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@google-cloud/firestore

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"use strict"; /** * Copyright 2024 Google LLC. All Rights Reserved. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ Object.defineProperty(exports, "__esModule", { value: true }); exports.VectorQuery = void 0; const field_value_1 = require("../field-value"); const path_1 = require("../path"); const util_1 = require("../util"); const query_util_1 = require("./query-util"); const vector_query_snapshot_1 = require("./vector-query-snapshot"); const query_profile_1 = require("../query-profile"); /** * A query that finds the documents whose vector fields are closest to a certain query vector. * Create an instance of `VectorQuery` with {@link Query.findNearest}. */ class VectorQuery { /** * @private * @internal */ constructor(_query, _options) { this._query = _query; this._options = _options; this._queryUtil = new query_util_1.QueryUtil(_query._firestore, _query._queryOptions, _query._serializer); } /** The query whose results participants in the vector search. Filtering * performed by the query will apply before the vector search. **/ get query() { return this._query; } /** * @private * @internal */ get _rawVectorField() { return typeof this._options.vectorField === 'string' ? this._options.vectorField : this._options.vectorField.toString(); } /** * @private * @internal */ get _rawDistanceResultField() { if (typeof this._options.distanceResultField === 'undefined') return; return typeof this._options.distanceResultField === 'string' ? this._options.distanceResultField : this._options.distanceResultField.toString(); } /** * @private * @internal */ get _rawQueryVector() { return Array.isArray(this._options.queryVector) ? this._options.queryVector : this._options.queryVector.toArray(); } /** * Plans and optionally executes this vector search query. Returns a Promise that will be * resolved with the planner information, statistics from the query execution (if any), * and the query results (if any). * * @return A Promise that will be resolved with the planner information, statistics * from the query execution (if any), and the query results (if any). */ async explain(options) { if (options === undefined) { options = {}; } const { result, explainMetrics } = await this._getResponse(options); if (!explainMetrics) { throw new Error('No explain results'); } return new query_profile_1.ExplainResults(explainMetrics, result || null); } /** * Executes this vector search query. * * @returns A promise that will be resolved with the results of the query. */ async get() { const { result } = await this._getResponse(); if (!result) { throw new Error('No VectorQuerySnapshot result'); } return result; } _getResponse(explainOptions) { return this._queryUtil._getResponse(this, /*transactionOrReadTime*/ undefined, // VectorQuery cannot be retried with cursors as they do not support cursors yet. /*retryWithCursor*/ false, explainOptions); } /** * Internal streaming method that accepts an optional transaction ID. * * @param transactionId - A transaction ID. * @private * @internal * @returns A stream of document results. */ _stream(transactionId) { return this._queryUtil._stream(this, transactionId, /*retryWithCursor*/ false); } /** * Internal method for serializing a query to its proto * representation with an optional transaction id. * * @private * @internal * @returns Serialized JSON for the query. */ toProto(transactionOrReadTime, explainOptions) { var _a, _b, _c; const queryProto = this._query.toProto(transactionOrReadTime); const queryVector = Array.isArray(this._options.queryVector) ? new field_value_1.VectorValue(this._options.queryVector) : this._options.queryVector; queryProto.structuredQuery.findNearest = { limit: { value: this._options.limit }, distanceMeasure: this._options.distanceMeasure, vectorField: { fieldPath: path_1.FieldPath.fromArgument(this._options.vectorField) .formattedName, }, queryVector: queryVector._toProto(this._query._serializer), distanceResultField: ((_a = this._options) === null || _a === void 0 ? void 0 : _a.distanceResultField) ? path_1.FieldPath.fromArgument(this._options.distanceResultField) .formattedName : undefined, distanceThreshold: ((_b = this._options) === null || _b === void 0 ? void 0 : _b.distanceThreshold) ? { value: (_c = this._options) === null || _c === void 0 ? void 0 : _c.distanceThreshold } : undefined, }; if (explainOptions) { queryProto.explainOptions = explainOptions; } return queryProto; } /** * Construct the resulting vector snapshot for this query with given documents. * * @private * @internal */ _createSnapshot(readTime, size, docs, changes) { return new vector_query_snapshot_1.VectorQuerySnapshot(this, readTime, size, docs, changes); } /** * Construct a new vector query whose result will start after To support stream(). * This now throws an exception because cursors are not supported from the backend for vector queries yet. * * @private * @internal * @returns Serialized JSON for the query. */ startAfter( // eslint-disable-next-line @typescript-eslint/no-unused-vars ...fieldValuesOrDocumentSnapshot) { throw new Error('Unimplemented: Vector query does not support cursors yet.'); } /** * Compares this object with the given object for equality. * * This object is considered "equal" to the other object if and only if * `other` performs the same vector distance search as this `VectorQuery` and * the underlying Query of `other` compares equal to that of this object * using `Query.isEqual()`. * * @param other - The object to compare to this object for equality. * @returns `true` if this object is "equal" to the given object, as * defined above, or `false` otherwise. */ isEqual(other) { if (this === other) { return true; } if (!(other instanceof VectorQuery)) { return false; } if (!this.query.isEqual(other.query)) { return false; } return (this._rawVectorField === other._rawVectorField && (0, util_1.isPrimitiveArrayEqual)(this._rawQueryVector, other._rawQueryVector) && this._options.limit === other._options.limit && this._options.distanceMeasure === other._options.distanceMeasure && this._options.distanceThreshold === other._options.distanceThreshold && this._rawDistanceResultField === other._rawDistanceResultField); } } exports.VectorQuery = VectorQuery; //# sourceMappingURL=vector-query.js.map