I built an AI tool to generates image slideshows and UGC-style videos

Hacker News

Hi HN, I built Lungo, a tool that generates image-based slideshows and UGC-style videos using AI. The system creates visuals and assembles them into structured, shareable content based on a text prompt. What it does: • Generates images from prompts using a custom diffusion model • Constructs slideshows or short-form videos with transitions and optional voiceover • Handles layout, text generation, and multi-language support • Outputs are consistent in resolution and format, ready for distribution I built with a React, firebase, OpenAI, Runway and ffmpeg. Feedback and questions welcome.

Visit product View on Hacker NewsMay 27, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: model, visual, openai · Missing: mac, agents, macos

72%72% 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

66%66% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

48%48% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

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

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

30%30% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

20%20% 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

5%5% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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