Alternatives
Products that do what INXM // local` OSS for using LLM as compiler and not as runtime does
The LLM is the compiler, not the runtime. Contribute to inxm-ai/inxm-local development by creating an account on GitHub.
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A while ago I started experimenting with compiling the Python interpreter to WASM. To build a secure, fast, and lightweight sandbox for code execution — ideal for running LLM-generated Python code.
2024 · github.com
- 5BA
Bash4LLM is a single-file Bash wrapper for interacting with LLMs from the terminal. I created it because I wanted something simple that worked without installing Python, Node, or any other runtime. It uses only Bash, curl, and jq. You can send prompts, start a small chat, process files line by line, stream output, and save session metadata in JSON format. I tried to make it safe and predictable: no use of the system /tmp, no use of eval. Groq is supported by default, and other providers can be added with dedicated Bash scripts in the extras/providers/ folder. Example: echo…
Jun 2026 · github.com
- 6LN
npm for LLMs — install, run, and share AI models. We’ve built llmpm, a CLI tool that makes open-source LLMs installable like packages. llmpm install llama3 llmpm run llama3 You can also package models with your projects so others can reproduce the same setup easily. Website: https://llmpm.co GitHub:https://github.com/llmpm/llmpm-dev
Mar 2026 · llmpm.co
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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
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Github: https://github.com/AmberSahdev/Open-Interface Binaries available for MacOS, Windows, and Linux.
2024 · github.com
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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
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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
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Hi everyone, I'm Vasek (https://x.com/mlejva), the CEO of the company behind this - https://e2b.dev. The company is called E2B. We're an open-source (https://github.com/e2b-dev) devtool that makes it easy to run untrusted AI-generated code in our secure sandboxes. You can think of us as coding runtime for LLMs. You can self host us on GCP (https://github.com/e2b-dev/infra/blob/main/self-host.md) and we're working on AWS, then Azure, and any Linux machine. This repo is one of our open-source projects that we're…
2025 · github.com
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I've created uithub, a tool that allows developers to easily get LLM context for their coding questions and perform AI repo analysis at scale. Here's what it does: - Get Context: Simply change the 'g' in github.com to 'u' to access AI-powered insights on any GitHub repo. - Flexible Querying: Fetch entire repos, specific branches/subfolders, or filter by file type and size. - API for Developers: Power the next generation of development tools with our API. Key features: - Customizable token limits - File type filtering - Multiple response formats - Size-based file exclusion I built this…
2024 · uithub.com
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Postgres GUI using the LLM already on your Mac. Free, open-source native macOS database GUI using Apple's on-device Foundation Model for text-to-sql. - betocmn/widen
21d ago · github.com
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We've built InferX, a specialized runtime environment that fundamentally changes how LLMs are served. The core problem we solve is the latency bottleneck in AI inference, especially with large models. Current systems waste resources or suffer from painfully slow cold starts. InferX's AI-native architecture, with its "snapshot" technology, enables: * *Sub-2s cold starts:* Spin up models instantly. * *High density:* Serve more LLMs on the same GPUs. * *Optimal efficiency:* Maximize GPU utilization. This isn't just another API; it's a new execution layer designed from the ground up for the…
2025 · github.com
- 15IB
Built a simple web app that tells you which open-source LLMs will work on your hardware. It auto-detects your specs, shows compatible models from Hugging Face, gives realistic performance estimates (tokens/sec), and recommends quantization settings. You can also manually input specs to see "what if I upgraded my RAM?" Made this after wasting time downloading giant models only to find they crawled on my hardware. Hope it saves you some frustration!
2025 · caniusellm.com
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hi everyone. how does moving llm call prompts and output structure definitions away from code into configuration land sound? would you use something like this if it was stable and well documented enough? please don't hold back the criticism. i appreciate all feedback (constructive & otherwise).
2024 · github.com
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Hi HN, I’ve been working on an experimental programming language called XXML. The project started from a frustration I kept running into across systems languages: Languages with strong ownership tend to avoid runtime reflection. Languages with rich reflection usually rely on GC or give up memory guarantees. Compile-time code generation often requires a separate macro language. I wanted to explore whether those tradeoffs are truly necessary. What XXML is trying to do XXML is a statically-typed, native language that: Uses explicit ownership and borrowing (no garbage collector) Supports runtime…
Dec 2025 · xxml-language.com
- 18OS
Hi HN, we’re Dylan and Matthew, building sublingual (https://github.com/sublingual-ai/sublingual), an open-source LLM observability tool you can use with zero code changes. As developers focused on iterating and building features as fast as possible, we felt observability would’ve been a helpful tool to have, but we found existing solutions had too much overhead to set up. So we gave ourselves the challenge of building an observability tool that you can integrate without changing a single line of code in your project. How it works Run your python application as usual with…
2025 · github.com
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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
- 20PB
Started this a few months ago because I wanted a better test runner for an entirely different LLM-based project, then got completely nerdsniped by making LLMs as easy as possible to hotswap into other projects. It's still on the early side but it's finally at the point where I would happily use it for my original project, so I figured I'd post it. It's also—almost by accident—fully remote compatible (permissioning system included!), so you can host it on a box and then connect a program to it remotely.
2023 · github.com
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Slupe lets you use web-based LLMs to modify local files without leaving the browser. npx slupe --clipboard It's a CLI tool that watches for LLM commands and executes them on your computer. Key features: - Custom syntax (NESL) designed for LLM reliability - fewer search/replace failures than existing approaches - Clipboard mode: copy from browser → Slupe executes → paste results back to clipboard - Generates instructions for LLMs based on your allowed actions - Sandboxed filesystem operations with configurable permissions + automatic git backups Motivation: I wanted to use web based Opus…
2025 · github.com
- 22IB
Link: https://docs.trysoma.ai/ For the past ~9 months I’ve been building Soma, an open-source AI agent & workflow runtime written in Rust, with a TypeScript SDK (Python coming soon). It’s not a framework; it’s meant to sit underneath whatever agent/tooling code you already write (Vercel AI SDK, LangChain, custom code, etc.). It provides features around your framework + a better DX for building agents. I’ve tried to take a Next.JS model: open-source, good DX, self-deployable. I originally set out to build a vertical back-office/operations product for SMEs. I needed a…
Dec 2025 · docs.trysoma.ai
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*Motivation* Hi hackers, I'm Asif. I know we dislike premature standardization, but hear me out. LLM Application development is extremely iterative, more so than most other types of application development. We need a process that allows us to iterate faster. LLM Development is highly iterative due to the activities that come with regular software development, as well as the need to make the LLM Application accurate and reduce hallucination. To improve hallucination, we need to trial and error various combinations of LLM models, prompt templates (e.g., few-shot, chain-of-thought), prompt…
2024 · github.com
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We've rolled out a feature for openbase.com that we think is a DX game changer for Node devs. Since the emergence of ECMA Script modules, it's been a continuous guessing game as to what kind of exports a package has. That's never really been discoverable without using a site like unpkg, or installing the package and inspecting package.json. Openbase now displays the ES Module support level (e.g. type of exports) on all of their package pages. We added this feature because our devs are some of the folks continually caught off guard by installing an NPM dependency only to find out it's…
2022
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