From 28c7fae7453c93a78abdb14173692a1838267022 Mon Sep 17 00:00:00 2001 From: Panagiotis Bailis Date: Fri, 29 Nov 2024 14:26:37 +0200 Subject: [PATCH] minor formatting changes on json requests --- .../retrievers-examples.asciidoc | 270 +++++++++--------- 1 file changed, 136 insertions(+), 134 deletions(-) diff --git a/docs/reference/search/search-your-data/retrievers-examples.asciidoc b/docs/reference/search/search-your-data/retrievers-examples.asciidoc index be34c0739ad81..ad1cc32dcee01 100644 --- a/docs/reference/search/search-your-data/retrievers-examples.asciidoc +++ b/docs/reference/search/search-your-data/retrievers-examples.asciidoc @@ -99,37 +99,37 @@ retriever. This retriever operates on top of two other retrievers: a `knn` retri ---- GET /retrievers_example/_search { - "retriever":{ - "rrf": { - "retrievers":[ - { - "standard":{ - "query":{ - "query_string":{ - "query": "(information retrieval) OR (artificial intelligence)", - "default_field": "text" - } - } - } - }, - { - "knn": { - "field": "vector", - "query_vector": [ - 0.23, - 0.67, - 0.89 - ], - "k": 3, - "num_candidates": 5 - } - } - ], - "rank_window_size": 10, - "rank_constant": 1 - } - }, - "_source": false + "retriever": { + "rrf": { + "retrievers": [ + { + "standard": { + "query": { + "query_string": { + "query": "(information retrieval) OR (artificial intelligence)", + "default_field": "text" + } + } + } + }, + { + "knn": { + "field": "vector", + "query_vector": [ + 0.23, + 0.67, + 0.89 + ], + "k": 3, + "num_candidates": 5 + } + } + ], + "rank_window_size": 10, + "rank_constant": 1 + } + }, + "_source": false } ---- // TEST @@ -192,43 +192,45 @@ we'll collapse our results based on the `year` field. ---- GET /retrievers_example/_search { - "retriever":{ - "rrf": { - "retrievers":[ - { - "standard":{ - "query":{ - "query_string":{ - "query": "(information retrieval) OR (artificial intelligence)", - "default_field": "text" - } - } - } - }, - { - "knn": { - "field": "vector", - "query_vector": [ - 0.23, - 0.67, - 0.89 - ], - "k": 3, - "num_candidates": 5 - } - } - ], - "rank_window_size": 10, - "rank_constant": 1 - } - }, - "collapse": { - "field": "year", - "inner_hits": { - "name": "topic related documents", - "_source": ["year"] - } - }, + "retriever": { + "rrf": { + "retrievers": [ + { + "standard": { + "query": { + "query_string": { + "query": "(information retrieval) OR (artificial intelligence)", + "default_field": "text" + } + } + } + }, + { + "knn": { + "field": "vector", + "query_vector": [ + 0.23, + 0.67, + 0.89 + ], + "k": 3, + "num_candidates": 5 + } + } + ], + "rank_window_size": 10, + "rank_constant": 1 + } + }, + "collapse": { + "field": "year", + "inner_hits": { + "name": "topic related documents", + "_source": [ + "year" + ] + } + }, "_source": false } ---- @@ -1114,44 +1116,44 @@ Let's start by reranking the results of the `rrf` retriever in our previous exam ---- GET retrievers_example/_search { - "retriever": { - "text_similarity_reranker": { - "retriever": { - "rrf": { - "retrievers": [ - { - "standard":{ - "query":{ - "query_string":{ - "query": "(information retrieval) OR (artificial intelligence)", - "default_field": "text" - } - } - } - }, - { - "knn": { - "field": "vector", - "query_vector": [ - 0.23, - 0.67, - 0.89 - ], - "k": 3, - "num_candidates": 5 - } - } - ], - "rank_window_size": 10, - "rank_constant": 1 - } - }, - "field": "text", - "inference_id": "my-rerank-model", - "inference_text": "What are the state of the art applications of AI in information retrieval?" - } - }, - "_source": false + "retriever": { + "text_similarity_reranker": { + "retriever": { + "rrf": { + "retrievers": [ + { + "standard": { + "query": { + "query_string": { + "query": "(information retrieval) OR (artificial intelligence)", + "default_field": "text" + } + } + } + }, + { + "knn": { + "field": "vector", + "query_vector": [ + 0.23, + 0.67, + 0.89 + ], + "k": 3, + "num_candidates": 5 + } + } + ], + "rank_window_size": 10, + "rank_constant": 1 + } + }, + "field": "text", + "inference_id": "my-rerank-model", + "inference_text": "What are the state of the art applications of AI in information retrieval?" + } + }, + "_source": false } ---- @@ -1221,34 +1223,34 @@ imagine we have a computationally expensive reranker that's specialized for AI c ---- GET retrievers_example/_search { - "retriever": { - "text_similarity_reranker": { - "retriever": { - "text_similarity_reranker": { - "retriever": { - "knn": { - "field": "vector", - "query_vector": [ - 0.23, - 0.67, - 0.89 - ], - "k": 3, - "num_candidates": 5 - } - }, - "rank_window_size": 100, - "field": "text", - "inference_id": "my-rerank-model", - "inference_text": "What are the state of the art applications of AI in information retrieval?" - } - }, - "rank_window_size": 10, - "field": "text", - "inference_id": "my-other-more-expensive-rerank-model", - "inference_text": "Applications of Large Language Models in technology and their impact on user satisfaction" - } - }, + "retriever": { + "text_similarity_reranker": { + "retriever": { + "text_similarity_reranker": { + "retriever": { + "knn": { + "field": "vector", + "query_vector": [ + 0.23, + 0.67, + 0.89 + ], + "k": 3, + "num_candidates": 5 + } + }, + "rank_window_size": 100, + "field": "text", + "inference_id": "my-rerank-model", + "inference_text": "What are the state of the art applications of AI in information retrieval?" + } + }, + "rank_window_size": 10, + "field": "text", + "inference_id": "my-other-more-expensive-rerank-model", + "inference_text": "Applications of Large Language Models in technology and their impact on user satisfaction" + } + }, "_source": false } ----