# SlothScroll: I Taught Gemma to Read Instagram So I Never Have To > Source: > Published: 2026-10-24 08:01:27+00:00 *This is a submission for the [Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady](https://dev.to/challenges/hacktoberfest-week3-2026-10-19)* ## What I Built Every morning I opened Instagram "just to catch up", and every morning the feed won. One quick check became another, with ads, reposts and giveaways in between. **SlothScroll** is my lazy fix. It's a morning digest of the Instagram pages I follow. Once a day a cloud browser visits those pages for me. **Gemma**, Google's open-weight model, reads every new post and writes a one-line gist. It also sorts the post into a topic (Sports, Science, Finance, Tech…) and quietly drops ads, reposts and giveaways. What I get is **one calm page and one email**, grouped by topic, with the 1–3 posts actually worth opening. I read it in about two minutes with my coffee, then close the tab. I never open Instagram. Who gets to be lazier? Anyone who follows news, sports or creator pages to *stay informed*, not to scroll. ## Demo 🔗 **Live:** [https://slothscroll-web-ngb7.onrender.com](https://slothscroll-web-ngb7.onrender.com) What you'll see in the video: - **Today's edition:** a greeting, the "scrolling saved" number, topic tabs, and Gemma's summary for each topic with its top picks - **The archive** , an RSS feed per page, and dark mode - **The morning email** , the same edition delivered to my inbox ## Code The latest code is on the [`SlothScroll` branch](https://github.com/452Harsh/SnoozeFeed/tree/SlothScroll). ## How I Built It - **Gemma (`gemma-4-26b-a4b-it`)** is the brain. It runs through an OpenAI-compatible client set by environment variables (`AI_BASE_URL` ,`AI_MODEL` ), so the same code can point at a hosted endpoint or, by changing one variable, a local Ollama. I use it for three jobs: 1. **Per post:** a one-line gist, the post's topic, and whether it's an ad, repost or giveaway. All three come back as JSON from a single call. When a caption is only emojis and hashtags, Gemma looks at the image instead. 2. **Per page:** a fallback category when I don't set one. 3. **Per topic:** a 2–3 line summary plus the posts worth opening. - **Browserbase + Stagehand** give it a real browser. I log in once through Browserbase's live view, and a persisted context keeps that session for daily runs. - **MongoDB Atlas** is the data layer. The cron job writes, the website reads, and a unique index on the post URL means a post is never processed twice. - **Render** runs everything from one`render.yaml` Blueprint: a**cron job** for the daily pipeline and a**web service** for the site. Every secret is`sync: false` , so none live in the repo. - **The website** is server-rendered HTML on Hono, with no frontend framework. It has light and dark mode, works on mobile, and loads quickly. - **ElevenLabs** narrated the demo video. **Slow and steady by design:** one run per day, public pages only, visited one at a time with random pauses. A page that fails is noted, and the edition still ships. If Instagram asks for a login, SlothScroll **stops and tells me** instead of trying to get around it. ### What broke (and how I fixed it) - **Gemma was slow for this job.** A demo run took about 4 minutes because the model reasoned before every answer. Setting`reasoning_effort: "minimal"` brought it down to**about 20 seconds** , with the same quality for one-line gists. - **Everything was "News".** Topics were assigned per page, so a football page's posts and an IPO story all landed in News. Now Gemma chooses a topic**per post** in the same call, with no extra requests. On my real feed the same 16 posts went from one topic to five. - **The browser died mid-run.** Browserbase sessions end after 5 minutes by default, and a full run takes longer. Asking for a 30-minute session fixed it. - **Half-emoji headlines.** Shortening captions sometimes cut an emoji in half and left "�". The page now cleans those characters before showing them. ## Why Does Open Innovation Matter? What you follow says a lot about you. Your reading habits are personal, and an open-weight model means **this digest doesn't have to depend on one company's closed API**: - **I choose where it runs.** Gemma is reached through a plain OpenAI-compatible endpoint, so switching providers is an environment-variable change. The client is built to switch to a local Ollama the same way, so the posts never have to leave my machine. - **It's cheap enough to run every day forever.** A small open model is plenty for one-line gists and topic tags. It's a daily habit, not a premium feature. - **It's inspectable and forkable.** The prompts, the pipeline and the model are all open, so anyone can adapt SlothScroll to their own pages, language or topics. ## The Lazy Payoff From a real run this week, using a deliberately conservative estimate of **8 seconds per post**: - **16 posts** from my pages became**5 topics** and one page, about**2 minutes of scrolling saved** that day. - **0 times** I opened Instagram. The real win is bigger than the 8-second math. One "quick check" usually turns into twenty minutes. SlothScroll ends the session before it starts, and it scales with the pages you follow: I've since added six more (The Verge, National Geographic, CNBC, Tasty, Netflix and 9GAG). ## Prize Categories - **Best Use of Gemma:** Gemma writes the gists, picks the topics, filters ads and summarizes each topic. - **Best Use of Render:** a Blueprint with a cron job for the agent pipeline and a web service for the front end. - **Best Use of Browserbase:** Stagehand drives a real browser with a persisted login, as a repeatable daily workflow. - **Best Use of MongoDB Atlas:** the database behind an app built on an open-weight model. - **Best Use of ElevenLabs:** narration for the demo video.