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Restructure inference docs (#2225)

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* Break Inference page into several pages

* Make all inference code snippets testable and clean up

* Make more snippets testable

* Edits

* Document automatic query and passage prefix injection in Cloud Inference

Qdrant Cloud Inference silently applies model-specific prefixes (e.g.
"query: "/"passage: " for E5, BGE-style instruction prefix for BGE/mxbai/
Snowflake arctic-embed) so users don't need to manage them manually.
Add a section explaining this behavior, the idempotency guarantee, and
the scope (Qdrant-hosted models only; external providers handle their own).

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* Document short query optimization in Cloud Inference

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* Update links

* Expand on external provider API key usage

* Add section about external provider API keys

* Default to header for external API keys

---------

Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
Abdon Pijpelink
2026-06-24 08:11:03 +02:00
committed by GitHub
co-authored by Claude Sonnet 4.6
parent 90d072eb03
commit 478b96554f
250 changed files with 3259 additions and 2187 deletions
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qdrant-landing/content/documentation/headless/snippets/inference/mrl/rust.rs
+7 -12
View File
@@ -6,9 +6,10 @@ use qdrant_client::{
};
pub async fn main() -> anyhow::Result<()> {
let client = Qdrant::from_url("http://localhost:6334").build()?;
let client = Qdrant::from_url("http://localhost:6334").build()?; // @hide
client
.with_header("openai-api-key", "<YOUR_OPENAI_API_KEY>")
.upsert_points(
UpsertPointsBuilder::new(
"{collection_name}",
@@ -20,10 +21,7 @@ pub async fn main() -> anyhow::Result<()> {
Document {
text: "Recipe for baking chocolate chip cookies".into(),
model: "openai/text-embedding-3-small".into(),
options: HashMap::<String, Value>::from_iter(vec![(
"openai-api-key".into(),
"<YOUR_OPENAI_API_KEY>".into(),
)]),
options: HashMap::new(),
},
)
.add_vector(
@@ -31,13 +29,10 @@ pub async fn main() -> anyhow::Result<()> {
Document {
text: "Recipe for baking chocolate chip cookies".into(),
model: "openai/text-embedding-3-small".into(),
options: HashMap::<String, Value>::from_iter(vec![
(
"openai-api-key".into(),
Value::from("<YOUR_OPENAI_API_KEY>"),
),
("mrl".into(), Value::from(64)),
]),
options: HashMap::<String, Value>::from_iter(vec![(
"mrl".into(),
Value::from(64),
)]),
},
),
Payload::default(),