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tower-of-joy Project Status

Last Updated: 2025-11-14 Version: 0.7.1-gitea-deployment

Current Phase

Phase: AI Orchestrator Development - Phase 1 (Foundation) Status: ✅ COMPLETED Started: 2025-11-13 Completed: 2025-11-13

Next Phase: AI Orchestrator - Phase 2 (Memory Systems) Status: 🔄 IN PROGRESS

Implementation Progress

✅ Completed

Planning & Documentation:

  • Research home server solutions (see containers/research.md)
  • Architecture decision: Portainer + Docker Compose
  • Implementation plan created (see containers/implementation-plan.md)
  • AGENTS.md populated with project-specific guidelines
  • Storage strategy defined (SSD for configs, HDD for content)

Phase 1: Foundation Setup:

  • Install NVIDIA Container Toolkit (v1.17.9-1 - downgraded for driver 470 compatibility)
  • Deploy Portainer (port 8001, host networking)
  • Configure GPU management (via docker-compose deploy configuration)
  • Mount 4TB media drive at /mnt/media
  • Configure AMP integration (kept on port 8080, no conflicts)
  • Add user to docker group
  • Deploy Nginx Proxy Manager (port 81, host networking)
  • Deploy Ollama ML infrastructure (port 11434, GPU-enabled)
  • Fix Docker networking issues (iptables FORWARD chain, host networking solution)

Phase 2: Networking & External Access:

  • Deploy Headscale (port 8085, mesh VPN control server)
  • Configure Headscale with custom 10.99.0.0/16 network range
  • Create homelab user and generate pre-auth keys
  • Document connection procedures for all device types

Phase 3: Monitoring & Management:

  • Deploy Uptime Kuma (port 3001, service uptime monitoring)
  • Deploy Netdata (port 19999, real-time system metrics)
  • Deploy Heimdall dashboard (port 8888, unified dashboard)

Phase 4: Optimization & Security:

  • Deploy Watchtower (automatic container updates, daily at 4 AM)
  • Configure Docker log rotation (10MB max, 3 files per container)
  • Configure UFW firewall (SSH, Tailscale, infrastructure services allowed)
  • Deploy maintenance container (scheduled backups & future maintenance tasks)
  • Configure automated Docker config backups (daily at 3 AM, 30-day retention, ~94MB/backup)

Application Deployment:

  • Deploy Open WebUI (LLM chat interface, port 82)
  • Integrate Open WebUI with Uptime Kuma (health monitoring)
  • Integrate Open WebUI with Organizr (dashboard tab + homepage)
  • Document Open WebUI in CONTAINERS.md
  • Deploy Core API (OpenAPI functions for Open WebUI, port 8083)
  • Integrate Core API with Uptime Kuma (health monitoring)
  • Integrate Core API with Organizr (dashboard tab)
  • Document Core API in CONTAINERS.md
  • Upgrade system to Python 3.12 (from EOL 3.8)

AI Orchestrator Development (Phase 1):

  • Implement OpenAI-compatible /v1/chat/completions endpoint
  • Implement OpenAI-compatible /v1/models endpoint
  • Add streaming support (Server-Sent Events format)
  • Add non-streaming response mode
  • Implement model aliasing system (gpt-3.5-turbo → gemma:7b, etc.)
  • Create Ollama client with connection pooling
  • Add proper request/response schemas (Pydantic models)
  • Deploy to ai-dataplane network with hot-reload
  • Test streaming and non-streaming responses
  • Update CONTAINERS.md documentation
  • Deploy Nextcloud (cloud storage and collaboration platform, port 8082)
  • Configure Nextcloud with MariaDB, Redis, and reverse proxy (https://cloud.schweitz.net)
  • Optimize Nextcloud (database indices, bigint conversion, cron background jobs)
  • Relocate Nextcloud cron to maintenance container
  • Integrate Nextcloud with Uptime Kuma (HTTP monitoring)
  • Integrate Nextcloud with Organizr (dashboard tab)
  • Document Nextcloud in CONTAINERS.md
  • Deploy Samba (network file sharing, ports 139/445)
  • Configure Samba shares (Media R/W, Downloads R/W, Backups R/O)
  • Disable host Samba service to prevent conflicts
  • Configure UFW firewall for Samba ports
  • Integrate Samba with Uptime Kuma (TCP port monitoring)
  • Document Samba in CONTAINERS.md
  • Fix Uptime Kuma network connectivity (multi-network bridge to all service networks)
  • Deploy Gitea (Git repository hosting, ports 3002/2222)
  • Configure Gitea with PostgreSQL database backend
  • Configure NPM reverse proxy for https://git.schweitz.net with Let's Encrypt SSL
  • Complete Gitea initial setup wizard and create admin account
  • Integrate Gitea with Uptime Kuma (HTTP monitoring)
  • Integrate Gitea with Organizr (dashboard tab)
  • Document Gitea in CONTAINERS.md

🔄 In Progress

Priority 1: Core-API Refactoring & Infrastructure Management:

  • Code Cleanup: Restructure Core API into function-specific controller files
    • Create /controllers directory structure
    • Create /clients directory structure
    • Create base.py controller base class
    • Add infrastructure settings to config.py (Portainer, NPM, Kuma URLs/credentials)
    • Create credentials management system (credentials.py gitignored, credentials.example.py template)
    • Update main.py routing to include infrastructure controller
    • Separate AI Orchestrator logic into ai_controller.py
    • Extract webscraper to tools_controller.py
    • Create health_controller.py for monitoring endpoints
  • Infrastructure Management Controller: Build automation API for service management
    • Create infrastructure_controller.py with read/list endpoints
    • Portainer Integration: HTTP client with access token authentication
      • get_endpoints() - List Docker environments
      • get_stacks() - List all stacks
      • get_stack(id) - Get stack details
      • create_stack() - Deploy from compose YAML
      • update_stack() - Update existing stack
      • delete_stack() - Remove stack
    • NPM Integration: HTTP client with JWT bearer token + auto-refresh
      • Token refresh mechanism (24h expiration handling)
      • get_proxy_hosts() - List all proxy hosts
      • get_proxy_host(id) - Get proxy details
      • create_proxy_host() - Create new proxy configuration
      • get_certificates() - List SSL certificates
      • create_certificate() - Request Let's Encrypt cert
    • Read/List Endpoints Implemented & Tested:
      • GET /infrastructure/health - Check Portainer/NPM connectivity ✅ TESTED
      • GET /infrastructure/services - List all deployed services ✅ TESTED (8 stacks)
      • GET /infrastructure/services/{name} - Get service details ✅ TESTED
      • GET /infrastructure/ports - List allocated ports (skeleton)
      • GET /infrastructure/domains - List configured domains ✅ TESTED
    • Portainer API Token: Generated programmatically and configured
    • Write Endpoints Implemented & Tested:
      • POST /infrastructure/services - Deploy new service ✅ TESTED
      • PUT /infrastructure/services/{name} - Update service ✅ TESTED
      • DELETE /infrastructure/services/{name} - Remove service ✅ TESTED
      • POST /infrastructure/proxy - Create proxy host with SSL ✅ IMPLEMENTED
    • Uptime Kuma Integration: WebSocket client (deferred - complex Socket.IO)
    • Replace ad-hoc shell scripts in /stacks with API endpoints
    • Add CLI wrapper for common operations

Priority 2: AI Orchestrator Enhancement (Phase 2 - Memory Systems):

  • Implement Tier 1: ConversationBufferMemory (in-memory, last 10 turns)
  • Implement Tier 2: ConversationSummaryMemory (SQLite summaries)
  • Integrate Tier 3: VectorStoreRetrieverMemory (Qdrant semantic search)
  • Create Qdrant collections (conversation_memory, documents, user_facts)
  • Implement memory consolidation service
  • Add conversation history API endpoints
  • Test memory persistence across container restarts

📋 Planned (After Current Work)

AI Orchestrator Phases 3-6:

  • Phase 3: Multi-agent workflows with LangGraph (Router, Chat, Research, Code agents)
  • Phase 4: Tool integration (web search, web scrape, document search)
  • Phase 5: RAG & advanced memory (hybrid retrieval, document upload)
  • Phase 6: Production hardening (metrics, monitoring, optimization)

🔮 Backlog (Future Enhancements)

Infrastructure Consolidation & Technical Debt:

  1. Centralized Database Container: Consolidate SQLite databases from multiple services (Uptime Kuma, Organizr, etc.) into a single PostgreSQL/MySQL container for easier management and backups
  2. Maintenance Container Consolidation: Migrate maintenance container cron jobs into Core API endpoints with scheduled triggers - consolidate custom code into single service
  3. Version Control Setup: Initialize portainer-core repository in Gitea for proper version control, branching, and change tracking
  4. Disaster Recovery Strategy: Design offsite backup solution with restore/bootstrap scripts for full tower-of-joy recreation on new hardware

Post-Phase 6 Integrations:

  • Nextcloud integration (file search, calendar management)
  • ComfyUI integration (image generation)
  • Home Assistant integration (smart home control)
  • Custom mobile apps (iOS/Android)

Current Blockers

None - All core services deployed and operational.

Next Steps

Priority 1: Core-API Refactoring & Infrastructure Management

Why Now: Clean up technical debt before adding more features. Build proper infrastructure management API to eliminate ad-hoc scripts and enable programmatic service deployment.

Immediate Actions:

  1. Refactor Core-API structure - Create controller-based architecture for maintainability
  2. Build Infrastructure Management API - Automate Portainer/NPM/Kuma operations
  3. Replace shell scripts - Migrate /stacks/*.sh to proper API endpoints with CLI wrappers

Benefits:

  • Cleaner codebase for future AI Orchestrator development
  • Automated service deployment and monitoring setup
  • Programmatic infrastructure management (no more manual NPM/Kuma configuration)
  • Foundation for self-managing homelab

Priority 2: AI Orchestrator Phase 2 (Memory Systems)

  • Implement 3-tier memory architecture: ConversationBufferMemory (Tier 1), ConversationSummaryMemory (Tier 2), Qdrant VectorStore (Tier 3)
  • Create Qdrant collections: conversation_memory, documents, user_facts
  • Build memory consolidation pipeline: Automatic summarization and vector embedding
  • Add conversation history endpoints: Query and manage conversation memory
  • Test integration with Open WebUI: Verify memory persistence and recall

Optional: Enhanced Capabilities

  • Connect Devices to Headscale: Set up additional devices on mesh VPN for remote access
  • Jellyfin Media Library: Populate media libraries with content
  • Nextcloud Desktop Clients: Install sync clients on workstations
  • External Monitoring: Set up Uptime Kuma notifications (email, Discord, etc.)
  • Advanced Automation: Expand maintenance container with additional scheduled tasks

Key Metrics

Metric Target Current Status
Containers Running 15+ 19 🟢 All Services Operational
GPU Accessible Yes Yes 🟢 Working
Storage Mounted 4.2TB 3.6TB (58% used) 🟢 Mounted
Services Accessible All 19/19 🟢 Complete
Remote Access Working Ready 🟢 Headscale + NPM
Firewall Active Yes Yes 🟢 UFW Configured
Backups Configured Yes Yes 🟢 Maintenance Container
Cloud Storage Yes Yes 🟢 Nextcloud Deployed
File Sharing Yes Yes 🟢 Samba Deployed
AI Orchestrator Phase 6 Phase 1 ✅ 🟡 In Progress (Phase 2 next)

Version History

  • v0.7.1-gitea-deployment (2025-11-14): Gitea Git service deployed with PostgreSQL, NPM reverse proxy (https://git.schweitz.net), SSH port 2222, full Uptime Kuma + Organizr integration
  • v0.7.0-ai-orchestrator-phase1 (2025-11-13): AI Orchestrator Phase 1 complete - OpenAI-compatible API (/v1/chat/completions, /v1/models) with model aliasing and streaming support
  • v0.6.0-applications (2025-11-13): Nextcloud and Samba deployed - cloud storage, file sharing, multi-network Uptime Kuma integration
  • v0.5.2-core-api (2025-11-13): Core API deployed for Open WebUI functions, Python 3.12 upgrade (from EOL 3.8)
  • v0.5.1-open-webui (2025-11-12): Open WebUI deployed with built-in voice capabilities (local STT/TTS)
  • v0.5.0-optimization (2025-11-11): Phase 4 complete - Optimization & security (Watchtower, UFW, log rotation, maintenance container)
  • v0.4.0-monitoring (2025-11-11): Phase 3 complete - Monitoring stack deployed (Uptime Kuma, Netdata, Heimdall)
  • v0.3.0-networking (2025-11-11): Phase 2 complete - Headscale deployed with 10.99.0.0/16 mesh network
  • v0.2.0-foundation (2025-11-11): Phase 1 complete - Portainer, NPM, Ollama deployed with GPU support
  • v0.1.0-planning (2025-11-11): Project initialized, research and planning complete

Quick Reference

Documentation:

  • Architecture research: containers/research.md
  • Implementation plan: containers/implementation-plan.md
  • Agent guidelines: AGENTS.md
  • System details: SYSTEM.md

Key Paths:

  • SSD configs: /home/jpmschweitzer/docker-data/
  • HDD content: /mnt/media/
  • Stacks: Managed in Portainer web UI

Active Services & Ports:

Application Services:

Update this file as you complete each phase and checkpoint

Recent Updates

2025-11-14 Evening (Session 3)

Core-API Refactoring - Write Endpoints:

  • ✅ Implemented POST /infrastructure/services - Deploy service from compose YAML
  • ✅ Implemented PUT /infrastructure/services/{name} - Update service configuration
  • ✅ Implemented DELETE /infrastructure/services/{name} - Remove service and stack
  • ✅ Implemented POST /infrastructure/proxy - Create proxy host with optional SSL
  • ✅ Tested all service management endpoints (POST/PUT/DELETE) with test-nginx stack
  • ✅ Updated main.py API description with write endpoints

Status: Infrastructure Management API complete (Phase 3 ✅) Next: Refactor existing controllers (Phase 4) or begin AI Orchestrator Phase 2

2025-11-14 Evening (Session 2)

Core-API Refactoring - Infrastructure Management:

  • ✅ Created credentials management system (credentials.py gitignored)
  • ✅ Generated Portainer API token programmatically via API
  • ✅ Integrated infrastructure controller into main.py
  • ✅ Fixed Pydantic validation bug (status int→str conversion)
  • ✅ Tested all infrastructure read endpoints with live data
  • ✅ Verified 8 Portainer stacks detected
  • ✅ Domains endpoint working with SSL status

Status: Infrastructure read endpoints complete and tested Next: Implement write endpoints (POST/PUT/DELETE)

2025-11-13 Evening

Phase 1 Testing & Bug Fix:

  • ✅ Completed comprehensive testing of Phase 1 implementation
  • ✅ Fixed model ID formatting issue (extra quotes in model names)
  • ✅ All 10/10 tests passing
  • ✅ Zero known issues remaining
  • ✅ Performance: 245ms average response time
  • ✅ 100% OpenAI API compatibility verified
  • ✅ Created comprehensive test results document (docs/phase1-test-results.md)

Status: Phase 1 100% complete and production-ready Next: Begin Phase 2 (Memory Systems) implementation

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