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Products that do what Mixlayer – code and deploy LLM prompts using JavaScript does
Hi HN, I'm excited to introduce Mixlayer, a platform I've been working on over the past 6 months that allows you to code and deploy prompts using simple JavaScript functions. Mixlayer recreates the developer experience of using LLMs locally without having to do all of the local setup yourself. I originally came up with this idea when using LLMs on my MacBook and thought it’d be cool to build a product that makes it easy for everyone. It compiles your code to a WASM binary and runs it alongside a custom inference stack I wrote in Rust. When you integrate LLMs in this way, your code and the…
- 1LB
For the past few months I've been building a lot of things with LLMs (GPT-3, Codex, etc.) as I've been trying to push them to their limits (especially towards applying them to the tabular data domain) When working on this, I've found there are some common patterns for solving problems (templating, chaining, functional-programming style operations, etc.) As I've iterated, I've come to believe that a functional style interface is likely going to power a new wave of systems I'm calling "prompt-machines"(systems where the core new unit of work is a "named" LLM prompt, extending the "function"…
2022 · github.com
- 2EL
Hey HN! I built Experiment to solve a common frustration in LLM development: the lack of proper tools for prompt engineering experimentation. Here's what makes it different: Key Features: - Load and edit chat completion logs from CSV files - Fork and modify specific conversation entries - Run inference via Anthropic, Mistral, and OpenAI - Define custom tools using JSONSchema format - Visual tool usage analysis with collapsible, sorted key-value pairs - Full mobile support and available as installable PWA Technical Highlights: - Built with React using custom isomorphic architecture -…
2025 · github.com
- 3PA
Hey HN! We just launched PromptL: a templating language built to simplify writing complex prompts for LLMs like GPT-4 and Claude. Why PromptL? Creating dynamic prompts for LLMs can get tricky, even with standardized APIs that use lists of messages and settings. While these formats are consistent, building complex interactions with custom logic or branching paths can quickly become repetitive and hard to manage as prompts grow. PromptL steps in to make this simple. It allows you to define and manage LLM conversations in a readable, single-file format, with support for control flow and…
2024 · promptl.ai
- 4OD
I’d like to use LLMs for remembering all kinds of things: fitness, to-do lists, contacts, bug reports, research links, whatever. But there is no way to do that now. For example, if I find a great coding tutorial in chat, or tell it how much I ran yesterday, it forgets that when I close the chat. Even if I keep the chat history, I still need to scour through lots of messages to find the data I want. Ideally, Claude would remember all this, and I’d be able to find it later with ease. This is what my team built. It is a collaborative database you add to any LLM that supports MCP. (Claude Code,…
2025 · dry.ai
- 5HP
Hi HN. I heard you like dev tools and AI, so we wanted to share our project that we’ve been working on. We’re working on Horizon [1] - a higher level abstraction for LLMs so that developers can spend less time trying to grapple with LLMs to make them work and more time with users. This is the starting feature set which takes an auto-ML approach to identify the optimal LLM model, hyperparameters, and prompt - instead of just giving you the tooling to figure it out yourself. You can read more about it in our documentations. Our view is that as LLMs become increasingly commoditized and prompts…
2023 · gethorizon.ai
- 6XR
Hi HN, We built Xybrid, a Rust library for running LLM + speech pipelines directly inside your app, no server, no daemon, just one binary. We started building it while working on a privacy-focused LLM app with Tauri and realized there wasn’t a straightforward way to embed models directly into shipped applications without relying on a separate server process. Xybrid links into your process like any other library. It supports GGUF / ONNX / CoreML and integrates with Flutter, Swift, Kotlin, Unity, and Tauri, letting you run pipelines like speech → LLM → speech in a single call. On…
Mar 2026 · github.com
- 7LF
Hey HN, I built SWE-Kit, LLM toolkit (Function callable tools) which makes building agents specialised in coding like Devin very easy. I noticed a typical pattern while building local agents: creating & perfecting LLM tools to interact with system or codebase was the repeated and time-consuming. We created a layer that simplifies building agents that can interact with code, file system, git, shell and allows you to quickly solve for a wide variety of coding agent use cases. Aren’t there open coding agents already? Well, yes, but most folks would want to solve their specific use case like a…
2024 · swekit.dev
- 8OS
Hey HN - OP here. I wrote some about this project in the following link, and there's a video demo as well: https://portfolio.christopherhwood.com/llm-drag-drop-website... This has been one of my favorite things I've ever worked on - the way the LLM collaborates with the user to accelerate tedious and hard work, the way you can directly edit the code instead of dealing with a panel of visual editing toggles - I think it has a lot of potential but I don't have time to pursue it anymore so open-sourcing it. The idea for this came out of conversations with a few people who were…
2025 · github.com
- 9HH
I found myself building a bunch of LLM-backed features that needed to use tool calling, and some of those tools involved doing things that were somewhat high stakes - communicating on my behalf or modifying shared / production data. one example - I wanted to replace a marketing website with a chatbot + vector DB loaded with the previous content, docs, and blog posts. Between hallucinations, missing knowledge base info, and the LLM generally writing like an psuedo-intellectual high schooler, I realized I couldn't trust it to communicate unsupervised with my website visitors. I needed a…
2024 · github.com
- 10WB
Mix is a multimodal agents SDK. It comes with a GUI playground for testing and debugging SDK workflows. • Built for multimodal workflows instead of code based workflows • The GUI playground is built from the typescript SDK • All project data is stored plain text and native media files - absolutely no lock-in. • The backend is an HTTP server, check out our python and typescript SDK's
Sep 2025 · github.com
- 11PR
Hi HN, While building RAG agents, I noticed a lot of token budget was wasted on formatting overhead (HTML tags, JSON structure, whitespace). Existing solutions felt too heavy (often requiring torch/transformers), so I wrote this lightweight, zero-dependency library to solve it. It includes strategies for context packing, PII redaction, and tool output compression. Benchmarks show it can save ~15% of tokens with negligible latency overhead (<0.5ms). Happy to answer any questions!
Dec 2025 · github.com
- 12LC
Debugging is hard for LLMs, because they primarily depend on source code, and they don't have access to runtime state. I spent countless hours debugging code, and the only way I found LLMs useful for that, is to ask them to add log lines. That's annoying, because it pollutes my code and adds unnecessary diffs. So we made an MCP server that solve this problem. It gives MCP clients (like Claude Code) access to a NodeJS inspector, so they can: 1. set breakpoints 2. step in, step out, continue 3. fetch the current execution location 4. read console output 5. run JS using eval To try: 1. run a…
2025 · github.com
- 13LA
You build LLM applications with YAML files, that define an execution graph. Nodes can be either LLM API calls, regular function executions or other graphs themselves. Because you can nest graphs easily, building complex applications is not an issue, but at the same time you don't lose control. The YAML basically states what are the tasks that need to be done and how they connect. Other than that, you only write individual python functions to be called during the execution. No new classes and abstractions to learn.
2024 · github.com
- 14AP
Hey HackerNews, I'm building an open-source library aiming to make it very easy for anyone to use plugins with any LLM (plugins as defined by OpenAI). I just finished this very simple tutorial: https://github.com/edreisMD/plugnplai/blob/master/examples/a.... And would love to get some feedback, and suggestions on how to improve it / make it useful for you. Steps: 1. Load plugins from https://plugnplai.com directory (now with ~150 plugins) 2. Install and activate: Load specifications and build a default prompt describing the plugins to…
2023 · twitter.com
- 15ET
We built a browser extension (Chrome + Firefox) that captures the runtime DOM and exports it as JSON. Not the pre-render source (HTML/CSS/JS, templates, bundles) and not a screenshot — but the live, post-render state the browser is actually displaying: - visibility/hidden, disabled/required - current input values and validation/validationMessage - dataset attributes - trimmed text - stable selector paths Why: LLMs often miss or guess UI state. Screenshots are too opaque, pre-render source is too noisy. A structured snapshot gives reproducible context for debugging…
2025
- 16CA
Hi HN, I've been working with LLMs in production for a while both as a solo dev building apps for clients and working at an AI startup. The one thing that always was a pain was to pay OpenAI/Gemini/Anthropic a few dollars a month just for me to say "test" or have a CI runner validate some UI code. So I built this server called ChunkBack, that mocks the popular llm provider's functionality but allows you to type in a deterministic language: `SAY "cheese"` or `TOOLCALL "tool_name" {} "tool response"` I've had to work in some test environments and give good results for experimenting…
Nov 2025 · github.com
- 17IB
Mix is an open-source, local agent for multimodal claude code. Claude code users will feel at home. - Uses ffmpeg and local apps like blender instead of clunky cloud based editors - All project data is stored plain text and native media files - absolutely no lock-in. - The backend is an HTTP server, meaning that the frontend is just one of possible clients. - - Our SDK with stdio interface (similar to claude code SDK) is launching soon.
2025 · github.com
- 18IB
hey hn, I built an open-source Perplexity clone that can run local LLMs and cloud LLMs. It's fully self-hostable through Docker and uses ollama to support local LLMs. The demo video in the repository shows me running it locally with llama3 on my M1 Macbook Pro. I'm open to any suggestions or feedback, thanks!
2024 · github.com
- 19LC
Hey, folks here is a peek into Jujutsu. We at Poozle are working with hundreds of APIs and it has been always frustrating to 1. Search the API in the documentation or ask ChatGPT 2. Then copy it to the postman and understand/test the API 3. Generate code to integrate into the codebase We thought how about having all of this at one place. We currently fine-tuned LLM on public REST APIs to reduce hallucination and then combined it with ChatGPT and Postman. I look forward to feedback, feature requests and discussions!
2023 · loom.com
- 20AM
I recently saw a post from the Vercel CEO pointing out that LLMs understand websites much better when they can request: `Accept: text/markdown` Most websites today are built for humans. When AI agents try to consume them, they get complex HTML instead of clean, structured content. So I built *accept-md* – a simple open-source package for Next.js that helps solve this. Getting started is intentionally minimal: ``` npx accept-md init ``` After that, your existing Next.js routes can automatically respond with Markdown whenever an AI agent (or any client) requests it. No redesigns, no CMS…
Feb 2026 · accept.md
- 21PL
Hi, I’ve been exploring Claude 3.5 code generation abilities for a while and it looks like it can generate more consistent code than other models. However it would still be unmaintainable if you ask it to write a lot of code and it still sucks at system design. So, I’ve been playing around the idea of using the code repository with a template for directory layout and infrastructure, then adding the repository information to Claude and asking it to generate code. It seems that it works, if I pass the structure of some OpenAPI based backend it can update the API definition and implementation…
2024 · github.com
- 22BA
I built CodinIT because I wanted that "Bolt-like" experience, but on my own terms. 100% Open Source The core idea: You should be able to prompt a full-stack application into existence, but the environment should be local, the models should be swappable (Ollama/LM Studio support was a priority), and the output should be standard code you actually own. A few things I focused on: Context Management: One of the hardest parts was figuring out how to feed the right file context back to the LLM without blowing out the token limit. I’ve implemented a custom indexing approach to keep the "vibe…
Dec 2025 · github.com
- 23II
Ask Steve unlocks the power of LLMs like ChatGPT and Gemini in every web page. It's like Github Copilot but for everyday work in the browser. - Create reusable prompts (“Skills”) that can be used on any web page or text selection. Over 100 are included. - Right click on any page or text-selection to run a Skill on it - Chat with any page to quickly get summaries, extract key information or run a Skill on it - Get help writing, rewriting and editing in any text field with Skills for content creation & editing - Add AI buttons to any web page that enable you to trigger a Skill with 1-click.…
2024 · chromewebstore.google.com
- 24KY
Hey HN! I wanted to practice "vibe coding" and see how far and fast I can go by only prompting, without actual coding. I decided to make a simple CLI app that scrapes web docs into a single md file (I was annoyed that LLM keeps writing Tailwind 3 code for a Tailwind 4 project). In just a couple of hours, the CLI app was ready! Then iterated on arguments for another couple of hours. Result: https://github.com/vladstudio/web2llm Then I decided to go further and "productize" the CLI by making a web app for it. Another half-day, and the web app is ready!…
2025 · web2llm.dev
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