mirror of
https://github.com/qdrant/landing_page.git
synced 2026-09-27 23:18:29 +02:00
feat: add rust snippets
This commit is contained in:
Daniel Boros
@@ -0,0 +1,25 @@
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```rust
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use qdrant_client::{
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Qdrant, QdrantError,
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qdrant::{Document, Query, QueryPointsBuilder, Value},
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};
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use std::collections::HashMap;
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let client = Qdrant::from_url("http://localhost:6333").build().unwrap();
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let mut options = HashMap::<String, Value>::new();
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options.insert("cohere-api-key".to_string(), "<YOUR_COHERE_API_KEY>".into());
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options.insert("output_dimension".to_string(), 512.into());
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client
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.query(
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QueryPointsBuilder::new("<your-collection_name>")
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.query(Query::new_nearest(Document {
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text: "a green square".into(),
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model: "cohere/embed-v4.0".into(),
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options,
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}))
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.build(),
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)
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.await?;
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```
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+25
@@ -0,0 +1,25 @@
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```rust
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use qdrant_client::{
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Payload, Qdrant, QdrantError,
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qdrant::{Document, PointStruct, UpsertPointsBuilder},
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};
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use std::collections::HashMap;
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let client = Qdrant::from_url("http://localhost:6333").build()?;
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let mut options = HashMap::new();
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options.insert("cohere-api-key".to_string(), "<YOUR_COHERE_API_KEY>".into());
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options.insert("output_dimension".to_string(), 512.into());
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client
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.upsert_points(UpsertPointsBuilder::new("<your-collection>",
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vec![
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PointStruct::new(1,
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Document {
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text: "Recipe for baking chocolate chip cookies requires flour, sugar, eggs, and chocolate chips.".into(),
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model: "openai/text-embedding-3-small".into(),
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options,
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},
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Payload::default())
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]).wait(true))
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.await?;
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```
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@@ -0,0 +1,23 @@
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```rust
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use qdrant_client::{
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Payload, Qdrant, QdrantError,
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qdrant::{Document, PointStruct, UpsertPointsBuilder},
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};
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use std::collections::HashMap;
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let client = Qdrant::from_url("http://localhost:6333").build()?;
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client
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.upsert_points(UpsertPointsBuilder::new("<your-collection>",
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vec![
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PointStruct::new(1,
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HashMap::from([("my-bm25-vector".to_string(),
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Document {
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text: "Recipe for baking chocolate chip cookies".into(),
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model: "qdrant/bm25".into(),
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options: HashMap::new(),
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}.into())]),
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Payload::default())
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]))
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.await?;
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```
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@@ -0,0 +1,25 @@
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```rust
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use qdrant_client::{
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Qdrant, QdrantError,
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qdrant::{Document, Query, QueryPointsBuilder, Value},
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};
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use std::collections::HashMap;
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let client = Qdrant::from_url("http://localhost:6333").build().unwrap();
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let mut options = HashMap::<String, Value>::new();
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options.insert("jina-api-key".to_string(), "<YOUR_JINAAI_API_KEY>".into());
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options.insert("dimensions".to_string(), 512.into());
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client
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.query(
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QueryPointsBuilder::new("<your-collection_name>")
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.query(Query::new_nearest(Document {
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text: "Mission to Mars".into(),
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model: "jinaai/jina-clip-v2".into(),
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options,
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}))
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.build(),
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)
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.await?;
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```
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+25
@@ -0,0 +1,25 @@
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```rust
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use qdrant_client::{
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Payload, Qdrant, QdrantError,
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qdrant::{Image, PointStruct, UpsertPointsBuilder},
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};
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use std::collections::HashMap;
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let client = Qdrant::from_url("http://localhost:6333").build()?;
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let mut options = HashMap::new();
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options.insert("jina-api-key".to_string(), "<YOUR_JINAAI_API_KEY>".into());
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options.insert("dimensions".to_string(), 512.into());
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client
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.upsert_points(UpsertPointsBuilder::new("<your-collection>",
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vec![
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PointStruct::new(1,
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Image {
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image: Some("https://qdrant.tech/example.png".into()),
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model: "jinaai/jina-clip-v2".into(),
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options,
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},
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Payload::default())
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]).wait(true))
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.await?;
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```
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@@ -0,0 +1,51 @@
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```rust
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use qdrant_client::{
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Payload, Qdrant, QdrantError,
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qdrant::{Document, PointStruct, UpsertPointsBuilder, Vectors},
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};
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use std::collections::HashMap;
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let client = Qdrant::from_url("http://localhost:6333").build()?;
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let mut jina_options = HashMap::new();
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jina_options.insert("jina-api-key".to_string(), "<YOUR_JINAAI_API_KEY>".into());
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jina_options.insert("dimensions".to_string(), 512.into());
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client
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.upsert_points(
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UpsertPointsBuilder::new(
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"<your-collection>",
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vec![PointStruct::new(
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1,
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NamedVectors::default()
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.add_vector(
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"image",
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Image {
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image: Some("https://qdrant.tech/example.png".into()),
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model: "jinaai/jina-clip-v2".into(),
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options: jina_options,
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},
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)
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.add_vector(
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"text",
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Document {
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text: "Mars, the red planet".into(),
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model: "sentence-transformers/all-minilm-l6-v2".into(),
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options: HashMap::new(),
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},
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)
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.add_vector(
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"bm25",
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Document {
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text: "How to bake cookies?".into(),
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model: "qdrant/bm25".into(),
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options: HashMap::new(),
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},
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),
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Payload::default(),
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)],
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)
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.wait(true),
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)
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.await?;
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```
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@@ -0,0 +1,25 @@
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```rust
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use qdrant_client::{
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Qdrant, QdrantError,
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qdrant::{Document, Query, QueryPointsBuilder, Value},
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};
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use std::collections::HashMap;
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let client = Qdrant::from_url("http://localhost:6333").build().unwrap();
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let mut options = HashMap::<String, Value>::new();
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options.insert("openai-api-key".to_string(), "<YOUR_OPENAI_API_KEY>".into());
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options.insert("dimensions".to_string(), 512.into());
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client
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.query(
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QueryPointsBuilder::new("<your-collection_name>")
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.query(Query::new_nearest(Document {
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text: "How to bake cookies?".into(),
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model: "openai/text-embedding-3-large".into(),
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options,
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}))
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.build(),
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)
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.await?;
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```
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+25
@@ -0,0 +1,25 @@
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```rust
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use qdrant_client::{
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Payload, Qdrant, QdrantError,
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qdrant::{Document, PointStruct, UpsertPointsBuilder},
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};
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use std::collections::HashMap;
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let client = Qdrant::from_url("http://localhost:6333").build()?;
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let mut options = HashMap::new();
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options.insert("openai-api-key".to_string(), "<YOUR_OPENAI_API_KEY>".into());
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options.insert("dimensions".to_string(), 512.into());
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client
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.upsert_points(UpsertPointsBuilder::new("<your-collection>",
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vec![
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PointStruct::new(1,
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Document {
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text: "Recipe for baking chocolate chip cookies".into(),
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model: "openai/text-embedding-3-large".into(),
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options,
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},
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Payload::default())
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]).wait(true))
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.await?;
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```
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@@ -0,0 +1,22 @@
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```rust
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use qdrant_client::{
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Qdrant, QdrantError,
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qdrant::{Document, Query, QueryPointsBuilder},
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};
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use std::collections::HashMap;
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let client = Qdrant::from_url("http://localhost:6333").build().unwrap();
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client
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.query(
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QueryPointsBuilder::new("<your-collection_name>")
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.query(Query::new_nearest(Document {
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text: "How to bake cookies?".into(),
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model: "qdrant/bm25".into(),
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options: HashMap::new(),
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}))
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.using("my-bm25-vector")
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.build(),
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)
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.await?;
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```
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