# 1. Install Ollama locally
curl -fsSL https://ollama.ai/install.sh | sh

# 2. Start Ollama server
ollama serve

# 3. Install required models (in another terminal)
ollama pull qwen3:0.6b
ollama pull qwen3:8b

# 4. Clone and start LocalGPT
git clone https://github.com/your-org/rag-system.git
cd rag-system
./start-docker.sh

# 5. Access the application
open http://localhost:3000

┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
│   Frontend      │────│    Backend      │────│    RAG API      │
│  (Container)    │    │  (Container)    │    │  (Container)    │
│   Port: 3000    │    │   Port: 8000    │    │   Port: 8001    │
└─────────────────┘    └─────────────────┘    └─────────────────┘
                                                        │
                                                        │ API calls
                                                        ▼
                                               ┌─────────────────┐
                                               │     Ollama      │
                                               │ (Local/Host)    │
                                               │   Port: 11434   │
                                               └─────────────────┘

# Ollama Configuration
OLLAMA_HOST=http://host.docker.internal:11434

# Service Configuration  
NODE_ENV=production
RAG_API_URL=http://rag-api:8001
NEXT_PUBLIC_API_URL=http://localhost:8000

# Database Paths (inside containers)
DATABASE_PATH=/app/backend/chat_data.db
LANCEDB_PATH=/app/lancedb
UPLOADS_PATH=/app/shared_uploads

# Start all services
./start-docker.sh

# Stop all services
./start-docker.sh stop

# Restart services
./start-docker.sh stop && ./start-docker.sh

# Check container status
./start-docker.sh status
docker compose ps

# View live logs
./start-docker.sh logs
docker compose logs -f

# View specific service logs
docker compose logs -f rag-api
docker compose logs -f backend
docker compose logs -f frontend

# Start manually
docker compose --env-file docker.env up --build -d

# Stop manually
docker compose down

# Rebuild specific service
docker compose build --no-cache rag-api
docker compose up -d rag-api

# Test all endpoints
curl -f http://localhost:3000 && echo "✅ Frontend OK"
curl -f http://localhost:8000/health && echo "✅ Backend OK"
curl -f http://localhost:8001/models && echo "✅ RAG API OK"
curl -f http://localhost:11434/api/tags && echo "✅ Ollama OK"

# RAG API container (most debugging happens here)
docker compose exec rag-api bash

# Backend container
docker compose exec backend bash

# Frontend container
docker compose exec frontend sh

# Test RAG system initialization
docker compose exec rag-api python -c "
from rag_system.main import get_agent
agent = get_agent('default')
print('✅ RAG System OK')
"

# Test Ollama connection from container
docker compose exec rag-api curl http://host.docker.internal:11434/api/tags

# Check environment variables
docker compose exec rag-api env | grep OLLAMA

# View Python packages
docker compose exec rag-api pip list | grep -E "(torch|transformers|lancedb)"

# Monitor container resources
docker stats

# Check disk usage
docker system df
df -h ./lancedb ./shared_uploads

# Check memory usage by service
docker stats --format "table {{.Name}}\t{{.CPUPerc}}\t{{.MemUsage}}\t{{.MemPerc}}"

# Check logs for specific error
docker compose logs [service-name]

# Rebuild from scratch
./start-docker.sh stop
docker system prune -f
./start-docker.sh

# Check for port conflicts
lsof -i :3000 -i :8000 -i :8001

# Verify Ollama is running
curl http://localhost:11434/api/tags

# Restart Ollama
pkill ollama
ollama serve

# Test from container
docker compose exec rag-api curl http://host.docker.internal:11434/api/tags

# Check memory usage
docker stats --no-stream
free -h  # On host

# Increase Docker memory limit
# Docker Desktop → Settings → Resources → Memory → 8GB+

# Use smaller models
ollama pull qwen3:0.6b  # Instead of qwen3:8b

# Clean build
docker compose build --no-cache frontend
docker compose up -d frontend

# Check frontend logs
docker compose logs frontend

# Check file permissions
ls -la backend/chat_data.db
ls -la lancedb/

# Reset permissions
chmod 664 backend/chat_data.db
chmod -R 755 lancedb/ shared_uploads/

# Test database access
docker compose exec backend sqlite3 /app/backend/chat_data.db ".tables"

# Nuclear option - reset everything
./start-docker.sh stop
docker system prune -a --volumes
rm -rf lancedb/* shared_uploads/* backend/chat_data.db
./start-docker.sh