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Products that do what Use local LLMs to organize your files does
Hi everyone, Just wanted to share a use case where local LLMs are genuinely helpful for daily workflows: file organization. I've been working on a C++ desktop app called AI File Sorter – it uses local LLMs via `llama.cpp` to help organize messy folders like `Downloads` or `Desktop`. Not sort files into folders solely based on extension or filename patterns, but based on what each file actually is supposed to do or does. Basically: what would normally take me a great deal of time for dragging and sorting can now be done in a few. It's cross-platform (Windows/macOS/Linux), and fully…
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Built this for my LLM workflows - needed searchable, persistent memory that wouldn't blow up storage costs. I also wanted to use it locally for my research. It's a content-addressed storage system with block-level deduplication (saves 30-40% on typical codebases). I have integrated the CLI tool into most of my workflows in Zed, Claude Code, and Cursor, and I provide the prompt I'm currently using in the repo. The project is in C++ and the build system is rough around the edges but is tested on macOS and Ubuntu 24.04.
2025 · github.com
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Hello HN, I've been working on this project for a while, and it has been in an "open" beta for some time. I finally believe it's ready for its first release. I hope you like it. Here are some potential questions that may arise: 1. How does it compare to LM Studio? It's likely that if you're already using LM Studio, you'll continue to do so. This project is designed to be more user-friendly. 2. Is it open-source? No, it is not. 3. Does it use any open-source libraries? Yes, it uses llama.cpp and a few others, as indicated in the license information included with the application. 4. Why is not…
2023 · avapls.com
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This is a small plugin I made for Simon Willison's llm utility. You can do things like: cat names.txt | llm sort -q "Which one of these names is best for a pet seagull?" cat books.txt | llm sort -q "Which book is more related to basic vs. advanced CS topics?" I see a lot of potential marrying LLMs with classic UNIX interfaces.
2025 · github.com
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I wanted a file management tool that actually understands what my files are about. Previous projects like LlamaFS (https://github.com/iyaja/llama-fs) aren't 100% local and require an AI API. So, I created a Python script that leverages AI to organize local files, running entirely on your device for complete privacy. It uses Google Gemma2 2B and llava-v1.6-vicuna-7b models for processing. Note: You won't need any API key and internet connection to run this project, it runs models entirely on your device. What it does: - Scans a specified input directory for files -…
2024 · github.com
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Hey Folks! I've been building an open source benchmark for measuring local LLM performance on your own hardware. The benchmarking tool is a CLI written on top of Llamafile to allow for portability across different hardware setups and operating systems. The website is a database of results from the benchmark, allowing you to explore the performance of different models and hardware configurations. Please give it a try! Any feedback and contribution is much appreciated. I'd love for this to serve as a helpful resource for the local AI community. For more check out: - Website:…
2025 · localscore.ai
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Dec 2025 · github.com
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Hi HackerNews, Lately, I have seen an explosion in posts offering paid APIs/services to get unstructured data into LLMs (i.e. langchain extract, ragflow, unstructured, unstract, just to name a few) and I have been largely disappointed by them, either because they fail to implement multimodal support, fail to give good context for "really tricky" PDFs / Word docs / Powerpoints, or are just plain difficult to use. In light of all these posts I figured I'd share my solution that has been working smoothly for me and my clients. I put it up on GitHub for free so you can check it…
2024 · github.com
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Jun 2026 · pypi.org
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I built localLLLM: a small community project for running local models. Live: https://locallllm.fly.dev The goal is simple: if someone has model + OS + GPU + RAM, they should get steps that actually work (ideally one liner) I need help populating and validating guides. If you run local models, please submit one working recipe (or report what failed). Would love to hear general feedback as well!
Apr 2026 · locallllm.fly.dev
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Hi HN, I am Jan, CTO and co-founder of Pathway.com. We’ve built a LLM microservice that answers questions about a corpus of documents, while automatically reacting to additions of new docs. The single, self-contained service fully replaces a complex multi-system pipeline that scans in real-time for new documents, indexes them into a specialized database and queries it to generate answers. Everyone can have their own real-time vector now. Github: https://github.com/pathwaycom/llm-app Demo video: https://youtu.be/kcrJSk00duw I am eager to hear your thoughts…
2023 · github.com
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Hi all! I’ve been into the “file-over-app” philosophy lately. The idea of using products through files you can control, in formats that are easy to read and retrieve. I built this directory (https://fileoverapp.latitude.so/) to organize tools following the same principles. The cool thing is most of them are open-source and you can even filter by that. Now I'm looking for more stuff. If you’re aware of similar software, you can contribute and submit a product. I’d love to hear your recommendations!
2024 · fileoverapp.latitude.so
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AI Files Agent Organizer, Space Saver, System Cleaner macOS
May 2026 · 1dot.ai
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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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I created a tool that consolidates information from the following inputs: GitHub repository URL (e.g., https://github.com/jimmc414/onefilellm) arXiv abstract URL (e.g., https://arxiv.org/abs/2401.14295) Local folder path (e.g., C:\python\PipMyRide) Youtube video URL (e.g., https://www.youtube.com/watch?v=KZ_NlnmPQYk) Webpage URL (e.g., https://llm.datasette.io/en/stable/) It outputs the repo, web documentation, arXiv paper or YT transcript to a text file and the clipboard, displaying a token count. It also…
2024 · github.com
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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
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Hi! I've found myself repeatedly writing little scripts to do bulk calls to LLMs for various tasks. For example, run some analysis on a large list of records. There are a few "gotchas" to doing this. For example, some service providers have rate limits, and some models will not reliably return JSON (if you're asking for it). So, I've written a command for this. What I've tried to do here is let the user break up prompts and configuration as they see fit. For example, you can have a prompt file which includes the API key, rate limit, settings, etc. all together, or break these up into…
2025 · 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
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A few months ago I was working on a flight search engine that would include pet transport costs (I know a few by hearth but storing them and make the calculations in the UI would be nice) While I was collecting pet pricing from several airlines I strugled to extract data in a common format without hallucinated values. That's when I thought: What if I use multiple LLMs and take the most common response to improve accuracy? This idea became this new project. You provide your documents, an SQLModel schema, an LLM provider, plus what you'd like to extract and Extrai does the rest. Including…
Nov 2025 · github.com
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