Gromit, the OSS, AI powered assistant for your website/app

Hacker News

Hello HN, Today we are launching Gromit, an open-source AI powered assistant for your website. Gromit digests your documentation and using redis with OpenAI embeddings creates an assistant that your customers can interact with. You can easily use Gromit to create a new way for your customers to interact with your documentation. It not only will give concise, conversational answers based on your documentation, but it also gives useful examples. The github repo for gromit: https://github.com/releasehub-com/gromit The github repo for an example using gromit: https://github.com/releasehub-com/gromit-example Blog post/s with technical details of Gromit: https://release.com/blog/gromit-an-open-source-ai-assistant-... https://release.com/blog/training-chatgpt-with-custom-librar... We were inspired by what supabase did with the creation of their own ai powered assistant here: https://supabase.com/blog/chatgpt-supabase-docs but we wanted to make one that used a more standard backend in redis and ruby. Gromit is super new; please give it a shot and make pull requests, leave comments, we would love to chat with you about it!

Visit product View on Hacker NewsMay 11, 2023

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Product HuntOn track for Day 1 leaderboard · Strong signals: new, chatgpt, openai · 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 · Missing: supports, reddit linkedin, podcasting

70%70% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

64%64% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

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

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

14%14% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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