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-rw-r--r--src/client/ClientRecommender.tsx8
-rw-r--r--src/client/apis/IBM_Recommender.ts66
-rw-r--r--src/client/util/DocumentManager.ts7
-rw-r--r--src/client/views/nodes/AudioBox.tsx26
-rw-r--r--src/client/views/nodes/FormattedTextBoxComment.tsx2
-rw-r--r--src/client/views/nodes/WebBox.tsx2
-rw-r--r--src/new_fields/Schema.ts2
-rw-r--r--src/server/ApiManagers/UploadManager.ts14
-rw-r--r--src/server/ApiManagers/UtilManager.ts44
-rw-r--r--src/server/DashUploadUtils.ts19
-rw-r--r--src/server/Recommender.ts274
-rw-r--r--src/server/SharedMediaTypes.ts1
12 files changed, 246 insertions, 219 deletions
diff --git a/src/client/ClientRecommender.tsx b/src/client/ClientRecommender.tsx
index cb1674943..0e67a6e57 100644
--- a/src/client/ClientRecommender.tsx
+++ b/src/client/ClientRecommender.tsx
@@ -5,10 +5,10 @@ import { CognitiveServices, Confidence, Tag, Service } from "./cognitive_service
import React = require("react");
import { observer } from "mobx-react";
import { observable, action, computed, reaction } from "mobx";
-var assert = require('assert');
-var sw = require('stopword');
-var FeedParser = require('feedparser');
-var https = require('https');
+// var assert = require('assert');
+// var sw = require('stopword');
+// var FeedParser = require('feedparser');
+// var https = require('https');
import "./ClientRecommender.scss";
import { JSXElement } from "babel-types";
import { RichTextField } from "../new_fields/RichTextField";
diff --git a/src/client/apis/IBM_Recommender.ts b/src/client/apis/IBM_Recommender.ts
index da6257f28..4e1c541c8 100644
--- a/src/client/apis/IBM_Recommender.ts
+++ b/src/client/apis/IBM_Recommender.ts
@@ -1,40 +1,40 @@
-import { Opt } from "../../new_fields/Doc";
+// import { Opt } from "../../new_fields/Doc";
-const NaturalLanguageUnderstandingV1 = require('ibm-watson/natural-language-understanding/v1');
-const { IamAuthenticator } = require('ibm-watson/auth');
+// const NaturalLanguageUnderstandingV1 = require('ibm-watson/natural-language-understanding/v1');
+// const { IamAuthenticator } = require('ibm-watson/auth');
-export namespace IBM_Recommender {
+// export namespace IBM_Recommender {
- // pass to IBM account is Browngfx1
+// // pass to IBM account is Browngfx1
- const naturalLanguageUnderstanding = new NaturalLanguageUnderstandingV1({
- version: '2019-07-12',
- authenticator: new IamAuthenticator({
- apikey: 'tLiYwbRim3CnBcCO4phubpf-zEiGcub1uh0V-sD9OKhw',
- }),
- url: 'https://gateway-wdc.watsonplatform.net/natural-language-understanding/api'
- });
+// const naturalLanguageUnderstanding = new NaturalLanguageUnderstandingV1({
+// version: '2019-07-12',
+// authenticator: new IamAuthenticator({
+// apikey: 'tLiYwbRim3CnBcCO4phubpf-zEiGcub1uh0V-sD9OKhw',
+// }),
+// url: 'https://gateway-wdc.watsonplatform.net/natural-language-understanding/api'
+// });
- const analyzeParams = {
- 'text': 'this is a test of the keyword extraction feature I am integrating into the program',
- 'features': {
- 'keywords': {
- 'sentiment': true,
- 'emotion': true,
- 'limit': 3
- },
- }
- };
+// const analyzeParams = {
+// 'text': 'this is a test of the keyword extraction feature I am integrating into the program',
+// 'features': {
+// 'keywords': {
+// 'sentiment': true,
+// 'emotion': true,
+// 'limit': 3
+// },
+// }
+// };
- export const analyze = async (_parameters: any): Promise<Opt<string>> => {
- try {
- const response = await naturalLanguageUnderstanding.analyze(_parameters);
- console.log(response);
- return (JSON.stringify(response, null, 2));
- } catch (err) {
- console.log('error: ', err);
- return undefined;
- }
- };
+// export const analyze = async (_parameters: any): Promise<Opt<string>> => {
+// try {
+// const response = await naturalLanguageUnderstanding.analyze(_parameters);
+// console.log(response);
+// return (JSON.stringify(response, null, 2));
+// } catch (err) {
+// console.log('error: ', err);
+// return undefined;
+// }
+// };
-} \ No newline at end of file
+// } \ No newline at end of file
diff --git a/src/client/util/DocumentManager.ts b/src/client/util/DocumentManager.ts
index 4e82459f0..162a8fffe 100644
--- a/src/client/util/DocumentManager.ts
+++ b/src/client/util/DocumentManager.ts
@@ -209,7 +209,12 @@ export class DocumentManager {
const maxLocation = StrCast(linkDoc.maximizeLocation, "inTab");
const targetContext = !Doc.AreProtosEqual(linkFollowDocContexts[reverse ? 1 : 0], currentContext) ? linkFollowDocContexts[reverse ? 1 : 0] : undefined;
const target = linkFollowDocs[reverse ? 1 : 0];
- target.currentTimecode !== undefined && (target.currentTimecode = linkFollowTimecodes[reverse ? 1 : 0]);
+ let annotatedDoc = await Cast(target.annotationOn, Doc);
+ if (annotatedDoc) {
+ annotatedDoc.currentTimecode !== undefined && (target.currentTimecode = linkFollowTimecodes[reverse ? 1 : 0]);
+ } else {
+ target.currentTimecode !== undefined && (target.currentTimecode = linkFollowTimecodes[reverse ? 1 : 0]);
+ }
DocumentManager.Instance.jumpToDocument(linkFollowDocs[reverse ? 1 : 0], zoom, (doc: Doc) => focus(doc, maxLocation), targetContext, linkDoc[Id], undefined, doc);
} else if (link) {
DocumentManager.Instance.jumpToDocument(link, zoom, (doc: Doc) => focus(doc, "onRight"), undefined, undefined);
diff --git a/src/client/views/nodes/AudioBox.tsx b/src/client/views/nodes/AudioBox.tsx
index ea26cc43d..05b9fd14a 100644
--- a/src/client/views/nodes/AudioBox.tsx
+++ b/src/client/views/nodes/AudioBox.tsx
@@ -20,6 +20,8 @@ import { DocumentView } from "./DocumentView";
import { Docs } from "../../documents/Documents";
import { ComputedField } from "../../../new_fields/ScriptField";
+// testing testing
+
interface Window {
MediaRecorder: MediaRecorder;
}
@@ -46,6 +48,7 @@ export class AudioBox extends DocExtendableComponent<FieldViewProps, AudioDocume
_ele: HTMLAudioElement | null = null;
_recorder: any;
_recordStart = 0;
+ _stream: MediaStream | undefined;
public static START = 0;
@observable private static _scrubTime = 0;
@@ -137,12 +140,11 @@ export class AudioBox extends DocExtendableComponent<FieldViewProps, AudioDocume
}
recordAudioAnnotation = () => {
- let gumStream: any;
const self = this;
navigator.mediaDevices.getUserMedia({
audio: true
}).then(function (stream) {
- gumStream = stream;
+ self._stream = stream;
self._recorder = new MediaRecorder(stream);
self.dataDoc[self.props.fieldKey + "-recordingStart"] = new DateField(new Date());
AudioBox.START = new DateField(new Date()).date.getTime();
@@ -154,23 +156,16 @@ export class AudioBox extends DocExtendableComponent<FieldViewProps, AudioDocume
method: 'POST',
body: formData
});
- const json = await res.json();
- json.map(async (file: any) => {
- const path = file.result.accessPaths.agnostic.client;
- const url = Utils.prepend(path);
- // upload to server with known URL
- self.props.Document[self.props.fieldKey] = new AudioField(url);
- });
+ const files = await res.json();
+ const url = Utils.prepend(files[0].result.accessPaths.agnostic.client);
+ // upload to server with known URL
+ self.props.Document[self.props.fieldKey] = new AudioField(url);
};
self._recordStart = new Date().getTime();
- console.log("RECORD START = " + self._recordStart);
runInAction(() => self.audioState = "recording");
setTimeout(self.updateRecordTime, 0);
self._recorder.start();
- setTimeout(() => {
- self.stopRecording();
- gumStream.getAudioTracks()[0].stop();
- }, 60 * 60 * 1000); // stop after an hour?
+ setTimeout(() => self._recorder && self.stopRecording(), 60 * 1000); // stop after an hour
});
}
@@ -183,8 +178,10 @@ export class AudioBox extends DocExtendableComponent<FieldViewProps, AudioDocume
stopRecording = action(() => {
this._recorder.stop();
+ this._recorder = undefined;
this.dataDoc.duration = (new Date().getTime() - this._recordStart) / 1000;
this.audioState = "paused";
+ this._stream?.getAudioTracks()[0].stop();
const ind = AudioBox.ActiveRecordings.indexOf(this.props.Document);
ind !== -1 && (AudioBox.ActiveRecordings.splice(ind, 1));
});
@@ -237,6 +234,7 @@ export class AudioBox extends DocExtendableComponent<FieldViewProps, AudioDocume
</audio>;
}
+ // line 226 is stop button but it doesn't do anything
render() {
const interactive = this.active() ? "-interactive" : "";
return <div className={`audiobox-container`} onContextMenu={this.specificContextMenu}
diff --git a/src/client/views/nodes/FormattedTextBoxComment.tsx b/src/client/views/nodes/FormattedTextBoxComment.tsx
index a3096f60b..61df188f8 100644
--- a/src/client/views/nodes/FormattedTextBoxComment.tsx
+++ b/src/client/views/nodes/FormattedTextBoxComment.tsx
@@ -83,7 +83,7 @@ export class FormattedTextBoxComment {
const keep = e.target && (e.target as any).type === "checkbox" ? true : false;
const textBox = FormattedTextBoxComment.textBox;
if (FormattedTextBoxComment.linkDoc && !keep && textBox) {
- DocumentManager.Instance.FollowLink(FormattedTextBoxComment.linkDoc, textBox.dataDoc,
+ DocumentManager.Instance.FollowLink(FormattedTextBoxComment.linkDoc, textBox.props.Document,
(doc: Doc, maxLocation: string) => textBox.props.addDocTab(doc, e.ctrlKey ? "inTab" : "onRight"));
} else if (textBox && (FormattedTextBoxComment.tooltipText as any).href) {
textBox.props.addDocTab(Docs.Create.WebDocument((FormattedTextBoxComment.tooltipText as any).href, { title: (FormattedTextBoxComment.tooltipText as any).href, _width: 200, _height: 400 }), "onRight");
diff --git a/src/client/views/nodes/WebBox.tsx b/src/client/views/nodes/WebBox.tsx
index c169d9423..2f8b6167f 100644
--- a/src/client/views/nodes/WebBox.tsx
+++ b/src/client/views/nodes/WebBox.tsx
@@ -36,7 +36,7 @@ export class WebBox extends DocAnnotatableComponent<FieldViewProps, WebDocument>
public static LayoutString(fieldKey: string) { return FieldView.LayoutString(WebBox, fieldKey); }
@observable private collapsed: boolean = true;
- @observable private url: string = "";
+ @observable private url: string = "hello";
private _longPressSecondsHack?: NodeJS.Timeout;
private _iframeRef = React.createRef<HTMLIFrameElement>();
diff --git a/src/new_fields/Schema.ts b/src/new_fields/Schema.ts
index 3f0ff4284..72bce283d 100644
--- a/src/new_fields/Schema.ts
+++ b/src/new_fields/Schema.ts
@@ -33,7 +33,7 @@ export function makeInterface<T extends Interface[]>(...schemas: T): InterfaceFu
get(target: any, prop, receiver) {
const field = receiver.doc[prop];
if (prop in schema) {
- const desc = (schema as any)[prop];
+ const desc = prop === "proto" ? Doc : (schema as any)[prop]; // bcz: proto doesn't appear in schemas ... maybe it should?
if (typeof desc === "object" && "defaultVal" in desc && "type" in desc) {//defaultSpec
return Cast(field, desc.type, desc.defaultVal);
} else if (typeof desc === "function" && !ObjectField.isPrototypeOf(desc) && !RefField.isPrototypeOf(desc)) {
diff --git a/src/server/ApiManagers/UploadManager.ts b/src/server/ApiManagers/UploadManager.ts
index 50a759c9d..42e33ece0 100644
--- a/src/server/ApiManagers/UploadManager.ts
+++ b/src/server/ApiManagers/UploadManager.ts
@@ -19,7 +19,8 @@ export enum Directory {
videos = "videos",
pdfs = "pdfs",
text = "text",
- pdf_thumbnails = "pdf_thumbnails"
+ pdf_thumbnails = "pdf_thumbnails",
+ audio = "audio"
}
export function serverPathToFile(directory: Directory, filename: string) {
@@ -61,9 +62,18 @@ export default class UploadManager extends ApiManager {
});
register({
+ method: Method.GET,
+ subscription: "/hello",
+ secureHandler: ({ req, res }) => {
+ res.send("<h1>world!</h1>");
+ }
+ });
+
+ register({
method: Method.POST,
subscription: "/uploadRemoteImage",
secureHandler: async ({ req, res }) => {
+
const { sources } = req.body;
if (Array.isArray(sources)) {
const results = await Promise.all(sources.map(source => DashUploadUtils.UploadImage(source)));
@@ -77,6 +87,7 @@ export default class UploadManager extends ApiManager {
method: Method.POST,
subscription: "/uploadDoc",
secureHandler: ({ req, res }) => {
+
const form = new formidable.IncomingForm();
form.keepExtensions = true;
// let path = req.body.path;
@@ -181,6 +192,7 @@ export default class UploadManager extends ApiManager {
method: Method.POST,
subscription: "/inspectImage",
secureHandler: async ({ req, res }) => {
+
const { source } = req.body;
if (typeof source === "string") {
return res.send(await DashUploadUtils.InspectImage(source));
diff --git a/src/server/ApiManagers/UtilManager.ts b/src/server/ApiManagers/UtilManager.ts
index d18529cf2..ad8119bf4 100644
--- a/src/server/ApiManagers/UtilManager.ts
+++ b/src/server/ApiManagers/UtilManager.ts
@@ -3,11 +3,11 @@ import { Method } from "../RouteManager";
import { exec } from 'child_process';
import RouteSubscriber from "../RouteSubscriber";
import { red } from "colors";
-import { IBM_Recommender } from "../../client/apis/IBM_Recommender";
-import { Recommender } from "../Recommender";
+// import { IBM_Recommender } from "../../client/apis/IBM_Recommender";
+// import { Recommender } from "../Recommender";
-const recommender = new Recommender();
-recommender.testModel();
+// const recommender = new Recommender();
+// recommender.testModel();
import executeImport from "../../scraping/buxton/final/BuxtonImporter";
export default class UtilManager extends ApiManager {
@@ -27,25 +27,25 @@ export default class UtilManager extends ApiManager {
}
});
- register({
- method: Method.POST,
- subscription: "/IBMAnalysis",
- secureHandler: async ({ req, res }) => res.send(await IBM_Recommender.analyze(req.body))
- });
+ // register({
+ // method: Method.POST,
+ // subscription: "/IBMAnalysis",
+ // secureHandler: async ({ req, res }) => res.send(await IBM_Recommender.analyze(req.body))
+ // });
- register({
- method: Method.POST,
- subscription: "/recommender",
- secureHandler: async ({ req, res }) => {
- const keyphrases = req.body.keyphrases;
- const wordvecs = await recommender.vectorize(keyphrases);
- let embedding: Float32Array = new Float32Array();
- if (wordvecs && wordvecs.dataSync()) {
- embedding = wordvecs.dataSync() as Float32Array;
- }
- res.send(embedding);
- }
- });
+ // register({
+ // method: Method.POST,
+ // subscription: "/recommender",
+ // secureHandler: async ({ req, res }) => {
+ // const keyphrases = req.body.keyphrases;
+ // const wordvecs = await recommender.vectorize(keyphrases);
+ // let embedding: Float32Array = new Float32Array();
+ // if (wordvecs && wordvecs.dataSync()) {
+ // embedding = wordvecs.dataSync() as Float32Array;
+ // }
+ // res.send(embedding);
+ // }
+ // });
register({
diff --git a/src/server/DashUploadUtils.ts b/src/server/DashUploadUtils.ts
index cc3dd75a4..cf78af60a 100644
--- a/src/server/DashUploadUtils.ts
+++ b/src/server/DashUploadUtils.ts
@@ -53,7 +53,7 @@ export namespace DashUploadUtils {
const size = "content-length";
const type = "content-type";
- const { imageFormats, videoFormats, applicationFormats } = AcceptibleMedia;
+ const { imageFormats, videoFormats, applicationFormats, audioFormats } = AcceptibleMedia;
export async function upload(file: File): Promise<Upload.FileResponse> {
const { type, path, name } = file;
@@ -76,14 +76,22 @@ export namespace DashUploadUtils {
if (applicationFormats.includes(format)) {
return UploadPdf(file);
}
- default: // "blob":
- return MoveParsedFile(file, Directory.videos);
+ case "audio":
+ if (audioFormats.includes(format)) {
+ return MoveParsedFile(file, Directory.audio);
+ }
}
console.log(red(`Ignoring unsupported file (${name}) with upload type (${type}).`));
return { source: file, result: new Error(`Could not upload unsupported file (${name}) with upload type (${type}).`) };
}
+ async function UploadAudio(file: File) {
+ const { path: sourcePath } = file;
+
+ return MoveParsedFile(file, Directory.audio);
+ }
+
async function UploadPdf(file: File) {
const { path: sourcePath } = file;
const dataBuffer = readFileSync(sourcePath);
@@ -94,6 +102,7 @@ export namespace DashUploadUtils {
const writeStream = createWriteStream(serverPathToFile(Directory.text, textFilename));
writeStream.write(result.text, error => error ? reject(error) : resolve());
});
+ console.log(MoveParsedFile(file, Directory.pdfs));
return MoveParsedFile(file, Directory.pdfs);
}
@@ -197,8 +206,10 @@ export namespace DashUploadUtils {
accessPaths: {
agnostic: getAccessPaths(destination, name)
}
+
}
- });
+ }
+ );
});
});
}
diff --git a/src/server/Recommender.ts b/src/server/Recommender.ts
index 1d2cb3858..aacdb4053 100644
--- a/src/server/Recommender.ts
+++ b/src/server/Recommender.ts
@@ -1,137 +1,137 @@
-//import { Doc } from "../new_fields/Doc";
-//import { StrCast } from "../new_fields/Types";
-//import { List } from "../new_fields/List";
-//import { CognitiveServices } from "../client/cognitive_services/CognitiveServices";
-
-// var w2v = require('word2vec');
-var assert = require('assert');
-var arxivapi = require('arxiv-api-node');
-import requestPromise = require("request-promise");
-import * as use from '@tensorflow-models/universal-sentence-encoder';
-import { Tensor } from "@tensorflow/tfjs-core/dist/tensor";
-require('@tensorflow/tfjs-node');
-
-//http://gnuwin32.sourceforge.net/packages/make.htm
-
-export class Recommender {
-
- private _model: any;
- static Instance: Recommender;
- private dimension: number = 0;
- private choice: string = ""; // Tensorflow or Word2Vec
-
- constructor() {
- console.log("creating recommender...");
- Recommender.Instance = this;
- }
-
- /***
- * Loads pre-trained model from TF
- */
-
- public async loadTFModel() {
- let self = this;
- return new Promise(res => {
- use.load().then(model => {
- self.choice = "TF";
- self._model = model;
- self.dimension = 512;
- res(model);
- });
- }
-
- );
- }
-
- /***
- * Loads pre-trained model from word2vec
- */
-
- // private loadModel(): Promise<any> {
- // let self = this;
- // return new Promise(res => {
- // w2v.loadModel("./node_modules/word2vec/examples/fixtures/vectors.txt", function (err: any, model: any) {
- // self.choice = "WV";
- // self._model = model;
- // self.dimension = model.size;
- // res(model);
- // });
- // });
- // }
-
- /***
- * Testing
- */
-
- public async testModel() {
- if (!this._model) {
- await this.loadTFModel();
- }
- if (this._model) {
- if (this.choice === "WV") {
- let similarity = this._model.similarity('father', 'mother');
- console.log(similarity);
- }
- else if (this.choice === "TF") {
- const model = this._model as use.UniversalSentenceEncoder;
- // Embed an array of sentences.
- const sentences = [
- 'Hello.',
- 'How are you?'
- ];
- const embeddings = await this.vectorize(sentences);
- if (embeddings) embeddings.print(true /*verbose*/);
- // model.embed(sentences).then(embeddings => {
- // // `embeddings` is a 2D tensor consisting of the 512-dimensional embeddings for each sentence.
- // // So in this example `embeddings` has the shape [2, 512].
- // embeddings.print(true /* verbose */);
- // });
- }
- }
- else {
- console.log("model not found :(");
- }
- }
-
- /***
- * Uses model to convert words to vectors
- */
-
- public async vectorize(text: string[]): Promise<Tensor | undefined> {
- if (!this._model) {
- await this.loadTFModel();
- }
- if (this._model) {
- if (this.choice === "WV") {
- let word_vecs = this._model.getVectors(text);
- return word_vecs;
- }
- else if (this.choice === "TF") {
- const model = this._model as use.UniversalSentenceEncoder;
- return new Promise<Tensor>(res => {
- model.embed(text).then(embeddings => {
- res(embeddings);
- });
- });
-
- }
- }
- }
-
- // public async trainModel() {
- // console.log("phrasing...");
- // w2v.word2vec("./node_modules/word2vec/examples/eng_news-typical_2016_1M-sentences.txt", './node_modules/word2vec/examples/my_phrases.txt', {
- // cbow: 1,
- // size: 200,
- // window: 8,
- // negative: 25,
- // hs: 0,
- // sample: 1e-4,
- // threads: 20,
- // iter: 200,
- // minCount: 2
- // });
- // console.log("phrased!!!");
- // }
-
-}
+// //import { Doc } from "../new_fields/Doc";
+// //import { StrCast } from "../new_fields/Types";
+// //import { List } from "../new_fields/List";
+// //import { CognitiveServices } from "../client/cognitive_services/CognitiveServices";
+
+// // var w2v = require('word2vec');
+// var assert = require('assert');
+// var arxivapi = require('arxiv-api-node');
+// import requestPromise = require("request-promise");
+// import * as use from '@tensorflow-models/universal-sentence-encoder';
+// import { Tensor } from "@tensorflow/tfjs-core/dist/tensor";
+// require('@tensorflow/tfjs-node');
+
+// //http://gnuwin32.sourceforge.net/packages/make.htm
+
+// export class Recommender {
+
+// private _model: any;
+// static Instance: Recommender;
+// private dimension: number = 0;
+// private choice: string = ""; // Tensorflow or Word2Vec
+
+// constructor() {
+// console.log("creating recommender...");
+// Recommender.Instance = this;
+// }
+
+// /***
+// * Loads pre-trained model from TF
+// */
+
+// public async loadTFModel() {
+// let self = this;
+// return new Promise(res => {
+// use.load().then(model => {
+// self.choice = "TF";
+// self._model = model;
+// self.dimension = 512;
+// res(model);
+// });
+// }
+
+// );
+// }
+
+// /***
+// * Loads pre-trained model from word2vec
+// */
+
+// // private loadModel(): Promise<any> {
+// // let self = this;
+// // return new Promise(res => {
+// // w2v.loadModel("./node_modules/word2vec/examples/fixtures/vectors.txt", function (err: any, model: any) {
+// // self.choice = "WV";
+// // self._model = model;
+// // self.dimension = model.size;
+// // res(model);
+// // });
+// // });
+// // }
+
+// /***
+// * Testing
+// */
+
+// public async testModel() {
+// if (!this._model) {
+// await this.loadTFModel();
+// }
+// if (this._model) {
+// if (this.choice === "WV") {
+// let similarity = this._model.similarity('father', 'mother');
+// console.log(similarity);
+// }
+// else if (this.choice === "TF") {
+// const model = this._model as use.UniversalSentenceEncoder;
+// // Embed an array of sentences.
+// const sentences = [
+// 'Hello.',
+// 'How are you?'
+// ];
+// const embeddings = await this.vectorize(sentences);
+// if (embeddings) embeddings.print(true /*verbose*/);
+// // model.embed(sentences).then(embeddings => {
+// // // `embeddings` is a 2D tensor consisting of the 512-dimensional embeddings for each sentence.
+// // // So in this example `embeddings` has the shape [2, 512].
+// // embeddings.print(true /* verbose */);
+// // });
+// }
+// }
+// else {
+// console.log("model not found :(");
+// }
+// }
+
+// /***
+// * Uses model to convert words to vectors
+// */
+
+// public async vectorize(text: string[]): Promise<Tensor | undefined> {
+// if (!this._model) {
+// await this.loadTFModel();
+// }
+// if (this._model) {
+// if (this.choice === "WV") {
+// let word_vecs = this._model.getVectors(text);
+// return word_vecs;
+// }
+// else if (this.choice === "TF") {
+// const model = this._model as use.UniversalSentenceEncoder;
+// return new Promise<Tensor>(res => {
+// model.embed(text).then(embeddings => {
+// res(embeddings);
+// });
+// });
+
+// }
+// }
+// }
+
+// // public async trainModel() {
+// // console.log("phrasing...");
+// // w2v.word2vec("./node_modules/word2vec/examples/eng_news-typical_2016_1M-sentences.txt", './node_modules/word2vec/examples/my_phrases.txt', {
+// // cbow: 1,
+// // size: 200,
+// // window: 8,
+// // negative: 25,
+// // hs: 0,
+// // sample: 1e-4,
+// // threads: 20,
+// // iter: 200,
+// // minCount: 2
+// // });
+// // console.log("phrased!!!");
+// // }
+
+// }
diff --git a/src/server/SharedMediaTypes.ts b/src/server/SharedMediaTypes.ts
index 185e787cc..3d3683912 100644
--- a/src/server/SharedMediaTypes.ts
+++ b/src/server/SharedMediaTypes.ts
@@ -10,6 +10,7 @@ export namespace AcceptibleMedia {
export const imageFormats = [...pngs, ...jpgs, ...gifs, ...webps, ...tiffs];
export const videoFormats = [".mov", ".mp4"];
export const applicationFormats = [".pdf"];
+ export const audioFormats = [".wav", ".mp3", ".flac", ".au", ".aiff", ".m4a", ".webm;codecs=opus"];
}
export namespace Upload {
generated by cgit v1.2.3-70-g09d2 (git 2.46.0) at 2025-10-07 06:36:06 +0000