Working with the CLI

The Emmi CLI provides a convenient way of performing high-level actions.

Each Python module exposes unique functionality and therefore its own set of commands.

A global --debug flag enables extended debug logging, useful for narrowing down issues, for example:

emmi-data --debug aws estimate ...

In this documentation we will be using CLI for Emmi Data Module.

Credential Setup

To communicate with services, you must configure credentials:

1. Create a file under your profile root, e.g. /users/username/.config/emmi/config.json.

2. Populate the file (replace empty strings with your values; unused services may stay empty):

{
    "huggingface": {
        "HF_TOKEN": ""
    },
    "aws": {
        "AWS_ACCESS_KEY_ID": "",
        "AWS_SECRET_ACCESS_KEY": "",
        "AWS_SESSION_TOKEN": "",
        "AWS_REGION": "",
        "AWS_DEFAULT_REGION": ""
    }
}

Note

For AWS the values AWS_SESSION_TOKEN, AWS_REGION, and AWS_DEFAULT_REGION are optional. In case when AWS_ACCESS_KEY_ID starts with ASIA... the AWS_SESSION_TOKEN needs to be provided.

Testing the Credentials

Verify your setup by running the estimate command, which fetches metadata and reports the estimated size:

Hugging Face:

emmi-data huggingface estimate EmmiAI/AB-UPT

AWS:

emmi-data aws estimate noaa-goes16 ABI-L1b-RadC/2023/001/00/

If you see no errors — congratulations, your setup works!

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