A React and Next.js UI Toolkit for LLMs

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Hey HN, I wanted to share a UI toolkit project I’ve been working on recently, born out of how difficult I found it to build a great UX on top of LLMs, and keep application state in sync. I’ve built: - A React/JS front-end library for conversational interfaces, which makes it super easy to bootstrap AI assistants and ChatGPT style UX: https://github.com/nlkitai/nlux - A set of adapters that simplify integration with AI backends such as LangServe and HuggingFace The library is highly configurable, easy to theme, supports markdown streaming (that was tough to get right!), custom rendering for AI response components, and it works smoothly with Next.js, React JS (of course), and even plain JavaScript (for the Vue.js folks out there ;). I built it with an architecture I’d love myself as a dev: high code modularity, zero dependencies, wide unit test coverage, and lots of documentation and examples. You can play with codesandbox previews and demos here: https://docs.nlkit.com/nlux Thanks for reading. It feels like we’re at a new frontier building with LLMs, and I’d love to hear what challenges you’ve had on integrating with them & building great UI & UX.

Visit product View on Hacker NewsJun 12, 2024

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Product HuntOn track for Day 1 leaderboard · Strong signals: new, chatgpt, code · Missing: mac, agents, macos

87%87% 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 HackersFits the IH revenue-focused audience · Strong signals: supports · Missing: reddit linkedin, podcasting, created

87%87% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

69%69% 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 · Strong signals: reviews, interface · Missing: plus, platform, intuitive

48%48% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

36%36% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

16%16% 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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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