The best Hacker News stories from Show from the past day
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Show HN: Collaborative live-coding MIDI sequencers in JavaScript
Show HN: Fern, a language for defining REST APIs that compiles into OpenAPI
Hi HN, this is Danny, Deep, and Zach.<p>We built Fern after our previous ed tech startup failed. We were frustrated with how much time we spent writing “API code” instead of working on the actual product. We tried to use OpenAPI but we were underwhelmed - the generated code wasn’t idiomatic and it still required manual work (custom templates, scripts, manually publishing SDKs to registries).<p>The Fern compiler takes your API as input and invokes generators that output things like: SDKs, server code, a Postman collection, and an OpenAPI spec.<p>Some technical highlights about the compiler + generators:<p>- The compiler (available as a CLI) handles syntactic + semantic validation. It also includes a linter that encodes best practices. If your API Definition compiles, you can have high confidence that the SDKs will generate correctly.<p>- After all the parsing and validation, the compiler outputs an intermediate representation that gets handed off to the generators. This prevents each generator from re-implementing the same parsing and validation logic.<p>- Each generator is implemented in the language it is targeting - e.g. the Python generators are written in Python, the TypeScript generators are written in TS. It makes the SDKs more idiomatic because every programming language generally has the best tooling/libraries for generating code in itself. We also think it’ll make community involvement + contribution easier.<p>- The generators can output the code to disk, but also push the code to a Github repo and publish the SDK directly to registries (e.g. npm, Maven).<p>We are looking for devs to use Fern for API development. If you have any feedback about the process, compiler, or the generated code, we’d love to hear it.<p>"Plant Store" example: <a href="https://github.com/fern-api/plantstore-api">https://github.com/fern-api/plantstore-api</a><p>Generated repos:<p>- <a href="https://github.com/fern-api/plantstore-node">https://github.com/fern-api/plantstore-node</a><p>- <a href="https://github.com/fern-api/plantstore-java">https://github.com/fern-api/plantstore-java</a><p>- <a href="https://github.com/fern-api/plantstore-postman">https://github.com/fern-api/plantstore-postman</a><p>- <a href="https://github.com/fern-api/plantstore-openapi">https://github.com/fern-api/plantstore-openapi</a>
Show HN: Use ChatGPT and Excel to get superpowers
During my winter holiday I played with ChatGPT and built an integration with the OpenAI Completion APIs and Excel. (And yes technically not ChatGPT but as close that we can get with the APIs that are available.)<p>I found this incredible useful for my work on Filestar.<p>I wrote some instructions here on how to try this yourself:<p><a href="https://www.linkedin.com/pulse/use-chatgpt-excel-get-superpowers-niels-bosma/?published=t" rel="nofollow">https://www.linkedin.com/pulse/use-chatgpt-excel-get-superpo...</a><p>Please let me know if you figure out any useful prompts.
Show HN: Sleuth, open source workspace search in natural language
Hey everyone,<p>We know how hard it can be to ramp up and learn the ins and outs of a new company.<p>- “Who should I talk to about customer onboarding?”<p>- “What was that project the onboarding team shipped in June, that had a massive impact on step 3 completion rate?”<p>Instead of asking someone the same question that’s been asked hundreds of times before, it’s more efficient to find answers in existing documents and past conversations. The problem is, this data is spread out across dozens of workplace apps, with search features that all work differently. That’s why we’ve created Sleuth, an open source library that allows you to search through your company’s entire history using natural language. It understands the intent of your question, not just the keywords. Here’s a demo:<p><a href="https://www.loom.com/share/71625cce862f4d4ea12b8a87ad94e407" rel="nofollow">https://www.loom.com/share/71625cce862f4d4ea12b8a87ad94e407</a><p>You can fork our repo (<a href="https://github.com/getsleuth/Sleuth">https://github.com/getsleuth/Sleuth</a>) and try it right now, or book a 15 min call (<a href="https://calendly.com/triton-founders/sleuth-feedback" rel="nofollow">https://calendly.com/triton-founders/sleuth-feedback</a>) with us to share your feedback.<p>How does it work?<p>Vector embeddings are generated for slack messages using OpenAI’s text-embedding-ada-002 model and stored in a Pinecone vector database for easy querying.<p>How is this different from Glean?<p>Glean is great, but we wanted to introduce a product that anyone can fork, use, and customize without ever talking to a sales team. Building in public makes for better products.<p>What integrations do you support?<p>Just Slack to start. What other integrations would you like to see?
Show HN: Sleuth, open source workspace search in natural language
Hey everyone,<p>We know how hard it can be to ramp up and learn the ins and outs of a new company.<p>- “Who should I talk to about customer onboarding?”<p>- “What was that project the onboarding team shipped in June, that had a massive impact on step 3 completion rate?”<p>Instead of asking someone the same question that’s been asked hundreds of times before, it’s more efficient to find answers in existing documents and past conversations. The problem is, this data is spread out across dozens of workplace apps, with search features that all work differently. That’s why we’ve created Sleuth, an open source library that allows you to search through your company’s entire history using natural language. It understands the intent of your question, not just the keywords. Here’s a demo:<p><a href="https://www.loom.com/share/71625cce862f4d4ea12b8a87ad94e407" rel="nofollow">https://www.loom.com/share/71625cce862f4d4ea12b8a87ad94e407</a><p>You can fork our repo (<a href="https://github.com/getsleuth/Sleuth">https://github.com/getsleuth/Sleuth</a>) and try it right now, or book a 15 min call (<a href="https://calendly.com/triton-founders/sleuth-feedback" rel="nofollow">https://calendly.com/triton-founders/sleuth-feedback</a>) with us to share your feedback.<p>How does it work?<p>Vector embeddings are generated for slack messages using OpenAI’s text-embedding-ada-002 model and stored in a Pinecone vector database for easy querying.<p>How is this different from Glean?<p>Glean is great, but we wanted to introduce a product that anyone can fork, use, and customize without ever talking to a sales team. Building in public makes for better products.<p>What integrations do you support?<p>Just Slack to start. What other integrations would you like to see?
Show HN: New GraphQL API for WordPress
Show HN: New GraphQL API for WordPress
Show HN: New GraphQL API for WordPress
Show HN: New GraphQL API for WordPress
Show HN: Loti – Remove revenge porn using facial recognition on adult sites
Show HN: Loti – Remove revenge porn using facial recognition on adult sites
Show HN: Mapperly – A .NET source generator for object to object mappings
Show HN: Mapperly – A .NET source generator for object to object mappings
Show HN: Mapperly – A .NET source generator for object to object mappings
Show HN: Mapperly – A .NET source generator for object to object mappings
Show HN: Grila – Calendar for keyboard addicts, always one keypress away
Show HN: Grila – Calendar for keyboard addicts, always one keypress away
Show HN: Grila – Calendar for keyboard addicts, always one keypress away
Show HN: Quick tunnels to localhost with one command and no binary download
Show HN: Quick tunnels to localhost with one command and no binary download