Qdrant · Schema
VectorParams
Params of single vector data storage
Artificial IntelligenceVector Databases
Properties
| Name | Type | Description |
|---|---|---|
| size | integer | Size of a vectors used |
| distance | object | |
| hnsw_config | object | Custom params for HNSW index. If none - values from collection configuration are used. |
| quantization_config | object | Custom params for quantization. If none - values from collection configuration are used. |
| on_disk | boolean | If true, vectors are served from disk, improving RAM usage at the cost of latency Default: false |
| datatype | object | Defines which datatype should be used to represent vectors in the storage. Choosing different datatypes allows to optimize memory usage and performance vs accuracy. - For `float32` datatype - vectors |
| multivector_config | object |
JSON Schema
{
"$schema": "https://json-schema.org/draft/2020-12/schema",
"$id": "#/components/schemas/VectorParams",
"title": "VectorParams",
"description": "Params of single vector data storage",
"type": "object",
"required": [
"distance",
"size"
],
"properties": {
"size": {
"description": "Size of a vectors used",
"type": "integer",
"format": "uint64",
"minimum": 1
},
"distance": {
"$ref": "#/components/schemas/Distance"
},
"hnsw_config": {
"description": "Custom params for HNSW index. If none - values from collection configuration are used.",
"anyOf": [
{
"$ref": "#/components/schemas/HnswConfigDiff"
},
{
"nullable": true
}
]
},
"quantization_config": {
"description": "Custom params for quantization. If none - values from collection configuration are used.",
"anyOf": [
{
"$ref": "#/components/schemas/QuantizationConfig"
},
{
"nullable": true
}
]
},
"on_disk": {
"description": "If true, vectors are served from disk, improving RAM usage at the cost of latency Default: false",
"type": "boolean",
"nullable": true
},
"datatype": {
"description": "Defines which datatype should be used to represent vectors in the storage. Choosing different datatypes allows to optimize memory usage and performance vs accuracy.\n\n- For `float32` datatype - vectors are stored as single-precision floating point numbers, 4 bytes. - For `float16` datatype - vectors are stored as half-precision floating point numbers, 2 bytes. - For `uint8` datatype - vectors are stored as unsigned 8-bit integers, 1 byte. It expects vector elements to be in range `[0, 255]`.",
"anyOf": [
{
"$ref": "#/components/schemas/Datatype"
},
{
"nullable": true
}
]
},
"multivector_config": {
"anyOf": [
{
"$ref": "#/components/schemas/MultiVectorConfig"
},
{
"nullable": true
}
]
}
}
}
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