AI Knowledge Website

A comprehensive, enterprise-grade platform for automated AI knowledge aggregation, curation, and publication. This project combines an Astro-based frontend with a sophisticated Python content pipeline to deliver high-quality, continuously updated AI knowledge resources.

Quick Start

Prerequisites

• Node.js 18+ and npm 8+
• Python 3.9+ with pip
• PostgreSQL 14+
• Redis 7+
• Git

Development Setup

# Clone the repository (private - requires authentication)
git clone https://github.com/gianlucamazza/website_ai-knowledge.git
cd website_ai-knowledge

# Install dependencies
make install

# Set up environment
cp .env.example .env
# Edit .env with your configuration

# Initialize database
make db-setup

# Start development services
make dev

Access the site at http://localhost:4321

Project Structure

website_ai-knowledge/
├── apps/site/              # Astro frontend application
│   ├── src/
│   │   ├── components/     # Reusable UI components
│   │   ├── content/        # Content collections (articles, glossary)
│   │   ├── layouts/        # Page layout templates
│   │   └── pages/          # Route definitions
│   └── tests/              # Frontend tests
├── pipelines/              # Python content processing pipeline
│   ├── ingest/             # Content source ingestion
│   ├── normalize/          # Data cleaning and standardization
│   ├── dedup/              # Duplicate detection algorithms
│   ├── enrich/             # Content enhancement
│   ├── publish/            # Output generation
│   └── orchestrators/      # LangGraph workflow management
├── security/               # Security modules and compliance
├── tests/                  # Python test suite
├── scripts/                # Automation and utility scripts
└── docs/                   # Comprehensive documentation

Core Features

Content Pipeline

• Automated Ingestion: Ethical web scraping with rate limiting and robots.txt compliance
• Duplicate Detection: Advanced SimHash and LSH algorithms with >98% accuracy
• Content Enrichment: AI-powered summarization, tagging, and cross-linking
• Quality Assurance: Multi-stage validation and schema compliance
• Workflow Orchestration: LangGraph-based pipeline management

Frontend Application

• Static Site Generation: Optimized Astro-based site with excellent performance
• Content Collections: Zod-validated content with structured metadata
• Search & Navigation: Full-text search and intelligent content discovery
• Responsive Design: Mobile-first design with accessibility compliance
• SEO Optimization: Structured data and meta tag management

Enterprise Features

• Security: Zero-trust architecture with comprehensive input validation
• Monitoring: Prometheus metrics, structured logging, and alerting
• Scalability: Horizontal scaling with Kubernetes deployment
• Compliance: GDPR, copyright, and ethical AI compliance
• CI/CD: Automated testing, quality gates, and deployment pipelines

Documentation

Getting Started

• Development Guide - Local development setup and workflow
• Deployment Guide - Production deployment procedures

Technical Documentation

• Architecture Overview - Comprehensive system architecture
• API Documentation - Pipeline API reference
• Code Standards - Code quality and style guidelines

Operational Documentation

• CI/CD Documentation - Continuous integration and deployment
• Monitoring Guide - System monitoring and alerting
• Troubleshooting - Common issues and solutions
• Maintenance Schedule - Regular maintenance tasks

Security Documentation

• Security Overview - Security architecture and practices
• Incident Response - Security incident procedures
• Compliance Guide - Regulatory compliance procedures

Technology Stack

Frontend

• Framework: Astro 4.x with TypeScript
• Styling: Tailwind CSS
• Validation: Zod schemas
• Testing: Vitest, Playwright

Backend Pipeline

• Language: Python 3.9+
• Orchestration: LangGraph
• Database: PostgreSQL 14+
• Cache: Redis 7+
• Processing: Celery, FastAPI

Infrastructure

• Containerization: Docker
• Orchestration: Kubernetes
• CI/CD: GitHub Actions
• Monitoring: Prometheus, Grafana
• Logging: Structured JSON logging

Performance Metrics

• Duplicate Detection: >98% precision, <2% false positives
• Pipeline Processing: <30 minutes for full content refresh
• Site Build Time: <5 minutes for incremental builds
• API Response Time: <200ms (95th percentile)
• Uptime: >99.9% availability target

Quality Standards

• Test Coverage: >95% code coverage requirement
• Security: Zero critical vulnerabilities policy
• Performance: Core Web Vitals compliance
• Accessibility: WCAG 2.1 AA compliance
• Code Quality: Automated linting and type checking

Common Tasks

Content Management

# Trigger content ingestion
make ingest

# Validate existing content
make validate

# Check for broken links
make link-check

# Run duplicate detection
make dedup-check

Development

# Run all tests
make test

# Run specific test suite
make test-unit
make test-integration
make test-performance

# Code quality checks
make lint
make type-check
make security-check

Deployment

# Deploy to staging
make deploy-staging

# Deploy to production (requires approval)
make deploy-production

# Rollback deployment
make rollback

Contributing

We welcome contributions from the community. Please read our Contributing Guide for detailed information on:

• Code style and standards
• Development workflow
• Testing requirements
• Pull request process
• Issue reporting

Support

• Documentation: Comprehensive guides in the docs/ directory
• Issue Tracking: GitHub Issues for bug reports and feature requests
• Security Issues: Report to security@example.com (not public issues)

License

This project is licensed under the MIT License. See LICENSE for details.

Acknowledgments

• OpenAI for GPT models used in content processing
• Anthropic for Claude models used in summarization
• The open-source community for the excellent tools and libraries

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Project Status: Production Ready Last Updated: $(date) Documentation Version: 1.0.0