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26 projects


在你的社区搜索本地企业,发现他们的故事和优惠。
@localmama4u · X

上传本地化文件,获得游戏类型和语气感知的AI翻译。
@polycontext · X
Context-aware localization for apps, games, and software.

Tovo - 本地AI应用,提供转录和会议协助,完全在设备上运行。
Tovo - AI 会议/面试助手 — 在会议中,Tovo 是一款注重隐私的 AI 助手,完全在您的设备上运行,为会议和对话提供实时转录和智能协助,无需向外部服务器发送任何数据。

免费的本地优先 API 客户端,支持 HTTP、WebSocket、GraphQL、gRPC、MQTT 等。无需账户或云端。
@HalxDocs · X
Reqit—a fast, local-first API client for developers.

虚拟宠物伴侣,在你的 browser viewport 中爬行,根据 page topics 做出响应。
@fujidevv02 · X
the world's first context-aware, local AI browser pet companion!

为现代团队自动化负载测试,无需复杂设置或手动脚本编写。
@GorodkovVi85373 · X
- load testing made easy even without enginnering team. Faster, cheaper, distributional

自动将视频翻译配音成多种语言。
@pradeepcep · X
AI powered translation and dubbing:

搜索餐厅,发现当地人真正吃饭的地方,避免旅游陷阱。
kingchesco · HN
I know $90 for a dining app sounds absurd. And it’s not even an app; it's a wrapper for an LLM. But it is how it is built that makes it so expensive. I had to make a whole API just to call it (which because its own SAAS). All just to bypass dumb google reviews. Google Maps and reviews send people to places optimized for tourists and good copywriters. To find actual local hole-in-the-walls algorithmically, I had to first build that api (called BWENDI), a "spatial gravity" engine using 100GB+ of tweaked OSM, GeoNames, and other proprietary data. Instead of aggregating reviews, it mathematically calculates foot-traffic, throughput, transaction stats, and economic criticality among other factors. Bwendi is A Python/Node ETL pipeline feeding an LMDB-backed context API. It uses a proprietary 1MB binary grid served via Cloudflare Workers for millisecond edge reads with near-zero overhead, hosted in Switzerland. This was done of course to get the purest location context around every street

找到本地收集者,面对面交易宝可梦、One Piece和万智牌卡牌。
@paxtondang · X

根据硬件规格发现本地可运行的AI模型,包括性能和价格估算。
cdnsteve · HN
Tokenstead, find AI models for your hardware

Recall 是用于工作会话的 AI 记忆。它在您工作时静静地运行,将您的日程整理成项目、线程和任务,这样您可以一键返回任何工作片段
@vitverb · X
hi :) One tap back to the work you meant to finish. No tasks to manage. Nothing to set up. Local-first