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Show HN: Time Portal – Get dropped into history, guess where you landed

Hi HN! I love imagining the past, so I made Time Portal, a game where you are dropped into a historical event and see AI video footage from that moment. You have to guess where you are in time and on the map. It’s like GeoGuessr (and heavily inspired by it!) but for historical events.<p>The videos are all created with AI. It’s a pipeline of Flux (images), Kling (video), and mmaudio (audio). The videos aren’t always historically accurate to the last detail. They might incorporate elements of folklore or have details from popular beliefs about the way things looked rather than the latest academic research on how they looked.<p>I’m thinking a lot about how to make the game more interactive. One thing that makes Geoguessr so fun for me is that you can move infinitely and always find more details to help you pinpoint the location. I want Time Portal to have a similar quality. I have a few ideas to try soon that will hopefully make the game more interactive and infinite.

Show HN: Time Portal – Get dropped into history, guess where you landed

Hi HN! I love imagining the past, so I made Time Portal, a game where you are dropped into a historical event and see AI video footage from that moment. You have to guess where you are in time and on the map. It’s like GeoGuessr (and heavily inspired by it!) but for historical events.<p>The videos are all created with AI. It’s a pipeline of Flux (images), Kling (video), and mmaudio (audio). The videos aren’t always historically accurate to the last detail. They might incorporate elements of folklore or have details from popular beliefs about the way things looked rather than the latest academic research on how they looked.<p>I’m thinking a lot about how to make the game more interactive. One thing that makes Geoguessr so fun for me is that you can move infinitely and always find more details to help you pinpoint the location. I want Time Portal to have a similar quality. I have a few ideas to try soon that will hopefully make the game more interactive and infinite.

Show HN: iOS app that corrects your form in real time using your phone's camera

My friends and I made an app that uses your phone's camera to track and improve your form. It'll give you visual and verbal feedback for every rep in real time, ensuring accountability. <a href="https://apps.apple.com/us/app/firefly-fitness/id6464440707">https://apps.apple.com/us/app/firefly-fitness/id6464440707</a> (No, we don’t store or view any camera footage as you're working out.)<p>The challenges and programs are free to try, no sign-ups or subscription required. (We do ask that you sign-up to save your stats). Just swipe down on the paywall. As a heads up, challenges and programs have pre-set strictness, so you’ll need to perform them with proper form.<p>I created a story-based workout where you start in a room, progress through increasingly difficult levels, and earn badges. I wanted to make the workouts more engaging - Solo Leveling and Lord of the Rings were a hard inspiration! Let me know your thoughts!<p>Background<p>We're three friends from Virginia Tech. Starting our journey, we had no idea what to build...until our CTO, who had never worked out before, created a rep-counting app to help himself. That’s when we realized we also forget our rep counts! We looked at other fitness apps and felt they were all the same, just with different designs. You can check out our building process here: <a href="https://www.youtube.com/watch?v=j5CAK40wTwo&t=195s" rel="nofollow">https://www.youtube.com/watch?v=j5CAK40wTwo&t=195s</a><p>But, after talking to a lot of people, we discovered three major issues:<p>1. Proper Form: It's hard to know if you have proper form until someone points it out. You either watch tons of videos, use a mirror/record yourself, or rely on a buddy to check if your form is correct.<p>2. Cost: For beginners who can't afford personal training services or smart gyms, this gives them an alternative option<p>3. Accountability: Our app only counts reps done with proper form using full range of motion (depending on the form strictness level you set).<p>It took a looonngg time...but we finally got the core feature working! We prioritized building a reliable pose tracker that accurately tracks fast movements. (Our old versions lagged in its detection, making the feedback triggers unreliable...cause you'd want to hear the feedback as soon as possible). Because of this, we were able to create our own exercise library, allowing us to control when and where to trigger feedback for form mistakes like 'Go Down lower' or 'Raise Your Right Arm Higher'. Also, form strictness adjuster and workout customization are a premium feature. But the challenges and programs are free.<p>Please exercise safely and would appreciate feedback! Hope to help a lot more people, please let us know what helped you start your fitness journey! Thank you!

Show HN: Krep a High-Performance String Search Utility Written in C

Show HN: Krep a High-Performance String Search Utility Written in C

Show HN: We built a Plug-in Home Battery for the 99.7% of us without Powerwalls

Hi HN! I’m Cole Ashman, founder of Pila Energy. I’ve spent my career working on home energy systems—first as an engineer on Tesla’s Powerwall, where I focused on the Backup Gateway, Solar Inverter, and metering systems. More recently, I led Product at SPAN, where we built the Smart Electrical Panel and integrated with most major home solar, EV, and battery systems.<p>Pila (<a href="https://pila.energy/" rel="nofollow">https://pila.energy/</a>) is a home battery that plugs into a standard wall outlet, provides smart backup power, energy shifting, and grid services. It’s more than a power bank—it’s a distributed energy system that can scale across multiple rooms, entire buildings, and work together in real time as a coordinated system. We built Pila to be local first with an open API to allow developers to build use cases on top of our hardware (Home Assistant, etc).<p>Big batteries like Tesla Powerwall and Enphase are great if you own a home and can afford a $10K+ electrical project, but they require permanent installation, electricians, and panel upgrades—which makes them inaccessible for renters, apartments, and cost-conscious homeowners. Over 50% of the cost of installing a Powerwall isn’t even the battery itself—it’s soft costs: labor, permitting, etc. We wanted to create an entry point for more people to access energy security at home.<p>How does it work?<p>Plug Pila into any 120V wall outlet, and power passes through to connected devices and appliances. The inverter, LFP battery, BMS, grid disconnection, controller, and wireless connectivity are all built in. (details at <a href="https://pila.energy/tech-specs" rel="nofollow">https://pila.energy/tech-specs</a>)<p>When an outage happens, the onboard inverter detects the power loss within 20ms and automatically disconnects from the grid (islanding). Whether you’re home or away, backup kicks in instantly. A built-in cellular radio ensures you get a notification even if your home WiFi is out. Pila is 1.6kWh. That will backup a standard fridge for over a day.<p>One key challenge we faced with a distributed architecture was coordination between batteries, for things like solar-following and managing real-time draw from your utility connection. Unlike large garage systems, where you can run a wired CAN bus, our batteries are spread across the home. We’re solving this with a sub-GHz wireless mesh network—self-healing, coordinator-less, and designed to make setup and expansion as simple as plugging in another unit.<p>Long-term, we’d love to open up this protocol to provide a more reliable communication layer for energy products in noisy built environments—reducing reliance on consumer Wi-Fi.<p>We want to deliver the value you’d expect from a whole-home battery like Powerwall, in a plug-in format. That means going beyond a basic lead acid UPS with real home energy management, useful insights about power use, power larger loads like sump pumps, and even deliver grid services.<p>Most portable batteries are missing the functionality that makes a home battery useful: no bidirectional power, no integration with solar or smart home systems, and no ability to manage home energy dynamically. They tend to be boxy, ruggedized, meant to be moved around, not seamlessly integrated into your living space. On top of that, many use e-mobility battery chemistries, which are great for delivering high power on demand but wear out faster when cycled daily for home energy use.<p>As a renter myself, I started Pila because these awesome energy products aren’t accessible enough. And frankly, generators are loud, expensive, and a pain to deal with. Even many Powerwall owners I’ve talked to say they really care about keeping the fridge, WiFi, and a sump pump running—so why does energy resilience have to be so complicated and expensive?<p>As the grid struggles to keep up with demand, we believe modular, renter-friendly batteries can make home energy resilience more accessible.<p>What's been your experience with home batteries? What recent power outages have you had, and how were you affected?

Show HN: We built a Plug-in Home Battery for the 99.7% of us without Powerwalls

Hi HN! I’m Cole Ashman, founder of Pila Energy. I’ve spent my career working on home energy systems—first as an engineer on Tesla’s Powerwall, where I focused on the Backup Gateway, Solar Inverter, and metering systems. More recently, I led Product at SPAN, where we built the Smart Electrical Panel and integrated with most major home solar, EV, and battery systems.<p>Pila (<a href="https://pila.energy/" rel="nofollow">https://pila.energy/</a>) is a home battery that plugs into a standard wall outlet, provides smart backup power, energy shifting, and grid services. It’s more than a power bank—it’s a distributed energy system that can scale across multiple rooms, entire buildings, and work together in real time as a coordinated system. We built Pila to be local first with an open API to allow developers to build use cases on top of our hardware (Home Assistant, etc).<p>Big batteries like Tesla Powerwall and Enphase are great if you own a home and can afford a $10K+ electrical project, but they require permanent installation, electricians, and panel upgrades—which makes them inaccessible for renters, apartments, and cost-conscious homeowners. Over 50% of the cost of installing a Powerwall isn’t even the battery itself—it’s soft costs: labor, permitting, etc. We wanted to create an entry point for more people to access energy security at home.<p>How does it work?<p>Plug Pila into any 120V wall outlet, and power passes through to connected devices and appliances. The inverter, LFP battery, BMS, grid disconnection, controller, and wireless connectivity are all built in. (details at <a href="https://pila.energy/tech-specs" rel="nofollow">https://pila.energy/tech-specs</a>)<p>When an outage happens, the onboard inverter detects the power loss within 20ms and automatically disconnects from the grid (islanding). Whether you’re home or away, backup kicks in instantly. A built-in cellular radio ensures you get a notification even if your home WiFi is out. Pila is 1.6kWh. That will backup a standard fridge for over a day.<p>One key challenge we faced with a distributed architecture was coordination between batteries, for things like solar-following and managing real-time draw from your utility connection. Unlike large garage systems, where you can run a wired CAN bus, our batteries are spread across the home. We’re solving this with a sub-GHz wireless mesh network—self-healing, coordinator-less, and designed to make setup and expansion as simple as plugging in another unit.<p>Long-term, we’d love to open up this protocol to provide a more reliable communication layer for energy products in noisy built environments—reducing reliance on consumer Wi-Fi.<p>We want to deliver the value you’d expect from a whole-home battery like Powerwall, in a plug-in format. That means going beyond a basic lead acid UPS with real home energy management, useful insights about power use, power larger loads like sump pumps, and even deliver grid services.<p>Most portable batteries are missing the functionality that makes a home battery useful: no bidirectional power, no integration with solar or smart home systems, and no ability to manage home energy dynamically. They tend to be boxy, ruggedized, meant to be moved around, not seamlessly integrated into your living space. On top of that, many use e-mobility battery chemistries, which are great for delivering high power on demand but wear out faster when cycled daily for home energy use.<p>As a renter myself, I started Pila because these awesome energy products aren’t accessible enough. And frankly, generators are loud, expensive, and a pain to deal with. Even many Powerwall owners I’ve talked to say they really care about keeping the fridge, WiFi, and a sump pump running—so why does energy resilience have to be so complicated and expensive?<p>As the grid struggles to keep up with demand, we believe modular, renter-friendly batteries can make home energy resilience more accessible.<p>What's been your experience with home batteries? What recent power outages have you had, and how were you affected?

Show HN: Factorio Learning Environment – Agents Build Factories

I'm Jack, and I'm excited to share a project that has channeled my Factorio addiction recently: the Factorio Learning Environment (FLE).<p>FLE is an open-source framework for developing and evaluating LLM agents in Factorio. It provides a controlled environment where AI models can attempt complex automation, resource management, and optimisation tasks in a grounded world with meaningful constraints.<p>A critical advantage of Factorio as a benchmark is its unbounded nature. Unlike many evals that are quickly saturated by newer models, Factorio's geometric complexity scaling means it won't be "solved" in the next 6 months (or possibly even years). This allows us to meaningfully compare models by the order-of-magnitude of resources they can produce - creating a benchmark with longevity.<p>The project began 18 months ago after years of playing Factorio, recognising its potential as an AI research testbed. A few months ago, our team (myself, Akbir, and Mart) came together to create a benchmark that tests agent capabilities in spatial reasoning and long-term planning.<p>Two technical innovations drove this project forward: First, we discovered that piping Lua into the Factorio console over TCP enables running (almost) arbitrary code without directly modding the game. Second, we developed a first-class Python API that wraps these Lua programs to provide a clean, type-hinted interface for AI agents to interact with Factorio through familiar programming paradigms.<p>Agents interact with FLE through a REPL pattern: 1. They observe the world (seeing the output of their last action) 2. Generate Python code to perform their next action 3. Receive detailed feedback (including exceptions and stdout)<p>We provide two main evaluation settings: - Lab-play: 24 structured tasks with fixed resources - Open-play: An unbounded task of building the largest possible factory on a procedurally generated map<p>We found that while LLMs show promising short-horizon skills, they struggle with spatial reasoning in constrained environments. They can discover basic automation strategies (like electric-powered drilling) but fail to achieve more complex automation (like electronic circuit manufacturing). Claude Sonnet 3.5 is currently the best model (by a significant margin).<p>The code is available at <a href="https://github.com/JackHopkins/factorio-learning-environment" rel="nofollow">https://github.com/JackHopkins/factorio-learning-environment</a>.<p>You'll need: - Factorio (version 1.1.110) - Docker - Python 3.10+<p>The README contains detailed installation instructions and examples of how to run evaluations with different LLM agents.<p>We would love to hear your thoughts and see what others can do with this framework!

Show HN: Factorio Learning Environment – Agents Build Factories

I'm Jack, and I'm excited to share a project that has channeled my Factorio addiction recently: the Factorio Learning Environment (FLE).<p>FLE is an open-source framework for developing and evaluating LLM agents in Factorio. It provides a controlled environment where AI models can attempt complex automation, resource management, and optimisation tasks in a grounded world with meaningful constraints.<p>A critical advantage of Factorio as a benchmark is its unbounded nature. Unlike many evals that are quickly saturated by newer models, Factorio's geometric complexity scaling means it won't be "solved" in the next 6 months (or possibly even years). This allows us to meaningfully compare models by the order-of-magnitude of resources they can produce - creating a benchmark with longevity.<p>The project began 18 months ago after years of playing Factorio, recognising its potential as an AI research testbed. A few months ago, our team (myself, Akbir, and Mart) came together to create a benchmark that tests agent capabilities in spatial reasoning and long-term planning.<p>Two technical innovations drove this project forward: First, we discovered that piping Lua into the Factorio console over TCP enables running (almost) arbitrary code without directly modding the game. Second, we developed a first-class Python API that wraps these Lua programs to provide a clean, type-hinted interface for AI agents to interact with Factorio through familiar programming paradigms.<p>Agents interact with FLE through a REPL pattern: 1. They observe the world (seeing the output of their last action) 2. Generate Python code to perform their next action 3. Receive detailed feedback (including exceptions and stdout)<p>We provide two main evaluation settings: - Lab-play: 24 structured tasks with fixed resources - Open-play: An unbounded task of building the largest possible factory on a procedurally generated map<p>We found that while LLMs show promising short-horizon skills, they struggle with spatial reasoning in constrained environments. They can discover basic automation strategies (like electric-powered drilling) but fail to achieve more complex automation (like electronic circuit manufacturing). Claude Sonnet 3.5 is currently the best model (by a significant margin).<p>The code is available at <a href="https://github.com/JackHopkins/factorio-learning-environment" rel="nofollow">https://github.com/JackHopkins/factorio-learning-environment</a>.<p>You'll need: - Factorio (version 1.1.110) - Docker - Python 3.10+<p>The README contains detailed installation instructions and examples of how to run evaluations with different LLM agents.<p>We would love to hear your thoughts and see what others can do with this framework!

Show HN: Factorio Learning Environment – Agents Build Factories

I'm Jack, and I'm excited to share a project that has channeled my Factorio addiction recently: the Factorio Learning Environment (FLE).<p>FLE is an open-source framework for developing and evaluating LLM agents in Factorio. It provides a controlled environment where AI models can attempt complex automation, resource management, and optimisation tasks in a grounded world with meaningful constraints.<p>A critical advantage of Factorio as a benchmark is its unbounded nature. Unlike many evals that are quickly saturated by newer models, Factorio's geometric complexity scaling means it won't be "solved" in the next 6 months (or possibly even years). This allows us to meaningfully compare models by the order-of-magnitude of resources they can produce - creating a benchmark with longevity.<p>The project began 18 months ago after years of playing Factorio, recognising its potential as an AI research testbed. A few months ago, our team (myself, Akbir, and Mart) came together to create a benchmark that tests agent capabilities in spatial reasoning and long-term planning.<p>Two technical innovations drove this project forward: First, we discovered that piping Lua into the Factorio console over TCP enables running (almost) arbitrary code without directly modding the game. Second, we developed a first-class Python API that wraps these Lua programs to provide a clean, type-hinted interface for AI agents to interact with Factorio through familiar programming paradigms.<p>Agents interact with FLE through a REPL pattern: 1. They observe the world (seeing the output of their last action) 2. Generate Python code to perform their next action 3. Receive detailed feedback (including exceptions and stdout)<p>We provide two main evaluation settings: - Lab-play: 24 structured tasks with fixed resources - Open-play: An unbounded task of building the largest possible factory on a procedurally generated map<p>We found that while LLMs show promising short-horizon skills, they struggle with spatial reasoning in constrained environments. They can discover basic automation strategies (like electric-powered drilling) but fail to achieve more complex automation (like electronic circuit manufacturing). Claude Sonnet 3.5 is currently the best model (by a significant margin).<p>The code is available at <a href="https://github.com/JackHopkins/factorio-learning-environment" rel="nofollow">https://github.com/JackHopkins/factorio-learning-environment</a>.<p>You'll need: - Factorio (version 1.1.110) - Docker - Python 3.10+<p>The README contains detailed installation instructions and examples of how to run evaluations with different LLM agents.<p>We would love to hear your thoughts and see what others can do with this framework!

Show HN: Factorio Learning Environment – Agents Build Factories

I'm Jack, and I'm excited to share a project that has channeled my Factorio addiction recently: the Factorio Learning Environment (FLE).<p>FLE is an open-source framework for developing and evaluating LLM agents in Factorio. It provides a controlled environment where AI models can attempt complex automation, resource management, and optimisation tasks in a grounded world with meaningful constraints.<p>A critical advantage of Factorio as a benchmark is its unbounded nature. Unlike many evals that are quickly saturated by newer models, Factorio's geometric complexity scaling means it won't be "solved" in the next 6 months (or possibly even years). This allows us to meaningfully compare models by the order-of-magnitude of resources they can produce - creating a benchmark with longevity.<p>The project began 18 months ago after years of playing Factorio, recognising its potential as an AI research testbed. A few months ago, our team (myself, Akbir, and Mart) came together to create a benchmark that tests agent capabilities in spatial reasoning and long-term planning.<p>Two technical innovations drove this project forward: First, we discovered that piping Lua into the Factorio console over TCP enables running (almost) arbitrary code without directly modding the game. Second, we developed a first-class Python API that wraps these Lua programs to provide a clean, type-hinted interface for AI agents to interact with Factorio through familiar programming paradigms.<p>Agents interact with FLE through a REPL pattern: 1. They observe the world (seeing the output of their last action) 2. Generate Python code to perform their next action 3. Receive detailed feedback (including exceptions and stdout)<p>We provide two main evaluation settings: - Lab-play: 24 structured tasks with fixed resources - Open-play: An unbounded task of building the largest possible factory on a procedurally generated map<p>We found that while LLMs show promising short-horizon skills, they struggle with spatial reasoning in constrained environments. They can discover basic automation strategies (like electric-powered drilling) but fail to achieve more complex automation (like electronic circuit manufacturing). Claude Sonnet 3.5 is currently the best model (by a significant margin).<p>The code is available at <a href="https://github.com/JackHopkins/factorio-learning-environment" rel="nofollow">https://github.com/JackHopkins/factorio-learning-environment</a>.<p>You'll need: - Factorio (version 1.1.110) - Docker - Python 3.10+<p>The README contains detailed installation instructions and examples of how to run evaluations with different LLM agents.<p>We would love to hear your thoughts and see what others can do with this framework!

Show HN: Seven39, a social media app that is only open for 3 hours every evening

I built this site as a quick test if a time boxed social media experience feels better than an endless one. So far I've just been using it with friends and it feels nice, but it seems like it is time to bring it to a larger audience.<p>Let me know what you think! It is just based on EST for now, sorry.

Show HN: Seven39, a social media app that is only open for 3 hours every evening

I built this site as a quick test if a time boxed social media experience feels better than an endless one. So far I've just been using it with friends and it feels nice, but it seems like it is time to bring it to a larger audience.<p>Let me know what you think! It is just based on EST for now, sorry.

Show HN: C++ AWS MSK IAM Auth Implementation – Goodbye Kafka Passwords

In 2023, AWS announced[1] IAM authentication for MSK Kafka clusters with support for "all programming languages"… except C++. While Java[2], Python[3], Go[4], and others got official SDKs, C++ developers/vendors were stuck hardcoding SCRAM-SHA credentials in code/configs or relying on heavier Java-based tools like Kafka Connect or Apache Flink.<p>Later, community projects added Rust[5] and Ruby[6] support. Why no C++? Rust might be the new favorite, but C++ is still king for high-performance data systems: minimal dependencies, lean resource use, and raw speed.<p>At Timeplus, we needed IAM auth for our C++ streaming engine, Proton, so we built it ourselves. Today, we’re open-sourcing our code for AWS MSK IAM authentication. It’s live in Timeplus Proton 1.6.12<p>Just attach an IAM role to your EC2 instance or EKS pod, then put the Timeplus Proton single binary inside, start the server, then run the following SQL to read or write MSK:<p>CREATE EXTERNAL STREAM msk_stream(column_defs) SETTINGS type='kafka',topic='topic2', brokers='prefix.kafka.us-west-2.amazonaws.com:9098', security_protocol='SASL_SSL', sasl_mechanism='AWS_MSK_IAM';<p>The core logic is just two files under 200 lines and you can reuse the code anywhere. <a href="https://github.com/timeplus-io/proton/blob/develop/src/IO/Kafka/AwsMskIamSigner.h">https://github.com/timeplus-io/proton/blob/develop/src/IO/Ka...</a> <a href="https://github.com/timeplus-io/proton/blob/develop/src/IO/Kafka/AwsMskIamSigner.cpp">https://github.com/timeplus-io/proton/blob/develop/src/IO/Ka...</a><p>We’d love to get your feedback and work together to make this a standalone library—or even get it into ClickHouse or AWS SDK for C++.<p>For those curious about Timeplus Proton: it’s an open-source streaming engine we built in C++ (think “FlinkSQL in C++” meets ClickHouse’s columnar storage). Later this month, we will also open-source our C++ code for Apache Iceberg read&write. Stay tuned.<p>Links:<p>[1] <a href="https://aws.amazon.com/blogs/big-data/amazon-msk-iam-authentication-now-supports-all-programming-languages/" rel="nofollow">https://aws.amazon.com/blogs/big-data/amazon-msk-iam-authent...</a> [2] <a href="https://github.com/aws/aws-msk-iam-auth">https://github.com/aws/aws-msk-iam-auth</a> [3] <a href="https://github.com/aws/aws-msk-iam-sasl-signer-python">https://github.com/aws/aws-msk-iam-sasl-signer-python</a> [4] <a href="https://github.com/aws/aws-msk-iam-sasl-signer-go">https://github.com/aws/aws-msk-iam-sasl-signer-go</a> [5] <a href="https://docs.rs/aws-msk-iam-sasl-signer" rel="nofollow">https://docs.rs/aws-msk-iam-sasl-signer</a> [6] <a href="https://rubygems.org/gems/aws-msk-iam-sasl-signer/" rel="nofollow">https://rubygems.org/gems/aws-msk-iam-sasl-signer/</a>

Show HN: Editable Games

I made an animation programming language that you can type into a textarea. I make little games with it. Now other people can customize the games I make with it.<p>I've been working on canvas language for 15 years now. Not very successful, but editable gifs turned out okay. Since it's my passion, I keep trying, and my latest is editable games - I'm not officially calling it that though.<p>I've had some interest in advergames and this would allow designers to easily customize games for their clients - the hidden objects game being the best example for this, and the only one made specifically for the purpose.<p>Anyways, games are interpreted at runtime by JavaScript. To publish, for example on itch or your own website, you need to submit your project file (download it from the dev studio) and wait a few minutes. You'll get back a JS file that contains your game.<p>ngl, although a passion project, I'd like this to one day be profitable - trying to work that out.<p>If interested, the main project site is <a href="https://canvaslanguage.com" rel="nofollow">https://canvaslanguage.com</a><p>I'd love to get some feedback. Although to be honest, I just want to show somebody my newest creation :)<p>Thank you.

Show HN: Editable Games

I made an animation programming language that you can type into a textarea. I make little games with it. Now other people can customize the games I make with it.<p>I've been working on canvas language for 15 years now. Not very successful, but editable gifs turned out okay. Since it's my passion, I keep trying, and my latest is editable games - I'm not officially calling it that though.<p>I've had some interest in advergames and this would allow designers to easily customize games for their clients - the hidden objects game being the best example for this, and the only one made specifically for the purpose.<p>Anyways, games are interpreted at runtime by JavaScript. To publish, for example on itch or your own website, you need to submit your project file (download it from the dev studio) and wait a few minutes. You'll get back a JS file that contains your game.<p>ngl, although a passion project, I'd like this to one day be profitable - trying to work that out.<p>If interested, the main project site is <a href="https://canvaslanguage.com" rel="nofollow">https://canvaslanguage.com</a><p>I'd love to get some feedback. Although to be honest, I just want to show somebody my newest creation :)<p>Thank you.

Show HN: Editable Games

I made an animation programming language that you can type into a textarea. I make little games with it. Now other people can customize the games I make with it.<p>I've been working on canvas language for 15 years now. Not very successful, but editable gifs turned out okay. Since it's my passion, I keep trying, and my latest is editable games - I'm not officially calling it that though.<p>I've had some interest in advergames and this would allow designers to easily customize games for their clients - the hidden objects game being the best example for this, and the only one made specifically for the purpose.<p>Anyways, games are interpreted at runtime by JavaScript. To publish, for example on itch or your own website, you need to submit your project file (download it from the dev studio) and wait a few minutes. You'll get back a JS file that contains your game.<p>ngl, although a passion project, I'd like this to one day be profitable - trying to work that out.<p>If interested, the main project site is <a href="https://canvaslanguage.com" rel="nofollow">https://canvaslanguage.com</a><p>I'd love to get some feedback. Although to be honest, I just want to show somebody my newest creation :)<p>Thank you.

Show HN: In-Browser Graph RAG with Kuzu-WASM and WebLLM

We show the potential of modern, embedded graph databases in the browser by demonstrating a fully in-browser chatbot that can perform Graph RAG using Kuzu (the graph database we're building) and WebLLM, a popular in-browser inference engine for LLMs. The post retrieves from the graph via a Text-to-Cypher pipeline that translates a user question into a Cypher query, and the LLM uses the retrieved results to synthesize a response. As LLMs get better, and WebGPU and Wasm64 become more widely adopted, we expect to be able to do more and more in the browser in combination with LLMs, so a lot of the performance limitations we see currently may not be as much of a problem in the future.<p>We will soon also be releasing a vector index as part of Kuzu that you can also use in the browser to build traditional RAG or Graph RAG that retrieves from both vectors and graphs. The system has come a long way since we open sourced it about 2 years ago, so please give us feedback about how it can be more useful!

Show HN: In-Browser Graph RAG with Kuzu-WASM and WebLLM

We show the potential of modern, embedded graph databases in the browser by demonstrating a fully in-browser chatbot that can perform Graph RAG using Kuzu (the graph database we're building) and WebLLM, a popular in-browser inference engine for LLMs. The post retrieves from the graph via a Text-to-Cypher pipeline that translates a user question into a Cypher query, and the LLM uses the retrieved results to synthesize a response. As LLMs get better, and WebGPU and Wasm64 become more widely adopted, we expect to be able to do more and more in the browser in combination with LLMs, so a lot of the performance limitations we see currently may not be as much of a problem in the future.<p>We will soon also be releasing a vector index as part of Kuzu that you can also use in the browser to build traditional RAG or Graph RAG that retrieves from both vectors and graphs. The system has come a long way since we open sourced it about 2 years ago, so please give us feedback about how it can be more useful!

Show HN: In-Browser Graph RAG with Kuzu-WASM and WebLLM

We show the potential of modern, embedded graph databases in the browser by demonstrating a fully in-browser chatbot that can perform Graph RAG using Kuzu (the graph database we're building) and WebLLM, a popular in-browser inference engine for LLMs. The post retrieves from the graph via a Text-to-Cypher pipeline that translates a user question into a Cypher query, and the LLM uses the retrieved results to synthesize a response. As LLMs get better, and WebGPU and Wasm64 become more widely adopted, we expect to be able to do more and more in the browser in combination with LLMs, so a lot of the performance limitations we see currently may not be as much of a problem in the future.<p>We will soon also be releasing a vector index as part of Kuzu that you can also use in the browser to build traditional RAG or Graph RAG that retrieves from both vectors and graphs. The system has come a long way since we open sourced it about 2 years ago, so please give us feedback about how it can be more useful!