import Exa from "npm:exa-js"; import { ComputeJSON, ComputeText, sb, Substrate } from "npm:substrate"; import { z } from "npm:zod"; import { zodToJsonSchema } from "npm:zod-to-json-schema"; const exa = new Exa(Deno.env.get("EXA_API_KEY")); const substrate = new Substrate({ apiKey: Deno.env.get("SUBSTRATE_API_KEY") }); // const query = "$BLAST"; const query = `"magic eden" OR "@magiceden"`; // Search for tweets from the last week const searchResults = await exa.searchAndContents(query, { text: { maxCharacters: 1000 }, type: "keyword", includeDomains: ["twitter.com"], category: "tweet", startPublishedDate: (new Date(Date.now() - 7 * 24 * 60 * 60 * 1000)).toISOString().split("T")[0], numResults: 20, }); // Extract summary, sentiment analysis, and other info for each tweet const extractedTweet = z.object({ summary: z.string().describe( "Summarize in a couple sentences: what is the text about and how it is related to the topic.", ), isProfile: z.boolean().describe("True if the link is a twitter profile, not a post."), sentiment: z.enum(["positive", "neutral", "negative"]), url: z.string().describe("url"), }); let summaries = []; for (const result of searchResults.results) { summaries.push( new ComputeJSON({ prompt: `Summarize this tweet and how it relates to the topic: ${query} COMMENT: ${JSON.stringify(result)}`, json_schema: zodToJsonSchema(extractedTweet), }, { cache_age: 60 * 60 * 24 }), ); } // Generate markdown summary const markdown = new ComputeText({ prompt: sb.concat( `Below is a list of summarized posts about ${query} on Twitter in the last week. Generate concise markdown summarizing the results. DO NOT INCLUDE a title or introduction. Categorize by sentiment. Include the summary of the tweet and sentiment. DO NOT INCLUDE tweets that are twitter profiles (isProfile = true). After the summary add a link to the tweet in this format: [full url](https://twitter.com//status/) Just return the markdown. Do not introduce with "Here is" or explain the output. RESULTS:\n`, // @ts-ignore ...summaries.map((s) => sb.jq(s.future.json_object, "@json")), ), model: "Llama3Instruct70B", }); const stream = await substrate.stream(markdown); // Render streaming markdown export default async function handler(req: Request): Promise { if (new URL(req.url).pathname === "/robots.txt") { return new Response("User-agent: *\nDisallow: /"); } let { readable, writable } = new TransformStream(); let writer = writable.getWriter(); const textEncoder = new TextEncoder(); writer.write(textEncoder.encode(`

`)); new Promise(async () => { for await (const event of stream.get(markdown)) { if (event.object === "node.delta") { const chunk = event.data.text || ""; writer.write(textEncoder.encode(``)); } } writer.write(textEncoder.encode(``)); writer.close(); }); return new Response(readable, { headers: { "Content-Type": "text/html", }, }); }

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