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Changelog

All notable changes to the AI Backend Services Stack will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

[1.0.0] - 2025-01-21

Added

  • Initial release of AI Backend Services Stack
  • PostgreSQL 15 with pgvector extension for vector operations
  • Redis 7 for caching and session management
  • ChromaDB for vector embeddings and similarity search
  • MinIO for S3-compatible object storage
  • Nginx reverse proxy for service routing
  • Comprehensive Makefile with 20+ commands
  • Health checks for all services
  • Auto-initialization SQL scripts
  • Docker Compose configuration with resource limits
  • Environment variable configuration
  • Basic authentication setup for ChromaDB
  • Backup and restore functionality
  • Complete documentation (README, DEPLOYMENT, CONTRIBUTING)
  • MIT License for open source distribution

Features

  • Easy Setup: Single make setup && make up command to start all services
  • Production Ready: Resource limits, health checks, and restart policies
  • Secure by Default: Configurable authentication and network isolation
  • Monitoring: Built-in health checks and status monitoring
  • Scalable: Resource limits and optimization guidelines
  • Extensible: Clear documentation for customization

Services Included

  • PostgreSQL 15 with pgvector (Port 5432)
  • Redis 7 with persistence (Port 6379)
  • ChromaDB latest (Port 8000)
  • MinIO latest (Ports 9000/9001)
  • Nginx reverse proxy (Ports 80/443)

Documentation

  • Comprehensive README with quick start guide
  • Detailed deployment guide for various platforms
  • Contributing guidelines
  • Example code for Python and Node.js integration
  • Troubleshooting guide

Supported Platforms

  • Local development (Docker Compose)
  • Docker Swarm
  • Kubernetes
  • AWS ECS/Fargate
  • Google Cloud Run/GKE
  • Azure Container Instances/AKS

[Unreleased]

Planned Features

  • Automated testing suite
  • Helm charts for Kubernetes
  • Terraform modules for cloud deployment
  • Grafana dashboards for monitoring
  • SSL/TLS configuration templates
  • High availability configurations
  • Performance benchmarking tools

Note: This project was created to provide a complete, production-ready backend infrastructure for AI applications. All services are carefully configured to work together seamlessly while maintaining security and performance best practices.