agnes-the-ai-analyst/docs/QUICKSTART.md

Quick Start Guide

Prerequisites

• Python 3.10+
• SSH access to a Linux server (for production deployment)
• Data source credentials (Keboola token, BigQuery service account, etc.)

Local Development Setup

1. Clone the repository:

   git clone <repo-url>
   cd ai-data-analyst
   

2. Run the initialization script:

   bash scripts/init.sh
   

3. Configure your instance:

   cp config/instance.yaml.example config/instance.yaml
   # Edit config/instance.yaml with your settings
   

4. Set up environment variables:

   # Edit .env with your data source credentials
   

5. Register your tables:

   # Tables are registered via the admin API or web UI — no config file needed
   

6. Sync data:

   source .venv/bin/activate
   python -m src.data_sync
   

Server Deployment

See DEPLOYMENT.md for full server setup instructions.

Using with Claude Code

Open the project in Claude Code. The CLAUDE.md file will guide the AI assistant through setup and analysis workflows.

Analyst Setup

1. Visit your instance URL (e.g., https://data.yourcompany.com)
2. Sign in with your company email
3. Register your SSH key
4. Follow the setup instructions to sync data locally

Analysis Workflow

1. Sync latest data: bash server/scripts/sync_data.sh
2. Open Claude Code in your project directory
3. Ask Claude to analyze your data using DuckDB

Hackathon

Point the shared agnes-dev VM at your branch image with scripts/switch-dev-vm.sh <branch-slug>. See HACKATHON.md for the full deploy-and-develop playbook.