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Apr 9, 2025
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DOC-5073 added TCE markup #1389

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33 changes: 17 additions & 16 deletions content/develop/data-types/vector-sets/_index.md
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Original file line number Diff line number Diff line change
Expand Up @@ -60,7 +60,7 @@ Start by adding the point vectors to a set called `points` using
The [`TYPE`]({{< relref "/commands/type" >}}) command returns a type of `vectorset`
for this object.

```
{{< clients-example vecset_tutorial vadd >}}
> VADD points VALUES 2 1.0 1.0 pt:A
(integer) 1
> VADD points VALUES 2 -1.0 -1.0 pt:B
Expand All @@ -73,26 +73,27 @@ for this object.
(integer) 1
> TYPE points
vectorset
```
{{< /clients-example >}}


Get the number of elements in the set (also known as the *cardinality* of the set)
using [`VCARD`]({{< relref "/commands/vcard" >}}) and the number of dimensions of
the vectors using [`VDIM`]({{< relref "/commands/vdim" >}}):

```
{{< clients-example vecset_tutorial vcardvdim >}}
> VCARD points
(integer) 5
> VDIM points
(integer) 2
```
{{< /clients-example >}}

Get the coordinate values from the elements using [`VEMB`]({{< relref "/commands/vemb" >}}).
Note that the values will not typically be the exact values you supplied when you added
the vector because
[quantization]({{< relref "/develop/data-types/vector-sets/performance#quantization-effects" >}})
is applied to improve performance.

```
{{< clients-example vecset_tutorial vemb >}}
> VEMB points pt:A
1) "0.9999999403953552"
2) "0.9999999403953552"
Expand All @@ -108,14 +109,14 @@ is applied to improve performance.
> VEMB points pt:E
1) "1"
2) "0"
```
{{< /clients-example >}}

Set and retrieve an element's JSON attribute data using
[`VSETATTR`]({{< relref "/commands/vsetattr" >}})
and [`VGETATTR`]({{< relref "/commands/vgetattr" >}}). You can also pass an empty string
to `VSETATTR` to delete the attribute data:

```
{{< clients-example vecset_tutorial attr >}}
> VSETATTR points pt:A "{\"name\": \"Point A\", \"description\": \"First point added\"}"
(integer) 1
> VGETATTR points pt:A
Expand All @@ -124,11 +125,11 @@ to `VSETATTR` to delete the attribute data:
(integer) 1
> VGETATTR points pt:A
(nil)
```
{{< /clients-example >}}

Remove an unwanted element with [`VREM`]({{< relref "/commands/vrem" >}})

```
{{< clients-example vecset_tutorial vrem >}}
> VADD points VALUES 2 0 0 pt:F
(integer) 1
127.0.0.1:6379> VCARD points
Expand All @@ -137,24 +138,24 @@ Remove an unwanted element with [`VREM`]({{< relref "/commands/vrem" >}})
(integer) 1
127.0.0.1:6379> VCARD points
(integer) 5
```
{{< /clients-example >}}

### Vector similarity search

Use [`VSIM`]({{< relref "/commands/vsim" >}}) to rank the points in order of their vector distance from a sample point:

```
{{< clients-example vecset_tutorial vsim_basic >}}
> VSIM points values 2 0.9 0.1
1) "pt:E"
2) "pt:A"
3) "pt:D"
4) "pt:C"
5) "pt:B"
```
{{< /clients-example >}}

Find the four elements that are closest to point A and show their distance "scores":

```
{{< clients-example vecset_tutorial vsim_options >}}
> VSIM points ELE pt:A WITHSCORES COUNT 4
1) "pt:A"
2) "1"
Expand All @@ -164,13 +165,13 @@ Find the four elements that are closest to point A and show their distance "scor
6) "0.5"
7) "pt:D"
8) "0.5"
```
{{< /clients-example >}}

Add some JSON attributes and use
[filter expressions]({{< relref "/develop/data-types/vector-sets/filtered-search" >}})
to include them in the search:

```
{{< clients-example vecset_tutorial vsim_filter >}}
> VSETATTR points pt:A "{\"size\":\"large\",\"price\": 18.99}"
(integer) 1
> VSETATTR points pt:B "{\"size\":\"large\",\"price\": 35.99}"
Expand All @@ -194,7 +195,7 @@ to include them in the search:
> VSIM points ELE pt:A FILTER '.size == "large" && .price > 20.00'
1) "pt:C"
2) "pt:B"
```
{{< /clients-example >}}

## More information

Expand Down