The best Hacker News stories from Show from the past day
Latest posts:
Show HN: HTML-to-Markdown – convert entire websites to Markdown with Golang/CLI
Hey HN!<p>I originally built “html-to-markdown” back in 2018 (while still in high school) to handle complex HTML conversions where other libraries struggled.<p>Now, I’ve released v2 — a complete rewrite designed to handle even more edge cases. It supports entire websites with a high accuracy.<p>Example use: I’ve used it in my RSS reader to strip HTML down to clean Markdown, similar to the "Reader Mode" in your Browser.<p>It can be used as a Golang package or as an CLI.<p>Give it a try & tell me what edge cases you encounter!
Show HN: Asterogue, my sci-fi roguelike, is now playable on the web
Show HN: Asterogue, my sci-fi roguelike, is now playable on the web
Show HN: Asterogue, my sci-fi roguelike, is now playable on the web
Show HN: GitQuill – free cross-platform GUI for Git, inspired by GitKraken
Show HN: GitQuill – free cross-platform GUI for Git, inspired by GitKraken
Show HN: Directional antenna alignment using phone motion sensors
Show HN: Directional antenna alignment using phone motion sensors
Show HN: Directional antenna alignment using phone motion sensors
Show HN: TutoriaLLM – AI Integrated programming tutorials
Hello! I’m So Tokumaru ( <a href="https://tokumaru.work" rel="nofollow">https://tokumaru.work</a> ), high school student from Japan working on ways to leverage large language models (LLMs) for K-12 programming education. Recently, I built a project called "TutoriaLLM," a self-hosted application designed to support educators and students through a multi-modal LLM that offers guided tutorials.<p>TutoriaLLM integrates voice (voice-to-voice) and text-based AI interactions into Blockly, a block editor widely known for its use in Scratch. It enables server-side code execution and allows students to test their code directly in Minecraft (Bedrock or Education Edition) without any setup.<p>I’m actively developing this project and aim to bring it to a level ready for use in programming education by next year. I’d love to hear any feedback!<p>Documentation: <a href="https://tutoriallm.com" rel="nofollow">https://tutoriallm.com</a><p>Demo: <a href="https://demo.tutoriallm.com" rel="nofollow">https://demo.tutoriallm.com</a><p>Repository: <a href="https://github.com/TutoriaLLM/TutoriaLLM">https://github.com/TutoriaLLM/TutoriaLLM</a>
Show HN: TutoriaLLM – AI Integrated programming tutorials
Hello! I’m So Tokumaru ( <a href="https://tokumaru.work" rel="nofollow">https://tokumaru.work</a> ), high school student from Japan working on ways to leverage large language models (LLMs) for K-12 programming education. Recently, I built a project called "TutoriaLLM," a self-hosted application designed to support educators and students through a multi-modal LLM that offers guided tutorials.<p>TutoriaLLM integrates voice (voice-to-voice) and text-based AI interactions into Blockly, a block editor widely known for its use in Scratch. It enables server-side code execution and allows students to test their code directly in Minecraft (Bedrock or Education Edition) without any setup.<p>I’m actively developing this project and aim to bring it to a level ready for use in programming education by next year. I’d love to hear any feedback!<p>Documentation: <a href="https://tutoriallm.com" rel="nofollow">https://tutoriallm.com</a><p>Demo: <a href="https://demo.tutoriallm.com" rel="nofollow">https://demo.tutoriallm.com</a><p>Repository: <a href="https://github.com/TutoriaLLM/TutoriaLLM">https://github.com/TutoriaLLM/TutoriaLLM</a>
Show HN: TutoriaLLM – AI Integrated programming tutorials
Hello! I’m So Tokumaru ( <a href="https://tokumaru.work" rel="nofollow">https://tokumaru.work</a> ), high school student from Japan working on ways to leverage large language models (LLMs) for K-12 programming education. Recently, I built a project called "TutoriaLLM," a self-hosted application designed to support educators and students through a multi-modal LLM that offers guided tutorials.<p>TutoriaLLM integrates voice (voice-to-voice) and text-based AI interactions into Blockly, a block editor widely known for its use in Scratch. It enables server-side code execution and allows students to test their code directly in Minecraft (Bedrock or Education Edition) without any setup.<p>I’m actively developing this project and aim to bring it to a level ready for use in programming education by next year. I’d love to hear any feedback!<p>Documentation: <a href="https://tutoriallm.com" rel="nofollow">https://tutoriallm.com</a><p>Demo: <a href="https://demo.tutoriallm.com" rel="nofollow">https://demo.tutoriallm.com</a><p>Repository: <a href="https://github.com/TutoriaLLM/TutoriaLLM">https://github.com/TutoriaLLM/TutoriaLLM</a>
Show HN: TutoriaLLM – AI Integrated programming tutorials
Hello! I’m So Tokumaru ( <a href="https://tokumaru.work" rel="nofollow">https://tokumaru.work</a> ), high school student from Japan working on ways to leverage large language models (LLMs) for K-12 programming education. Recently, I built a project called "TutoriaLLM," a self-hosted application designed to support educators and students through a multi-modal LLM that offers guided tutorials.<p>TutoriaLLM integrates voice (voice-to-voice) and text-based AI interactions into Blockly, a block editor widely known for its use in Scratch. It enables server-side code execution and allows students to test their code directly in Minecraft (Bedrock or Education Edition) without any setup.<p>I’m actively developing this project and aim to bring it to a level ready for use in programming education by next year. I’d love to hear any feedback!<p>Documentation: <a href="https://tutoriallm.com" rel="nofollow">https://tutoriallm.com</a><p>Demo: <a href="https://demo.tutoriallm.com" rel="nofollow">https://demo.tutoriallm.com</a><p>Repository: <a href="https://github.com/TutoriaLLM/TutoriaLLM">https://github.com/TutoriaLLM/TutoriaLLM</a>
Show HN: Draw.Audio – A musical sketchpad using the Web Audio API
Show HN: Draw.Audio – A musical sketchpad using the Web Audio API
Show HN: Draw.Audio – A musical sketchpad using the Web Audio API
Show HN: Draw.Audio – A musical sketchpad using the Web Audio API
Show HN: BemiDB – Postgres read replica optimized for analytics
Hi HN! We're Evgeny and Arjun, and we’re building a better way to do analytics with Postgres.<p>We love Postgres for its simplicity, power, and rich ecosystem. But engineers have to still get bogged down with heavyweight and expensive OLAP systems when connecting an analytics data stack.<p>Postgres is amazing at OLTP queries, but not for OLAP queries (large data scans and aggregations). Even in this case, we’ve still heard from countless scaling startups that they still try to use only a read replica to run analytics workloads since they don’t want to deal with the data engineering complexity of the alternative. This actually works surprising well initially, but starts to break for them as they scale or when integrating multiple data sources. Adding lots of indexes to support analytics also slows down their transactional write performance.<p>When growing out of “just use Postgres”, companies have to understand and wrangle complex ETL pipelines, CDC processes, and data warehouses — adding layers of complexity that defeat the simplicity that undermines their initial choice for Postgres as their data storage in the first place.<p>We thought there had to be a better way, so we’re building BemiDB. It’s designed to handle complex analytical queries at scale without the usual overhead. It’s a single binary that automatically syncs with Postgres data and is Postgres-compatible, so it’s like querying standard Postgres and works with all existing tools.<p>Under the hood, we use Apache Iceberg (with Parquet data files) stored in S3. This allows for bottomless inexpensive storage, compressed data in columnar files, and an open format that guarantees compatibility with other data tools.<p>We embed DuckDB as the query engine for in-memory analytics that work for complex queries. With efficient columnar storage and vectorized execution, we’re aiming for faster results without heavy infra. BemiDB communicates over the Postgres wire protocol to make all querying Postgres-compatible.<p>We want to simplify data stacks for companies that use Postgres by reducing complexity (single binary and S3), using non-proprietary data formats (Iceberg open tables), and removing vendor lock-in (open source). We'd love to hear your feedback! What do you think?
Show HN: BemiDB – Postgres read replica optimized for analytics
Hi HN! We're Evgeny and Arjun, and we’re building a better way to do analytics with Postgres.<p>We love Postgres for its simplicity, power, and rich ecosystem. But engineers have to still get bogged down with heavyweight and expensive OLAP systems when connecting an analytics data stack.<p>Postgres is amazing at OLTP queries, but not for OLAP queries (large data scans and aggregations). Even in this case, we’ve still heard from countless scaling startups that they still try to use only a read replica to run analytics workloads since they don’t want to deal with the data engineering complexity of the alternative. This actually works surprising well initially, but starts to break for them as they scale or when integrating multiple data sources. Adding lots of indexes to support analytics also slows down their transactional write performance.<p>When growing out of “just use Postgres”, companies have to understand and wrangle complex ETL pipelines, CDC processes, and data warehouses — adding layers of complexity that defeat the simplicity that undermines their initial choice for Postgres as their data storage in the first place.<p>We thought there had to be a better way, so we’re building BemiDB. It’s designed to handle complex analytical queries at scale without the usual overhead. It’s a single binary that automatically syncs with Postgres data and is Postgres-compatible, so it’s like querying standard Postgres and works with all existing tools.<p>Under the hood, we use Apache Iceberg (with Parquet data files) stored in S3. This allows for bottomless inexpensive storage, compressed data in columnar files, and an open format that guarantees compatibility with other data tools.<p>We embed DuckDB as the query engine for in-memory analytics that work for complex queries. With efficient columnar storage and vectorized execution, we’re aiming for faster results without heavy infra. BemiDB communicates over the Postgres wire protocol to make all querying Postgres-compatible.<p>We want to simplify data stacks for companies that use Postgres by reducing complexity (single binary and S3), using non-proprietary data formats (Iceberg open tables), and removing vendor lock-in (open source). We'd love to hear your feedback! What do you think?
Show HN: BemiDB – Postgres read replica optimized for analytics
Hi HN! We're Evgeny and Arjun, and we’re building a better way to do analytics with Postgres.<p>We love Postgres for its simplicity, power, and rich ecosystem. But engineers have to still get bogged down with heavyweight and expensive OLAP systems when connecting an analytics data stack.<p>Postgres is amazing at OLTP queries, but not for OLAP queries (large data scans and aggregations). Even in this case, we’ve still heard from countless scaling startups that they still try to use only a read replica to run analytics workloads since they don’t want to deal with the data engineering complexity of the alternative. This actually works surprising well initially, but starts to break for them as they scale or when integrating multiple data sources. Adding lots of indexes to support analytics also slows down their transactional write performance.<p>When growing out of “just use Postgres”, companies have to understand and wrangle complex ETL pipelines, CDC processes, and data warehouses — adding layers of complexity that defeat the simplicity that undermines their initial choice for Postgres as their data storage in the first place.<p>We thought there had to be a better way, so we’re building BemiDB. It’s designed to handle complex analytical queries at scale without the usual overhead. It’s a single binary that automatically syncs with Postgres data and is Postgres-compatible, so it’s like querying standard Postgres and works with all existing tools.<p>Under the hood, we use Apache Iceberg (with Parquet data files) stored in S3. This allows for bottomless inexpensive storage, compressed data in columnar files, and an open format that guarantees compatibility with other data tools.<p>We embed DuckDB as the query engine for in-memory analytics that work for complex queries. With efficient columnar storage and vectorized execution, we’re aiming for faster results without heavy infra. BemiDB communicates over the Postgres wire protocol to make all querying Postgres-compatible.<p>We want to simplify data stacks for companies that use Postgres by reducing complexity (single binary and S3), using non-proprietary data formats (Iceberg open tables), and removing vendor lock-in (open source). We'd love to hear your feedback! What do you think?