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/*
* Hotdata API
*
* Powerful data platform API for instant databases, queries, and analytics.
*
* The version of the OpenAPI document: 1.0.0
* Contact: developers@hotdata.dev
* Generated by: https://openapi-generator.tech
*/
use crate::models;
use serde::{Deserialize, Serialize};
/// IndexEntryResponse : One index in a cross-table listing: the index itself plus the connection, schema, and table it belongs to.
#[derive(Clone, Default, Debug, PartialEq, Serialize, Deserialize)]
pub struct IndexEntryResponse {
/// How this vector index organises the vectors it searches: `hnsw` or `ivf`. Absent for BM25 and sorted indexes.
#[serde(rename = "algorithm", skip_serializing_if = "Option::is_none")]
pub algorithm: Option<String>,
#[serde(rename = "columns")]
pub columns: Vec<String>,
#[serde(rename = "created_at")]
pub created_at: String,
#[serde(rename = "index_name")]
pub index_name: String,
#[serde(rename = "index_type")]
pub index_type: String,
/// Distance metric this index was built with. Only present for vector indexes.
#[serde(rename = "metric", skip_serializing_if = "Option::is_none")]
pub metric: Option<String>,
/// Number of clusters an `ivf` index was built with. This can be smaller than the `nlist` requested when the index was created, because the number is capped by how many vectors the clusters were fitted to. Absent for every other kind of index.
#[serde(rename = "nlist", skip_serializing_if = "Option::is_none")]
pub nlist: Option<i64>,
/// How much of an `ivf` index a search reads, as a fraction greater than 0 and at most 1, when the index was created with one. When absent, the server chooses how much each search reads: a width measured on this index's own data when it was built, scaled to the number of results a search asks for, or a server default when no measurement could be made. Absent for every other kind of index.
#[serde(rename = "probe_fraction", skip_serializing_if = "Option::is_none")]
pub probe_fraction: Option<f64>,
/// Source text column for an embedding-backed vector index. A query searches it via `vector_distance(<source_column>, …)`; the indexed `columns` hold the generated embedding column instead. Absent for BM25, sorted, and direct (existing-column) vector indexes.
#[serde(rename = "source_column", skip_serializing_if = "Option::is_none")]
pub source_column: Option<String>,
#[serde(rename = "status")]
pub status: models::IndexStatus,
#[serde(rename = "updated_at")]
pub updated_at: String,
/// How precisely this vector index stores each number of a vector. Always present for an `ivf` index, which stores `int8` unless it was created with another precision. For an `hnsw` index it is present only when the index was created with an explicit precision; absent means it stores at the same precision as the column. Absent for BM25 and sorted indexes.
#[serde(rename = "vector_precision", skip_serializing_if = "Option::is_none")]
pub vector_precision: Option<String>,
#[serde(
rename = "connection_id",
default,
with = "::serde_with::rust::double_option",
skip_serializing_if = "Option::is_none"
)]
pub connection_id: Option<Option<String>>,
#[serde(rename = "schema_name")]
pub schema_name: String,
#[serde(rename = "table_name")]
pub table_name: String,
}
impl IndexEntryResponse {
/// One index in a cross-table listing: the index itself plus the connection, schema, and table it belongs to.
pub fn new(
columns: Vec<String>,
created_at: String,
index_name: String,
index_type: String,
status: models::IndexStatus,
updated_at: String,
schema_name: String,
table_name: String,
) -> IndexEntryResponse {
IndexEntryResponse {
algorithm: None,
columns,
created_at,
index_name,
index_type,
metric: None,
nlist: None,
probe_fraction: None,
source_column: None,
status,
updated_at,
vector_precision: None,
connection_id: None,
schema_name,
table_name,
}
}
}