I made a React component to add our platform-powered search to your UI

Hacker News

Hey everyone! I’m extremely excited to share a project I led for our company- Vectara. If you’re not familiar with us, we specialize in retrieval augmented generation, or RAG, allowing you to get the most accurate answers and summaries about your data. But more than that, we also do semantic search. And I’m proud to say I work with some really great engineers who ensure that we do that pretty darn well too! And that’s where this comes in. For my fellow React developers out there, this one’s for you! Our new ReactSearch component allows you to add a semantic search UI, powered by our platform, to your app in just a few lines. Check it out!

Visit product View on Hacker NewsJan 19, 2024

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Product HuntOn track for Day 1 leaderboard · Strong signals: new · 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.

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

81%81% 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: platform · Missing: plus, intuitive, reviews

49%49% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

44%44% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

34%34% 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

11%11% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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