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Abdon PijpelinkandClaude Sonnet 4.6
478b96554f
* 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>
42 lines
1.3 KiB
Markdown
42 lines
1.3 KiB
Markdown
---
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title: BM25
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weight: 20
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---
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# Server-side Inference: BM25
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[BM25](/documentation/search/text-search/#bm25) (Best Matching 25) is a ranking function for text search. BM25 uses sparse vectors that represent documents, where each dimension corresponds to a word. Qdrant can generate these sparse embeddings from input text directly on the server.
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While upserting points, provide the text and the `qdrant/bm25` embedding model:
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{{< code-snippet path="/documentation/headless/snippets/inference/ingest/" >}}
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Qdrant uses the model to generate the embeddings and stores the point with the resulting vector. Retrieving the point shows the embeddings that were generated:
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```json
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....
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"my-bm25-vector": {
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"indices": [
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112174620,
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177304315,
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662344706,
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771857363,
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1617337648
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],
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"values": [
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1.6697302,
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1.6697302,
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1.6697302,
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1.6697302,
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1.6697302
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]
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}
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....
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]
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```
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Similarly, use the BM25 model at query time by providing the query string and the `qdrant/bm25` embedding model:
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{{< code-snippet path="/documentation/headless/snippets/inference/query/" >}}
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Read more about full-text search with BM25 in the [text search guide](/documentation/search/text-search/#full-text-search). |