{"id":16022,"date":"2024-07-16T12:50:20","date_gmt":"2024-07-16T19:50:20","guid":{"rendered":"https:\/\/www.couchbase.com\/blog\/?p=16022"},"modified":"2025-06-13T16:36:49","modified_gmt":"2025-06-13T23:36:49","slug":"couchbase-vector-search-in-5-minutes","status":"publish","type":"post","link":"https:\/\/www.couchbase.com\/blog\/es\/couchbase-vector-search-in-5-minutes\/","title":{"rendered":"Empieza a usar Couchbase Vector Search en 5 minutos"},"content":{"rendered":"<h2><span style=\"font-weight: 400;\">Qu\u00e9 es un vector<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Un vector es un objeto que representa un elemento del mundo real como un <em>matriz de n\u00fameros flotantes<\/em>.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Cada elemento del mundo real se representa en formato vectorial (como una matriz) y tiene muchas dimensiones (atributos) asociadas al objeto en funci\u00f3n de sus caracter\u00edsticas.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Por ejemplo, si queremos representar Colores en formato Vectorial, podemos crear un array de valores de atributos. Ejemplo <\/span><span style=\"font-weight: 400;\">[\"R\", \"G\", \"B\"]<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Cada color de una imagen RGB est\u00e1 representado por tres valores: la cantidad de luz roja, verde y azul presente. Estos valores suelen oscilar entre 0 y 255, indicando la intensidad de cada componente de color.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Rojo puro= <\/span><span style=\"font-weight: 400;\">[ \"255\", \"0\", \"0\"]<\/span><\/p>\n<p><span style=\"font-weight: 400;\">D\u00f3nde:<\/span><\/p>\n<ul>\n<li style=\"list-style-type: none;\">\n<ul>\n<li><span style=\"font-weight: 400;\">R representa la intensidad del rojo (en este caso, intensidad m\u00e1xima, 255),<\/span><\/li>\n<li><span style=\"font-weight: 400;\">G representa la intensidad del verde (en este caso, 0, por lo que no hay verde),<\/span><\/li>\n<li><span style=\"font-weight: 400;\">B representa la intensidad del azul (en este caso, 0, por lo que no hay azul).<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p>Del mismo modo, puede representar cualquier color utilizando este formato vectorial RGB, con valores que van de 0 a 255 para cada canal de color.<\/p>\n<p><span style=\"font-weight: 400;\">Si queremos encontrar coincidencias cercanas para el color rojo, podemos averiguarlo bas\u00e1ndonos en el primer valor del atributo del color.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Los objetos del mundo real pueden tener muchos otros atributos que tienen que representar y, por lo tanto, un Vector que representa un objeto del mundo real est\u00e1 representado por una matriz m\u00e1s grande de 512, 1028, 1536 o 2048 valores de atributos.<\/span><\/p>\n<h2><span style=\"font-weight: 400;\">\u00bfQu\u00e9 es la b\u00fasqueda vectorial?<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">La b\u00fasqueda vectorial es un m\u00e9todo de b\u00fasqueda de elementos basado en su representaci\u00f3n vectorial. En la b\u00fasqueda vectorial, cada elemento se representa en un espacio multidimensional en el que cada dimensi\u00f3n representa el valor del atributo del elemento.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Encontrar\u00e1 m\u00e1s informaci\u00f3n en:<\/span><\/p>\n<ul>\n<li style=\"list-style-type: none;\">\n<ul>\n<li><span style=\"font-weight: 400;\"><a href=\"https:\/\/www.couchbase.com\/blog\/es\/products\/vector-search\/\">Capacidad de b\u00fasqueda vectorial de Couchbase<\/a><\/span><\/li>\n<li><a href=\"https:\/\/www.couchbase.com\/blog\/es\/tag\/vector-search\/\"><span style=\"font-weight: 400;\">Blogs sobre B\u00fasqueda vectorial<\/span><\/a> y <a href=\"https:\/\/www.couchbase.com\/blog\/es\/vector-databases\/\">Bases de datos vectoriales<\/a><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<h3><span style=\"font-weight: 400;\">Casos de uso en el sector<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">La b\u00fasqueda vectorial puede utilizarse en diversos sectores y para distintos casos de uso:<\/span><\/p>\n<ol>\n<li style=\"list-style-type: none;\">\n<ol>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Generaci\u00f3n de contenidos<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Detecci\u00f3n de anomal\u00edas<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">B\u00fasqueda h\u00edbrida<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Chatbots con IA.<\/span><\/li>\n<\/ol>\n<\/li>\n<\/ol>\n<h2><span style=\"font-weight: 400;\">\u00bfB\u00fasqueda vectorial frente a b\u00fasqueda de texto completo?<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Tanto la b\u00fasqueda vectorial como la b\u00fasqueda de texto completo son m\u00e9todos utilizados para buscar en colecciones de datos, pero funcionan de forma diferente y se adaptan a distintos tipos de datos y casos de uso.<\/span><\/p>\n<p><b>B\u00fasqueda de texto completo:<\/b><span style=\"font-weight: 400;\"> es una t\u00e9cnica utilizada en la recuperaci\u00f3n de informaci\u00f3n para buscar y analizar el contenido textual de documentos o bases de datos. A diferencia de los m\u00e9todos de b\u00fasqueda tradicionales, que se basan en frases exactas o palabras clave, los motores de b\u00fasqueda de texto completo analizan el contenido de los documentos o registros para realizar b\u00fasquedas basadas en el significado y el contexto de las palabras.<\/span><span style=\"font-weight: 400;\">.<\/span><span style=\"font-weight: 400;\">\u00a0<\/span><\/p>\n<table>\n<tbody>\n<tr>\n<td><\/td>\n<td><strong>\u00c1rea de comparaci\u00f3n<\/strong><\/td>\n<td><strong>B\u00fasqueda de texto completo<\/strong><\/td>\n<td><strong>B\u00fasqueda vectorial<\/strong><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">1<\/span><\/td>\n<td><strong>Representaci\u00f3n de datos<\/strong><\/td>\n<td><span style=\"font-weight: 400;\">Los datos se representan como documentos de texto o cadenas<\/span><\/td>\n<td><span style=\"font-weight: 400;\">Los datos se representan como vectores en un espacio multidimensional<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">2<\/span><\/td>\n<td><strong>Criterios de concordancia<\/strong><\/td>\n<td><span style=\"font-weight: 400;\">Coincidencia exacta o difusa<\/span><\/td>\n<td><span style=\"font-weight: 400;\">Partido vecino m\u00e1s pr\u00f3ximo<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">3<\/span><\/td>\n<td><strong>Buscar en<\/strong><\/td>\n<td><span style=\"font-weight: 400;\">B\u00fasqueda o comparaci\u00f3n textual<\/span><\/td>\n<td><span style=\"font-weight: 400;\">B\u00fasqueda contextual o comparaci\u00f3n basada en atributos del objeto.<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">4<\/span><\/td>\n<td><strong>Caso pr\u00e1ctico<\/strong><\/td>\n<td><span style=\"font-weight: 400;\">B\u00fasqueda en un documento, p\u00e1gina web, contenido de correo electr\u00f3nico, etc.<\/span><\/td>\n<td><span style=\"font-weight: 400;\">B\u00fasqueda por audio, v\u00eddeo, imagen, texto, etc.<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2><span style=\"font-weight: 400;\">\u00bfPor qu\u00e9 Couchbase para la b\u00fasqueda vectorial?<\/span><\/h2>\n<ol>\n<li style=\"list-style-type: none;\">\n<ol>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\"><strong>Vector en todos nuestros productos<\/strong>: La primera del sector en anunciar la compatibilidad con las tres implantaciones: en la nube, local y m\u00f3vil.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\"><strong>Amplias capacidades<\/strong>: Cach\u00e9 integrada, b\u00fasqueda de texto completo, b\u00fasqueda anal\u00edtica, series temporales, clave-valor, eventos y otras funciones junto con la b\u00fasqueda vectorial en una \u00fanica plataforma.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\"><strong>Integraci\u00f3n de los ecosistemas<\/strong>: <a href=\"https:\/\/python.langchain.com\/v0.2\/docs\/integrations\/providers\/couchbase\/\">Cadena LangChain<\/a> y <a href=\"https:\/\/docs.llamaindex.ai\/en\/latest\/api_reference\/storage\/vector_store\/couchbase\/\">LlamaIndex<\/a> integraci\u00f3n.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\"><strong>Velocidad y flexibilidad demostradas<\/strong>: Arquitectura en memoria, formato json flexible e indexaci\u00f3n potente.<\/span><\/li>\n<\/ol>\n<\/li>\n<\/ol>\n<p><span style=\"font-weight: 400;\">Encontrar\u00e1 m\u00e1s informaci\u00f3n en nuestro <a href=\"https:\/\/www.couchbase.com\/blog\/es\/announcing-vector-search\/\">anuncio de lanzamiento de la b\u00fasqueda vectorial<\/a>.\u00a0<\/span><\/p>\n<h2><span style=\"font-weight: 400;\">Requisitos previos<\/span><\/h2>\n<ol>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Couchbase Capella o Couchbase Server 7.6 EE\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Ya ha creado una base de datos<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Datos de la muestra:<\/span>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Descargar archivo <\/span><a href=\"https:\/\/cbc-remote-execution-examples-prod.s3.amazonaws.com\/color_data_2vectors.zip\"><span style=\"font-weight: 400;\">datos_colores_2vectores.zip<\/span><\/a><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Para este ejemplo, utilizaremos el <em>rgb.json<\/em> archivo\u00a0<\/span><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Archivo de \u00edndice: <em>color-index.json<\/em><\/span><span style=\"font-weight: 400;\"><br \/>\n<\/span><\/p>\n<ul>\n<li><em>color-index.json:<\/em>\n<pre class=\"height:300 nums:false scroll:true minimize:true lang:js decode:true\">{\r\n    \"type\": \"fulltext-index\",\r\n    \"name\": \"color-index\",\r\n    \"sourceType\": \"gocbcore\",\r\n    \"sourceName\": \"vector-sample\",\r\n    \"sourceUUID\": \"789365cccdf940ee2814a5dd2752040a\",\r\n    \"planParams\": {\r\n      \"maxPartitionsPerPIndex\": 512,\r\n      \"indexPartitions\": 1\r\n    },\r\n    \"params\": {\r\n      \"doc_config\": {\r\n        \"docid_prefix_delim\": \"\",\r\n        \"docid_regexp\": \"\",\r\n        \"mode\": \"scope.collection.type_field\",\r\n        \"type_field\": \"type\"\r\n      },\r\n      \"mapping\": {\r\n        \"analysis\": {},\r\n        \"default_analyzer\": \"standard\",\r\n        \"default_datetime_parser\": \"dateTimeOptional\",\r\n        \"default_field\": \"_all\",\r\n        \"default_mapping\": {\r\n          \"dynamic\": false,\r\n          \"enabled\": false\r\n        },\r\n        \"default_type\": \"_default\",\r\n        \"docvalues_dynamic\": false,\r\n        \"index_dynamic\": false,\r\n        \"store_dynamic\": false,\r\n        \"type_field\": \"_type\",\r\n        \"types\": {\r\n        \"color.rgb\": {\r\n          \"dynamic\": false,\r\n          \"enabled\": true,\r\n          \"properties\": {\r\n            \"brightness\": {\r\n              \"dynamic\": false,\r\n              \"enabled\": true,\r\n              \"fields\": [\r\n                {\r\n                  \"index\": true,\r\n                  \"name\": \"brightness\",\r\n                  \"store\": true,\r\n                  \"type\": \"number\"\r\n                }\r\n              ]\r\n            },\r\n            \"color\": {\r\n              \"dynamic\": false,\r\n              \"enabled\": true,\r\n              \"fields\": [\r\n                {\r\n                  \"analyzer\": \"en\",\r\n                  \"index\": true,\r\n                  \"name\": \"color\",\r\n                  \"store\": true,\r\n                  \"type\": \"text\"\r\n                }\r\n              ]\r\n            },\r\n            \"colorvect_dot\": {\r\n              \"dynamic\": false,\r\n              \"enabled\": true,\r\n              \"fields\": [\r\n                {\r\n                  \"dims\": 3,\r\n                  \"index\": true,\r\n                  \"name\": \"colorvect_dot\",\r\n                  \"similarity\": \"dot_product\",\r\n                  \"type\": \"vector\"\r\n                }\r\n              ]\r\n            },\r\n            \"colorvect_l2\": {\r\n              \"dynamic\": false,\r\n              \"enabled\": true,\r\n              \"fields\": [\r\n                {\r\n                  \"dims\": 3,\r\n                  \"index\": true,\r\n                  \"name\": \"colorvect_l2\",\r\n                  \"similarity\": \"l2_norm\",\r\n                  \"type\": \"vector\"\r\n                }\r\n              ]\r\n            },\r\n            \"description\": {\r\n              \"dynamic\": false,\r\n              \"enabled\": true,\r\n              \"fields\": [\r\n                {\r\n                  \"analyzer\": \"en\",\r\n                  \"index\": true,\r\n                  \"name\": \"description\",\r\n                  \"store\": true,\r\n                  \"type\": \"text\"\r\n                }\r\n              ]\r\n            },\r\n            \"embedding_vector_dot\": {\r\n              \"dynamic\": false,\r\n              \"enabled\": true,\r\n              \"fields\": [\r\n                {\r\n                  \"dims\": 1536,\r\n                  \"index\": true,\r\n                  \"name\": \"embedding_vector_dot\",\r\n                  \"similarity\": \"dot_product\",\r\n                  \"type\": \"vector\"\r\n                }\r\n              ]\r\n            }\r\n          }\r\n        }\r\n      }\r\n    },\r\n    \"store\": {\r\n      \"indexType\": \"scorch\",\r\n      \"segmentVersion\": 16\r\n    }\r\n  },\r\n  \"sourceParams\": {}\r\n}<\/pre>\n<\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Ejemplo de definici\u00f3n de b\u00fasqueda:<br \/>\n<\/span><code>{\"fields\": [\"*\"], \"query\": { \"match_none\": \"\" }, \"knn\": [ { \"k\": 2, \"field\": \"colorvect_l2\", \"vector\": [ 0, 0, 128 ] } ] }<\/code><\/li>\n<\/ol>\n<h2><span style=\"font-weight: 400;\">Pasos<\/span><\/h2>\n<h3><span style=\"font-weight: 400;\">Crear datos de muestra<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">Abra Capella UI, vaya a <em>Base de datos<\/em>e inicie la importaci\u00f3n de datos mediante la importaci\u00f3n desde el navegador utilizando las herramientas de datos:<\/span><\/p>\n<ul>\n<li style=\"list-style-type: none;\">\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"2\"><span style=\"font-weight: 400;\">Utilice el archivo de datos de ejemplo rgb.json proporcionado en los requisitos previos.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"2\"><span style=\"font-weight: 400;\">Elija una opci\u00f3n <strong>cargar desde el navegador<\/strong>.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"2\"><span style=\"font-weight: 400;\">Selecciona el archivo: <em>rgb.json<\/em><\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"2\"><span style=\"font-weight: 400;\">Especificar nuevo cubo con nombre: <em>vector-muestra<\/em><\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"2\"><span style=\"font-weight: 400;\">Especificar nuevo \u00e1mbito con nombre: <em>color<\/em><\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"2\"><span style=\"font-weight: 400;\">Especificar nueva colecci\u00f3n con nombre: <em>rgb<\/em><\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"2\"><span style=\"font-weight: 400;\">En el paso 3, <em>previsualizar<\/em> tus datos,<br \/>\n<\/span>Elija c\u00f3mo Capella crea identificadores para cada uno de sus documentos. Seleccione la opci\u00f3n como campo y especifique el campo: <strong>Id<\/strong> como se muestra en la siguiente captura de pantalla.<\/li>\n<li style=\"font-weight: 400;\" aria-level=\"2\"><span style=\"font-weight: 400;\">Haz clic en Importar.<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p><a href=\"https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/2024\/07\/image2-1.png\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-16023\" style=\"border: 1px solid black;\" src=\"https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/2024\/07\/image2-1.png\" alt=\"\" width=\"571\" height=\"651\" srcset=\"https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2024\/07\/image2-1.png 571w, https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2024\/07\/image2-1-263x300.png 263w, https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2024\/07\/image2-1-300x342.png 300w\" sizes=\"auto, (max-width: 571px) 100vw, 571px\" \/><\/a><\/p>\n<p><a href=\"https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/2024\/07\/image7.png\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-large wp-image-16024\" style=\"border: 1px solid black;\" src=\"https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/2024\/07\/image7-1024x423.png\" alt=\"\" width=\"900\" height=\"372\" srcset=\"https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2024\/07\/image7-1024x423.png 1024w, https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2024\/07\/image7-300x124.png 300w, https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2024\/07\/image7-768x317.png 768w, https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2024\/07\/image7-1536x634.png 1536w, https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2024\/07\/image7-1320x545.png 1320w, https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2024\/07\/image7.png 1900w\" sizes=\"auto, (max-width: 900px) 100vw, 900px\" \/><\/a><\/p>\n<p><a href=\"https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/2024\/07\/image6.png\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-large wp-image-16025\" style=\"border: 1px solid black;\" src=\"https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/2024\/07\/image6-1024x432.png\" alt=\"\" width=\"900\" height=\"380\" srcset=\"https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2024\/07\/image6-1024x432.png 1024w, https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2024\/07\/image6-300x127.png 300w, https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2024\/07\/image6-768x324.png 768w, https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2024\/07\/image6-1536x649.png 1536w, https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2024\/07\/image6-1320x558.png 1320w, https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2024\/07\/image6.png 1906w\" sizes=\"auto, (max-width: 900px) 100vw, 900px\" \/><\/a><\/p>\n<h3><span style=\"font-weight: 400;\">Crear \u00edndice de b\u00fasqueda vectorial\u00a0<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">En Opciones de b\u00fasqueda en <strong>Herramientas de datos<\/strong>:<\/span><\/p>\n<ul>\n<li style=\"list-style-type: none;\">\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"2\"><strong>Crear \u00edndice de b\u00fasqueda<br \/>\n<a href=\"https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/2024\/07\/image9.png\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-16026\" style=\"border: 1px solid black;\" src=\"https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/2024\/07\/image9-1024x333.png\" alt=\"\" width=\"645\" height=\"210\" srcset=\"https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2024\/07\/image9-1024x333.png 1024w, https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2024\/07\/image9-300x97.png 300w, https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2024\/07\/image9-768x250.png 768w, https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2024\/07\/image9.png 1234w\" sizes=\"auto, (max-width: 645px) 100vw, 645px\" \/><\/a><br \/>\n<\/strong><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"2\"><span style=\"font-weight: 400;\">Seleccione <strong>modo avanzado<\/strong><\/span><\/li>\n<li aria-level=\"2\"><span style=\"font-weight: 400;\">Haga clic en <strong>\u00cdndice Definici\u00f3n<\/strong> en la parte derecha de la interfaz de usuario<\/span><\/li>\n<li aria-level=\"2\"><span style=\"font-weight: 400;\">Seleccionar opci\u00f3n <strong>Importar desde archivo<\/strong><\/span><\/li>\n<li aria-level=\"2\"><span style=\"font-weight: 400;\">Elegir archivo <em>color-index.json<\/em> especificado en los requisitos previos<\/span><\/li>\n<li aria-level=\"2\"><span style=\"font-weight: 400;\">Especifique el nombre del \u00edndice como:\u00a0<em> color-index.json<\/em><\/span><\/li>\n<li aria-level=\"2\"><span style=\"font-weight: 400;\">Elige cubo: <em>vector-muestra<\/em><\/span><\/li>\n<li aria-level=\"2\"><span style=\"font-weight: 400;\">El \u00e1mbito se rellenar\u00e1 autom\u00e1ticamente como <em>color<\/em><\/span><\/li>\n<li aria-level=\"2\"><span style=\"font-weight: 400;\">Haga clic en <strong>Crear \u00edndice<\/strong><\/span><span style=\"font-weight: 400;\"><br \/>\n<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p><a href=\"https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/2024\/07\/image5-1.png\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-large wp-image-16027\" style=\"border: 1px solid black;\" src=\"https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/2024\/07\/image5-1-1024x423.png\" alt=\"\" width=\"900\" height=\"372\" srcset=\"https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2024\/07\/image5-1-1024x423.png 1024w, https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2024\/07\/image5-1-300x124.png 300w, https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2024\/07\/image5-1-768x318.png 768w, https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2024\/07\/image5-1-1320x546.png 1320w, https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2024\/07\/image5-1.png 1323w\" sizes=\"auto, (max-width: 900px) 100vw, 900px\" \/><\/a><\/p>\n<h3><span style=\"font-weight: 400;\">Realizar una b\u00fasqueda vectorial\u00a0<\/span><\/h3>\n<p><span style=\"font-weight: 400;\">Seleccione <strong>Buscar en<\/strong> en el <em>\u00edndice de color<\/em> fila (bot\u00f3n cerca del extremo derecho)<\/span><\/p>\n<p><a href=\"https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/2024\/07\/image3-1.png\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-large wp-image-16028\" style=\"border: 1px solid black;\" src=\"https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/2024\/07\/image3-1-1024x292.png\" alt=\"\" width=\"900\" height=\"257\" srcset=\"https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2024\/07\/image3-1-1024x292.png 1024w, https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2024\/07\/image3-1-300x86.png 300w, https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2024\/07\/image3-1-768x219.png 768w, https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2024\/07\/image3-1-1320x377.png 1320w, https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2024\/07\/image3-1.png 1380w\" sizes=\"auto, (max-width: 900px) 100vw, 900px\" \/><\/a><\/p>\n<p><span style=\"font-weight: 400;\">Pegue el texto de b\u00fasqueda del paso previo en la ventana Buscar.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Haga clic en <strong>Buscar en<\/strong> para obtener un resultado (se muestra en la ventana debajo del texto de b\u00fasqueda).<\/span><\/p>\n<p><a href=\"https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/2024\/07\/image8.png\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-large wp-image-16029\" style=\"border: 1px solid black;\" src=\"https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/2024\/07\/image8-1024x371.png\" alt=\"\" width=\"900\" height=\"326\" srcset=\"https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2024\/07\/image8-1024x371.png 1024w, https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2024\/07\/image8-300x109.png 300w, https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2024\/07\/image8-768x279.png 768w, https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2024\/07\/image8-1536x557.png 1536w, https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2024\/07\/image8-1320x479.png 1320w, https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2024\/07\/image8.png 1839w\" sizes=\"auto, (max-width: 900px) 100vw, 900px\" \/><\/a><\/p>\n<p>&nbsp;<\/p>\n<h2><span style=\"font-weight: 400;\">Conclusi\u00f3n<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">En este post, hemos repasado los conceptos b\u00e1sicos de lo que es la b\u00fasqueda vectorial y c\u00f3mo empezar r\u00e1pidamente con la b\u00fasqueda vectorial con Couchbase.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Despu\u00e9s de ejecutar una b\u00fasqueda vectorial b\u00e1sica, uno puede combinar f\u00e1cilmente consultas SQL con b\u00fasqueda vectorial en Couchbase, ayudando a consolidar su pila de bases de datos y evitar escribir m\u00faltiples consultas para obtener un \u00fanico resultado significativo para una aplicaci\u00f3n.<\/span><\/p>\n<h3><span style=\"font-weight: 400;\">Empezar gratis<\/span><\/h3>\n<ul>\n<li style=\"list-style-type: none;\">\n<ul>\n<li><span style=\"font-weight: 400;\">Comienza tu <\/span><a href=\"https:\/\/cloud.couchbase.com\/sign-up\"><span style=\"font-weight: 400;\">Cuenta de prueba de 30 d\u00edas para Capella<\/span><\/a><span style=\"font-weight: 400;\"> para realizar su primer experimento hoy mismo.<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<h3><span style=\"font-weight: 400;\">Referencias<\/span><\/h3>\n<ol>\n<li style=\"list-style-type: none;\">\n<ul>\n<li><span style=\"font-weight: 400;\"><a href=\"https:\/\/www.couchbase.com\/blog\/es\/announcing-vector-search\/\">Anuncio de lanzamiento de Vector Search<\/a>\u00a0<\/span><\/li>\n<li><span style=\"font-weight: 400;\"><a href=\"https:\/\/www.couchbase.com\/blog\/es\/products\/vector-search\/\">Capacidad de b\u00fasqueda vectorial de Couchbase<\/a><\/span><\/li>\n<li><a href=\"https:\/\/www.couchbase.com\/blog\/es\/tag\/vector-search\/\"><span style=\"font-weight: 400;\">Blogs sobre B\u00fasqueda vectorial<\/span><\/a> y <a href=\"https:\/\/www.couchbase.com\/blog\/es\/vector-databases\/\">Bases de datos vectoriales<\/a><\/li>\n<\/ul>\n<\/li>\n<\/ol>\n<p>&nbsp;<\/p>","protected":false},"excerpt":{"rendered":"<p>What is a Vector A Vector is an object that represents a real-world item as an array of floating numbers.\u00a0 Each item in the real world is represented in Vector format(as an array) and has many dimensions (attributes) associated with [&hellip;]<\/p>","protected":false},"author":85424,"featured_media":16031,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[10122,1815,2225,1816,9936,9937],"tags":[9963,9995],"ppma_author":[9996],"class_list":["post-16022","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-artificial-intelligence-ai","category-best-practices-and-tutorials","category-cloud","category-couchbase-server","category-search","category-vector-search","tag-langchain","tag-llamaindex"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v26.0 (Yoast SEO v26.0) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Get Started With Couchbase Vector Search In 5 Minutes - The Couchbase Blog<\/title>\n<meta name=\"description\" content=\"Vector search and full-text search are both methods used for 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