AI Slack Bot Builder

A modular web application for building and managing AI-powered Slack bots with workflow automation capabilities.

Features

• Workflows: Create and manage automated workflows with code generation
• Slack Bot: Manage bot installation across Slack channels
• Integrations: Connect with Kubernetes, Jira, and Grafana
• Git Repository: Version control and file management
• PostgreSQL Database: Persistent storage for all application data

Quick Start with Docker

Prerequisites

• Docker
• Docker Compose

Running the Application

1. Clone the repository

   git clone <repository-url>
   cd slack-bot-builder

2. Build and start all services

   docker-compose up --build

3. Access the application

   • Frontend: http://localhost
   • Backend API: http://localhost:5000
   • Database: localhost:5432

Database Credentials

• Database: slack_bot_db
• Username: slack_bot_user
• Password: slack_bot_password
• Host: postgres (internal) or localhost (external)
• Port: 5432

Development

Backend Development

The backend is a Flask application with PostgreSQL database support.

Key Files:

• backend/app.py - Main Flask application
• backend/db_utils.py - Database utilities and managers
• backend/init.sql - Database schema and initial data

Database Managers:

• WorkflowManager - Manage workflows
• SlackChannelManager - Manage Slack channels
• IntegrationManager - Manage integrations
• WorkspaceManager - Manage workspace information

Frontend Development

The frontend is a React TypeScript application with modular page structure.

Key Files:

• frontend/src/App.tsx - Main application with navigation
• frontend/src/pages/ - Page components
  • WorkflowsPage.tsx - Workflow management
  • SlackBotPage.tsx - Slack bot management
  • IntegrationsPage.tsx - Integration management
  • GitRepoPage.tsx - Git repository management

Docker Services

PostgreSQL Database

• Image: postgres:15-alpine
• Port: 5432
• Volume: postgres_data (persistent)
• Initialization: backend/init.sql

Backend API

• Base Image: python:3.11-slim
• Port: 5000
• Dependencies: Flask, psycopg2-binary, python-dotenv
• Environment: Connected to PostgreSQL database

Frontend

• Build Stage: node:18-alpine
• Production Stage: nginx:alpine
• Port: 80
• Features: React SPA with API proxy to backend

Database Schema

Tables

1. workflows - Store workflow configurations and generated code
2. integrations - Store integration settings and connection status
3. slack_channels - Store Slack channel information and bot installation status
4. workspace - Store workspace information

Sample Data

The database is initialized with sample data including:

• Sample workflows
• Integration configurations (Kubernetes, Jira, Grafana)
• Sample Slack channels with bot installation status
• Workspace information

API Endpoints

Workflows

• GET /api/workflows - Get all workflows
• POST /api/workflows - Create new workflow
• PUT /api/workflows/:id - Update workflow
• DELETE /api/workflows/:id - Delete workflow

Slack Channels

• GET /api/slack/channels - Get all channels
• PUT /api/slack/channels/:id/install - Install/remove bot

Integrations

• GET /api/integrations - Get all integrations
• PUT /api/integrations/:id/connect - Connect/disconnect integration

Environment Variables

Backend

• DATABASE_URL - PostgreSQL connection string
• FLASK_ENV - Flask environment (development/production)
• FLASK_APP - Flask application entry point

Database

• POSTGRES_DB - Database name
• POSTGRES_USER - Database username
• POSTGRES_PASSWORD - Database password

Commands

Development

# Start all services
docker-compose up

# Start in background
docker-compose up -d

# View logs
docker-compose logs -f

# Stop all services
docker-compose down

# Rebuild and start
docker-compose up --build

# Access database
docker-compose exec postgres psql -U slack_bot_user -d slack_bot_db

Production

# Build production images
docker-compose -f docker-compose.yml build

# Start production services
docker-compose -f docker-compose.yml up -d

Troubleshooting

Database Connection Issues

1. Check if PostgreSQL container is running: docker-compose ps
2. Check database logs: docker-compose logs postgres
3. Verify environment variables in docker-compose.yml

Frontend Build Issues

1. Clear node_modules: docker-compose exec frontend rm -rf node_modules
2. Rebuild frontend: docker-compose build frontend

Backend Issues

1. Check Python dependencies: docker-compose exec backend pip list
2. Check application logs: docker-compose logs backend

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Test with Docker setup
5. Submit a pull request

License

This project is licensed under the MIT License.