Pregonero

LLM-filtered tech digest delivered to Telegram every morning.

There is too much noise on the internet to keep up with the tech industry. Pregonero filters it for you: every morning receive a digest in Telegram with the releases, tools and technical articles that are truly worth it — no basic tutorials, no business news, no noise.

RSS feeds → fetch → deduplicate → LLM filter → Telegram digest

How it works

1. Fetch — fetches items from 11 RSS/Atom sources (Hacker News, GitHub Blog, Changelog, Reddit, dev.to, Lobsters, GitHub Trending). Items older than 24h are discarded.
2. Deduplication — ignores any already-processed URL, stored in a local SQLite database.
3. Filter — sends each new item to Groq (llama-3.3-70b-versatile), which approves or rejects based on a strict classifier aimed at senior AI engineers.
4. Publication — all approved items are grouped into a single Telegram digest with 3 bullets each: what it is, why it matters and a concrete use case. Output is in Spanish.
5. Storage — each processed item (approved, rejected or errored) is saved in SQLite to avoid reprocessing.

Requirements

• Bun >= 1.0
• Groq API key
• Telegram bot token + chat ID

Installation

# Install dependencies
bun install

# Set up environment
cp .env.example .env
# Edit .env and fill in GROQ_API_KEY, TELEGRAM_BOT_TOKEN, TELEGRAM_CHAT_ID

Usage

# Start the scheduler (runs immediately then follows CRON_SCHEDULE)
bun start

# Run the pipeline once and exit
bun run-now

# Development mode (auto-restarts on file changes)
bun dev

# Type checking
bun typecheck

Environment variables

Variable	Default	Description
GROQ_API_KEY	—	Groq API key
TELEGRAM_BOT_TOKEN	—	Bot token from @BotFather
TELEGRAM_CHAT_ID	—	Numeric chat ID where the digest is published
CRON_SCHEDULE	0 8 * * *	Cron expression (default: 8am daily)
MAX_AI_CALLS_PER_RUN	20	Maximum AI calls per run
AI_CALL_DELAY_MS	1000	Pause between consecutive AI calls (ms)
DB_PATH	./data/pregonero.db	SQLite database path
DRY_RUN	false	Skips Telegram sending and DB writes
LOG_LEVEL	info	Log level: debug, info, warn, error

Feeds

Configured in feeds.json as an array of { url, weight } objects. Higher weight means more proportional slots per run via weighted round-robin.

Default sources:

• Hacker News Show HN and top items
• GitHub Blog
• Changelog News
• Reddit: r/programming, r/MachineLearning, r/LocalLLaMA
• dev.to: tools & AI tags
• Lobsters (programming)
• GitHub Trending (daily)

CI / Scheduled execution

A GitHub Actions workflow (.github/workflows/daily.yml) runs the pipeline automatically at 7:00 UTC every day (8:00 CET). The SQLite database is persisted between runs via actions/cache to maintain deduplication state.

Required repository secrets: GROQ_API_KEY, TELEGRAM_BOT_TOKEN, TELEGRAM_CHAT_ID.

The workflow also supports manual triggering from the Actions tab.

Project structure

src/
  index.ts      — entry point, cron scheduler
  runner.ts     — main pipeline orchestrator
  fetcher.ts    — RSS fetch and parsing (24h filter)
  ai.ts         — LLM classifier with Groq
  telegram.ts   — digest formatting and Telegram delivery
  db.ts         — SQLite persistence
  config.ts     — environment variable configuration
  logger.ts     — structured logger
feeds.json      — RSS feed list with weights
.github/
  workflows/
    daily.yml   — scheduled GitHub Actions workflow

Tech stack

• Runtime: Bun
• AI: Groq (llama-3.3-70b-versatile) via groq-sdk
• Telegram: grammY
• Database: Bun SQLite (built-in)
• Feeds: rss-parser
• Scheduling: node-cron / GitHub Actions