add semantic search

src/lib/components/SearchResults.svelte

@@ -0,0 +1,36 @@
+<script lang="ts">
+	import { searchResults } from '$lib/store';
+	import type { SearchResult } from '$lib/utils/search';
+
+	let results: SearchResult[] = [];
+
+	searchResults.subscribe((value: SearchResult[]) => {
+		results = value ? value : [];
+	});
+
+	function slugToTitle(slug: string) {
+		return slug
+			.replace(/-/g, ' ')
+			.split(' ')
+			.map((word) => word.charAt(0).toUpperCase() + word.slice(1))
+			.join(' ');
+	}
+</script>
+
+{#if results.length > 0}
+	<div class="container mx-auto flex flex-col items-center">
+		<div class="prose">
+			<h1 class="py-6">Search results:</h1>
+		</div>
+		<ul>
+			{#each results as result}
+				<li class="py-4">
+					<h3 class="pb-1">
+						<a class="link" href="/poetry/{result.poem.id}">{slugToTitle(result.poem.id)}</a>
+						<p class="text-sm">(Relevance: {(result.similarity * 100).toFixed(3)})%</p>
+					</h3>
+				</li>
+			{/each}
+		</ul>
+	</div>
+{/if}

src/lib/store.ts

@@ -0,0 +1,5 @@
+import { writable } from 'svelte/store';
+import type { SearchResult } from './utils/search';
+
+const initArray: SearchResult[] = [];
+export const searchResults = writable(initArray);

src/lib/utils/search.ts

@@ -0,0 +1,24 @@
+// src/lib/initModel.ts
+import use, { UniversalSentenceEncoder } from '@tensorflow-models/universal-sentence-encoder';
+// eslint-disable-next-line @typescript-eslint/no-unused-vars
+import * as tf from '@tensorflow/tfjs-node';
+
+export type Embedding = {
+	id: string;
+	vector: number[];
+};
+
+export type SearchResult = {
+	poem: Embedding;
+	similarity: number;
+};
+
+let model: UniversalSentenceEncoder | null = null;
+
+export async function getModel(): Promise<UniversalSentenceEncoder> {
+	if (!model) {
+		model = await use.load();
+		console.log('Model loaded successfully!');
+	}
+	return model;
+}