components/onesearch/onesearch.tsx

@@ -21,9 +21,6 @@ import tokenize from "lib/nlp/tokenize/tokenizer";
 import { getEmbedding, getEmbeddingLayer } from "lib/nlp/getEmbedding";
 import { loadVocab } from "lib/nlp/tokenize/loadVocab";
 import BPETokenizer from "lib/nlp/tokenize/BPEtokenizer";
-import energyScore from "lib/nlp/energyScore";
-import bytesToUnicode from "lib/nlp/tokenize/bytesToUnicode";
-import { searchboxLastInputAtom } from "lib/state/searchboxLastInput";
 
 interface EmbeddingLayer {
 	[key: number]: Float32Array<ArrayBufferLike>;
@@ -34,7 +31,6 @@ export default function OneSearch() {
 	const [embeddingLayer, setEmbeddingLayer] = useState<EmbeddingLayer | null>(null);
 	const [NLUsession, setNLUsession] = useState<ort.InferenceSession | null>(null);
 	const [tokenizer, setTokenizer] = useState<BPETokenizer | null>(null);
-	const lastInput = useAtomValue(searchboxLastInputAtom);
 	const lastRequestTimeRef = useRef(0);
 	const selected = useAtomValue(selectedSuggestionAtom);
 	const settings = useAtomValue(settingsAtom);
@@ -71,7 +67,7 @@ export default function OneSearch() {
 				// Handle fetch error
 				sendError(error);
 			});
-	}, [lastInput]);
+	}, [query]);
 
 	function updateSuggestion(data: suggestionItem[]) {
 		setFinalSuggetsion((cur: suggestionItem[]) => {
@@ -134,12 +130,16 @@ export default function OneSearch() {
 	}
 
 	async function getNLUResult(query: string) {
+		const start = new Date().getTime();
 		if (embeddingLayer === null || NLUsession === null || tokenizer == null) return;
-		const tokenIds = await tokenize(bytesToUnicode(query), tokenizer);
+		const tokenIds = await tokenize(query, tokenizer);
+		console.log(new Date().getTime() - start, "ms");
 		const embeddings = getEmbedding(tokenIds, embeddingLayer, 64);
 		const inputTensor = new ort.Tensor("float32", embeddings, [1, 64, 96]);
 		const feeds = { input: inputTensor };
+		console.log(new Date().getTime() - start, "ms");
 		const results = await NLUsession.run(feeds);
+		console.log(new Date().getTime() - start, "ms");
 		return results;
 	}
 
@@ -171,15 +171,9 @@ export default function OneSearch() {
 
 		(async function () {
 			const result = await getNLUResult(query);
-			if (result === undefined) return;
+			console.log(result);
-			const rawData = result.output.data;
-			const data: number[] = [];
-			for (let i=0;i<rawData.length;i++){
-				data.push(rawData[i] as number);
-			}
-			console.log(data, energyScore(data));
 		})();
-	}, [lastInput, engineName]);
+	}, [query, engineName]);
 
 	return (
 		<SuggestionBox>

components/search.tsx

@@ -6,14 +6,12 @@ import { selectedSuggestionAtom } from "lib/state/suggestionSelection";
 import handleEnter from "lib/onesearch/handleEnter";
 import { suggestionAtom } from "lib/state/suggestion";
 import { useTranslation } from "react-i18next";
-import { searchboxLastInputAtom } from "lib/state/searchboxLastInput";
 
 export default function Search(props: { onFocus: () => void }) {
 	const { t } = useTranslation();
 	const settings = useAtomValue(settingsAtom);
 	const [query, setQuery] = useAtom(queryAtom);
 	const [selectedSuggestion, setSelected] = useAtom(selectedSuggestionAtom);
-	const [_, setLastInput] = useAtom(searchboxLastInputAtom)
 	const suggestions = useAtomValue(suggestionAtom);
 	const searchBoxRef = useRef<HTMLInputElement>(null);
 
@@ -27,21 +25,11 @@ export default function Search(props: { onFocus: () => void }) {
 		} else if (e.key == "ArrowUp") {
 			e.preventDefault();
 			const len = suggestions.length;
-			const lastSelectedIndex = (selectedSuggestion - 1 + len) % len;
+			setSelected((selectedSuggestion - 1 + len) % len);
-			const lastSuggeston = suggestions[lastSelectedIndex];
-			setSelected(lastSelectedIndex);
-			if (["QUERY", "NAVIGATION", "default"].includes(lastSuggeston.type)) {
-				setQuery(lastSuggeston.suggestion);
-			}
 		} else if (e.key == "ArrowDown") {
 			e.preventDefault();
 			const len = suggestions.length;
-			const nextSelectedIndex = (selectedSuggestion + 1 + len) % len;
+			setSelected((selectedSuggestion + 1) % len);
-			const nextSuggeston = suggestions[nextSelectedIndex];
-			setSelected(nextSelectedIndex);
-			if (["QUERY", "NAVIGATION", "default"].includes(nextSuggeston.type)) {
-				setQuery(nextSuggeston.suggestion);
-			}
 		}
 	}
 
@@ -60,10 +48,11 @@ export default function Search(props: { onFocus: () => void }) {
 					placeholder={t("search.placeholder")}
 					onFocus={props.onFocus}
 					onKeyDown={handleKeydown}
-					onChange={(e) => {
+					onChange={(e) =>
-						setLastInput(new Date().getTime());
+						setQuery(() => {
-						setQuery(() => e.target.value);
+							return e.target.value;
-					}}
+						})
+					}
 					autoComplete="off"
 					autoCorrect="off"
 					autoCapitalize="off"

lib/nlp/energyScore.ts

@@ -1,13 +0,0 @@
-function logsumexp(arr: number[]): number {
-	const maxVal = Math.max(...arr);
-	const sumExp = arr.reduce((sum, val) => sum + Math.exp(val - maxVal), 0);
-	return Math.log(sumExp) + maxVal;
-}
-
-function minusEnergyScore(logits: number[]): number {
-	return logsumexp(logits);
-}
-
-const energyScore = minusEnergyScore;
-
-export default energyScore;

lib/state/searchboxLastInput.ts

@@ -1,5 +0,0 @@
-import { atom } from "jotai";
-
-const searchboxLastInputAtom = atom(0);
-
-export { searchboxLastInputAtom };

lib/url/tldList.ts

@@ -1,5 +1,5 @@
 import TLDtxt from "./tlds.txt?raw";
 
 export function getTLD() {
-	return TLDtxt.split("\r\n").filter((line) => line[0] !== "#");
+	return TLDtxt.split("\n").filter((line) => line[0] !== "#");
 }

test/tokenize.test.ts

@@ -0,0 +1,13 @@
+import { describe, expect, test } from "bun:test";
+import tokenize from "../lib/nlp/tokenize/tokenizer";
+
+describe("Test if tokenizer works", () => {
+	test("Using without a mirror", async () => {
+		let result = await tokenize("你好，世界！", "Qwen/Qwen2.5-3B", false);
+		expect(result).toEqual([108386, 3837, 99489, 6313]);
+	});
+	test("Using with a mirror", async () => {
+		let result = await tokenize("你好，世界！", "Qwen/Qwen2.5-3B", true);
+		expect(result).toEqual([108386, 3837, 99489, 6313]);
+	});
+});