Unity AI - Reporting AI

A comprehensive AI-powered reporting system that integrates with Metabase to provide intelligent query generation and data insights.

Features

• AI-powered SQL query generation from natural language
• Integration with Metabase for data visualization
• Real-time chat interface for data queries
• Multi-tenant schema support
• PostgreSQL with pgvector for embeddings storage

Quick Start

Prerequisites

• Docker and Docker Compose
• Git

Development Setup

1. Clone the repository:

git clone <repository-url>
cd unity-ai/applications

2. Set required environment variables:

export OPENAI_API_KEY="your_openai_api_key"
export JWT_SECRET="your_jwt_secret_key"
export METABASE_URL="your_metabase_url"
export METABASE_USERNAME="your_metabase_username"
export METABASE_PASSWORD="your_metabase_password"

Or alternatively, copy the environment template:

cp .env.example .env
# Configure environment variables in .env

3. Start development environment:

docker-compose -f docker-compose.dev.yml up --build

Production Deployment

1. Set required environment variables:

export OPENAI_API_KEY="your_openai_api_key"
export JWT_SECRET="your_jwt_secret_key"
export METABASE_URL="your_metabase_url"
export METABASE_USERNAME="your_metabase_username"
export METABASE_PASSWORD="your_metabase_password"

2. Deploy:

docker-compose up --build -d

Architecture

• Backend: Python Flask API with OpenAI integration
• Frontend: Angular application with modern UI
• Database: PostgreSQL with pgvector extension
• Development Tools: pgAdmin for database management

Services

• Frontend: http://localhost:80
• Backend API: http://localhost:5000
• Database: localhost:5432
• pgAdmin (dev only): http://localhost:8080

Project Structure

applications/
├── src/
│   ├── Unity.AI.Reporting.Backend/     # Python Flask backend
│   └── Unity.AI.Reporting.Frontend/    # Angular frontend
├── docker-compose.yml                   # Production compose
└── docker-compose.dev.yml              # Development compose

See individual component READMEs for detailed documentation:

• Backend Documentation
• Frontend Documentation