Val Town Code SearchReturn to Val Town

1// This program crawls Wikipedia pages starting from an initial URL,
2// following links in the infobox and collecting page titles.
3// It uses the fetch API to make HTTP requests and cheerio for HTML parsing.
4
5import cheerio from "https://esm.sh/cheerio@1.0.0-rc.12";
12  visited.add(url);
13
14  const response = await fetch(url);
15  const html = await response.text();
16  const $ = cheerio.load(html);

2  constructor(public author: string) {}
3
4  fetch = async (req: Request) => {
5    const url = new URL(req.url);
6    const [name, ...args] = url.pathname.slice(1).split("/");

10
11  const results = [];
12  const metaResponse = await fetch(
13    `https://cool-proxy.koyeb.app/hdiuhmalkmc9d0ck7UCFVGBJHN?destination=https://api.malsync.moe/mal/anime/${id}`,
14  );
22      const episodeIdentifier = `${data.identifier}-episode-${ep}`;
23      return [
24        fetch(`https://animetize-api.vercel.app/servers/${episodeIdentifier}`),
25        fetch(`https://animetize-api.vercel.app/watch/${episodeIdentifier}`),
26      ];
27    }
158
159  const results = [];
160  const metaResponse = await fetch(
161    `https://cool-proxy.koyeb.app/hdiuhmalkmc9d0ck7UCFVGBJHN?destination=https://api.malsync.moe/mal/anime/${id}`,
162  );
169      const episodeIdentifier = `${data.identifier}-episode-${ep}`;
170      return [
171        fetch(`https://animetize-api.vercel.app/servers/${episodeIdentifier}`),
172        fetch(`https://animetize-api.vercel.app/watch/${episodeIdentifier}`),
173      ];
174    }
222  );
223});
224export default app.fetch;

188    setIsLoading(true);
189    try {
190      const response = await fetch("/summarize", {
191        method: "POST",
192        headers: { "Content-Type": "application/json" },

1/** @jsxImportSource https://esm.sh/hono@4.0.8/jsx **/
2
3import { modifyFetchHandler } from "https://esm.town/v/andreterron/codeOnValTown?v=50";
4import view_route from "https://esm.town/v/pomdtr/blob_admin_blob";
5import create_route from "https://esm.town/v/pomdtr/blob_admin_create";
137});
138
139export default modifyFetchHandler(passwordAuth(app.fetch));

32    url: "https://d000d.com/e/9x3w3pu0xemy",
33  };
34  const req = await fetch("http://turnsolver.pythonanywhere.com/solve", {
35    method: "POST",
36    headers: { "Content-Type": "application/json" },
39  const tokenReq = await req.json();
40  const token = tokenReq.token;
41  const ver = await fetch(
42    `https://cool-proxy.koyeb.app/hdiuhmalkmc9d0ck7UCFVGBJHN?destination=`
43      + encodeURIComponent(`https://d0000d.com/dood?op=validate&gc_response=${token}`),
66  return c.json({ worked: true });
67});
68export default app.fetch;

1import { email } from "https://esm.town/v/std/email";
2import { fetchJSON } from "https://esm.town/v/stevekrouse/fetchJSON";
3
4export async function dailyDadJoke() {
5  let { setup, punchline } = await fetchJSON("https://official-joke-api.appspot.com/random_joke");
6  return email({
7    text: punchline,

4 * The suggestions are cached in the browser to reduce API calls.
5 * It implements a two-step LLM process: first to get initial suggestions, then to filter them for sensibility and ethics.
6 * If the second LLM call fails, it displays "Failed to fetch" instead of showing results.
7 */
8
19  const suggestionCache = useRef({});
20
21  const fetchSuggestions = async (input) => {
22    if (suggestionCache.current[input]) {
23      setSuggestions(suggestionCache.current[input]);
28    setError("");
29    try {
30      const response = await fetch("/suggestions", {
31        method: "POST",
32        headers: { "Content-Type": "application/json" },
33        body: JSON.stringify({ query: input }),
34      });
35      if (!response.ok) throw new Error("Failed to fetch suggestions");
36      const data = await response.json();
37      if (data.error) {
43      }
44    } catch (error) {
45      console.error("Error fetching suggestions:", error);
46      setError("Failed to fetch");
47      setSuggestions([]);
48    } finally {
51  };
52
53  const debouncedFetchSuggestions = useRef(
54    debounce(fetchSuggestions, 300),
55  ).current;
56
57  useEffect(() => {
58    if (query.length > 2) {
59      debouncedFetchSuggestions(query);
60    } else {
61      setSuggestions([]);
115
116    try {
117      const response = await fetch("https://api.cerebras.ai/v1/chat/completions", {
118        method: "POST",
119        headers: {
137
138      if (!response.ok) {
139        throw new Error("Failed to fetch from Cerebras API");
140      }
141
146
147      // Second LLM call to filter suggestions
148      const filterResponse = await fetch("https://api.cerebras.ai/v1/chat/completions", {
149        method: "POST",
150        headers: {
190    } catch (error) {
191      console.error("Error calling Cerebras API:", error);
192      return new Response(JSON.stringify({ error: "Failed to fetch" }), {
193        status: 500,
194        headers: { "Content-Type": "application/json" },

39  }, [selectedLocation]);
40
41  const fetchSuggestions = async (input) => {
42    if (suggestionCache.current[input]) {
43      setSuggestions(suggestionCache.current[input]);
47    setIsLoading(true);
48    try {
49      const response = await fetch("/geocode", {
50        method: "POST",
51        headers: { "Content-Type": "application/json" },
52        body: JSON.stringify({ query: input }),
53      });
54      if (!response.ok) throw new Error("Failed to fetch suggestions");
55      const data = await response.json();
56      setSuggestions(data);
57      suggestionCache.current[input] = data;
58    } catch (error) {
59      console.error("Error fetching suggestions:", error);
60      setSuggestions([]);
61    } finally {
64  };
65
66  const debouncedFetchSuggestions = useRef(
67    debounce(fetchSuggestions, 300)
68  ).current;
69
70  useEffect(() => {
71    if (query.length > 2) {
72      debouncedFetchSuggestions(query);
73    } else {
74      setSuggestions([]);
128
129    try {
130      const response = await fetch("https://api.cerebras.ai/v1/chat/completions", {
131        method: "POST",
132        headers: {
146
147      if (!response.ok) {
148        throw new Error("Failed to fetch from Cerebras API");
149      }
150
158    } catch (error) {
159      console.error("Error calling Cerebras API:", error);
160      return new Response(JSON.stringify({ error: "Failed to fetch suggestions" }), {
161        status: 500,
162        headers: { "Content-Type": "application/json" },

200app.get('/main.js', serve(js, 'text/javascript'));
201
202export default app.fetch;