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Products that do what BloClaw does
AI workspace for scientific discovery
- 1LC
Outlines is a Python library that focuses on text generation with large language models. Brandon and I are not LLM experts and started the project a few months ago because we wanted to understand better how the generation process works. Our original background is probabilistic, relational and symbolic programming. Recently we came up with a fast way to generate text that matches a regex (https://blog.normalcomputing.ai/posts/2023-07-27-regex-guide...). The basic idea is simple: regular expressions have an equivalent Deterministic-Finite Automaton (DFA) representation. We…
2023 · github.com
- 2GA
For the past three years I've been building what I hope will be the next Blender, tackling the lack of any good 2D design or image editing tools outside the Adobe monopoly. This was our first year participating in Google Summer of Code and this Q3 update includes the big payoff from that, covering the most progress we've made so far as a project. If you're a Rust dev, consider getting involved as we apply for the next GSoC in the new year— you could be our intern next summer :) Q3 progress report: https://graphite.rs/blog/graphite-progress-report-q3-2024/
2024 · graphite.rs
- 3MA
I've invented a new alternative to forking / vendoring / monkey-patching packages in Python. It's a bit like OverlayFS for Python modules - it allows you write modifications for a target module (lower) in a new module (upper), and have these combined in a new virtual module (mount). It works by rewriting imports using AST transformations, then running both the lower and upper module's code in the new Python module. This prevents polluting the global namespace when monkey-patching, and means if you want to make changes to a third-party package, you don't have to take on the…
Oct 2025 · github.com
- 4AS
Hi all! A little background: I've been working on natto.dev, a spatial environment for JavaScript. I'm really excited about new interfaces for code (leveraging metaphors we're good at, spatial reasoning, making state visible, design tools, etc). With all the buzz around PyScript, I discovered Pyodide and got it working inside natto. This Python version is a stripped down version of https://natto.dev (eg interactive outputs, multiplayer) so please check that out if this interests you. I'm excited to share this spatial environment for Python. Imagine Jupyter cells arranged on a 2D…
2022 · python.natto.dev
- 5LS
2024 · github.com
- 6
- 7AJ
Here's a project I've been working on for a little while now. Ripl is a JS library that provides a unified API for rendering shapes on both canvas and SVG interchangeably. Over the years I've used D3 extensively to create data visualisations so I figured I'd have a go at making my own version with a slightly more modern API and stricter TypeScript support. I am aware there are already libraries that can draw to multiple contexts interchangeably, but I've added a few little niceties to Ripl that (as far as I know) some other libraries don't have such as CSS-like query selectors, DOM-like…
2024 · github.com
- 8MC
Hi HN, Jack here! I'm one of the creators of MonkeyPatch, an easy tool that helps you build LLM-powered functions and apps that get cheaper and faster the more you use them. For example, if you need to classify PDFs, extract product feedback from tweets, or auto-generate synthetic data, you can spin up an LLM-powered Python function in <5 minutes to power your application. Unlike existing LLM clients, these functions generate well-typed outputs with guardrails to mitigate unexpected behavior. After about 200-300 calls, these functions will begin to get cheaper and faster. We've seen 8-10x…
2023 · github.com
- 9
- 10RL
We've been building data pipelines that scrape websites and extract structured data for a while now. If you've done this, you know the drill: you write CSS selectors, the site changes its layout, everything breaks at 2am, and you spend your morning rewriting parsers. LLMs seemed like the obvious fix — just throw the HTML at GPT and ask for JSON. Except in practice, it's more painful than that: - Raw HTML is full of nav bars, footers, and tracking junk that eats your token budget. A typical product page is 80% noise. - LLMs return malformed JSON more often than you'd expect, especially with…
Mar 2026 · github.com
- 11IW
2023 · github.com
- 12HO
For the last year I’ve been developing Hyperparam — a collection of small, fast, dependency-free open-source libraries designed for data scientists and ML engineers to actually look at their data. - Hyparquet: Read any Parquet file in browser/node.js - Icebird: Explore Iceberg tables without needing Spark/Presto - HighTable: Virtual scrolling of millions of rows - Hyparquet-Writer: Export Parquet easily from JS - Hyllama: Read llama.cpp .gguf LLM metadata efficiently CLI for viewing local files: npx hyperparam dataset.parquet Example dataset on Hugging Face Space:…
2025 · hyperparam.app
- 13HP
I built a Rust-powered Wavelet Matrix library for Python. There were surprisingly few practical Wavelet Matrix implementations available for Python, so I implemented one with a focus on performance, usability, and typed APIs. It supports fast rank/select, top-k, quantile, range queries, and even dynamic updates. Feedback welcome!
Dec 2025 · pypi.org
- 14CR
This is an evolving toolkit of capabilities helpful for analysing and reverse engineering legacy Cobol code. Currently, the following capabilities are available: - Program / Section-level flowchart generation based on AST (SVG or PNG) - Parse Tree generation (with export to JSON) - Control Flow Tree generation (with export to JSON) - Allows embedding code comments as comment nodes in the graph - The SMOJOL Interpreter (WIP) - Injecting AST and Control Flow into Neo4J - Injecting Cobol data layouts from Data Division into Neo4J (with dependencies like MOVE, COMPUTE, etc.) + export to…
2024 · github.com
- 15IG
Rerun 0.21 comes with a new graph viewer that's written in Rust and runs in the browser via wasm. It's powered by a new force based layout engine that is a port of much of d3-force to Rust. (The release also contains some other cool stuff like undo/redo implemented on top of a timeseries DB.) We built this with applications in robotics and spatial computing in mind but would love to hear feedback from folks that would see this as useful in other domains as well.
2024 · rerun.io
- 16ML
Just wanted to share with HN a simple/minimal open source Python library that generates SVG files visualizing two dimensional data and distributions, in case others find it useful or interesting. I wrote it as a fun project, mostly because I found that the standard libraries in Python generated unnecessarily large SVG files. One nice property is that I can configure the visuals through CSS, which allows me to support dark/light mode browser settings. The graphs are specified as JSON files (the repository includes a few examples). It supports scatterplots, line plots, histograms,…
Mar 2026 · github.com
- 17
RAG-ready web scraping that cuts your LLM token costs
Apr 2026 · geekflare.com
- 18AT
I recently built a small open-source tool to benchmark different LLM API endpoints — including OpenAI, Claude, and self-hosted models (like llama.cpp). It runs a configurable number of test requests and reports two key metrics: • First-token latency (ms): How long it takes for the first token to appear • Output speed (tokens/sec): Overall output fluency Demo: https://llmapitest.com/ Code: https://github.com/qjr87/llm-api-test The goal is to provide a simple, visual, and reproducible way to evaluate performance across different LLM providers, including…
2025 · llmapitest.com
- 19IC
2024 · github.com
- 20CA
Hey HN, just wanted to share a fun, vibe-coded Friday night experiment: a little playground for writing cellular automata in a subset of Rust, which is then compiled into WGSL. Since it lets you dynamically change parameters while the simulation is running via a TUI, it's easy to discover weird behaviors without remembering how you got there. If you press "s", it will save the complete history to a JSON file (a timeline of the parameters that were changed at given ticks), so you can replay it and regenerate the discovery. You can pan/zoom, and while the main simulation window is in…
Feb 2026 · github.com
- 21PA
Hi HN, I’m experimenting with a small Python library called PicoFlow for building LLM agent workflows using a lightweight DSL. I’ve been using tools like LangChain and CrewAI, and wanted to explore a simpler, more function-oriented way to compose agent logic, closer to normal Python control flow and async functions. PicoFlow focuses on: - composing async functions with operators - minimal core and few concepts to learn - explicit data flow through a shared context - easy embedding into existing services A typical flow looks like: flow = plan >> retrieve >> answer await flow(ctx) Patterns…
Jan 2026
- 22OS
I just published an open-source protein and ligand viewer. Goal: fast and easy-to-use. Long-term: It's a platform for docking and molecular dynamics. The basic functionality for viewing and inspecting work. I'm currently working on Coot-like electron-density viewing. I'm gradually splitting it into standalone libs, published to crates.io. Some are up already, others are integrated, and will be split off when sufficiently mature and decoupled. Uses parallel execution when able, through thread pools (Rayon), CPU SIMD and Cuda. The default control scheme is non-standard, unless you play video…
2025 · github.com
- 23SP
I built Sculptor after repeatedly seeing founders try to hire data scientists for a task that ultimately boiled down to extracting structured data from unstructured text (customer records, social posts, websites, etc) using an LLM API. We ended up reinventing this pattern internally at least three times in the past year, so I published Sculptor as a streamlined, open-source solution: - Simple schema-based extraction, with parallelization and type validation. - Multi-step pipelines with filtering or transforms between steps. - Configure everything in YAML/JSON for easy reuse. It’s MIT…
2025 · github.com
- 24LA
G'day, HN! I'm one of the maintainers of `llm`. I've been working alongside a trusty group of contributors to bring this project to life, and we're now at a point where we're ready to share it with the world. Large language models (LLMs) are taking the computing world by storm due to their emergent abilities that allow them to perform a wide variety of tasks, including translation, summarization, code generation, and even some degree of reasoning. However, the ecosystem around LLMs is still in its infancy, and it can be difficult to get started with these models. `llm` is a one-stop shop for…
2023 · github.com
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