The best Hacker News stories from Show from the past day
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Show HN: Nango – Open unified API for product integrations
Today customers expect every SaaS product to integrate with the other tools they use. Nango is a tool for engineers at SaaS companies to help them ship integrations fast, without compromising on the integration’s depth and quality. It supports more than 100 APIs out of the box.<p>Other integration companies have focused on building a lot of pre-built integrations. These are fast to ship and low maintenance, but they limit how deeply you can integrate with the external APIs.<p>We take a different approach: we make it easier for developers to build and maintain product integrations in code. This lets you create exactly the integration your customers need without compromising on speed and maintainability, and without having to build complex infrastructure (OAuth, retries, rate-limit handling, change detection, monitoring & logging, alerting, etc.).<p>Our platform has two layers: (1) An API-agnostic infrastructure built with Temporal and Postgres, and (2) lambda function-like integrations written in typescript by any developer.<p>Integrations are rarely more than 50 lines of code (here is an example: <a href="https://bit.ly/nango-example" rel="nofollow noreferrer">https://bit.ly/nango-example</a>), thanks to the developer tooling we’ve built in: authentication, pagination, retries, change detection, rate-limit handling, monitoring, Slack alerts, etc.<p>We have pre-built integration templates you can clone and extend—or you can build entirely custom integrations. Your integrations live in your repo and are tested and deployed to Nango with a CLI.<p>In your product, you use a single API to interact with all your integrations. This lets you easily grow the available integrations with minimal code changes in your product.<p>As a community-driven project, anybody can contribute integration templates and APIs to the platform. In fact, more than 30% of the APIs we support today have been contributed by our community.<p>Nango grew out of a “universal OAuth” project called Pizzly and powers the integrations of 100+ SaaS products today. We have an active community of 800+ developers (<a href="https://nango.dev/slack">https://nango.dev/slack</a>).<p>All auth-related features are free forever, and we monetize with sync-related features. The entire code base and all integrations are source-available: <a href="https://github.com/NangoHQ/nango">https://github.com/NangoHQ/nango</a>.<p>We hope Nango can help connect all SaaS products together and look forward to your feedback!
Show HN: Nango – Open unified API for product integrations
Today customers expect every SaaS product to integrate with the other tools they use. Nango is a tool for engineers at SaaS companies to help them ship integrations fast, without compromising on the integration’s depth and quality. It supports more than 100 APIs out of the box.<p>Other integration companies have focused on building a lot of pre-built integrations. These are fast to ship and low maintenance, but they limit how deeply you can integrate with the external APIs.<p>We take a different approach: we make it easier for developers to build and maintain product integrations in code. This lets you create exactly the integration your customers need without compromising on speed and maintainability, and without having to build complex infrastructure (OAuth, retries, rate-limit handling, change detection, monitoring & logging, alerting, etc.).<p>Our platform has two layers: (1) An API-agnostic infrastructure built with Temporal and Postgres, and (2) lambda function-like integrations written in typescript by any developer.<p>Integrations are rarely more than 50 lines of code (here is an example: <a href="https://bit.ly/nango-example" rel="nofollow noreferrer">https://bit.ly/nango-example</a>), thanks to the developer tooling we’ve built in: authentication, pagination, retries, change detection, rate-limit handling, monitoring, Slack alerts, etc.<p>We have pre-built integration templates you can clone and extend—or you can build entirely custom integrations. Your integrations live in your repo and are tested and deployed to Nango with a CLI.<p>In your product, you use a single API to interact with all your integrations. This lets you easily grow the available integrations with minimal code changes in your product.<p>As a community-driven project, anybody can contribute integration templates and APIs to the platform. In fact, more than 30% of the APIs we support today have been contributed by our community.<p>Nango grew out of a “universal OAuth” project called Pizzly and powers the integrations of 100+ SaaS products today. We have an active community of 800+ developers (<a href="https://nango.dev/slack">https://nango.dev/slack</a>).<p>All auth-related features are free forever, and we monetize with sync-related features. The entire code base and all integrations are source-available: <a href="https://github.com/NangoHQ/nango">https://github.com/NangoHQ/nango</a>.<p>We hope Nango can help connect all SaaS products together and look forward to your feedback!
Show HN: QBasic 4.5 on Android
My father, who hung up his coding hat in the '80s, recently entered the golden years of retirement.<p>One day, he mused about the simplicity and educational value of BASIC and wondered if there was a way to share its charm using today's technology.<p>Specifically, he was looking for an Android application that could run BASIC so he could "teach programming while drinking coffee with [his] friends".<p>Thus, BabaBASIC was born—a hat tip to 'Babá', the Greek term for "dad", and a reminder of who sparked this journey.<p>The first iteration of this was made over a 10-hour all-nighter using existing open-source libraries.<p>I ended up forking the BASIC-like implementation to make it more byte-for-byte compatible with QBasic 4.5, which is what my father used back in the 90s to teach me programming.<p>This is the first thing I have ever made of which he approves.
Show HN: QBasic 4.5 on Android
My father, who hung up his coding hat in the '80s, recently entered the golden years of retirement.<p>One day, he mused about the simplicity and educational value of BASIC and wondered if there was a way to share its charm using today's technology.<p>Specifically, he was looking for an Android application that could run BASIC so he could "teach programming while drinking coffee with [his] friends".<p>Thus, BabaBASIC was born—a hat tip to 'Babá', the Greek term for "dad", and a reminder of who sparked this journey.<p>The first iteration of this was made over a 10-hour all-nighter using existing open-source libraries.<p>I ended up forking the BASIC-like implementation to make it more byte-for-byte compatible with QBasic 4.5, which is what my father used back in the 90s to teach me programming.<p>This is the first thing I have ever made of which he approves.
Show HN: QBasic 4.5 on Android
My father, who hung up his coding hat in the '80s, recently entered the golden years of retirement.<p>One day, he mused about the simplicity and educational value of BASIC and wondered if there was a way to share its charm using today's technology.<p>Specifically, he was looking for an Android application that could run BASIC so he could "teach programming while drinking coffee with [his] friends".<p>Thus, BabaBASIC was born—a hat tip to 'Babá', the Greek term for "dad", and a reminder of who sparked this journey.<p>The first iteration of this was made over a 10-hour all-nighter using existing open-source libraries.<p>I ended up forking the BASIC-like implementation to make it more byte-for-byte compatible with QBasic 4.5, which is what my father used back in the 90s to teach me programming.<p>This is the first thing I have ever made of which he approves.
Show HN: Modeling Berlin subway lines in graph database
Show HN: Javaflame – Simple Flamegraph for your Java application
Javaflame will generate a flamegraph of your application function calls, including the argument values and the return of each function.<p>Check <a href="https://beothorn.github.io/javaflame" rel="nofollow noreferrer">https://beothorn.github.io/javaflame</a> to see an example.<p>There are already some tools that render flamegraphs for java, but they are focused on measuring performance or require some other process running along with the application. They also record function calls, but do not record the arguments or return values from those functions.<p>I needed instead something to help understand and debug my applications that was better than adding breakpoints and slowly step over every call.<p>This is a simple java agent that renders a flamegraph on a html file, no extra dependencies or other processes involved. All you need is an extra argument passed to the JVM on the command line pointing to the java agent.<p>It calls toString on every parameter and return value of every function that is included on the filter, so I wouldn't use this outside your dev machine.
Show HN: Bulletpapers – ArXiv AI paper summarizer, won Anthropic Hackathon
Show HN: Bulletpapers – ArXiv AI paper summarizer, won Anthropic Hackathon
Show HN: Bulletpapers – ArXiv AI paper summarizer, won Anthropic Hackathon
Show HN: Unreal Engine 4 WASM space game
Note that the demo may take up to 30 seconds to load, and initially present a white screen. I can assure you - it's worth the wait!
Show HN: Unreal Engine 4 WASM space game
Note that the demo may take up to 30 seconds to load, and initially present a white screen. I can assure you - it's worth the wait!
Show HN: Roboco-op, a computational blackboard for efficient human/AI collab
Show HN: Roboco-op, a computational blackboard for efficient human/AI collab
Show HN: Roboco-op, a computational blackboard for efficient human/AI collab
Show HN: Patterns – Habit Tracker App
Hi everyone<p>I'm a Notion-addicted person and love to build my own template to cover different aspects of my life, either work or personal stuff. Once, I wanted to build a habit tracker template, and I realized Notion was not the best solution. You can organize it in a much more efficient way just with a pen and a piece of paper. However, the best tool should live on your devices and have a correct structure. Then, I decided to try to build an app using SwiftUI and SwiftData.<p>The goal was to make it a very basic version in one month. But it took me two months. I tried to add only the core features for MVP and see if it works for others. On Twitter, it already received some love, and I'm very excited to share the app here to get even more feedback.<p>Let me know what you think
Show HN: Scorecard.gg – minimalist scoring tool for your favorite board games
Show HN: Scorecard.gg – minimalist scoring tool for your favorite board games
Show HN: Scorecard.gg – minimalist scoring tool for your favorite board games
Show HN: Open-source model and scorecard for measuring hallucinations in LLMs
Hi all! This morning, we released a new Apache 2.0 licensed model on HuggingFace for detecting hallucinations in retrieval augmented generation (RAG) systems.<p>What we've found is that even when given a "simple" instruction like "summarize the following news article," every LLM that's available hallucinates to some extent, making up details that never existed in the source article -- and some of them quite a bit. As a RAG provider and proponents of ethical AI, we want to see LLMs get better at this. We've published an open source model, a blog more thoroughly describing our methodology (and some specific examples of these summarization hallucinations), and a GitHub repository containing our evaluation from the most popular generative LLMs available today. Links to all of them are referenced in the blog here, but for the technical audience here, the most interesting additional links might be:<p>- <a href="https://huggingface.co/vectara/hallucination_evaluation_model" rel="nofollow noreferrer">https://huggingface.co/vectara/hallucination_evaluation_mode...</a><p>- <a href="https://github.com/vectara/hallucination-leaderboard">https://github.com/vectara/hallucination-leaderboard</a><p>We hope that releasing these under a truly open source license and detailing the methodology, we hope to increase the viability of anyone really quantitatively measuring and improving the generative LLMs they're publishing.