Add code snippets for the text search guide (#2056)

* Python snippets * TS snippets * Rust snippets * Java snippets * C# snippets * Go snippets * Generate .md files * Hide client connection in Rust snippets * Switch to builder pattern for Rust snippets * Use Document::new instead of DocumentBuilder::new * docs: Updated Go snippets Signed-off-by: Anush008 <mail@anush.sh> * docs: Updated Java snippets Signed-off-by: Anush008 <anushshetty90@gmail.com> * docs: Updated C# snippets Signed-off-by: Anush008 <anushshetty90@gmail.com> * docs: Updated BM25 avg_len Java snippet Signed-off-by: Anush008 <anushshetty90@gmail.com> * chore: review and format rust snippets * chore: trigger pr update * chore: remove qdrant_storage folder * fix: remove tokio::main * chore: trigger pr update * Regenerate .md files * George's feedback: set bm25 params at ingest-time, change Python client init to use cloud inference explicitly, and mark bm25 options unavailable in FastEmbed --------- Signed-off-by: Anush008 <mail@anush.sh> Signed-off-by: Anush008 <anushshetty90@gmail.com> Co-authored-by: Anush008 <mail@anush.sh> Co-authored-by: Anush008 <anushshetty90@gmail.com> Co-authored-by: Daniel Boros <dancixx@gmail.com>
2026-10-05 10:58:32 +02:00 · 2026-01-16 17:57:08 +05:30
parent b5e0908946
commit 2497c368ed
329 changed files with 7854 additions and 20 deletions
@@ -14,7 +14,7 @@ Qdrant is a vector search engine, making it a great tool for [semantic search](#
 Semantic search is a search technique that focuses on the meaning of the text rather than just matching on keywords. This is achieved by converting text into [vectors](/documentation/concepts/vectors/) (embeddings) using machine learning models. These vectors capture the semantic meaning of the text, enabling you to find similar text even if it doesn't share exact keywords.

 <aside role="status">
-The examples in this guide use <a href="/documentation/concepts/inference">inference</a> to let Qdrant generate the vectors. Inference is only available on <a href="/documentation/concepts/inference/#qdrant-cloud-inference">Qdrant Cloud</a>, with the exception of the BM25 model. If you are not running on Qdrant Cloud, you can use a library like <a href="/documentation/fastembed/">FastEmbed</a> to generate vectors on the client side.
+The examples in this guide use <a href="/documentation/concepts/inference">inference</a> to let Qdrant generate the vectors. Inference is only available on <a href="/documentation/concepts/inference/#qdrant-cloud-inference">Qdrant Cloud</a>, with the exception of the BM25 model. If you are not running on Qdrant Cloud, you can use a library like <a href="/documentation/fastembed/">FastEmbed</a> to generate vectors on the client side. When using FastEmbed, refer to the documentation, as its API may differ from that of server-side inference.
 </aside>

 For example, to search through a collection of books, you could use a model like the `all-MiniLM-L6-v2` sentence transformer model. First, create a collection and configure a dense vector for the book descriptions:
@@ -197,7 +197,7 @@ After ingesting data, you can query the sparse vector. The following example sea

 #### Configuring BM25 Parameters

-The BM25 [ranking function](https://en.wikipedia.org/wiki/Okapi_BM25#The_ranking_function) includes three adjustable parameters that you can set to optimize search results for your specific use case:
+The BM25 [ranking function](https://en.wikipedia.org/wiki/Okapi_BM25#The_ranking_function) includes three adjustable parameters that you can set at ingest time to optimize search results for your specific use case:

 - `k`. Controls term frequency saturation. Higher values increase the influence of term frequency. Defaults to 1.2.
 - `b`. Controls document length normalization. Ranges from 0 (no normalization) to 1 (full normalization). A higher value means longer documents have less impact. Defaults to 0.75.
@@ -205,7 +205,7 @@ The BM25 [ranking function](https://en.wikipedia.org/wiki/Okapi_BM25#The_ranking

 For instance, book titles are generally shorter than 256 words. To achieve more accurate scoring when searching for book titles, you could calculate or estimate the average title length and set the `avg_len` parameter accordingly:

-{{< code-snippet path="/documentation/headless/snippets/text-search/query-bm25-avglen/" >}}
+{{< code-snippet path="/documentation/headless/snippets/text-search/ingest-bm25-avglen/" >}}

 #### Language-specific Settings

@@ -0,0 +1,51 @@
+using Qdrant.Client;
+using Qdrant.Client.Grpc;
+using static Qdrant.Client.Grpc.Conditions;
+
+public class Snippet
+{
+    public static async Task Run()
+    {
+        var client = new QdrantClient("localhost", 6334); // @hide
+
+        var searchStrict = new QueryPoints
+        {
+            CollectionName = "books",
+            Query = new Document
+            {
+                Text = "time travel",
+                Model = "sentence-transformers/all-minilm-l6-v2",
+            },
+            Using = "description-dense",
+            Filter = new Filter { Must = { MatchText("title", "time travel") } },
+        };
+
+        var searchRelaxed = new QueryPoints
+        {
+            CollectionName = "books",
+            Query = new Document
+            {
+                Text = "time travel",
+                Model = "sentence-transformers/all-minilm-l6-v2",
+            },
+            Using = "description-dense",
+            Filter = new Filter { Must = { MatchTextAny("title", "time travel") } },
+        };
+
+        var searchVectorOnly = new QueryPoints
+        {
+            CollectionName = "books",
+            Query = new Document
+            {
+                Text = "time travel",
+                Model = "sentence-transformers/all-minilm-l6-v2",
+            },
+            Using = "description-dense",
+        };
+
+        await client.QueryBatchAsync(
+            collectionName: "books",
+            queries: new List<QueryPoints> { searchStrict, searchRelaxed, searchVectorOnly }
+        );
+    }
+}
@@ -0,0 +1,45 @@
+```csharp
+using Qdrant.Client;
+using Qdrant.Client.Grpc;
+using static Qdrant.Client.Grpc.Conditions;
+
+var searchStrict = new QueryPoints
+{
+    CollectionName = "books",
+    Query = new Document
+    {
+        Text = "time travel",
+        Model = "sentence-transformers/all-minilm-l6-v2",
+    },
+    Using = "description-dense",
+    Filter = new Filter { Must = { MatchText("title", "time travel") } },
+};
+
+var searchRelaxed = new QueryPoints
+{
+    CollectionName = "books",
+    Query = new Document
+    {
+        Text = "time travel",
+        Model = "sentence-transformers/all-minilm-l6-v2",
+    },
+    Using = "description-dense",
+    Filter = new Filter { Must = { MatchTextAny("title", "time travel") } },
+};
+
+var searchVectorOnly = new QueryPoints
+{
+    CollectionName = "books",
+    Query = new Document
+    {
+        Text = "time travel",
+        Model = "sentence-transformers/all-minilm-l6-v2",
+    },
+    Using = "description-dense",
+};
+
+await client.QueryBatchAsync(
+    collectionName: "books",
+    queries: new List<QueryPoints> { searchStrict, searchRelaxed, searchVectorOnly }
+);
+```
@@ -0,0 +1,32 @@
+```go
+strict := &qdrant.QueryPoints{
+	CollectionName: "books",
+	Query: qdrant.NewQueryNearest(
+		qdrant.NewVectorInputDocument(&qdrant.Document{Model: "sentence-transformers/all-minilm-l6-v2", Text: "time travel"}),
+	),
+	Using:  qdrant.PtrOf("description-dense"),
+	Filter: &qdrant.Filter{Must: []*qdrant.Condition{qdrant.NewMatchText("title", "time travel")}},
+}
+
+relaxed := &qdrant.QueryPoints{
+	CollectionName: "books",
+	Query: qdrant.NewQueryNearest(
+		qdrant.NewVectorInputDocument(&qdrant.Document{Model: "sentence-transformers/all-minilm-l6-v2", Text: "time travel"}),
+	),
+	Using:  qdrant.PtrOf("description-dense"),
+	Filter: &qdrant.Filter{Must: []*qdrant.Condition{qdrant.NewMatchTextAny("title", "time travel")}},
+}
+
+vectorOnly := &qdrant.QueryPoints{
+	CollectionName: "books",
+	Query: qdrant.NewQueryNearest(
+		qdrant.NewVectorInputDocument(&qdrant.Document{Model: "sentence-transformers/all-minilm-l6-v2", Text: "time travel"}),
+	),
+	Using: qdrant.PtrOf("description-dense"),
+}
+
+client.QueryBatch(context.Background(), &qdrant.QueryBatchPoints{
+	CollectionName: "books",
+	QueryPoints:    []*qdrant.QueryPoints{strict, relaxed, vectorOnly},
+})
+```
@@ -0,0 +1,56 @@
+```java
+import static io.qdrant.client.ConditionFactory.*;
+import static io.qdrant.client.QueryFactory.nearest;
+import static io.qdrant.client.WithPayloadSelectorFactory.enable;
+
+import io.qdrant.client.QdrantClient;
+import io.qdrant.client.QdrantGrpcClient;
+import io.qdrant.client.grpc.Common.Filter;
+import io.qdrant.client.grpc.Points.*;
+import java.util.*;
+
+QdrantClient client =
+
+QueryPoints searchStrict =
+    QueryPoints.newBuilder()
+        .setCollectionName("books")
+        .setQuery(
+            nearest(
+                Document.newBuilder()
+                    .setText("time travel")
+                    .setModel("sentence-transformers/all-minilm-l6-v2")
+                    .build()))
+        .setUsing("description-dense")
+        .setFilter(Filter.newBuilder().addMust(matchText("title", "time travel")).build())
+        .setWithPayload(enable(true))
+        .build();
+
+QueryPoints searchRelaxed =
+    QueryPoints.newBuilder()
+        .setCollectionName("books")
+        .setQuery(
+            nearest(
+                Document.newBuilder()
+                    .setText("time travel")
+                    .setModel("sentence-transformers/all-minilm-l6-v2")
+                    .build()))
+        .setUsing("description-dense")
+        .setFilter(Filter.newBuilder().addMust(matchTextAny("title", "time travel")).build())
+        .setWithPayload(enable(true))
+        .build();
+
+QueryPoints searchVectorOnly =
+    QueryPoints.newBuilder()
+        .setCollectionName("books")
+        .setQuery(
+            nearest(
+                Document.newBuilder()
+                    .setText("time travel")
+                    .setModel("sentence-transformers/all-minilm-l6-v2")
+                    .build()))
+        .setUsing("description-dense")
+        .setWithPayload(enable(true))
+        .build();
+
+client.queryBatchAsync("books", List.of(searchStrict, searchRelaxed, searchVectorOnly)).get();
+```
@@ -0,0 +1,36 @@
+```python
+from qdrant_client import QdrantClient, models
+
+client = QdrantClient(
+    url="https://xyz-example.qdrant.io:6333",
+    api_key="<your-api-key>",
+    cloud_inference=True,
+)
+
+client.query_batch_points(
+    collection_name="books",
+    requests=[
+        models.QueryRequest(
+            query=models.Document(text="time travel", model="sentence-transformers/all-minilm-l6-v2"),
+            using="description-dense",
+            with_payload=True,
+            filter=models.Filter(
+                must=[models.FieldCondition(key="title", match=models.MatchText(text="time travel"))]
+            ),
+        ),
+        models.QueryRequest(
+            query=models.Document(text="time travel", model="sentence-transformers/all-minilm-l6-v2"),
+            using="description-dense",
+            with_payload=True,
+            filter=models.Filter(
+                must=[models.FieldCondition(key="title", match=models.MatchTextAny(text_any="time travel"))]
+            ),
+        ),
+        models.QueryRequest(
+            query=models.Document(text="time travel", model="sentence-transformers/all-minilm-l6-v2"),
+            using="description-dense",
+            with_payload=True,
+        ),
+    ],
+)
+```
@@ -0,0 +1,42 @@
+```rust
+use qdrant_client::Qdrant;
+use qdrant_client::qdrant::{
+    Condition, Document, Filter, Query, QueryBatchPointsBuilder, QueryPointsBuilder,
+};
+
+let strict_filter = Filter::must([Condition::matches("title", "time travel".to_string())]);
+let relaxed_filter = Filter::must([Condition::matches("title", "time travel".to_string())]);
+
+let searches = vec![
+    QueryPointsBuilder::new("books")
+        .query(Query::new_nearest(Document::new(
+            "time travel",
+            "sentence-transformers/all-minilm-l6-v2",
+        )))
+        .using("description-dense")
+        .filter(strict_filter)
+        .with_payload(true)
+        .build(),
+    QueryPointsBuilder::new("books")
+        .query(Query::new_nearest(Document::new(
+            "time travel",
+            "sentence-transformers/all-minilm-l6-v2",
+        )))
+        .using("description-dense")
+        .filter(relaxed_filter)
+        .with_payload(true)
+        .build(),
+    QueryPointsBuilder::new("books")
+        .query(Query::new_nearest(Document::new(
+            "time travel",
+            "sentence-transformers/all-minilm-l6-v2",
+        )))
+        .using("description-dense")
+        .with_payload(true)
+        .build(),
+];
+
+client
+    .query_batch(QueryBatchPointsBuilder::new("books", searches))
+    .await?;
+```
@@ -0,0 +1,27 @@
+```typescript
+client.queryBatch("books", {
+  searches: [
+    {
+      query: { text: "time travel", model: "sentence-transformers/all-minilm-l6-v2" },
+      using: "description-dense",
+      with_payload: true,
+      filter: {
+        must: [{ key: "title", match: { text: "time travel" } }],
+      },
+    },
+    {
+      query: { text: "time travel", model: "sentence-transformers/all-minilm-l6-v2" },
+      using: "description-dense",
+      with_payload: true,
+      filter: {
+        must: [{ key: "title", match: { text_any: "time travel" } }],
+      },
+    },
+    {
+      query: { text: "time travel", model: "sentence-transformers/all-minilm-l6-v2" },
+      using: "description-dense",
+      with_payload: true,
+    },
+  ],
+});
+```
@@ -0,0 +1,54 @@
+package snippet
+
+// @hide-start
+import (
+	"context"
+
+	"github.com/qdrant/go-client/qdrant"
+)
+
+// @hide-end
+func Main() {
+	//@hide-start
+	client, err := qdrant.NewClient(&qdrant.Config{
+		Host: "localhost",
+		Port: 6334,
+	})
+
+	if err != nil {
+		panic(err)
+	}
+	// @hide-end
+
+	strict := &qdrant.QueryPoints{
+		CollectionName: "books",
+		Query: qdrant.NewQueryNearest(
+			qdrant.NewVectorInputDocument(&qdrant.Document{Model: "sentence-transformers/all-minilm-l6-v2", Text: "time travel"}),
+		),
+		Using:  qdrant.PtrOf("description-dense"),
+		Filter: &qdrant.Filter{Must: []*qdrant.Condition{qdrant.NewMatchText("title", "time travel")}},
+	}
+
+	relaxed := &qdrant.QueryPoints{
+		CollectionName: "books",
+		Query: qdrant.NewQueryNearest(
+			qdrant.NewVectorInputDocument(&qdrant.Document{Model: "sentence-transformers/all-minilm-l6-v2", Text: "time travel"}),
+		),
+		Using:  qdrant.PtrOf("description-dense"),
+		Filter: &qdrant.Filter{Must: []*qdrant.Condition{qdrant.NewMatchTextAny("title", "time travel")}},
+	}
+
+	vectorOnly := &qdrant.QueryPoints{
+		CollectionName: "books",
+		Query: qdrant.NewQueryNearest(
+			qdrant.NewVectorInputDocument(&qdrant.Document{Model: "sentence-transformers/all-minilm-l6-v2", Text: "time travel"}),
+		),
+		Using: qdrant.PtrOf("description-dense"),
+	}
+
+	client.QueryBatch(context.Background(), &qdrant.QueryBatchPoints{
+		CollectionName: "books",
+		QueryPoints:    []*qdrant.QueryPoints{strict, relaxed, vectorOnly},
+	})
+
+}
@@ -0,0 +1,61 @@
+package com.example.snippets_amalgamation;
+
+import static io.qdrant.client.ConditionFactory.*;
+import static io.qdrant.client.QueryFactory.nearest;
+import static io.qdrant.client.WithPayloadSelectorFactory.enable;
+
+import io.qdrant.client.QdrantClient;
+import io.qdrant.client.QdrantGrpcClient;
+import io.qdrant.client.grpc.Common.Filter;
+import io.qdrant.client.grpc.Points.*;
+import java.util.*;
+
+public class Snippet {
+  public static void run() throws Exception {
+    QdrantClient client =
+        new QdrantClient(QdrantGrpcClient.newBuilder("localhost", 6334, false).build()); // @hide
+
+    QueryPoints searchStrict =
+        QueryPoints.newBuilder()
+            .setCollectionName("books")
+            .setQuery(
+                nearest(
+                    Document.newBuilder()
+                        .setText("time travel")
+                        .setModel("sentence-transformers/all-minilm-l6-v2")
+                        .build()))
+            .setUsing("description-dense")
+            .setFilter(Filter.newBuilder().addMust(matchText("title", "time travel")).build())
+            .setWithPayload(enable(true))
+            .build();
+
+    QueryPoints searchRelaxed =
+        QueryPoints.newBuilder()
+            .setCollectionName("books")
+            .setQuery(
+                nearest(
+                    Document.newBuilder()
+                        .setText("time travel")
+                        .setModel("sentence-transformers/all-minilm-l6-v2")
+                        .build()))
+            .setUsing("description-dense")
+            .setFilter(Filter.newBuilder().addMust(matchTextAny("title", "time travel")).build())
+            .setWithPayload(enable(true))
+            .build();
+
+    QueryPoints searchVectorOnly =
+        QueryPoints.newBuilder()
+            .setCollectionName("books")
+            .setQuery(
+                nearest(
+                    Document.newBuilder()
+                        .setText("time travel")
+                        .setModel("sentence-transformers/all-minilm-l6-v2")
+                        .build()))
+            .setUsing("description-dense")
+            .setWithPayload(enable(true))
+            .build();
+
+    client.queryBatchAsync("books", List.of(searchStrict, searchRelaxed, searchVectorOnly)).get();
+  }
+}
@@ -0,0 +1,34 @@
+from qdrant_client import QdrantClient, models
+
+client = QdrantClient(
+    url="https://xyz-example.qdrant.io:6333",
+    api_key="<your-api-key>",
+    cloud_inference=True,
+)
+
+client.query_batch_points(
+    collection_name="books",
+    requests=[
+        models.QueryRequest(
+            query=models.Document(text="time travel", model="sentence-transformers/all-minilm-l6-v2"),
+            using="description-dense",
+            with_payload=True,
+            filter=models.Filter(
+                must=[models.FieldCondition(key="title", match=models.MatchText(text="time travel"))]
+            ),
+        ),
+        models.QueryRequest(
+            query=models.Document(text="time travel", model="sentence-transformers/all-minilm-l6-v2"),
+            using="description-dense",
+            with_payload=True,
+            filter=models.Filter(
+                must=[models.FieldCondition(key="title", match=models.MatchTextAny(text_any="time travel"))]
+            ),
+        ),
+        models.QueryRequest(
+            query=models.Document(text="time travel", model="sentence-transformers/all-minilm-l6-v2"),
+            using="description-dense",
+            with_payload=True,
+        ),
+    ],
+)
@@ -0,0 +1,46 @@
+use qdrant_client::Qdrant;
+use qdrant_client::qdrant::{
+    Condition, Document, Filter, Query, QueryBatchPointsBuilder, QueryPointsBuilder,
+};
+
+pub async fn main() -> anyhow::Result<()> {
+    let client = Qdrant::from_url("http://localhost:6334").build()?; // @hide
+
+    let strict_filter = Filter::must([Condition::matches("title", "time travel".to_string())]);
+    let relaxed_filter = Filter::must([Condition::matches("title", "time travel".to_string())]);
+
+    let searches = vec![
+        QueryPointsBuilder::new("books")
+            .query(Query::new_nearest(Document::new(
+                "time travel",
+                "sentence-transformers/all-minilm-l6-v2",
+            )))
+            .using("description-dense")
+            .filter(strict_filter)
+            .with_payload(true)
+            .build(),
+        QueryPointsBuilder::new("books")
+            .query(Query::new_nearest(Document::new(
+                "time travel",
+                "sentence-transformers/all-minilm-l6-v2",
+            )))
+            .using("description-dense")
+            .filter(relaxed_filter)
+            .with_payload(true)
+            .build(),
+        QueryPointsBuilder::new("books")
+            .query(Query::new_nearest(Document::new(
+                "time travel",
+                "sentence-transformers/all-minilm-l6-v2",
+            )))
+            .using("description-dense")
+            .with_payload(true)
+            .build(),
+    ];
+
+    client
+        .query_batch(QueryBatchPointsBuilder::new("books", searches))
+        .await?;
+
+    Ok(())
+}
@@ -0,0 +1,29 @@
+import { QdrantClient } from "@qdrant/js-client-rest"; // @hide
+
+const client = new QdrantClient({ host: "localhost", port: 6333 }); // @hide
+
+client.queryBatch("books", {
+  searches: [
+    {
+      query: { text: "time travel", model: "sentence-transformers/all-minilm-l6-v2" },
+      using: "description-dense",
+      with_payload: true,
+      filter: {
+        must: [{ key: "title", match: { text: "time travel" } }],
+      },
+    },
+    {
+      query: { text: "time travel", model: "sentence-transformers/all-minilm-l6-v2" },
+      using: "description-dense",
+      with_payload: true,
+      filter: {
+        must: [{ key: "title", match: { text_any: "time travel" } }],
+      },
+    },
+    {
+      query: { text: "time travel", model: "sentence-transformers/all-minilm-l6-v2" },
+      using: "description-dense",
+      with_payload: true,
+    },
+  ],
+});
@@ -0,0 +1,16 @@
+using Qdrant.Client;
+using Qdrant.Client.Grpc;
+
+public class Snippet
+{
+    public static async Task Run()
+    {
+        var client = new QdrantClient("localhost", 6334); // @hide
+
+        await client.CreatePayloadIndexAsync(
+            collectionName: "books",
+            fieldName: "author",
+            schemaType: PayloadSchemaType.Keyword
+        );
+    }
+}
@@ -0,0 +1,10 @@
+```csharp
+using Qdrant.Client;
+using Qdrant.Client.Grpc;
+
+await client.CreatePayloadIndexAsync(
+    collectionName: "books",
+    fieldName: "author",
+    schemaType: PayloadSchemaType.Keyword
+);
+```
@@ -0,0 +1,7 @@
+```go
+client.CreateFieldIndex(context.Background(), &qdrant.CreateFieldIndexCollection{
+	CollectionName: "books",
+	FieldName:      "author",
+	FieldType:      qdrant.FieldType_FieldTypeKeyword.Enum(),
+})
+```
@@ -0,0 +1,12 @@
+```java
+import io.qdrant.client.QdrantClient;
+import io.qdrant.client.QdrantGrpcClient;
+import io.qdrant.client.grpc.Collections.PayloadSchemaType;
+
+QdrantClient client =
+
+client
+    .createPayloadIndexAsync(
+        "books", "author", PayloadSchemaType.Keyword, null, null, null, null)
+    .get();
+```
@@ -0,0 +1,15 @@
+```python
+from qdrant_client import QdrantClient, models
+
+client = QdrantClient(
+    url="https://xyz-example.qdrant.io:6333",
+    api_key="<your-api-key>",
+    cloud_inference=True,
+)
+
+client.create_payload_index(
+    collection_name="books",
+    field_name="author",
+    field_schema=models.PayloadSchemaType.KEYWORD
+)
+```
@@ -0,0 +1,12 @@
+```rust
+use qdrant_client::Qdrant;
+use qdrant_client::qdrant::{CreateFieldIndexCollectionBuilder, FieldType};
+
+client
+    .create_field_index(CreateFieldIndexCollectionBuilder::new(
+        "books",
+        "author",
+        FieldType::Keyword,
+    ))
+    .await?;
+```
@@ -0,0 +1,6 @@
+```typescript
+client.createPayloadIndex("books", {
+  field_name: "author",
+  field_schema: "keyword",
+});
+```
@@ -0,0 +1,29 @@
+package snippet
+
+// @hide-start
+import (
+	"context"
+
+	"github.com/qdrant/go-client/qdrant"
+)
+
+// @hide-end
+func Main() {
+	//@hide-start
+	client, err := qdrant.NewClient(&qdrant.Config{
+		Host: "localhost",
+		Port: 6334,
+	})
+
+	if err != nil {
+		panic(err)
+	}
+	// @hide-end
+
+	client.CreateFieldIndex(context.Background(), &qdrant.CreateFieldIndexCollection{
+		CollectionName: "books",
+		FieldName:      "author",
+		FieldType:      qdrant.FieldType_FieldTypeKeyword.Enum(),
+	})
+
+}
@@ -0,0 +1,17 @@
+package com.example.snippets_amalgamation;
+
+import io.qdrant.client.QdrantClient;
+import io.qdrant.client.QdrantGrpcClient;
+import io.qdrant.client.grpc.Collections.PayloadSchemaType;
+
+public class Snippet {
+  public static void run() throws Exception {
+    QdrantClient client =
+        new QdrantClient(QdrantGrpcClient.newBuilder("localhost", 6334, false).build()); // @hide
+
+    client
+        .createPayloadIndexAsync(
+            "books", "author", PayloadSchemaType.Keyword, null, null, null, null)
+        .get();
+  }
+}
@@ -0,0 +1,13 @@
+from qdrant_client import QdrantClient, models
+
+client = QdrantClient(
+    url="https://xyz-example.qdrant.io:6333",
+    api_key="<your-api-key>",
+    cloud_inference=True,
+)
+
+client.create_payload_index(
+    collection_name="books",
+    field_name="author",
+    field_schema=models.PayloadSchemaType.KEYWORD
+)
@@ -0,0 +1,16 @@
+use qdrant_client::Qdrant;
+use qdrant_client::qdrant::{CreateFieldIndexCollectionBuilder, FieldType};
+
+pub async fn main() -> anyhow::Result<()> {
+    let client = Qdrant::from_url("http://localhost:6334").build()?; // @hide
+
+    client
+        .create_field_index(CreateFieldIndexCollectionBuilder::new(
+            "books",
+            "author",
+            FieldType::Keyword,
+        ))
+        .await?;
+
+    Ok(())
+}
@@ -0,0 +1,8 @@
+import { QdrantClient } from "@qdrant/js-client-rest"; // @hide
+
+const client = new QdrantClient({ host: "localhost", port: 6333 }); // @hide
+
+client.createPayloadIndex("books", {
+  field_name: "author",
+  field_schema: "keyword",
+});
@@ -0,0 +1,15 @@
+using Qdrant.Client;
+using Qdrant.Client.Grpc;
+
+public class Snippet
+{
+    public static async Task Run()
+    {
+        var client = new QdrantClient("localhost", 6334); // @hide
+
+        await client.CreateCollectionAsync(
+            collectionName: "books",
+            sparseVectorsConfig: ("title-bm25", new SparseVectorParams { Modifier = Modifier.Idf })
+        );
+    }
+}
@@ -0,0 +1,9 @@
+```csharp
+using Qdrant.Client;
+using Qdrant.Client.Grpc;
+
+await client.CreateCollectionAsync(
+    collectionName: "books",
+    sparseVectorsConfig: ("title-bm25", new SparseVectorParams { Modifier = Modifier.Idf })
+);
+```
@@ -0,0 +1,9 @@
+```go
+client.CreateCollection(context.Background(), &qdrant.CreateCollection{
+	CollectionName: "books",
+	SparseVectorsConfig: qdrant.NewSparseVectorsConfig(
+		map[string]*qdrant.SparseVectorParams{
+			"title-bm25": {Modifier: qdrant.Modifier_Idf.Enum()},
+		}),
+})
+```
@@ -0,0 +1,20 @@
+```java
+import io.qdrant.client.QdrantClient;
+import io.qdrant.client.QdrantGrpcClient;
+import io.qdrant.client.grpc.Collections.*;
+
+QdrantClient client =
+
+client
+    .createCollectionAsync(
+        CreateCollection.newBuilder()
+            .setCollectionName("books")
+            .setSparseVectorsConfig(
+                SparseVectorConfig.newBuilder()
+                    .putMap(
+                        "title-bm25",
+                        SparseVectorParams.newBuilder().setModifier(Modifier.Idf).build())
+                    .build())
+            .build())
+    .get();
+```
@@ -0,0 +1,16 @@
+```python
+from qdrant_client import QdrantClient, models
+
+client = QdrantClient(
+    url="https://xyz-example.qdrant.io:6333",
+    api_key="<your-api-key>",
+    cloud_inference=True,
+)
+
+client.create_collection(
+    collection_name="books",
+    sparse_vectors_config={
+        "title-bm25": models.SparseVectorParams(modifier=models.Modifier.IDF)
+    },
+)
+```
@@ -0,0 +1,16 @@
+```rust
+use qdrant_client::Qdrant;
+use qdrant_client::qdrant::{
+    CreateCollectionBuilder, Modifier, SparseVectorParamsBuilder, SparseVectorsConfigBuilder,
+};
+
+let mut sparse = SparseVectorsConfigBuilder::default();
+sparse.add_named_vector_params(
+    "title-bm25",
+    SparseVectorParamsBuilder::default().modifier(Modifier::Idf),
+);
+
+client
+    .create_collection(CreateCollectionBuilder::new("books").sparse_vectors_config(sparse))
+    .await?;
+```
@@ -0,0 +1,7 @@
+```typescript
+client.createCollection("books", {
+  sparse_vectors: {
+    "title-bm25": { modifier: "idf" },
+  },
+});
+```
@@ -0,0 +1,31 @@
+package snippet
+
+// @hide-start
+import (
+	"context"
+
+	"github.com/qdrant/go-client/qdrant"
+)
+
+// @hide-end
+func Main() {
+	//@hide-start
+	client, err := qdrant.NewClient(&qdrant.Config{
+		Host: "localhost",
+		Port: 6334,
+	})
+
+	if err != nil {
+		panic(err)
+	}
+	// @hide-end
+
+	client.CreateCollection(context.Background(), &qdrant.CreateCollection{
+		CollectionName: "books",
+		SparseVectorsConfig: qdrant.NewSparseVectorsConfig(
+			map[string]*qdrant.SparseVectorParams{
+				"title-bm25": {Modifier: qdrant.Modifier_Idf.Enum()},
+			}),
+	})
+
+}
@@ -0,0 +1,25 @@
+package com.example.snippets_amalgamation;
+
+import io.qdrant.client.QdrantClient;
+import io.qdrant.client.QdrantGrpcClient;
+import io.qdrant.client.grpc.Collections.*;
+
+public class Snippet {
+  public static void run() throws Exception {
+    QdrantClient client =
+        new QdrantClient(QdrantGrpcClient.newBuilder("localhost", 6334, false).build()); // @hide
+
+    client
+        .createCollectionAsync(
+            CreateCollection.newBuilder()
+                .setCollectionName("books")
+                .setSparseVectorsConfig(
+                    SparseVectorConfig.newBuilder()
+                        .putMap(
+                            "title-bm25",
+                            SparseVectorParams.newBuilder().setModifier(Modifier.Idf).build())
+                        .build())
+                .build())
+        .get();
+  }
+}
@@ -0,0 +1,14 @@
+from qdrant_client import QdrantClient, models
+
+client = QdrantClient(
+    url="https://xyz-example.qdrant.io:6333",
+    api_key="<your-api-key>",
+    cloud_inference=True,
+)
+
+client.create_collection(
+    collection_name="books",
+    sparse_vectors_config={
+        "title-bm25": models.SparseVectorParams(modifier=models.Modifier.IDF)
+    },
+)
@@ -0,0 +1,20 @@
+use qdrant_client::Qdrant;
+use qdrant_client::qdrant::{
+    CreateCollectionBuilder, Modifier, SparseVectorParamsBuilder, SparseVectorsConfigBuilder,
+};
+
+pub async fn main() -> anyhow::Result<()> {
+    let client = Qdrant::from_url("http://localhost:6334").build()?; // @hide
+
+    let mut sparse = SparseVectorsConfigBuilder::default();
+    sparse.add_named_vector_params(
+        "title-bm25",
+        SparseVectorParamsBuilder::default().modifier(Modifier::Idf),
+    );
+
+    client
+        .create_collection(CreateCollectionBuilder::new("books").sparse_vectors_config(sparse))
+        .await?;
+
+    Ok(())
+}
@@ -0,0 +1,9 @@
+import { QdrantClient } from "@qdrant/js-client-rest"; // @hide
+
+const client = new QdrantClient({ host: "localhost", port: 6333 }); // @hide
+
+client.createCollection("books", {
+  sparse_vectors: {
+    "title-bm25": { modifier: "idf" },
+  },
+});
@@ -0,0 +1,25 @@
+using Qdrant.Client;
+using Qdrant.Client.Grpc;
+
+public class Snippet
+{
+    public static async Task Run()
+    {
+        var client = new QdrantClient("localhost", 6334); // @hide
+
+        await client.CreateCollectionAsync(
+            collectionName: "books",
+            vectorsConfig: new VectorParamsMap
+            {
+                Map =
+                {
+                    ["description-dense"] = new VectorParams
+                    {
+                        Size = 384,
+                        Distance = Distance.Cosine,
+                    },
+                },
+            }
+        );
+    }
+}
@@ -0,0 +1,19 @@
+```csharp
+using Qdrant.Client;
+using Qdrant.Client.Grpc;
+
+await client.CreateCollectionAsync(
+    collectionName: "books",
+    vectorsConfig: new VectorParamsMap
+    {
+        Map =
+        {
+            ["description-dense"] = new VectorParams
+            {
+                Size = 384,
+                Distance = Distance.Cosine,
+            },
+        },
+    }
+);
+```
@@ -0,0 +1,12 @@
+```go
+client.CreateCollection(context.Background(), &qdrant.CreateCollection{
+	CollectionName: "books",
+	VectorsConfig: qdrant.NewVectorsConfigMap(
+		map[string]*qdrant.VectorParams{
+			"description-dense": {
+				Size:     384,
+				Distance: qdrant.Distance_Cosine,
+			},
+		}),
+})
+```
@@ -0,0 +1,26 @@
+```java
+import io.qdrant.client.QdrantClient;
+import io.qdrant.client.QdrantGrpcClient;
+import io.qdrant.client.grpc.Collections.*;
+
+QdrantClient client =
+
+client
+    .createCollectionAsync(
+        CreateCollection.newBuilder()
+            .setCollectionName("books")
+            .setVectorsConfig(
+                VectorsConfig.newBuilder()
+                    .setParamsMap(
+                        VectorParamsMap.newBuilder()
+                            .putMap(
+                                "description-dense",
+                                VectorParams.newBuilder()
+                                    .setSize(384)
+                                    .setDistance(Distance.Cosine)
+                                    .build())
+                            .build())
+                    .build())
+            .build())
+    .get();
+```
@@ -0,0 +1,16 @@
+```python
+from qdrant_client import QdrantClient, models
+
+client = QdrantClient(
+    url="https://xyz-example.qdrant.io:6333",
+    api_key="<your-api-key>",
+    cloud_inference=True,
+)
+
+client.create_collection(
+    collection_name="books",
+    vectors_config={
+        "description-dense": models.VectorParams(size=384, distance=models.Distance.COSINE)
+    },
+)
+```
@@ -0,0 +1,16 @@
+```rust
+use qdrant_client::Qdrant;
+use qdrant_client::qdrant::{
+    CreateCollectionBuilder, Distance, VectorParamsBuilder, VectorsConfigBuilder,
+};
+
+let mut vectors_config = VectorsConfigBuilder::default();
+vectors_config.add_named_vector_params(
+    "description-dense",
+    VectorParamsBuilder::new(384, Distance::Cosine),
+);
+
+client
+    .create_collection(CreateCollectionBuilder::new("books").vectors_config(vectors_config))
+    .await?;
+```
@@ -0,0 +1,7 @@
+```typescript
+client.createCollection("books", {
+  vectors: {
+    "description-dense": { size: 384, distance: "Cosine" },
+  },
+});
+```
@@ -0,0 +1,34 @@
+package snippet
+
+// @hide-start
+import (
+	"context"
+
+	"github.com/qdrant/go-client/qdrant"
+)
+
+// @hide-end
+func Main() {
+	//@hide-start
+	client, err := qdrant.NewClient(&qdrant.Config{
+		Host: "localhost",
+		Port: 6334,
+	})
+
+	if err != nil {
+		panic(err)
+	}
+	// @hide-end
+
+	client.CreateCollection(context.Background(), &qdrant.CreateCollection{
+		CollectionName: "books",
+		VectorsConfig: qdrant.NewVectorsConfigMap(
+			map[string]*qdrant.VectorParams{
+				"description-dense": {
+					Size:     384,
+					Distance: qdrant.Distance_Cosine,
+				},
+			}),
+	})
+
+}
@@ -0,0 +1,31 @@
+package com.example.snippets_amalgamation;
+
+import io.qdrant.client.QdrantClient;
+import io.qdrant.client.QdrantGrpcClient;
+import io.qdrant.client.grpc.Collections.*;
+
+public class Snippet {
+  public static void run() throws Exception {
+    QdrantClient client =
+        new QdrantClient(QdrantGrpcClient.newBuilder("localhost", 6334, false).build()); // @hide
+
+    client
+        .createCollectionAsync(
+            CreateCollection.newBuilder()
+                .setCollectionName("books")
+                .setVectorsConfig(
+                    VectorsConfig.newBuilder()
+                        .setParamsMap(
+                            VectorParamsMap.newBuilder()
+                                .putMap(
+                                    "description-dense",
+                                    VectorParams.newBuilder()
+                                        .setSize(384)
+                                        .setDistance(Distance.Cosine)
+                                        .build())
+                                .build())
+                        .build())
+                .build())
+        .get();
+  }
+}
@@ -0,0 +1,14 @@
+from qdrant_client import QdrantClient, models
+
+client = QdrantClient(
+    url="https://xyz-example.qdrant.io:6333",
+    api_key="<your-api-key>",
+    cloud_inference=True,
+)
+
+client.create_collection(
+    collection_name="books",
+    vectors_config={
+        "description-dense": models.VectorParams(size=384, distance=models.Distance.COSINE)
+    },
+)
@@ -0,0 +1,20 @@
+use qdrant_client::Qdrant;
+use qdrant_client::qdrant::{
+    CreateCollectionBuilder, Distance, VectorParamsBuilder, VectorsConfigBuilder,
+};
+
+pub async fn main() -> anyhow::Result<()> {
+    let client = Qdrant::from_url("http://localhost:6334").build()?; // @hide
+
+    let mut vectors_config = VectorsConfigBuilder::default();
+    vectors_config.add_named_vector_params(
+        "description-dense",
+        VectorParamsBuilder::new(384, Distance::Cosine),
+    );
+
+    client
+        .create_collection(CreateCollectionBuilder::new("books").vectors_config(vectors_config))
+        .await?;
+
+    Ok(())
+}
@@ -0,0 +1,9 @@
+import { QdrantClient } from "@qdrant/js-client-rest"; // @hide
+
+const client = new QdrantClient({ host: "localhost", port: 6333 }); // @hide
+
+client.createCollection("books", {
+  vectors: {
+    "description-dense": { size: 384, distance: "Cosine" },
+  },
+});
@@ -0,0 +1,29 @@
+using Qdrant.Client;
+using Qdrant.Client.Grpc;
+
+public class Snippet
+{
+    public static async Task Run()
+    {
+        var client = new QdrantClient("localhost", 6334); // @hide
+
+        await client.CreateCollectionAsync(
+            collectionName: "books",
+            vectorsConfig: new VectorParamsMap
+            {
+                Map =
+                {
+                    ["description-dense"] = new VectorParams
+                    {
+                        Size = 384,
+                        Distance = Distance.Cosine,
+                    },
+                },
+            },
+            sparseVectorsConfig: new SparseVectorConfig
+            {
+                Map = { ["isbn-bm25"] = new SparseVectorParams { Modifier = Modifier.Idf } },
+            }
+        );
+    }
+}
@@ -0,0 +1,23 @@
+```csharp
+using Qdrant.Client;
+using Qdrant.Client.Grpc;
+
+await client.CreateCollectionAsync(
+    collectionName: "books",
+    vectorsConfig: new VectorParamsMap
+    {
+        Map =
+        {
+            ["description-dense"] = new VectorParams
+            {
+                Size = 384,
+                Distance = Distance.Cosine,
+            },
+        },
+    },
+    sparseVectorsConfig: new SparseVectorConfig
+    {
+        Map = { ["isbn-bm25"] = new SparseVectorParams { Modifier = Modifier.Idf } },
+    }
+);
+```
@@ -0,0 +1,13 @@
+```go
+client.CreateCollection(context.Background(), &qdrant.CreateCollection{
+	CollectionName: "books",
+	VectorsConfig: qdrant.NewVectorsConfigMap(
+		map[string]*qdrant.VectorParams{
+			"description-dense": {Size: 384, Distance: qdrant.Distance_Cosine},
+		}),
+	SparseVectorsConfig: qdrant.NewSparseVectorsConfig(
+		map[string]*qdrant.SparseVectorParams{
+			"isbn-bm25": {Modifier: qdrant.Modifier_Idf.Enum()},
+		}),
+})
+```
@@ -0,0 +1,32 @@
+```java
+import io.qdrant.client.QdrantClient;
+import io.qdrant.client.QdrantGrpcClient;
+import io.qdrant.client.grpc.Collections.*;
+
+QdrantClient client =
+
+client
+    .createCollectionAsync(
+        CreateCollection.newBuilder()
+            .setCollectionName("books")
+            .setVectorsConfig(
+                VectorsConfig.newBuilder()
+                    .setParamsMap(
+                        VectorParamsMap.newBuilder()
+                            .putMap(
+                                "description-dense",
+                                VectorParams.newBuilder()
+                                    .setSize(384)
+                                    .setDistance(Distance.Cosine)
+                                    .build())
+                            .build())
+                    .build())
+            .setSparseVectorsConfig(
+                SparseVectorConfig.newBuilder()
+                    .putMap(
+                        "isbn-bm25",
+                        SparseVectorParams.newBuilder().setModifier(Modifier.Idf).build())
+                    .build())
+            .build())
+    .get();
+```
@@ -0,0 +1,19 @@
+```python
+from qdrant_client import QdrantClient, models
+
+client = QdrantClient(
+    url="https://xyz-example.qdrant.io:6333",
+    api_key="<your-api-key>",
+    cloud_inference=True,
+)
+
+client.create_collection(
+    collection_name="books",
+    vectors_config={
+        "description-dense": models.VectorParams(size=384, distance=models.Distance.COSINE)
+    },
+    sparse_vectors_config={
+        "isbn-bm25": models.SparseVectorParams(modifier=models.Modifier.IDF)
+    },
+)
+```
@@ -0,0 +1,27 @@
+```rust
+use qdrant_client::Qdrant;
+use qdrant_client::qdrant::{
+    CreateCollectionBuilder, Distance, Modifier, SparseVectorParamsBuilder,
+    SparseVectorsConfigBuilder, VectorParamsBuilder, VectorsConfigBuilder,
+};
+
+let mut vectors = VectorsConfigBuilder::default();
+vectors.add_named_vector_params(
+    "description-dense",
+    VectorParamsBuilder::new(384, Distance::Cosine),
+);
+
+let mut sparse = SparseVectorsConfigBuilder::default();
+sparse.add_named_vector_params(
+    "isbn-bm25",
+    SparseVectorParamsBuilder::default().modifier(Modifier::Idf),
+);
+
+client
+    .create_collection(
+        CreateCollectionBuilder::new("books")
+            .vectors_config(vectors)
+            .sparse_vectors_config(sparse),
+    )
+    .await?;
+```
@@ -0,0 +1,10 @@
+```typescript
+client.createCollection("books", {
+  vectors: {
+    "description-dense": { size: 384, distance: "Cosine" },
+  },
+  sparse_vectors: {
+    "isbn-bm25": { modifier: "idf" },
+  },
+});
+```
@@ -0,0 +1,35 @@
+package snippet
+
+// @hide-start
+import (
+	"context"
+
+	"github.com/qdrant/go-client/qdrant"
+)
+
+// @hide-end
+func Main() {
+	//@hide-start
+	client, err := qdrant.NewClient(&qdrant.Config{
+		Host: "localhost",
+		Port: 6334,
+	})
+
+	if err != nil {
+		panic(err)
+	}
+	// @hide-end
+
+	client.CreateCollection(context.Background(), &qdrant.CreateCollection{
+		CollectionName: "books",
+		VectorsConfig: qdrant.NewVectorsConfigMap(
+			map[string]*qdrant.VectorParams{
+				"description-dense": {Size: 384, Distance: qdrant.Distance_Cosine},
+			}),
+		SparseVectorsConfig: qdrant.NewSparseVectorsConfig(
+			map[string]*qdrant.SparseVectorParams{
+				"isbn-bm25": {Modifier: qdrant.Modifier_Idf.Enum()},
+			}),
+	})
+
+}
@@ -0,0 +1,37 @@
+package com.example.snippets_amalgamation;
+
+import io.qdrant.client.QdrantClient;
+import io.qdrant.client.QdrantGrpcClient;
+import io.qdrant.client.grpc.Collections.*;
+
+public class Snippet {
+  public static void run() throws Exception {
+    QdrantClient client =
+        new QdrantClient(QdrantGrpcClient.newBuilder("localhost", 6334, false).build()); // @hide
+
+    client
+        .createCollectionAsync(
+            CreateCollection.newBuilder()
+                .setCollectionName("books")
+                .setVectorsConfig(
+                    VectorsConfig.newBuilder()
+                        .setParamsMap(
+                            VectorParamsMap.newBuilder()
+                                .putMap(
+                                    "description-dense",
+                                    VectorParams.newBuilder()
+                                        .setSize(384)
+                                        .setDistance(Distance.Cosine)
+                                        .build())
+                                .build())
+                        .build())
+                .setSparseVectorsConfig(
+                    SparseVectorConfig.newBuilder()
+                        .putMap(
+                            "isbn-bm25",
+                            SparseVectorParams.newBuilder().setModifier(Modifier.Idf).build())
+                        .build())
+                .build())
+        .get();
+  }
+}
@@ -0,0 +1,17 @@
+from qdrant_client import QdrantClient, models
+
+client = QdrantClient(
+    url="https://xyz-example.qdrant.io:6333",
+    api_key="<your-api-key>",
+    cloud_inference=True,
+)
+
+client.create_collection(
+    collection_name="books",
+    vectors_config={
+        "description-dense": models.VectorParams(size=384, distance=models.Distance.COSINE)
+    },
+    sparse_vectors_config={
+        "isbn-bm25": models.SparseVectorParams(modifier=models.Modifier.IDF)
+    },
+)
@@ -0,0 +1,31 @@
+use qdrant_client::Qdrant;
+use qdrant_client::qdrant::{
+    CreateCollectionBuilder, Distance, Modifier, SparseVectorParamsBuilder,
+    SparseVectorsConfigBuilder, VectorParamsBuilder, VectorsConfigBuilder,
+};
+
+pub async fn main() -> anyhow::Result<()> {
+    let client = Qdrant::from_url("http://localhost:6334").build()?; // @hide
+
+    let mut vectors = VectorsConfigBuilder::default();
+    vectors.add_named_vector_params(
+        "description-dense",
+        VectorParamsBuilder::new(384, Distance::Cosine),
+    );
+
+    let mut sparse = SparseVectorsConfigBuilder::default();
+    sparse.add_named_vector_params(
+        "isbn-bm25",
+        SparseVectorParamsBuilder::default().modifier(Modifier::Idf),
+    );
+
+    client
+        .create_collection(
+            CreateCollectionBuilder::new("books")
+                .vectors_config(vectors)
+                .sparse_vectors_config(sparse),
+        )
+        .await?;
+
+    Ok(())
+}
@@ -0,0 +1,12 @@
+import { QdrantClient } from "@qdrant/js-client-rest"; // @hide
+
+const client = new QdrantClient({ host: "localhost", port: 6333 }); // @hide
+
+client.createCollection("books", {
+  vectors: {
+    "description-dense": { size: 384, distance: "Cosine" },
+  },
+  sparse_vectors: {
+    "isbn-bm25": { modifier: "idf" },
+  },
+});
@@ -0,0 +1,26 @@
+using Qdrant.Client;
+using Qdrant.Client.Grpc;
+
+public class Snippet
+{
+    public static async Task Run()
+    {
+        var client = new QdrantClient("localhost", 6334); // @hide
+
+        await client.CreatePayloadIndexAsync(
+            collectionName: "books",
+            fieldName: "title",
+            schemaType: PayloadSchemaType.Text,
+            indexParams: new PayloadIndexParams
+            {
+                TextIndexParams = new TextIndexParams
+                {
+                    Tokenizer = TokenizerType.Word,
+                    AsciiFolding = true,
+                    PhraseMatching = true,
+                    Lowercase = true,
+                },
+            }
+        );
+    }
+}
@@ -0,0 +1,20 @@
+```csharp
+using Qdrant.Client;
+using Qdrant.Client.Grpc;
+
+await client.CreatePayloadIndexAsync(
+    collectionName: "books",
+    fieldName: "title",
+    schemaType: PayloadSchemaType.Text,
+    indexParams: new PayloadIndexParams
+    {
+        TextIndexParams = new TextIndexParams
+        {
+            Tokenizer = TokenizerType.Word,
+            AsciiFolding = true,
+            PhraseMatching = true,
+            Lowercase = true,
+        },
+    }
+);
+```
@@ -0,0 +1,14 @@
+```go
+client.CreateFieldIndex(context.Background(), &qdrant.CreateFieldIndexCollection{
+	CollectionName: "books",
+	FieldName:      "title",
+	FieldType:      qdrant.FieldType_FieldTypeText.Enum(),
+	FieldIndexParams: qdrant.NewPayloadIndexParamsText(
+		&qdrant.TextIndexParams{
+			Tokenizer:      qdrant.TokenizerType_Word,
+			Lowercase:      qdrant.PtrOf(true),
+			AsciiFolding:   qdrant.PtrOf(true),
+			PhraseMatching: qdrant.PtrOf(true),
+		}),
+})
+```
@@ -0,0 +1,29 @@
+```java
+import io.qdrant.client.QdrantClient;
+import io.qdrant.client.QdrantGrpcClient;
+import io.qdrant.client.grpc.Collections.PayloadIndexParams;
+import io.qdrant.client.grpc.Collections.PayloadSchemaType;
+import io.qdrant.client.grpc.Collections.TextIndexParams;
+import io.qdrant.client.grpc.Collections.TokenizerType;
+
+QdrantClient client =
+
+client
+    .createPayloadIndexAsync(
+        "books",
+        "title",
+        PayloadSchemaType.Text,
+        PayloadIndexParams.newBuilder()
+            .setTextIndexParams(
+                TextIndexParams.newBuilder()
+                    .setTokenizer(TokenizerType.Word)
+                    .setAsciiFolding(true)
+                    .setPhraseMatching(true)
+                    .setLowercase(true)
+                    .build())
+            .build(),
+        null,
+        null,
+        null)
+    .get();
+```
@@ -0,0 +1,15 @@
+```python
+from qdrant_client import QdrantClient, models
+
+client = QdrantClient(
+    url="https://xyz-example.qdrant.io:6333",
+    api_key="<your-api-key>",
+    cloud_inference=True,
+)
+
+client.create_payload_index(
+    collection_name="books",
+    field_name="title",
+    field_schema=models.TextIndexParams(type=models.TextIndexType.TEXT, ascii_folding=True, phrase_matching=True),
+)
+```
@@ -0,0 +1,19 @@
+```rust
+use qdrant_client::Qdrant;
+use qdrant_client::qdrant::{
+    CreateFieldIndexCollectionBuilder, FieldType, TextIndexParamsBuilder, TokenizerType,
+};
+
+let params = TextIndexParamsBuilder::new(TokenizerType::Word)
+    .ascii_folding(true)
+    .phrase_matching(true)
+    .lowercase(true)
+    .build();
+
+client
+    .create_field_index(
+        CreateFieldIndexCollectionBuilder::new("books", "title", FieldType::Text)
+            .field_index_params(params),
+    )
+    .await?;
+```
@@ -0,0 +1,10 @@
+```typescript
+client.createPayloadIndex("books", {
+  field_name: "title",
+  field_schema: {
+    type: "text",
+    ascii_folding: true,
+    phrase_matching: true,
+  },
+});
+```
@@ -0,0 +1,36 @@
+package snippet
+
+// @hide-start
+import (
+	"context"
+
+	"github.com/qdrant/go-client/qdrant"
+)
+
+// @hide-end
+func Main() {
+	//@hide-start
+	client, err := qdrant.NewClient(&qdrant.Config{
+		Host: "localhost",
+		Port: 6334,
+	})
+
+	if err != nil {
+		panic(err)
+	}
+	// @hide-end
+
+	client.CreateFieldIndex(context.Background(), &qdrant.CreateFieldIndexCollection{
+		CollectionName: "books",
+		FieldName:      "title",
+		FieldType:      qdrant.FieldType_FieldTypeText.Enum(),
+		FieldIndexParams: qdrant.NewPayloadIndexParamsText(
+			&qdrant.TextIndexParams{
+				Tokenizer:      qdrant.TokenizerType_Word,
+				Lowercase:      qdrant.PtrOf(true),
+				AsciiFolding:   qdrant.PtrOf(true),
+				PhraseMatching: qdrant.PtrOf(true),
+			}),
+	})
+
+}
@@ -0,0 +1,34 @@
+package com.example.snippets_amalgamation;
+
+import io.qdrant.client.QdrantClient;
+import io.qdrant.client.QdrantGrpcClient;
+import io.qdrant.client.grpc.Collections.PayloadIndexParams;
+import io.qdrant.client.grpc.Collections.PayloadSchemaType;
+import io.qdrant.client.grpc.Collections.TextIndexParams;
+import io.qdrant.client.grpc.Collections.TokenizerType;
+
+public class Snippet {
+  public static void run() throws Exception {
+    QdrantClient client =
+        new QdrantClient(QdrantGrpcClient.newBuilder("localhost", 6334, false).build()); // @hide
+
+    client
+        .createPayloadIndexAsync(
+            "books",
+            "title",
+            PayloadSchemaType.Text,
+            PayloadIndexParams.newBuilder()
+                .setTextIndexParams(
+                    TextIndexParams.newBuilder()
+                        .setTokenizer(TokenizerType.Word)
+                        .setAsciiFolding(true)
+                        .setPhraseMatching(true)
+                        .setLowercase(true)
+                        .build())
+                .build(),
+            null,
+            null,
+            null)
+        .get();
+  }
+}
@@ -0,0 +1,13 @@
+from qdrant_client import QdrantClient, models
+
+client = QdrantClient(
+    url="https://xyz-example.qdrant.io:6333",
+    api_key="<your-api-key>",
+    cloud_inference=True,
+)
+
+client.create_payload_index(
+    collection_name="books",
+    field_name="title",
+    field_schema=models.TextIndexParams(type=models.TextIndexType.TEXT, ascii_folding=True, phrase_matching=True),
+)
@@ -0,0 +1,23 @@
+use qdrant_client::Qdrant;
+use qdrant_client::qdrant::{
+    CreateFieldIndexCollectionBuilder, FieldType, TextIndexParamsBuilder, TokenizerType,
+};
+
+pub async fn main() -> anyhow::Result<()> {
+    let client = Qdrant::from_url("http://localhost:6334").build()?; // @hide
+
+    let params = TextIndexParamsBuilder::new(TokenizerType::Word)
+        .ascii_folding(true)
+        .phrase_matching(true)
+        .lowercase(true)
+        .build();
+
+    client
+        .create_field_index(
+            CreateFieldIndexCollectionBuilder::new("books", "title", FieldType::Text)
+                .field_index_params(params),
+        )
+        .await?;
+
+    Ok(())
+}
@@ -0,0 +1,12 @@
+import { QdrantClient } from "@qdrant/js-client-rest"; // @hide
+
+const client = new QdrantClient({ host: "localhost", port: 6333 }); // @hide
+
+client.createPayloadIndex("books", {
+  field_name: "title",
+  field_schema: {
+    type: "text",
+    ascii_folding: true,
+    phrase_matching: true,
+  },
+});
@@ -0,0 +1,25 @@
+using Qdrant.Client;
+using Qdrant.Client.Grpc;
+
+public class Snippet
+{
+    public static async Task Run()
+    {
+        var client = new QdrantClient("localhost", 6334); // @hide
+
+        await client.CreatePayloadIndexAsync(
+            collectionName: "books",
+            fieldName: "title",
+            schemaType: PayloadSchemaType.Text,
+            indexParams: new PayloadIndexParams
+            {
+                TextIndexParams = new TextIndexParams
+                {
+                    Tokenizer = TokenizerType.Word,
+                    AsciiFolding = true,
+                    Lowercase = true,
+                },
+            }
+        );
+    }
+}
@@ -0,0 +1,19 @@
+```csharp
+using Qdrant.Client;
+using Qdrant.Client.Grpc;
+
+await client.CreatePayloadIndexAsync(
+    collectionName: "books",
+    fieldName: "title",
+    schemaType: PayloadSchemaType.Text,
+    indexParams: new PayloadIndexParams
+    {
+        TextIndexParams = new TextIndexParams
+        {
+            Tokenizer = TokenizerType.Word,
+            AsciiFolding = true,
+            Lowercase = true,
+        },
+    }
+);
+```
@@ -0,0 +1,13 @@
+```go
+client.CreateFieldIndex(context.Background(), &qdrant.CreateFieldIndexCollection{
+	CollectionName: "books",
+	FieldName:      "title",
+	FieldType:      qdrant.FieldType_FieldTypeText.Enum(),
+	FieldIndexParams: qdrant.NewPayloadIndexParamsText(
+		&qdrant.TextIndexParams{
+			Tokenizer:    qdrant.TokenizerType_Word,
+			Lowercase:    qdrant.PtrOf(true),
+			AsciiFolding: qdrant.PtrOf(true),
+		}),
+})
+```
@@ -0,0 +1,28 @@
+```java
+import io.qdrant.client.QdrantClient;
+import io.qdrant.client.QdrantGrpcClient;
+import io.qdrant.client.grpc.Collections.PayloadIndexParams;
+import io.qdrant.client.grpc.Collections.PayloadSchemaType;
+import io.qdrant.client.grpc.Collections.TextIndexParams;
+import io.qdrant.client.grpc.Collections.TokenizerType;
+
+QdrantClient client =
+
+client
+    .createPayloadIndexAsync(
+        "books",
+        "title",
+        PayloadSchemaType.Text,
+        PayloadIndexParams.newBuilder()
+            .setTextIndexParams(
+                TextIndexParams.newBuilder()
+                    .setTokenizer(TokenizerType.Word)
+                    .setAsciiFolding(true)
+                    .setLowercase(true)
+                    .build())
+            .build(),
+        null,
+        null,
+        null)
+    .get();
+```
@@ -0,0 +1,15 @@
+```python
+from qdrant_client import QdrantClient, models
+
+client = QdrantClient(
+    url="https://xyz-example.qdrant.io:6333",
+    api_key="<your-api-key>",
+    cloud_inference=True,
+)
+
+client.create_payload_index(
+    collection_name="books",
+    field_name="title",
+    field_schema=models.TextIndexParams(type=models.TextIndexType.TEXT, ascii_folding=True),
+)
+```
@@ -0,0 +1,18 @@
+```rust
+use qdrant_client::Qdrant;
+use qdrant_client::qdrant::{
+    CreateFieldIndexCollectionBuilder, FieldType, TextIndexParamsBuilder, TokenizerType,
+};
+
+let params = TextIndexParamsBuilder::new(TokenizerType::Word)
+    .ascii_folding(true)
+    .lowercase(true)
+    .build();
+
+client
+    .create_field_index(
+        CreateFieldIndexCollectionBuilder::new("books", "title", FieldType::Text)
+            .field_index_params(params),
+    )
+    .await?;
+```
@@ -0,0 +1,9 @@
+```typescript
+client.createPayloadIndex("books", {
+  field_name: "title",
+  field_schema: {
+    type: "text",
+    ascii_folding: true,
+  },
+});
+```
@@ -0,0 +1,35 @@
+package snippet
+
+// @hide-start
+import (
+	"context"
+
+	"github.com/qdrant/go-client/qdrant"
+)
+
+// @hide-end
+func Main() {
+	//@hide-start
+	client, err := qdrant.NewClient(&qdrant.Config{
+		Host: "localhost",
+		Port: 6334,
+	})
+
+	if err != nil {
+		panic(err)
+	}
+	// @hide-end
+
+	client.CreateFieldIndex(context.Background(), &qdrant.CreateFieldIndexCollection{
+		CollectionName: "books",
+		FieldName:      "title",
+		FieldType:      qdrant.FieldType_FieldTypeText.Enum(),
+		FieldIndexParams: qdrant.NewPayloadIndexParamsText(
+			&qdrant.TextIndexParams{
+				Tokenizer:    qdrant.TokenizerType_Word,
+				Lowercase:    qdrant.PtrOf(true),
+				AsciiFolding: qdrant.PtrOf(true),
+			}),
+	})
+
+}
@@ -0,0 +1,33 @@
+package com.example.snippets_amalgamation;
+
+import io.qdrant.client.QdrantClient;
+import io.qdrant.client.QdrantGrpcClient;
+import io.qdrant.client.grpc.Collections.PayloadIndexParams;
+import io.qdrant.client.grpc.Collections.PayloadSchemaType;
+import io.qdrant.client.grpc.Collections.TextIndexParams;
+import io.qdrant.client.grpc.Collections.TokenizerType;
+
+public class Snippet {
+  public static void run() throws Exception {
+    QdrantClient client =
+        new QdrantClient(QdrantGrpcClient.newBuilder("localhost", 6334, false).build()); // @hide
+
+    client
+        .createPayloadIndexAsync(
+            "books",
+            "title",
+            PayloadSchemaType.Text,
+            PayloadIndexParams.newBuilder()
+                .setTextIndexParams(
+                    TextIndexParams.newBuilder()
+                        .setTokenizer(TokenizerType.Word)
+                        .setAsciiFolding(true)
+                        .setLowercase(true)
+                        .build())
+                .build(),
+            null,
+            null,
+            null)
+        .get();
+  }
+}
@@ -0,0 +1,13 @@
+from qdrant_client import QdrantClient, models
+
+client = QdrantClient(
+    url="https://xyz-example.qdrant.io:6333",
+    api_key="<your-api-key>",
+    cloud_inference=True,
+)
+
+client.create_payload_index(
+    collection_name="books",
+    field_name="title",
+    field_schema=models.TextIndexParams(type=models.TextIndexType.TEXT, ascii_folding=True),
+)
@@ -0,0 +1,22 @@
+use qdrant_client::Qdrant;
+use qdrant_client::qdrant::{
+    CreateFieldIndexCollectionBuilder, FieldType, TextIndexParamsBuilder, TokenizerType,
+};
+
+pub async fn main() -> anyhow::Result<()> {
+    let client = Qdrant::from_url("http://localhost:6334").build()?; // @hide
+
+    let params = TextIndexParamsBuilder::new(TokenizerType::Word)
+        .ascii_folding(true)
+        .lowercase(true)
+        .build();
+
+    client
+        .create_field_index(
+            CreateFieldIndexCollectionBuilder::new("books", "title", FieldType::Text)
+                .field_index_params(params),
+        )
+        .await?;
+
+    Ok(())
+}
@@ -0,0 +1,11 @@
+import { QdrantClient } from "@qdrant/js-client-rest"; // @hide
+
+const client = new QdrantClient({ host: "localhost", port: 6333 }); // @hide
+
+client.createPayloadIndex("books", {
+  field_name: "title",
+  field_schema: {
+    type: "text",
+    ascii_folding: true,
+  },
+});
@@ -0,0 +1,23 @@
+using Qdrant.Client;
+using Qdrant.Client.Grpc;
+using static Qdrant.Client.Grpc.Conditions;
+
+public class Snippet
+{
+    public static async Task Run()
+    {
+        var client = new QdrantClient("localhost", 6334); // @hide
+
+        await client.QueryAsync(
+            collectionName: "books",
+            query: new Document
+            {
+                Text = "time travel",
+                Model = "sentence-transformers/all-minilm-l6-v2",
+            },
+            usingVector: "description-dense",
+            filter: MatchPhrase("title", "time machine"),
+            payloadSelector: true
+        );
+    }
+}
@@ -0,0 +1,17 @@
+```csharp
+using Qdrant.Client;
+using Qdrant.Client.Grpc;
+using static Qdrant.Client.Grpc.Conditions;
+
+await client.QueryAsync(
+    collectionName: "books",
+    query: new Document
+    {
+        Text = "time travel",
+        Model = "sentence-transformers/all-minilm-l6-v2",
+    },
+    usingVector: "description-dense",
+    filter: MatchPhrase("title", "time machine"),
+    payloadSelector: true
+);
+```
@@ -0,0 +1,16 @@
+```go
+client.Query(context.Background(), &qdrant.QueryPoints{
+	CollectionName: "books",
+	Query: qdrant.NewQueryNearest(
+		qdrant.NewVectorInputDocument(&qdrant.Document{
+			Model: "sentence-transformers/all-minilm-l6-v2",
+			Text:  "time travel",
+		}),
+	),
+	Using:       qdrant.PtrOf("description-dense"),
+	WithPayload: qdrant.NewWithPayload(true),
+	Filter: &qdrant.Filter{
+		Must: []*qdrant.Condition{qdrant.NewMatchPhrase("title", "time machine")},
+	},
+})
+```
@@ -0,0 +1,32 @@
+```java
+import static io.qdrant.client.ConditionFactory.*;
+import static io.qdrant.client.QueryFactory.nearest;
+import static io.qdrant.client.WithPayloadSelectorFactory.enable;
+
+import io.qdrant.client.QdrantClient;
+import io.qdrant.client.QdrantGrpcClient;
+import io.qdrant.client.grpc.Collections.*;
+import io.qdrant.client.grpc.Common.Filter;
+import io.qdrant.client.grpc.Points.*;
+import java.util.*;
+
+QdrantClient client =
+
+Filter filter = Filter.newBuilder().addMust(matchPhrase("title", "time machine")).build();
+
+client
+    .queryAsync(
+        QueryPoints.newBuilder()
+            .setCollectionName("books")
+            .setQuery(
+                nearest(
+                    Document.newBuilder()
+                        .setText("time travel")
+                        .setModel("sentence-transformers/all-minilm-l6-v2")
+                        .build()))
+            .setUsing("description-dense")
+            .setFilter(filter)
+            .setWithPayload(enable(true))
+            .build())
+    .get();
+```
@@ -0,0 +1,19 @@
+```python
+from qdrant_client import QdrantClient, models
+
+client = QdrantClient(
+    url="https://xyz-example.qdrant.io:6333",
+    api_key="<your-api-key>",
+    cloud_inference=True,
+)
+
+client.query_points(
+    collection_name="books",
+    query=models.Document(text="time travel", model="sentence-transformers/all-minilm-l6-v2"),
+    using="description-dense",
+    with_payload=True,
+    query_filter=models.Filter(
+        must=[models.FieldCondition(key="title", match=models.MatchPhrase(phrase="time machine"))]
+    ),
+)
+```
@@ -0,0 +1,20 @@
+```rust
+use qdrant_client::Qdrant;
+use qdrant_client::qdrant::{Condition, Document, Filter, Query, QueryPointsBuilder};
+
+let filter = Filter::must([Condition::matches("title", "time machine".to_string())]);
+
+client
+    .query(
+        QueryPointsBuilder::new("books")
+            .query(Query::new_nearest(Document::new(
+                "time travel",
+                "sentence-transformers/all-minilm-l6-v2",
+            )))
+            .using("description-dense")
+            .filter(filter)
+            .with_payload(true)
+            .build(),
+    )
+    .await?;
+```
@@ -0,0 +1,15 @@
+```typescript
+client.query("books", {
+  query: {
+    text: "time travel",
+    model: "sentence-transformers/all-minilm-l6-v2",
+  },
+  using: "description-dense",
+  with_payload: true,
+  filter: {
+    must: [
+      { key: "title", match: { phrase: "time machine" } },
+    ],
+  },
+});
+```
@@ -0,0 +1,38 @@
+package snippet
+
+// @hide-start
+import (
+	"context"
+
+	"github.com/qdrant/go-client/qdrant"
+)
+
+// @hide-end
+func Main() {
+	//@hide-start
+	client, err := qdrant.NewClient(&qdrant.Config{
+		Host: "localhost",
+		Port: 6334,
+	})
+
+	if err != nil {
+		panic(err)
+	}
+	// @hide-end
+
+	client.Query(context.Background(), &qdrant.QueryPoints{
+		CollectionName: "books",
+		Query: qdrant.NewQueryNearest(
+			qdrant.NewVectorInputDocument(&qdrant.Document{
+				Model: "sentence-transformers/all-minilm-l6-v2",
+				Text:  "time travel",
+			}),
+		),
+		Using:       qdrant.PtrOf("description-dense"),
+		WithPayload: qdrant.NewWithPayload(true),
+		Filter: &qdrant.Filter{
+			Must: []*qdrant.Condition{qdrant.NewMatchPhrase("title", "time machine")},
+		},
+	})
+
+}
@@ -0,0 +1,37 @@
+package com.example.snippets_amalgamation;
+
+import static io.qdrant.client.ConditionFactory.*;
+import static io.qdrant.client.QueryFactory.nearest;
+import static io.qdrant.client.WithPayloadSelectorFactory.enable;
+
+import io.qdrant.client.QdrantClient;
+import io.qdrant.client.QdrantGrpcClient;
+import io.qdrant.client.grpc.Collections.*;
+import io.qdrant.client.grpc.Common.Filter;
+import io.qdrant.client.grpc.Points.*;
+import java.util.*;
+
+public class Snippet {
+  public static void run() throws Exception {
+    QdrantClient client =
+        new QdrantClient(QdrantGrpcClient.newBuilder("localhost", 6334, false).build()); // @hide
+
+    Filter filter = Filter.newBuilder().addMust(matchPhrase("title", "time machine")).build();
+
+    client
+        .queryAsync(
+            QueryPoints.newBuilder()
+                .setCollectionName("books")
+                .setQuery(
+                    nearest(
+                        Document.newBuilder()
+                            .setText("time travel")
+                            .setModel("sentence-transformers/all-minilm-l6-v2")
+                            .build()))
+                .setUsing("description-dense")
+                .setFilter(filter)
+                .setWithPayload(enable(true))
+                .build())
+        .get();
+  }
+}
@@ -0,0 +1,17 @@
+from qdrant_client import QdrantClient, models
+
+client = QdrantClient(
+    url="https://xyz-example.qdrant.io:6333",
+    api_key="<your-api-key>",
+    cloud_inference=True,
+)
+
+client.query_points(
+    collection_name="books",
+    query=models.Document(text="time travel", model="sentence-transformers/all-minilm-l6-v2"),
+    using="description-dense",
+    with_payload=True,
+    query_filter=models.Filter(
+        must=[models.FieldCondition(key="title", match=models.MatchPhrase(phrase="time machine"))]
+    ),
+)
@@ -0,0 +1,24 @@
+use qdrant_client::Qdrant;
+use qdrant_client::qdrant::{Condition, Document, Filter, Query, QueryPointsBuilder};
+
+pub async fn main() -> anyhow::Result<()> {
+    let client = Qdrant::from_url("http://localhost:6334").build()?; // @hide
+
+    let filter = Filter::must([Condition::matches("title", "time machine".to_string())]);
+
+    client
+        .query(
+            QueryPointsBuilder::new("books")
+                .query(Query::new_nearest(Document::new(
+                    "time travel",
+                    "sentence-transformers/all-minilm-l6-v2",
+                )))
+                .using("description-dense")
+                .filter(filter)
+                .with_payload(true)
+                .build(),
+        )
+        .await?;
+
+    Ok(())
+}
@@ -0,0 +1,17 @@
+import { QdrantClient } from "@qdrant/js-client-rest"; // @hide
+
+const client = new QdrantClient({ host: "localhost", port: 6333 }); // @hide
+
+client.query("books", {
+  query: {
+    text: "time travel",
+    model: "sentence-transformers/all-minilm-l6-v2",
+  },
+  using: "description-dense",
+  with_payload: true,
+  filter: {
+    must: [
+      { key: "title", match: { phrase: "time machine" } },
+    ],
+  },
+});
@@ -0,0 +1,23 @@
+using Qdrant.Client;
+using Qdrant.Client.Grpc;
+using static Qdrant.Client.Grpc.Conditions;
+
+public class Snippet
+{
+    public static async Task Run()
+    {
+        var client = new QdrantClient("localhost", 6334); // @hide
+
+        await client.QueryAsync(
+            collectionName: "books",
+            query: new Document
+            {
+                Text = "space opera",
+                Model = "sentence-transformers/all-minilm-l6-v2",
+            },
+            usingVector: "description-dense",
+            filter: MatchTextAny("title", "space war"),
+            payloadSelector: true
+        );
+    }
+}
@@ -0,0 +1,17 @@
+```csharp
+using Qdrant.Client;
+using Qdrant.Client.Grpc;
+using static Qdrant.Client.Grpc.Conditions;
+
+await client.QueryAsync(
+    collectionName: "books",
+    query: new Document
+    {
+        Text = "space opera",
+        Model = "sentence-transformers/all-minilm-l6-v2",
+    },
+    usingVector: "description-dense",
+    filter: MatchTextAny("title", "space war"),
+    payloadSelector: true
+);
+```
@@ -0,0 +1,16 @@
+```go
+client.Query(context.Background(), &qdrant.QueryPoints{
+	CollectionName: "books",
+	Query: qdrant.NewQueryNearest(
+		qdrant.NewVectorInputDocument(&qdrant.Document{
+			Model: "sentence-transformers/all-minilm-l6-v2",
+			Text:  "space opera",
+		}),
+	),
+	Using:       qdrant.PtrOf("description-dense"),
+	WithPayload: qdrant.NewWithPayload(true),
+	Filter: &qdrant.Filter{
+		Must: []*qdrant.Condition{qdrant.NewMatchTextAny("title", "space war")},
+	},
+})
+```
--- a/Show More
+++ b/Show More