She was Busy for a Newspaper read: Now reading it in a few minutes

Aditi — Mon, 05 Oct 2026 06:46:48 +0000

This is a submission for the Hacktoberfest Weekend Challenge: Build for a Friend

What I Built

Current Daily is a free daily study pack for my friend Asha, who is preparing for the UPSC Civil Services exam. Reading a whole newspaper every day takes hours, and most of it is not exam material. So I built her a daily current affairs digest that can generate 15 news points and 10 historical events of the day and send them on Telegram. In the evening, it will remind her to revise it.

Every morning, the app reads headlines from PIB, The Hindu, and BusinessLine, keeps the points that matter for UPSC, tags each one with a GS paper (GS1 to GS4) and a topic, and adds up to 10 historical events for the date. The pack is posted to a public Telegram channel and shown on a website that can be filtered by GS paper. In the evening, a short revision message goes out with recent points. Anyone can join the channel, with no sign-up.

Every point links to its source article, so it can be checked in seconds.

Demo

Website: https://current-daily.vercel.app/
Telegram channel: https://t.me/Current_Daily_Reminder

I handed it to Asha, and she said it was nice and really less time-consuming than before and she could read it in the short break during her study sessions.

Code

Esu05 / Current-Daily

An app to bring you current affairs and historical event of the day.

Current Daily

A free daily study pack for everyone. Every morning it collects the day's news, keeps the points that matter for the Civil Services exam, adds important historical events for the date, and delivers everything on a website and a Telegram channel. Every evening it sends a short revision reminder.

The filtering and summarising is done by Gemma 3 (4B), an open-weight model that runs through Ollama. There is no paid API, no API key, and no cost per run.

For readers

You do not need to install anything.

Open the website to read the day's pack and filter it by GS paper (GS1 to GS4).
Join the Telegram channel to get the pack every morning and a revision reminder every evening.
Tap the source link on any point to read the full article.

This is a first-pass filter, not a replacement for reading the newspaper or…

View on GitHub

How I Built It

Model: Gemma 3 (4B), an open-weight model, running locally through Ollama.
Pipeline: Node.js scripts collect RSS headlines and drop obvious junk (city news, sports, crime, Hindi headlines). Each remaining headline goes to Gemma on its own. Gemma gives a 1 to 5 usefulness score and picks a topic, and items scoring 3 or more are kept, up to 15.
GS tags are decided by code, not the model. Gemma picks a topic such as Polity or Economy, and a lookup table maps it to a GS paper. Small models were unreliable at choosing the paper directly.
Links cannot be mismatched. Each URL comes from the feed item that was screened, never from the model. An early version let the model pick items by number from one long list, and it attached the wrong links to summaries. Screening one headline per call fixed that.
History: Wikipedia's "On this day" feed, filtered to remove disasters and entertainment, then Gemma picks up to 10 events useful for GS1.
Automation: A GitHub Actions workflow installs Ollama, pulls Gemma, builds the pack, commits it, and posts to Telegram every morning. A second workflow sends the evening revision.
Frontend: React, Vite and Tailwind, deployed on Vercel. Each daily commit redeploys the site.

Why Does Open Innovation Matter?

It costs nothing to run. There is no API key and no per-call bill, which makes a daily job possible on a student budget.
Nothing leaves my own runner. The model runs inside the job itself, and no reader data goes to a third-party AI service.
It is swappable. Changing the model is one line. A larger model judges relevance better, and a fine-tuned one could follow a specific exam style or write in Hindi.
Anyone can fork it and adapt the feeds and rules for their own exam.

Where it fell short: a 4B model is lenient on borderline items, sometimes returns broken output, and can garble numbers and dates. I handle that with rules around the model, a blocklist that grows from real output, and a source link on every card. Indian Express blocks GitHub's servers, so it is not in the automated run.

Prize Categories

Best Use of Gemma
Best Use of GitHub Copilot (project automated with GitHub Actions)

DEV Community: Aditi