Show HN: Kando – A cross-platform pie menu for your desktop
47 by schneegans | 15 comments on Hacker News. Kando is a cross-platform open source pie menu which I am currently developing! It offers an unconventional, fast, highly efficient, and fun way of interacting with your computer! You can use it to launch applications, simulate keyboard shortcuts, open files, and much more. Let me know what you think about it!
Manchester United manager Ruben Amorim questions the "choices" of people close to forward Marcus Rashford after he said he was ready for a "new challenge".
Ange Postecoglou accuses Match of the Day's Steve Wilson of discounting the impact of Tottenham's defensive injuries after their 6-3 defeat by Liverpool.
Show HN: Gentrace – connect to your LLM app code and run/eval it from a UI
10 by dsaffy | 0 comments on Hacker News. Hey HN - Doug from Gentrace here. We originally launched via Show HN in August of 2023 as evaluation and observability for generative AI: https://ift.tt/5KnQNxi Since then, everyone from the model providers to LLM ops companies built a prompt playground. We had one too, until we realized this was totally the wrong approach: - It's not connected to your application code - They don't support all models - You have to rebuild evals for just this one prompt (can't use your end-to-end evals) In other words, it was a ton of work and time to use these to actually make your app better. So, we built a new experience and are relaunching around this idea: Gentrace is a collaborative LLM app testing and experimentation platform that brings together engineers, PMs, subject matter experts, and more to run and test your actual end-to-end app. To do this, use our SDK to: - connect your app to Gentrace as a live runner over websocket (local) / via webhook (staging, prod) - wrap your parameters (eg prompt, model, top-k) so they become tunable knobs in the front end - edit the parameters and then run / evaluate the actual app code with datasets and evals in Gentrace We think it's great for tuning retrieval systems, upgrading models, and iterating on prompts. It's free to trial. Would love to hear your feedback / what you think!
Northampton Saints kick-start their Investec Champions Cup campaign with a comfortable bonus-point victory over Castres at a blustery Franklin's Gardens.
Red Bull’s Max Verstappen wins a dramatic Qatar Grand Prix that was brought to life by two mid-race safety cars and a penalty for McLaren’s Lando Norris.
Show HN: Vicinity – Fast, Lightweight Nearest Neighbors with Flexible Back Ends
9 by Pringled | 0 comments on Hacker News. We’ve just open-sourced Vicinity, a lightweight approximate nearest neighbors (ANN) search package that allows for fast experimentation and comparison of a larger number of well known algorithms. Main features: - Lightweight: the base package only uses Numpy - Unified interface: use any of the supported algorithms and backends with a single interface: HNSW, Annoy, FAISS, and many more algorithms and libraries are supported - Easy evaluation: evaluate the performance of your backend with a simple function to measure queries per second vs recall - Serialization: save and load your index for persistence After working with a large number of ANN libraries over the years, we found it increasingly cumbersome to learn the interface, features, quirks, and limitations of every library. After writing custom evaluation code to measure the speed and performance for the 100th time to compare libraries, we decided to build this as a way to easily use a large number of algorithms and libraries with a unified, simple interface that allows for quick comparison and evaluation. We are curious to hear your feedback! Are there any algorithms that are missing that you use? Any extra evaluation metrics that are useful?