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Version 93
8/30/2024
/**
* This code creates a search engine prototype with autocomplete functionality using the Cerebras LLM API.
* It uses React for the frontend and the Cerebras API for generating autocomplete suggestions.
* The suggestions are cached in the browser to reduce API calls.
* It implements a two-step LLM process: first to get initial suggestions, then to filter them for sensibility and ethics.
* If the second LLM call fails, it displays "Failed to fetch" instead of showing results.
*/
/** @jsxImportSource https://esm.sh/react */
import debounce from "https://esm.sh/lodash.debounce";
import React, { useEffect, useRef, useState } from "https://esm.sh/react";
import { createRoot } from "https://esm.sh/react-dom/client";
function App() {
const [query, setQuery] = useState("");
const [suggestions, setSuggestions] = useState([]);
const [isLoading, setIsLoading] = useState(false);
const [error, setError] = useState("");
const suggestionCache = useRef({});
const fetchSuggestions = async (input) => {
if (suggestionCache.current[input]) {
setSuggestions(suggestionCache.current[input]);
return;
}
setIsLoading(true);
setError("");
try {
const response = await fetch("/suggestions", {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify({ query: input }),
});
if (!response.ok) throw new Error("Failed to fetch suggestions");
const data = await response.json();
sharanbabu-legitimatetantiger.web.val.run
Updated: August 30, 2024