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talksik
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/*! firebase-admin v10.0.1 */
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"use strict";
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/*!
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* Copyright 2020 Google Inc.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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Object.defineProperty(exports, "__esModule", { value: true });
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exports.MachineLearningApiClient = exports.isGcsTfliteModelOptions = void 0;
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var api_request_1 = require("../utils/api-request");
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var error_1 = require("../utils/error");
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var utils = require("../utils/index");
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var validator = require("../utils/validator");
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var machine_learning_utils_1 = require("./machine-learning-utils");
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var ML_V1BETA2_API = 'https://firebaseml.googleapis.com/v1beta2';
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var FIREBASE_VERSION_HEADER = {
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'X-Firebase-Client': "fire-admin-node/" + utils.getSdkVersion(),
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};
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// Operation polling defaults
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var POLL_DEFAULT_MAX_TIME_MILLISECONDS = 120000; // Maximum overall 2 minutes
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var POLL_BASE_WAIT_TIME_MILLISECONDS = 3000; // Start with 3 second delay
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var POLL_MAX_WAIT_TIME_MILLISECONDS = 30000; // Maximum 30 second delay
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function isGcsTfliteModelOptions(options) {
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var _a, _b;
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var gcsUri = (_b = (_a = options) === null || _a === void 0 ? void 0 : _a.tfliteModel) === null || _b === void 0 ? void 0 : _b.gcsTfliteUri;
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return typeof gcsUri !== 'undefined';
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}
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exports.isGcsTfliteModelOptions = isGcsTfliteModelOptions;
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/**
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* Class that facilitates sending requests to the Firebase ML backend API.
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*
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* @internal
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*/
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var MachineLearningApiClient = /** @class */ (function () {
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function MachineLearningApiClient(app) {
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this.app = app;
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if (!validator.isNonNullObject(app) || !('options' in app)) {
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throw new machine_learning_utils_1.FirebaseMachineLearningError('invalid-argument', 'First argument passed to admin.machineLearning() must be a valid '
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+ 'Firebase app instance.');
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}
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this.httpClient = new api_request_1.AuthorizedHttpClient(app);
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}
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MachineLearningApiClient.prototype.createModel = function (model) {
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var _this = this;
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if (!validator.isNonNullObject(model) ||
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!validator.isNonEmptyString(model.displayName)) {
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var err = new machine_learning_utils_1.FirebaseMachineLearningError('invalid-argument', 'Invalid model content.');
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return Promise.reject(err);
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}
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return this.getProjectUrl()
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.then(function (url) {
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var request = {
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method: 'POST',
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url: url + "/models",
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data: model,
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};
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return _this.sendRequest(request);
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});
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};
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MachineLearningApiClient.prototype.updateModel = function (modelId, model, updateMask) {
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var _this = this;
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if (!validator.isNonEmptyString(modelId) ||
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!validator.isNonNullObject(model) ||
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!validator.isNonEmptyArray(updateMask)) {
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var err = new machine_learning_utils_1.FirebaseMachineLearningError('invalid-argument', 'Invalid model or mask content.');
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return Promise.reject(err);
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}
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return this.getProjectUrl()
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.then(function (url) {
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var request = {
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method: 'PATCH',
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url: url + "/models/" + modelId + "?updateMask=" + updateMask.join(),
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data: model,
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};
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return _this.sendRequest(request);
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});
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};
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MachineLearningApiClient.prototype.getModel = function (modelId) {
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var _this = this;
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return Promise.resolve()
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.then(function () {
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return _this.getModelName(modelId);
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})
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.then(function (modelName) {
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return _this.getResourceWithShortName(modelName);
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});
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};
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MachineLearningApiClient.prototype.getOperation = function (operationName) {
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var _this = this;
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return Promise.resolve()
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.then(function () {
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return _this.getResourceWithFullName(operationName);
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});
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};
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MachineLearningApiClient.prototype.listModels = function (options) {
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var _this = this;
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if (options === void 0) { options = {}; }
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if (!validator.isNonNullObject(options)) {
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var err = new machine_learning_utils_1.FirebaseMachineLearningError('invalid-argument', 'Invalid ListModelsOptions');
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return Promise.reject(err);
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}
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if (typeof options.filter !== 'undefined' && !validator.isNonEmptyString(options.filter)) {
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var err = new machine_learning_utils_1.FirebaseMachineLearningError('invalid-argument', 'Invalid list filter.');
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return Promise.reject(err);
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}
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if (typeof options.pageSize !== 'undefined') {
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if (!validator.isNumber(options.pageSize)) {
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var err = new machine_learning_utils_1.FirebaseMachineLearningError('invalid-argument', 'Invalid page size.');
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return Promise.reject(err);
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}
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if (options.pageSize < 1 || options.pageSize > 100) {
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var err = new machine_learning_utils_1.FirebaseMachineLearningError('invalid-argument', 'Page size must be between 1 and 100.');
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return Promise.reject(err);
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}
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}
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if (typeof options.pageToken !== 'undefined' && !validator.isNonEmptyString(options.pageToken)) {
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var err = new machine_learning_utils_1.FirebaseMachineLearningError('invalid-argument', 'Next page token must be a non-empty string.');
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return Promise.reject(err);
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}
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return this.getProjectUrl()
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.then(function (url) {
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var request = {
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method: 'GET',
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url: url + "/models",
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data: options,
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};
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return _this.sendRequest(request);
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});
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};
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MachineLearningApiClient.prototype.deleteModel = function (modelId) {
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var _this = this;
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return this.getProjectUrl()
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.then(function (url) {
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var modelName = _this.getModelName(modelId);
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var request = {
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method: 'DELETE',
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url: url + "/" + modelName,
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};
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return _this.sendRequest(request);
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});
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};
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/**
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* Handles a Long Running Operation coming back from the server.
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*
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* @param op - The operation to handle
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* @param options - The options for polling
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*/
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MachineLearningApiClient.prototype.handleOperation = function (op, options) {
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if (op.done) {
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if (op.response) {
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return Promise.resolve(op.response);
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}
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else if (op.error) {
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var err = machine_learning_utils_1.FirebaseMachineLearningError.fromOperationError(op.error.code, op.error.message);
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return Promise.reject(err);
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}
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// Done operations must have either a response or an error.
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throw new machine_learning_utils_1.FirebaseMachineLearningError('invalid-server-response', 'Invalid operation response.');
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}
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// Operation is not done
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if (options === null || options === void 0 ? void 0 : options.wait) {
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return this.pollOperationWithExponentialBackoff(op.name, options);
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}
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var metadata = op.metadata || {};
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var metadataType = metadata['@type'] || '';
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if (!metadataType.includes('ModelOperationMetadata')) {
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throw new machine_learning_utils_1.FirebaseMachineLearningError('invalid-server-response', "Unknown Metadata type: " + JSON.stringify(metadata));
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}
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return this.getModel(extractModelId(metadata.name));
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};
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// baseWaitMillis and maxWaitMillis should only ever be modified by unit tests to run faster.
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MachineLearningApiClient.prototype.pollOperationWithExponentialBackoff = function (opName, options) {
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var _this = this;
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var _a, _b, _c;
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var maxTimeMilliseconds = (_a = options === null || options === void 0 ? void 0 : options.maxTimeMillis) !== null && _a !== void 0 ? _a : POLL_DEFAULT_MAX_TIME_MILLISECONDS;
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var baseWaitMillis = (_b = options === null || options === void 0 ? void 0 : options.baseWaitMillis) !== null && _b !== void 0 ? _b : POLL_BASE_WAIT_TIME_MILLISECONDS;
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var maxWaitMillis = (_c = options === null || options === void 0 ? void 0 : options.maxWaitMillis) !== null && _c !== void 0 ? _c : POLL_MAX_WAIT_TIME_MILLISECONDS;
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var poller = new api_request_1.ExponentialBackoffPoller(baseWaitMillis, maxWaitMillis, maxTimeMilliseconds);
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return poller.poll(function () {
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return _this.getOperation(opName)
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.then(function (responseData) {
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if (!responseData.done) {
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return null;
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}
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if (responseData.error) {
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var err = machine_learning_utils_1.FirebaseMachineLearningError.fromOperationError(responseData.error.code, responseData.error.message);
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throw err;
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}
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return responseData.response;
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});
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});
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};
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/**
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* Gets the specified resource from the ML API. Resource names must be the short names without project
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* ID prefix (e.g. `models/123456789`).
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*
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* @param {string} name Short name of the resource to get. e.g. 'models/12345'
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* @returns {Promise<T>} A promise that fulfills with the resource.
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*/
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MachineLearningApiClient.prototype.getResourceWithShortName = function (name) {
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var _this = this;
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return this.getProjectUrl()
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.then(function (url) {
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var request = {
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method: 'GET',
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url: url + "/" + name,
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};
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return _this.sendRequest(request);
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});
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};
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/**
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* Gets the specified resource from the ML API. Resource names must be the full names including project
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* number prefix.
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* @param fullName - Full resource name of the resource to get. e.g. projects/123465/operations/987654
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* @returns {Promise<T>} A promise that fulfulls with the resource.
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*/
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MachineLearningApiClient.prototype.getResourceWithFullName = function (fullName) {
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var request = {
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method: 'GET',
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url: ML_V1BETA2_API + "/" + fullName
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};
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return this.sendRequest(request);
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};
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MachineLearningApiClient.prototype.sendRequest = function (request) {
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var _this = this;
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request.headers = FIREBASE_VERSION_HEADER;
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return this.httpClient.send(request)
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.then(function (resp) {
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return resp.data;
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})
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.catch(function (err) {
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throw _this.toFirebaseError(err);
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});
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};
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MachineLearningApiClient.prototype.toFirebaseError = function (err) {
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if (err instanceof error_1.PrefixedFirebaseError) {
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return err;
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}
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var response = err.response;
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if (!response.isJson()) {
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return new machine_learning_utils_1.FirebaseMachineLearningError('unknown-error', "Unexpected response with status: " + response.status + " and body: " + response.text);
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}
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var error = response.data.error || {};
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var code = 'unknown-error';
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if (error.status && error.status in ERROR_CODE_MAPPING) {
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code = ERROR_CODE_MAPPING[error.status];
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}
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var message = error.message || "Unknown server error: " + response.text;
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return new machine_learning_utils_1.FirebaseMachineLearningError(code, message);
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};
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MachineLearningApiClient.prototype.getProjectUrl = function () {
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return this.getProjectIdPrefix()
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.then(function (projectIdPrefix) {
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return ML_V1BETA2_API + "/" + projectIdPrefix;
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});
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};
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MachineLearningApiClient.prototype.getProjectIdPrefix = function () {
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var _this = this;
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if (this.projectIdPrefix) {
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return Promise.resolve(this.projectIdPrefix);
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}
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return utils.findProjectId(this.app)
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.then(function (projectId) {
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if (!validator.isNonEmptyString(projectId)) {
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throw new machine_learning_utils_1.FirebaseMachineLearningError('invalid-argument', 'Failed to determine project ID. Initialize the SDK with service account credentials, or '
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+ 'set project ID as an app option. Alternatively, set the GOOGLE_CLOUD_PROJECT '
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+ 'environment variable.');
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}
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_this.projectIdPrefix = "projects/" + projectId;
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return _this.projectIdPrefix;
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});
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};
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MachineLearningApiClient.prototype.getModelName = function (modelId) {
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if (!validator.isNonEmptyString(modelId)) {
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throw new machine_learning_utils_1.FirebaseMachineLearningError('invalid-argument', 'Model ID must be a non-empty string.');
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}
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if (modelId.indexOf('/') !== -1) {
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throw new machine_learning_utils_1.FirebaseMachineLearningError('invalid-argument', 'Model ID must not contain any "/" characters.');
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}
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return "models/" + modelId;
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};
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return MachineLearningApiClient;
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}());
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exports.MachineLearningApiClient = MachineLearningApiClient;
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var ERROR_CODE_MAPPING = {
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INVALID_ARGUMENT: 'invalid-argument',
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NOT_FOUND: 'not-found',
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RESOURCE_EXHAUSTED: 'resource-exhausted',
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UNAUTHENTICATED: 'authentication-error',
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UNKNOWN: 'unknown-error',
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};
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function extractModelId(resourceName) {
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return resourceName.split('/').pop();
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}
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