Your first analysis¶
Explore a small dataset, ask a follow-up question and keep the result in a Python notebook.
You'll need:
- uv, which provides the
uvxcommand. Install it, then reopen your terminal. - Docker, installed and running: Docker Desktop on Windows or macOS, Docker Engine on Linux. Your notebook code runs in a Docker container that sees only your data folder, read-only, with no network.
- An OpenAI API key for the default setup.
- A web browser.
These steps work in PowerShell on Windows and in a terminal on macOS or Linux. uvx downloads Hailer,
its dependencies and a suitable Python version when needed. You do not need to clone this repository.
1. Create a workspace and sign in¶
Run these commands in your terminal:
init creates your settings (hailer.toml), a starter notebook and a data/ folder. At the login prompt,
paste your API key; input is hidden and the key is saved in your operating system's credential store.
The starter settings use OpenAI with gpt-5.5 and the Docker kernel ([kernel] runtime = "docker").
If Docker is not on your machine, init says so and how to get it.
For a company or another model endpoint, follow custom endpoint setup
after init, using that provider's login command, then continue below.
2. Add your data¶
Copy the CSV, Parquet, JSON or Excel files you want to analyse into the data/ folder inside my-analysis.
Any filenames work.
For a small example, download sales.csv into data/, or save the following as data/sales.csv:
3. Start chatting¶
From the same terminal, run:
The first start downloads Hailer's kernel image, which takes a minute or two. Then Hailer opens the notebook in your browser and starts the chat in your terminal. Keep the notebook tab open while you work; it provides the live session that runs the analysis.
You can type or paste your first question while chat preparation continues. Pressing Enter keeps one message waiting and sends it when preparation finishes; you can keep editing your next draft meanwhile.
Ask a question in the terminal, for example:
With the sample CSV, try:
Tables and charts appear in the notebook. Type /exit to finish. To continue later, open a terminal
in my-analysis and run uvx hailer again; it resumes your conversation and active notebook.
Use /new for a fresh conversation, or /help to see the chat commands.
If startup fails, run uvx hailer doctor for checks and suggested fixes, or see
Troubleshooting. Docker is not installed. or
Docker is not running. means exactly that: install or start Docker and run uvx hailer again. doctor
starts no kernel: every uvx hailer session starts its own and stops it when the chat ends.
Data and code: files are read locally, but your messages, code and notebook tool outputs (which can include data samples) go to the configured model endpoint. Notebook code runs in the Docker container, which sees your data folder read-only and has no network. See Security and Isolated kernel (Docker) for details.