mirror of
https://github.com/qdrant/landing_page.git
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Distance matrix API docs (#1221)
* Distance matrix API docs * fix * add java examples * rust examples * add slots for missing examples * better * fix url * move to explore * reinstate query planning * add go examples * more imports * guess typescript and add imports * guess csharp * fix python snippet * add filters to go snippets --------- Co-authored-by: generall <andrey@vasnetsov.com>
This commit is contained in:
Arnaud Gourlay
co-authored by
generall
generall
parent
ac7ef1e586
commit
ece9e08e11
@@ -171,32 +171,32 @@ await client.QueryAsync(
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```go
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import (
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"context"
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"context"
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"github.com/qdrant/go-client/qdrant"
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"github.com/qdrant/go-client/qdrant"
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)
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client, err := qdrant.NewClient(&qdrant.Config{
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Host: "localhost",
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Port: 6334,
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Host: "localhost",
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Port: 6334,
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})
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client.Query(context.Background(), &qdrant.QueryPoints{
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CollectionName: "{collection_name}",
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Query: qdrant.NewQueryRecommend(&qdrant.RecommendInput{
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Positive: []*qdrant.VectorInput{
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qdrant.NewVectorInputID(qdrant.NewIDNum(100)),
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qdrant.NewVectorInputID(qdrant.NewIDNum(231)),
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},
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Negative: []*qdrant.VectorInput{
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qdrant.NewVectorInputID(qdrant.NewIDNum(718)),
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},
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}),
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Filter: &qdrant.Filter{
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Must: []*qdrant.Condition{
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qdrant.NewMatch("city", "London"),
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},
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},
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CollectionName: "{collection_name}",
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Query: qdrant.NewQueryRecommend(&qdrant.RecommendInput{
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Positive: []*qdrant.VectorInput{
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qdrant.NewVectorInputID(qdrant.NewIDNum(100)),
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qdrant.NewVectorInputID(qdrant.NewIDNum(231)),
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},
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Negative: []*qdrant.VectorInput{
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qdrant.NewVectorInputID(qdrant.NewIDNum(718)),
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},
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}),
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Filter: &qdrant.Filter{
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Must: []*qdrant.Condition{
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qdrant.NewMatch("city", "London"),
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},
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},
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})
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```
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@@ -368,28 +368,28 @@ await client.QueryAsync(
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```go
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import (
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"context"
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"context"
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"github.com/qdrant/go-client/qdrant"
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"github.com/qdrant/go-client/qdrant"
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)
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client, err := qdrant.NewClient(&qdrant.Config{
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Host: "localhost",
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Port: 6334,
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Host: "localhost",
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Port: 6334,
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})
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client.Query(context.Background(), &qdrant.QueryPoints{
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CollectionName: "{collection_name}",
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Query: qdrant.NewQueryRecommend(&qdrant.RecommendInput{
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Positive: []*qdrant.VectorInput{
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qdrant.NewVectorInputID(qdrant.NewIDNum(100)),
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qdrant.NewVectorInputID(qdrant.NewIDNum(231)),
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},
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Negative: []*qdrant.VectorInput{
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qdrant.NewVectorInputID(qdrant.NewIDNum(718)),
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},
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}),
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Using: qdrant.PtrOf("image"),
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CollectionName: "{collection_name}",
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Query: qdrant.NewQueryRecommend(&qdrant.RecommendInput{
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Positive: []*qdrant.VectorInput{
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qdrant.NewVectorInputID(qdrant.NewIDNum(100)),
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qdrant.NewVectorInputID(qdrant.NewIDNum(231)),
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},
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Negative: []*qdrant.VectorInput{
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qdrant.NewVectorInputID(qdrant.NewIDNum(718)),
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},
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}),
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Using: qdrant.PtrOf("image"),
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})
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```
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@@ -518,44 +518,44 @@ await client.QueryAsync(
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Positive = { 100, 231 },
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Negative = { 718 }
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},
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usingVector: "image",
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limit: 10,
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usingVector: "image",
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limit: 10,
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lookupFrom: new LookupLocation
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{
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CollectionName = "{external_collection_name}",
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VectorName = "{external_vector_name}",
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}
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{
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CollectionName = "{external_collection_name}",
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VectorName = "{external_vector_name}",
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}
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);
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```
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```go
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import (
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"context"
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"context"
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"github.com/qdrant/go-client/qdrant"
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"github.com/qdrant/go-client/qdrant"
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)
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client, err := qdrant.NewClient(&qdrant.Config{
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Host: "localhost",
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Port: 6334,
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Host: "localhost",
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Port: 6334,
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})
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client.Query(context.Background(), &qdrant.QueryPoints{
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CollectionName: "{collection_name}",
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Query: qdrant.NewQueryRecommend(&qdrant.RecommendInput{
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Positive: []*qdrant.VectorInput{
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qdrant.NewVectorInputID(qdrant.NewIDNum(100)),
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qdrant.NewVectorInputID(qdrant.NewIDNum(231)),
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},
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Negative: []*qdrant.VectorInput{
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qdrant.NewVectorInputID(qdrant.NewIDNum(718)),
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},
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}),
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Using: qdrant.PtrOf("image"),
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LookupFrom: &qdrant.LookupLocation{
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CollectionName: "{external_collection_name}",
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VectorName: qdrant.PtrOf("{external_vector_name}"),
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},
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CollectionName: "{collection_name}",
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Query: qdrant.NewQueryRecommend(&qdrant.RecommendInput{
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Positive: []*qdrant.VectorInput{
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qdrant.NewVectorInputID(qdrant.NewIDNum(100)),
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qdrant.NewVectorInputID(qdrant.NewIDNum(231)),
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},
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Negative: []*qdrant.VectorInput{
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qdrant.NewVectorInputID(qdrant.NewIDNum(718)),
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},
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}),
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Using: qdrant.PtrOf("image"),
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LookupFrom: &qdrant.LookupLocation{
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CollectionName: "{external_collection_name}",
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VectorName: qdrant.PtrOf("{external_vector_name}"),
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},
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})
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```
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@@ -792,82 +792,82 @@ var client = new QdrantClient("localhost", 6334);
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var filter = MatchKeyword("city", "london");
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await client.QueryBatchAsync(
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collectionName: "{collection_name}",
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queries:
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[
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new QueryPoints()
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{
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CollectionName = "{collection_name}",
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Query = new RecommendInput {
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collectionName: "{collection_name}",
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queries:
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[
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new QueryPoints()
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{
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CollectionName = "{collection_name}",
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Query = new RecommendInput {
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Positive = { 100, 231 },
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Negative = { 718 },
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},
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Limit = 3,
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Filter = filter,
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},
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new QueryPoints()
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{
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CollectionName = "{collection_name}",
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Query = new RecommendInput {
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Limit = 3,
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Filter = filter,
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},
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new QueryPoints()
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{
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CollectionName = "{collection_name}",
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Query = new RecommendInput {
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Positive = { 200, 67 },
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Negative = { 300 },
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},
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Limit = 3,
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Filter = filter,
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}
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]
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Limit = 3,
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Filter = filter,
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}
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]
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);
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```
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```go
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import (
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"context"
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"context"
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"github.com/qdrant/go-client/qdrant"
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"github.com/qdrant/go-client/qdrant"
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)
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client, err := qdrant.NewClient(&qdrant.Config{
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Host: "localhost",
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Port: 6334,
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Host: "localhost",
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Port: 6334,
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})
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filter := qdrant.Filter{
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Must: []*qdrant.Condition{
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qdrant.NewMatch("city", "London"),
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},
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Must: []*qdrant.Condition{
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qdrant.NewMatch("city", "London"),
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},
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}
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client.QueryBatch(context.Background(), &qdrant.QueryBatchPoints{
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CollectionName: "{collection_name}",
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QueryPoints: []*qdrant.QueryPoints{
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{
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CollectionName: "{collection_name}",
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Query: qdrant.NewQueryRecommend(&qdrant.RecommendInput{
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Positive: []*qdrant.VectorInput{
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qdrant.NewVectorInputID(qdrant.NewIDNum(100)),
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qdrant.NewVectorInputID(qdrant.NewIDNum(231)),
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},
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Negative: []*qdrant.VectorInput{
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qdrant.NewVectorInputID(qdrant.NewIDNum(718)),
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},
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},
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),
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Filter: &filter,
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},
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{
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CollectionName: "{collection_name}",
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Query: qdrant.NewQueryRecommend(&qdrant.RecommendInput{
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Positive: []*qdrant.VectorInput{
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qdrant.NewVectorInputID(qdrant.NewIDNum(200)),
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qdrant.NewVectorInputID(qdrant.NewIDNum(67)),
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},
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Negative: []*qdrant.VectorInput{
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qdrant.NewVectorInputID(qdrant.NewIDNum(300)),
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},
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},
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),
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Filter: &filter,
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},
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},
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CollectionName: "{collection_name}",
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QueryPoints: []*qdrant.QueryPoints{
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{
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CollectionName: "{collection_name}",
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Query: qdrant.NewQueryRecommend(&qdrant.RecommendInput{
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Positive: []*qdrant.VectorInput{
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qdrant.NewVectorInputID(qdrant.NewIDNum(100)),
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qdrant.NewVectorInputID(qdrant.NewIDNum(231)),
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},
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Negative: []*qdrant.VectorInput{
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qdrant.NewVectorInputID(qdrant.NewIDNum(718)),
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},
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},
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),
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Filter: &filter,
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},
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{
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CollectionName: "{collection_name}",
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Query: qdrant.NewQueryRecommend(&qdrant.RecommendInput{
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Positive: []*qdrant.VectorInput{
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qdrant.NewVectorInputID(qdrant.NewIDNum(200)),
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qdrant.NewVectorInputID(qdrant.NewIDNum(67)),
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},
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Negative: []*qdrant.VectorInput{
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qdrant.NewVectorInputID(qdrant.NewIDNum(300)),
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},
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},
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),
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Filter: &filter,
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},
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},
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},
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)
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```
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@@ -1069,8 +1069,8 @@ using Qdrant.Client.Grpc;
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var client = new QdrantClient("localhost", 6334);
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await client.QueryAsync(
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collectionName: "{collection_name}",
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query: new DiscoverInput {
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collectionName: "{collection_name}",
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query: new DiscoverInput {
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Target = new float[] { 0.2f, 0.1f, 0.9f, 0.7f },
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Context = new ContextInput {
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Pairs = {
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@@ -1085,39 +1085,39 @@ await client.QueryAsync(
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}
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},
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},
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limit: 10
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limit: 10
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);
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```
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```go
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import (
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"context"
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"context"
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"github.com/qdrant/go-client/qdrant"
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"github.com/qdrant/go-client/qdrant"
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)
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client, err := qdrant.NewClient(&qdrant.Config{
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Host: "localhost",
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Port: 6334,
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Host: "localhost",
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Port: 6334,
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})
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client.Query(context.Background(), &qdrant.QueryPoints{
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CollectionName: "{collection_name}",
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Query: qdrant.NewQueryDiscover(&qdrant.DiscoverInput{
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Target: qdrant.NewVectorInput(0.2, 0.1, 0.9, 0.7),
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Context: &qdrant.ContextInput{
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Pairs: []*qdrant.ContextInputPair{
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{
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Positive: qdrant.NewVectorInputID(qdrant.NewIDNum(100)),
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Negative: qdrant.NewVectorInputID(qdrant.NewIDNum(718)),
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},
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{
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Positive: qdrant.NewVectorInputID(qdrant.NewIDNum(200)),
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Negative: qdrant.NewVectorInputID(qdrant.NewIDNum(300)),
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},
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},
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},
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}),
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CollectionName: "{collection_name}",
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Query: qdrant.NewQueryDiscover(&qdrant.DiscoverInput{
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Target: qdrant.NewVectorInput(0.2, 0.1, 0.9, 0.7),
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Context: &qdrant.ContextInput{
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Pairs: []*qdrant.ContextInputPair{
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{
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Positive: qdrant.NewVectorInputID(qdrant.NewIDNum(100)),
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Negative: qdrant.NewVectorInputID(qdrant.NewIDNum(718)),
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},
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{
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Positive: qdrant.NewVectorInputID(qdrant.NewIDNum(200)),
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Negative: qdrant.NewVectorInputID(qdrant.NewIDNum(300)),
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},
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},
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},
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}),
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})
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```
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@@ -1289,30 +1289,30 @@ await client.QueryAsync(
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```go
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import (
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"context"
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"context"
|
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|
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"github.com/qdrant/go-client/qdrant"
|
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"github.com/qdrant/go-client/qdrant"
|
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)
|
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client, err := qdrant.NewClient(&qdrant.Config{
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Host: "localhost",
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Port: 6334,
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Host: "localhost",
|
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Port: 6334,
|
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})
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client.Query(context.Background(), &qdrant.QueryPoints{
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CollectionName: "{collection_name}",
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Query: qdrant.NewQueryContext(&qdrant.ContextInput{
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Pairs: []*qdrant.ContextInputPair{
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{
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Positive: qdrant.NewVectorInputID(qdrant.NewIDNum(100)),
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Negative: qdrant.NewVectorInputID(qdrant.NewIDNum(718)),
|
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},
|
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{
|
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Positive: qdrant.NewVectorInputID(qdrant.NewIDNum(200)),
|
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Negative: qdrant.NewVectorInputID(qdrant.NewIDNum(300)),
|
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},
|
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},
|
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}),
|
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CollectionName: "{collection_name}",
|
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Query: qdrant.NewQueryContext(&qdrant.ContextInput{
|
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Pairs: []*qdrant.ContextInputPair{
|
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{
|
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Positive: qdrant.NewVectorInputID(qdrant.NewIDNum(100)),
|
||||
Negative: qdrant.NewVectorInputID(qdrant.NewIDNum(718)),
|
||||
},
|
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{
|
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Positive: qdrant.NewVectorInputID(qdrant.NewIDNum(200)),
|
||||
Negative: qdrant.NewVectorInputID(qdrant.NewIDNum(300)),
|
||||
},
|
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},
|
||||
}),
|
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})
|
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```
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|
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@@ -1324,3 +1324,343 @@ Notes about context search:
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* Best possible score is `0.0`, and it is normal that many points get this score.
|
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|
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</aside>
|
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|
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## Distance Matrix
|
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|
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*Available as of v1.12.0*
|
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|
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The distance matrix API allows to calculate the distance between sampled pairs of vectors and to return the result as a sparse matrix.
|
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|
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Such API enables new data exploration use cases such as clustering similar vectors, visualization of connections or dimension reduction.
|
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|
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The API input request consists of the following parameters:
|
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- `sample`: the number of vectors to sample
|
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- `limit`: the number of scores to return per sample
|
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- `filter`: the filter to apply to constraint the samples
|
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|
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Let's have a look at a basic example with `sample=100`, `limit=10`:
|
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|
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The engine starts by selecting `100` random points from the collection, then for each of the selected points, it will compute the top `10` closest points **within** the samples.
|
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|
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This will results in a total of 1000 scores represented as a sparse matrix for efficient processing.
|
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|
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The distance matrix API offers two output formats to ease the integration with different tools.
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### Pairwise format
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|
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Returns the distance matrix as a list of pairs of point `ids` with their respective score.
|
||||
|
||||
```http
|
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POST /collections/{collection_name}/points/search/matrix/pairs
|
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{
|
||||
"sample": 10,
|
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"limit": 2,
|
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"filter": {
|
||||
"must": {
|
||||
"key": "color",
|
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"match": { "value": "red" }
|
||||
}
|
||||
}
|
||||
}
|
||||
```
|
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|
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```python
|
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from qdrant_client import QdrantClient, models
|
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|
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client.search_matrix_pairs(
|
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collection_name="{collection_name}",
|
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sample=10,
|
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limit=2,
|
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query_filter=models.Filter(
|
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must=[
|
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models.FieldCondition(
|
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key="color", match=models.MatchValue(value="red")
|
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),
|
||||
]
|
||||
),
|
||||
)
|
||||
```
|
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|
||||
```java
|
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import static io.qdrant.client.ConditionFactory.matchKeyword;
|
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|
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import io.qdrant.client.QdrantClient;
|
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import io.qdrant.client.QdrantGrpcClient;
|
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import io.qdrant.client.grpc.Points.Filter;
|
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import io.qdrant.client.grpc.Points.SearchMatrixPoints;
|
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|
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QdrantClient client =
|
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new QdrantClient(QdrantGrpcClient.newBuilder("localhost", 6334, false).build());
|
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|
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client
|
||||
.searchMatrixPairsAsync(
|
||||
Points.SearchMatrixPoints.newBuilder()
|
||||
.setCollectionName(collectionName)
|
||||
.setFilter(Filter.newBuilder().addMust(matchKeyword("color", "red")).build())
|
||||
.setSample(10)
|
||||
.setLimit(2)
|
||||
.build())
|
||||
.get();
|
||||
```
|
||||
|
||||
```rust
|
||||
use qdrant_client::qdrant::{Condition, Filter, SearchMatrixPointsBuilder};
|
||||
use qdrant_client::Qdrant;
|
||||
|
||||
client
|
||||
.search_matrix_pairs(
|
||||
SearchMatrixPointsBuilder::new("collection_name")
|
||||
.filter(Filter::must(vec![Condition::matches(
|
||||
"color",
|
||||
"red".to_string(),
|
||||
)]))
|
||||
.sample(10)
|
||||
.limit(2),
|
||||
)
|
||||
.await?;
|
||||
```
|
||||
|
||||
```typescript
|
||||
import { QdrantClient } from "@qdrant/js-client-rest";
|
||||
|
||||
const client = new QdrantClient({ host: "localhost", port: 6333 });
|
||||
|
||||
client.searchMatrixPairs("{collection_name}", {
|
||||
filter: {
|
||||
must: [
|
||||
{
|
||||
key: "color",
|
||||
match: {
|
||||
value: "red",
|
||||
},
|
||||
},
|
||||
],
|
||||
},
|
||||
sample: 10,
|
||||
limit: 2,
|
||||
});
|
||||
```
|
||||
|
||||
```csharp
|
||||
using Qdrant.Client;
|
||||
using Qdrant.Client.Grpc;
|
||||
using static Qdrant.Client.Grpc.Conditions;
|
||||
|
||||
var client = new QdrantClient("localhost", 6334);
|
||||
|
||||
await client.SearchMatrixPairs(
|
||||
collectionName: "{collection_name}",
|
||||
filter: MatchKeyword("color", "red"),
|
||||
sample: 10,
|
||||
limit: 2
|
||||
);
|
||||
```
|
||||
|
||||
```go
|
||||
import (
|
||||
"context"
|
||||
|
||||
"github.com/qdrant/go-client/qdrant"
|
||||
)
|
||||
|
||||
client, err := qdrant.NewClient(&qdrant.Config{
|
||||
Host: "localhost",
|
||||
Port: 6334,
|
||||
})
|
||||
|
||||
sample := uint64(10)
|
||||
limit := uint64(2)
|
||||
res, err := client.SearchMatrixPairs(ctx, &qdrant.SearchMatrixPoints{
|
||||
CollectionName: "{collection_name}",
|
||||
Sample: &sample,
|
||||
Limit: &limit,
|
||||
Filter: &qdrant.Filter{
|
||||
Must: []*qdrant.Condition{
|
||||
qdrant.NewMatch("color", "red"),
|
||||
},
|
||||
},
|
||||
})
|
||||
```
|
||||
|
||||
Returns
|
||||
|
||||
```json
|
||||
{
|
||||
"result": {
|
||||
"pairs": [
|
||||
{"a": 1, "b": 3, "score": 1.4063001},
|
||||
{"a": 1, "b": 4, "score": 1.2531},
|
||||
{"a": 2, "b": 1, "score": 1.1550001},
|
||||
{"a": 2, "b": 8, "score": 1.1359},
|
||||
{"a": 3, "b": 1, "score": 1.4063001},
|
||||
{"a": 3, "b": 4, "score": 1.2218001},
|
||||
{"a": 4, "b": 1, "score": 1.2531},
|
||||
{"a": 4, "b": 3, "score": 1.2218001},
|
||||
{"a": 5, "b": 3, "score": 0.70239997},
|
||||
{"a": 5, "b": 1, "score": 0.6146},
|
||||
{"a": 6, "b": 3, "score": 0.6353},
|
||||
{"a": 6, "b": 4, "score": 0.5093},
|
||||
{"a": 7, "b": 3, "score": 1.0990001},
|
||||
{"a": 7, "b": 1, "score": 1.0349001},
|
||||
{"a": 8, "b": 2, "score": 1.1359},
|
||||
{"a": 8, "b": 3, "score": 1.0553}
|
||||
]
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
### Offset format
|
||||
|
||||
Returns the distance matrix as a four arrays:
|
||||
- `offsets_row` and `offsets_col`, represent the positions of non-zero distance values in the matrix.
|
||||
- `scores` contains the distance values.
|
||||
- `ids` contains the point ids corresponding to the distance values.
|
||||
|
||||
```http
|
||||
POST /collections/{collection_name}/points/search/matrix/offsets
|
||||
{
|
||||
"sample": 10,
|
||||
"limit": 2,
|
||||
"filter": {
|
||||
"must": {
|
||||
"key": "color",
|
||||
"match": { "value": "red" }
|
||||
}
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
```python
|
||||
from qdrant_client import QdrantClient, models
|
||||
|
||||
client.search_matrix_pairs(
|
||||
collection_name="{collection_name}",
|
||||
sample=10,
|
||||
limit=2,
|
||||
query_filter=models.Filter(
|
||||
must=[
|
||||
models.FieldCondition(
|
||||
key="color", match=models.MatchValue(value="red")
|
||||
),
|
||||
]
|
||||
),
|
||||
)
|
||||
```
|
||||
|
||||
```java
|
||||
import static io.qdrant.client.ConditionFactory.matchKeyword;
|
||||
|
||||
import io.qdrant.client.QdrantClient;
|
||||
import io.qdrant.client.QdrantGrpcClient;
|
||||
import io.qdrant.client.grpc.Points.Filter;
|
||||
import io.qdrant.client.grpc.Points.SearchMatrixPoints;
|
||||
|
||||
QdrantClient client =
|
||||
new QdrantClient(QdrantGrpcClient.newBuilder("localhost", 6334, false).build());
|
||||
|
||||
client
|
||||
.searchMatrixOffsetsAsync(
|
||||
SearchMatrixPoints.newBuilder()
|
||||
.setCollectionName(collectionName)
|
||||
.setFilter(Filter.newBuilder().addMust(matchKeyword("color", "red")).build())
|
||||
.setSample(10)
|
||||
.setLimit(2)
|
||||
.build())
|
||||
.get();
|
||||
```
|
||||
|
||||
```rust
|
||||
use qdrant_client::qdrant::{Condition, Filter, SearchMatrixPointsBuilder};
|
||||
use qdrant_client::Qdrant;
|
||||
|
||||
client
|
||||
.search_matrix_offsets(
|
||||
SearchMatrixPointsBuilder::new("collection_name")
|
||||
.filter(Filter::must(vec![Condition::matches(
|
||||
"color",
|
||||
"red".to_string(),
|
||||
)]))
|
||||
.sample(10)
|
||||
.limit(2),
|
||||
)
|
||||
.await?;
|
||||
```
|
||||
|
||||
```typescript
|
||||
import { QdrantClient } from "@qdrant/js-client-rest";
|
||||
|
||||
const client = new QdrantClient({ host: "localhost", port: 6333 });
|
||||
|
||||
client.searchMatrixOffsets("{collection_name}", {
|
||||
filter: {
|
||||
must: [
|
||||
{
|
||||
key: "color",
|
||||
match: {
|
||||
value: "red",
|
||||
},
|
||||
},
|
||||
],
|
||||
},
|
||||
sample: 10,
|
||||
limit: 2,
|
||||
});
|
||||
```
|
||||
|
||||
```csharp
|
||||
using Qdrant.Client;
|
||||
using Qdrant.Client.Grpc;
|
||||
using static Qdrant.Client.Grpc.Conditions;
|
||||
|
||||
var client = new QdrantClient("localhost", 6334);
|
||||
|
||||
await client.SearchMatrixOffsets(
|
||||
collectionName: "{collection_name}",
|
||||
filter: MatchKeyword("color", "red"),
|
||||
sample: 10,
|
||||
limit: 2
|
||||
);
|
||||
```
|
||||
|
||||
```go
|
||||
import (
|
||||
"context"
|
||||
|
||||
"github.com/qdrant/go-client/qdrant"
|
||||
)
|
||||
|
||||
client, err := qdrant.NewClient(&qdrant.Config{
|
||||
Host: "localhost",
|
||||
Port: 6334,
|
||||
})
|
||||
|
||||
sample := uint64(10)
|
||||
limit := uint64(2)
|
||||
res, err := client.SearchMatrixOffsets(ctx, &qdrant.SearchMatrixPoints{
|
||||
CollectionName: "{collection_name}",
|
||||
Sample: &sample,
|
||||
Limit: &limit,
|
||||
Filter: &qdrant.Filter{
|
||||
Must: []*qdrant.Condition{
|
||||
qdrant.NewMatch("color", "red"),
|
||||
},
|
||||
},
|
||||
})
|
||||
```
|
||||
|
||||
Returns
|
||||
|
||||
```json
|
||||
{
|
||||
"result": {
|
||||
"offsets_row": [0, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 6, 6, 7, 7],
|
||||
"offsets_col": [2, 3, 0, 7, 0, 3, 0, 2, 2, 0, 2, 3, 2, 0, 1, 2],
|
||||
"scores": [
|
||||
1.4063001, 1.2531, 1.1550001, 1.1359, 1.4063001,
|
||||
1.2218001, 1.2531, 1.2218001, 0.70239997, 0.6146, 0.6353,
|
||||
0.5093, 1.0990001, 1.0349001, 1.1359, 1.0553
|
||||
],
|
||||
"ids": [1, 2, 3, 4, 5, 6, 7, 8]
|
||||
}
|
||||
}
|
||||
```
|
||||
Reference in New Issue
Block a user