microdao-daarion/NODE-2-CURRENT-STATE.md

📊 Node #2 Current State — MacBook Pro M4 Max

Дата: 2025-11-22
Node ID: node-2-macbook-m4max
Статус: 🟡 Частково налаштовано (Development Services Running)

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✅ Що вже працює

🤖 AI/LLM Services

1. Ollama (Подвійна інсталяція)

# Native Ollama (via Pieces OS)
curl http://localhost:11434/api/tags
# Status: ✅ Running
# PID: 1999
# Process: /Applications/Pieces OS.app/Contents/Resources/ollama-darwin serve

# Docker Ollama
curl http://localhost:11435/api/tags  
# Container: ollama-ai
# Status: ✅ Running (20 hours uptime)
# Port: 0.0.0.0:11435->11434/tcp

Встановлені моделі (8 моделей, завантажено 2025-11-21):

• mistral-nemo:12b (7.1 GB, Q4_0, 12.2B params) — завантажено 14 годин тому
• gemma2:27b (15 GB, Q4_0, 27.2B params) — завантажено 15 годин тому
• deepseek-coder:33b (18 GB, Q4_0, 33B params) — завантажено 15 годин тому
• qwen2.5-coder:32b (19 GB, Q4_K_M, 32.8B params) — завантажено 15 годин тому
• deepseek-r1:70b (42 GB, Q4_K_M, 70.6B params) — завантажено 15 годин тому
• starcoder2:3b (1.7 GB, Q4_0, 3B params) — завантажено 15 годин тому
• phi3:latest (2.2 GB, Q4_0, 3.8B params) — завантажено 17 годин тому
• gpt-oss:latest (13 GB, MXFP4, 20.9B params) — завантажено 17 годин тому

Загальний розмір: ~118 GB моделей
Загальна кількість параметрів: ~201.5B параметрів

2. LobeChat (AI Chat Interface)

# Web UI: http://localhost:3210
curl http://localhost:3210
# Container: lobe-chat
# Status: ✅ Running (20 hours uptime)
# Image: lobehub/lobe-chat

🗄️ Database & Storage Services

3. Qdrant (Vector Database)

# API: http://localhost:6333
curl http://localhost:6333/healthz
# Container: qdrant-vector-db
# Status: ⚠️ Unhealthy (but API responds)
# Image: qdrant/qdrant:latest
# Ports: 0.0.0.0:6333-6335->6333-6335/tcp
# Volume: apple_qdrant_storage

Проблема: Docker показує unhealthy, але API працює. Потребує перевірки логів.

4. MeiliSearch (Full-text Search)

# API: http://localhost:7700
curl http://localhost:7700
# Container: meilisearch-search
# Status: ✅ Healthy (20 hours uptime)
# Image: getmeili/meilisearch:v1.11

📊 Development Tools

5. Jupyter Lab (Data Science Notebook)

# Web UI: http://localhost:8888
curl http://localhost:8888
# Container: jupyter-lab
# Status: ✅ Healthy (20 hours uptime)
# Image: jupyter/datascience-notebook:latest

6. NATS JetStream (Message Broker)

# NATS: nats://localhost:4222
# Management: http://localhost:8222
nc -zv localhost 4222
# Container: nats-jetstream
# Status: ✅ Running (3 hours uptime)
# Image: nats:latest
# Ports: 4222 (client), 6222 (routing), 8222 (monitoring)

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📦 Docker Infrastructure

Volumes

docker volume ls | grep -E "(dagi|daarion|qdrant)"

• apple_qdrant_storage — Qdrant vector embeddings
• microdao-daarion_rag-model-cache — RAG model cache

Networks

• daarion-network (bridge) — Custom Docker network

Data Directories

• /Users/apple/github-projects/microdao-daarion/data/rbac/ — RBAC database (empty, ready)

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🔧 Configuration Files

✅ Present

• .env — Environment variables (2.3 KB, configured)
• .env.example — Template (4.6 KB)
• docker-compose.yml — Services definition (7.1 KB, updated 2025-01-17)
• router-config.yml — Router rules (7.4 KB, updated 2025-01-17)
• router-config.yml.backup — Config backup (4.5 KB)

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🐍 Python Environment

Installed Packages

pip3 list | grep -E "(fastapi|uvicorn|httpx|pydantic|openai)"

• ✅ httpx 0.28.1 — HTTP client for async requests
• ✅ openai 2.8.0 — OpenAI SDK
• ✅ pydantic 2.12.4 — Data validation
• ✅ pydantic_core 2.41.5 — Pydantic core
• ❌ fastapi — MISSING (need for DAGI Router)
• ❌ uvicorn — MISSING (need for FastAPI server)

Required Installation

pip3 install fastapi uvicorn python-multipart aiofiles

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🚫 Що НЕ працює (потрібно запустити)

DAGI Stack Core Services

1. DAGI Router (Port 9102)

# Status: ❌ Not running
# Purpose: Main routing engine for AI requests
# Command to start:
python3 main_v2.py --config router-config.yml --port 9102

2. Memory Service (Port 8000)

# Status: ❌ Not running
# Purpose: Agent memory and context management
# Requires: PostgreSQL
# Command to start:
cd services/memory-service && python3 main.py

3. DevTools Backend (Port 8008)

# Status: ❌ Not running
# Purpose: File operations, test execution
# Command to start:
cd devtools-backend && python3 main.py

4. Bot Gateway (Port 9300)

# Status: ❌ Not running
# Purpose: Telegram/Discord bot integration
# Command to start:
cd gateway-bot && python3 main.py

5. RBAC Service (Port 9200)

# Status: ❌ Not running
# Purpose: Role-based access control
# Database: SQLite at data/rbac/rbac.db (empty)
# Command to start:
cd microdao && python3 main.py

6. RAG Service (Port 9500)

# Status: ❌ Not running
# Purpose: Document retrieval and Q&A
# Requires: PostgreSQL, embeddings
# Command to start:
cd services/rag-service && python3 main.py

7. Parser Service (Port 9400)

# Status: ❌ Not running
# Purpose: Document parsing and Q&A generation
# Command to start:
cd services/parser-service && python3 main.py

8. CrewAI Orchestrator (Port 9010)

# Status: ❌ Not running
# Purpose: Multi-agent workflow coordination
# Command to start:
cd orchestrator && python3 crewai_backend.py

Supporting Services

9. PostgreSQL (Port 5432)

# Status: ❌ Not running
# Purpose: Memory, RAG, and core data storage
# Database: daarion_memory
# Start via docker-compose:
docker-compose up -d postgres

10. Redis (Port 6379)

# Status: ❌ Not running
# Purpose: Cache and session management
# Start via docker-compose:
docker-compose up -d redis

11. Neo4j (Port 7474/7687)

# Status: ❌ Not running
# Purpose: Graph database for DAO relationships
# Start via docker-compose:
docker-compose up -d neo4j

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📋 Action Plan (Priority Order)

Phase 1: Python Environment (5 min)

# Install missing dependencies
pip3 install fastapi uvicorn python-multipart aiofiles sqlalchemy asyncpg

# Verify installation
python3 -c "import fastapi, uvicorn; print('✅ Ready')"

Phase 2: Core Database (10 min)

# Start PostgreSQL
docker-compose up -d postgres

# Wait for ready
sleep 5

# Verify connection
docker exec dagi-postgres pg_isready

# Initialize DAARION memory database
docker exec -it dagi-postgres psql -U postgres -c "CREATE DATABASE daarion_memory;"

Phase 3: DAGI Router (15 min)

# Validate configuration
python3 config_loader.py

# Start router in background
nohup python3 main_v2.py --config router-config.yml --port 9102 > logs/router.log 2>&1 &

# Test health
curl http://localhost:9102/health

Phase 4: Supporting Services (20 min)

# Start Redis
docker-compose up -d redis

# Start Memory Service
cd services/memory-service
nohup python3 main.py > ../../logs/memory.log 2>&1 &
cd ../..

# Test Memory Service
curl http://localhost:8000/health

Phase 5: Optional Services (on-demand)

# DevTools (for development)
cd devtools-backend
python3 main.py

# RBAC (for microDAO features)
cd microdao
python3 main.py

# RAG Service (for document Q&A)
cd services/rag-service
python3 main.py

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🔍 Diagnostics Commands

Check Running Services

# All Docker containers
docker ps -a

# All listening ports
lsof -i -P | grep LISTEN | grep -E "(9102|8000|8008|3210|6333|11434)"

# Python processes
ps aux | grep python | grep -E "(main|uvicorn)"

Check Logs

# Docker logs
docker logs qdrant-vector-db
docker logs lobe-chat
docker logs ollama-ai

# Application logs (when services start)
tail -f logs/router.log
tail -f logs/memory.log

Test Services

# Ollama native
curl http://localhost:11434/api/tags

# Ollama Docker
curl http://localhost:11435/api/tags

# LobeChat
curl http://localhost:3210

# Qdrant
curl http://localhost:6333/healthz

# MeiliSearch
curl http://localhost:7700/health

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🔗 Related Documentation

• NODE-2-MACBOOK-SPECS.md — Complete hardware specs
• INFRASTRUCTURE.md — Network nodes overview
• WARP.md — Main developer guide
• docker-compose.yml — Service definitions

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📊 Resource Usage (Current)

CPU & Memory

# Check current usage
top -l 1 | head -n 10

# Docker resource usage
docker stats --no-stream

Estimated current usage:

• CPU: ~10-15% (background services)
• RAM: ~8-10 GB (Ollama + containers)
• Disk: ~275 GB used / 2 TB total

Available for DAGI Stack:

• CPU: 16 cores (mostly free)
• RAM: ~54 GB free
• Disk: 1.72 TB free

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Last Updated: 2025-01-17 by WARP AI
Status: 🟡 Partially Ready — Development services running, core DAGI services need to be started
Next Command: pip3 install fastapi uvicorn && docker-compose up -d postgres