Environment Variables¶

Fetch ML supports environment variables for configuration, allowing you to override config file settings and deploy in different environments.

Priority Order¶

Environment variables (highest priority)
Configuration file values
Default values (lowest priority)

Variable Prefixes¶

General Configuration¶

FETCH_ML_* - General server and application settings

CLI Configuration¶

FETCH_ML_CLI_* - CLI-specific settings (overrides ~/.ml/config.toml)

TUI Configuration¶

FETCH_ML_TUI_* - TUI-specific settings (overrides TUI config file)

CLI Environment Variables¶

Variable	Config Field	Example
`FETCH_ML_CLI_HOST`	`worker_host`	`localhost`
`FETCH_ML_CLI_USER`	`worker_user`	`mluser`
`FETCH_ML_CLI_BASE`	`worker_base`	`/opt/ml`
`FETCH_ML_CLI_PORT`	`worker_port`	`22`
`FETCH_ML_CLI_API_KEY`	`api_key`	`your-api-key-here`

TUI Environment Variables¶

Variable	Config Field	Example
`FETCH_ML_TUI_HOST`	`host`	`localhost`
`FETCH_ML_TUI_USER`	`user`	`mluser`
`FETCH_ML_TUI_SSH_KEY`	`ssh_key`	`~/.ssh/id_rsa`
`FETCH_ML_TUI_PORT`	`port`	`22`
`FETCH_ML_TUI_BASE_PATH`	`base_path`	`/opt/ml`
`FETCH_ML_TUI_TRAIN_SCRIPT`	`train_script`	`train.py`
`FETCH_ML_TUI_REDIS_ADDR`	`redis_addr`	`localhost:6379`
`FETCH_ML_TUI_REDIS_PASSWORD`	`redis_password`	``
`FETCH_ML_TUI_REDIS_DB`	`redis_db`	`0`
`FETCH_ML_TUI_KNOWN_HOSTS`	`known_hosts`	`~/.ssh/known_hosts`

Server Environment Variables (Auth & Debug)¶

These variables control server-side authentication behavior and are intended only for local development and debugging.

Variable	Purpose	Allowed In Production?
`FETCH_ML_ALLOW_INSECURE_AUTH`	When set to `1` and `FETCH_ML_DEBUG=1`, allows the API server to run with `auth.enabled: false` by injecting a default admin user.	No. Must never be set in production.
`FETCH_ML_DEBUG`	Enables additional debug behaviors. Required (set to `1`) to activate the insecure auth bypass above.	No. Must never be set in production.

When both variables are set to 1 and auth.enabled is false, the server logs a clear warning and treats all requests as coming from a default admin user. This mode is convenient for local homelab experiments but is insecure by design and must not be used on any shared or internet-facing environment.

Usage Examples¶

Development Environment¶

export FETCH_ML_CLI_HOST=localhost
export FETCH_ML_CLI_USER=devuser
export FETCH_ML_CLI_API_KEY=dev-key-123456789012
./ml status

Production Environment¶

export FETCH_ML_CLI_HOST=prod-server.example.com
export FETCH_ML_CLI_USER=mluser
export FETCH_ML_CLI_API_KEY=prod-key-abcdef1234567890
./ml status

Docker/Kubernetes¶

env:
  - name: FETCH_ML_CLI_HOST
    value: "ml-server.internal"
  - name: FETCH_ML_CLI_USER
    value: "mluser"
  - name: FETCH_ML_CLI_API_KEY
    valueFrom:
      secretKeyRef:
        name: ml-secrets
        key: api-key

Using .env file¶

# Copy the example file
cp .env.example .env

# Edit with your values
vim .env

# Load in your shell
export $(cat .env | xargs)

Backward Compatibility¶

The CLI also supports the legacy ML_* prefix for backward compatibility, but FETCH_ML_CLI_* takes priority if both are set.

Legacy Variable	New Variable
`ML_HOST`	`FETCH_ML_CLI_HOST`
`ML_USER`	`FETCH_ML_CLI_USER`
`ML_BASE`	`FETCH_ML_CLI_BASE`
`ML_PORT`	`FETCH_ML_CLI_PORT`
`ML_API_KEY`	`FETCH_ML_CLI_API_KEY`