<cfcollection>

edit

Allows you to create and administer Search collections.

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This tag is also supported within <cfscript>


		<cfcollection
    engine=string
    categories=boolean
    action=create|repair|delete|optimize|list|map|categoryList
    collection=string
    path=string
    language=string
    name=string
    mode=hybrid|keyword|vector
    embedding=string
    ratio=numeric
>

Attribute	Description	Default
engine _{string, optional}	edit This attribute only exists for compatibility reasons to other CFML engines, the attribute is completely ignored by Lucee.
categories _{boolean, optional}	edit Used only for creating a collection
action _{string, optional}	edit Specifies the action to perform.	list
collection _{string, optional}	edit Specifies a collection name or an alias if action = "map"
path _{string, optional}	edit Absolute path to a Lucene collection.
language _{string, optional}	edit language the collection is based on: possible values are: english, german, russian, dutch, french, italian, norwegian, portuguese, spanish, brazilian, chinese, greek, thai, danish, japanese, norwegian, korean
name _{string, optional}	edit Name for the query results returned by the list action. _{Alias: variable}
mode _{string, optional}	edit Specifies the search algorithm to use when querying this collection. Options: `keyword`: Traditional term-based search using Lucene (default) `vector`: Pure semantic search using vector embeddings `hybrid`: Combines keyword and vector search for optimal results, balancing term matching with semantic understanding When set to `keyword`, the `embedding` attribute is ignored. Vector and hybrid modes require an embedding service to be specified.
embedding _{string, optional}	edit Specifies the embedding service to use for creating vector representations of documents, enabling semantic search capabilities. Valid options: `TF-IDF`: Uses Term Frequency-Inverse Document Frequency statistical method for generating document vectors `word2vec`: Uses pre-trained word vectors to create document embeddings with better semantic understanding class-name: Name of a custom class implementing the `org.lucee.extension.search.lucene.embedding.EmbeddingService` interface _{Alias: embeddingservice}
ratio _{numeric, optional}	edit When `mode="hybrid"`, this value controls the balance between keyword and vector search components. Value range is 0.0 to 1.0, where: 0.5: Equal weight given to both keyword and vector search (default) Values greater than 0.5: Greater emphasis on vector search (semantic matching) Values less than 0.5: Greater emphasis on keyword search (exact term matching) For example, a ratio of 0.7 would give 70% weight to vector search and 30% to keyword search. This attribute is ignored when mode is not "hybrid".

Examples

edit

<cfcollection action="Create" collection="colName" path= "path" language="">
<cfcollection action="Delete" collection="colName">

<cfcollection>

Examples

See also