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larafeed
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A good looking feed reader for the web
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larafeed
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# Larafeed <!-- badges -->  Larafeed is a simple feed reader. ## Features - A pleasant and snappy UI - Entries are marked as read when you view them - Entry links open in a new tab - Keyboard shortcuts and quick feed navigation - RSS, Atom, RDF, and JSON Feed support - Background feed updates - Failures are stored and displayed in the UI - Custom feed names and categories - Entry filtering per subscription by title, content, or author - Read, starred, and archived entries - AI-generated summaries - Favicon display with automatic dark-mode styling - OPML import and export - Google Reader and Fever API support with revocable app tokens - Support is partial, but works with [Reeder Classic](https://reederapp.com/classic/) - Passkey-only private access - Estimated reading time for each entry ### Screenshots & demo #### Reader view  #### Demo of the LLM summary generation <https://github.com/user-attachments/assets/0553f893-cc5a-4efa-b098-1b1e10545698> #### Demo of the feed refreshing UX <https://github.com/user-attachments/assets/a420f8cd-d306-4a0d-afe3-d391852055ad> #### Demo of the quick add feed from a bookmark <https://github.com/user-attachments/assets/bb266745-5d16-4d06-9534-653df38212bc> ## Technical overview ```mermaid flowchart LR Browser["React + Mantine<br/>React Router + TanStack Query"] Worker["Cloudflare Worker<br/>Hono + Effect"] D1[(D1)] Queues[Cloudflare Queues] Cron[Cron Triggers] Images[Cloudflare Images] AI[AI Gateway] Gemini[Gemini] Feeds[Feed publishers] Browser <--> Worker Worker <--> D1 Worker <--> Queues Cron --> Worker Worker --> Images Worker --> AI --> Gemini Worker --> Feeds ``` - The TypeScript backend runs on [Cloudflare Workers](https://workers.cloudflare.com/) with [Hono](https://hono.dev/) for routing and [Effect](https://effect.website/) for application logic. - The frontend uses React with the amazing [Mantine](https://mantine.dev/) components and hooks, React Router, and TanStack Query. - D1 stores users, subscriptions, entries, sessions, and durable job state. - Queues process feed discovery, refreshes, and favicons one feed at a time. - Feed requests use conditional HTTP headers to avoid downloading unchanged content. - Cloudflare Images proxies article images for privacy and performance. - AI summaries use Gemini through Cloudflare AI Gateway and are cached in D1. - Google Reader and Fever APIs are implemented from scratch. - I relied heavily on the implementations in [FreshRSS](https://github.com/FreshRSS/FreshRSS/tree/edge/p/api) and [Miniflux](https://github.com/miniflux/v2/tree/main/internal). - Using [Reeder Classic](https://reederapp.com/classic/) with Miniflux as a backend, I inspected the API calls with [mitmproxy](https://mitmproxy.org/) to reverse-engineer the protocols. ## Deploy to Cloudflare [](https://deploy.workers.cloudflare.com/?url=https://github.com/angristan/larafeed) The installer provisions the Worker, D1 database, and Queues, then applies all D1 migrations. It asks for the public HTTPS origin and a private operator secret used to create the first administrator enrollment link. See the [deployment guide](docs/deployment.md) for administrator enrollment and optional integrations. Operational and reader-client details are in the [operations](docs/operations.md) and [compatibility API](docs/compatibility-apis.md) guides. ## Development Requirements: Node.js 24, npm, and Bun. ```bash npm ci npx playwright install chromium cp .dev.vars.local.example .dev.vars npm run d1:migrate:local npm run dev ``` Run the complete validation suite with `npm run validate`. ## License Larafeed is licensed under the [MIT license](LICENSE).
