LibreAI – Private AI chat app with open-source models (no ChatGPT)

Hacker News

I built LibreAI to provide a private, self-hostable alternative to ChatGPT using open-source models like Mistral, LLaMA 3, and Phi via Ollama. It's fast, streams responses in real-time (via HTMX), and has zero telemetry. There’s a free tier to try it out and a paid option to support development. Would love feedback, feature requests, or model suggestions! Built with Go Fiber + HTMX, hosted on my own infra. No JavaScript frontends here :) Live at: https://libreai.app

Visit product View on Hacker NewsApr 16, 2025

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Actual performance

2points

1comments

Did not reach leaderboard

Launch Intel predictions

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

93%93% 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 · Missing: supports, reddit linkedin, podcasting

76%76% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

56%56% 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: host · Missing: plus, platform, intuitive

38%38% 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

35%35% 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

20%20% 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, paid · Missing: web3, crypto, cryptocurrency

7%7% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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