A

A faster way to set up Flowise and Qdrant for AI agent development

Hacker News

A faster way to set up Flowise and Qdrant for AI agent development

I’ve been experimenting with Flowise and Qdrant to build AI agents, and I wanted to share a setup that eliminates the usual manual infrastructure deployment. Instead of manually doing cloud configuration and database setup, I used Qubinets to spin up everything in less than 5 minutes. How I did it? - I created a project in Qubinets (No cloud account needed for quick testing). - Selected Flowise AI (for building AI agents) and Qdrant (for vector storage). - Clicked Instantiate—Qubinets handled the full deployment. - Waited a few minutes, then logged into Flowise and started building. Why This is Useful - No manual setup—everything is pre-configured. - Great for prototyping—test AI agents fast without worrying about infrastructure. - Scalable—switch to a persistent cloud setup when moving to production. Here's the full breakdown -> https://youtu.be/yEJyyjbHsPc?si=dTVF5jGVVWq5Wna5

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Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent · Missing: mac, macos, cursor
86%86% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
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Indie HackersFits the IH revenue-focused audience · Strong signals: created, started · Missing: supports, reddit linkedin, podcasting
80%80% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal
43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
33%33% 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.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
29%29% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
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