Knowbase – personal knowledge base powered by ChatGPT

Hacker News

Hello all, I always loved curating my 'knowledge base' catalog on desktop. Discovering AI capabilities last year left me with no choice but to create... an AI-powered knowledge base. I like to think about it as Dropbox and ChatGPT combined. It can also transcribe your recordings. To build this I used FastAPI and AngularJS. I also use Langchain for dealing with with LLMs and Modal for deployment and scalability. Happy to hear if someone finds it usefull :).

Visit product View on Hacker NewsOct 17, 2023

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

91%91% 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

57%57% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released

47%47% 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

31%31% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

13%13% predicted probability of success on BetaList, based on ML models trained on real launch data.

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

12%12% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Correct prediction on native model

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