feat: add maximum and minimum nprobes properties (#2430)

This exposes the maximum_nprobes and minimum_nprobes feature that was
added in https://github.com/lancedb/lance/pull/3903

<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit

- **New Features**
- Added support for specifying minimum and maximum probe counts in
vector search queries, allowing finer control over search behavior.
- Users can now independently set minimum and maximum probes for vector
and hybrid queries via new methods and parameters in Python, Node.js,
and Rust APIs.

- **Bug Fixes**
- Improved parameter validation to ensure correct usage of minimum and
maximum probe values.

- **Tests**
- Expanded test coverage to validate correct handling, serialization,
and error cases for the new probe parameters.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->

nodejs/__test__/table.test.ts

@@ -559,6 +559,32 @@ describe("When creating an index", () => {
     rst = await tbl.query().limit(2).offset(1).nearestTo(queryVec).toArrow();
     expect(rst.numRows).toBe(1);
 
+    // test nprobes
+    rst = await tbl.query().nearestTo(queryVec).limit(2).nprobes(50).toArrow();
+    expect(rst.numRows).toBe(2);
+    rst = await tbl
+      .query()
+      .nearestTo(queryVec)
+      .limit(2)
+      .minimumNprobes(15)
+      .toArrow();
+    expect(rst.numRows).toBe(2);
+    rst = await tbl
+      .query()
+      .nearestTo(queryVec)
+      .limit(2)
+      .minimumNprobes(10)
+      .maximumNprobes(20)
+      .toArrow();
+    expect(rst.numRows).toBe(2);
+
+    expect(() => tbl.query().nearestTo(queryVec).minimumNprobes(0)).toThrow(
+      "Invalid input, minimum_nprobes must be greater than 0",
+    );
+    expect(() => tbl.query().nearestTo(queryVec).maximumNprobes(5)).toThrow(
+      "Invalid input, maximum_nprobes must be greater than minimum_nprobes",
+    );
+
     await tbl.dropIndex("vec_idx");
     const indices2 = await tbl.listIndices();
     expect(indices2.length).toBe(0);

nodejs/lancedb/query.ts

@@ -448,6 +448,10 @@ export class VectorQuery extends QueryBase<NativeVectorQuery> {
    * For best results we recommend tuning this parameter with a benchmark against
    * your actual data to find the smallest possible value that will still give
    * you the desired recall.
+   *
+   * For more fine grained control over behavior when you have a very narrow filter
+   * you can use `minimumNprobes` and `maximumNprobes`.  This method sets both
+   * the minimum and maximum to the same value.
    */
   nprobes(nprobes: number): VectorQuery {
     super.doCall((inner) => inner.nprobes(nprobes));
@@ -455,6 +459,33 @@ export class VectorQuery extends QueryBase<NativeVectorQuery> {
     return this;
   }
 
+  /**
+   * Set the minimum number of probes used.
+   *
+   * This controls the minimum number of partitions that will be searched.  This
+   * parameter will impact every query against a vector index, regardless of the
+   * filter.  See `nprobes` for more details.  Higher values will increase recall
+   * but will also increase latency.
+   */
+  minimumNprobes(minimumNprobes: number): VectorQuery {
+    super.doCall((inner) => inner.minimumNprobes(minimumNprobes));
+    return this;
+  }
+
+  /**
+   * Set the maximum number of probes used.
+   *
+   * This controls the maximum number of partitions that will be searched.  If this
+   * number is greater than minimumNprobes then the excess partitions will _only_ be
+   * searched if we have not found enough results.  This can be useful when there is
+   * a narrow filter to allow these queries to spend more time searching and avoid
+   * potential false negatives.
+   */
+  maximumNprobes(maximumNprobes: number): VectorQuery {
+    super.doCall((inner) => inner.maximumNprobes(maximumNprobes));
+    return this;
+  }
+
   /*
    * Set the distance range to use
    *

nodejs/src/query.rs

@@ -178,6 +178,31 @@ impl VectorQuery {
         self.inner = self.inner.clone().nprobes(nprobe as usize);
     }
 
+    #[napi]
+    pub fn minimum_nprobes(&mut self, minimum_nprobe: u32) -> napi::Result<()> {
+        self.inner = self
+            .inner
+            .clone()
+            .minimum_nprobes(minimum_nprobe as usize)
+            .default_error()?;
+        Ok(())
+    }
+
+    #[napi]
+    pub fn maximum_nprobes(&mut self, maximum_nprobes: u32) -> napi::Result<()> {
+        let maximum_nprobes = if maximum_nprobes == 0 {
+            None
+        } else {
+            Some(maximum_nprobes as usize)
+        };
+        self.inner = self
+            .inner
+            .clone()
+            .maximum_nprobes(maximum_nprobes)
+            .default_error()?;
+        Ok(())
+    }
+
     #[napi]
     pub fn distance_range(&mut self, lower_bound: Option<f64>, upper_bound: Option<f64>) {
         // napi doesn't support f32, so we have to convert to f32