/opt/canhelp/node_modules/drizzle-orm/sql/functions
Edit: /opt/canhelp/node_modules/drizzle-orm/sql/functions/vector.d.ts (4537B)
import type { AnyColumn } from "../../column.js";
import type { TypedQueryBuilder } from "../../query-builders/query-builder.js";
import { type SQL, type SQLWrapper } from "../sql.js";
/**
* Used in sorting and in querying, if used in sorting,
* this specifies that the given column or expression should be sorted in an order
* that minimizes the L2 distance to the given value.
* If used in querying, this specifies that it should return the L2 distance
* between the given column or expression and the given value.
*
* ## Examples
*
* ```ts
* // Sort cars by embedding similarity
* // to the given embedding
* db.select().from(cars)
* .orderBy(l2Distance(cars.embedding, embedding));
* ```
*
* ```ts
* // Select distance of cars and embedding
* // to the given embedding
* db.select({distance: l2Distance(cars.embedding, embedding)}).from(cars)
* ```
*/
export declare function l2Distance(column: SQLWrapper | AnyColumn, value: number[] | string[] | TypedQueryBuilder
| string): SQL;
/**
* L1 distance is one of the possible distance measures between two probability distribution vectors and it is
* calculated as the sum of the absolute differences.
* The smaller the distance between the observed probability vectors, the higher the accuracy of the synthetic data
*
* ## Examples
*
* ```ts
* // Sort cars by embedding similarity
* // to the given embedding
* db.select().from(cars)
* .orderBy(l1Distance(cars.embedding, embedding));
* ```
*
* ```ts
* // Select distance of cars and embedding
* // to the given embedding
* db.select({distance: l1Distance(cars.embedding, embedding)}).from(cars)
* ```
*/
export declare function l1Distance(column: SQLWrapper | AnyColumn, value: number[] | string[] | TypedQueryBuilder | string): SQL;
/**
* Used in sorting and in querying, if used in sorting,
* this specifies that the given column or expression should be sorted in an order
* that minimizes the inner product distance to the given value.
* If used in querying, this specifies that it should return the inner product distance
* between the given column or expression and the given value.
*
* ## Examples
*
* ```ts
* // Sort cars by embedding similarity
* // to the given embedding
* db.select().from(cars)
* .orderBy(innerProduct(cars.embedding, embedding));
* ```
*
* ```ts
* // Select distance of cars and embedding
* // to the given embedding
* db.select({ distance: innerProduct(cars.embedding, embedding) }).from(cars)
* ```
*/
export declare function innerProduct(column: SQLWrapper | AnyColumn, value: number[] | string[] | TypedQueryBuilder | string): SQL;
/**
* Used in sorting and in querying, if used in sorting,
* this specifies that the given column or expression should be sorted in an order
* that minimizes the cosine distance to the given value.
* If used in querying, this specifies that it should return the cosine distance
* between the given column or expression and the given value.
*
* ## Examples
*
* ```ts
* // Sort cars by embedding similarity
* // to the given embedding
* db.select().from(cars)
* .orderBy(cosineDistance(cars.embedding, embedding));
* ```
*
* ```ts
* // Select distance of cars and embedding
* // to the given embedding
* db.select({distance: cosineDistance(cars.embedding, embedding)}).from(cars)
* ```
*/
export declare function cosineDistance(column: SQLWrapper | AnyColumn, value: number[] | string[] | TypedQueryBuilder | string): SQL;
/**
* Hamming distance between two strings or vectors of equal length is the number of positions at which the
* corresponding symbols are different. In other words, it measures the minimum number of
* substitutions required to change one string into the other, or equivalently,
* the minimum number of errors that could have transformed one string into the other
*
* ## Examples
*
* ```ts
* // Sort cars by embedding similarity
* // to the given embedding
* db.select().from(cars)
* .orderBy(hammingDistance(cars.embedding, embedding));
* ```
*/
export declare function hammingDistance(column: SQLWrapper | AnyColumn, value: number[] | string[] | TypedQueryBuilder | string): SQL;
/**
* ## Examples
*
* ```ts
* // Sort cars by embedding similarity
* // to the given embedding
* db.select().from(cars)
* .orderBy(jaccardDistance(cars.embedding, embedding));
* ```
*/
export declare function jaccardDistance(column: SQLWrapper | AnyColumn, value: number[] | string[] | TypedQueryBuilder | string): SQL;