feat: support multivector for JS SDK (#2527)

Signed-off-by: BubbleCal <bubble-cal@outlook.com>

docs/src/js/classes/VectorQuery.md

@@ -386,6 +386,53 @@ called then every valid row from the table will be returned.
 
 ***
 
+### maximumNprobes()
+
+```ts
+maximumNprobes(maximumNprobes): VectorQuery
+```
+
+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.
+
+#### Parameters
+
+* **maximumNprobes**: `number`
+
+#### Returns
+
+[`VectorQuery`](VectorQuery.md)
+
+***
+
+### minimumNprobes()
+
+```ts
+minimumNprobes(minimumNprobes): VectorQuery
+```
+
+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.
+
+#### Parameters
+
+* **minimumNprobes**: `number`
+
+#### Returns
+
+[`VectorQuery`](VectorQuery.md)
+
+***
+
 ### nprobes()
 
 ```ts
@@ -413,6 +460,10 @@ 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.
+
 #### Parameters
 
 * **nprobes**: `number`