
+
+/// Replace DataFusion's top-level field candidates with qualified leaf paths.
+///
+/// DataFusion resolves nested fields but its `FieldNotFound` error only lists the
+/// top-level Arrow fields. This makes a missing leaf look unavailable even when it
+/// exists below a struct. Keep every other Lance/DataFusion error unchanged and
+/// enrich only this one schema error at the LanceDB query boundary.
+fn enrich_lance_field_not_found(
+    error: lance::Error,
+    schema: &lance_core::datatypes::Schema,
+) -> Error {
+    let Some(field) = find_missing_field(&error) else {
+        return error.into();
+    };
+    field_not_found_error(field, &Schema::from(schema))
+}
+
+fn field_not_found_diagnostic(
+    error: &(dyn std::error::Error + 'static),
+    schema: &Schema,
+) -> Option<Error> {
+    let field = find_missing_field(error)?;
+    Some(field_not_found_error(field, schema))
+}
+
+fn field_not_found_error(field: &Column, schema: &Schema) -> Error {
+    let valid_fields = leaf_field_paths(schema);
+    let mut message = format!("Schema error: No field named {}", field.quoted_flat_name());
+    if !valid_fields.is_empty() {
+        message.push_str(". Valid fields are ");
+        message.push_str(&valid_fields.join(", "));
+    }
+    message.push('.');
+
+    Error::InvalidInput { message }
+}
+
+fn find_missing_field<'a>(error: &'a (dyn std::error::Error + 'static)) -> Option<&'a Column> {
+    if let Some(DataFusionError::SchemaError(schema_error, _)) =
+        error.downcast_ref::<DataFusionError>()
+        && let SchemaError::FieldNotFound { field, .. } = schema_error.as_ref()
+    {
+        return Some(field);
+    }
+
+    error.source().and_then(find_missing_field)
+}
+
+fn leaf_field_paths(schema: &Schema) -> Vec<String> {
+    fn format_segment(segment: &str) -> String {
+        // Quote every segment instead of maintaining a SQL keyword list. Bare
+        // lowercase names such as `true` can be parsed as expressions rather
+        // than identifiers, while backticks preserve all field names in both
+        // local SQL parsers.
+        format!("`{}`", segment.replace('`', "``"))
+    }
+
+    fn visit(fields: &arrow_schema::Fields, path: &mut Vec<String>, paths: &mut Vec<String>) {
+        for field in fields {
+            // Neither local planner can address an empty field-path segment,
+            // even when it is backtick-quoted. Do not advertise leaves beneath
+            // such a segment as valid filter fields.
+            if field.name().is_empty() {
+                continue;
+            }
+            path.push(field.name().clone());
+            match field.data_type() {
+                DataType::Struct(children) if !children.is_empty() => {
+                    visit(children, path, paths);
+                }
+                _ => {
+                    paths.push(
+                        path.iter()
+                            .map(|segment| format_segment(segment))
+                            .collect::<Vec<_>>()
+                            .join("."),
+                    );
+                }
+            }
+            path.pop();
+        }
+    }
+
+    let mut paths = Vec::new();
+    visit(schema.fields(), &mut Vec::new(), &mut paths);
+    paths
 }

 //Helper functions below
@@ -687,7 +825,10 @@ async fn parse_arrow_ipc_response(bytes: bytes::Bytes) -> Result<DatasetRecordBa
 #[cfg(test)]
 #[allow(deprecated)]
 mod tests {
-    use arrow_array::{ArrayRef, FixedSizeListArray, Float32Array};
+    use arrow_array::{
+        ArrayRef, FixedSizeListArray, Float32Array, Int32Array, RecordBatch, StringArray,
+        StructArray,
+    };
    use futures::TryStreamExt;
    use lance_arrow::FixedSizeListArrayExt;
    use std::sync::{
@@ -696,7 +837,8 @@ mod tests {
    };

    use super::*;
-    use crate::query::{QueryExecutionOptions, QueryRequest};
+    use crate::query::{ExecutableQuery, QueryBase, QueryExecutionOptions, QueryRequest};
+    use crate::table::BaseTable;

    fn fixed_size_list_array(values: Vec<f32>, dimension: i32) -> FixedSizeListArray {
        FixedSizeListArray::try_new_from_values(Float32Array::from(values), dimension).unwrap()
@@ -836,7 +978,6 @@ mod tests {
    async fn test_execute_query_local_routing() {
        use crate::connect;
        use crate::table::query::execute_query;
-        use arrow_array::{Int32Array, RecordBatch};
        use arrow_schema::{DataType, Field, Schema};

        let conn = connect("memory://").execute().await.unwrap();
@@ -876,6 +1017,164 @@ mod tests {
        assert_eq!(count, 2); // 4 and 5
    }

+    #[tokio::test]
+    async fn test_missing_filter_field_lists_nested_fields_in_local_planners() {
+        use crate::connect;
+        use arrow_schema::{DataType, Field, Schema};
+
+        let conn = connect("memory://").execute().await.unwrap();
+        let metadata = Arc::new(StructArray::from(vec![
+            (
+                Arc::new(Field::new("year", DataType::Int32, false)),
+                Arc::new(Int32Array::from(vec![2024])) as ArrayRef,
+            ),
+            (
+                Arc::new(Field::new("genre", DataType::Utf8, false)),
+                Arc::new(StringArray::from(vec!["fiction"])) as ArrayRef,
+            ),
+            (
+                Arc::new(Field::new("Title", DataType::Int32, false)),
+                Arc::new(Int32Array::from(vec![7])) as ArrayRef,
+            ),
+            (
+                Arc::new(Field::new("true", DataType::Int32, false)),
+                Arc::new(Int32Array::from(vec![8])) as ArrayRef,
+            ),
+            (
+                Arc::new(Field::new("", DataType::Int32, false)),
+                Arc::new(Int32Array::from(vec![10])) as ArrayRef,
+            ),
+        ]));
+        let vector = Arc::new(fixed_size_list_array(vec![0.0, 1.0], 2));
+        let schema = Arc::new(Schema::new(vec![
+            Field::new("id", DataType::Int32, false),
+            Field::new("vector", vector.data_type().clone(), false),
+            Field::new("content", DataType::Utf8, false),
+            Field::new("metadata", metadata.data_type().clone(), false),
+        ]));
+        let batch = RecordBatch::try_new(
+            schema,
+            vec![
+                Arc::new(Int32Array::from(vec![1])),
+                vector,
+                Arc::new(StringArray::from(vec!["example"])),
+                metadata,
+            ],
+        )
+        .unwrap();
+        let table = conn
+            .create_table("nested_error", batch)
+            .execute()
+            .await
+            .unwrap();
+
+        let error = table
+            .query()
+            .only_if("year = 2024")
+            .execute()
+            .await
+            .err()
+            .expect("query should reject the unqualified nested field");
+        let case_sensitive_path = "`metadata`.`Title`";
+        let keyword_path = "`metadata`.`true`";
+        let expected = format!(
+            "No field named year. Valid fields are `id`, `vector`, `content`, `metadata`.`year`, `metadata`.`genre`, {case_sensitive_path}, {keyword_path}."
+        );
+
+        assert!(
+            error.to_string().contains(&expected),
+            "unexpected error: {error}"
+        );
+        for (path, value) in [(case_sensitive_path, 7), (keyword_path, 8)] {
+            table
+                .query()
+                .only_if(format!("{path} = {value}"))
+                .execute()
+                .await
+                .expect("the path advertised by the diagnostic should be reusable");
+        }
+
+        table.set_unenforced_primary_key(["id"]).await.unwrap();
+        table
+            .set_lsm_write_spec(crate::table::LsmWriteSpec::unsharded())
+            .await
+            .unwrap();
+        let lsm_error = table
+            .query()
+            .only_if("year = 2024")
+            .execute()
+            .await
+            .err()
+            .expect("LSM query should reject the unqualified nested field");
+
+        assert!(
+            lsm_error.to_string().contains(&expected),
+            "unexpected LSM error: {lsm_error}"
+        );
+        for (path, value) in [(case_sensitive_path, 7), (keyword_path, 8)] {
+            table
+                .query()
+                .only_if(format!("{path} = {value}"))
+                .execute()
+                .await
+                .expect("the path advertised by the diagnostic should be reusable in LSM queries");
+        }
+    }
+
+    #[test]
+    fn test_leaf_field_paths_preserve_arbitrary_depth() {
+        use arrow_schema::{DataType, Field, Schema};
+
+        fn nested_field(path: &[&str]) -> Field {
+            let mut segments = path.iter().rev();
+            let mut field = Field::new(
+                *segments.next().expect("path must have a leaf"),
+                DataType::Int32,
+                false,
+            );
+            for segment in segments {
+                field = Field::new(*segment, DataType::Struct(vec![field].into()), false);
+            }
+            field
+        }
+
+        let schema = Schema::new(vec![
+            nested_field(&["a", "b", "c", "d", "e"]),
+            nested_field(&["metadata", "child.with.dot"]),
+            nested_field(&["metadata", "Title"]),
+            nested_field(&["metadata", "123child"]),
+            nested_field(&["metadata", "child`tick"]),
+            nested_field(&["metadata", ""]),
+            nested_field(&["", "child"]),
+        ]);
+
+        assert_eq!(
+            leaf_field_paths(&schema),
+            vec![
+                "`a`.`b`.`c`.`d`.`e`",
+                "`metadata`.`child.with.dot`",
+                "`metadata`.`Title`",
+                "`metadata`.`123child`",
+                "`metadata`.`child``tick`",
+            ]
+        );
+
+        let source = DataFusionError::SchemaError(
+            Box::new(SchemaError::FieldNotFound {
+                field: Box::new(Column::from_name("missing")),
+                valid_fields: Vec::new(),
+            }),
+            Box::new(None),
+        );
+        let error = field_not_found_diagnostic(&source, &schema).unwrap();
+        assert!(
+            error.to_string().contains(
+                "Valid fields are `a`.`b`.`c`.`d`.`e`, `metadata`.`child.with.dot`, `metadata`.`Title`, `metadata`.`123child`, `metadata`.`child``tick`"
+            ),
+            "unexpected error: {error}"
+        );
+    }
+
    #[derive(Debug, Default)]
    struct CountingNamespaceClient {
        query_table_calls: AtomicUsize,
@@ -889,10 +1188,56 @@ mod tests {

        async fn query_table(&self, _request: NsQueryTableRequest) -> lance::Result<bytes::Bytes> {
            self.query_table_calls.fetch_add(1, Ordering::SeqCst);
-            panic!("approx_mode queries must not be pushed down to namespace query_table");
+            panic!("query must not be pushed down to namespace query_table");
        }
    }

+    #[tokio::test]
+    async fn test_execute_query_pinned_snapshot_with_namespace_pushdown_runs_locally() {
+        use crate::connect;
+        use arrow_array::{Int32Array, RecordBatch};
+        use arrow_schema::{DataType, Field, Schema};
+
+        let conn = connect("memory://").execute().await.unwrap();
+        let schema = Arc::new(Schema::new(vec![Field::new("id", DataType::Int32, false)]));
+        let batch = RecordBatch::try_new(
+            schema,
+            vec![Arc::new(Int32Array::from(vec![1, 2, 3, 4, 5]))],
+        )
+        .unwrap();
+        let table = conn
+            .create_table("test_pinned_namespace_fallback", vec![batch])
+            .execute()
+            .await
+            .unwrap();
+
+        let namespace_client = Arc::new(CountingNamespaceClient::default());
+        let mut native_table = table.as_native().unwrap().clone();
+        native_table.namespace_client = Some(namespace_client.clone());
+        native_table
+            .pushdown_operations
+            .insert(NamespaceClientPushdownOperation::QueryTable);
+
+        let snapshot = native_table.checkout_current().await.unwrap();
+        let snapshot = snapshot.as_any().downcast_ref::<NativeTable>().unwrap();
+        assert!(snapshot.dataset.time_travel_version().is_some());
+
+        let query = AnyQuery::Query(QueryRequest {
+            filter: Some(QueryFilter::Sql("id > 3".to_string())),
+            ..Default::default()
+        });
+        let stream = execute_query(snapshot, &query, QueryExecutionOptions::default())
+            .await
+            .unwrap();
+        let batches = stream.try_collect::<Vec<_>>().await.unwrap();
+
+        assert_eq!(
+            batches.iter().map(|batch| batch.num_rows()).sum::<usize>(),
+            2
+        );
+        assert_eq!(namespace_client.query_table_calls.load(Ordering::SeqCst), 0);
+    }
+
    #[tokio::test]
    async fn test_execute_query_approx_mode_with_namespace_pushdown_runs_locally() {
        use crate::connect;
@@ -1010,7 +1355,38 @@ mod tests {
    }

    #[tokio::test]
-    async fn test_create_plan_multivector_structure() {
+    async fn test_query_snapshot_disables_namespace_pushdown() {
+        use crate::connect;
+        use crate::table::BaseTable;
+        use arrow_array::{Int32Array, RecordBatch};
+        use arrow_schema::{DataType, Field, Schema};
+
+        let conn = connect("memory://").execute().await.unwrap();
+        let schema = Arc::new(Schema::new(vec![Field::new("id", DataType::Int32, false)]));
+        let batch =
+            RecordBatch::try_new(schema, vec![Arc::new(Int32Array::from(vec![1, 2, 3]))]).unwrap();
+        let table = conn
+            .create_table("test_snapshot_namespace_fallback", vec![batch])
+            .execute()
+            .await
+            .unwrap();
+        let mut native_table = table.as_native().unwrap().clone();
+        native_table.namespace_client = Some(Arc::new(CountingNamespaceClient::default()));
+        native_table
+            .pushdown_operations
+            .insert(NamespaceClientPushdownOperation::QueryTable);
+
+        let snapshot = BaseTable::query_snapshot(&native_table).await.unwrap();
+        let snapshot = snapshot.as_any().downcast_ref::<NativeTable>().unwrap();
+        assert!(
+            !can_execute_namespace_query(snapshot, &AnyQuery::Query(QueryRequest::default()),)
+                .await
+                .unwrap()
+        );
+    }
+
+    #[tokio::test]
+    async fn test_create_plan_batch_vector_uses_shared_scan() {
        use arrow_array::{Float32Array, RecordBatch};
        use arrow_schema::{DataType, Field, Schema};
        use datafusion_physical_plan::display::DisplayableExecutionPlan;
@@ -1037,11 +1413,18 @@ mod tests {
            .unwrap();
        let native_table = table.as_native().unwrap();

-        // This triggers the "create_multi_vector_plan" logic branch
+        // A batch of vectors against a fixed-size vector column should use
+        // Lance's native batch KNN path instead of independent scan plans.
        let q1 = Arc::new(Float32Array::from(vec![1.0, 2.0]));
        let q2 = Arc::new(Float32Array::from(vec![3.0, 4.0]));

        let req = VectorQueryRequest {
+            base: QueryRequest {
+                filter: Some(QueryFilter::Sql("id >= 0".to_string())),
+                limit: Some(1),
+                select: Select::Columns(vec!["id".to_string()]),
+                ..Default::default()
+            },
            column: Some("vector".to_string()),
            query_vector: vec![q1, q2],
            ..Default::default()
@@ -1058,19 +1441,17 @@ mod tests {
            .indent(true)
            .to_string();

-        // We expect a RepartitionExec wrapping a UnionExec
        assert!(
-            display.contains("RepartitionExec"),
-            "Plan should include Repartitioning"
+            display.contains("KNNVectorDistance: queries=2"),
+            "plan should use native batch KNN, got:\n{display}"
        );
        assert!(
-            display.contains("UnionExec"),
-            "Plan should include a Union of multiple searches"
+            !display.contains("UnionExec"),
+            "flat batch KNN should share one scan, got:\n{display}"
        );
-        // We expect the projection to add the 'query_index' column (logic inside multi_vector_plan)
        assert!(
            display.contains("query_index"),
-            "Plan should add query_index column"
+            "plan should add query_index column, got:\n{display}"
        );
    }

@@ -27,6 +27,8 @@ use std::sync::Arc;

 use arrow_array::Array;
 use arrow_schema::{DataType, Schema as ArrowSchema};
+use datafusion::common::{DataFusionError, ToDFSchema};
+use datafusion::prelude::SessionContext;
 use datafusion_physical_plan::expressions::Column;
 use datafusion_physical_plan::projection::ProjectionExec;
 use datafusion_physical_plan::{ExecutionPlan, PhysicalExpr};
@@ -298,7 +300,7 @@ async fn build_read_context(
    for shard_id in shard_ids {
        let manifest_store =
            ShardManifestStore::new(store.clone(), &base_path, shard_id, scan_batch_size);
-        if let Some(manifest) = manifest_store.read_latest().await? {
+        if let Some(manifest) = manifest_store.latest().await? {
            snapshots.push(snapshot_from_manifest(shard_id, &manifest, &exclude));
        }
    }
@@ -391,7 +393,21 @@ fn base_scanner(
    }
    if let Some(filter) = &query.base.filter {
        scanner = match filter {
-            QueryFilter::Sql(sql) => scanner.filter(sql)?,
+            QueryFilter::Sql(sql) => {
+                // Parse here instead of inside `LsmScanner::filter` so the typed
+                // DataFusion `FieldNotFound` error is still available for the
+                // same nested-field enrichment used by the ordinary scanner.
+                let schema = ArrowSchema::from(dataset.schema());
+                let df_schema = schema.clone().to_dfschema().map_err(|error| {
+                    enrich_filter_error(error, &schema, "Failed to create DFSchema")
+                })?;
+                let expr = SessionContext::new()
+                    .parse_sql_expr(sql, &df_schema)
+                    .map_err(|error| {
+                        enrich_filter_error(error, &schema, "Failed to parse filter expression")
+                    })?;
+                scanner.filter_expr(expr)
+            }
            QueryFilter::Datafusion(expr) => scanner.filter_expr(expr.clone()),
            QueryFilter::Substrait(_) => {
                return Err(Error::NotSupported {
@@ -403,6 +419,12 @@ fn base_scanner(
    Ok(scanner)
 }

+fn enrich_filter_error(error: DataFusionError, schema: &ArrowSchema, context: &str) -> Error {
+    super::field_not_found_diagnostic(&error, schema).unwrap_or_else(|| Error::InvalidInput {
+        message: format!("{context}: {error}"),
+    })
+}
+
 /// Plain scan: filter / projection / limit over base ∪ SSTables ∪ in-memory.
 /// The plain scan applies limit and offset inside the planner.
 async fn plain_plan(
@@ -55,7 +55,9 @@ pub struct DropColumnsResult {
 pub struct FieldMetadataUpdate {
    /// Dot-separated path to the field (e.g. `"embedding"` or `"address.zip"`).
    pub path: String,
-    /// Keys to set (`Some`) or delete (`None`).
+    /// Keys to set (`Some`) or delete (`None`). See
+    /// [`Table::update_field_metadata`](crate::Table::update_field_metadata) for
+    /// the conventional `lancedb:*` keys.
    pub metadata: HashMap<String, Option<String>>,
    /// If `true`, replace the field's entire metadata map instead of merging.
    pub replace: bool,
@@ -62,22 +62,33 @@ impl UpdateBuilder {
    }

    /// Executes the update operation.
-    pub async fn execute(self) -> Result<UpdateResult> {
+    pub async fn execute(mut self) -> Result<UpdateResult> {
        if self.columns.is_empty() {
            Err(Error::InvalidInput {
                message: "at least one column must be specified in an update operation".to_string(),
            })
        } else {
+            self.canonicalize_filter()?;
            self.parent.clone().update(self).await
        }
    }
+
+    pub(crate) fn canonicalize_filter(&mut self) -> Result<()> {
+        self.filter = self
+            .filter
+            .take()
+            .map(|predicate| crate::expr::canonicalize_sql_predicate(&predicate))
+            .transpose()?;
+        Ok(())
+    }
 }

 /// Internal implementation of the update logic
 pub(crate) async fn execute_update(
    table: &NativeTable,
-    update: UpdateBuilder,
+    mut update: UpdateBuilder,
 ) -> Result<UpdateResult> {
+    update.canonicalize_filter()?;
    table.dataset.ensure_mutable()?;

    // 1. Snapshot the current dataset
@@ -225,6 +225,159 @@ pub(crate) fn resolve_arrow_field_path(schema: &Schema, column: &str) -> Result<
    Ok((canonical_path, Field::from(*field)))
 }

+pub(crate) struct ResolvedFtsField {
+    pub canonical_path: String,
+    pub field: Field,
+    pub list_depth: usize,
+}
+
+/// Canonicalize a public FTS field path while keeping Arrow list item names hidden.
+pub(crate) fn resolve_lance_fts_field_path(
+    schema: &lance_core::datatypes::Schema,
+    column: &str,
+) -> Result<ResolvedFtsField> {
+    let names =
+        lance_core::datatypes::parse_field_path(column).map_err(|e| Error::InvalidInput {
+            message: format!("Invalid field path `{}`: {}", column, e),
+        })?;
+    let (root_name, remaining_names) = names.split_first().ok_or_else(|| Error::InvalidInput {
+        message: "FTS field path cannot be empty".to_string(),
+    })?;
+    let mut field = schema
+        .fields
+        .iter()
+        .find(|field| field.name == *root_name)
+        .or_else(|| {
+            schema
+                .fields
+                .iter()
+                .find(|field| field.name.eq_ignore_ascii_case(root_name))
+        })
+        .ok_or_else(|| fts_field_not_found(schema, column))?;
+    let mut canonical_names = vec![field.name.clone()];
+    let mut list_depth = 0;
+
+    for name in remaining_names {
+        while matches!(
+            field.data_type(),
+            DataType::List(_) | DataType::LargeList(_)
+        ) {
+            list_depth += 1;
+            field = field.children.first().ok_or_else(|| Error::Schema {
+                message: format!(
+                    "FTS field path `{}` has a list without an item field",
+                    column
+                ),
+            })?;
+        }
+        if !matches!(field.data_type(), DataType::Struct(_)) {
+            return Err(fts_field_not_found(schema, column));
+        }
+        field = field
+            .children
+            .iter()
+            .find(|field| field.name == *name)
+            .or_else(|| {
+                field
+                    .children
+                    .iter()
+                    .find(|field| field.name.eq_ignore_ascii_case(name))
+            })
+            .ok_or_else(|| fts_field_not_found(schema, column))?;
+        canonical_names.push(field.name.clone());
+    }
+
+    let mut terminal = field;
+    while matches!(
+        terminal.data_type(),
+        DataType::List(_) | DataType::LargeList(_)
+    ) {
+        list_depth += 1;
+        terminal = terminal.children.first().ok_or_else(|| Error::Schema {
+            message: format!(
+                "FTS field path `{}` has a list without an item field",
+                column
+            ),
+        })?;
+    }
+
+    let canonical_path = lance_core::datatypes::format_field_path(
+        &canonical_names
+            .iter()
+            .map(String::as_str)
+            .collect::<Vec<_>>(),
+    );
+    Ok(ResolvedFtsField {
+        canonical_path,
+        field: Field::from(field),
+        list_depth,
+    })
+}
+
+fn fts_field_not_found(schema: &lance_core::datatypes::Schema, column: &str) -> Error {
+    Error::Schema {
+        message: format!(
+            "Field path `{}` not found in schema. Available field paths: {}",
+            column,
+            schema.field_paths().join(", ")
+        ),
+    }
+}
+
+fn find_public_fts_field_path_by_id(
+    field: &lance_core::datatypes::Field,
+    field_id: i32,
+    path: &mut Vec<String>,
+) -> bool {
+    if field.id == field_id {
+        return true;
+    }
+    match field.data_type() {
+        DataType::List(_) | DataType::LargeList(_) => field
+            .children
+            .first()
+            .is_some_and(|child| find_public_fts_field_path_by_id(child, field_id, path)),
+        DataType::Struct(_) => field.children.iter().any(|child| {
+            path.push(child.name.clone());
+            let found = find_public_fts_field_path_by_id(child, field_id, path);
+            if !found {
+                path.pop();
+            }
+            found
+        }),
+        _ => false,
+    }
+}
+
+pub(crate) fn public_fts_field_path_by_id(
+    schema: &lance_core::datatypes::Schema,
+    field_id: i32,
+) -> Result<String> {
+    for root in &schema.fields {
+        let mut path = vec![root.name.clone()];
+        if find_public_fts_field_path_by_id(root, field_id, &mut path) {
+            return Ok(lance_core::datatypes::format_field_path(
+                &path.iter().map(String::as_str).collect::<Vec<_>>(),
+            ));
+        }
+    }
+    Err(Error::Schema {
+        message: format!("Field id `{}` not found in schema", field_id),
+    })
+}
+
+pub(crate) fn resolve_arrow_fts_field_path(
+    schema: &Schema,
+    column: &str,
+) -> Result<(String, Field)> {
+    let lance_schema =
+        lance_core::datatypes::Schema::try_from(schema).map_err(|e| Error::Schema {
+            message: format!("Invalid schema: {}", e),
+        })?;
+    let resolved = resolve_lance_fts_field_path(&lance_schema, column)?;
+    Ok((resolved.canonical_path, resolved.field))
+}
+
 pub fn supported_btree_data_type(dtype: &DataType) -> bool {
    dtype.is_integer()
        || dtype.is_floating()
@@ -480,6 +633,36 @@ mod tests {

    use super::*;

+    #[test]
+    fn test_public_fts_field_path_prefers_exact_case() {
+        let text_list = || {
+            DataType::List(Arc::new(Field::new(
+                "item",
+                DataType::Struct(vec![Field::new("content", DataType::Utf8, true)].into()),
+                true,
+            )))
+        };
+        let schema = Schema::new(vec![
+            Field::new("Docs", text_list(), true),
+            Field::new("docs", text_list(), true),
+        ]);
+
+        let (path, _) = resolve_arrow_fts_field_path(&schema, "docs.content").unwrap();
+        assert_eq!(path, "docs.content");
+
+        let lance_schema = lance_core::datatypes::Schema::try_from(&schema).unwrap();
+        let field_id = lance_schema
+            .resolve_case_insensitive("docs.item.content")
+            .unwrap()
+            .last()
+            .unwrap()
+            .id;
+        assert_eq!(
+            public_fts_field_path_by_id(&lance_schema, field_id).unwrap(),
+            "docs.content"
+        );
+    }
+
    #[test]
    fn test_guess_default_column() {
        let schema_no_vector = Schema::new(vec![
@@ -5,12 +5,14 @@ use std::sync::Arc;

 use arrow_array::{
    Array, ArrayRef, BinaryArray, Int64Array, LargeBinaryArray, RecordBatch, StringArray,
-    StructArray, UInt64Array,
+    StructArray, UInt64Array, new_null_array,
 };
 use arrow_schema::{DataType, Field, Fields, Schema};
 use futures::TryStreamExt;
 use lance::Dataset;
+use lance::dataset::WriteParams;
 use lance_file::version::{ConcreteFileVersion, LanceFileVersion};
+use lance_table::format::BasePath;
 use lancedb::{
    Connection, Error, Result, Table,
    blob::{BlobRangeRequest, blob},
@@ -19,7 +21,7 @@ use lancedb::{
        ListingDatabaseOptions, NewTableConfig, OPT_NEW_TABLE_ENABLE_STABLE_ROW_IDS,
    },
    query::{ExecutableQuery, QueryBase},
-    table::{AddDataMode, CompactionOptions, OptimizeAction, OptimizeStats},
+    table::{AddDataMode, CompactionOptions, OptimizeAction, OptimizeStats, WriteOptions},
 };
 use tempfile::tempdir;

@@ -261,11 +263,11 @@ async fn add_rejects_uncoercible_blob_input() -> Result<()> {
    let batch = RecordBatch::try_new(
        Arc::new(Schema::new(vec![
            Field::new("id", DataType::Int64, false),
-            Field::new("image", DataType::Utf8, true),
+            Field::new("image", DataType::Int64, true),
        ])),
        vec![
            Arc::new(Int64Array::from(vec![1])),
-            Arc::new(StringArray::from(vec!["not bytes"])),
+            Arc::new(Int64Array::from(vec![42])),
        ],
    )
    .unwrap();
@@ -1332,3 +1334,223 @@ async fn optimize_preserves_blob_v2_null_and_empty_distinction() -> Result<()> {
    );
    Ok(())
 }
+
+fn uri_struct_batch(id: i64, uri: &str) -> RecordBatch {
+    let image_field = blob("image", true);
+    let DataType::Struct(child_fields) = image_field.data_type().clone() else {
+        unreachable!("blob field is a struct");
+    };
+    let children: Vec<ArrayRef> = child_fields
+        .iter()
+        .map(|field| match field.name().as_str() {
+            "uri" => Arc::new(StringArray::from(vec![Some(uri)])) as ArrayRef,
+            _ => new_null_array(field.data_type(), 1),
+        })
+        .collect();
+    let image = StructArray::new(child_fields, children, None);
+    RecordBatch::try_new(
+        Arc::new(Schema::new(vec![
+            Field::new("id", DataType::Int64, false),
+            image_field,
+        ])),
+        vec![Arc::new(Int64Array::from(vec![id])), Arc::new(image)],
+    )
+    .unwrap()
+}
+
+fn uri_string_batch(id: i64, uri: &str) -> RecordBatch {
+    RecordBatch::try_new(
+        Arc::new(Schema::new(vec![
+            Field::new("id", DataType::Int64, false),
+            Field::new("image", DataType::Utf8, true),
+        ])),
+        vec![
+            Arc::new(Int64Array::from(vec![id])),
+            Arc::new(StringArray::from(vec![Some(uri)])),
+        ],
+    )
+    .unwrap()
+}
+
+fn write_payload_file_uri(dir: &std::path::Path, name: &str, payload: &[u8]) -> String {
+    let path = dir.join(name);
+    std::fs::write(&path, payload).unwrap();
+    url::Url::from_file_path(&path).unwrap().to_string()
+}
+
+#[tokio::test]
+async fn external_uri_struct_round_trips_with_flag() -> Result<()> {
+    let tmp = tempdir().unwrap();
+    let db = connect(tmp.path().join("db").to_str().unwrap())
+        .execute()
+        .await?;
+    let payload: &[u8] = b"external-struct-payload";
+    let uri = write_payload_file_uri(tmp.path(), "payload.bin", payload);
+    let table = db
+        .create_empty_table("t", blob_table_schema())
+        .execute()
+        .await?;
+
+    table
+        .add(uri_struct_batch(1, &uri))
+        .allow_external_blob_outside_bases(true)
+        .execute()
+        .await?;
+
+    let ids = collect_row_ids(&table).await?;
+    let bytes = table.fetch_blobs("image", &ids).await?;
+    assert_eq!(bytes.value(0), payload);
+    Ok(())
+}
+
+#[tokio::test]
+async fn external_uri_add_requires_opt_in() -> Result<()> {
+    let tmp = tempdir().unwrap();
+    let db = connect(tmp.path().join("db").to_str().unwrap())
+        .execute()
+        .await?;
+    let uri = write_payload_file_uri(tmp.path(), "payload.bin", b"unreachable");
+    let table = db
+        .create_empty_table("t", blob_table_schema())
+        .execute()
+        .await?;
+
+    let err = table
+        .add(uri_struct_batch(1, &uri))
+        .execute()
+        .await
+        .unwrap_err();
+
+    assert!(
+        err.to_string()
+            .contains("allow_external_blob_outside_bases"),
+        "got: {err}"
+    );
+    assert_eq!(table.count_rows(None).await?, 0);
+    Ok(())
+}
+
+#[tokio::test]
+async fn string_uri_input_round_trips_as_external_reference() -> Result<()> {
+    let tmp = tempdir().unwrap();
+    let db = connect(tmp.path().join("db").to_str().unwrap())
+        .execute()
+        .await?;
+    let payload: &[u8] = b"external-string-payload";
+    let uri = write_payload_file_uri(tmp.path(), "payload.bin", payload);
+    let table = db
+        .create_empty_table("t", blob_table_schema())
+        .execute()
+        .await?;
+
+    table
+        .add(uri_string_batch(1, &uri))
+        .allow_external_blob_outside_bases(true)
+        .execute()
+        .await?;
+
+    let ids = collect_row_ids(&table).await?;
+    let bytes = table.fetch_blobs("image", &ids).await?;
+    assert_eq!(bytes.value(0), payload);
+
+    let files = table.fetch_blob_files("image", &ids).await?;
+    let file = files[0].as_ref().expect("missing blob file");
+    assert_eq!(file.uri(), Some(uri.as_str()));
+    Ok(())
+}
+
+#[tokio::test]
+async fn string_uri_inside_registered_base_does_not_need_the_flag() -> Result<()> {
+    let tmp = tempdir().unwrap();
+    let db_path = tmp.path().join("db");
+    let external_base = tmp.path().join("external_base");
+    let object_dir = external_base.join("objects");
+    std::fs::create_dir_all(&object_dir).unwrap();
+    let payload: &[u8] = b"mapped-in-base";
+    let object_path = object_dir.join("mapped.bin");
+    std::fs::write(&object_path, payload).unwrap();
+    let object_uri = url::Url::from_file_path(&object_path).unwrap().to_string();
+    let base_uri = url::Url::from_file_path(&external_base)
+        .unwrap()
+        .to_string();
+
+    let db = connect(db_path.to_str().unwrap()).execute().await?;
+    let table = db
+        .create_empty_table("t", blob_table_schema())
+        .write_options(WriteOptions {
+            lance_write_params: Some(WriteParams {
+                initial_bases: Some(vec![BasePath {
+                    id: 1,
+                    name: Some("external".to_string()),
+                    path: base_uri,
+                    is_dataset_root: false,
+                }]),
+                ..Default::default()
+            }),
+        })
+        .execute()
+        .await?;
+
+    table
+        .add(uri_string_batch(1, &object_uri))
+        .execute()
+        .await?;
+
+    let ids = collect_row_ids(&table).await?;
+    let bytes = table.fetch_blobs("image", &ids).await?;
+    assert_eq!(bytes.value(0), payload);
+    Ok(())
+}
+
+#[tokio::test]
+async fn external_uri_rows_mix_with_inline_rows() -> Result<()> {
+    let tmp = tempdir().unwrap();
+    let db = connect(tmp.path().join("db").to_str().unwrap())
+        .execute()
+        .await?;
+    let external_payload: &[u8] = b"external-bytes";
+    let uri = write_payload_file_uri(tmp.path(), "payload.bin", external_payload);
+    let table =
+        create_inline_blob_table(&db, "t", &[1], &[Some(b"inline-bytes".as_slice())]).await?;
+
+    table
+        .add(uri_string_batch(2, &uri))
+        .allow_external_blob_outside_bases(true)
+        .execute()
+        .await?;
+
+    let pairs = collect_id_rowid(&table).await?;
+    let row_ids: Vec<u64> = pairs.iter().map(|(_, r)| *r).collect();
+    let bytes = table.fetch_blobs("image", &row_ids).await?;
+    for (i, (id, _)) in pairs.iter().enumerate() {
+        match id {
+            1 => assert_eq!(bytes.value(i), b"inline-bytes"),
+            2 => assert_eq!(bytes.value(i), external_payload),
+            _ => unreachable!(),
+        }
+    }
+    Ok(())
+}
+
+#[tokio::test]
+async fn malformed_string_uri_is_rejected_at_write() -> Result<()> {
+    let tmp = tempdir().unwrap();
+    let db = connect(tmp.path().join("db").to_str().unwrap())
+        .execute()
+        .await?;
+    let table = db
+        .create_empty_table("t", blob_table_schema())
+        .execute()
+        .await?;
+
+    let err = table
+        .add(uri_string_batch(1, "not a uri"))
+        .allow_external_blob_outside_bases(true)
+        .execute()
+        .await
+        .unwrap_err();
+
+    assert!(err.to_string().contains("not a uri"), "got: {err}");
+    assert_eq!(table.count_rows(None).await?, 0);
+    Ok(())
+}
@@ -20,25 +20,6 @@ fn job_result(name: &str) -> Value {
    serde_json::from_str::<Value>(&fixture(name)).expect("remote Job fixture")["result"].clone()
 }

-fn assert_no_secret_values(value: &Value) {
-    match value {
-        Value::Object(values) => {
-            for (key, value) in values {
-                assert!(
-                    !matches!(
-                        key.as_str(),
-                        "secret_value" | "secret_values" | "resolved_secret" | "resolved_secrets"
-                    ),
-                    "client canonical value must not model resolved secret material"
-                );
-                assert_no_secret_values(value);
-            }
-        }
-        Value::Array(values) => values.iter().for_each(assert_no_secret_values),
-        _ => {}
-    }
-}
-
 #[test]
 fn function_version_job_result_matches_shared_canonical_golden() {
    let result = job_result("remote_function_job.json");
@@ -47,7 +28,6 @@ fn function_version_job_result_matches_shared_canonical_golden() {
    assert_eq!(version.name(), "embed");
    assert_eq!(version.version(), "fv_01K3EXACT");
    assert_eq!(version.runtime_digest(), "sha256:runtime");
-    assert_eq!(version.required_secrets(), &["HF_TOKEN"]);
    assert_eq!(
        version.to_canonical_json().expect("canonical JSON"),
        fixture("remote_function_version.canonical.json").trim()
@@ -84,7 +64,6 @@ fn application_and_binding_match_shared_remote_goldens() {

    let binding = FunctionBinding::from_json(&fixture("remote_function_binding.json"))
        .expect("binding fixture");
-    assert_eq!(binding.revision(), 3);
    assert_eq!(binding.function().version, "fv_01K3TEXT");
    assert_eq!(binding.outputs()[0].output_ordinal, 0);
    assert_eq!(binding.outputs()[1].output_ordinal, 1);
@@ -163,21 +142,3 @@ fn floating_point_application_literals_are_rejected_consistently() {
            .contains("floating-point Function literals")
    );
 }
-
-#[test]
-fn canonical_client_values_contain_secret_names_only() {
-    let result = job_result("remote_function_job.json");
-    let version = FunctionVersion::from_json(&result.to_string()).expect("FunctionVersion result");
-    let canonical: Value = serde_json::from_str(
-        &version
-            .to_canonical_json()
-            .expect("canonical FunctionVersion"),
-    )
-    .expect("canonical JSON");
-
-    assert_eq!(
-        canonical["required_secrets"],
-        serde_json::json!(["HF_TOKEN"])
-    );
-    assert_no_secret_values(&canonical);
-}
@@ -6,7 +6,6 @@ use std::path::PathBuf;

 use lancedb::Error;
 use lancedb::function::FunctionRegistrationRequest;
-use serde_json::Value;

 fn fixture(name: &str) -> String {
    let path = PathBuf::from(env!("CARGO_MANIFEST_DIR"))
@@ -15,25 +14,6 @@ fn fixture(name: &str) -> String {
    fs::read_to_string(path).expect("fixture must be readable")
 }

-fn assert_no_secret_values(value: &Value) {
-    match value {
-        Value::Object(values) => {
-            for (key, value) in values {
-                assert!(
-                    !matches!(
-                        key.as_str(),
-                        "secret_value" | "secret_values" | "resolved_secret" | "resolved_secrets"
-                    ),
-                    "registration requests must not model resolved secret material"
-                );
-                assert_no_secret_values(value);
-            }
-        }
-        Value::Array(values) => values.iter().for_each(assert_no_secret_values),
-        _ => {}
-    }
-}
-
 #[test]
 fn registration_request_matches_shared_canonical_golden() {
    let request = FunctionRegistrationRequest::from_json(&fixture(
@@ -42,16 +22,10 @@ fn registration_request_matches_shared_canonical_golden() {
    .expect("registration request");
    assert_eq!(request.name, "normalize_score");
    assert_eq!(request.artifact.adapter.kind, "scalar_to_arrow_batch");
-    assert_eq!(request.required_secrets, ["API_TOKEN"]);
    assert_eq!(
        request.to_canonical_json().expect("canonical request"),
        fixture("remote_function_registration_request.canonical.json").trim()
    );
-
-    let value: Value =
-        serde_json::from_str(&request.to_canonical_json().expect("canonical request"))
-            .expect("request JSON");
-    assert_no_secret_values(&value);
 }

 #[tokio::test]
@@ -24,8 +24,7 @@
        "kind": "scalar",
        "arrow_type": "fixed_size_list<float32, 3>",
        "nullable": false
-      },
-      "group_id": "fg_fixed"
+      }
    },
    "binding_metadata_version": 1,
    "input_bindings": [
@@ -76,4 +75,4 @@
      }
    ]
  }
-}
+}
@@ -1 +1 @@
-{"columns":{"normalized_text":"search_text","token_count":"search_token_count"},"function":{"name":"text_features","version":"fv_01K3TEXT"},"group_id":"fg_01K3TEXT","inputs":[{"kind":"column","parameter":"title","value":{"path":"title"}},{"kind":"column","parameter":"body","value":{"path":"body"}}],"output":{"fields":[{"arrow_type":"utf8","name":"normalized_text","nullable":false},{"arrow_type":"int64","name":"token_count","nullable":false}],"kind":"named_struct"}}
+{"columns":{"normalized_text":"search_text","token_count":"search_token_count"},"function":{"name":"text_features","version":"fv_01K3TEXT"},"inputs":[{"kind":"column","parameter":"title","value":{"path":"title"}},{"kind":"column","parameter":"body","value":{"path":"body"}}],"output":{"fields":[{"arrow_type":"utf8","name":"normalized_text","nullable":false},{"arrow_type":"int64","name":"token_count","nullable":false}],"kind":"named_struct"}}
--- a/Show More
+++ b/Show More