Show HN: Open-Source Pull Request AI Reviewer https://ift.tt/xhb5Ayk

Show HN: Open-Source Pull Request AI Reviewer Hey HN, Over the last year, I’ve reviewed more than 1000 code changes. Most of the time was spent catching obvious mistakes rather than debating complex design decisions. If we estimate ~10 minutes per review, that’s 160+ hours spent reviewing code in just one year. So I thought: could I get some of that time back using LLMs? That's why I spent the last few weekends building Presubmit.ai, an open-source AI reviewer that runs as a Github Action right when you open a Pull Request. The results so far are promising: I estimate it can reduce the review time by 50%, which in my case would mean I save 80hours (~10 working days) per year. Unlike similar SaaS solutions, the goal is not to replace the human reviewer but to highlight obvious mistakes early, spot security vulnerabilities and give more context about the change. I like to think of it as a “pre-reviewer”. Some of its features are: * Line-by-line comments * PR summarization * Title generation on request * Responds to review comments It supports all major LLMs, but I’ve found Anthropic's Claude works best for this use case. Please give it a try and share your feedback! https://ift.tt/vNMh8Ug https://ift.tt/vNMh8Ug November 22, 2024 at 08:28PM

Show HN: Pull Request Reviewed by LLM https://ift.tt/5lv07eP

Show HN: Pull Request Reviewed by LLM This year I’ve reviewed more than 1000 code changes. Most of the time was spent catching obvious mistakes rather than debating complex design decisions. If we estimate ~10 minutes per review, that’s 160+ hours spent reviewing code in just one year. So I thought: could I get some of that time back using LLMs? That's why I spent the last few weekends building an LLM-based prereviewer that should take a first pass before the actual human reviewer. The results so far are promising: I estimate it can reduce the review time by 50%, which in my case would mean I save 80hours (~10 working days) per year. Linked above is an example of a PR where I'm testing the AI reviewer and it showcase how it can detect bugs, suggest best practices about token validity, generate summary and title, and even chat with me in review comments. The AI reviewer is a simple Github action that runs everytime I open or synchronize a pull request and you can see the source code at https://ift.tt/vNMh8Ug . https://ift.tt/cS2bKkM November 22, 2024 at 11:29PM

Show HN: I made a free business name generator that allows easy export https://ift.tt/uhQdIEN

Show HN: I made a free business name generator that allows easy export I made a free business name generator where users can: - Generate business ideas - Copy all the ideas at once - Export ideas in CSV and PDF Please give it a try and let me know :) https://ift.tt/7JjAZLX November 22, 2024 at 01:50AM

Show HN: VS Code extensions that display CGM blood glucose levels in status bar https://ift.tt/9yaw3rd

Show HN: VS Code extensions that display CGM blood glucose levels in status bar As a Type 1 diabetic, I need to continuously monitor my blood glucose levels. I’ve implemented a couple of Visual Studio Code extensions that retrieve the latest blood glucose readings from your CGM and display them in your VS Code status bar. One VS code extension uses the Nightscout CGM to retrieve the blood glucose readings. It requires users to run the Nightscout application on a hosted server. A nice benefit of Nightscout application is that it works with all the major CGM devices. However, a slight drawback of this option is that it requires a hosted third party software (Nightscout) for proper functionality. I’ve also implemented a Visual Studio code extension for those (like myself) that use the Freestyle Libre CGM. This version connects directly to LibreLinkUp to retrieve the latest blood glucose readings and display them in your VS code status bar. This removes the dependency for the intermediary Nightscout application. If you are or know any software engineers living with diabetes, these tools might be helpful with diabetes management. These are tools I built for myself that help me manage my diabetes. They are completely free and open source. I am not selling anything. Users of the tools can use them without any restrictions or connection to me. I am genuinely trying to help others in the community that are software engineers and might find this helpful. If you try out any of these extensions, I’d love to hear back from you. Any feedback on improvements are very welcome and appreciated. - https://ift.tt/t3AqbBZ... - https://ift.tt/IVmTXiM... November 22, 2024 at 12:19AM

Show HN: My Remote Teaching Station (Mk IV) https://ift.tt/lwjbJes

Show HN: My Remote Teaching Station (Mk IV) The remote teaching station has been evolving for the last four years. The Mk IV is the most advanced and most attractive version so far. https://ift.tt/C8nblm7 November 21, 2024 at 10:07PM

Show HN: Self-Host Next.js in Production https://ift.tt/8Nl97qp

Show HN: Self-Host Next.js in Production https://ift.tt/PDnhpqE November 21, 2024 at 03:37AM

Show HN: Autotab – Programmable AI browser for turning web tasks into APIs https://ift.tt/0mJye2M

Show HN: Autotab – Programmable AI browser for turning web tasks into APIs Hey HN, we're Alexi and Jonas the co-founders of Autotab ( https://autotab.com ). Autotab is a chrome-based browser you can teach to do complex tasks, with a simple API for running them from your app or backend. Here is a walkthrough of how it works: https://youtu.be/63co74JHy1k , and you can try it for free at https://autotab.com by downloading the app. Why a dedicated editor? The number one blocker we've found in building more flexible, agentic automations is performance quality BY FAR ( https://ift.tt/z61iD7R... ). For all the talk of cost, latency, and safety, the fact is most people are still just struggling to get agents to work. The keys to solving reliability are better models, yes, but also intent specification. Even humans don't zero-shot these tasks from a prompt. They need to be shown how to perform them, and then refined with question-asking + feedback over time. It is also quite difficult to formulate complete requirements on the spot from memory. The editor makes it easy to build the specification up as you step through your workflow, while generating successful task trajectories for the model. This is the only way we've been able to get the reliability we need for production use cases. But why build a browser? Autotab started as a Chrome extension (with a Show HN post! https://ift.tt/iyrKI7p ). As we iterated with users, we realized that we needed to focus on creating the control surface for intent specification, and that being stuck in a chrome sidepanel wasn't going to work. We also knew that we needed a level of control for the model that we couldn't get without owning the browser. In Autotab, the browser becomes a canvas on which the user and the model are taking turns showing and explaining the task. Key features: 1. Self-healing automations that don't break when sites change 2. Dedicated authoring tool that builds memory for the model while defining steps for the automation 3. Control flows and deep configurability to keep automations on track, even when navigating complex reasoning tasks 4. Works with any website (no site-specific APIs needed) 5. Runs securely in the cloud or locally 6. Simple REST API + client libraries for Python, Node We'd love to get any early feedback from the HN community, ideas for where you'd like the product to go, or experiences in this space. We will be in the comments for the next few hours to respond! November 21, 2024 at 01:52AM