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Getting started

Requirements

Tool Version Notes
Python 3.14+ With tkinter, used for the native folder picker (included in the python.org installers)
Node.js 24+ npm comes with it
OS Windows, macOS or Linux The app needs a desktop session for the folder picker

An AI provider is optional. Everything except the AI assistant and AI insights works without one.

Install and run

1. Backend

cd backend
python -m venv venv
# Windows: venv\Scripts\activate
source venv/bin/activate
pip install -r requirements.txt
python -m app.main

The API listens on http://localhost:8000, with interactive docs at http://localhost:8000/docs.

The backend must be started from the backend/ directory, because it reads config.yaml and stores its state in backend/.data_expert/ relative to the working directory.

2. Frontend

cd frontend
npm install
npm run dev

Open http://127.0.0.1:5173.

Corporate networks: if npm install fails with certificate errors, let Node use the system certificate store: NODE_OPTIONS=--use-system-ca npm install (PowerShell: $env:NODE_OPTIONS="--use-system-ca").

One-command start

start.sh (macOS/Linux) and start.bat (Windows) create the virtual environment, install dependencies and start both servers.

Docker

docker compose up --build

Put datasets in a data/ folder next to docker-compose.yml; it is mounted at /data in the backend container. The native folder picker cannot open inside a container, so Docker is mainly useful for API development. Running natively is recommended.

First steps

  1. Click Choose folder in the sidebar and select a folder that contains data files.
  2. The folder tree lists supported files: Parquet, CSV, TSV, JSON, JSON Lines, JSON.gz, Feather, Avro, ORC and Excel.
  3. Click a file to load it. It appears under Loaded; select it to open it.
  4. Use the tabs in the top bar:
    • Browse: rows, filters, search, editing and the AI assistant
    • Stats: profile, distributions, correlations and AI insights
    • History: versions of the file
    • Export and Combine
  5. The ? button in the top bar (or User guide in the footer) opens the in-app guide.

Optional: connect an AI provider

Click the sparkle button in the top bar. Pick a local server (Ollama, LM Studio, llama.cpp, vLLM, Jan, LocalAI) or a cloud provider (OpenAI, Anthropic, Gemini, OpenRouter and more), enter the model and an API key if needed, and click Test connection. See AI assistant.

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