{"repo":"philippdubach/rss-swipr","free":true,"listed":false,"github":"https://github.com/philippdubach/rss-swipr","clone":"git clone https://github.com/philippdubach/rss-swipr.git","description":"An intelligent RSS feed reader with a Tinder-style swipe interface that learns your preferences and recommends articles you'll love. Powered by a hybrid ML model achieving 75.4% ROC-AUC on personalized recommendations","language":"Python","stars":10,"topics":["machine-learning","random-forest","reccommendation","rss","rss-aggregator","rss-reader"],"license":"MIT","category":"machine-learning","readme_excerpt":"RSS Swipr A swipe-based RSS reader that learns your preferences. Swipe through articles to train a personalized ML model that recommends content you'll enjoy. Quick Start Open http://127.0.0.1:5000 in your browser. Usage 1. Add RSS Feeds 1. Click Settings (gear icon) 2. Go to Feeds tab 3. Paste CSV or upload a file: 4. Click Refresh Feeds to fetch articles 2. Swipe Articles - Swipe right = Like - Swipe up = Neutral - Swipe left = Dislike The app tracks your votes, link clicks, and reading time to build training data. 3. Train Your Model Once you have enough votes (50+ recommended): 1. Export : Settings → Export → Download Training Data (CSV) 2. Train : Open the Google Colab notebook, upload your CSV, run all cells 3. Upload : Settings → Models → Upload the generated .pkl file 4. Activate : Click \"Activate\" to use your model for recommendations 4. Backup & Restore To use your training data on a fresh install: 1. Keep your training data.csv from the export step 2. On new install: import feeds, refresh to fetch articles 3. Settings → Export → Import Training Data (upload your CSV) This restores your voting history by matching articles via URL. How It Works - Thompson Sampling : 80% exploit (best predictions), 20% explore (diversity) - Hybrid Features : Combines text analysis with behavioral signals - No cloud dependency : All data stays local in SQLite databases Project Structure Requirements - Python 3.8+ - Dependencies: Flask, pandas, scikit-learn, xgboost, feedparser License ","default_branch":null,"files":null,"tree":[],"storefront":"/r/philippdubach","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/philippdubach/rss-swipr/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}