Alternatives
Products that do what I built a deep research tool for local file system does
I was experimenting with building a local dataset generator with deep research workflow a while back and that got me thinking. what if the same workflow could run on my own files instead of the internet. being able to query pdfs, docs or notes and get back a structured report sounded useful. so I made a small terminal tool that does exactly that. I point it to local files like pdf, docx, txt or jpg. it extracts the text, splits it into chunks, runs semantic search, builds a structure from my query, and then writes out a markdown report section by section. it feels like having a lightweight…
- 1TA
I 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...
2024 · embedding.io
- 2DT
I got tired of open file.docx → wait 8 seconds → close Word just to read a document, so I built a terminal-native Word viewer! What it does: * View `.docx` files directly in your terminal with (mostly) proper formatting * Tables actually look like tables (with Unicode borders!) * Nested lists work correctly with indentation * Full-text search with highlighting * Copy content straight to clipboard with `c` * Export to markdown/CSV/JSON Why I made this: Working on servers over SSH, I constantly hit Word docs I needed to check quickly. The existing solutions I'm aware of either strip…
2025 · github.com
- 3AD
2023 · gist.github.com
- 4BA
Hey HN, solo dev here. After years of frustration with how LLMs handle complex documents, especially PDFs with tables, I decided to build a solution myself. My approach uses a Markdown conversion step to preserve the table structure, which seems to work surprisingly well for chunking. This little parser is the first public piece of a much larger, privacy-focused AI platform I'm building. I'm pretty much running on fumes financially, so any feedback, critique, or support is massively appreciated. Happy to answer any questions about the approach!
Nov 2025 · github.com
- 5TA
2023 · github.com
- 6IM
Hi HN, Since 2019, I’ve been working on a writing platform designed for creating complex documents (e.g., theses). I personally use it for everything as it also allows to classify documents in categories so you can organize them efficiently. As of a few months ago, the app is also available in the browser, and you can now invite coworkers to collaborate on a document in real time. The app is somewhat inspired by LyX. It offers an intuitive, modern editor, but users don’t need to know any LaTeX. When it’s time to export, they can choose from a range of templates (IEEE paper, thesis, etc.). A…
2025
- 7GF
Just open-sourced a small terminal tool I’ve been working on. The idea came from wondering how useful it’d be if you could just describe the kind of dataset you need, and it would go out, do the deep research, and return something structured and usable. You give it a description, and it pulls relevant info from across the web, suggests a schema based on what it finds, and generates a clean dataset. The schema is editable, and it also adds a short explanation of what the dataset covers. In some cases, it even asks follow-up questions to make the structure more useful. Started off as a quick…
2025 · github.com
- 8DO
Documind is an open-source tool that turns documents into structured data using AI. What it does: - Extracts specific data from PDFs based on your custom schema - Returns clean, structured JSON that's ready to use - Works with just a PDF link + your schema definition Just run npm install documind to get started.
2024 · github.com
- 9DT
2024 · github.com
- 10MO
Hey HN, we’re Adi and Arnav. A few months ago, we hit a wall trying to get LLMs to answer questions over research papers and instruction manuals. Everything worked fine, until the answer lived inside an image or diagram embedded in the PDF. Even GPT‑4o flubbed it (we recently tried O3 with the same, and surprisingly it flubbed it too). Naive RAG pipelines just pulled in some text chunks and ignored the rest. We took an invention disclosure PDF (https://drive.google.com/file/d/1ySzQgbNZkC5dPLtE3pnnVL2rW_9...) containing an IRR‑vs‑frequency graph and asked GPT “From…
2025 · github.com
- 11SG
Sep 2025 · github.com
- 12
Doing research with agents is fun until they blow way past budget, jumble the sources, and don't even give you the best possible answer, just sound confident. And if you want to run some research task on local data - you have no idea where your data ends up after the prompt consumes it. So I built this tool: a deep-research agent with an enforced budget, verified quotes, and a privacy boundary for local data. 1. Never spend more than you budgeted (measured overshoot is 0%). 2. Every claim carries a source 3. Data stays local (give a CSV, it'll analyze it without the data ever leaving your…
24d ago · github.com
- 13
GUI disk analyzers are great for figuring out what's filling up your laptop/desktop drive. On containers or remote servers, the options are limited to purely text based utilities (e.g. du) or list-centric TUIs (e.g. ncdu) which are usually limited to viewing one directory at a time. I created leaves to fill that gap. Inspired by classic utilities like WinDirStat and KDirStat, it uses a 2-dimensional treemap^1 visualization to show the entire directory hierarchy with proportionally sized rectangles. It's performant enough to handle millions of files, thanks to Rust and multi-threading.…
Jul 2026 · github.com
- 14IJ
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
- 15MO
Solo Dev. Couch Potato. Build a Standalone Open Source Deep research tool. And it Beats Google , Open ai and Perplexity in Multible Metrics : https://veritas-test.neocities.org/ ( pls translate it its german) Guys : lets get this to be used. Because KNOWLAGE Shouldnt be locked behind Paywalls
Feb 2026 · github.com
- 16MD
2021 · github.com
- 17SS
2023 · github.com
- 18AS
2024 · github.com
- 19IB
I really like using NoteBook LM, especially when I have a bunch of research papers I'm trying to extract insights from. For example, if I'm implementing a new feature (like re-ranking) into Morphik, I like to create a notebook with some papers about it, and then compare those models with each other on different benchmarks. I thought it would be cool to create a free, completely open-source version of it, so that I could use some private docs (like my journal!) and see if a NoteBook LM like system can help with that. I've found it to be insanely helpful, so I added a version of it onto the…
2025 · github.com
- 20OS
Hi, I'm building an open-source self-hostable document extraction tool powered by LLM. There are popular data extraction tools and OCR tools in the market. None of them are open source. Most accounting firms, law firms, insurance, back office, and real-estate folks would like to use a tool like this. You can add PDF documents, Images, and audio files and create columns to answer questions on documents or extract information into tabular format. Access to repo: https://github.com/harishdeivanayagam/rowfill Screenshots:…
2025 · github.com
- 21GD
Hello HN, I’m Andrew from docs.dev (https://docs.dev/), an AI powered docs assistant. With docs.dev you can generate your docs directly from your codebase, existing docs and other context sources. We don’t believe AI will replace technical writers—our goal is to make it easier for teams to get a solid first draft that they can review, edit, and improve. Think of it as a head start, not a finished product. More info on what we’ve built below but we wanted to release a quick, 1 minute, generate docs from your codebase tool. Try it out here:…
2025 · app.docs.dev
- 22TR
Hey HN, Today, we’re launching tile.run, an API that extracts structured data from unstructured documents (PDF, images, text) with support for custom schemas. The Problem: Extracting data out of unstructured documents is surprisingly hard. We built tile.run while solving this for our product Kili (automation for invoicing/reconciliation). We found that getting to accuracy that is reliable enough for automation is challenging. Dense documents (e.g., lots of tables or line items) are even harder, and these are the most valuable to automate. After talking to other teams and developers, we…
2024 · tile.run
- 23AT
Hi HN, I built a simple TUI for viewing and editing .md files in the terminal. More and more markdown files keep appearing in our projects, and I found myself needing a quick way to view(with syntax highlighting) and edit them without leaving the terminal, so I built this
Apr 2026 · mdee.bkh.dev
- 24IA
Hey HN! I've build a simple tool to index and search your documents. This uses two great open source libraries: apache tika (for extracting content from docs) and apache lucene (for searching). It's been built with kotlin ktor as a web framework. You can index all kind of files (i.e doc, docx, xls, ppt, pdf, txt, html even ORC pdfs) and then search them using very advanced queries like "always contain X", "never contain X", "X near Y", wildcard search, proper stemming support etc. We're using it on my work where we have hundreds of thousands of doc/docx/pdf files and it works…
2024 · github.com
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