mirror of
https://github.com/qdrant/landing_page.git
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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>
This commit is contained in:
Abdon Pijpelink
co-authored by
Anush008
Anush008
Daniel Boros
Anush008
Anush008
Daniel Boros
parent
b5e0908946
commit
2497c368ed
+36
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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); // @hide
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await client.UpsertAsync(
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collectionName: "books",
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wait: true,
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points: new List<PointStruct>
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{
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new()
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{
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Id = 1,
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Vectors = new Dictionary<string, Vector>
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{
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["title-bm25"] = new Document
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{
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Text = "La Máquina del Tiempo",
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Model = "qdrant/bm25",
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},
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},
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Payload =
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{
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["title"] = "La Máquina del Tiempo",
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["author"] = "H.G. Wells",
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["isbn"] = "9788411486880",
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},
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},
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}
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);
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}
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}
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+30
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```csharp
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using Qdrant.Client;
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using Qdrant.Client.Grpc;
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await client.UpsertAsync(
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collectionName: "books",
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wait: true,
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points: new List<PointStruct>
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{
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new()
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{
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Id = 1,
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Vectors = new Dictionary<string, Vector>
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{
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["title-bm25"] = new Document
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{
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Text = "La Máquina del Tiempo",
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Model = "qdrant/bm25",
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},
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},
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Payload =
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{
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["title"] = "La Máquina del Tiempo",
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["author"] = "H.G. Wells",
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["isbn"] = "9788411486880",
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},
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},
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}
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);
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```
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+21
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```go
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client.Upsert(context.Background(), &qdrant.UpsertPoints{
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CollectionName: "books",
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Points: []*qdrant.PointStruct{
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{
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Id: qdrant.NewIDNum(uint64(1)),
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Vectors: qdrant.NewVectorsMap(map[string]*qdrant.Vector{
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"title-bm25": qdrant.NewVectorDocument(&qdrant.Document{
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Model: "qdrant/bm25",
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Text: "La Máquina del Tiempo",
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}),
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}),
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Payload: qdrant.NewValueMap(map[string]any{
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"title": "La Máquina del Tiempo",
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"author": "H.G. Wells",
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"isbn": "9788411486880",
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}),
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},
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},
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})
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```
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+34
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```java
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import static io.qdrant.client.PointIdFactory.id;
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import static io.qdrant.client.ValueFactory.value;
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import static io.qdrant.client.VectorFactory.vector;
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import static io.qdrant.client.VectorsFactory.namedVectors;
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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.*;
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import java.util.*;
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QdrantClient client =
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PointStruct point =
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PointStruct.newBuilder()
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.setId(id(1))
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.setVectors(
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namedVectors(
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Map.of(
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"title-bm25",
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vector(
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Document.newBuilder()
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.setText("La Máquina del Tiempo")
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.setModel("qdrant/bm25")
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.build()))))
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.putAllPayload(
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Map.of(
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"title", value("La Máquina del Tiempo"),
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"author", value("H.G. Wells"),
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"isbn", value("9788411486880")))
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.build();
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client.upsertAsync("books", List.of(point)).get();
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```
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+30
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```python
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from qdrant_client import QdrantClient, models
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client = QdrantClient(
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url="https://xyz-example.qdrant.io:6333",
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api_key="<your-api-key>",
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cloud_inference=True,
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)
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client.upsert(
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collection_name="books",
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points=[
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models.PointStruct(
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id=1,
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vector={
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"title-bm25": models.Document(
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text="La Máquina del Tiempo",
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model="qdrant/bm25",
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options={"language": "spanish"},
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)
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},
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payload={
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"title": "La Máquina del Tiempo",
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"author": "H.G. Wells",
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"isbn": "9788411486880",
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},
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)
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],
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)
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```
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+30
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```rust
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use std::collections::HashMap;
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use qdrant_client::qdrant::{DocumentBuilder, PointStruct, UpsertPointsBuilder, Value};
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use qdrant_client::{Payload, Qdrant};
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use serde_json::json;
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let mut options = HashMap::new();
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options.insert("language".to_string(), Value::from("spanish"));
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let point = PointStruct::new(
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1,
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HashMap::from([(
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"title-bm25".to_string(),
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DocumentBuilder::new("La Máquina del Tiempo", "qdrant/bm25")
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.options(options)
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.build(),
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)]),
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Payload::try_from(json!({
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"title": "La Máquina del Tiempo",
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"author": "H.G. Wells",
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"isbn": "9788411486880",
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}))
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.unwrap(),
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);
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client
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.upsert_points(UpsertPointsBuilder::new("books", vec![point]).wait(true))
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.await?;
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```
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+22
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```typescript
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client.upsert("books", {
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wait: true,
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points: [
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{
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id: 1,
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vector: {
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"title-bm25": {
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text: "La Máquina del Tiempo",
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model: "qdrant/bm25",
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options: { language: "spanish" },
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},
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},
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payload: {
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title: "La Máquina del Tiempo",
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author: "H.G. Wells",
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isbn: "9788411486880",
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},
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},
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],
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});
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```
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+43
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package snippet
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// @hide-start
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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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// @hide-end
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func Main() {
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//@hide-start
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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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if err != nil {
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panic(err)
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}
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// @hide-end
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client.Upsert(context.Background(), &qdrant.UpsertPoints{
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CollectionName: "books",
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Points: []*qdrant.PointStruct{
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{
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Id: qdrant.NewIDNum(uint64(1)),
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Vectors: qdrant.NewVectorsMap(map[string]*qdrant.Vector{
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"title-bm25": qdrant.NewVectorDocument(&qdrant.Document{
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Model: "qdrant/bm25",
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Text: "La Máquina del Tiempo",
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}),
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}),
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Payload: qdrant.NewValueMap(map[string]any{
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"title": "La Máquina del Tiempo",
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"author": "H.G. Wells",
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"isbn": "9788411486880",
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}),
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},
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},
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})
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}
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+39
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package com.example.snippets_amalgamation;
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import static io.qdrant.client.PointIdFactory.id;
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import static io.qdrant.client.ValueFactory.value;
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import static io.qdrant.client.VectorFactory.vector;
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import static io.qdrant.client.VectorsFactory.namedVectors;
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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.*;
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import java.util.*;
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public class Snippet {
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public static void run() throws Exception {
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QdrantClient client =
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new QdrantClient(QdrantGrpcClient.newBuilder("localhost", 6334, false).build()); // @hide
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PointStruct point =
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PointStruct.newBuilder()
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.setId(id(1))
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.setVectors(
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namedVectors(
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Map.of(
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"title-bm25",
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vector(
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Document.newBuilder()
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.setText("La Máquina del Tiempo")
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.setModel("qdrant/bm25")
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.build()))))
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.putAllPayload(
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Map.of(
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"title", value("La Máquina del Tiempo"),
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"author", value("H.G. Wells"),
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"isbn", value("9788411486880")))
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.build();
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client.upsertAsync("books", List.of(point)).get();
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}
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}
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+28
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from qdrant_client import QdrantClient, models
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client = QdrantClient(
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url="https://xyz-example.qdrant.io:6333",
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api_key="<your-api-key>",
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cloud_inference=True,
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)
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client.upsert(
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collection_name="books",
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points=[
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models.PointStruct(
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id=1,
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vector={
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"title-bm25": models.Document(
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text="La Máquina del Tiempo",
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model="qdrant/bm25",
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options={"language": "spanish"},
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)
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},
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payload={
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"title": "La Máquina del Tiempo",
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"author": "H.G. Wells",
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"isbn": "9788411486880",
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},
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)
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],
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)
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+34
@@ -0,0 +1,34 @@
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use std::collections::HashMap;
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use qdrant_client::qdrant::{DocumentBuilder, PointStruct, UpsertPointsBuilder, Value};
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use qdrant_client::{Payload, Qdrant};
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use serde_json::json;
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pub async fn main() -> anyhow::Result<()> {
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let client = Qdrant::from_url("http://localhost:6334").build()?; // @hide
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let mut options = HashMap::new();
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options.insert("language".to_string(), Value::from("spanish"));
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let point = PointStruct::new(
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1,
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HashMap::from([(
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"title-bm25".to_string(),
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DocumentBuilder::new("La Máquina del Tiempo", "qdrant/bm25")
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.options(options)
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.build(),
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)]),
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Payload::try_from(json!({
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"title": "La Máquina del Tiempo",
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"author": "H.G. Wells",
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"isbn": "9788411486880",
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}))
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.unwrap(),
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);
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client
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.upsert_points(UpsertPointsBuilder::new("books", vec![point]).wait(true))
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.await?;
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Ok(())
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}
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+24
@@ -0,0 +1,24 @@
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import { QdrantClient } from "@qdrant/js-client-rest"; // @hide
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const client = new QdrantClient({ host: "localhost", port: 6333 }); // @hide
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client.upsert("books", {
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wait: true,
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points: [
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{
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id: 1,
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vector: {
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"title-bm25": {
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text: "La Máquina del Tiempo",
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model: "qdrant/bm25",
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options: { language: "spanish" },
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},
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},
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payload: {
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title: "La Máquina del Tiempo",
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author: "H.G. Wells",
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isbn: "9788411486880",
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},
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},
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],
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});
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Reference in New Issue
Block a user