version: '3.8'

# SearXNG Metasearch Engine
# Purpose: Privacy-focused metasearch aggregating 246+ search engines
# Port: 8087 (HTTP API)
# GPU: NO - Pure CPU application
# Storage: Minimal (config only, no data persistence)
# Integration: Core-AI service tool for web search capability

services:
  searxng:
    image: searxng/searxng:latest
    container_name: searxng
    restart: unless-stopped
    ports:
      - "8087:8080"  # HTTP API (JSON format enabled)
    volumes:
      # Mount config directory (will be auto-populated on first run)
      - /home/jpmschweitzer/docker-data/searxng:/etc/searxng:rw
    environment:
      - TZ=Europe/Amsterdam
      - SEARXNG_BASE_URL=http://searxng:8087/
      # Valkey/Redis configuration for result caching (using shared Redis DB 5)
      - SEARXNG_VALKEY_URL=redis://redis-shared:6379/5
      # Enabled output formats (JSON required for API access)
      - SEARXNG_SETTINGS_FORMATS=html,json
    cap_drop:
      - ALL
    cap_add:
      - CHOWN
      - SETGID
      - SETUID
    logging:
      driver: "json-file"
      options:
        max-size: "10m"
        max-file: "3"
    deploy:
      resources:
        limits:
          cpus: '1.0'
          memory: 512M
        reservations:
          memory: 128M
    networks:
      - docker-dataplane
    healthcheck:
      test: ["CMD", "wget", "--no-verbose", "--tries=1", "--spider", "http://localhost:8080/healthz"]
      interval: 30s
      timeout: 10s
      retries: 3
      start_period: 40s

networks:
  docker-dataplane:
    external: true
    name: docker-dataplane

# SearXNG Overview:
# - Metasearch engine: Aggregates results from 246+ search sources
# - Privacy-first: No tracking, no profiling, no data collection
# - Multi-format: HTML (web UI), JSON (API), CSV, RSS
# - Customizable: Enable/disable specific engines per category
#
# Search Categories:
# - general: Web search (Google, Bing, DuckDuckGo, etc.)
# - images: Image search
# - videos: Video search
# - news: News articles
# - map: Geographic/location
# - music: Music/audio
# - it: Programming/technical (StackOverflow, GitHub, docs)
# - science: Academic (arXiv, PubMed, Semantic Scholar)
# - files: File repositories
# - social media: Social platforms
#
# Setup Instructions:
#
# 1. Create configuration directory:
#    mkdir -p ~/docker-data/searxng/config
#
# 2. Deploy stack:
#    docker-compose -f searxng.yml up -d
#
#    Note: First run will auto-generate settings.yml with secret key
#
# 3. Stop container to edit config:
#    docker stop searxng
#
# 4. Enable JSON format in settings.yml:
#    Edit ~/docker-data/searxng/config/settings.yml
#    Find the 'search:' section and set:
#      formats:
#        - html
#        - json
#
# 5. Restart container:
#    docker start searxng
#
# 6. Verify deployment:
#    # Web UI test:
#    curl http://localhost:8087/
#
#    # JSON API test:
#    curl "http://localhost:8087/search?q=python&format=json" | jq '.results[0]'
#
#    # Health check:
#    curl http://localhost:8087/healthz
#
# API Usage:
#
# Basic search:
#   GET http://searxng:8080/search?q=query&format=json
#
# With category filter:
#   GET http://searxng:8080/search?q=machine+learning&format=json&categories=science
#
# With language:
#   GET http://searxng:8080/search?q=query&format=json&language=en
#
# With time range:
#   GET http://searxng:8080/search?q=news&format=json&time_range=day
#
# Available categories:
#   general, images, videos, news, map, music, it, science, files, social_media
#
# Time ranges:
#   day, week, month, year
#
# Response format (JSON):
# {
#   "query": "search term",
#   "results": [
#     {
#       "url": "https://example.com",
#       "title": "Page title",
#       "content": "Description snippet",
#       "engine": "google",
#       "score": 1.0
#     }
#   ],
#   "suggestions": ["related", "searches"],
#   "number_of_results": 42
# }
#
# Integration with Core-AI:
#
# Add to services/core-ai/src/tools/local.py:
#
#   @register_tool
#   async def web_search(query: str, category: str = "general") -> str:
#       """Search the web using SearXNG metasearch engine."""
#       response = await httpx.get(
#           "http://searxng:8080/search",
#           params={"q": query, "format": "json", "categories": category},
#           timeout=10.0
#       )
#       results = response.json()["results"][:5]
#       return "\n\n".join([
#           f"[{r['title']}]({r['url']})\n{r.get('content', '')}"
#           for r in results
#       ])
#
# Performance Tuning:
#
# Response times: 2-5 seconds (aggregating multiple sources)
# Redis caching: Reduces duplicate queries (DB 5 on redis-shared)
# Engine selection: Disable slow engines to improve speed
#
# Edit settings.yml to disable slow engines:
#   engines:
#     - name: slowengine
#       disabled: true
#
# Resource Usage (expected):
#   CPU: ~0.2-0.5 cores (varies with query load)
#   RAM: ~150-300MB (depends on cache size)
#   Disk: ~10-50MB (config only, no data storage)
#   Network: Variable (depends on upstream engine responses)
#
# Redis Database Allocation:
#   DB 5: SearXNG result cache
#
# Security:
#   - Dropped all capabilities except essential (CHOWN, SETGID, SETUID)
#   - No data persistence (privacy by design)
#   - Can run behind Nginx Proxy Manager for HTTPS
#   - Optional Tor support (requires additional config)
#
# Monitoring:
#
# View logs:
#   docker logs -f searxng
#
# Check engine stats:
#   curl http://localhost:8080/stats
#
# Check health:
#   docker exec searxng wget -q -O- http://localhost:8080/healthz
#
# Engine Configuration Tips:
#
# To optimize for AI/LLM use cases, consider enabling these engines:
#   - General: google, bing, duckduckgo, brave
#   - Technical: stackoverflow, github, devdocs, mdn
#   - Academic: arxiv, pubmed, semantic_scholar, google_scholar
#   - Documentation: readthedocs, man (Linux man pages)
#
# Disable to improve speed:
#   - Slow engines (check /stats page)
#   - Engines you don't need (social media if not relevant)
#   - Engines with frequent timeouts
#
# Advanced Configuration:
#
# Custom engines can be added to settings.yml
# See: https://docs.searxng.org/dev/engines/index.html
#
# Limiter (rate limiting) can be configured to prevent abuse
# See: https://docs.searxng.org/admin/engines/settings.html#limiter
#
# After Deployment:
# 1. Access UI: http://localhost:8080
# 2. Test JSON API: curl "http://localhost:8080/search?q=test&format=json"
# 3. Review engine stats: http://localhost:8080/stats
# 4. Integrate with core-ai service