From b7d584945d4c8151d8bda8b86f48e262c2f08711 Mon Sep 17 00:00:00 2001 From: Panagiotis Bailis Date: Fri, 8 Nov 2024 12:07:38 +0200 Subject: [PATCH] removing references to semantic query --- .../retrievers-overview.asciidoc | 29 +++---------------- .../retrievers_examples.asciidoc | 8 ++--- 2 files changed, 8 insertions(+), 29 deletions(-) diff --git a/docs/reference/search/search-your-data/retrievers-overview.asciidoc b/docs/reference/search/search-your-data/retrievers-overview.asciidoc index 377718e442aa0..0a205c684e40d 100644 --- a/docs/reference/search/search-your-data/retrievers-overview.asciidoc +++ b/docs/reference/search/search-your-data/retrievers-overview.asciidoc @@ -70,8 +70,7 @@ When using compound retrievers, only the query element is allowed, which enforce The following example demonstrates the powerful queries that we can now compose, and how retrievers simplify this process. -To show the full functionality, in this exercise, we'll assume that we have access to a <> through the inference service, -as well as access to <>, for building semantic queries. +To show the full functionality, in this exercise, we'll assume that we have access to a <> through the inference service. To begin with, we'll set up the necessary services and have them in place for later use. @@ -89,22 +88,7 @@ PUT _inference/rerank/my-awesome-rerank-model ---- //NOTCONSOLE -[source,js] ----- -// Setup ELSER as `my-elser-endpoint` -PUT _inference/sparse_embedding/my-elser-endpoint -{ - "service": "elser", - "service_settings": { - "num_allocations": 1, - "num_threads": 1 - }, - "task_settings": {} -} ----- -//NOTCONSOLE - -Now that we have our services in place, lets create the `retrievers_example` index, and add some documents to it. +Now that we have our reranking service in place, lets create the `retrievers_example` index, and add some documents to it. [source,js] ---- PUT retrievers_example @@ -118,18 +102,13 @@ PUT retrievers_example "index": true }, "text": { - "type": "text", - "copy_to": "inference_field" + "type": "text" }, "year": { "type": "integer" }, "topic": { "type": "keyword" - }, - "inference_field": { - "type": "semantic_text", - "inference_id": "my-elser-endpoint" } } } @@ -184,7 +163,7 @@ POST /retrievers_example/_doc/5 Now that we also have our documents in place, let's try to run some queries using retrievers. -include::retrievers_examples.asciidoc[tag=basic-rrf-retriever-with-semantic-query] +include::retrievers_examples.asciidoc[tag=basic-rrf-retriever-with-simple-query-and-knn] include::retrievers_examples.asciidoc[tag=rrf-retriever-with-collapse] include::retrievers_examples.asciidoc[tag=text-similarity-reranker-on-top-of-rrf] include::retrievers_examples.asciidoc[tag=rrf-on-top-of-semantic-reranker] diff --git a/docs/reference/search/search-your-data/retrievers_examples.asciidoc b/docs/reference/search/search-your-data/retrievers_examples.asciidoc index 8438a6732a54e..d4b8751f76f48 100644 --- a/docs/reference/search/search-your-data/retrievers_examples.asciidoc +++ b/docs/reference/search/search-your-data/retrievers_examples.asciidoc @@ -1,9 +1,9 @@ -tag::basic-rrf-retriever-with-semantic-query[] +tag::basic-rrf-retriever-with-simple-query-and-knn[] [discrete] -=== Combining kNN and semantic search with RRF +=== Combining query and kNN with RRF First, let's examine how to combine two different types of queries: a `kNN` query and a -`semantic` query. While these queries may produce scores in different ranges, we can use +`query_string` query. While these queries may produce scores in different ranges, we can use Reciprocal Rank Fusion (`rrf`) to combine the results and generate a merged final result list. @@ -45,7 +45,7 @@ GET /retrievers_example/_search } ---- //NOTCONSOLE -end::basic-rrf-retriever-with-semantic-query[] +end::basic-rrf-retriever-with-simple-query-and-knn[] tag::rrf-retriever-with-collapse[] [discrete]