Helios – Java Client for OpenAI Compatible REST APIs

Hacker News

Hey HN, We open sourced our internal project, Helios, a lightweight Java client for interacting with OpenAI chat completion-compatible REST APIs. Why Helios? Helios avoids external dependencies – with one exception: Jackson. After all, trying to handle JSON without Jackson is like attempting stand-up comedy without a punchline. Helios was initially developed to address our internal needs at Singular, but we’re excited to contribute it back to the community. We're looking forward to any feedback or contributions that can help make it even more useful and feature complete. Cheers, Uday

Visit product View on Hacker NewsMar 26, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: openai, apis, open · Missing: mac, agents, macos

83%83% 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: ios, compatible · Missing: supports, reddit linkedin, podcasting

80%80% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

66%66% 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

40%40% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

32%32% 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

15%15% 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

5%5% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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