Autonomous content discovery and delivery engine — with primitives for principal-shaped agent capabilities
Project description
🪨 Pebbles
A smart content discovery engine that brings you interesting things from across the web — like a penguin bringing pebbles to its mate.
Pebbles monitors multiple sources (Hacker News, Reddit, RSS feeds, YouTube, Letterboxd), matches content against your interests using keyword or semantic matching, and delivers personalized recommendations via Telegram or email. Set daily limits, priority interests, and negative keywords to stay informed without getting overwhelmed.
Quick Start
Installation
pip install pebbles-core
Configuration
Create ~/.config/pebbles/config.yaml:
recipients:
- name: "Jake"
telegram_id: 123456789
max_daily_pebbles: 3
interests:
- tags: ["surfing", "ocean"]
keywords: ["surf", "wave", "ocean", "swell"]
priority: 2
- tags: ["climbing"]
keywords: ["climbing", "bouldering", "crag"]
negative_keywords: ["indoor"]
priority: 1
sources:
hackernews:
enabled: true
reddit:
enabled: true
subreddits: ["surfing", "climbing"]
delivery:
telegram:
bot_token: "your-bot-token-here"
matching:
use_semantic_matching: false
semantic_threshold: 0.35
Run
# One-time fetch
pebbles run
# Continuous loop (checks every 30 minutes)
pebbles run --loop
Configuration Reference
Recipients
Each recipient defines who receives pebbles and what they care about:
recipients:
- name: "Jake" # Display name
telegram_id: 123456789 # Optional: Telegram user ID
email: "jake@example.com" # Optional: Email address
max_daily_pebbles: 3 # Daily limit (default: 5)
interests:
- tags: ["surfing"] # Category tags
keywords: ["surf", "wave"] # Match keywords
negative_keywords: ["pool"] # Exclude keywords
priority: 2 # 1=normal, 2=high, 3=must-have
At least one of telegram_id or email must be provided per recipient.
Sources
Hacker News
sources:
hackernews:
enabled: true
sources:
reddit:
enabled: true
subreddits:
- "surfing"
- "climbing"
- "technology"
RSS Feeds
sources:
rss:
enabled: true
feeds:
- "https://example.com/feed.xml"
- "https://blog.example.com/rss"
YouTube
sources:
youtube:
enabled: true
api_key: "your-youtube-api-key"
queries:
- "surf documentary"
- "climbing training"
Letterboxd
sources:
letterboxd:
enabled: true
usernames:
- "username1"
- "username2"
Delivery
Telegram
delivery:
telegram:
bot_token: "your-telegram-bot-token"
delivery:
email:
smtp_host: "smtp.gmail.com"
smtp_port: 587
smtp_user: "you@gmail.com"
smtp_password: "your-app-password"
smtp_from: "Pebbles <you@gmail.com>" # Optional
Matching
matching:
use_semantic_matching: false # Enable AI-powered matching
semantic_threshold: 0.35 # Similarity threshold (0.0-1.0)
Semantic matching uses sentence-transformers (all-MiniLM-L6-v2) for contextual understanding. Falls back to keyword matching if unavailable.
Deployment
Docker
docker run -d \
--name pebbles \
-v $(pwd)/config:/root/.config/pebbles \
-v $(pwd)/data:/root/.local/share/pebbles \
--env-file .env \
pebbles-core:latest
Docker Compose
services:
pebbles:
image: pebbles-core:latest
volumes:
- ./config:/root/.config/pebbles
- ./data:/root/.local/share/pebbles
env_file: .env
restart: unless-stopped
Create .env:
TELEGRAM_BOT_TOKEN=your-token
SMTP_PASSWORD=your-password
Roadmap
Pebbles was built in phases:
- Phase 1: Core engine + HackerNews source
- Phase 2: Production hardening (logging, retries, error handling)
- Phase 3: Multi-source expansion (Reddit, RSS, YouTube, Letterboxd)
- Phase 4: Smart matching (semantic understanding, priority scoring, frequency caps)
- Phase 5: Polish + ship (email delivery, Docker deployment, docs)
Future ideas: Mastodon source, Discord delivery, web dashboard, collaborative filtering.
Contributing
See CONTRIBUTING.md for how to add sources, delivery adapters, or improve matching.
License
MIT
Project details
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