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NextJS starter to build apps with image / text gen / vector search

Hacker News

NextJS starter to build apps with image / text gen / vector search

Hi HN! I'm Aryan, the maker of TemplateAI. I tinkered with a bunch of AI side projects in 2023 and realized I'm repeating a lot of the same stuff: calling text and image gen models, setting up vector search and generating embeddings, storing everything, building components for chats and generated content. Plus dozens of hours spent building the rest of stack – auth, payments, dashboard and landing etc. I packaged it all into one NextJS template so others can skip past the boilerplate and go straight to the AI features. The template is designed for three big use cases: image generation, text generation, and vector search / retrieval. It uses a slightly opinionated stack: TypeScript-first with NextJS (App router), Supabase as the database layer, OpenAI's LLMs for text generation, Replicate API for image generation, and tools like LangChain and Vercel ai sdk to simplify RAG and response streaming. For authentication and vector databases, I stuck with Supabase Auth and pgvector to avoid adding yet another piece to an already-complicated stack. (There's certainly other vectorstores out there that would speed up retrieval that I'm considering adding to the template.) Also wanted to make sure everything's launch-friendly, so I added in landing page components, a Stripe integration, and more. Please check out TemplateAI and share your thoughts and feedback, thanks!

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Product HuntOn track for Day 1 leaderboard · Strong signals: model, apps, stripe · Missing: mac, agents, macos
90%90% 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
88%88% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Strong signals: plus, friendly · Missing: platform, intuitive, reviews
55%55% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
51%51% 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: apps · Missing: mobile apps, ios, personal
42%42% 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
19%19% 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
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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