Files
portainer-core/STATUS.md
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jpmschweitzer e3b451b7b0 feat(ai): complete ADK migration and optimize system health checks
Major architectural changes and improvements:

## ADK Framework Migration (v0.10.0)
- Migrated from LangChain/LangGraph to Google ADK 1.3.0 with LiteLLM 1.80.5
- Improved tool calling reliability with local Ollama models
- Converted all 10 tools to ADK async generator format
- Updated streaming pipeline for ADK event system
- Enhanced error handling and agent initialization

## Model Optimization
- Switched from gemma3:12b (10GB VRAM) to gemma3:4b (4.8GB VRAM)
- Reduced VRAM usage from 91% to 43% (5.4GB freed)
- Optimized for production stability with memory headroom

## Health Check System Overhaul
- Optimized /health/full: 6ms response (was 30s+)
- Added model verification: confirms configured model is available
- New /health/diagnostics endpoint with optional deep testing
- Added currently loaded models tracking
- Clear emoji status indicators (//⚠️)
- Fixed AGENT_AVAILABLE flag export for proper health reporting

## Ollama Client Enhancements
- Added list_models() method for model inventory
- Enhanced model verification in health checks
- Better error handling and reporting

## Documentation Updates
- Updated STATUS.md to v0.10.0-adk-migration
- Comprehensive CHANGELOG.md entry with migration details
- Updated PLANS.md showing Phase 4 complete
- Updated ai-orchestrator-plan.md with ADK status
- Added MIGRATION_PLAN_LANGCHAIN_TO_ADK.md
- Added ADK_Ollama_Research.md with implementation analysis

## Technical Details
- 10 tools: 7 infrastructure + 2 research + 1 response tool
- Framework: Google ADK with UnifiedAgent pattern
- System prompt: v7_adk_best_practice
- Container health: Now passing Docker healthchecks
- Response times: Simple queries ~0.3-1s, Research ~4-7s
2025-11-26 08:36:50 +01:00

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Project Status

Last Updated: 2025-11-26 Version: 0.10.0-adk-migration

Current Phase

Active Work: AI Infrastructure Optimization & System Hardening Status: STABLE - ADK Migration Complete, All Systems Operational

See PLANS.md for complete implementation roadmap and CHANGELOG.md for version history.

In Progress

Priority 1: Security & SSO Implementation (Authentik)

  • Milestone 1: Authentik Deployment

    • Deploy Authentik server and worker containers
    • Configure shared PostgreSQL database (authentik_user, authentik database)
    • Configure shared Redis (DB 0)
    • Fix health checks (Python urllib instead of wget/curl)
    • Create NPM proxy host for auth.schweitz.net
    • Generate admin recovery key and set password
    • Memory optimization: 563MB total (80-90% reduction vs previous attempt)
  • Milestone 2: Google OAuth Integration

    • Create Google OAuth credentials (Client ID/Secret)
    • Configure Authentik Google source via API
    • Configure identification stage to show social login
    • Test Google OAuth login (successful)
    • Verify user creation (jpmschweitzer@gmail.com - external type)
  • Milestone 3: Forward Auth for Organizr COMPLETE (2025-11-21)

    • Create Authentik Proxy Provider (Organizr Proxy) via API
    • Create Authentik Application (Organizr) via API
    • Assign provider to embedded outpost (embedded outpost failed)
    • Deploy standalone outpost container (authentik-proxy on port 9443)
    • Configure Redis connection for standalone outpost
    • Verify outpost endpoints operational
    • Configure NPM forward auth for home.schweitz.net
    • Test SSO access to Organizr (Google OAuth login working)
    • Verify no redirect loops
    • Fix Organizr auto-login (moved headers to location / block)

Resolution: Embedded outpost has version-specific issues in 2024.8.4. Deployed standalone authentik-proxy container successfully. Forward auth fully operational with Organizr auto-login working.

Standalone Outpost Details:

  • Container: authentik-proxy (port 9445:9443)
  • Status: Healthy (websocket connected, ping endpoint responding)
  • Memory: ~150MB
  • Provider: Organizr Proxy (forward_single mode)
  • Token: 9blMGz71CFMJszs7AedQefgydpTnwvybjmMn0AlYilIKBV5LIq7snqnCodwX

NPM Configuration:

  • Applied to: home.schweitz.net (Organizr) ONLY
  • Forward auth: https://localhost:9445/outpost.goauthentik.io (NPM on host network)
  • WebSocket support: Enabled
  • Headers: X-authentik-username, X-authentik-email, X-authentik-groups, X-authentik-name, X-authentik-uid
  • Status: Fully operational, tested in incognito

Critical Fix: Authentication headers must be set inside location / block, not at server level, for proper forwarding to backend applications.

Priority 2: Core-API Refactoring & Infrastructure Management COMPLETE

  • 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
    • Create credentials management system
    • 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

    • Portainer Integration (HTTP client with access token)
    • NPM Integration (HTTP client with JWT bearer token + auto-refresh)
    • Read/List Endpoints (all implemented & tested)
    • Write Endpoints (POST/PUT/DELETE all implemented & tested)
    • Portainer API Token generated programmatically
    • Uptime Kuma Integration (deferred - complex Socket.IO)
    • Replace ad-hoc shell scripts in /stacks with API endpoints
    • Add CLI wrapper for common operations

Priority 3: AI Orchestrator Phase 2 (Memory Systems) COMPLETE

  • Implement Tier 1: ConversationBufferMemory (in-memory, last 10 turns)
  • Implement Tier 2/3: Unified Qdrant storage (persistent + semantic search)
  • Create Qdrant collection (core_api_conversations with 768d nomic-embed-text)
  • Implement auto-consolidation service (triggers at 10 turns)
  • Add memory persistence across container restarts
  • Implement dual-retrieval (buffer + Qdrant)
  • Phase 2.5: Multi-Tenancy (user_id isolation with default "llm-testuser")

Implementation Details:

  • Tier 1 (Buffer): In-memory storage for last 10 turns (< 1ms access)
  • Tier 2/3 (Qdrant): Unified persistent storage + semantic search (768d embeddings)
  • Auto-Consolidation: Automatically moves buffer → Qdrant at 10 turns
  • Multi-Tenancy: Single collection with user_id filtering (default: "llm-testuser")
  • Embedding Model: nomic-embed-text (768 dimensions, via Ollama)
  • Memory Retrieval: Dual-check buffer + Qdrant for cross-restart persistence
  • Status: 32 points stored, tested with multiple users, recall working after restarts

Priority 4: AI Orchestrator - Framework Migration COMPLETE (2025-11-26)

  • Phase 3: Research Capabilities (DuckDuckGo, web scraping) - COMPLETE (2025-11-24)
  • Framework Migration: LangChain/LangGraph → Google ADK - COMPLETE (2025-11-26)
  • Migrate agent orchestrator to Google ADK with LiteLLM
  • Convert all 9 tools to ADK async generator format
  • Update streaming pipeline for ADK event format
  • Switch model to gemma3:12b with ADK-optimized prompts
  • Implement comprehensive agent health checks
  • Update requirements.txt (remove langchain*, add google-adk)
  • Production testing and validation

Current Implementation (as of 2025-11-26):

  • Framework: Google ADK 1.3.0 with LiteLLM 1.80.5 (migrated from LangChain)
  • Model: gemma3:12b (upgraded from mistral:7b)
  • System Prompt: v7_adk_best_practice (optimized for ADK)
  • Total Tool Count: 9 tools (7 infrastructure + 2 research)
  • Tools Format: ADK async generators with proper streaming support
  • Architecture: UnifiedAgent with stateless sessions

Tools Available:

  • Infrastructure (7): get_current_time, list_services, get_service_details, list_stacks, get_stack_details, list_npm_hosts, get_npm_host_details
  • Research (2): web_search (DuckDuckGo + auto-scrape), web_scrape (targeted extraction)

Migration Benefits Achieved:

  • Improved tool calling reliability with Ollama models
  • Better streaming support with ADK event system
  • Model flexibility (works with Gemma, Mistral, Qwen families)
  • Cleaner architecture with unified agent pattern
  • Production-ready health monitoring

Performance Metrics (Post-Migration):

  • Simple queries: ~0.3-1s response time
  • Tool-using queries: ~2-5s response time
  • Research queries: ~4-7s response time
  • Tool calling success rate: Monitoring in progress
  • VRAM usage: ~8GB with gemma3:12b

Optional Future Enhancements (deferred):

  • Multi-agent routing patterns (Phase 4+)
  • Code specialist agent with codestral (Phase 4+)
  • Time-based memory consolidation
  • User filtering in Qdrant queries
  • User management API endpoints

Current Blockers

None - SSO implementation complete for critical services. Remaining service rollout deferred in favor of other priorities.

Key Metrics

Metric Target Current Status
Containers Running 15+ 22 🟢 All Services Operational
GPU Accessible Yes Yes 🟢 Working (RTX 2080 Ti)
Storage Used <80% 58% HDD (3.6TB/3.7TB) 🟢 Healthy
Services Accessible All 21/21 🟢 Complete
Remote Access Working Ready 🟢 Headscale + NPM
Firewall Active Yes Yes 🟢 UFW Configured
Backups Configured Yes Yes 🟢 Daily @ 3 AM
AI Orchestrator Phase 6 Phase 4 🟢 ADK Migration Complete
SSO (Authentik) Phase 5 Core Complete 🟢 Organizr + Core API Protected

Quick Reference

Documentation

Key Paths

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

Active Services & URLs

Infrastructure:

Networking:

Monitoring:

Applications:

Background Services:

  • Watchtower: Automatic updates daily @ 4 AM
  • Maintenance: Automated backups daily @ 3 AM

For detailed implementation history and completed work, see CHANGELOG.md