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I Made GIF Hosting Open Source Self-Hosted GIF Platform

Hacker News

I Made GIF Hosting Open Source Self-Hosted GIF Platform

Key Features Generous File Size Limit: Support for GIFs up to 25MB (easily configurable to more as code is open source, you just need to change a single environment variable MAX_FILE_SIZE=25000000) Bulk Upload Support: Upload multiple GIFs at once Privacy Controls: Choose between public and private GIFs Multiple Sharing Formats: Direct links HTML embed codes Markdown-ready links Social media sharing Dark/Light Theme: Easy on the eyes, regardless of your preference Modern UI: Clean, responsive design that works on all devices Search Functionality: Quickly find your GIFs Secure Authentication: Protect your content Technical Stack The platform is built with modern technologies: Frontend: React + TypeScript + Chakra UI Backend: Node.js + Express Database: PostgreSQL with Drizzle ORM Storage: Local file system with automatic cleanup Container: Docker for easy deployment Security: Rate limiting, JWT authentication, and XSS protection

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Actual performance

1points
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
86%86% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: dock, single, code · Missing: mac, agents, macos
59%59% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: open source, 000, io · Missing: https docs, excited, just released
48%48% 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: platform, host · Missing: plus, intuitive, reviews
46%46% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
27%27% 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
14%14% 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
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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