LLM from URL –– A free AI chat completion service directly from URL
LLM from URL —— A free AI chat completion service directly from URL Usage: In the address bar of any web browser, type your question after https://818233.xyz/ and hit Enter to get the instant answer. You know the best part of this? Whitespace in the url is supported in most web browsers! You can also use curl or Wget to retrieve the appended url by replacing any whitespace with a '+' character. If you need to have an actual '+' character in your question, just use '++'. Example: The url "https://818233.xyz/hi there" in any web browser will return the same answer…
LLM from URL –– A free AI chat completion service directly from URL launched on August 8, 2025 with 8 votes, #2,487 of 8,530 launches that month and more than 75% of that year's launches. The site was still online in September 2026, 1 year on.
What it does
818233.xyz is a community tweet sharing platform. Submit tweets via our Telegram bot and discover newsworthy content shared by the community.
In the maker’s words, at launch
LLM from URL —— A free AI chat completion service directly from URL Usage: In the address bar of any web browser, type your question after https://818233.xyz/ and hit Enter to get the instant answer. You know the best part of this? Whitespace in the url is supported in most web browsers! You can also…
Does a similar job
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I built a free in-browser Llama 3 chatbot powered by WebGPU2024 · github.com · ▲547I spent the last few days building out a nicer ChatGPT-like interface to use Mistral 7B and Llama 3 fully within a browser (no deps and installs). I’ve used the WebLLM project by MLC AI for a while to interact with LLMs in the browser when handling sensitive data but I found their UI quite lacking for serious use so I built a much better interface around WebLLM. I’ve been using it as a therapist and coach. And it’s wonderful knowing that my personal information never leaves my local computer. Should work on Desktop with Chrome or Edge. Other browsers are adding WebGPU support as well - see…
- WEWebGPU enables local LLM in the browser – demo site with AI chat2025 · andreinwald.github.io · ▲145
Browser LLM demo working on JavaScript and WebGPU. WebGPU is already supported in Chrome, Safari, Firefox, iOS (v26) and Android. Demo, similar to ChatGPT https://andreinwald.github.io/browser-llm/ Code https://github.com/andreinwald/browser-llm - No need to use your OPENAI_API_KEY - its local model that runs on your device - No network requests to any API - No need to install any program - No need to download files on your device (model is cached in browser) - Site will ask before downloading large files (llm model) to browser cache - Hosted on Github…
I wrote an open-source browser alternative for Computer Use for any LLM2024 · github.com · ▲180Hey HN, I made Browser-Use, an open-source tool that lets (all Langchain supported) LLMs execute tasks directly in the browser just with function calling. It allows you to build agents that interact with web elements using natural language prompts. We created a layer that simplifies website interaction for LLMs by extracting xPaths and interactive elements like buttons and input fields (and other fancy things). This enables you to design custom web automation and scraping functions without manual inspection through DevTools. Hasn't this been done a lot of times? Good question, as a general…
Turn any website into a knowledge base for LLMs2024 · embedding.io · ▲305I built this tool because I wanted a way to just take a bunch of URLs or domains, and query their content in RAG applications. It takes away the pain of crawling, extracting content, chunking, vectorizing, and updating periodically. I'm curious to see if it can be useful to others. I meant to launch this six months ago but life got in the way...
- IBIn-Browser Graph RAG with Kuzu-WASM and WebLLM2025 · blog.kuzudb.com · ▲158
We show the potential of modern, embedded graph databases in the browser by demonstrating a fully in-browser chatbot that can perform Graph RAG using Kuzu (the graph database we're building) and WebLLM, a popular in-browser inference engine for LLMs. The post retrieves from the graph via a Text-to-Cypher pipeline that translates a user question into a Cypher query, and the LLM uses the retrieved results to synthesize a response. As LLMs get better, and WebGPU and Wasm64 become more widely adopted, we expect to be able to do more and more in the browser in combination with LLMs, so a lot of…

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