The best Hacker News stories from Show from the past day
Latest posts:
Show HN: Image Upscaler AI
Show HN: Image Upscaler AI
Show HN: Image Upscaler AI
Show HN: Image Upscaler AI
Show HN: Image Upscaler AI
Show HN: Kysely, a type-safe SQL query builder for TypeScript
Show HN: Kysely, a type-safe SQL query builder for TypeScript
Show HN: gpt-engineer – platform for devs to tinker with AI programming tools
Hello Hacker News community,<p>Wanted to share a project I started working on during my spare time and was then discovered by many in the open source community last week.<p>GPT Engineer’s mission:
Be the open platform for devs to tinker with and build their personal code-generation toolbox.<p>I believe it's key for us devs to engage in how building software can and will change.<p>You can find more info about the flexible technical "philosophy" to make it work well, and the community we want it to become on github:
https://github.com/AntonOsika/gpt-engineer<p>The project is still in early stages. It's clear that there is a lot of room for improvement as the space to combine tricks that guide LLM's is large.<p>Appreciate any suggestions, experiences, or ideas on the project from you all!
Show HN: gpt-engineer – platform for devs to tinker with AI programming tools
Hello Hacker News community,<p>Wanted to share a project I started working on during my spare time and was then discovered by many in the open source community last week.<p>GPT Engineer’s mission:
Be the open platform for devs to tinker with and build their personal code-generation toolbox.<p>I believe it's key for us devs to engage in how building software can and will change.<p>You can find more info about the flexible technical "philosophy" to make it work well, and the community we want it to become on github:
https://github.com/AntonOsika/gpt-engineer<p>The project is still in early stages. It's clear that there is a lot of room for improvement as the space to combine tricks that guide LLM's is large.<p>Appreciate any suggestions, experiences, or ideas on the project from you all!
Show HN: gpt-engineer – platform for devs to tinker with AI programming tools
Hello Hacker News community,<p>Wanted to share a project I started working on during my spare time and was then discovered by many in the open source community last week.<p>GPT Engineer’s mission:
Be the open platform for devs to tinker with and build their personal code-generation toolbox.<p>I believe it's key for us devs to engage in how building software can and will change.<p>You can find more info about the flexible technical "philosophy" to make it work well, and the community we want it to become on github:
https://github.com/AntonOsika/gpt-engineer<p>The project is still in early stages. It's clear that there is a lot of room for improvement as the space to combine tricks that guide LLM's is large.<p>Appreciate any suggestions, experiences, or ideas on the project from you all!
Show HN: I created Units Converter that contains 5000 units across 78 categories
I have been working on my project for the last one year and developed around 600+ tools. The units converter covers almost every possible unit and I am planning to add more to it.
Show HN: I created Units Converter that contains 5000 units across 78 categories
I have been working on my project for the last one year and developed around 600+ tools. The units converter covers almost every possible unit and I am planning to add more to it.
Show HN: I created Units Converter that contains 5000 units across 78 categories
I have been working on my project for the last one year and developed around 600+ tools. The units converter covers almost every possible unit and I am planning to add more to it.
Show HN: I created Units Converter that contains 5000 units across 78 categories
I have been working on my project for the last one year and developed around 600+ tools. The units converter covers almost every possible unit and I am planning to add more to it.
Show HN: Global Pomodoro every 30 minutes
I love using the Pomodoro technique with my friends. We each share what we want to accomplish in 25 minutes, work together, and then take a 5-minute break to discuss our progress.<p>Recently, I had an idea to take this concept to the next level. If you think about it, 25 + 5 = 30 minutes - the perfect amount of time for a global Pomodoro session to start every half hour.<p>After several evenings of brainstorming and collaboration, I'm excited to introduce Pomodorr.io. This platform allows individuals from around the world to come together and work on their projects during these global Pomodoro sessions.<p>So, meet Pomodorr.io. Every 30 minutes, a global pomodoro kicks off in the world. There is a general chat to feel the shoulder of remote colleagues in terms of efficiency. You can meet me and my friends there almost every day.
Show HN: Lissom.CSS - A classless, minimalist, and themeable CSS library
This is a personal take on making a classless semantic CSS library.
Show HN: Inngest – Developer platform for background jobs and workflows
Hi HN! We’re Dan and Tony - founders of Inngest (<a href="https://www.inngest.com/" rel="nofollow noreferrer">https://www.inngest.com/</a>). Inngest is a developer platform and toolchain for developing, testing and running background jobs, and workflows. Inngest invokes your jobs via HTTP, wherever you want to deploy your code.<p>Shipping reliable background jobs and workflows is a time suck for any software team. They’re painful to develop locally and getting into production is a tedious experience of configuring infra. When you want to add scheduling, orchestrate multi-step workflows or handle concurrency or idempotency, you spend even more time building bespoke systems - not your actual product.<p>Software engineers spend a ton of duplicated effort building and rebuilding this at every company. It shouldn’t be this way.<p>We’ve taken our experience building and scaling reliable, secure queueing systems across Healthcare, B2B SaaS, and developer infra companies. With Inngest, we sought out to create a single platform and set of developer tools to unburden the developer.<p>- You write functions alongside your API, in your existing codebase with our simple SDK. We invoke your functions via HTTPS, so there are no additional worker services to setup.<p>- End-to-end local development, with one command. Our dev server runs Inngest on any machine with a web interface to visualize, debug, and test your functions with zero additional dependencies.<p>- Our serverless queue calls you, so you can run your code anywhere - serverless, servers or edge.<p>- Inngest manages state across functions and long-running workflows for you. We handle retries, concurrency, idempotency, and coordinating parallel and sequential workloads out-of-the-box.<p>We’ve helped users like:<p>- Snaplet.dev uses Inngest to handle the lifecycle of managing preview databases for their developer platform.<p>- Ocoya.com re-build their e-commerce and social media scheduling workflows in days while dramatically simplifying their infra to run solely with Inngest + serverless functions.<p>- Secta.ai uses Inngest to run all of their AI image generation models on GPU-optimized instances.<p>Today, we have a TypeScript SDK and we will expand to other languages soon (Go is next). We’re building in the open on Github and we offer usage-based plans with a generous free tier.<p>We’re excited to share this with HN and we’re eager for your feedback! What are your experiences building systems for background jobs and workflows?
Show HN: Inngest – Developer platform for background jobs and workflows
Hi HN! We’re Dan and Tony - founders of Inngest (<a href="https://www.inngest.com/" rel="nofollow noreferrer">https://www.inngest.com/</a>). Inngest is a developer platform and toolchain for developing, testing and running background jobs, and workflows. Inngest invokes your jobs via HTTP, wherever you want to deploy your code.<p>Shipping reliable background jobs and workflows is a time suck for any software team. They’re painful to develop locally and getting into production is a tedious experience of configuring infra. When you want to add scheduling, orchestrate multi-step workflows or handle concurrency or idempotency, you spend even more time building bespoke systems - not your actual product.<p>Software engineers spend a ton of duplicated effort building and rebuilding this at every company. It shouldn’t be this way.<p>We’ve taken our experience building and scaling reliable, secure queueing systems across Healthcare, B2B SaaS, and developer infra companies. With Inngest, we sought out to create a single platform and set of developer tools to unburden the developer.<p>- You write functions alongside your API, in your existing codebase with our simple SDK. We invoke your functions via HTTPS, so there are no additional worker services to setup.<p>- End-to-end local development, with one command. Our dev server runs Inngest on any machine with a web interface to visualize, debug, and test your functions with zero additional dependencies.<p>- Our serverless queue calls you, so you can run your code anywhere - serverless, servers or edge.<p>- Inngest manages state across functions and long-running workflows for you. We handle retries, concurrency, idempotency, and coordinating parallel and sequential workloads out-of-the-box.<p>We’ve helped users like:<p>- Snaplet.dev uses Inngest to handle the lifecycle of managing preview databases for their developer platform.<p>- Ocoya.com re-build their e-commerce and social media scheduling workflows in days while dramatically simplifying their infra to run solely with Inngest + serverless functions.<p>- Secta.ai uses Inngest to run all of their AI image generation models on GPU-optimized instances.<p>Today, we have a TypeScript SDK and we will expand to other languages soon (Go is next). We’re building in the open on Github and we offer usage-based plans with a generous free tier.<p>We’re excited to share this with HN and we’re eager for your feedback! What are your experiences building systems for background jobs and workflows?
Show HN: Autolabel, a Python library to label and enrich text data with LLMs
Hi HN! I'm excited to share Autolabel, an open-source Python library to label and enrich text datasets with any Large Language Model (LLM) of your choice.<p>We built Autolabel because access to clean, labeled data is a huge bottleneck for most ML/data science teams. The most capable LLMs are able to label data with high accuracy, and at a fraction of the cost and time compared to manual labeling. With Autolabel, you can leverage LLMs to label any text dataset with <5 lines of code.<p>We’re eager for your feedback!
Show HN: Autolabel, a Python library to label and enrich text data with LLMs
Hi HN! I'm excited to share Autolabel, an open-source Python library to label and enrich text datasets with any Large Language Model (LLM) of your choice.<p>We built Autolabel because access to clean, labeled data is a huge bottleneck for most ML/data science teams. The most capable LLMs are able to label data with high accuracy, and at a fraction of the cost and time compared to manual labeling. With Autolabel, you can leverage LLMs to label any text dataset with <5 lines of code.<p>We’re eager for your feedback!