Control Panel Local Setup

This guide walks you through setting up Cuemeet locally for development and testing purposes.

Prerequisites

Before you begin, make sure you have the following installed:

Git
Docker and Docker Compose
Node.js (v14 or later) - Optional for local development without Docker
Python 3.10 or higher - Optional for local development without Docker

Installation Steps

Clone the repository

git clone https://github.com/CueMeet/Meeting-Bots-Control-Panel.git
cd Meeting-Bots-Control-Panel

Project Folder Structure

Click to expand folder structure

.
├── CODE_OF_CONDUCT.md
├── CONTRIBUTING.md
├── LICENSE
├── README.md
├── api-backend
│   ├── Dockerfile
│   ├── Makefile
│   ├── README.md
│   ├── nest-cli.json
│   ├── package.json
│   ├── src
│   ├── test
│   ├── tsconfig.build.json
│   ├── tsconfig.json
│   └── yarn.lock
├── assets
│   ├── banner.png
│   └── cuemeet-logo.png
├── docker-compose.yml
├── pg-db
│   └── init-multiple-databases.sql
├── protos
│   └── worker_backend.transcript_management
└── worker-backend
    ├── Dockerfile
    ├── Makefile
    ├── README.md
    ├── api
    ├── manage.py
    ├── nltk
    ├── poetry.lock
    ├── pyproject.toml
    └── worker_backend

Configure Environment Variables

Click to view/copy Backend API .env configuration

# Backend API Configuration
# Application
PORT=4000
NODE_ENV=development
CORS_ALLOWED_ORIGINS=*

# Database
DB_HOST=pg-db
DB_PORT=5432
DB_USERNAME=meetingbots_user
DB_PASSWORD=cuecard-meting-bots-secret
DB_DATABASE=meetingbots_db_backend_api


# Redis
REDIS_HOST=redis
REDIS_PORT=6379


# AWS (Must be filled in from AWS setup steps)
AWS_ACCESS_KEY=  # Your AWS Access Key from AWS setup
AWS_SECRET_KEY=  # Your AWS Secret Key from AWS setup

## S3
AWS_BUCKET_REGION=  # Your S3 bucket region
AWS_MEETING_BOT_BUCKET_NAME=  # Your S3 bucket name

## ECS (Must match the AWS configurations)
AWS_ECS_CLUSTER_NAME=  # Your AWS ECS Cluster Name
AWS_SECURITY_GROUP=  # Your AWS Security Group ID
AWS_VPS_SUBNET=  # Your AWS Subnet ID
ECS_TASK_DEFINITION_GOOGLE=  # Task Definition for Google Meet bots
ECS_CONTAINER_NAME_GOOGLE=  # Container Name for Google Meet bots
ECS_TASK_DEFINITION_ZOOM=  # Task Definition for Zoom bots
ECS_CONTAINER_NAME_ZOOM=  # Container Name for Zoom bots
ECS_TASK_DEFINITION_TEAMS=  # Task Definition for Microsoft Teams bots
ECS_CONTAINER_NAME_TEAMS=  # Container Name for Microsoft Teams bots


# Meeting Bot
MEETING_BOT_RETRY_COUNT=2


# Worker Backend gRPC URL
WORKER_BACKEND_GRPC_URL=worker-grpc:5500

⚠️ Important: The AWS-related environment variables must be obtained from the AWS Setup Guide. Complete the AWS setup first and copy the relevant values into this file.

Click to view/copy Worker API .env configuration

# Worker API Configuration
DJANGO_SETTINGS_MODULE=worker_backend.settings
DJANGO_SECRET_KEY=8b1336ae5f72ec7e949e787054976962a85fb1ca935da5ca59ba0448eae178b1336ae5f7204
DEBUG=True
STATIC_URL=/static/
ALLOWED_HOSTS=*
CORS_ALLOWED_ORIGINS=*


## PG Database
DB_USERNAME=meetingbots_user
DB_PASSWORD=cuecard-meting-bots-secret
DB_NAME=meetingbots_db_worker
DB_HOST=pg-db
DB_PORT=5432


# Redis Configuration
REDIS_HOST=redis
REDIS_PORT=6379
REDIS_DB=2


# AWS Configuration
AWS_ACCESS_KEY_ID= # Your AWS Access Key from AWS setup
AWS_SECRET_ACCESS_KEY= # Your AWS Access Key from AWS setup

## AWS S3
AWS_REGION= # Your S3 bucket region
AWS_STORAGE_BUCKET_NAME= # Your S3 bucket name

_SIGNED_URL_EXPIRY_TIME=60

## HIGHLIGHT
HIGHLIGHT_PROJECT_ID=""
HIGHLIGHT_ENVIRONMENT_NAME=""


## ASSEMBLY AI
ASSEMBLY_AI_API_KEY="" # https://www.assemblyai.com API KEY 

Docker Compose Configuration

docker-compose.yml

services:
  backend-api:
    container_name: backend_rest
    build:
      context: ./api-backend
      dockerfile: Dockerfile
    ports:
      - "4000:4000"
    depends_on:
      - pg-db
      - redis

  worker-api:
    container_name: worker_rest
    build:
      context: ./worker-backend
      dockerfile: Dockerfile
    command: python manage.py migrate && gunicorn worker_backend.wsgi:application --workers 4 --bind 0.0.0.0:8000
    ports:
      - "8000:8000"
    depends_on:
      - pg-db
      - redis
      - backend-api

  worker-grpc:
    container_name: grpc-server
    restart: always
    image: cuemeet:worker-backend
    command: bash -c "echo 'Starting gRPC server...' && python manage.py grpcrunaioserver 0.0.0.0:5500 --max-workers 2 --verbosity 3"
    # ports: ## Uncomment this if you want to expose grpc port
    #   - "5500:5500"
    depends_on:
      - pg-db
      - redis
      - backend-api
      - worker-api

  redis:
    image: redis:alpine
    container_name: redis
    restart: always
    # ports: ## Uncomment this if you want to expose redis port
    #   - "6379:6379"

  pg-db:
    image: postgres:16
    container_name: postgres_db
    restart: always
    volumes:
      - postgres_data:/var/lib/postgresql/data
      - ./pg-db/init-multiple-databases.sql:/docker-entrypoint-initdb.d/init-multiple-databases.sql
    # ports: ## Uncomment this if you want to expose postgres port
    #   - "5432:5432"
    env_file:
      - ./pg-db/.db.env

  celery_worker:
    container_name: celery_worker
    build:
      context: ./worker-backend
      dockerfile: Dockerfile
    command: celery -A worker_backend worker --loglevel=info --concurrency=4
    depends_on:
      - redis
      - pg-db
      - worker-api

  flower:
    container_name: flower
    build:
      context: ./worker-backend
      dockerfile: Dockerfile
    command: celery -A worker_backend flower --port=5555
    ports:
      - "5556:5555"
    depends_on:
      - redis
      - worker-grpc

  documentation:
    container_name: documentation
    build:
      context: ./documentation
      dockerfile: Dockerfile
    ports:
      - "6000:3000"

volumes:
  postgres_data:
    driver: local

Start the Services

# Build and start all services
docker compose up -d

# Check service status
docker compose ps

# Stop the service
docker compose down

The services will be available at:

Backend API: http://localhost:4000
Worker API: http://localhost:8000
Worker gRPC: worker-grpc:5500 (internal only — accessible via Docker Compose network)
PostgreSQL: pg-db:5432 (internal only — accessible via Docker Compose network)
Redis: redis:6379 (internal only — accessible via Docker Compose network)

Database Migrations

For the Backend API(Nest.js)

Automatic Migrations are configured

For the Worker API (Django):

# Run migrations
python manage.py migrate

Troubleshooting

Common Issues

Container Startup Issues

Ensure all required ports (4000, 8000) are available
Check if Docker daemon is running
Verify environment variables are set correctly

Database Connection Issues

Ensure PostgreSQL container is running: docker-compose ps
Check logs: docker-compose logs pg-db
Verify database credentials in both .env files

Service Dependencies

Backend API must be running for Worker API to function properly

Check service logs:

docker-compose logs backend-api
docker-compose logs worker-api

Next Steps

Once you have your local setup working:

Proceed to AWS Setup for production deployment
Explore the API Documentation
Configure your Bot Settings

Prerequisites​

Installation Steps​

Project Folder Structure​

Database Migrations​

Troubleshooting​

Common Issues​

Container Startup Issues​

Database Connection Issues​

Service Dependencies​

Next Steps​