Supported data types for retriever input schema fields. Retriever input schemas define what parameters users can provide when executing a retriever. This includes all bucket schema types plus additional reference types. Types fall into three categories: 1. Metadata Types (JSON types): - Standard JSON-compatible types - Examples: string, number, boolean, date - Inherited from BucketSchemaFieldType 2. File Types (blobs): - Users can upload files/content as search inputs - Examples: text, image, video, pdf - Inherited from BucketSchemaFieldType 3. Reference Types (structured metadata): - Special types for referencing existing documents - Examples: document_reference - Only available in retriever input schemas (NOT in bucket schemas) DOCUMENT_REFERENCE Usage: Accept document reference for "find similar" queries. Example - Find similar products retriever: { "reference_product": { "type": "document_reference", "description": "Find products similar to this one", "required": true } } Execution input: { "inputs": { "reference_product": { "collection_id": "col_products", "document_id": "doc_item_123" } } } The system will use the pre-computed features from doc_item_123 to find similar documents without re-processing.
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STRING(value:'string') -
NUMBER(value:'number') -
INTEGER(value:'integer') -
FLOAT(value:'float') -
BOOLEAN(value:'boolean') -
OBJECT(value:'object') -
ARRAY(value:'array') -
DATE(value:'date') -
DATETIME(value:'datetime') -
TEXT(value:'text') -
IMAGE(value:'image') -
AUDIO(value:'audio') -
VIDEO(value:'video') -
PDF(value:'pdf') -
EXCEL(value:'excel') -
DOCUMENT_REFERENCE(value:'document_reference')