[{"_1":2,"_3":-5,"_4":-5},"loaderData",{"_5":6,"_7":8,"_9":10},"actionData","errors","root",{"_178":179,"_180":181},"routes/_app.x.$handle.$name",{"_98":97,"_32":45,"_106":85,"_27":107,"_13":14,"_108":-5,"_11":109,"_110":111,"_112":113,"_114":115,"_116":117,"_20":-5,"_118":119,"_120":121,"_122":25,"_123":124,"_125":49,"_126":-5,"_127":-5,"_128":129},"routes/_app.x.$handle.$name.branch.$branch.version.$version.diff",{"_11":12,"_13":14,"_15":16,"_17":-5,"_18":-5},"project",{"_43":44,"_32":45,"_38":46,"_47":-5,"_48":49,"_50":51,"_52":51,"_53":-5,"_54":-5,"_18":55,"_56":31,"_57":49,"_58":-5,"_59":-5,"_60":61,"_62":63,"_64":-5,"_65":-5,"_66":-5,"_67":-5,"_68":69,"_70":69,"_71":72,"_73":72,"_74":72,"_75":69,"_76":69,"_77":78,"_79":80,"_81":82,"_83":25},"version",8,"changes",[19],"aiChatInfo","userId",{"_20":21,"_22":23,"_24":25,"_26":25,"_27":28,"_29":28},"file",{"_30":31,"_32":28,"_33":34,"_35":37,"_38":39,"_40":14,"_41":42,"_24":25},"previous",{"_30":31,"_32":28,"_33":34,"_35":36},"deleted",false,"deletedHere","path","main.tsx","latestPath","fileId","885ecc76-252d-11f0-8a67-569c3dd06744","name","fileType","http","content","import { Hono } from \"npm:hono@3.2.7\";\nimport _ from \"npm:lodash\";\n// https://gist.github.com/maxmcd/b170e57d53cb942642c35b135e2d52f1 (takes a bit of time to load)\nimport { searchEmojis } from \"https://esm.town/v/maxm/emojiVectorEmbeddings\";\nimport { extractValInfo } from \"https://esm.town/v/pomdtr/extractValInfo\";\nconst app = new Hono();\n\nconst { htmlUrl } = extractValInfo(import.meta.url);\n\nconst fuseOptions = {\n // Only search for prefixes to make things faster\n location: 0,\n threshold: 0,\n distance: 0,\n};\n\n// Search endpoint\napp.get(\"/search\", async (c) => {\n let query = c.req.query(\"q\");\n if (typeof query !== \"string\") {\n return c.text(\"Invalid query\", 400);\n }\n query = query.trim();\n const t0 = performance.now();\n const results = await searchEmojis(query);\n return c.json(results, 200, { \"Time\": String(performance.now() - t0) });\n});\n\n// Serve the frontend\napp.get(\"/\", (c) => {\n return c.html(html);\n});\n\nconst html = `\n\n\n\n \n \n Emoji Instant Search\n \n \n \n\n\n

Simple Wikipedia Instant Search

\n Just a little demo to demonstrate instant search on Val Town.\n
\n Check out the\n source and build your own!\n

\n search\n \n

\n View Source\n\n \n\n\n`;\n\nexport default app.fetch.bind(app);","import { Hono } from \"npm:hono@3.2.7\";\nimport _ from \"npm:lodash\";\n// https://gist.github.com/maxmcd/b170e57d53cb942642c35b135e2d52f1 (takes a bit of time to load)\nimport { searchEmojis } from \"https://esm.town/v/maxm/emojiVectorEmbeddings\";\nimport { extractValInfo } from \"https://esm.town/v/pomdtr/extractValInfo\";\nconst app = new Hono();\n\nconst { htmlUrl } = extractValInfo(import.meta.url);\n\nconst fuseOptions = {\n // Only search for prefixes to make things faster\n location: 0,\n threshold: 0,\n distance: 0,\n};\n\n// Search endpoint\napp.get(\"/search\", async (c) => {\n let query = c.req.query(\"q\");\n if (typeof query !== \"string\") {\n return c.text(\"Invalid query\", 400);\n }\n query = query.trim();\n const t0 = performance.now();\n const results = await searchEmojis(query);\n return c.json(results, 200, { \"Time\": String(performance.now() - t0) });\n});\n\n// Serve the frontend\napp.get(\"/\", (c) => {\n return c.html(html);\n});\n\nconst html = `\n\n\n\n \n \n Emoji Instant Search\n \n \n \n\n\n

Emoji Instant Search

\n Just a little demo to demonstrate instant search on Val Town.\n
\n Check out the\n source and build your own!\n

\n search\n \n

\n View Source\n\n \n\n\n`;\n\nexport default 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Emoji Instant Search\n\nUses vector embeddings to get \"vibes\" search on emojis\n\n\n![image.png](https://imagedelivery.net/iHX6Ovru0O7AjmyT5yZRoA/df520ac1-06f0-4502-902e-0e07adaab400/public)\n\nWays this could be better:\n\n- Give it a better name, like: actuallygoodemojisearch.net\n- Index the emojis better, eg: feed the emoji image into an llm and get a richer description of what the emoji is and represents.\n- Make static pages for each emoji with \"related\" emojis (do vector similarity on the current emoji against other 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Diff · v8