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https://github.com/qdrant/landing_page.git
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upload snippets
This commit is contained in:
Dylan Couzon
+1
@@ -0,0 +1 @@
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This code snippet shows the canonical pattern for combining hybrid search fusion with business-logic ranking. The inner prefetch fuses sparse and dense results with RRF, then the outer `FormulaQuery` applies exponential decay on a `published_at` payload field to boost recent documents. Use this pattern any time you want fusion plus recency, popularity, geo decay, or category-conditional multipliers, rather than trying to encode those signals as fusion weights.
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+53
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using Qdrant.Client;
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using Qdrant.Client.Grpc;
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public class Snippet
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{
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public static async Task Run()
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{
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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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prefetch:
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[
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new PrefetchQuery {
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Prefetch = {
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new PrefetchQuery {
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Query = new(float, uint)[] { (0.22f, 1), (0.8f, 42) },
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Using = "sparse",
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Limit = 100
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},
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new PrefetchQuery {
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Query = new float[] { 0.01f, 0.45f, 0.67f },
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Using = "dense",
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Limit = 100
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},
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},
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Query = Fusion.Rrf,
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Limit = 100
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},
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],
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query: new Formula
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{
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Expression = new SumExpression
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{
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Sum =
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{
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"$score", // the fused score from the RRF prefetch
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Expression.FromExpDecay(
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new()
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{
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X = Expression.FromDateTimeKey("published_at"),
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Target = Expression.FromDateTime("YYYY-MM-DDT00:00:00Z"),
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Scale = 86400 * 180, // 180 days in seconds
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Midpoint = 0.5f
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}
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)
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}
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}
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},
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limit: 10
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);
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}
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}
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+49
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```csharp
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using Qdrant.Client;
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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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prefetch:
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[
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new PrefetchQuery {
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Prefetch = {
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new PrefetchQuery {
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Query = new(float, uint)[] { (0.22f, 1), (0.8f, 42) },
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Using = "sparse",
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Limit = 100
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},
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new PrefetchQuery {
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Query = new float[] { 0.01f, 0.45f, 0.67f },
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Using = "dense",
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Limit = 100
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},
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},
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Query = Fusion.Rrf,
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Limit = 100
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},
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],
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query: new Formula
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{
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Expression = new SumExpression
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{
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Sum =
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{
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"$score", // the fused score from the RRF prefetch
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Expression.FromExpDecay(
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new()
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{
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X = Expression.FromDateTimeKey("published_at"),
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Target = Expression.FromDateTime("YYYY-MM-DDT00:00:00Z"),
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Scale = 86400 * 180, // 180 days in seconds
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Midpoint = 0.5f
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}
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)
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}
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}
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},
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limit: 10
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);
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```
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+48
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```go
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import (
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"context"
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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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})
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client.Query(context.Background(), &qdrant.QueryPoints{
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CollectionName: "{collection_name}",
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Prefetch: []*qdrant.PrefetchQuery{
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{
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Prefetch: []*qdrant.PrefetchQuery{
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{
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Query: qdrant.NewQuerySparse([]uint32{1, 42}, []float32{0.22, 0.8}),
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Using: qdrant.PtrOf("sparse"),
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Limit: qdrant.PtrOf(uint64(100)),
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},
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{
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Query: qdrant.NewQueryDense([]float32{0.01, 0.45, 0.67}),
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Using: qdrant.PtrOf("dense"),
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Limit: qdrant.PtrOf(uint64(100)),
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},
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},
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Query: qdrant.NewQueryFusion(qdrant.Fusion_RRF),
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Limit: qdrant.PtrOf(uint64(100)),
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},
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},
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Query: qdrant.NewQueryFormula(&qdrant.Formula{
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Expression: qdrant.NewExpressionSum(&qdrant.SumExpression{
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Sum: []*qdrant.Expression{
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qdrant.NewExpressionVariable("$score"), // the fused score from the RRF prefetch
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qdrant.NewExpressionExpDecay(&qdrant.DecayParamsExpression{
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X: qdrant.NewExpressionDatetimeKey("published_at"),
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Target: qdrant.NewExpressionDatetime("YYYY-MM-DDT00:00:00Z"),
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Scale: qdrant.PtrOf(float32(86400 * 180)), // 180 days in seconds
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Midpoint: qdrant.PtrOf(float32(0.5)),
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}),
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},
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}),
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}),
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Limit: qdrant.PtrOf(uint64(10)),
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})
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```
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+65
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```java
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import static io.qdrant.client.ExpressionFactory.datetime;
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import static io.qdrant.client.ExpressionFactory.datetimeKey;
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import static io.qdrant.client.ExpressionFactory.expDecay;
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import static io.qdrant.client.ExpressionFactory.sum;
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import static io.qdrant.client.ExpressionFactory.variable;
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import static io.qdrant.client.QueryFactory.formula;
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import static io.qdrant.client.QueryFactory.fusion;
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import static io.qdrant.client.QueryFactory.nearest;
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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.DecayParamsExpression;
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import io.qdrant.client.grpc.Points.Formula;
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import io.qdrant.client.grpc.Points.Fusion;
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import io.qdrant.client.grpc.Points.PrefetchQuery;
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import io.qdrant.client.grpc.Points.QueryPoints;
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import io.qdrant.client.grpc.Points.SumExpression;
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import java.util.List;
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QdrantClient client =
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new QdrantClient(QdrantGrpcClient.newBuilder("localhost", 6334, false).build());
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client.queryAsync(
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QueryPoints.newBuilder()
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.setCollectionName("{collection_name}")
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.addPrefetch(
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PrefetchQuery.newBuilder()
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.addPrefetch(
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PrefetchQuery.newBuilder()
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.setQuery(nearest(List.of(0.22f, 0.8f), List.of(1, 42)))
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.setUsing("sparse")
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.setLimit(100)
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.build())
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.addPrefetch(
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PrefetchQuery.newBuilder()
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.setQuery(nearest(List.of(0.01f, 0.45f, 0.67f)))
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.setUsing("dense")
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.setLimit(100)
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.build())
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.setQuery(fusion(Fusion.RRF))
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.setLimit(100)
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.build())
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.setQuery(
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formula(
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Formula.newBuilder()
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.setExpression(
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sum(
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SumExpression.newBuilder()
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.addSum(variable("$score"))
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.addSum(
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expDecay(
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DecayParamsExpression.newBuilder()
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.setX(datetimeKey("published_at"))
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.setTarget(
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datetime("YYYY-MM-DDT00:00:00Z"))
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.setScale(86400 * 180)
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.setMidpoint(0.5f)
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.build()))
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.build()))
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.build()))
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.setLimit(10)
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.build())
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.get();
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```
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+41
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```python
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from qdrant_client import QdrantClient, models
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client = QdrantClient(url="http://localhost:6333")
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client.query_points(
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collection_name="{collection_name}",
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prefetch=models.Prefetch(
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prefetch=[
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models.Prefetch(
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query=models.SparseVector(indices=[1, 42], values=[0.22, 0.8]),
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using="sparse",
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limit=100,
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),
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models.Prefetch(
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query=[0.01, 0.45, 0.67], # <-- dense vector
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using="dense",
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limit=100,
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),
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],
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query=models.FusionQuery(fusion=models.Fusion.RRF),
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limit=100,
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),
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query=models.FormulaQuery(
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formula=models.SumExpression(
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sum=[
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"$score", # the fused score from the RRF prefetch
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models.ExpDecayExpression(
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exp_decay=models.DecayParamsExpression(
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x=models.DatetimeKeyExpression(datetime_key="published_at"),
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target=models.DatetimeExpression(datetime="YYYY-MM-DDT00:00:00Z"),
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scale=86400 * 180, # 180 days in seconds
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midpoint=0.5,
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)
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),
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]
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)
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),
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limit=10,
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)
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```
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+43
@@ -0,0 +1,43 @@
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```rust
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use qdrant_client::Qdrant;
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use qdrant_client::qdrant::{
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DecayParamsExpressionBuilder, Expression, FormulaBuilder, Fusion, PrefetchQueryBuilder, Query,
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QueryPointsBuilder,
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};
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let client = Qdrant::from_url("http://localhost:6334").build()?;
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client.query(
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QueryPointsBuilder::new("{collection_name}")
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.add_prefetch(
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PrefetchQueryBuilder::default()
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.add_prefetch(
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PrefetchQueryBuilder::default()
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.query(Query::new_nearest([(1, 0.22), (42, 0.8)].as_slice()))
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.using("sparse")
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.limit(100u64),
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)
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.add_prefetch(
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PrefetchQueryBuilder::default()
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.query(Query::new_nearest(vec![0.01, 0.45, 0.67]))
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.using("dense")
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.limit(100u64),
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)
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.query(Query::new_fusion(Fusion::Rrf))
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.limit(100u64),
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)
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.query(
|
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FormulaBuilder::new(Expression::sum_with([
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Expression::score(),
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Expression::exp_decay(
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DecayParamsExpressionBuilder::new(Expression::datetime_key("published_at"))
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.target(Expression::datetime("YYYY-MM-DDT00:00:00Z"))
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.scale(86400.0 * 180.0)
|
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.midpoint(0.5),
|
||||
),
|
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])),
|
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)
|
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.limit(10u64),
|
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)
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.await?;
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```
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+43
@@ -0,0 +1,43 @@
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```typescript
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import { QdrantClient } from "@qdrant/js-client-rest";
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const client = new QdrantClient({ host: "localhost", port: 6333 });
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await client.query("{collection_name}", {
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prefetch: {
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prefetch: [
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{
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query: {
|
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values: [0.22, 0.8],
|
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indices: [1, 42],
|
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},
|
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using: "sparse",
|
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limit: 100,
|
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},
|
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{
|
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query: [0.01, 0.45, 0.67], // <-- dense vector
|
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using: "dense",
|
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limit: 100,
|
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},
|
||||
],
|
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query: { fusion: "rrf" },
|
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limit: 100,
|
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},
|
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query: {
|
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formula: {
|
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sum: [
|
||||
"$score", // the fused score from the RRF prefetch
|
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{
|
||||
exp_decay: {
|
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x: { datetime_key: "published_at" },
|
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target: { datetime: "YYYY-MM-DDT00:00:00Z" },
|
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scale: 86400 * 180, // 180 days in seconds
|
||||
midpoint: 0.5,
|
||||
},
|
||||
},
|
||||
],
|
||||
},
|
||||
},
|
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limit: 10,
|
||||
});
|
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```
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+52
@@ -0,0 +1,52 @@
|
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package snippet
|
||||
|
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import (
|
||||
"context"
|
||||
|
||||
"github.com/qdrant/go-client/qdrant"
|
||||
)
|
||||
|
||||
func Main() {
|
||||
client, err := qdrant.NewClient(&qdrant.Config{
|
||||
Host: "localhost",
|
||||
Port: 6334,
|
||||
})
|
||||
|
||||
if err != nil { panic(err) } // @hide
|
||||
|
||||
client.Query(context.Background(), &qdrant.QueryPoints{
|
||||
CollectionName: "{collection_name}",
|
||||
Prefetch: []*qdrant.PrefetchQuery{
|
||||
{
|
||||
Prefetch: []*qdrant.PrefetchQuery{
|
||||
{
|
||||
Query: qdrant.NewQuerySparse([]uint32{1, 42}, []float32{0.22, 0.8}),
|
||||
Using: qdrant.PtrOf("sparse"),
|
||||
Limit: qdrant.PtrOf(uint64(100)),
|
||||
},
|
||||
{
|
||||
Query: qdrant.NewQueryDense([]float32{0.01, 0.45, 0.67}),
|
||||
Using: qdrant.PtrOf("dense"),
|
||||
Limit: qdrant.PtrOf(uint64(100)),
|
||||
},
|
||||
},
|
||||
Query: qdrant.NewQueryFusion(qdrant.Fusion_RRF),
|
||||
Limit: qdrant.PtrOf(uint64(100)),
|
||||
},
|
||||
},
|
||||
Query: qdrant.NewQueryFormula(&qdrant.Formula{
|
||||
Expression: qdrant.NewExpressionSum(&qdrant.SumExpression{
|
||||
Sum: []*qdrant.Expression{
|
||||
qdrant.NewExpressionVariable("$score"), // the fused score from the RRF prefetch
|
||||
qdrant.NewExpressionExpDecay(&qdrant.DecayParamsExpression{
|
||||
X: qdrant.NewExpressionDatetimeKey("published_at"),
|
||||
Target: qdrant.NewExpressionDatetime("YYYY-MM-DDT00:00:00Z"),
|
||||
Scale: qdrant.PtrOf(float32(86400 * 180)), // 180 days in seconds
|
||||
Midpoint: qdrant.PtrOf(float32(0.5)),
|
||||
}),
|
||||
},
|
||||
}),
|
||||
}),
|
||||
Limit: qdrant.PtrOf(uint64(10)),
|
||||
})
|
||||
}
|
||||
+44
@@ -0,0 +1,44 @@
|
||||
```http
|
||||
POST /collections/{collection_name}/points/query
|
||||
{
|
||||
"prefetch": {
|
||||
"prefetch": [
|
||||
{
|
||||
"query": {
|
||||
"indices": [1, 42], // <┐
|
||||
"values": [0.22, 0.8] // <┴─sparse vector
|
||||
},
|
||||
"using": "sparse",
|
||||
"limit": 100
|
||||
},
|
||||
{
|
||||
"query": [0.01, 0.45, 0.67, ...], // <-- dense vector
|
||||
"using": "dense",
|
||||
"limit": 100
|
||||
}
|
||||
],
|
||||
"query": { "fusion": "rrf" },
|
||||
"limit": 100
|
||||
},
|
||||
"query": {
|
||||
"formula": {
|
||||
"sum": [
|
||||
"$score", // the fused score from the RRF prefetch
|
||||
{
|
||||
"exp_decay": {
|
||||
"x": {
|
||||
"datetime_key": "published_at"
|
||||
},
|
||||
"target": {
|
||||
"datetime": "YYYY-MM-DDT00:00:00Z"
|
||||
},
|
||||
"scale": 15552000, // 180 days in seconds
|
||||
"midpoint": 0.5
|
||||
}
|
||||
}
|
||||
]
|
||||
}
|
||||
},
|
||||
"limit": 10
|
||||
}
|
||||
```
|
||||
+69
@@ -0,0 +1,69 @@
|
||||
package com.example.snippets_amalgamation;
|
||||
|
||||
import static io.qdrant.client.ExpressionFactory.datetime;
|
||||
import static io.qdrant.client.ExpressionFactory.datetimeKey;
|
||||
import static io.qdrant.client.ExpressionFactory.expDecay;
|
||||
import static io.qdrant.client.ExpressionFactory.sum;
|
||||
import static io.qdrant.client.ExpressionFactory.variable;
|
||||
import static io.qdrant.client.QueryFactory.formula;
|
||||
import static io.qdrant.client.QueryFactory.fusion;
|
||||
import static io.qdrant.client.QueryFactory.nearest;
|
||||
|
||||
import io.qdrant.client.QdrantClient;
|
||||
import io.qdrant.client.QdrantGrpcClient;
|
||||
import io.qdrant.client.grpc.Points.DecayParamsExpression;
|
||||
import io.qdrant.client.grpc.Points.Formula;
|
||||
import io.qdrant.client.grpc.Points.Fusion;
|
||||
import io.qdrant.client.grpc.Points.PrefetchQuery;
|
||||
import io.qdrant.client.grpc.Points.QueryPoints;
|
||||
import io.qdrant.client.grpc.Points.SumExpression;
|
||||
import java.util.List;
|
||||
|
||||
public class Snippet {
|
||||
public static void run() throws Exception {
|
||||
QdrantClient client =
|
||||
new QdrantClient(QdrantGrpcClient.newBuilder("localhost", 6334, false).build());
|
||||
|
||||
client.queryAsync(
|
||||
QueryPoints.newBuilder()
|
||||
.setCollectionName("{collection_name}")
|
||||
.addPrefetch(
|
||||
PrefetchQuery.newBuilder()
|
||||
.addPrefetch(
|
||||
PrefetchQuery.newBuilder()
|
||||
.setQuery(nearest(List.of(0.22f, 0.8f), List.of(1, 42)))
|
||||
.setUsing("sparse")
|
||||
.setLimit(100)
|
||||
.build())
|
||||
.addPrefetch(
|
||||
PrefetchQuery.newBuilder()
|
||||
.setQuery(nearest(List.of(0.01f, 0.45f, 0.67f)))
|
||||
.setUsing("dense")
|
||||
.setLimit(100)
|
||||
.build())
|
||||
.setQuery(fusion(Fusion.RRF))
|
||||
.setLimit(100)
|
||||
.build())
|
||||
.setQuery(
|
||||
formula(
|
||||
Formula.newBuilder()
|
||||
.setExpression(
|
||||
sum(
|
||||
SumExpression.newBuilder()
|
||||
.addSum(variable("$score"))
|
||||
.addSum(
|
||||
expDecay(
|
||||
DecayParamsExpression.newBuilder()
|
||||
.setX(datetimeKey("published_at"))
|
||||
.setTarget(
|
||||
datetime("YYYY-MM-DDT00:00:00Z"))
|
||||
.setScale(86400 * 180)
|
||||
.setMidpoint(0.5f)
|
||||
.build()))
|
||||
.build()))
|
||||
.build()))
|
||||
.setLimit(10)
|
||||
.build())
|
||||
.get();
|
||||
}
|
||||
}
|
||||
+39
@@ -0,0 +1,39 @@
|
||||
from qdrant_client import QdrantClient, models
|
||||
|
||||
client = QdrantClient(url="http://localhost:6333")
|
||||
|
||||
client.query_points(
|
||||
collection_name="{collection_name}",
|
||||
prefetch=models.Prefetch(
|
||||
prefetch=[
|
||||
models.Prefetch(
|
||||
query=models.SparseVector(indices=[1, 42], values=[0.22, 0.8]),
|
||||
using="sparse",
|
||||
limit=100,
|
||||
),
|
||||
models.Prefetch(
|
||||
query=[0.01, 0.45, 0.67], # <-- dense vector
|
||||
using="dense",
|
||||
limit=100,
|
||||
),
|
||||
],
|
||||
query=models.FusionQuery(fusion=models.Fusion.RRF),
|
||||
limit=100,
|
||||
),
|
||||
query=models.FormulaQuery(
|
||||
formula=models.SumExpression(
|
||||
sum=[
|
||||
"$score", # the fused score from the RRF prefetch
|
||||
models.ExpDecayExpression(
|
||||
exp_decay=models.DecayParamsExpression(
|
||||
x=models.DatetimeKeyExpression(datetime_key="published_at"),
|
||||
target=models.DatetimeExpression(datetime="YYYY-MM-DDT00:00:00Z"),
|
||||
scale=86400 * 180, # 180 days in seconds
|
||||
midpoint=0.5,
|
||||
)
|
||||
),
|
||||
]
|
||||
)
|
||||
),
|
||||
limit=10,
|
||||
)
|
||||
+45
@@ -0,0 +1,45 @@
|
||||
use qdrant_client::Qdrant;
|
||||
use qdrant_client::qdrant::{
|
||||
DecayParamsExpressionBuilder, Expression, FormulaBuilder, Fusion, PrefetchQueryBuilder, Query,
|
||||
QueryPointsBuilder,
|
||||
};
|
||||
|
||||
pub async fn main() -> anyhow::Result<()> {
|
||||
let client = Qdrant::from_url("http://localhost:6334").build()?;
|
||||
|
||||
client.query(
|
||||
QueryPointsBuilder::new("{collection_name}")
|
||||
.add_prefetch(
|
||||
PrefetchQueryBuilder::default()
|
||||
.add_prefetch(
|
||||
PrefetchQueryBuilder::default()
|
||||
.query(Query::new_nearest([(1, 0.22), (42, 0.8)].as_slice()))
|
||||
.using("sparse")
|
||||
.limit(100u64),
|
||||
)
|
||||
.add_prefetch(
|
||||
PrefetchQueryBuilder::default()
|
||||
.query(Query::new_nearest(vec![0.01, 0.45, 0.67]))
|
||||
.using("dense")
|
||||
.limit(100u64),
|
||||
)
|
||||
.query(Query::new_fusion(Fusion::Rrf))
|
||||
.limit(100u64),
|
||||
)
|
||||
.query(
|
||||
FormulaBuilder::new(Expression::sum_with([
|
||||
Expression::score(),
|
||||
Expression::exp_decay(
|
||||
DecayParamsExpressionBuilder::new(Expression::datetime_key("published_at"))
|
||||
.target(Expression::datetime("YYYY-MM-DDT00:00:00Z"))
|
||||
.scale(86400.0 * 180.0)
|
||||
.midpoint(0.5),
|
||||
),
|
||||
])),
|
||||
)
|
||||
.limit(10u64),
|
||||
)
|
||||
.await?;
|
||||
|
||||
Ok(())
|
||||
}
|
||||
+41
@@ -0,0 +1,41 @@
|
||||
import { QdrantClient } from "@qdrant/js-client-rest";
|
||||
|
||||
const client = new QdrantClient({ host: "localhost", port: 6333 });
|
||||
|
||||
await client.query("{collection_name}", {
|
||||
prefetch: {
|
||||
prefetch: [
|
||||
{
|
||||
query: {
|
||||
values: [0.22, 0.8],
|
||||
indices: [1, 42],
|
||||
},
|
||||
using: "sparse",
|
||||
limit: 100,
|
||||
},
|
||||
{
|
||||
query: [0.01, 0.45, 0.67], // <-- dense vector
|
||||
using: "dense",
|
||||
limit: 100,
|
||||
},
|
||||
],
|
||||
query: { fusion: "rrf" },
|
||||
limit: 100,
|
||||
},
|
||||
query: {
|
||||
formula: {
|
||||
sum: [
|
||||
"$score", // the fused score from the RRF prefetch
|
||||
{
|
||||
exp_decay: {
|
||||
x: { datetime_key: "published_at" },
|
||||
target: { datetime: "YYYY-MM-DDT00:00:00Z" },
|
||||
scale: 86400 * 180, // 180 days in seconds
|
||||
midpoint: 0.5,
|
||||
},
|
||||
},
|
||||
],
|
||||
},
|
||||
},
|
||||
limit: 10,
|
||||
});
|
||||
Reference in New Issue
Block a user