A robust, open-source framework for Spiking Neural Networks on low-end FPGAs

Show HN: Simple modenized .NET NuGet server reached RC

Show HN: Simple modenized .NET NuGet server reached RC A simple .NET NuGet server implementation built on Node.js that provides essential NuGet v3 API endpoints.Key Features:* Easy setup, run NuGet server in 10 seconds! * NuGet V3 API compatibility: Support for modern NuGet client operations * No need database management: Store package file and nuspecs into filesystem directly, feel free any database managements * Package publish: Flexible client to upload .nupkg files via HTTP POST using cURL and others * Basic authentication: Setup authentication for publish and general access when you want it * Reverse proxy support: Configurable trusted reverse proxy handling for proper URL resolution * Modern Web UI with enhanced features. * Package importer: Included package importer from existing NuGet server * Docker image available

Show HN: I Built a XSLT Blog Framework

Show HN: I Built a XSLT Blog Framework A few weeks ago a friend sent me grug-brain XSLT (1) which inspired me to redo my personal blog in XSLT.Rather than just build my own blog on it, I wrote it up for others to use and I've published it on GitHub <a href="https://github.com/vgr-land/vgr-xslt-blog-framework" rel="nofollow">https://github.com/vgr-land/vgr-xslt-blog-framework</a> (2)Since others have XSLT on the mind, now seems just as good of a time as any to share it with the world. Evidlo@ did a fine job explaining the "how" xslt works (3)The short version on how to publish using this framework is:1. Create a new post in HTML wrapped in the XML headers and footers the framework expects.2. Tag the post so that its unique and the framework can find it on build3. Add the post to the posts.xml fileAnd that's it. No build system to update menus, no RSS file to update (posts.xml is the rss file). As a reusable framework, there are likely bugs lurking in CSS, but otherwise I'm finding it perfectly usable for my needs.Finally, it'd be a shame if XSLT is removed from the HTML spec (4), I've found it quite eloquent in its simplicity.(1) <a href="https://news.ycombinator.com/item?id=44393817">https://news.ycombinator.com/item?id=44393817</a>(2) <a href="https://github.com/vgr-land/vgr-xslt-blog-framework" rel="nofollow">https://github.com/vgr-land/vgr-xslt-blog-framework</a>(3) <a href="https://news.ycombinator.com/item?id=44988271">https://news.ycombinator.com/item?id=44988271</a>(4) <a href="https://news.ycombinator.com/item?id=44952185">https://news.ycombinator.com/item?id=44952185</a>(Aside - First time caller long time listener to hn, thanks!)

Ergonomic errors in Rust: write fast, debug with ease, handle precisely

ResurrectedGod: The Ruby Framework for Process Management

Show HN: TraceRoot – Open-source agentic debugging for distributed services

Show HN: TraceRoot – Open-source agentic debugging for distributed services Hey Xinwei and Zecheng here, we are the authors of TraceRoot (<a href="https://github.com/traceroot-ai/traceroot">https://github.com/traceroot-ai/traceroot</a>).TraceRoot (<a href="https://traceroot.ai">https://traceroot.ai</a>) is an open-source debugging platform that helps engineers fix production issues faster by combining structured traces, logs, source code contexts and discussions in Github PRs, issues and Slack channels, etc. with AI Agents.At the heart are our lightweight Python (<a href="https://github.com/traceroot-ai/traceroot-sdk">https://github.com/traceroot-ai/traceroot-sdk</a>) and TypeScript (<a href="https://github.com/traceroot-ai/traceroot-sdk-ts">https://github.com/traceroot-ai/traceroot-sdk-ts</a>) SDKs - they can hook into your app using OpenTelemetry and captures logs and traces. These are either sent to a local Jaeger (<a href="https://www.jaegertracing.io/" rel="nofollow">https://www.jaegertracing.io/</a>) + SQLite backend or to our cloud backend, where we correlate them into a single view. From there, our custom agent takes over.The agent builds a heterogeneous execution tree that merges spans, logs, and GitHub context into one internal structure. This allows it to model the control and data flow of a request across services. It then uses LLMs to reason over this tree - pruning irrelevant branches, surfacing anomalous spans, and identifying likely root causes. You can ask questions like “what caused this timeout?” or “summarize the errors in these 3 spans”, and it can trace the failure back to a specific commit, summarize the chain of events, or even propose a fix via a draft PR.We also built a debugging UI that ties everything together - you explore traces visually, pick spans of interest, and get AI-assisted insights with full context: logs, timings, metadata, and surrounding code. Unlike most tools, TraceRoot stores long-term debugging history and builds structured context for each company - something we haven’t seen many others do in this space.What’s live today:- Python and TypeScript SDKs for structured logs and traces.- AI summaries, GitHub issue generation, and PR creation.- Debugging UI that ties everything togetherTraceRoot is MIT licensed and easy to self-host (via Docker). We support both local mode (Jaeger + SQLite) and cloud mode. Inspired by OSS projects like PostHog and Supabase - core is free, enterprise features like agent mode multi-tenant and slack integration are paid.If you find it interesting, you can see a demo video here: <a href="https://www.youtube.com/watch?v=nb-D3LM0sJM" rel="nofollow">https://www.youtube.com/watch?v=nb-D3LM0sJM</a>We’d love you to try TraceRoot (<a href="https://traceroot.ai">https://traceroot.ai</a>) and share any feedback. If you're interested, our code is available here: <a href="https://github.com/traceroot-ai/traceroot">https://github.com/traceroot-ai/traceroot</a>. If we don’t have something, let us know and we’d be happy to build it for you. We look forward to your comments!

Show HN: Pontoon – Open-source customer data syncs

Show HN: Pontoon – Open-source customer data syncs Hi HN,We’re Alex and Kalan, the creators of Pontoon (<a href="https://github.com/pontoon-data/Pontoon">https://github.com/pontoon-data/Pontoon</a>). Pontoon is an open-source data export platform that makes it really easy to create data syncs and send data to your enterprise customers. Check out our demo here: <a href="https://app.storylane.io/share/onova7c23ai6">https://app.storylane.io/share/onova7c23ai6</a> or try it out with docker: <a href="https://pontoon-data.github.io/Pontoon/getting-started/quick-start/" rel="nofollow">https://pontoon-data.github.io/Pontoon/getting-started/quick...</a>While at our prior roles as data engineers, we’ve both felt the pain of data APIs. We either had to spend weeks building out data pipelines in house or spend a lot on ETL tools like Fivetran (<a href="https://www.fivetran.com/" rel="nofollow">https://www.fivetran.com/</a>). However, there were a few companies that offered data syncs that would sync directly to our data warehouse (eg. Redshift, Snowflake, etc.), and when that was an option, we always chose it. This led us to wonder “Why don’t more companies offer data syncs?”. It turns out, building reliable cross-cloud data syncs is difficult. That’s why we built Pontoon.We designed Pontoon to be:- Easily deployed: we provide a single, self-contained Docker image for easy deployment and Docker Compose for larger workloads (<a href="https://pontoon-data.github.io/Pontoon/getting-started/quick-start/" rel="nofollow">https://pontoon-data.github.io/Pontoon/getting-started/quick...</a>)- Support modern data warehouses: we support syncing to/from Snowflake, BigQuery, Redshift, and Postgres.- Sync cross cloud: sync from BigQuery to Redshift, Snowflake to BigQuery, Postgres to Redshift, etc.- Developer friendly: data syncs can also be built via the API- Open source: Pontoon is free to use by anyoneUnder the hood, we use Apache Arrow (<a href="https://arrow.apache.org/" rel="nofollow">https://arrow.apache.org/</a>) to move data between sources and destinations. Arrow is very performant - we wanted to use a library that could handle the scale of moving millions of records per minute.In the shorter-term, there are several improvements we want to make, like:- Adding support for DBT models to make adding data models easier- UX improvements like better error messaging and monitoring of data syncs- More sources and destinations (S3, GCS, Databricks, etc.)- Improve the API for a more developer friendly experience (it’s currently tied pretty closely to the front end)In the longer-term, we want to make data sharing as easy as possible. As data engineers, we sometimes felt like second class citizens with how we were told to get the data we needed - “just loop through this api 1000 times”, “you probably won’t get rate limited” (we did), “we can schedule an email to send you a csv every day”. We want to change how modern data sharing is done and make it simple for everyone.Give it a try <a href="https://github.com/pontoon-data/Pontoon">https://github.com/pontoon-data/Pontoon</a>. Cheers!

CAMARA: Open-source API for telecom and 5G networks

Show HN: Easy Python Time Parsing

Show HN: Easy Python Time Parsing I recently build a python time-parser that can parse most formats in a single line. Might be useful to some here. (Also happy to hear feedback and feature requests)

Gitea Private, Fast, Reliable DevOps Platform

Show HN: RULER – Easily apply RL to any agent

Show HN: RULER – Easily apply RL to any agent Hey HN, Kyle here, one of the co-founders of OpenPipe.Reinforcement learning is one of the best techniques for making agents more reliable, and has been widely adopted by frontier labs. However, adoption in the outside community has been slow because it's so hard to implement.One of the biggest challenges when adapting RL to a new task is the need for a task-specific "reward function" (way of measuring success). This is often difficult to define, and requires either high-quality labeled data and/or significant domain expertise to generate.RULER is a drop-in reward function that works across different tasks without any of that complexity.It works by showing N trajectories to an LLM judge and asking it to rank them relative to each other. This sidesteps the calibration issues that plague most LLM-as-judge approaches. Combined with GRPO (which only cares about relative scores within groups), it just works (surprisingly well!).We have a full writeup on the blog, including results on 4 production tasks. On all 4 tasks, small Qwen 2.5 models trained with RULER+GRPO beat the best prompted frontier model, despite being significantly smaller and cheaper to run. Surprisingly, they even beat models trained with hand-crafted reward functions on 3/4 tasks! <a href="https://openpipe.ai/blog/ruler">https://openpipe.ai/blog/ruler</a>Repo: <a href="https://github.com/OpenPipe/ART">https://github.com/OpenPipe/ART</a>

Show HN: Smart Switcher - data driven tool to improve the window switching

Show HN: Smart Switcher - data driven tool to improve the window switching Hello, my name is Andrew. I'm an indie developer and I'm excited to release Smart Switcher for Windows 10/11. I'm looking for feedback on the overall project and the application itself.I built this because I couldn't find a window switching/management solution that worked for me. I tried all kinds of different solutions, virtual desktop extensions, obscure GUI window managers, you name it. Overtime I realized I wanted something that prioritizes one window at a time, is keyboard driven with has minimal if no GUI elements. I figured this part out, but knew something was missing. I had my eureka moment when I realized I could combine my switching method with a prediction algorithm. This led to the creation of Smart Switcher.Smart Switcher is a data driven window switcher aimed at improving the overall window switching experience. It logs data on your windows switching, then a prediction algorithm analyzes this data and uses it to predict which window you would want to switch to next. When you need to switch windows, you press the switch shortcut to switch to the next predicted window. If this isn't the window you wanted, press the override shortcut to switch to the next most likely window. You can press the override shortcut as many times as needed until you arrive at your desired window.It’s a paid app with a demo and trial version. There is a introductory discount and some additional discount tiers for early adopters.Any feedback is appreciated! Thanks!

Show HN: Virby, a vfkit-based Linux builder for Nix-Darwin

Show HN: Virby, a vfkit-based Linux builder for Nix-Darwin Virby is a module for nix-darwin that configures a lightweight linux VM as a remote build machine for nix, allowing linux packages to be built on macOS.