Show HN: TERMy – A fast terminal assistant that does not use LLMs https://ift.tt/IKuSDxg

Show HN: TERMy – A fast terminal assistant that does not use LLMs I love research and development, you may have heard of me because of PJON (Padded Jittering Operative Network). It is a network protocol I started developing in 2010, which was recently implemented in silicon by the ETH Zurich university thanks to the research of Pius Sieber. I am excited to share with you TERMy, a terminal assistant built on top of the NPC-Forge framework. Unlike everything else being built today, TERMy does not use embeddings, machine-learning or LLMs. It runs on the CPU (even on a Raspberry Pi Zero) both in the terminal or client-side in a browser tab and responds in milliseconds. It is a cynical but very knowledgeable Linux terminal assistant that translates your natural language into shell commands without relying on a single artificial neuron. I had a chance to focus for 2 months on my personal projects since early July, during the strange times of AI price hikes and the end of subsidized tokenmaxing. I was curious to see if I could develop from scratch a terminal assistant capable of handling simple natural language requests. I have a bad memory and got used to ask to copilot "activate the virtual environment" or similar trivial operations spending a non negligible sum every month. I started thinking, maybe I can do something to make my workflow more efficient? Do I really need trillions of parameters to accomplish those tasks? How it Works When you type a prompt, it goes through a lightweight NLU pipeline written in ~1000 lines of Python that implement the following steps: 1. Strip expletives, interjections, encouraging, discouraging and thanking words (remove noise) 2. Sentiment analysis 3. Exact Match (very fast) 4. Template Match (slower) 5. Probabilistic Match (even slower) Step 5 relies on: 1. IDF (Inverse Document Frequency) to identify rare words. 2. BOW (Bag Of Words) to accommodate word inversions. 3. IDF weighted Levenshtein to safely handle typos. Permission gating is hardcoded into the dataset and enforced for all potentially destructive commands, so it's inherently safer than letting an unpredictable LLM run wild on your machine. - TERMy in operation: https://www.youtube.com/watch?v=qeIp0xePLBg - Variance and typo tolerance: https://www.youtube.com/watch?v=tQvGDk6fkk0 - Copilot integration: https://www.youtube.com/watch?v=Wzzouhq2a8A - Advanced features: https://www.youtube.com/watch?v=qeIp0xePLBg - Source Code: https://ift.tt/HKc7avw https://ift.tt/IKOyoTD September 4, 2026 at 02:33PM

Show HN: Sirenfall, a civil defense siren synthesized in Web Audio https://ift.tt/30tOjT9

Show HN: Sirenfall, a civil defense siren synthesized in Web Audio I built a cool browser scene, a shelter window over a dystopian city in the rain. Pull the breaker and a siren tower spins up. The wind-down is super unsettling and I love it. The siren is not a recording. Two port rings make a 5:6 dual tone, 515 and 618 Hz. The horn turns at 4 RPM and everything (loudness, brightness, doppler and stereo position) follows the horn angle you can see on the tower. Rain and thunder are the only recordings. Build it yourself, source is one HTML file and MIT: https://ift.tt/MhteJyV How it works: https://sirenfall.live/how-it-works Press F for fullscreen, S to save a picture. Landscape on phones. No cookies, no personal data, the only request besides audio is an anonymous page-count pixel. Appreciate any feedback and shoutout to the siren community! https://sirenfall.live/ September 4, 2026 at 02:14AM

Show HN: NGPDFs – 50 PDF tools that never upload your files https://ift.tt/286Rdg1

Show HN: NGPDFs – 50 PDF tools that never upload your files https://ngpdfs.com September 3, 2026 at 11:13PM

Show HN: Arbitale – emergent choose your own adventure game https://ift.tt/Y3R5KGX

Show HN: Arbitale – emergent choose your own adventure game Hi everyone! I am building Arbitale and it is currently in pre-alpha. I'm looking for play-testers who can give feedback on the product. The goal is to eventually have different characters in the game be their own agents, with emergent narratives that are totally unique to each playthrough. Each agent acts according to its own pre-written incentives. Would love to hear what you think! https://ift.tt/8FjTDQY September 3, 2026 at 12:12AM

Show HN: SufferTrails, the Anti-AllTrails https://ift.tt/ArtsGgO

Show HN: SufferTrails, the Anti-AllTrails Don't get me wrong. I love a good family-friendly hike as much as anyone else. But sometimes you want to be grimacing, not smiling, on the trail. SufferTrails is that, and not much else. All trails not allowed. https://ift.tt/Uyhe2Em September 2, 2026 at 11:27PM

Show HN: AQ – A multiplayer workspace for coding agents on your own cloud https://ift.tt/mbFW5tC

Show HN: AQ – A multiplayer workspace for coding agents on your own cloud https://aq.dev/ September 2, 2026 at 11:16PM

Show HN: Newton's Orchard – Browser-based space/gravity playground https://ift.tt/mlkdS1M

Show HN: Newton's Orchard – Browser-based space/gravity playground Hi HN! My son spent a lot of time in 5th grade playing with the 2-dimensional PhET gravity/space sims[1]. His STEM class uses it, and he was playing with it at home, and has been looking for more. I found several space sims/playgrounds online, including NASA's Eyes on the Solar System[2], but nothing that seemed to offer a real progression from what he was getting out of the PhET sims, so I built Newton's Orchard over the summer for him. https://ift.tt/g0LIwiT The source is also published at https://ift.tt/SiPt07a It features deterministic time scrubbing, all bodies are editable, different preset systems and experiments, missions to complete (complete 3 to unlock the blackhole object type and mission), and a gallery for user submissions. I would very much appreciate feedback from HN - particularly from the lens of making it engaging and illuminating for students, and anyone that would like to just get a feel for how gravity works. Thank you! [1] https://ift.tt/WSpqDP2... [2] https://ift.tt/I4lrZqR https://ift.tt/g0LIwiT September 1, 2026 at 10:13PM