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Phase 2.1 Service Foundation - COMPLETE ✅

Date: 2026-01-22 Status: All components implemented and tested

Summary

Phase 2.1 Service Foundation has been successfully implemented according to ../architecture/SERVICE_IMPLEMENTATION_SPEC_v0.1.md.

Implemented Components

1. Infrastructure (Docker Compose)

  • ✅ PostgreSQL 17 with pgvector
  • ✅ Elasticsearch 8.19
  • ✅ Kibana 8.19
  • ✅ Neo4j 5.26 LTS
  • All services running with health checks

2. Database Schema (docker/postgres/init.sql)

  • ✅ sessions table
  • ✅ metrics table (time-series)
  • ✅ captains_log_captures table
  • ✅ captains_log_reflections table
  • ✅ api_costs table
  • ✅ embeddings table with pgvector HNSW index

3. Service Layer

Data Models (src/personal_agent/service/models.py)

  • ✅ Pydantic models for API validation
  • ✅ SQLAlchemy models for database ORM
  • ✅ Session and Metrics models complete

Database Connection (src/personal_agent/service/database.py)

  • ✅ Async SQLAlchemy engine with connection pooling
  • ✅ FastAPI dependency injection support
  • ✅ Database initialization

Repositories

  • ✅ session_repository.py - Full CRUD operations
  • ✅ metrics_repository.py - Write, query, stats, batch operations

FastAPI Application (src/personal_agent/service/app.py)

  • ✅ Lifespan management (startup/shutdown)
  • ✅ Health check endpoint
  • ✅ Session CRUD endpoints
  • ✅ Chat endpoint (placeholder for orchestrator)
  • ✅ Elasticsearch logging integration

4. Telemetry

  • ✅ es_logger.py - Async Elasticsearch logger
  • ✅ Event logging with daily index rotation
  • ✅ Batch operations and search functionality

5. CLI Client

  • ✅ ui/service_client.py - HTTP client
  • ✅ Typer-based CLI commands
  • ✅ Rich terminal output

6. Configuration

  • ✅ All service settings added to AppConfig
  • ✅ Database URL and connection settings
  • ✅ Elasticsearch configuration
  • ✅ Neo4j settings (for Phase 2.2)
  • ✅ Claude API settings (for Phase 2.2)
  • ✅ Feature flags

7. Dependencies

  • ✅ FastAPI and Uvicorn
  • ✅ SQLAlchemy with asyncpg
  • ✅ Elasticsearch client (8.x compatible)
  • ✅ Neo4j driver
  • ✅ Anthropic API client

8. Initialization Scripts

  • ✅ scripts/init-services.sh - Full service initialization
  • ✅ scripts/setup-elasticsearch.sh - ES templates and ILM
  • ✅ docker/elasticsearch/index-template.json
  • ✅ docker/elasticsearch/ilm-policy.json

Service URLs

Service URL Notes
Personal Agent API http://localhost:9000 FastAPI service (changed from 8000)
SLM Server Router http://localhost:8000 Multi-model LLM routing service
PostgreSQL localhost:5432 user: agent, db: personal_agent
Elasticsearch http://localhost:9200 Logging and search
Kibana http://localhost:5601 Log visualization
Neo4j Browser http://localhost:7474 Knowledge graph (Phase 2.2)
Neo4j Bolt bolt://localhost:7687 Neo4j driver connection

SLM Server Backend Models

Model Role Port Backend
liquid/lfm2.5-1.2b Router 8500 MLX (8-bit)
qwen/qwen3-4b-2507 Standard 8501 MLX (8-bit)
qwen/qwen3-8b Reasoning 8502 MLX (8-bit)
mistralai/devstral-small-2-2512 Coding 8503 MLX (8-bit)

Key Fixes Applied

  1. SQLAlchemy metadata conflict: Renamed metadata column to metadata_ in SessionModel
  2. Elasticsearch version compatibility: Pinned elasticsearch client to 8.x (was 9.x)
  3. Port conflict: Changed default service port from 8000 to 9000 (LLM server uses 8000)

Testing

# Start services
./scripts/init-services.sh

# Start FastAPI service
uv run uvicorn personal_agent.service.app:app --reload --port 9000

# Test endpoints
curl http://localhost:9000/health
curl -X POST http://localhost:9000/sessions -H "Content-Type: application/json" -d '{"channel": "CLI"}'
curl -X POST "http://localhost:9000/chat?message=Hello"

# View logs in Kibana
open http://localhost:5601

# Check database
docker-compose exec postgres psql -U agent -d personal_agent -c "\dt"

Next: Phase 2.2

Phase 2.2 (Memory & Second Brain) can now begin:

  • Neo4j integration
  • Entity extraction with Claude
  • Captain's Log refactoring
  • Background consolidation
  • Adaptive scheduling

Files Created/Modified

New Files

  • docker-compose.yml
  • docker/postgres/init.sql
  • docker/elasticsearch/index-template.json
  • docker/elasticsearch/ilm-policy.json
  • scripts/init-services.sh
  • scripts/setup-elasticsearch.sh
  • scripts/README.md
  • src/personal_agent/service/init.py
  • src/personal_agent/service/app.py
  • src/personal_agent/service/database.py
  • src/personal_agent/service/models.py
  • src/personal_agent/service/repositories/init.py
  • src/personal_agent/service/repositories/session_repository.py
  • src/personal_agent/service/repositories/metrics_repository.py
  • src/personal_agent/telemetry/es_logger.py
  • src/personal_agent/ui/service_client.py

Modified Files

  • pyproject.toml (added service dependencies)
  • src/personal_agent/config/settings.py (added service configuration)

Validation

All acceptance criteria from the spec have been met:

  • ✅ Service starts and runs continuously
  • ✅ Sessions persist across service restarts
  • ✅ Elasticsearch logs events
  • ✅ Health checks report component status
  • ✅ All docker services healthy
  • ✅ Database tables created and accessible