ZdenekSrotyr 22cfbfe5fb docs: update references to deleted files

- QUICKSTART.md: replace data_description.md.example copy step with
  note that tables are registered via the admin API or web UI
- NOTIFICATIONS.md: replace examples/ section with planned-feature note
- telegram_bot.md: remove examples/notifications/ rows from deployment
  table and example scripts section; note feature is planned
- dev_docs/README.md: remove plan-corporate-memory.md entry
- duckdb_manager.py: update comment from remote_query.py to query API endpoint

2026-04-09 17:15:19 +02:00

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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

Clone the repository:

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

Run the initialization script:
```
bash scripts/init.sh
```

Configure your instance:

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

Set up environment variables:

# Edit .env with your data source credentials

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

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

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

Analysis Workflow

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

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