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CR Chatbot - Docker Setup Guide

This guide provides comprehensive instructions for deploying CR Chatbot using Docker containers.

Quick Start

The fastest way to get CR Chatbot running with Docker:

# Clone and start
git clone https://github.com/3eekeeper/cr-chatbot.git
cd cr-chatbot
docker-compose up -d

# Access at http://localhost:8080

Docker Compose (Recommended)

Basic Setup

# Start CR Chatbot only
docker-compose up -d cr-chatbot

# View logs
docker-compose logs -f cr-chatbot

# Stop services
docker-compose down

Full Stack with Ollama

To run both CR Chatbot and Ollama together:

  1. Edit docker-compose.yml and uncomment the Ollama service:
# Uncomment these lines:
ollama:
  image: ollama/ollama:latest
  # ... rest of configuration
  1. Start both services:
docker-compose up -d
  1. Pull a model (one-time setup):
# Pull a model into Ollama
docker-compose exec ollama ollama pull llama3.2
  1. Access the services:

Manual Docker Commands

Build and Run

# Build the image
docker build -t cr-chatbot .

# Run the container
docker run -d \
  --name cr-chatbot \
  -p 8080:80 \
  --restart unless-stopped \
  cr-chatbot

# View logs
docker logs -f cr-chatbot

# Stop and remove
docker stop cr-chatbot
docker rm cr-chatbot

Custom Port

# Run on port 3000 instead
docker run -d \
  --name cr-chatbot \
  -p 3000:80 \
  cr-chatbot

Production Deployment

Optimized Build

# Build production image
docker build \
  -t cr-chatbot:prod \
  --build-arg NODE_ENV=production \
  .

# Run with production settings
docker run -d \
  --name cr-chatbot-prod \
  --restart unless-stopped \
  -p 80:80 \
  --memory=128m \
  --cpus=0.5 \
  cr-chatbot:prod

Behind Reverse Proxy

For production deployments behind nginx or Apache:

# Run on internal port
docker run -d \
  --name cr-chatbot-internal \
  --restart unless-stopped \
  -p 127.0.0.1:8080:80 \
  cr-chatbot:prod

Environment Variables

You can customize the deployment using environment variables:

docker run -d \
  --name cr-chatbot \
  -p 8080:80 \
  -e NGINX_HOST=localhost \
  -e NGINX_PORT=80 \
  cr-chatbot

Persistent Storage

Save Configurations

# Create volume for persistent config
docker volume create cr-chatbot-config

# Run with volume mount
docker run -d \
  --name cr-chatbot \
  -p 8080:80 \
  -v cr-chatbot-config:/usr/share/nginx/html/config \
  cr-chatbot

Health Checks

The Docker image includes health checks:

# Check container health
docker ps

# View health check logs
docker inspect --format='{{json .State.Health}}' cr-chatbot

Troubleshooting

Container Won't Start

# Check logs
docker logs cr-chatbot

# Inspect configuration
docker inspect cr-chatbot

Port Already In Use

# Find what's using the port
lsof -i :8080

# Use different port
docker run -d -p 8081:80 --name cr-chatbot cr-chatbot

Ollama Connection Issues

# Verify Ollama is running
docker-compose ps

# Check Ollama logs
docker-compose logs ollama

# Test Ollama API
curl http://localhost:11434/api/tags

Updates

Update CR Chatbot

# Pull latest changes
git pull

# Rebuild and restart
docker-compose down
docker-compose build --no-cache
docker-compose up -d

Update Base Images

# Update nginx base image
docker pull nginx:alpine

# Rebuild with latest base
docker build --no-cache -t cr-chatbot .

Resource Usage

  • Memory: ~50MB (nginx + static files)
  • CPU: Minimal (static content serving)
  • Storage: ~10MB (container image)
  • Network: Port 80/8080 for HTTP

Security Considerations

  1. HTTPS: Use reverse proxy for SSL termination
  2. Firewall: Restrict access to necessary ports only
  3. Updates: Keep base images updated regularly
  4. Networks: Use Docker networks for internal communication

Development

Development with Hot Reload

# Mount source code for development
docker run -d \
  --name cr-chatbot-dev \
  -p 8080:80 \
  -v $(pwd)/cr-chatbot:/usr/share/nginx/html/cr-chatbot \
  cr-chatbot

Debug Mode

# Run with debug logging
docker run -d \
  --name cr-chatbot-debug \
  -p 8080:80 \
  -e NGINX_LOG_LEVEL=debug \
  cr-chatbot

Multi-Architecture Support

The Docker image supports multiple architectures:

# Build for ARM64 (Apple Silicon, Raspberry Pi)
docker buildx build \
  --platform linux/arm64 \
  -t cr-chatbot:arm64 .

# Build for AMD64 (Intel/AMD)
docker buildx build \
  --platform linux/amd64 \
  -t cr-chatbot:amd64 .

Integration Examples

With Traefik

version: '3.8'
services:
  cr-chatbot:
    build: .
    labels:
      - "traefik.enable=true"
      - "traefik.http.routers.cr-chatbot.rule=Host(`chatbot.example.com`)"
      - "traefik.http.routers.cr-chatbot.tls.certresolver=letsencrypt"

With Kubernetes

apiVersion: apps/v1
kind: Deployment
metadata:
  name: cr-chatbot
spec:
  replicas: 2
  selector:
    matchLabels:
      app: cr-chatbot
  template:
    metadata:
      labels:
        app: cr-chatbot
    spec:
      containers:
      - name: cr-chatbot
        image: cr-chatbot:latest
        ports:
        - containerPort: 80

Support

For Docker-specific issues:

  1. Check container logs: docker logs cr-chatbot
  2. Verify network connectivity: docker network ls
  3. Test health check: docker exec cr-chatbot curl http://localhost/
  4. Review resource usage: docker stats cr-chatbot

For application issues, see the main README.md and CONTRIBUTING.md.