Alternatives
Products that do what JSON Translator does
Translate app locales with LLMs without breaking the code
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Hey HN, we’re building an open specification that lets agents discover and invoke APIs with natural language, built on the OpenAPI standard. agents.json clearly defines the contract between LLMs and API as a standard that's open, observable, and replicable. Here’s a walkthrough of how it works: https://youtu.be/kby2Wdt2Dtk?si=59xGCDy48Zzwr7ND. There’s 2 parts to this: 1. An agents.json file describes how to link API calls together into outcome-based tools for LLMs. This file sits alongside an OpenAPI file. 2. The agents.json SDK loads agents.json files as tools for an LLM that…
2025 · github.com
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Hi HN, I’m Joan, the developer of Quicklang. I made this app to easily translate and keep in sync all my localization JSON files for my side projects. While searching online for a similar tool, I only found enterprise solutions that do not allow direct editing of JSON files. I used to use ChatGPT to translate the JSON translation file changes before coding Quicklang. However, I realized that ChatGPT only allows you to input short content for translation into another language (even if you provide a .json file), and each time I had to request translations for one language at a time. So, I…
2024 · quicklang.app
- 5CI
I build this app because I was tired of using Google Translate to translate my locale files (i18n). I wanted to use a more efficient and accurate translation tool. ChatGPT, however, always break my json and cannot translate large contents. So I build this app to solve these problems. Hope it can save your time. github: https://github.com/ObservedObserver/chatgpt-i18n online app: https://chatgpt-i18n.vercel.app/
2023 · github.com
- 6WW
I spent a few hours last weekend testing whether AI can replace code by executing directly. Built a contact manager where every HTTP request goes to an LLM with three tools: database (SQLite), webResponse (HTML/JSON/JS), and updateMemory (feedback). No routes, no controllers, no business logic. The AI designs schemas on first request, generates UIs from paths alone, and evolves based on natural language feedback. It works—forms submit, data persists, APIs return JSON—but it's catastrophically slow (30-60s per request), absurdly expensive ($0.05/request), and has zero UI…
Nov 2025 · github.com
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We've been building data pipelines that scrape websites and extract structured data for a while now. If you've done this, you know the drill: you write CSS selectors, the site changes its layout, everything breaks at 2am, and you spend your morning rewriting parsers. LLMs seemed like the obvious fix — just throw the HTML at GPT and ask for JSON. Except in practice, it's more painful than that: - Raw HTML is full of nav bars, footers, and tracking junk that eats your token budget. A typical product page is 80% noise. - LLMs return malformed JSON more often than you'd expect, especially with…
Mar 2026 · github.com
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Built an auditable AI (Bible) translation pipeline: Hebrew/Greek source packets -> verse JSON with notes rolling up to chapters, books, and testaments. Final texts compiled with metrics (TTR, n-grams). This is the first full-text example as far as I know (Gen Z bible doesn't count). There are hallucinations and issues, but the overall quality surprised me. LLMs have a lot of promise translating and rendering 'accessible' more ancient texts. The technology has a lot of benefit for the faithful, that I think is only beginning to be explored.
Jan 2026 · biblexica.com
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Recently featured in a LangChain blog https://blog.langchain.dev/empowering-development-with-flowt... , use LLMs to construct an API first runnable workflow with an IDE experience.
2024 · github.com
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Hi HN, We built Neurooo.com, an automatic translation tool like DeepL or Google Translate, but using LLMs with OpenAI and Mistral. We noticed that LLMs were quite good at translating informal or contextual text, and also way cheaper than DeepL or Google Translate when you factor in the cost per character. So we decided to try and build a similar translation interface to see if we can match the leaders in term of ease of use and quality. We're quite happy about it and people around us seem to think that we're even better in many cases (abbreviations, informal emails, business translations,…
2024 · neurooo.com
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- 24AS
I built this because I was frustrated with how messy translation files get as projects scale. Most i18n solutions force you to manage big JSON dictionaries, spread across multiple files, and then manually wire everything into your UI. It quickly becomes hard to keep things organized, especially in component-heavy apps. This approach is component-first i18n: translations live close to the UI they belong to. That makes it easier to keep things organized, avoid duplication, and scale without the usual chaos of string management. It’s lightweight, works with React/Next.js, and is designed…
2025 · github.com
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