Open-Source Discord Bot That Answers Questions from Your Developer Docs

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I’ve been working on Ragpi, an open-source AI assistant API that answers questions by pulling information from your developer docs, GitHub issues and READMEs. I recently added a Discord integration, allowing you to deploy a Ragpi-powered bot in your server so your community can get relevant, documentation-backed answers on the spot. It’s still a work in progress, and I’d really appreciate any feedback or ideas you might have. If you’re curious, here are some links: Main Ragpi Repo: https://github.com/ragpi/ragpi Discord Bot Repo: https://github.com/ragpi/ragpi-discord Discord Integration Docs: https://docs.ragpi.io/integrations/discord Thanks for checking it out, and let me know what you think!

Visit product View on Hacker NewsFeb 13, 2025

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

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

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

68%68% predicted probability of success on Hacker News, based on ML models trained on real launch data.

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TrustMRRFits verified-revenue profile · Strong signals: answers · Missing: mobile apps, ios, personal

60%60% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

37%37% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

25%25% 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

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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.

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