@GbadegesinAkee2 · X

Check out what I just built with Lovable!

3stacks · HN

Lector, a FOSS self-hosted language reader (with a cloud option)

@viewofmind · X

@Berbir12 · X

Dense reading shouldn’t stop your momentum. Highlight the passage that isn’t clicking. Strang turns it into a short visual explanation, right inside your browser. One complete video is free.

@AboeyasAlharthy · X

Check out what I just built with Lovable!

u/SonikaAI · Reddit

I built SonikaAI to translate books/documents and turn them into audiobooks in one upload The problem I kept running into was pretty simple: I had a document or book in a language I wasn't comfortable reading, and turning it into something I could actually use took multiple steps. Translate it somewhere. Download or copy the result. Then, if I wanted to listen instead of read, move it into another tool for text-to-speech. For longer documents, that also meant dealing with formatting, splitt

Transmonkey — 所有您所需的翻译工具，一应俱全 - [更多介绍](https://www.transmonkey.ai/faq)

@Mrzxy91 · X

自建中转上线了 Claude Code / Codex 可用 #ClaudeCode #Codex #Cursor #AI中转 #Sub2API

mikicat · V2EX

[分享创造] 做了一个纯本地离线运行的语音转文字工具： Free Local Transcription 大家好， 平时经常有一些包含敏感信息或者不想上传到第三方服务器的音频（如会议记录、采访、个人备忘等）需要转文字。市面上很多工具本质上都是套壳调用云端 API ，既有数据泄露风险，长期用也有不小的 API 成本。 结合自己的模型优化经验，我做了一个完全基于本地算力运行的音频转文字工具：Free Local Transcription 🔗 体验地址： https://freelocaltranscription.com/ 主要特点 100% 本地运行 / 零数据外传：推理完全在设备本地完成，音频文件不会上传到任何服务器，断网状态下也能保证隐私与安全。 无需 API Key / 完全免费：依靠本地算力运行，不需要填 API Key ，也没有按分钟计费的困扰。 即开即用：界面保持极简，拖入音频即可直接进行本地转写。 目前的权衡与折衷 相比直接走云端高性能 GPU 集群，本地推理的速度会直接取决于用户的设备配置与硬件性能，老旧设备上可能存在内存占

@DoriaJefferson3 · X

@0mislice · X

@TaskyOrionix · X

is there anyone start their startup journey with Free builds? ☺️ our 👏 is one