I

I Internationalized an AI Chatbot in 10 minutes

Hacker News

I Internationalized an AI Chatbot in 10 minutes

Hi HN! I’m Brian, and I've recently been working on an open-source React and Next.js internationalization library called gt-next, and I thought it’d be cool to show how I internationalized Vercel’s AI Chatbot with it. Feel free to try it out today! Just `npm i gt-next gt-next-cli` . Here’s a quick summary: - I internationalized and shipped a multilingual chatbot in a total of 10 minutes - I've included a 5 minute video walkthrough of the entire process - You can check out the complete, internationalized chatbot at: https://example-ai-chatbot-ten.vercel.app/ We also have docs at: https://generaltranslation.com/docs The source code for the AI Chatbot is here: https://github.com/General-Translation/ai-chatbot Any feedback or comments are welcome!

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Product HuntOn track for Day 1 leaderboard · Strong signals: code, open · Missing: mac, agents, macos
54%54% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
49%49% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: video · Missing: mobile apps, ios, personal
42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
27%27% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
24%24% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency
7%7% predicted probability of success on BetaList, based on ML models trained on real launch data.

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