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I made an AI short-form video generator for TikTok

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I made an AI short-form video generator for TikTok

I made an AI short-form video generator for TikTok, YouTube Shorts and Instagram Reels. Everything is automated: script, narration, images, captions sync and the editing. It reduces time to create faceless content from hours down to minutes, and efforts for the user down to a prompt. Think ChatGPT to create short-form videos. Before getting into how it's built, let me give some context. Here's how I go the idea. While scrolling through my YouTube feed, I suddenly started noticing more and more fully AI generated content. More precisely, I'm talking about the script, the narration, the images, the captions… It all seemed like it was made using OpenAI, StabilityAI and other popular models. I dug deeper and got to learn how there are people making money off of faceless channels and theme pages that are essentially social media accounts centered around 1 specific topic (memes, motivational content, travel, etc.) I got the prototype done within 2 days. And I'm not gonna lie, I was kinda shocked how good this all was. I ended up using Next.js hosted on a VPS with SQLite as the database. I also started using Linear to keep track of all tasks and it was such a breeze to work with their Mac app. The pipeline is a bunch of Python scripts calling APIs. The biggest technical challenge that I foresee is how much RAM combining 1 video takes. I'm using ffmpeg and it goes up to 1.1Gb per video. I'll definitely have to look into compressing the AI generated images beforehand and also eventually store them probably on Cloudflare to free up storage space.

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, model, user · Missing: agents, macos, agent
88%88% 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 · Strong signals: started · Missing: supports, reddit linkedin, podcasting
84%84% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: video · Missing: mobile apps, ios, personal
62%62% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, pipe, io · Missing: https docs, excited, just released
46%46% 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 · Strong signals: host · 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: arr · Missing: mrr, revenue, profit
26%26% 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.

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