Search

Render this badge:


Use the middleware: https://www.val.town/v/substrate/substrateBadgeMiddleware

Or:

import substrateBadge from "https://esm.town/v/substrate/substrateBadge";

export default async function(req: Request): Promise<Response> {

const badge = substrateBadge(import.meta.url);

const html = `

const left = 80;

<rect width="${width}" height="${height}" fill="#111" rx="${radius}" ry="${radius}" />

<a href="https://substrate.run">

<text x="8" y="17" textAnchor="start" fill="#fff" style="font-family:system-ui,sans-serif;font-size:12px;font-weight:500;letter-spacing:-0.05em;">

Substrate

</text>

import wrapper from "https://esm.town/v/substrate/substrateBadgeMiddleware";

async function handler(req: Request): Promise<Response> {

import valTownBadge from "https://esm.town/v/substrate/substrateBadge";

export default function badgeMiddleware(handler, url: string) {

return async function(req: Request): Promise<Response> {

Starter template for Substrate demos

import promptHeader from "https://esm.town/v/substrate/promptHeader";

import wrapper from "https://esm.town/v/substrate/substrateBadgeMiddleware";

import { ComputeJSON, ComputeText, GenerateImage, sb, Substrate } from "npm:substrate";

async function handler(req: Request): Promise<Response> {

const { prompt = "modernism" } = Object.fromEntries(searchParams);

// Substrate graph

const substrate = new Substrate({ apiKey: Deno.env.get("SUBSTRATE_API_KEY") });

const startup_name = new ComputeText({

startup_name.future.text,

const stream = await substrate.stream(haiku);

async function* content() {

Demo of embedding images with [substrate](https://www.substrate.run/), and querying them for semantic relevance.

Use the query parameter `prompt` to control the search.


import { renderToString } from "npm:react-dom@18/server";

import { QueryVectorStore, sb, Substrate } from "npm:substrate";

type ShotResult = {

async function getResults(q: string, n: number): Promise<ShotResult[]> {

const substrate = new Substrate({

apiKey: process.env.SUBSTRATE_API_KEY,

const collectionName = "shotclip";

}, { cache_age: 60 * 60 });

const res = await substrate.run(query);

return res.get(query).results[0] as ShotResult[];

<a

href="https://www.substrate.run/"

style={{

fontSize: "12px",

[made with substrate]

</a>

Demo of embedding images with [substrate](https://www.substrate.run/), and querying them for semantic relevance.

Use the query parameter `prompt` to control the search.


import { renderToString } from "npm:react-dom@18/server";

import { QueryVectorStore, sb, Substrate } from "npm:substrate";

type ShotResult = {

async function getResults(q: string, n: number): Promise<ShotResult[]> {

const substrate = new Substrate({

apiKey: process.env.SUBSTRATE_API_KEY,

const collectionName = "shotclip";

}, { cache_age: 60 * 60 });

const res = await substrate.run(query);

return res.get(query).results[0] as ShotResult[];

<a

href="https://www.substrate.run/"

style={{

fontSize: "12px",

[made with substrate]

</a>

[sub.audio](https://sub.audio) – generate subtitles and chapters for any audio URL.

Speech-to-text and chapter summaries powered by [Substrate](https://substrate.run)

🪩 To fork, [sign up for Substrate](https://substrate.run/signin) to get your own API key and $50 free credits

import { ComputeJSON, sb, Substrate, TranscribeSpeech } from "npm:substrate";

import { extractValInfo } from "https://esm.town/v/pomdtr/extractValInfo?v=29";

async function processAudio(audio_uri) {

const substrate = new Substrate({ apiKey: Deno.env.get("SUBSTRATE_API_KEY") });

const opts = { cache_age: 60 * 60 * 24 * 7 };

opts,

const res = await substrate.run(transcribe, chapters, timestamps);

return {

<meta name="viewport" content="width=device-width, initial-scale=1.0" />

<link rel="icon" href="https://www.substrate.run/favicon.ico" type="image/x-icon">

<link

!audio_uri

? `<a id="federer-link" href="?url=https://media.substrate.run/federer-dartmouth.m4a">Or try an example: federer-dartmouth.m4a</a>`

<div id="loading">Running...</div>

</div>

<a id="made-with" href="https://substrate.run" target="_blank"

>made with <b>substrate</b></a

<a id="view-source" href="${extractValInfo(import.meta.url).htmlUrl}" target="_blank"

Find comments on HN (powered by [Algolia](https://hn.algolia.com/api)), extract content and return a streaming markdown summary (powered by [Substrate](https://substrate.run)).

The RAG portion of this is 34 lines of Substrate code. Read the walkthrough: https://x.com/vprtwn/status/1812844236401762513

🪩 To fork, [sign up for Substrate](https://substrate.run/signin) to get your own API key and $50 free credits.

See also:

- https://www.val.town/v/substrate/twitterRAG

import { hnSearch } from "https://esm.town/v/stevekrouse/hnSearch";

import { ComputeJSON, ComputeText, sb, Substrate } from "npm:substrate";

import { z } from "npm:zod";

import { zodToJsonSchema } from "npm:zod-to-json-schema";

const substrate = new Substrate({ apiKey: Deno.env.get("SUBSTRATE_API_KEY") });

markdown.id = "markdown";

const stream = await substrate.stream(markdown);

export default async function handler(req: Request): Promise<Response> {

const renderMarkdown = (await import("https://esm.town/v/substrate/renderMarkdown")).default;

return renderMarkdown(stream);

marginTop: "20px",

<img

src="https://media.substrate.run/sval-layout-5.png"

alt="Svalboard Keyboard Layout"

style={{

Find comments on HN (powered by [Algolia](https://hn.algolia.com/api)), extract content and return a streaming markdown summary (powered by [Substrate](https://substrate.run)).

The RAG portion of this is 34 lines of Substrate code. Twitter thread walkthrough: https://x.com/vprtwn/status/1812844236401762513

🪩 To fork, [sign up for Substrate](https://substrate.run/signin) to get your own API key and $50 free credits.

import { hnSearch } from "https://esm.town/v/stevekrouse/hnSearch";

import inputHeader from "https://esm.town/v/substrate/inputHeader";

import { ComputeJSON, ComputeText, sb, Substrate } from "npm:substrate";

import { z } from "npm:zod";

import { zodToJsonSchema } from "npm:zod-to-json-schema";

const substrate = new Substrate({ apiKey: Deno.env.get("SUBSTRATE_API_KEY") });

model: "Llama3Instruct70B",

const stream = await substrate.stream(markdown);

Find similar pages on HN and return a streaming markdown summary.

Powered by [Exa](https://exa.ai/) and [Substrate](https://substrate.run).

🪩 To fork, [sign up for Substrate](https://substrate.run/signin) to get your own API key and $50 free credits.

import urlHeader from "https://esm.town/v/substrate/urlHeader";

import Exa from "npm:exa-js";

import { ComputeText, GenerateImage, sb, Substrate } from "npm:substrate";

const exa = new Exa(Deno.env.get("EXA_API_KEY"));

const substrate = new Substrate({ apiKey: Deno.env.get("SUBSTRATE_API_KEY") });

export default async function handler(req: Request): Promise<Response> {

model: "Llama3Instruct70B",

const stream = await substrate.stream(summary);

let { readable, writable } = new TransformStream();

NOTE: We've disabled the Exa API key in this demo due to high volume – you'll need to fork and provide your own to use it.

Search on Twitter (powered by [Exa](https://exa.ai)) and return a streaming markdown summary (powered by [Substrate](https://substrate.run)).

To fork, [sign up for Substrate](https://substrate.run/) to get your own API key and $51 free credits.

You'll also need Exa, which comes with generous free credits and can be a much cheaper alternative to the Twitter API.

import Exa from "npm:exa-js";

import { ComputeJSON, ComputeText, sb, Substrate } from "npm:substrate";

import { z } from "npm:zod";

const exa = new Exa(Deno.env.get("EXA_API_KEY"));

const substrate = new Substrate({ apiKey: Deno.env.get("SUBSTRATE_API_KEY") });

const query = `"exa.ai" OR "@ExaAILabs"`;

markdown.id = "markdown";

const stream = await substrate.stream(markdown);

export default async function handler(req: Request): Promise<Response> {

const renderMarkdown = (await import("https://esm.town/v/substrate/renderMarkdown")).default;

return renderMarkdown(stream);