Trending Vals

Track iPhone trade-in prices iPhone trade in values - to trade phones back to Apple themselves - fluctuate over time , and eventually they no longer accept certain kinds of phones. You can still trade in an iPhone 7 - released in 2016 , about 6 years ago as of this writing. But no longer does an iPhone 6 have value back to Apple. This tracks those values - it runs every month and records prices to iphoneTradeInValues , which I'll visualize once there's some data.

Forked from moe/exampleP5sketch

Forked from xkonti/gptMemoryManager

Serve Readme Usage import codeOnValTown from "https://esm.town/v/andreterron/codeOnValTown?v=50"; import { serveReadme } from "https://esm.town/v/pomdtr/serve_readme"; const val = extractValInfo(import.meta.url); export default serveReadme({ val, title: "Code Search is Easy", }); Example @pomdtr/code_search_is_easy (rendered at https://code-search-is-easy.pomdtr.me )

Returns a simple privacy policy for the GPT Memory API. Examples of input: apiName : Memory API contactEmail : some@email.com lastUpdated : 2023-11-28

dialog Renders windows 98 dialog boxes as SVGs. Using satori and styles from 98.css Usage https://jdan-dialog.web.val.run/? w =200& h =110& title =Hello& caption =World w (default: 200): the width of the dialog h (default: 110): the height of the dialog title (default: "{title}"): the text in the title bar caption (default: "{caption}"): the caption text

Forked from xkonti/extractHttpEndpoint

Forked from ireneg/perceptiveSilverDog

Forked from ireneg/highGreenTahr

Forked from stevekrouse/valTownInspirationEmail

Forked from jordan/bsky_rss_poll

Forked from xkonti/gameIdeaApi

Render form and save data This val provides a web-based interface for collecting email addresses. It features a dual-functionality approach: when accessed via a web browser using a GET request, it serves an HTML form where users can submit their email address. If the script receives a POST request, it implies that the form has been submitted, and it proceeds to handle the incoming data. Fork this val to customize it and use it on your account.

Telemetry For Vals. Telemetry is a library that lets you trace val town executions with opentelemetry. All traces are stored in val.town sqlite and there is an integrated trace viewer to see them. Quickstart Instrument an http val like this. import { init, tracedHandler, } from "https://esm.town/v/saolsen/telemetry"; // Set up tracing by passing in `import.meta.url`. // be sure to await it!!! await init(import.meta.url); async function handler(req: Request): Promise<Response> { // whatever else you do. return } export default tracedHandler(handler); This will instrument the http val and trace every request. Too add additional traces see this widgets example . Then, too see your traces create another http val like this. import { traceViewer } from "https://esm.town/v/saolsen/telemetry"; export default traceViewer; This val will serve a UI that lets you browse traces. For example, you can see my UI here . Tracing By wrapping your http handler in tracedHandler all your val executions will be traced. You can add additional traces by using the helpers. trace lets you trace a block of syncronous code. import { trace } from "https://esm.town/v/saolsen/telemetry"; trace("traced block", () => { // do something }); traceAsync lets you trace a block of async code. import { traceAsync } from "https://esm.town/v/saolsen/telemetry"; await traceAsync("traced block", await () => { // await doSomething(); }); traced wraps an async function in tracing. import { traceAsync } from "https://esm.town/v/saolsen/telemetry"; const myTracedFunction: () => Promise<string> = traced( "myTracedFunction", async () => { // await sleep(100); return "something"; }, ); fetch is a traced version of the builtin fetch function that traces the request. Just import it and use it like you would use fetch . sqlite is a traced version of the val town sqlite client. Just import it and use it like you would use https://www.val.town/v/std/sqlite attribute adds an attribute to the current span, which you can see in the UI. event adds an event to the current span, which you can see in the UI.

WIP Searcher for HN whos hiring posts HonoJs doesn't support render for async components so the style is off for the home page. And the state changes don't register in html rendering so thinking of using react instead.

This project is an argument summarizer that leverages AI to analyze and extract key arguments from a given text. Goals: Provide a user-friendly interface for inputting text Process the input using a large language model (LLama3 via Groq) Extract and structure key arguments, explanations, and relevant quotes Present the summarized arguments in a clear, organized format The main pipeline: User inputs text through a web interface The input is sent to an AI model for processing The AI extracts and structures the arguments The results are validated against a predefined schema The structured arguments are displayed to the user This tool aims to help users quickly understand the main points and supporting evidence in complex texts or discussions, making it valuable for research, debate preparation, or general comprehension of argumentative content.

Plausible analytics Call track with the domain you set up in plausible and the request. I've been using saolsen.val-name . Note that there is no auth for the plausible events API, so if somebody forks the val it'll still work but track all their val page loads in your dashboard which is kinda weird but also kinda cool, idk. See https://www.val.town/v/saolsen/plausible_example for how to use.

Check if a URL is valid Returns true if a URL is valid and false if not

Forked from maxm/discordBotExample

Forked from jeffreyyoung/BaseBot

Cerebras Debater An app that debates with itself while you watch Setup Sign up for Cerebras Get a Cerebras API Key Save it in a Val Town environment variable called CEREBRAS_API_KEY

Simple API wrapper for sending a message over XMPP to any Jabber ID on the federated network. import sendxmpp from "https://esm.town/v/singpolyma/sendxmpp"; await sendxmpp("someone@example.com", "Hello!");

Simple helper for sending a message over XMPP. For an API that doesn't require your own bot setup see https://www.val.town/v/singpolyma/sendxmpp import sendxmpp from "https://esm.town/v/singpolyma/sendxmpplib"; await sendxmpp("someone@example.com", "Hello!"); Also supports optional keepalive to send multiple messages with one connection: import sendxmpp from "https://esm.town/v/singpolyma/sendxmpplib"; await sendxmpp("someone@example.com", "1", true); await sendxmpp("someone@example.com", "2", true); await sendxmpp("someone@example.com", "3); Or even manual disconnect: import sendxmpp from "https://esm.town/v/singpolyma/sendxmpplib"; await sendxmpp("someone@example.com", "1", true); await sendxmpp("someone@example.com", "2", true); const stop = sendxmpp("someone@example.com", "3", true); stop(); Environment variables needed for your bot: XMPP_URI=wss://example.com XMPP_DOMAIN=example.com XMPP_USERNAME=bot XMPP_PASSWORD=password Only websockets or direct tls (xmpps://) connections are supported until https://github.com/denoland/deno/issues/26685 is fixed

🤖 A gateway to Hugging Face's Inference API You can perform various NLP tasks using different models . The gateway supports multiple tasks, including feature extraction, text classification, token classification, question answering, summarization, translation, text generation, and sentence similarity. Features Feature Extraction : Extract features from text using models like BAAI/bge-base-en-v1.5 . Text Classification : Classify text sentiment, emotions, etc., using models like j-hartmann/emotion-english-distilroberta-base . Token Classification : Perform named entity recognition (NER) and other token-level classifications. Question Answering : Answer questions based on a given context. Summarization : Generate summaries of longer texts. Translation : Translate text from one language to another. Text Generation : Generate text based on a given prompt. Sentence Similarity : Calculate semantic similarity between sentences. Usage Send a POST request with the required inputs to the endpoint with the appropriate task and model parameters. Or use the default models. # Example Default Model Request curl -X POST -H "Content-Type: application/json" -d '{"inputs": {"source_sentence": "Hello World", "sentences": ["Goodbye World", "How are you?", "Nice to meet you."]}}' "https://iamseeley-hfapigateway.web.val.run/?task=feature-extraction" Example Requests Feature Extraction curl -X POST -H "Content-Type: application/json" -d '{"inputs": ["Hello World", "Goodbye World"]}' "https://iamseeley-hfapigateway.web.val.run/?task=feature-extraction&model=BAAI/bge-base-en-v1.5" Feature Extraction curl -X POST -H "Content-Type: application/json" -d '{"inputs": {"source_sentence": "Hello World", "sentences": ["Goodbye World", "How are you?", "Nice to meet you."]}}' "https://iamseeley-hfapigateway.web.val.run/?task=feature-extraction&model=sentence-transformers/all-MiniLM-L6-v2" Text Classification curl -X POST -H "Content-Type: application/json" -d '{"inputs": "I love programming!"}' "https://iamseeley-hfapigateway.web.val.run/?task=text-classification&model=j-hartmann/emotion-english-distilroberta-base" Token Classification curl -X POST -H "Content-Type: application/json" -d '{"inputs": "My name is John and I live in New York."}' "https://iamseeley-hfApiGateway.web.val.run/?task=token-classification&model=dbmdz/bert-large-cased-finetuned-conll03-english" Question Answering curl -X POST -H "Content-Type: application/json" -d '{"inputs": {"question": "What is the capital of France?", "context": "The capital of France is Paris, a major European city and a global center for art, fashion, gastronomy, and culture."}}' "https://iamseeley-hfapigateway.web.val.run/?task=question-answering&model=deepset/roberta-base-squad2" Summarization curl -X POST -H "Content-Type: application/json" -d '{"inputs": "The tower is 324 metres (1,063 ft) tall, about the same height as an 81-storey building, and the tallest structure in Paris. Its base is square, measuring 125 metres (410 ft) on each side. During its construction, the Eiffel Tower surpassed the Washington Monument to become the tallest man-made structure in the world, a title it held for 41 years until the Chrysler Building in New York City was finished in 1930. It was the first structure to reach a height of 300 metres. Due to the addition of a broadcasting aerial at the top of the tower in 1957, it is now taller than the Chrysler Building by 5.2 metres (17 ft). Excluding transmitters, the Eiffel Tower is the second tallest free-standing structure in France after the Millau Viaduct."}' "https://iamseeley-hfapigateway.web.val.run/?task=summarization&model=sshleifer/distilbart-cnn-12-6" Translation curl -X POST -H "Content-Type: application/json" -d '{"inputs": "Hello, how are you?"}' "https://iamseeley-hfapigateway.web.val.run/?task=translation&model=google-t5/t5-small" Text Generation curl -X POST -H "Content-Type: application/json" -d '{"inputs": "Once upon a time"}' "https://iamseeley-hfapigateway.web.val.run/?task=text-generation&model=gpt2" Sentence Similarity curl -X POST -H "Content-Type: application/json" -d '{"inputs": {"source_sentence": "Hello World", "sentences": ["Goodbye World"]}}' "https://iamseeley-hfapigateway.web.val.run/?task=sentence-similarity&model=sentence-transformers/all-MiniLM-L6-v2" Val Examples Using Pipeline import Pipeline from "https://esm.town/v/iamseeley/pipeline"; // ... } else if (req.method === "POST") { const { inputs } = await req.json(); const pipeline = new Pipeline("task", "model"); const result = await pipeline.run(inputs); return new Response(JSON.stringify(result), { headers: { "Content-Type": "application/json" } }); } } exampleTranslation exampleTextClassification exampleFeatureExtraction exampleTextGeneration exampleSummarization exampleQuestionAnswering

Forked from stevekrouse/btcPriceAlert

An implementation of simpletext blog by jonfraser . Installation info coming later.

Forked from stevekrouse/newRSSItems

Forked from pomdtr/gfm

Dependency Graph Explorer This val allows for dependency graph exploration. getDependencyGraph Iteratively explores the dependency graph of a val and its children, returning the results. arguments valUrlOrSlug string - the full val url or slug ( author/name ) of the val returns An object containing: dependencyMap Map<string, string[]> - A map of vals (by id) to dependencies (vals or non-val id) moduleMap Map<string, Module> - A map of modules (by val or non-val id) to module information. Module object contains: slug string - the slug of the module, how it should be displayed visually id string - the id of the module, corresponding to how it's displayed in the code, normally as a url. websiteUrl string - the website link for the module, a normally a link to either valtown or npm. category string|null - the category of the module, such as "valtown", "esm.sh", or "npm". Those without a predefined category are in null.

Copy of ArcGISIdentityManager.authorize() , OAuth2 authentication for the ESRI ArcGIS API which is implemented as Express middleware, ported to Hono.