What is FlowiseAI?
FlowiseAI is an open-source generative AI development platform for building AI agents and LLM workflows. Here are its key features:
Core Capabilities:
- Visual drag-and-drop interface for creating AI workflows without coding
- Built on LangChain framework with Node.js and React
- Low-code/no-code workflow automation specifically for LLM applications
- Supports conversational agents, templates, and cloud deployment
Key Features:
- Ready-to-use app templates
- Conversational agents with memory capabilities
- Seamless deployment on cloud platforms
- API integration capabilities
- Cross-platform compatibility
- Comprehensive monitoring and reporting
- Visual workflow builder for connecting large language models and tools
FlowiseAI Docker Compose Installation Guide
Prerequisites
Before starting the installation, ensure you have:
- Docker and Docker Compose installed on your system
- A VPS or server where you can host FlowiseAI
- Basic knowledge of Docker and command line operations
- (Optional) Reverse proxy setup for SSL and domain access
Step 1: Create Docker Compose File
Create a new directory for your FlowiseAI installation and create a docker-compose.yml file:
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version: "3.9" services: flowise-db: image: postgres:16-alpine hostname: flowise-db environment: POSTGRES_DB: ${POSTGRES_DB} POSTGRES_USER: ${POSTGRES_USER} POSTGRES_PASSWORD: ${POSTGRES_PASSWORD} volumes: - ./flowise-db-data:/var/lib/postgresql/data restart: unless-stopped healthcheck: test: ["CMD-SHELL", "pg_isready -U ${POSTGRES_USER} -d ${POSTGRES_DB}"] interval: 5s timeout: 5s retries: 5 flowise: image: flowiseai/flowise:latest container_name: flowiseai hostname: flowise healthcheck: test: wget --no-verbose --tries=1 --spider http://localhost:${PORT} ports: - 5023:${PORT} volumes: - ./flowiseai:/root/.flowise environment: DEBUG: false PORT: ${PORT} FLOWISE_USERNAME: ${FLOWISE_USERNAME} FLOWISE_PASSWORD: ${FLOWISE_PASSWORD} APIKEY_PATH: /root/.flowise SECRETKEY_PATH: /root/.flowise LOG_LEVEL: info LOG_PATH: /root/.flowise/logs DATABASE_TYPE: postgres DATABASE_PORT: 5432 DATABASE_HOST: flowise-db DATABASE_NAME: ${POSTGRES_DB} DATABASE_USER: ${POSTGRES_USER} DATABASE_PASSWORD: ${POSTGRES_PASSWORD} restart: on-failure:5 depends_on: flowise-db: condition: service_healthy entrypoint: /bin/sh -c "sleep 3; flowise start" # Optional: Database Backup Service flowise-db-backup: container_name: flowise-db-backup image: tiredofit/db-backup volumes: - ./backups:/backup environment: DB_TYPE: postgres DB_HOST: flowise-db DB_NAME: ${POSTGRES_DB} DB_USER: ${POSTGRES_USER} DB_PASS: ${POSTGRES_PASSWORD} DB_BACKUP_INTERVAL: 720 DB_CLEANUP_TIME: 72000 CHECKSUM: SHA1 COMPRESSION: GZ CONTAINER_ENABLE_MONITORING: false depends_on: flowise-db: condition: service_healthy restart: unless-stopped |
Step 2: Create Environment File
Create a .env file in the same directory with your configuration:
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# Application Configuration PORT=3000 FLOWISE_USERNAME=admin FLOWISE_PASSWORD=your_secure_password # Database Configuration POSTGRES_USER=flowiseuser POSTGRES_PASSWORD=your_db_password POSTGRES_DB=flowise |
Important Security Notes:
- Replace
your_secure_passwordandyour_db_passwordwith strong, unique passwords - Consider using environment-specific passwords for production deployments
Step 3: Deploy FlowiseAI
Navigate to your project directory and run:
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# Create necessary directories mkdir -p flowise-db-data flowiseai backups # Start the services docker-compose up -d |
Step 4: Verify Installation
Check if all containers are running:
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docker ps |
You should see three containers running:
flowiseai(main application)flowise-db(PostgreSQL database)flowise-db-backup(optional backup service)
Check the logs to ensure everything started correctly:
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# Check FlowiseAI logs docker-compose logs flowise # Check database logs docker-compose logs flowise-db |
Step 5: Access FlowiseAI
Once deployed, you can access FlowiseAI at:
- Local access:
http://localhost:5023 - Login credentials: Use the username and password from your
.envfile
Directory Structure
After installation, your directory structure should look like:
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flowiseai/ ├── docker-compose.yml ├── .env ├── flowise-db-data/ # PostgreSQL data ├── flowiseai/ # FlowiseAI application data │ ├── logs/ │ └── ... └── backups/ # Database backups (if enabled) └── ... |
Next Steps
- Create Your First Flow: Access the web interface and start building AI workflows
- Explore Templates: Check the marketplace for pre-built flow templates
- API Integration: Use the REST API for external integrations
- Security: Review and strengthen authentication settings for production use
