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dealplustech-astro/node_modules/drizzle-orm/sql/functions/vector.d.cts

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+import type { AnyColumn } from "../../column.cjs";
+import type { TypedQueryBuilder } from "../../query-builders/query-builder.cjs";
+import { type SQL, type SQLWrapper } from "../sql.cjs";
+/**
+ * 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<any> | 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<any> | 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<any> | 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<any> | 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<any> | 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<any> | string): SQL;